Autosuficientes para operar como han operado, lejos del ideal de universidad que ha expresado previamente el autor, lo que me parece ha reducido significativamente la confianza en ellas de la sociedad.

Se puede esperar entonces que comunidades que han tenido problemas serios de crecimiento tengan universidades con problemas serios en su operación.

Continuación de la contemplación con el corazón

https://www.reddit.com/r/typewriters/comments/1ou3svd/just_toured_the_museum_of_printing_in_haverhill/

Museum of Printing in Haverhill, MA has a section of typewriters.

Reviewer #1 (Public review):

Summary:

Noell et al have presented a careful study of the dissociation kinetics of Kinesin (1,2,3) classes of motors moving in vitro on a microtubule. These motors move against the opposing force from a ~1 micron DNA strand (DNA tensiometer) that is tethered to the microtubule and also bound to the motor via specific linkages (Figure 1A). The authors compare the time for which motors remain attached to the microtubule when they are tethered to the DNA, versus when they are not. If the former is longer, the interpretation is that the force on the motor from the stretched DNA (presumed to be working solely along the length of the microtubule) causes the motor's detachment rate from the microtubule to be reduced. Thus, the specific motor exhibits "catch-bond" like behaviour.

Strengths:

The motivation is good - to understand how kinesin competes against dynein through the possible activation of a catch bond. Experiments are well done, and there is an effort to model the results theoretically.

Weaknesses:

The motivation of these studies is to understand how kinesin (1/2/3) motors would behave when they are pitted in a tug of war against dynein motors as they transport cargo in a bidirectional manner on microtubules. Earlier work on dynein and kinesin motors using optical tweezers has suggested that dynein shows a catch bond phenomenon, whereas such signatures were not seen for kinesin. Based on their data with the DNA tensiometer, the authors would like to claim that (i) Kinesin1 and Kinesin2 also show catch-bonding and (ii) the earlier results using optical traps suffer from vertical forces, which complicates the catch-bond interpretation.

While the motivation of this work is reasonable, and the experiments are careful, I find significant issues that the authors have not addressed:

(1) Figure 1B shows the PREDICTED force-extension curve for DNA based on a worm-like chain model. Where is the experimental evidence for this curve? This issue is crucial because the F-E curve will decide how and when a catch-bond is induced (if at all it is) as the motor moves against the tensiometer. Unless this is actually measured by some other means, I find it hard to accept all the results based on Figure 1B.

(2) The authors can correct me on this, but I believe that all the catch-bond studies using optical traps have exerted a load force that exceeds the actual force generated by the motor. For example, see Figure 2 in reference 42 (Kunwar et al). It is in this regime (load force > force from motor) that the dissociation rate is reduced (catch-bond is activated). Such a regime is never reached in the DNA tensiometer study because of the very construction of the experiment. I am very surprised that this point is overlooked in this manuscript. I am therefore not even sure that the present experiments even induce a catch-bond (in the sense reported for earlier papers).

(3) I appreciate the concerns about the Vertical force from the optical trap. But that leads to the following questions that have not at all been addressed in this paper:

(i) Why is the Vertical force only a problem for Kinesins, and not a problem for the dynein studies?

(ii) The authors state that "With this geometry, a kinesin motor pulls against the elastic force of a stretched DNA solely in a direction parallel to the microtubule". Is this really true? What matters is not just how the kinesin pulls the DNA, but also how the DNA pulls on the kinesin. In Figure 1A, what is the guarantee that the DNA is oriented only in the plane of the paper? In fact, the DNA could even be bending transiently in a manner that it pulls the kinesin motor UPWARDS (Vertical force). How are the authors sure that the reaction force between DNA and kinesin is oriented SOLELY along the microtubule?

(4) For this study to be really impactful and for some of the above concerns to be addressed, the data should also have included DNA tensiometer experiments with Dynein. I wonder why this was not done?

While I do like several aspects of the paper, I do not believe that the conclusions are supported by the data presented in this paper for the reasons stated above.

Author response:

Reviewer 1 (Public review):

(1) Figure 1B shows the PREDICTED force-extension curve for DNA based on a worm-like chain model. Where is the experimental evidence for this curve? This issue is crucial because the F-E curve will decide how and when a catch-bond is induced (if at all it is) as the motor moves against the tensiometer. Unless this is actually measured by some other means, I find it hard to accept all the results based on Figure 1B.

The Worm-Like-Chain model for the elasticity of DNA was established by early work from the Bustamante lab (Smith et al., 1992)  and Marko and Siggia (Marko and Siggia, 1995), and was further validated and refined by the Block lab (Bouchiat et al., 1999; Wang et al., 1997). The 50 nm persistence length is the consensus value, and was shown to be independent of force and extension in Figure 3 of Bouchiat et al (Bouchiat et al., 1999). However, we would like to stress that for our conclusions, the precise details of the Force-Extension relationship of our dsDNA are immaterial. The key point is that the motor stretches the DNA and stalls when it reaches its stall force. Our claim of the catch-bond character of kinesin is based on the longer duration at stall compared to the run duration in the absence of load. Provided that the motor is indeed stalling because it has stretched out the DNA (which is strongly supported by the repeated stalling around the predicted extension corresponding to ~6 pN of force), then the stall duration depends on neither the precise value for the extension nor the precise value of the force at stall.

(2) The authors can correct me on this, but I believe that all the catch-bond studies using optical traps have exerted a load force that exceeds the actual force generated by the motor. For example, see Figure 2 in reference 42 (Kunwar et al). It is in this regime (load force > force from motor) that the dissociation rate is reduced (catch-bond is activated). Such a regime is never reached in the DNA tensiometer study because of the very construction of the experiment. I am very surprised that this point is overlooked in this manuscript. I am therefore not even sure that the present experiments even induce a catch-bond (in the sense reported for earlier papers).

It is true that Kunwar et al measured binding durations at super-stall loads and used that to conclude that dynein does act as a catch-bond (but kinesin does not) (Kunwar et al., 2011). However, we would like to correct the reviewer on this one. This approach of exerting super-stall forces and measuring binding durations is in fact less common than the approach of allowing the motor to walk up to stall and measuring the binding duration. This ‘fixed trap’ approach has been used to show catch-bond behavior of dynein (Leidel et al., 2012; Rai et al., 2013) and kinesin (Kuo et al., 2022; Pyrpassopoulos et al., 2020). For the non-processive motor Myosin I, a dynamic force clamp was used to keep the actin filament in place while the myosin generated a single step (Laakso et al., 2008). Because the motor generates the force, these are not superstall forces either.

(3) I appreciate the concerns about the Vertical force from the optical trap. But that leads to the following questions that have not at all been addressed in this paper:

(i) Why is the Vertical force only a problem for Kinesins, and not a problem for the dynein studies?

Actually, we do not claim that vertical force is not a problem for dynein; our data do not speak to this question. There is debate in the literature as to whether dynein has catch bond behavior in the traditional single-bead optical trap geometry - while some studies have measured dynein catch bond behavior (Kunwar et al., 2011; Leidel et al., 2012; Rai et al., 2013), others have found that dynein has slip-bond or ideal-bond behavior (Ezber et al., 2020; Nicholas et al., 2015; Rao et al., 2019). This discrepancy may relate to vertical forces, but not in an obvious way.

(ii) The authors state that "With this geometry, a kinesin motor pulls against the elastic force of a stretched DNA solely in a direction parallel to the microtubule". Is this really true? What matters is not just how the kinesin pulls the DNA, but also how the DNA pulls on the kinesin. In Figure 1A, what is the guarantee that the DNA is oriented only in the plane of the paper? In fact, the DNA could even be bending transiently in a manner that it pulls the kinesin motor UPWARDS (Vertical force). How are the authors sure that the reaction force between DNA and kinesin is oriented SOLELY along the microtubule?

We acknowledge that “solely” is an absolute term that is too strong to describe our geometry. We will soften this term in our revision to “nearly parallel to the microtubule”. In the Geometry Calculations section of Supplementary Methods, we calculate that if the motor and streptavidin are on the same protofilament, the vertical force will be <1% of the horizontal force. We also note that if the motor is on a different protofilament, there will be lateral forces and forces perpendicular to the microtubule surface, except they are oriented toward rather than away from the microtubule. The DNA can surely bend due to thermal forces, but because inertia plays a negligible role at the nanoscale (Howard, 2001; Purcell, 1977), any resulting upward forces will only be thermal forces, which the motor is already subjected to at all times.

(4) For this study to be really impactful and for some of the above concerns to be addressed, the data should also have included DNA tensiometer experiments with Dynein. I wonder why this was not done?

As much as we would love to fully characterize dynein here, this paper is about kinesin and it took a substantial effort. The dynein work merits a stand-alone paper.

While I do like several aspects of the paper, I do not believe that the conclusions are supported by the data presented in this paper for the reasons stated above.

The three key points the reviewer makes are the validity of the worm-like-chain model, the question of superstall loads, and the role of DNA bending in generating vertical forces. We hope that we have fully addressed these concerns in our responses above.

Reviewer #2 (Public review):

Major comments:

(1) The use of the term "catch bond" is misleading, as the authors do not really mean consistently a catch bond in the classical sense (i.e., a protein-protein interaction having a dissociation rate that decreases with load). Instead, what they mean is that after motor detachment (i.e., after a motor protein dissociating from a tubulin protein), there is a slip state during which the reattachment rate is higher as compared to a motor diffusing in solution. While this may indeed influence the dynamics of bidirectional cargo transport (e.g., during tug-of-war events), the used terms (detachment (with or without slip?), dissociation, rescue, ...) need to be better defined and the results discussed in the context of these definitions. It is very unsatisfactory at the moment, for example, that kinesin-3 is at first not classified as a catch bond, but later on (after tweaking the definitions) it is. In essence, the typical slip/catch bond nomenclature used for protein-protein interaction is not readily applicable for motors with slippage.

We appreciate the reviewer’s point and we will work to streamline and define terms in our revision.

(2) The authors define the stall duration as the time at full load, terminated by >60 nm slips/detachments. Isn't that a problem? Smaller slips are not detected/considered... but are also indicative of a motor dissociation event, i.e., the end of a stall. What is the distribution of the slip distances? If the slip distances follow an exponential decay, a large number of short slips are expected, and the presented data (neglecting those short slips) would be highly distorted.

The reviewer brings up a good point that there may be undetected slips. To address this question, we plotted the distribution of slip distances for kinesin-3, which by far had the most slip events. As the reviewer suggested, it is indeed an exponential distribution. Our preliminary analysis suggests that roughly 20% of events are missed due to this 60 nm cutoff. This will change our unloaded duration numbers slightly, but this will not alter our conclusions.\

(3) Along the same line: Why do the authors compare the stall duration (without including the time it took the motor to reach stall) to the unloaded single motor run durations? Shouldn't the times of the runs be included?

The elastic force of the DNA spring is variable as the motor steps up to stall, and so if we included the entire run duration then it would be difficult to specify what force we were comparing to unloaded. More importantly, if we assume that any stepping and detachment behavior is history independent, then it is mathematically proper to take any arbitrary starting point (such as when the motor reaches stall), start the clock there, and measure the distribution of detachments durations relative to that starting point.

More importantly, what we do in Fig. 3 is to separate out the ramps from the stalls and, using a statistical model, we compute a separate duration parameter (which is the inverse of the off-rate) for the ramp and the stall. What we find is that the relationship between ramp, stall, and unloaded durations is different for the three motors, which is interesting in itself.

(4) At many places, it appears too simple that for the biologically relevant processes, mainly/only the load-dependent off-rates of the motors matter. The stall forces and the kind of motor-cargo linkage (e.g., rigid vs. diffusive) do likely also matter. For example: "In the context of pulling a large cargo through the viscous cytoplasm or competing against dynein in a tug-of-war, these slip events enable the motor to maintain force generation and, hence, are distinct from true detachment events." I disagree. The kinesin force at reattachment (after slippage) is much smaller than at stall. What helps, however, is that due to the geometry of being held close to the microtubule (either by the DNA in the present case or by the cargo in vivo) the attachment rate is much higher. Note also that upon DNA relaxation, the motor is likely kept close to the microtubule surface, while, for example, when bound to a vesicle, the motor may diffuse away from the microtubule quickly (e.g., reference 20).

We appreciate the reviewer’s detailed thinking here, and we offer our perspective. As to the first point, we agree that the stall force is relevant and that the rigidity of the motor-cargo linkage will play a role. The goal of the sentence on pulling cargo that the reviewer highlights is to set up our analysis of slips, which we define as rearward displacements that don’t return to the baseline before force generation resumes. We agree that force after slippage is much smaller than at stall, and we plan to clarify that section of text. However, as shown in the model diagram in Fig. 5, we differentiate between the slip state (and recovery from this slip state) and the detached state (and reattachment from this detached state). This delineation is important because, as the reviewer points out, if we are measuring detachment and reattachment with our DNA tensiometer, then the geometry of a vesicle in a cell will be different and diffusion away from the microtubule or elastic recoil perpendicular to the microtubule will suppress this reattachment.

Our evidence for a slip state in which the motor maintains association with the microtubule comes from optical trapping work by Tokelis et al (Toleikis et al., 2020) and Sudhakar et al (Sudhakar et al., 2021). In particular, Sudhakar used small, high index Germanium microspheres that had a low drag coefficient. They showed that during ‘slip’ events, the relaxation time constant of the bead back to the center of the trap was nearly 10-fold slower than the trap response time, consistent with the motor exerting drag on the microtubule. (With larger beads, the drag of the bead swamps the motor-microtubule friction.) Another piece of support for the motor maintaining association during a slip is work by Ramaiya et al. who used birefringent microspheres to exert and measure rotational torque during kinesin stepping (Ramaiya et al., 2017). In most traces, when the motor returned to baseline following a stall, the torque was dissipated as well, consistent with a ‘detached’ state. However, a slip event is shown in S18a where the motor slips backward while maintaining torque. This is best explained by the motor slipping backward in a state where the heads are associated with the microtubule (at least sufficiently to resist rotational forces). Thus, we term the resumption after slip to be a rescue from the slip state rather than a reattachment from the detached state.

To finish the point, with the complex geometry of a vesicle, during slip events the motor remains associated with the microtubule and hence primed for recovery. This recovery rate is expected to be the same as for the DNA tensiometer. Following a detachment, however, we agree that there will likely be a higher probability of reattachment in the DNA tensiometer due to proximity effects, whereas with a vesicle any elastic recoil or ‘rolling’ will pull the detached motor away from the microtubule, suppressing reattachment. We plan to clarify these points in the text of the revision.

(5) Why were all motors linked to the neck-coil domain of kinesin-1? Couldn't it be that for normal function, the different coils matter? Autoinhibition can also be circumvented by consistently shortening the constructs.

We chose this dimerization approach to focus on how the mechoanochemical properties of kinesins vary between the three dominant transport families. We agree that in cells, autoinhibition of both kinesins and dynein likely play roles in regulating bidirectional transport, as will the activity of other regulatory proteins. The native coiled-coils may act as as ‘shock absorbers’ due to their compliance, or they might slow the motor reattachment rate due to the relatively large search volumes created by their long lengths (10s of nm). These are topics for future work. By using the neck-coil domain of kinesin-1 for all three motors, we eliminate any differences in autoinhibition or other regulation between the three kinesin families and focus solely on differences in the mechanochemistry of their motor domains.

(6) I am worried about the neutravidin on the microtubules, which may act as roadblocks (e.g. DOI: 10.1039/b803585g), slip termination sites (maybe without the neutravidin, the rescue rate would be much lower?), and potentially also DNA-interaction sites? At 8 nM neutravidin and the given level of biotinylation, what density of neutravidin do the authors expect on their microtubules? Can the authors rule out that the observed stall events are predominantly the result of a kinesin motor being stopped after a short slippage event at a neutravidin molecule?

We will address these points in our revision.

(7) Also, the unloaded runs should be performed on the same microtubules as in the DNA experiments, i.e., with neutravidin. Otherwise, I do not see how the values can be compared.

We will address this point in our revision.

(8) If, as stated, "a portion of kinesin-3 unloaded run durations were limited by the length of the microtubules, meaning the unloaded duration is a lower limit." corrections (such as Kaplan-Meier) should be applied, DOI: 10.1016/j.bpj.2017.09.024.

(9) Shouldn't Kaplan-Meier also be applied to the ramp durations ... as a ramp may also artificially end upon stall? Also, doesn't the comparison between ramp and stall duration have a problem, as each stall is preceded by a ramp ...and the (maximum) ramp times will depend on the speed of the motor? Kinesin-3 is the fastest motor and will reach stall much faster than kinesin-1. Isn't it obvious that the stall durations are longer than the ramp duration (as seen for all three motors in Figure 3)?

The reviewer rightly notes the many challenges in estimating the motor off-rates during ramps. To estimate ramp off-rates and as an independent approach to calculating the unloaded and stall durations, we developed a Markov model coupled with Bayesian inference methods to estimate a duration parameter (equivalent to the inverse of the off-rate) for the unloaded, ramp, and stall duration distributions. With the ramps, we have left censoring due to the difficulty in detecting the start of the ramps in the fluctuating baseline, and we have right censoring due to reaching stall (with different censoring of the ramp duration for the three motors due to their different speeds). The Markov model assumes a constant detachment probability and history independence, and thus is robust even in the face of left and right censoring (details in the Supplementary section). This approach is preferred over Kaplan-Meier because, although these non-parametric methods make no assumptions for the distribution, they require the user to know exactly where the start time is.

Regarding the potential underestimate of the kinesin-3 unloaded run duration due to finite microtubule lengths. The first point is that the unloaded duration data in Fig. 2C are quite linear up to 6 s and are well fit by the single-exponential fit (the points above 6s don’t affect the fit very much). The second point is that when we used our Markov model (which is robust against right censoring) to estimate the unloaded and stall durations, the results agreed with the single-exponential fits very well (Table S2). For instance, the single-exponential fit for the kinesin-3 unloaded duration was 2.74 s (2.33 – 3.17 s 95% CI) and the estimate from the Markov model was 2.76 (2.28 – 3.34 s 95% CI). Thus, we chose not to make any corrections due to finite microtubule lengths.

(10) It is not clear what is seen in Figure S6A: It looks like only single motors (green, w/o a DNA molecule) are walking ... Note: the influence of the attached DNA onto the stepping duration of a motor may depend on the DNA conformation (stretched and near to the microtubule (with neutravidin!) in the tethered case and spherically coiled in the untethered case).

In Figure S6A kymograph, the green traces are GFP-labeled kinesin-1 without DNA attached (which are in excess) and the red diagonal trace is a motor with DNA attached. There are also two faint horizontal red traces, which are labeled DNA diffusing by (smearing over a large area during a single frame). Panel S6B shows run durations of motors with DNA attached. We agree that the DNA conformation will differ if it is attached and stretched (more linear) versus simply being transported (random coil), but by its nature this control experiment is only addressing random coil DNA.

(11) Along this line: While the run time of kinesin-1 with DNA (1.4 s) is significantly shorter than the stall time (3.0 s), it is still larger than the unloaded run time (1.0 s). What do the authors think is the origin of this increase?

Our interpretation of the unloaded kinesin-DNA result is that the much slower diffusion constant of the DNA relative to the motor alone enables motors to transiently detach and rebind before the DNA cargo has diffused away, thus extending the run duration. In contrast, such detachment events for motors alone normally result in the motor diffusing away from the microtubule, terminating the run. This argument has been used to reconcile the longer single-motor run lengths in the gliding assay versus the bead assay (Block et al., 1990). Notably, this slower diffusion constant should not play a role in the DNA tensiometer geometry because if the motor transiently detaches, then it will be pulled backward by the elastic forces of the DNA and detected as a slip or detachment event. We will address this point in the revision.

(12) "The simplest prediction is that against the low loads experienced during ramps, the detachment rate should match the unloaded detachment rate." I disagree. I would already expect a slight increase.

Agreed. We will change this text to: “The prediction for a slip bond is that against the low loads experienced during ramps, the detachment rate should be equal to or faster than the unloaded detachment rate.”

(13) Isn't the model over-defined by fitting the values for the load-dependence of the strong-to-weak transition and fitting the load dependence into the transition to the slip state?

Essentially, yes, it is overdefined, but that is essentially by design and it is still very useful. Our goal here was to make as simple a model as possible that could account for the data and use it to compare model parameters for the different motor families. Ignoring the complexity of the slip and detached states, a model with a strong and weak state in the stepping cycle and a single transition out of the stepping cycle is the simplest formulation possible. And having rate constants (k_S-W and k_slip in our case) that vary exponentially with load makes thermodynamic sense for modeling mechanochemistry (Howard, 2001). Thus, we were pleasantly surprised that this bare-bones model could recapitulate the unloaded and stall durations for all three motors (Fig. 5C-E).

(14) "When kinesin-1 was tethered to a glass coverslip via a DNA linker and hydrodynamic forces were imposed on an associated microtubule, kinesin-1 dissociation rates were relatively insensitive to loads up to ~3 pN, inconsistent with slip-bond characteristics (37)." This statement appears not to be true. In reference 37, very similar to the geometry reported here, the microtubules were fixed on the surface, and the stepping of single kinesin motors attached to large beads (to which defined forces were applied by hydrodynamics) via long DNA linkers was studied. In fact, quite a number of statements made in the present manuscript have been made already in ref. 37 (see in particular sections 2.6 and 2.7), and the authors may consider putting their results better into this context in the Introduction and Discussion. It is also noteworthy to discuss that the (admittedly limited) data in ref. 37 does not indicate a "catch-bond" behavior but rather an insensitivity to force over a defined range of forces.

The reviewer misquoted our sentence. The actual wording of the sentence was: “When kinesin-1 was connected to micron-scale beads through a DNA linker and hydrodynamic forces parallel to the microtubule imposed, dissociation rates were relatively insensitive to loads up to ~3 pN, inconsistent with slip-bond characteristics (Urbanska et al., 2021).” The sentence the reviewer quoted was in a previous version that is available on BioRxiv and perhaps they were reading that version. Nonetheless, in the revision we will note in the Discussion that this behavior was indicative of an ideal bond (not a catch-bond), and we will also add a sentence in the Introduction highlighting this work.

Reviewer #3 (Public review):

The authors attribute the differences in the behaviour of kinesins when pulling against a DNA tether compared to an optical trap to the differences in the perpendicular forces. However, the compliance is also much different in these two experiments. The optical trap acts like a ~ linear spring with stiffness ~ 0.05 pN/nm. The dsDNA tether is an entropic spring, with negligible stiffness at low extensions and very high compliance once the tether is extended to its contour length (Fig. 1B). The effect of the compliance on the results should be addressed in the manuscript.

This is an interesting point. To address it, we calculated the predicted stiffness of the dsDNA by taking the slope of theoretical force-extension curve in Fig. 1B. Below 650 nm extension, the stiffness is <0.001 pN/nM; it reaches 0.01 pN/nM at 855 nm, and at 960 nm where the force is 6 pN the stiffness is roughly 0.2 pN/nm. That value is higher than the quoted 0.05 pN/nm trap stiffness, but for reference, at this stiffness, an 8 nm step leads to a 1.6 pN jump in force, which is reasonable. Importantly, the stiffness of kinesin motors has been estimated to be in the range of 0.3 pN (Coppin et al., 1996; Coppin et al., 1997). Granted, this stiffness is also nonlinear, but what this means is that even at stall, our dsDNA tether has a similar predicted compliance to the motor that is pulling on it. We will address this point in our revision.  

Compared to an optical trapping assay, the motors are also tethered closer to the microtubule in this geometry. In an optical trap assay, the bead could rotate when the kinesin is not bound. The authors should discuss how this tethering is expected to affect the kinesin reattachment and slipping. While likely outside the scope of this study, it would be interesting to compare the static tether used here with a dynamic tether like MAP7 or the CAP-GLY domain of p150glued.

Please see our response to Reviewer #2 Major Comment #4 above, which asks this same question in the context of intracellular cargo. We plan to address this in our revision. Regarding a dynamic tether, we agree that’s interesting – there are kinesins that have a second, non-canonical binding site that achieves this tethering (ncd and Cin8); p150glued likely does this naturally for dynein-dynactin-activator complexes; and we speculated in a review some years ago (Hancock, 2014) that during bidirectional transport kinesin and dynein may act as dynamic tethers for one another when not engaged, enhancing the activity of the opposing motor.

In the single-molecule extension traces (Figure 1F-H; S3), the kinesin-2 traces often show jumps in position at the beginning of runs (e.g., the four runs from ~4-13 s in Fig. 1G). These jumps are not apparent in the kinesin-1 and -3 traces. What is the explanation? Is kinesin-2 binding accelerated by resisting loads more strongly than kinesin-1 and -3?

Due to the compliance of the dsDNA, the 95% limits for the initial attachment position are +/- 290 nm (Fig. S2). Thus, some apparent ‘jumps’ from the detached state are expected. We will take a closer look at why there are jumps for kinesin-2 that aren’t apparent for kinesin-1 or -3.

When comparing the durations of unloaded and stall events (Fig. 2), there is a potential for bias in the measurement, where very long unloaded runs cannot be observed due to the limited length of the microtubule (Thompson, Hoeprich, and Berger, 2013), while the duration of tethered runs is only limited by photobleaching. Was the possible censoring of the results addressed in the analysis?

Yes. Please see response to Reviewer #2 points (8) and (9) above.

The mathematical model is helpful in interpreting the data. To assess how the "slip" state contributes to the association kinetics, it would be helpful to compare the proposed model with a similar model with no slip state. Could the slips be explained by fast reattachments from the detached state?

In the model, the slip state and the detached states are conceptually similar; they only differ in the sequence (slip to detached) and the transition rates into and out of them. The simple answer is: yes, the slips could be explained by fast reattachments from the detached state. In that case, the slip state and recovery could be called a “detached state with fast reattachment kinetics”. However, the key data for defining the kinetics of the slip and detached states is the distribution of Recovery times shown in Fig. 4D-F, which required a triple exponential to account for all of the data. If we simplified the model by eliminating the slip state and incorporating fast reattachment from a single detached state, then the distribution of Recovery times would be a single-exponential with a time constant equivalent to t₁, which would be a poor fit to the experimental distributions in Fig. 4D-F.

We appreciate the efforts and helpful suggestions of all three reviewers and the Editor.

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Acórdão 2450/2025 Plenário (Representação, Relator Ministro Jorge Oliveira)

Licitação. Estudo de viabilidade. Locação (Licitação). Veículo. Estudo técnico preliminar. Análise de custos. Benefícios. Opção. Aquisição. Tecnologia. Ciclo de vida.

• No estudo técnico preliminar de licitação para locação de veículos, deve ser realizada análise do custo-benefício da opção de locação em comparação com a de aquisição, bem como exame do custo do ciclo de vida do objeto e avaliação das alternativas tecnológicas possíveis (como estudo comparativo entre veículos a combustão e híbridos), em cumprimento ao disposto no art. 11, inciso I, da Lei 14.133/2021.

Author response:

Reviewer #1 (Public review):

Fombellida-Lopez and colleagues describe the results of an ART intensification trial in people with HIV infection (PWH) on suppressive ART to determine the effect of increasing the dose of one ART drug, dolutegravir, on viral reservoirs, immune activation, exhaustion, and circulating inflammatory markers. The authors hypothesize that ART intensification will provide clues about the degree to which low-level viral replication is occurring in circulation and in tissues despite ongoing ART, which could be identified if reservoirs decrease and/or if immune biomarkers change. The trial design is straightforward and well-described, and the intervention appears to have been well tolerated. The investigators observed an increase in dolutegravir concentrations in circulation, and to a lesser degree in tissues, in the intervention group, indicating that the intervention has functioned as expected (ART has been intensified in vivo). Several outcome measures changed during the trial period in the intervention group, leading the investigators to conclude that their results provide strong evidence of ongoing replication on standard ART. The results of this small trial are intriguing, and a few observations in particular are hypothesis-generating and potentially justify further clinical trials to explore them in depth. However, I am concerned about over-interpretation of results that do not fully justify the authors' conclusions.

We thank Reviewer #1 for their thoughtful and constructive comments, which helped us clarify and improve the manuscript. Below, we address each of the reviewer’s points and describe the changes that we implemented in the revised version. We acknowledge the reviewer’s concern regarding potential overinterpretation of certain findings, and in the revised version we took particular care to ensure that all conclusions are supported by the data and framed within the exploratory nature of the study.

(1) Trial objectives: What was the primary objective of the trial? This is not clearly stated. The authors describe changes in some reservoir parameters and no changes in others. Which of these was the primary outcome? No a priori hypothesis / primary objective is stated, nor is there explicit justification (power calculations, prior in vivo evidence) for the small n, unblinded design, and lack of placebo control. In the abstract (line 36, "significant decreases in total HIV DNA") and conclusion (lines 244-246), the authors state that total proviral DNA decreased as a result of ART intensification. However, in Figures 2A and 2E (and in line 251), the authors indicate that total proviral DNA did not change. These statements are confusing and appear to be contradictory. Regarding the decrease in total proviral DNA, I believe the authors may mean that they observed transient decrease in total proviral DNA during the intensification period (day 28 in particular, Figure 2A), however this level increases at Day 56 and then returns to baseline at Day 84, which is the source of the negative observation. Stating that total proviral DNA decreased as a result of the intervention when it ultimately did not is misleading, unless the investigators intended the day 28 timepoint as a primary endpoint for reservoir reduction - if so, this is never stated, and it is unclear why the intervention would then be continued until day 84? If, instead, reservoir reduction at the end of the intervention was the primary endpoint (again, unstated by the authors), then it is not appropriate to state that the total proviral reservoir decreased significantly when it did not.

We agree with the reviewer that the primary objective of the study was not explicitly stated in the submitted manuscript. We clarified this in the revised manuscript (lines 361-364). As registered on ClinicalTrials.gov (NCT05351684), the primary outcome was defined as “To evaluate the impact of treatment intensification at the level of total and replication-competent reservoir (RCR) in blood and in tissues”, with a time frame of 3 months. Accordingly, our aim was to explore whether any measurable reduction in the HIV reservoir (total or replication-competent) occurred during the intensification period, including at day 28, 56, or 84. The protocol did not prespecify a single time point for this effect to occur, and the exploratory design allowed for detection of transient or sustained changes within the intensification window.

We recognize that this scope was not clearly articulated in the original text and may have led to confusion in interpreting the transient drop in total HIV DNA observed at day 28. While total DNA ultimately returned to baseline by the end of intensification, the presence of a transient reduction during this 3-month window still fits within the framework of the study’s registered objective. Moreover, although the change in total HIV DNA was transient, it aligns with the consistent direction of changes observed across the multiple independent measures, including CA HIV RNA, RNA/DNA ratio and intact HIV DNA, collectively supporting a biological effect of intensification.

We would also like to stress that this is the first clinical trial ever, in which an ART intensification is performed not by adding an extra drug but by increasing the dosage of an existing drug. Therefore, we were more interested in the overall, cumulative, effect of intensification throughout the entire trial period, than in differences between groups at individual time points. We clarified in the revised manuscript that this was a proof-of-concept phase 2 study, designed to reveal biological effects of ART intensification rather than confirm efficacy in a powered comparison. The absence of a prespecified statistical endpoint or sample size calculation reflects the exploratory nature of the trial.

(2) Intervention safety and tolerability: The results section lacks a specific heading for participant safety and tolerability of the intervention. I was wondering about clinically detectable viremia in the study. Were there any viral blips? Was the increased DTG well tolerated? This drug is known to cause myositis, headache, CPK elevation, hepatotoxicity, and headache. Were any of these observed? What is the authors' interpretation of the CD4:8 ratio change (line 198)? Is this a significant safety concern for a longer duration of intensification? Was there also a change in CD4% or only in absolute counts? Was there relative CD4 depletion observed in the rectal biopsy samples between days 0 and 84? Interestingly, T cells dropped at the same timepoints that reservoirs declined... how do the authors rule out that reservoir decline reflects transient T cell decline that is non-specific (not due to additional blockade of replication)?

We improved the Methods section to clarify how safety and tolerability were assessed during the study (lines 389-396). Safety evaluations were conducted on day 28 and day 84 and included a clinical examination and routine laboratory testing (liver function tests, kidney function, and complete blood count). Medication adherence was also monitored through pill counts performed by the study nurses.

No virological blips above 50 copies/mL were observed and no adverse events were reported by participants during the 3-month intensification period. Although CPK levels were not included in the routine biological monitoring, no participant reported muscle pain or other symptoms suggestive of muscle toxicity.

The CD4:CD8 ratio decrease noted during intensification was not associated with significant changes in absolute CD4 or CD8 counts, as shown in Figure 5. We interpret this ratio change as a transient redistribution rather than an immunological risk, therefore we do not consider it to represent a safety concern.

We would like to clarify that CD4⁺ T-cell counts did not significantly decrease in any of the treatment groups, as shown in Figure 5. The apparent decline observed concerns the CD4/CD8 ratio, which transiently dropped, but not the absolute number of CD4⁺ T cells. Moreover, although the dynamics of total HIV DNA is indeed similar to that of CD4/CD8 ratio (both declined transiently and then returned to baseline by day 84), the dynamics of unspliced RNA and unspliced RNA/total DNA ratio are clearly different, as these markers demonstrated a sustained decrease that was maintained throughout the trial period, even when the CD4/CD8 ratio already returned to baseline. Also, we observed a significant decrease in intact HIV DNA at day 84 compared to day 0. These effects cannot be easily explained by a transient decline in CD4+ cells.

(3) The investigators describe a decrease in intact proviral DNA after 84 days of ART intensification in circulating cells (Figure 2D), but no changes to total proviral DNA in blood or tissue (Figures 2A and 2E; IPDA does not appear to have been done on tissue samples). It is not clear why ART intensification would result in a selective decrease in intact proviruses and not in total proviruses if the source of these reservoir cells is due to ongoing replication. These reservoir results have multiple interpretations, including (but not limited to) the investigators' contention that this provides strong evidence of ongoing replication. However, ongoing replication results in the production of both intact and mutated/defective proviruses that both contribute to reservoir size (with defective proviruses vastly outnumbering intact proviruses). The small sample size and well-described heterogeneity of the HIV reservoir (with regard to overall size and composition) raise the possibility that the study was underpowered to detect differences over the 84-day intervention period. No power calculations or prior studies were described to justify the trial size or the duration of the intervention. Readers would benefit from a more nuanced discussion of reservoir changes observed here.

We sincerely thank the reviewer for this insightful comment. We fully agree that the reservoir dynamics observed in our study might raise several possible interpretations, and that its complexity, resulting from continuous cycles of expansion and contraction, reflects the heterogeneity of the latent reservoir. 

Total HIV DNA in PBMCs showed a transient decline during intensification (notably at day 28), ultimately returning to baseline by day 84. This biphasic pattern likely reflects the combined effects of suppression of ongoing low-level replication by an increased DTG dosage, followed by the expansion of infected cell clones (mostly harbouring defective proviruses). In other words, the transient decrease in total (intact + defective) DNA at day 28 may be due to an initial decrease in newly infected cells upon ART intensification, however at the subsequent time points this effect was masked by proliferation (clonal expansion) of infected cells with defective proviruses. Recent studies suggest that intact and defective proviruses are subjected to different selection pressures by the immune system on ART (PMID: 38337034) and their decay on therapy is different (intact proviruses are cleared much more rapidly than defectives). In addition, defective proviruses can be preferentially expanded as they can reprogram the host cell proliferation machinery (https://doi.org/10.1101/2025.09.22.676989). This explains why in our study the intact proviruses decreased, but the total proviruses did not change, between days 0 and 84, in the intensification group. Interestingly, in the control group, we observed a significant increase in total DNA at day 84 compared to day 0, with no difference for the intact DNA, which is also in line with the clonal expansion of defective proviruses.

Importantly, we observed a significant decrease in intact proviral DNA between day 0 and day 84 in the intensification group (Figure 2D). This result directly addresses the study’s primary objective: assessing the impact of intensification on the replication-competent reservoir. In comparison, as the reviewer rightly points out, total HIV DNA includes over 90% defective genomes, which limits its interpretability as a biomarker of biologically relevant reservoir changes. In addition, other reservoir markers, such as cell-associated unspliced RNA and RNA/DNA ratios, also showed consistent trends supporting a biologically relevant effect of intensification. Even in the absence of sustained changes in total HIV DNA, the coherence across the different independent measures of the reservoir (intact DNA, unspliced RNA), suggests an effect indicative of ongoing replication pre-intensification.

Regarding tissue reservoirs, the lack of substantial change in total HIV DNA between days 0 and 84 is also in line with the predominance of defective sequences in these compartments. Moreover, the limited increase in rectal tissue dolutegravir levels during intensification (from 16.7% to 20% of plasma concentrations) may have limited the efficacy of the intervention in this site.

As for the IPDA on rectal biopsies, we attempted the assay using two independent DNA extraction methods (Promega Reliaprep and Qiagen Puregene), but both yielded high DNA shearing index values, and intact proviral detection was successful in only 3 of 40 samples. Given the poor DNA integrity, these results were not interpretable.

That said, we fully acknowledge the limitations of our study, especially the small sample size, and we agree with the reviewer that caution is needed when interpreting these findings. In the revised manuscript, we adopted a more measured tone in the discussion (lines 340-346), stating that these observations are exploratory and hypothesis-generating, and require confirmation in larger, more powered studies. Nonetheless, we believe that the convergence of multiple reservoir markers pointing in the same direction constitutes a meaningful biological effect that deserves further investigation.

(4) While a few statistically significant changes occurred in immune activation markers, it is not clear that these are biologically significant. Lines 175-186 and Figure 3: The change in CD4 cells + for TIGIT looks as though it declined by only 1-2%, and at day 84, the confidence interval appears to widen significantly at this timepoint, spanning an interquartile range of 4%. The only other immune activation/exhaustion marker change that reached statistical significance appears to be CD8 cells + for CD38 and HLA-DR, however, the decline appears to be a fraction of a percent, with the control group trending in the same direction. Despite marginal statistical significance, it is not clear there is any biological significance to these findings; Figure S6 supports the contention that there is no significant change in these parameters over time or between groups. With most markers showing no change and these two showing very small changes (and the latter moving in the same direction as the control group), these results do not justify the statement that intensifying DTG decreases immune activation and exhaustion (lines 38-40 in the abstract and elsewhere).

We agree with the reviewer that the observed changes in immune activation and exhaustion markers were modest. We revised the abstract and the manuscript text (including a section header) to reflect this more accurately (lines 39, 175, 185, 253). We noted that these differences, while statistically significant (e.g., in TIGIT+ CD4+ T cells and CD38+HLA-DR+ CD8+ T cells), were limited in magnitude. We explicitly acknowledged these limitations and interpreted the findings with appropriate caution.

(5) There are several limitations of the study design that deserve consideration beyond those discussed at line 327. The study was open-label and not placebo-controlled, which may have led to some medication adherence changes that confound results (authors describe one observation that may be evidence of this; lines 146-148). Randomized/blinded / cross-over design would be more robust and help determine signal from noise, given relatively small changes observed in the intervention arm.There does not seem to be a measurement of key outcome variables after treatment intensification ceased - evidence of an effect on replication through ART intensification would be enhanced by observing changes once intensification was stopped. Why was intensification maintained for 84 days? More information about the study duration would be helpful. Table 1 indicates that participants were 95% male. Sex is known to be a biological variable, particularly with regard to HIV reservoir size and chronic immune activation in PWH. Worldwide, 50% of PWH are women. Research into improving management/understanding of disease should reflect this, and equal participation should be sought in trials. Table 1 shows differing baseline reservoir sizes between the control and intervention groups. This may have important implications, particularly for outcomes where reservoir size is used as the denominator.

We expanded the limitations section to address several key aspects raised by the reviewer: the absence of blinding and placebo control, the predominantly male study population, and the lack of postintervention follow-up. While we acknowledge that open-label designs can introduce behavioural biases, including potential changes in adherence, we now explicitly state that placebo-controlled, blinded trials would provide a more robust assessment and are warranted in future research (lines 340346). 

The 84-day duration of intensification was chosen based on previous studies and provided sufficient time for observing potential changes in viral transcription and reservoir dynamics. However, we agree that including post-intervention follow-up would have strengthened the conclusions, and we highlighted this limitation and future direction in the revised manuscript (lines 340-346). 

The sex imbalance is now clearly acknowledged as a limitation in the revised manuscript, and we fully support ongoing efforts to promote equitable recruitment in HIV research. We would like to add that, in our study, rectal biopsies were coupled with anal cancer screening through HPV testing. This screening is specifically recommended for younger men who have sex with men (MSM), as outlined in the current EACS guidelines (see: https://eacs.sanfordguide.com/eacs part2/cancer/cancerscreening-methods). As a result, MSM participants had both a clinical incentive and medical interest to undergo this procedure, which likely contributed to the higher proportion of male participants in the study.

Lastly, although baseline total HIV DNA was higher in the intensified group, our statistical approach is based on a within-subject (repeated-measures) design, in which the longitudinal change of a parameter within the same participant during the study was the main outcome. In other words, we are not comparing absolute values of any marker between the groups, we are looking at changes of parameters from baseline within participants, and these are not expected to be affected by baseline imbalances.

(6) Figure 1: the increase in DTG levels is interesting - it is not uniform across participants. Several participants had lower levels of DTG at the end of the intervention. Though unlikely to be statistically significant, it would be interesting to evaluate if there is a correlation between change in DTG concentrations and virologic / reservoir / inflammatory parameters. A positive relationship between increasing DTG concentration and decreased cell-associated RNA, for example, would help support the hypothesis that ongoing replication is occurring.

We agree with the reviewer that assessing correlations between DTG concentrations and virological, immunological, or inflammatory markers would be highly informative. In fact, we initially explored this question in a preliminary way by examining whether individuals who showed a marked increase in DTG levels after intensification also demonstrated stronger changes in the viral reservoir. While this exploratory analysis did not reveal any clear associations, we would like to emphasize that correlating biological effects with DTG concentrations measured at a single timepoint may have limited interpretability. A more comprehensive understanding of the relationship between drug exposure and reservoir dynamics would ideally require multiple pharmacokinetic measurements over time, including pre-intensification baselines. This is particularly important given that DTG concentrations vary across individuals and over time, depending on adherence, metabolism, and other individual factors.

(7) Figure 2: IPDA in tissue- was this done? scRNA in blood (single copy assay) - would this be expected to correlate with usCaRNA? The most unambiguous result is the decrease in cell-associated RNA - accompanying results using single-copy assay in plasma would be helpful to bolster this result.

As mentioned in our response to point 3, we attempted IPDA on tissue samples, but technical limitations prevented reliable detection of intact proviruses. Regarding residual viremia, we did perform ultra-sensitive plasma HIV RNA quantification but due to a technical issue (an inadvertent PBMC contamination during plasma separation) that affected the reliability of the results we felt uncomfortable including these data in the manuscript.

The use of the US RNA / Total DNA ratio is not helpful/difficult to interpret since the control and intervention arms were unmatched for total DNA reservoir size at study entry.

We respectfully disagree with this comment. The US RNA/total DNA ratio is commonly used to assess the relative transcriptional activity of the viral reservoir, rather than its absolute size. While we acknowledge that the total HIV-1 DNA levels differed at baseline between the two groups, the US RNA/total DNA ratio specifically reflects the relationship between transcriptional activity and reservoir size within each individual, and is therefore not directly confounded by baseline differences in total DNA alone.

Moreover, our analyses focus on within-subject longitudinal changes from baseline, not on direct between-group comparisons of absolute marker values. As such, the observed changes in the US RNA/total DNA ratio over time are interpreted relative to each participant's baseline, mitigating concerns related to baseline imbalances between groups.

Reviewer #2 (Public review):

Summary:

An intensification study with a double dose of 2nd generation integrase inhibitor with a background of nucleoside analog inhibitors of the HIV retrotranscriptase in 2, and inflammation is associated with the development of co-morbidities in 20 individuals randomized with controls, with an impact on the levels of viral reservoirs and inflammation markers. Viral reservoirs in HIV are the main impediment to an HIV cure, and inflammation is associated with co-morbidities.

Strengths:

The intervention that leads to a decrease of viral reservoirs and inflammation is quite straightforward forward as a doubling of the INSTI is used in some individuals with INSTI resistance, with good tolerability.

This is a very well documented study, both in blood and tissues, which is a great achievement due to the difficulty of body sampling in well-controlled individuals on antiretroviral therapy. The laboratory assays are performed by specialists in the field with state-of-the art quantification assays. Both the introduction and the discussion are remarkably well presented and documented.

The findings also have a potential impact on the management of chronic HIV infection.

Weaknesses:

I do not think that the size of the study can be considered a weakness, nor the fact that it is open-label either.

We thank Reviewer #2 for their constructive and supportive comments. We appreciate their positive assessment of the study design, the translational relevance of the intervention, and the technical quality of the assays. We also take note of their perspective regarding sample size and study design, which supports our positioning of this trial as an exploratory, hypothesis-generating phase 2 study.

Reviewer #3 (Public review):

The introduction does a very good job of discussing the issue around whether there is ongoing replication in people with HIV on antiretroviral therapy. Sporadic, non-sustained replication likely occurs in many PWH on ART related to adherence, drug-drug interactions and possibly penetration of antivirals into sanctuary areas of replication and as the authors point out proving it does not occur is likely not possible and proving it does occur is likely very dependent on the population studied and the design of the intervention. Whether the consequences of this replication in the absence of evolution toward resistance have clinical significance challenging question to address.

It is important to note that INSTI-based therapy may have a different impact on HIV replication events that results in differences in virus release for specific cell type (those responsible for "second phase" decay) by blocking integration in cells that have completed reverse transcription prior to ART initiation but have yet to be fully activated. In a PI or NNRTI-based regimen, those cells will release virus, whereas with an INSTI-based regimen, they will not.

Given the very small sample size, there is a substantial risk of imbalance between the groups in important baseline measures. Unfortunately, with the small sample size, a non-significant P value is not helpful when comparing baseline measures between groups. One suggestion would be to provide the full range as opposed to the inter-quartile range (essentially only 5 or 6 values). The authors could also report the proportion of participants with baseline HIV RNA target not detected in the two groups.

We thank Reviewer #3 for their thoughtful and balanced review. We are grateful for the recognition of the strength of the Introduction, the complexity of evaluating residual replication, and the technical execution of the assays. We also appreciate the insightful suggestions for improving the clarity and transparency of our results and discussion.

We revised the manuscript to address several of the reviewer’s key concerns. We agree that the small sample size increases the risk of baseline imbalances. We acknowledged these limitations in the manuscript (lines 327-330). For transparency, we now provide both the full range and the IQR for all parameters in Table 1. However, we would like to stress that our statistical approach is based on a within-subject (repeated-measures) design, in which the longitudinal change of a parameter within the same participant during the study was the main outcome. In other words, we are not comparing absolute values of any marker between the groups, we are looking at changes of parameters from baseline within participants, and these are not expected to be affected by baseline imbalances.

A suggestion that there is a critical imbalance between groups is that the control group has significantly lower total HIV DNA in PBMC, despite the small sample size. The control group also has numerically longer time of continuous suppression, lower unspliced RNA, and lower intact proviral DNA. These differences may have biased the ability to see changes in DNA and US RNA in the control group.

We acknowledge the significant baseline difference in total HIV DNA between groups, which we have clearly reported. However, the other variables mentioned, such as duration of continuous viral suppression, unspliced RNA levels, and intact proviral DNA, did not differ significantly between groups at baseline, despite differences in the median values (that are always present). These numerical differences do not necessarily indicate a critical imbalance.

Notably, there was no significant difference in the change in US RNA/DNA between groups (Figure 2C).

The nonsignificant difference in the change in US RNA/total DNA between groups is not unexpected, given the significant between-group differences for both US RNA and total DNA changes. Since the ratio combines both markers, it is likely to show attenuated between-group differences compared to the individual components. However, while the difference did not reach statistical significance (p = 0.09), we still observed a trend towards a greater reduction in the US RNA/total DNA ratio in the intervention group.

The fact that the median relative change appears very similar in Figure 2C, yet there is a substantial difference in P values, is also a comment on the limits of the current sample size. 

Although we surely agree that in general, the limited sample size impacts statistical power, we would like to point out that in Figure 2C, while the medians may appear similar, the ranges do differ between groups. At days 56 and 84, the median fold changes from baseline are indeed close but the full interquartile range in the DTG group stays below 1, while in the control group, the interquartile range is wider and covers approximately equal distance above and below 1. This explains the difference in p values between the groups.

The text should report the median change in US RNA and US RNA/DNA when describing Figures 2A-2C.

These data are already reported in the Results section (lines 164–166): "By day 84, US RNA and US RNA/total DNA ratio had decreased from day 0 by medians (IQRs) of 5.1 (3.3–6.4) and 4.6 (3.1–5.3) fold, respectively (p = 0.016 for both markers)."

This statistical comparison of changes in IPDA results between groups should be reported. The presentation of the absolute values of all the comparisons in the supplemental figures is a strength of the manuscript.

In the assessment of ART intensification on immune activation and exhaustion, the fact that none of the comparisons between randomized groups were significant should be noted and discussed.

We would like to point out that a statistically significant difference between the randomized groups was observed for the frequency of CD4⁺ T cells expressing TIGIT, as shown in Figure 3A and reported in the Results section (p = 0.048).

The changes in CD4:CD8 ratio and sCD14 levels appear counterintuitive to the hypothesis and are commented on in the discussion.

Overall, the discussion highlights the significant changes in the intensified group, which are suggestive. There is limited discussion of the comparisons between groups where the results are less convincing.

We observed statistically significant differences between the randomized groups for total DNA (p<0.001) and US RNA (p=0.01), as well as for the frequency of CD4⁺ T cells expressing TIGIT (p=0.048). We would like to stress that US RNA is a key marker of residual replication as it is very sensitive to de novo infection events. As discussed in the manuscript (lines 291-294), a newly infected CD4+ T lymphocyte can contain hundreds to thousands of US HIV RNA copies at the peak of infection. Therefore, a change in the US RNA level upon ART intensification is a very sensitive indicator of new infections. The fact that for US RNA we observed both a significant reduction in the intensified group and a significant difference between the groups is a strong indicator that some new infections had been occurring prior to intensification.

The limitations of the study should be more clearly discussed. The small sample size raises the possibility of imbalance at baseline. The supplemental figures (S3-S5) are helpful in showing the differences between groups at baseline, and the variability of measurements is more apparent. The lack of blinding is also a weakness, though the PK assessments do help (note 3TC levels rise substantially in both groups for most of the time on study (Figure S2).

The many assays and comparisons are listed as a strength. The many comparisons raise the possibility of finding significance by chance. In addition, if there is an imbalance at baseline outcomes, measuring related parameters will move in the same direction.

We agree that the multiple comparisons raise the possibility of chance findings but would like to stress that in an exploratory study like this it is very important to avoid a type II error. In addition, the consistent directionality of the most relevant outcomes (US RNA and intact DNA) lends biological plausibility to the observed effects.

The limited impact on activation and inflammation should be addressed in the discussion, as they are highlighted as a potentially important consequence of intermittent, not sustained replication in the introduction.

The study is provocative and well executed, with the limitations listed above. Pharmacokinetic analyses help mitigate the lack of blinding. The major impact of this work is if it leads to a much larger randomized, controlled, blinded study of a longer duration, as the authors point out.

Finally, we fully endorse the reviewer’s suggestion that the primary contribution of this study lies in its value as a proof-of-concept and foundation for future randomized, blinded trials of greater scale and duration. We highlighted this more clearly in the revised Discussion (lines 340-346).

Reviewer #1 (Recommendations for the authors):

(1) Lines 84-87: How would chronic immune activation/inflammation be expected to differ if viral antigen is being released from stable reservoirs rather than low-level replication?

This is a very insightful question. Although release of viral antigens from stable reservoirs could certainly also trigger immune activation/inflammation, the reservoir cells in PWH on long-term ART are constantly being negatively selected by the immune system (PMID: 38337034; PMID: 36596305) so that after a number of years on therapy, most proviruses are either transcriptionally silent or express only a low amount of viral RNA/antigen. Recent evidence suggests that these selected cells possess specific biological properties that include mechanisms that limit proviral gene expression (PMID: 36599977; PMID: 36599978). In comparison, low-level replication would result in de novo infection of unselected, activated CD4+ cells that are expected to produce much more viral antigen than preselected reservoir cells.

(2) Lines 249-253: There are multiple ways to explain this observation - alternatively, the total proviral DNA declined due to transient CD4 depletion.

As discussed above, CD4⁺ T-cell counts did not significantly decrease in any of the treatment groups, as shown in Figure 5. The apparent decline observed concerns the CD4/CD8 ratio, which transiently dropped, but not the absolute number of CD4⁺ T cells. Moreover, although the dynamics of total HIV DNA is indeed similar to that of CD4/CD8 ratio (both declined transiently and then returned to baseline by day 84), the dynamics of unspliced RNA and unspliced RNA/total DNA ratio is clearly different, as these markers demonstrated a sustained decrease that was maintained throughout the trial period. Also, we observed a significant decrease in intact HIV DNA at day 84 compared to day 0. These effects cannot be easily explained by a transient decline in CD4+ cells.

(3) Lines 301-305: This is a confusing explanation for not seeing an effect in tissue. Overall, there was no change in total proviral DNA in blood between days 0 and 84 either - yet the explanation for this observation is different (249-253). Was IPDA not performed on the tissue? Wouldn't this be the preferred test for reservoir depletion?

We thank the reviewer for bringing this point to our attention. We modified the Discussion to prevent the confusion (lines 303-305). As for the IPDA on tissue, we attempted this assay on the tissue samples using two independent DNA extraction methods (Promega Reliaprep and Qiagen Puregene), but both yielded high DNA shearing index values, and intact proviral detection was successful in only 3 of 40 samples. Given the poor DNA integrity, these results were not interpretable.

Author response:

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

Reviewer #1 (Public review):

Weaknesses:

Only 1 gene (katG) gave a strong and 1 (Mab_1456c) exhibited a minor defect. Two of the clones did not show any persistence phenotype (blaR and recR) and one (pafA) showed a minor phenotype,

We have now carried out more detailed validation studies on the Tn-Seq, with analysis of timedependent killing over 14 d. This more comprehensive analysis shows that 4 of 5 genes analyzed do indeed have antibiotic tolerance defects under the conditions that Tn-Seq predicted a survival defect (Revised Figure 3). In addition, we found that even before actual cell death, several mutants had delayed resumption of growth after antibiotic removal (Figure 3 Supplemental).

Fig 3 - Why is there such a huge difference in the extent of killing of the control strain in media, when exposed to TIG/LZD, when compared to Fig. 1C and Fig. 4. In Fig. 1C, M. abs grown in media decreases by >1 log by Day 3 and >4 log by Day 6, whereas in Fig. 3, the bacterial load decreases by <1 log by Day 3 and <2 log by Day 6. This needs to be clarified, if the experimental conditions were different, because if comparing to Fig. 1C data then the katG mutant strain phenotype is not very different.

We agree with the reviewer that there is variability in the timing and extent of cell death from experiment to experiment. As noted by the reviewer, in Figure 1C the largest decrement in survival is between day 1 - day 3 (also seen in Figure 6A). As they noted in Figure 4 the largest decrement is between day 3 – day 6 (also seen in Figure 3A, Figure 5F). In each experiment with katG mutants we carefully compare the mutant vs. the control strain within that experiment, which is more accurate than comparing the behavior of mutant in one experiment to a control in another experiment.

Reviewer #2 (Public review):

Weaknesses:

.First, word-choice decisions could better conform to the published literature. Alternatively, novel definitions could be included. In particular, the data support the concept of phenotypic tolerance, not persistence. 

We appreciate the reviewers comments, text modified.

Second, two of the novel observations could be explored more extensively to provide mechanistic explanations for the phenomena. 

We have added several additional experiments, these are detailed below in response to specific comments.

Reviewer #3 (Public review):

Weaknesses:

The findings could not be validated in clinical strains.

We understand the reviewer’s concern that the katG phenotype was only observed in one of the two clinical strains we studied. We feel that our findings are relevant beyond the ATCC 19977 strain for two reasons

(1) We have performed additional analyses of the two clinical isolates and indeed find significant accumulation of ROS following antibiotic exposure in both of these strains (revised Figure 6A).

(2) We do in fact see a role for katG in starvation-induced antibiotic tolerance in Mabs clinical strain-2. It is not surprising that different strains from a particular species may have some different responses to stresses – for example, there is wide strain-specific variability in susceptibility to different phages within a species based on which particular phage defense modules a given strain carries (for example PMID: 37160116). We speculate that different Mabs strains may express varying levels of other antioxidant factors and note that the genes encoding several such factors were identified by our Tn-Seq screen including the peroxidases ahpC, ahpD, and ahpE. Our analysis of the genetic interactions between katG and these other factors is ongoing. 

Comments/Suggestions

(1) In Fig1E, the authors show no difference in killing Mtb with or without adaptation in PBS. These data are contrary to the data presented in Figure 1B. These also do not align with the data of M. smegmatis and M. abscesses. Please discuss these observations in light of the Duncan model of persistence (Mol Microbiol. 2002 Feb;43(3):717-31.).’

The above referenced Duncan laboratory study found tolerance after prolonged starvation but did not actually examine tolerance at early time points. While some of the transcriptional and metabolic changes seen by Duncan and others are slow, other groups have described starvation responses in Mtb that are quite rapid. For example, the stringent response mediator ppGpp accumulates within a few hours after onset of starvation in Mtb (PMID: 30906866). We suspect that a rapid signaling response such as this underlies the phenotype we observe. Regarding the difference between Mtb and other mycobacterial species we also find it surprising that Mtb had a much more rapid starvation response. This is a clear species-specific difference that may reflect an adaptation of Mtb to the nutrient-limited physiologic niche within host macrophages.

(2) Line 151, the authors state that they have used an M. abscesses Tn mutant library of ~ 55,000 mutant strains. The manuscript will benefit from the description of the coverage of total TA sites covered by the mutants.

Text modified to add this detail. There are 91,559 TA sites in the abscessus genome. Thus, our Tn density is ~60%.

(3) Line 155: Please explain how long the cells were kept in an Antibiotic medium.

This technical detail was noted above on line 153 in the original text: “…and then exposed them to TIG/LZD for 6 days”. To clarify the overall conditions, we have also revised the text of the manuscript and added the detail of how long cells were passaged after removal of antibiotics.

(4) Line 201: data not shown. Delayed resumption of growth after removal of antibiotic would be helpful in indicating drug resilience. This data could enhance the manuscript.

Data now provided in Figure 3 Supplemental

(5) Figures 4C and 4F represent the kill curve. It will be good to show the date with CFU against the drug concentration in place of OD600. CFU rather than OD600 best reflects growth inhibition.

Figures 4C and 4F are measuring the minimum inhibitory concentration (MIC) to stop the overall growth of the bacterial population. While we agree that CFU could be analyzed, this would be measuring a different outcome – cell death and the minimum bactericidal concentration (MBC). In these experiments we sought to specifically examine the MIC so as to separate growth inhibition from cell death. For this we used the standard method employed by clinical microbiology laboratories for MIC, which is optical density of the culture (PMID: 10325306).

(6) Figure 5C. The authors shall show the effect of TIG/LZD on M. abscesses ROS production without the PBS adaptation. It is important to conclude that TIG/LZD induces ROS in cells. Authors should utilize ROS scavengers such as Thiourea, DFO, etc., to conclude ROS's contribution to bacterial killing following inhibition of transcription and translation.

New data added (revised Figure 5 and Figure 5 Supplemental)  

(7) Line 303. Remove "note".

Text revised. We thank the reviewer for identifying this typographical error.  

(8) The introduction and Discussion are very similar, and several lines are repeated.

Text revised with overlapping content removed.

Reviewer #1 (Recommendations for the authors):

It appears that the same datasets for PBS adapted cultures were plotted in A-C and D-F. Either this should be specifically mentioned in the legend or it might be better to integrate the non-adapted plots into A-C which would also allow easier comparison.

Appreciate the reviewer’s suggestion; text modified with added clarification to figure legend.

This manuscript is focused on M. abs and the antibiotics TIG/LZD, so the Mtb data or data using the antibiotics INH/RIF/EMB and serves more as a distraction and can be removed

We appreciate the reviewer’s perspective. However, we wish to include these data to show the similarities (and differences) in starvation-induced tolerance between the three organisms.

Fig 3 -As mentioned for Fig. 1, it appears that the same dataset was used for the control in all the figures A-E. This should be explicitly stated in the Figure legend.

Appreciate the reviewer’s suggestion; text modified with added clarification to figure legend.

The divergent results from the clinical strains are extremely interesting. It would be helpful to determine the oxidative stress levels (similar to the cellROX data shown in 5E), to tease out if the difference in katG role is because of lack of ROS induction in these strains or due to expression of alternate anti-oxidative stress defense mechanisms.

We have performed additional cellROX analysis as suggested by the reviewer and found that the ROS induction is indeed present across all three Mabs strains, but that katG is only required in one of the two strains (Strain #2). These data are now included in the revised Figure 6.

Reviewer #2 (Recommendations for the authors):

GENERAL COMMENTS

This is a nice piece of work that uses the pathogen Mabs as a test subject.

The work has findings that likely apply generally to antibiotics and mycobacteria: 1) phenotypic tolerance is associated with suppression of ROS, 2) lethal protein synthesis inhibitors act via accumulation of ROS, and 3) levofloxacin behaves in an unexpected way. Each is a new observation. However, I believe that each topic requires more work to be firmly established to be suitable for eLife.

Phenotypic tolerance: Association with suppression of ROS is important but expected. I would solidify the conclusion by performing several additional experiments. For example, confirm the lethal effect of ROS by reducing it with an iron chelator and a radical scavenger. There is a large literature on effects of iron uptake, levels, etc. on antibiotic lethality that could be applied to this question. In 2013 Imlay argued against the validity of fluorescent probes. Perhaps getting the same results with another probe would strengthen the conclusion.

We have carried out additional experiments with both an iron chelator and small molecule ROS scavengers to further test this idea but note that these experiments have several inherent limitations: 1) These compounds have highly pleiotropic effects. For example while N-acetyl cysteine (NAC) is an antioxidant it also increases mycobacterial respiration and was shown to paradoxically decrease antibiotic tolerance in M. tuberculosis (PMID: 28396391). 2) It has been shown by the Imlay group that small-molecule antioxidants are often ineffective in quenching ROS in bacteria (PMID: 388893820), making negative results difficult to interpret. Nonetheless, we present new experimental data showing that iron chelation does indeed improve the survival of antibiotic-treated Mabs (revised Figure 5).  However,  small molecule antioxidants such as thiourea do not restore antibiotic tolerance and actually increased bacterial cell death, suggesting that they may be affecting respiration in Mabs in a manner similar to that seen for NAC in Mtb. We also note that our genetic analysis, which identified numerous other genes encoding proteins with antioxidant function (Figure 2) is a strong additional argument in support of the importance of ROS in antibiotic-mediated lethality. 

Regarding the concern raised by Imlay about the validity of oxidation-sensitive dyes - this relates to concern bacterial autofluorescence induced by antibiotics that can confound analyses in some species. We have ruled this out in our analyses by using bacteria unstained by cellROX as controls to confirm that there is negligible autofluorescence in Mabs (<0.1%, Figure 5E, Figure 6A).

Protein synthesis inhibitors: At present, this is simply an observation. More work is needed to suggest a mechanism. For example, with E. coli the aminoglycosides are protein synthesis inhibitors that also cause membrane damage. Membrane damage is known to stimulate ROS-mediated killing. Your observation needs to be extended because chloramphenicol, another protein synthesis inhibitor, blocks ROS production. The lethality may be a property of mycobacteria: does it occur with E. coli (note that rifampicin is bacteriostatic with E. coli but lethal to Mtb)?

We agree with the reviewer that the mechanism underlying ROS accumulation following transcription or translational inhibition in Mabs is of significant interest. It is likely to be a mechanism different from E. coli, because in E. coli tetracyclines and rifamycins are both bacteriostatic, whereas in Mabs they are both bactericidal. Determining the mechanism by which translation inhibitors cause ROS accumulation in Mabs is an ongoing effort in our laboratory using proteomics and metabolomics, but is outside the scope of this manuscript.

Levofloxacin: This is also at the observational stage but is unexpected. In other studies, ROS is involved in quinolone-mediated killing of bacteria. Why is this not the case with Mabs? The observation should be solidified by showing the contrast with moxifloxacin, since this compound has been studied with mycobacteria (Shee 2022 AAC). With E. coli, quinolone structure can affect the relative contribution of ROS to killing (Malik 2007 AAC), as is also seen with Mtb (Malik 2006 AAC). What is happening in the present work with levofloxacin, an important anti-tuberculosis drug? Is there a structure explanation (compare with ofloxacin)?

While these are interesting questions, a detailed exploration of the structure-function relationships between different fluoroquinolone antibiotics and their varying activities on Mtb and Mabs is outside the scope of this manuscript.  

The writing is generally easy to follow. However, the concept of persistence should be changed to phenotypic tolerance with text changes throughout. I base this suggestion on the definitions of tolerance and persistence as stated in the consensus review (Balaban 2019 Nat Micro Rev). Experimentally, tolerance is seen as a gradual decline in survival following antibiotic addition; the decline is slower than seen with wild-type cells. The data presented in this paper fit that definition. In contrast, persistence refers to a rapid drop in survival followed by a distinct plateau (Balaban 2019 Nat Micro Rev; for example, see Wu Lewis AAC 2012 ). Moreover, to claim persistence, it would be necessary to demonstrate subpopulation status, which is not done. The Balaban review is an attempt to bring order to the field with respect to persistence and tolerance, since the two are commonly used without regard for a consistent definition.

We appreciate the reviewer’s suggestion; text modified in multiple places to clarify.

Another issue requiring clarification is the relationship between resistance and tolerance. Killing by antibiotics is a two-step process, as most clearly seen with quinolones. First a reversible bacteriostatic event occurs. Resistance blocks that bacteriostatic damage. Then a lethal metabolic response to that damage occurs. Tolerance selectively blocks the second, killing event, a distinct process that often involves the accumulation of ROS. Direct antibiotic-mediated damage is an additional mode of killing that also stems from the reversible, bacteriostatic damage created by antibiotics. The authors recognize the distinction but could make it clearer. Take a look at Zheng (JJ Collins) 2020, 2022.

Text modified to clarify this point

Many readers would also like to see a bit more background on Mabs. For example, does it grow rapidly? Are there features that make it a good model for studying mycobacteria or bacteria in general? The more general, the better.

Text modified, background added

Below I have listed specific comments that I hope are useful in bringing the work to publication and making it highly cited.

SPECIFIC COMMENTS

Line 30 unexpectedly. I would delete this word because the result is expected from the ROS work of Shee et al 2022 with mycobacteria. Moreover, Zeng et al 2022 PNAS showed that ROS participates in antimicrobial tolerance, and persistence is a form of tolerance (Balalban et al, 2019, Nat Micro Rev).

Text modified as per review suggestion

Line 39 key goal: this is probably untrue in the general sense stated, since bacteriostatic antibiotics are sufficient to clear infection (Wald-Dickler 2019 Clin Infect Dis). However, it is likely to be the goal for Mtb infections.

We agree with the reviewer that bacteriostatic antibiotics are effective in treating most types of infections and do not claim otherwise in the manuscript. However, from a clinical standpoint, eradication of the pathogen causing the infection is indeed the goal of antibiotic therapy in virtually all circumstances (with the exception of specific scenarios such as cystic fibrosis where it is recognized that the infecting organism cannot be fully eliminated). In most cases, the combination of bacteriostatic antibiotics and the host immune response is sufficient to achieve eradication. We have modified the manuscript text to reflect this nuance noted by the reviewer.

Line 62 several: you list three, but hipAB works via ppGpp, so the sentence needs fixing

Text modified  

Line 70 uncertain: this uncertainty is unreferenced. Since everything is uncertain, this vague phrase does not add to the story.

The reviewer makes an interesting philosophical argument. However, we would submit that some aspects of biology, for example the regulation of glycolysis, are understood in great detail. However, other mechanisms, such as the precise mechanisms of lethality for diverse antibiotics in different bacterial species, are far more uncertain and remain a subject of debate (for example PMID: 39910302). Text not modified.

Line 72 somewhat controversial: I would delete this, because the points in the Science papers by Lewis and Imlay have been clarified and in some cases refuted by prior and subsequent work.

Text modified

Line 72 presumed: this suggests that it is wrong and perhaps a different idea has replaced it. Another, and more likely view is that there is an additional mode of killing. I suggest rephrasing to be more in line with the literature.

Text modified for clarity. In this sentence “presume” refers to the historical concept that direct target inhibition was solely responsible for antibiotic lethality. As the reviewer notes, there is now significant literature that ROS (and perhaps other secondary effects) also contribute to bacterial killing.  

Line 73 However and the following might also: this phrasing, plus the presumed, misleads the reader from your intent. I suggest rephrasing.

See above re: line 72

Line 75 citations: these are inappropriate and should be changed to fit the statement. I suggest the initial paper by Collins (Kohanski 2007 Cell) a recent paper by Zhao (Zeng PNAS 2022), and a review Drlica Expert Rev Anti-infect Therapy 2021). The present citations are fine if you want to narrow the statement to mycobacteria, but the history is that the E. coli work came first and was then generalized to mycobacteria. A mycobacterial paper for ROS is Shee 2022 AAC.

We thank the reviewer for noticing that we inadvertently omitted several important E. coli-related references. These have been added.

Line 75 and 76: Conversely ... unresolved. Compelling arguments have been made that show major flaws in the two papers cited, and a large body of evidence has now accumulated showing the validity of the idea promoted by the Collins lab, beginning with Kohanski 2007. In addition to many papers by Collins, see Hong 2019 PNAS and Zeng 2022 PNAS). It is fine if you want to counter the arguments against the Lewis and Imlay papers (summarized in Drlica & Zhao 2021 Expert Rev Anti-infect Therapy), but making a blanket statement suggests that the authors are unfamiliar with the literature.

We agree with the reviewer that the weight of the evidence supports a role for antibiotic-induced ROS as an important mechanism for antibiotic lethality under many (though not all) conditions. We have revised the text to better reflect this nuance.

Line 78. Advantages over what?

Text modified

Line 80 exposure: to finish the logic you need to show that E. coli and S. aureus persisters fail to do this.

We thank the reviewer for their suggestion but studying these other organisms is outside the scope of this study. 

Line 82 whereas: this misdirects the reader. It would seem that a simple "and" is better

Text modified

Line 89 I think this paragraph is about the need to study Mabs, the subject of the present report. This paragraph could use a more appropriate topic sentence to guide the reader so that no guessing is involved. I suggest rephrasing this paragraph to make the case for studying more compelling.

Text modified

Line 96. I suggest citing several references after subinhibitory concentration of antibiotic.

The references are in the following sentence alongside the key observations.

Line 99. Genetic analysis: how does this phrase fit with the idea of persister cells arising stochastically?

There are two issues: 1) We would argue that persister formation is not completely stochastic, but rather a probability that can be modified both genetically and by environment (for example hipA PMID: 6348026). 2) Even if persister formation were totally stochastic, the survival of these cells may depend on specific genes – as we indeed find in our Tn-Seq analysis of Mabs.  

Line 106. In this paragraph you need to define persister. The consensus definition (Balaban 2019 Nat Micro Rev) is a subpopulation of tolerant cells. Tolerance is defined as the slowing or absence of killing while an antibiotic retains its ability to block growth. See Zeng 2022 PNAS for example with rapidly growing cells. Phenotypic tolerance is the absence of killing due to environmental perturbations, most notably nutrient starvation, dormancy, and growth to stationary phase. By extension, phenotypic persistence would be subpopulation status of a phenotypically tolerant cells. If you have a different definition, it is important to state it and emphasize that you disagree with the consensus statement.

Text modified  

Line 109 unexpectedly. I would delete this word, because the literature leads the reader to expect this result unless you make a clear case for Mabs being fundamentally different from other bacteria with respect to how antibiotics kill bacteria (this is unlikely, see Shee 2022 AAC). Indeed, lines 111-113 state extensions of E. coli work, although suppression of ROS in phenotypic tolerance and genetic persistence have not been demonstrated.

Text modified

Line 124 you might add, in parentheses and with references, that a property of persisters is crosspersistence to multiple antibiotic classes. This is also true for tolerance, both genetic and phenotypic. An addition will support your approach.

Text modified

Line 128 minimal

Text not modified. We appreciate the reviewer’s preference but both “minimal” and “minimum” are both widely accepted terms. Indeed, the Balaban et al 2019 consensus statement on definitions cited by the author above also uses “minimum” (PMID: 30980069), as do IDSA clinical guidelines (PMID: 39108079).

Line 130 is MIC somehow connected to killing or did you also measure killing? Note that blocking growth and killing cells are mechanistically distinct phenomena, although they are related. By being upstream from killing, blockage of growth will also interfere with killing.

Text modified

Line 133 PBS is undefined

Text modified

Line 134 increase in persisters ... you need to establish that these are not phenotypically tolerant cells. Do they constitute the entire population (tolerance)? Your data would be more indicative of persisters if you saw a distinct plateau with the PBS samples, as such data are often used to document persistence (retardation of killing is a property of tolerance, Balaban 2019). Fig. 1B is clearly phenotypic tolerance, as the entire population grows. Your data suggest that you are not measuring persistence as defined in the literature (Balaban 2019). Line 139 persister should be tolerance •

Text modified

Lines 142, 143, 144. 159, 163, 171, 181, 211, 226, 238, 246, 277, 279,289 persistent should be tolerant

Text modified

Line 146 fig 1E Mtb does not show the adaptation phenomenon and it is clearly tolerant, not persistent. This should be pointed out. As stated, you may be misleading the reader.

Text modified  

*Line 169. Please make it clear whether these genes are affecting antibiotic susceptibility (MIC will affect killing because blocking growth is upstream) or if you are dealing with tolerance (no change in MIC). These measurements are essential and should included as a table. By antibiotic response, do you mean that antibiotics change expression levels?

Regarding MICs, the data for MICs in control and katG mutant are presented in Figure 4C and 4F. Regarding ‘response’ we have clarified the text of this sentence.

Line 174 Interestingly should be as expected

Text not modified; tetracyclines do not induce ROS in E. coli and oxazolidinones have not been studied in this regard.

Line 183 you need to include citations. You can cite the ability of chloramphenicol to block ROS-mediated killing of E. coli. That allows you to use the word unexpected

Text modified

Line 199. All of the data in Fig. 3 shows tolerance, not persistence, requiring word changes in this paragraph.

Text modified

Line 226. The MIC experiment is important. You can add that this result solidifies the idea that blocking growth and killing cells are distinct phenomena. You can cite Shee 2022 AAC for a mycobacterial paper

Text modified

Line 241. The result with levofloxacin is unexpected, because the fluoroquinolones are widely reported to induce ROS, even with mycobacteria (see Shee 2022 AAC). You need to point this out and perhaps redo the experiment to make sure it is correct.

We appreciate the reviewer’s interest in this question. All experiments in this paper were repeated multiple times. This particular experiment was repeated 3 times and in all replicates the katG mutant was sensitized to translation inhibitors but not levofloxacin. Shee et al examined Mtb treated with moxifloxacin and found ROS generation, but did not assess whether a Mtb katG mutant had impaired survival. Thus, in addition to differences in: i) the species studied and ii) the particular fluoroquinolone used, the two sets of experiments were designed to address different questions (ROS accumulation vs protection by katG) . A cell might accumulate ROS without a katG mutant having impaired survival if genetic redundancy exists – a result we indeed see in our clinical Mabs strains under some conditions (new data included in revised Figure 6A).  

Line 269 Additional controls would bolster the conclusion: use of an antioxidant such as thiourea and an iron chelator (dipyridyl) both should reduce ROS effects.

New experiments performed, revised Figure 5.

Line 276 the word no is singular

Text modified

Line 284 this suggested ... in fact previous work suggested. This summary paragraph might go better as the first paragraph of the Discussion

Text modified to specify that this is in reference to the work in this manuscript

Lines 294-299 Most of this is redundant and should be deleted.

Text modified

Line 299 this species is vague

Text modified

Line 310 Do you want to discuss spoT?

Text not modified

Line 313 paragraph is largely redundant

Text modified

Line 314 controversial. As above, I would delete this, especially since it is not referenced and is unlikely to be true. If you believe it, you have the obligation to show why the ROS-lethality idea is untrue. If you are referring to Lewis and Imlay, there were almost a dozen supporting papers before 2013 and many after. This statement does not make the present work more important, so deletion costs you nothing.

Text modified

Line 314 direct disruption of targets. This is clearly not a general principle, because the quinolones rapidly kill while inhibition of gyrase by temperature-sensitive mutations does not (Kreuzer 1979 J.Bact; Steck 1985). Indeed, formation of drug-gyrase-DNA complexes is reversible: death is not.

Text modified

Line 318 as pointed out above, you have not brought this story up to date. The two papers mainly focused on Kohanski 2007, ignoring other available evidence.’’

Text modified

Line 326 you need to cite Shee 2022 AAC

Text modified

Line 342 the idea of mutants being protective is not novel, as several have been reported with E. coli studies. Thus, there is a general principle involved.

We agree that this suggests a potential general principle

Line 344. It depends on the inhibitor. For example, aminoglycosides are translation inhibitors and they also cause the accumulation of ROS.

We agree that ROS generation depends on the inhibitor, and indeed upon other variables including drug concentration, growth conditions, and bacterial species as well.  

Line 347. You need to point out the considerable data showing that the absence of catalase increases killing

Text modified

Line 363 look at Shee 2022 AAC and Jacobs 2021 AAC

Text modified, reference added.

Line 585 I suggest having a colleague provide critical comments on the manuscript and acknowledge that person.

Text not modified

iter(tag=None) が正しいような気がします。

https://docs.python.org/ja/3/library/xml.etree.elementtree.html#xml.etree.ElementTree.Element.iter

Author response:

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

Reviewer #1 (Public review):

Summary:

Pavel et al. analyzed a cohort of atrial fibrillation (AF) patients from the University of Illinois at Chicago, identifying TTN truncating variants (TTNtvs) and TTN missense variants (TTNmvs). They reported a rare TTN missense variant (T32756I) associated with adverse clinical outcomes in AF patients. To investigate its functional significance, the authors modeled the TTN-T32756I variant using human induced pluripotent stem cell-derived atrial cardiomyocytes (iPSC-aCMs). They demonstrated that mutant cells exhibit aberrant contractility, increased activity of the cardiac potassium channel KCNQ1 (Kv7.1), and dysregulated calcium homeostasis. Interestingly, these effects occurred without compromising sarcomeric integrity. The study further identified increased binding of the titin-binding protein Four-and-a-Half Lim domains 2 (FHL2) with KCNQ1 and its modulatory subunit KCNE1 in the TTN-T32756I iPSCaCMs.

Strengths:

This work has translational potential, suggesting that targeting KCNQ1 or FHL2 could represent a novel therapeutic strategy for improving cardiac function. The findings may also have broader implications for treating patients with rare, disease-causing variants in sarcomeric proteins and underscore the importance of integrating genomic analysis with experimental evidence to advance AF research and precision medicine.

Weaknesses

(1) Variant Identification: It is unclear how the TTN missense variant (T32756I) was identified using REVEL, as none of the patients' parents reportedly carried the mutation or exhibited AF symptoms. Are there other TTN variants identified in the three patients carrying TTN-T32756I? Clarification on this point is necessary.  

We thank the reviewer for their insightful comment. We have now clarified these in the method section.

Line 484-491: “The TTN-T32756I variant (REVEL Score: 0.58758, Supplementary Table 1) was prioritized due to its occurrence in multiple unrelated individuals within our clinical AF cohort, despite no reported family history of AF in affected individuals. While no parental inheritance was observed, the possibility of de novo origin cannot be excluded. Furthermore, this variant is located within a region overlapping a deletion mutation recently shown to cause AF in a zebrafish model, supporting its potential pathogenicity [37]. Notably, the affected individuals did not carry additional loss-of-function TTN variants.”

(2) Patient-Specific iPSC Lines: Since the TTN-T32756I variant was modeled using only one healthy iPSC line, it is unclear whether patient-specific iPSC-derived atrial cardiomyocytes would exhibit similar AF-related phenotypes. This limitation should be addressed.

We have now acknowledged this limitation in the revised manuscript.

Line 505-509: “Due to the patients' unavailability of peripheral blood mononuclear cells (PBMCs), we utilized a healthy iPSC line and introduced the TTN-T32756I variant using CRISPR/Cas9 genome editing. This approach ensures an isogenic background, thereby minimizing genetic variability and providing a controlled system to study the direct effects of the mutation.”

(3) Hypertension as a Confounding Factor: The three patients carrying TTN-T32756I also have hypertension. Could the hypertension associated with this variant contribute secondarily to AF? The authors should discuss or rule out this possibility.

We have now explicitly discussed this in the revised manuscript.

Line 362-367: “Hypertension is a common comorbidity in patients with AF and could contribute to disease progression. However, all three individuals carrying TTN-T32756I exhibited earlyonset AF (onset before 66 years), with one case occurring as early as 36 years. This suggests a potential two-hit mechanism, where genetic predisposition and comorbidities influence disease risk. Importantly, our iPSC model isolates the genetic effects of TTN-T32756I from other factors, supporting a direct pathogenic role.”

(4) FHL2 and KCNQ1-KCNE1 Interaction: Immunostaining data demonstrating the colocalization of FHL2 with the KCNQ1-KCNE1 (MinK) complex in TTN-T32756I iPSC-aCMs are needed to strengthen the mechanistic findings.

We thank the reviewer for this insightful suggestion. We agree that additional immunostaining data would further strengthen the evidence for FHL2 colocalization with the KCNQ1-KCNE1 complex in TTN-T32756I iPSC-aCMs. In line with this, we have expanded our analysis to include both co-immunoprecipitation and confocal microscopy.  As described in the revised manuscript (Lines 282–287), the colocalization between KCNE1 and FHL2 was increased by approximately threefold in TTN-T32756I iPSC-aCMs compared with WT, supporting an enhanced interaction between these proteins (Figure 5A, Supplementary Figure 6). We are generating additional immunostaining data to validate and extend these findings, and we will incorporate them into the revised submission to further substantiate the mechanistic link proposed.

Line 282-287: “…..if TTN-T32756I increases I_ks by modulating the interaction between KCNQ1KCNE1 and FHL2, we performed co-immunoprecipitation studies and confocal microscopy in both WT and TTN-T32756I-iPSC-aCMs. The co-localization between KCNE1 and FHL2 increased ~3 fold in TTN-T32756I-iPSC-aCMs, suggesting an increased interaction between them (Figure 5A, Supplementary Figure 7).”

(5) Functional Characterization of FHL2-KCNQ1-KCNE1 Interaction: To further validate the proposed mechanism, additional functional assays are necessary to characterize the interaction between FHL2 and the KCNQ1-KCNE1 complex in TTN-T32756I iPSC-aCMs.

We thank the reviewer for this valuable suggestion. We agree that additional functional assays would provide further validation of the proposed mechanism. However, we believe such in-depth characterization warrants a dedicated follow-up study and is beyond the scope of the current revision. In this work, our primary objective is to establish that the TTN missense variant can exert a detrimental effect and serve as a substrate for AF. 

Line 418-419: “Further study is needed to validate the proposed mechanism and determine if TTNmvs in other regions are associated with AF by a similar process.”

Reviewer #2 (Public review):

Summary:

The authors present data from a single-center cohort of African-American and Hispanic/Latinx individuals with atrial fibrillation (AF). This study provides insight into the incidences and clinical impact of missense variants in this population in the Titin (TTN) gene. In addition, the authors identified a single amino acid TTN missense variant (TTN-T32756I) that was further studied using human induced pluripotent stem cell-derived atrial cardiomyocytes (iPSC-aCMs). These studies demonstrated that the Four-and-a-Half Lim domains 2 (FHL2) has increased binding with KCNQ1 and its modulatory subunit KCNE1 in the TTN-T32756I-iPSCaCMs, enhancing the slow delayed rectifier potassium current (Iks) and is a potential mechanism for atrial fibrillation. Finally, the authors demonstrate that suppression of FHL2 could normalize the Iks current.

Strengths:

The strengths of this manuscript/study are listed below:

(1) This study includes a previously underrepresented population in the study of the genetic and mechanistic basis of AF.

(2) The authors utilize current state-of-the-art methods to investigate the pathogenicity of a specific TTN missense variant identified in this underrepresented patient population.

(3) The findings of this study identify a potential therapeutic for treating atrial fibrillation.

Weaknesses:

(1) The authors do not include a non-AF group when evaluating the incidence and clinical significance of TTN missense variants in AF patients.

We appreciate the reviewer’s comment and acknowledge the limitation of not including a non-AF control group in our clinical analysis. As noted in the revised manuscript (Lines 347–353), our cohort was derived from a single-center registry of individuals with AF and therefore lacks a matched non-AF control population for direct comparison of TTN missense variant incidence. We agree that future studies incorporating larger, multiethnic validation cohorts with both AF and non-AF individuals, as well as evaluating AF-specific measures such as arrhythmia burden and treatment response, will be essential to fully elucidate the clinical significance of TTN missense variants in AF.

Line 347-353: “Our cohort is derived from a single-center multi-ethnic registry of individuals with AF and lacks a matched cohort of non-AF controls to compare the incidence of TTN missense variants.  Further study exploring these associations in mult-ethnic, larger validation cohorts that include both AF and non-AF individuals and examining AF-specific measures such as arrhythmia burden or treatment response will be necessary to fully understand the clinical importance of TTNmvs in AF.”

(2) The authors do not provide evidence that TTN-T32756I-iPSC-aCMs are arrhythmogenic, only that there is an increase in the Iks current and associated action potential changes. More specifically, the authors report that "compared to the WT, TTN-T32756I-iPSC-aCMs exhibited increased arrhythmic frequency," yet it is unclear what they are referring to by "arrhythmic frequency."

We thank the reviewer for this important point and for highlighting the need for clarification. In our study, the term “arrhythmic frequency” was intended to describe the increased spontaneous beating rate, irregular action potential patterns, and abnormal calcium handling observed in TTN-T32756I iPSC-aCMs compared with WT. These findings support the concept that the AF-associated TTN-T32756I variant promotes ion channel remodeling and perturbs excitation–contraction coupling, thereby creating a potential arrhythmogenic substrate for AF. To avoid ambiguity, we have removed the term “arrhythmic frequency” and revised the text for clarity and precision (Lines 222–223).

Lines 222-223: “Compared to the WT, TTN-T32756I-iPSC-aCMs exhibited increased frequency along with a significant reduction of the time to 50% and 90% decline of calcium transients (Figure 3G-I, Supplementary Figure 4F).”

(3) There seem to be discrepancies regarding the impact of the TTN-T32756I variant on mechanical function. Specifically, the authors report "both reduced contraction and abnormal relaxation in TTN-T32756I-iPSC-aCMs" yet, separately report "the contraction amplitude of the mutant was also increased . . . suggesting an increased contractile force by the TTN-T32756IiPSC-aCMs and TTN-T32756I-iPSC-CMs exhibited similar calcium transient amplitudes as the WT."

We thank the reviewer for highlighting this critical point and apologize for the lack of clarity. We intended to distinguish between changes in contractile force and contractile dynamics. Specifically, the increased contraction amplitude observed in TTN-T32756I iPSCaCMs reflects enhanced contractile force, whereas the reduced contraction duration and impaired relaxation reflect abnormalities in contractile kinetics. Together, these findings indicate that the TTN-T32756I variant alters both the strength and the temporal dynamics of contraction, consistent with dysfunctional mechanical performance. We have revised the text accordingly to more accurately convey these results (Lines 187–192).

Lines 187-192: “Compared to WT, the beating frequency of the TTN-T32756I-iPSC-aCMs was significantly increased (52 ± 7.8 vs. 98 ± 7.5 beats per min, P=0.001; Figure 2C) coupled with the reduction of the contraction duration (456.5 ± 61.45 vs 262.9 ± 48.16 msec, P=0.032; Figure 2D), the peak-to-peak time (1529 ± 195.5 vs 636.6 ± 135.8 msec, P=0.004; Supplementary Figure 3B),  and the relaxation (281.5 ± 42.95 vs 79.40 ± 21.14 msec, P=0.003; Supplementary Figure 3A).”

Reviewer #3 (Public review):

Summary:

The authors describe the abnormal contractile function and cellular electrophysiology in an iPSC model of atrial myocytes with a titin missense variant. They provide contractility data by sarcomere length imaging, calcium imaging, and voltage clamp of the repolarizing current iKs. While each of the findings is interesting, the paper comes across as too descriptive because there is no data merging to support a cohesive mechanistic story/statement, especially from the electrophysiological standpoint. There is not enough support for the title "A Titin Missense Variant Causes Atrial Fibrillation", since there is no strong causative evidence. There is some interesting clinical data regarding the variant of interest and its association with HF hospitalization, which may lead to future important discoveries regarding atrial fibrillation.

Strengths:

The manuscript is well written, and a wide range of experimental techniques are used to probe this atrial fibrillation model.

Weaknesses

(1) While the clinical data is interesting, it is essential to rule out heart failure with preserved EF as a confounder. HFpEF leads to AF due to increased atrial remodeling, so the fact that patients with this missense variant have increased HF hospitalizations does not necessarily directly support the variant as causative of AF. It could be that the variant is associated directly with HFpEF instead, and this needs to be addressed and corrected in the analyses.

We appreciate the reviewer’s insightful comment and agree that HFpEF-related atrial remodeling could represent a potential confounder in the association between TTN missense variants and AF. The primary aim of our clinical analysis was to assess the potential significance of TTNmv in AF, recognizing the inherent limitations of retrospective observational data in establishing causality. To complement this, our in vitro studies were specifically designed to demonstrate that TTNmv can alter the electrophysiological substrate, thereby predisposing to AF independent of clinical comorbidities.

While HFpEF is an important consideration, to our knowledge, no existing literature directly implicates TTNmv in HFpEF pathogenesis. In contrast, loss-of-function TTN variants are more commonly associated with HFrEF and dilated cardiomyopathy, and even these associations remain an area of active debate. To address potential confounding in our cohort, we adjusted for reduced ejection fraction in multivariable analyses of clinical outcomes. Additionally, we performed a sensitivity analysis excluding patients with nonischemic dilated cardiomyopathy (Supplementary Table 6). Together, these approaches mitigate the potential impact of heart failure subtypes on our findings, while our mechanistic studies strengthen the argument that TTNmv may contribute directly to AF susceptibility.

(2) All contractility and electrophysiologic data should be done with pacing at the same rate in both control and missense variant groups, to control for the effect of cycle length on APD and calcium loading. A shorter APD cannot be claimed when the firing rate of one set of cells is much faster than the other, since shorter APD is to be expected with a quicker rate. Similarly, contractility is affected by diastolic interval because of the influence of SR calcium content on the myocyte power stroke. So the cells need to be paced at the same rate in the IonOptix for any direct comparison of contractility. The authors should familiarize themselves with the concept of electrical restitution.

We thank the reviewer for this crucial technical comment. iPSC-derived cardiomyocytes (iPSC-CMs) are known to exhibit spontaneous automaticity due to the presence of pacemaker-like currents and reduced I_K1, which enables interrogation of their intrinsic electrophysiological properties and disease-relevant remodeling. In our study, we leveraged this feature to test the hypothesis that TTN missense variants alter electrophysiological properties through ion channel remodeling. That said, we fully agree with the reviewer that pacing iPSCCMs at a controlled cycle length is essential for minimizing rate-dependent effects on APD, calcium handling, and contractility, and would improve the interpretability of group comparisons. While iPSC-CMs with matched genetic backgrounds are expected to display broadly comparable electrophysiological profiles, biological and technical variability can influence spontaneous beating rates, thereby confounding direct comparisons. To address this, we have incorporated pacing protocols into our revised experimental design to ensure that APD and contractility measurements are obtained under identical cycle lengths, consistent with the concept of electrical restitution.

(3) It is interesting that the firing rate of the myocytes is faster with the missense variant. This should lead to a hypothesis and investigation of abnormal automaticity or triggered activity, which may also explain the increased contractility since all these mechanisms are related to the SR's calcium clock and calcium loading. See #2 above for suggestions on how to probe calcium handling adequately. Such an investigation into impulse initiation mechanisms would be compelling in supporting the primary statement of the paper since these are actual mechanisms thought to cause AF.

We thank the reviewer for this insightful suggestion. We agree that the faster firing rate observed in TTN-T32756I iPSC-aCMs raises the possibility of abnormal automaticity or triggered activity, both of which are highly relevant to AF pathophysiology. As these mechanisms are tightly coupled to calcium handling and the SR calcium clock, further probing of calcium cycling abnormalities would provide valuable mechanistic insights. While this level of investigation is beyond the scope of the current study, we view it as a compelling future direction that could directly link TTN missense variants to impulse initiation abnormalities contributing to AF. 

(4) The claim of shortened APD without correcting for cycle length is problematic. However, linking shortened APD in isolated cells alone to AF causation is more complicated. To have a setup for reentry, there must be a gradient of APD from short to long, and this can only be demonstrated at the tissue level, not at the cellular level, so reentry should not be invoked here. If shortened APD is demonstrated with correction of the cycle length problem, restitution curves can be made showing APD shortening at different cycle lengths. If restitution is abnormal (i.e. the APD does not shorten normally in relation to the diastolic interval), this may lead to triggered activity which is an arrhythmogenic mechanism. This would also tie in well with the finding of abnormally elevated iKs current since iKs is a repolarizing current directly responsible for restitution.

We thank the reviewer for this necessary clarification. We agree that isolated cell studies cannot directly demonstrate reentrant circuits and that reentry should not be inferred solely from cellular APD data. Our observation of shortened APD and abnormal beating patterns in TTN-T32756I iPSC-aCMs suggests ion channel remodeling that may predispose to arrhythmogenic conditions. Still, we recognize that tissue-level gradients of APD are required to establish reentry as a mechanism. Accordingly, we have removed mention of “the reentrant mechanism” from the revised manuscript and limited our interpretation to the cellular findings. Future studies incorporating pacing protocols and restitution curve analyses will be valuable in determining whether abnormal APD restitution and elevated I_Ks contribute to triggered activity, thereby providing a more direct mechanistic link to AF (Lines 101–105).

Lines 101-105: “Our study showed that the TTN-T32756I iPSC-aCMs exhibited a striking AF-like EP phenotype in vitro, and transcriptomic analyses revealed that the TTNmv increases the activity of the FHL2, which then modulates the slow delayed rectifier potassium current (I_Ks) to cause AF.” 

Reviewer #1 (Recommendations for the authors):

Electrophysiological Phenotype in Ventricular CMs: Has the iPSC line carrying TTN-T32756I been differentiated into ventricular cardiomyocytes (iPSC-vCMs)? The reported cellular phenotype in iPSC-aCMs does not seem to specifically reflect an AF phenotype. Does the variant produce similar electrophysiological alterations in iPSC-vCMs?

We thank the reviewer for this thoughtful comment. To date, we have not differentiated the TTN-T32756I iPSC line into ventricular cardiomyocytes (iPSC-vCMs). Our current work focuses on iPSC-aCMs, where we demonstrate that the AF-associated TTNT32756I variant induces ion channel remodeling and abnormal beating patterns, thereby creating a potential arrhythmogenic substrate relevant to AF. We agree that investigating whether this variant produces similar or distinct electrophysiological alterations in iPSC-vCMs would provide essential insights into chamber-specific effects and broaden our mechanistic understanding. We have acknowledged this as a future direction in the revised manuscript (Lines 422–425).

Lines 422-425: “While we have not yet explored the effect of TTN-T32756I in iPSC-derived ventricular cardiomyocytes, it would be interesting to investigate whether this variant produces similar or distinct electrophysiological alterations in the ventricular cardiomyocytes.”

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

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Reply to the reviewers

This is a reply/revision plan, not definitive. Planned and already implemented revisions are underlined.

First of all, we wish to express our gratitude to the reviewers: they helped to improve the paper.

Reviewer #1:* **

Reviewer #1 wrote: Major Comments: 1.Differential gene/pathway analysis across epithelial clusters: What are the differential genes or pathways among the epithelial clusters? Without CCA/Harmony integration, do the tumor subgroups show distinct differences? In addition, I suggest applying NMF or hdWGCNA to identify shared modules and test whether ATC and PTC harbor overlapping regulatory modules.

*

Reply plan: Both reviewers suggested some regulatory network analysis. We proposed to run SCENIC+ (Nature Methods, 2023, https://doi.org/10.1038/s41592-023-01938-4) on our data__.__

* Reviewer #1 wrote: 2.Validation of TSHR/TPO-based subgrouping: While the TSHR/TPO grouping appears appropriate for stratification at the single-cell level, it is necessary to exclude sequencing depth as a confounding factor. Should validate the existence of these subpopulations using mIHC/IF on corresponding samples. *

__Reply plan: __We made claims about RNA expression, not protein expression. Thus, validation should be at the RNA level:

• We already replicated part of our analysis on the dataset published by Lu et al. (JCI 2023, https://doi.org/10.1172/JCI169653), see Figs. 3 and 4. This effort will be extended to all single cell analysis results from our study in the revised paper.
• We will also present plots demonstrating that the sequencing depth is similar in the different cancer cell subgroups-further excluding it as a confounding factor. Reviewer #1 wrote: *3.Impact of mutational differences on conclusions: According to Supplementary Table 1, almost all PTC cases carried BRAF mutations, whereas four ATC patients harbored no BRAF mutation. Could this difference influence the conclusions of the study? Although the authors briefly mention this in the Discussion, a more thorough clarification is warranted. *

Reply plan: The dataset of Lu et al. includes BRAF-mutated ATCs along with BRAF-mutated PTCs. Therefore, the replication mentioned earlier will also address those concerns. In fact, Fig. 4E-I already confirm in Lu et al. data the ordered loss of markers. Replication will be extended to other results of the study and be more emphasized in the paper.

* Reviewer #1 wrote: 4. The statement "Myeloid and T cells also grouped in specific clusters" seems descriptive. Is this clustering biologically meaningful? Please elaborate.

*

__Reply plan: __This is an important point, and accordingly, a cell mixing experiment was specifically designed to sort apart technical effects from biological effects. We therefore know with certainty that the myeloid and T cell patients-specific clusters are the result of biological variation (Fig. 1). We further demonstrate that part of this variation is associated with hypoxia (Supp. Fig 4). So yes, the clustering is biologically meaningful.

* Reviewer #1 wrote: Minor Comments: In Figure 2C, the "Epith TSHR-" population resembles myeloid cells. Could the authors clarify why this is the case? For the correlation analysis in Figure 2C, were highly variable genes or all genes used?

*

Reply plan: There is a simple explanation: The Epith TSHR- population the reviewer is referring to are cells from anaplastic thyroid cancers (ATC), which are tumors notoriously infiltrated by macrophages (Supp. Fig. 4). A high correlation of Epith TSHR- and macrophages proportion across our panel of ATC and papillary cancer (PTC) is therefore expected. Among other things, Fig. 2C shows that high correlation, but it is not meant to and does not show that Epith TSHR- and macrophages "resemble" one another. It shows that their proportions are highly positively correlated. This correlation analysis does not rely on gene expression but on cell type proportions. It measures co-occurrence rather than resemblance. The text has been clarified in order to prevent any confusion.

• *

* __Reviewer #2: __

Reviewer #2 wrote: 1. This study largely confirms established facts that 1) PTC due to BRAF driver mutation is a heterogeneous tumour entity and 2) ATC is the most dedifferentiated of all thyroid cancers. Although interesting, observations of a highly variable tissue cell composition including immune cells and the gradual loss of thyroid differentiation markers, in part linked to tumor subclone development featured by altered chromosomal copy numbers, are thus not surprising.

*

__Reply plan: __We wish to respectfully express our take on this perception of the work:

• There is a difference between conjecturing a high heterogeneity in the cell composition of thyroid cancers and establishing it with the level of accuracy and quantitative rigor our analysis provides. The extreme amplitude of that variation was surprising to us: the size of the microenvironment makes from 8.4 to 80% of the cells in PTCs driven by the same BRAF mutation.
• We don't simply show that a subclone characterized by a large number of copy number events is less differentiated. We go all the way proving that those copy number alterations are associated with specific cell states that produce specific histology (Fig. 5). It required a combination of single cell transcriptomics, spatial transcriptomics and sophisticated computational analysis to establish that connection between genomic changes and histology. The fragmentation of epithelial sheets uncovered from CNV analysis had escaped the attention of pathologist colleagues and ours at first, this is not a parameter typically assessed in diagnostic, to our knowledge.
• We don't simply show that there is a gradual loss of differentiation markers: this loss is ordered in a very specific way that mirrors the gain of markers during thyroid organoid differentiation. * Reviewer #2 wrote: 2. Considering tumor progression, comparison of PTC and ATC should preferably include specimens with the same driver mutation (BRAF or RAS), which is not the case here. This notion should be more clearly explained to readers. An optional improvement would be to conduct similar analyses on an ATC specimen that contains more differentiated PTC tumor portions arguably suggesting that PTC progresses to ATC (by mechanisms that are still largely unexplored).

*

__Reply plan: __This is clearly a limitation of our study. As already proposed in our reply to reviewer number one, we will extend to all our single cell results the replication of our analysis in the dataset of Lu e al., which includes ATCs and PTCs harboring the BRAF-mutation.

* Reviewer #2 wrote: 3. Comments on findings of lymphocytic infiltration need to be balanced. Although autoimmune thyroid disease in infered a risk factor of developing malignancy it is unlikely that the majority of TCGA samples of PTC is associated with thyroiditis as indicated in Fig. 3 and Suppl Fig. 3. Immune cell abundance may rather reflect the tumor immune microenvironment (TIME).

*

__Reply plan: __The figure the reviewer is referring to demonstrates that PTC occurring in a background of thyroiditis also has a higher proportion of B cells. We did not claim, and the figure did not show, that "the majority of TCGA samples of PTC is associated with thyroiditis", because they don't. This point has been clarified.

* Reviewer #2 wrote: 4. Some tissue sections seem of quite poor quality either shape-wise of containing rifts e.g. PTC7 in Fig. 3 and PTC2 in Fig. 5. The authors should explain whether and how this might influence analysis.

*

__Reply plan: __Spatial transcriptomics is typically performed on frozen sections. Frozen sections, which are obviously of lower visual quality than slice from FFPE preserved samples. Since no computational analyses were performed on the image, this lower quality has no impact on our results. Regarding RNA quality, the RINs were >7 for all tumors. RINs are now presented in Supp table S1.

Reviewer #2 wrote: The experiment on mouse ESC/organoids (Fig. 6H-J) does not show much of an expected enhanced thyroid progenitor cell proliferation after induction of the mutant Braf allele by tamoxifen, which raises doupt whether the subsequent promoted growth by fibronectin at all is oncogene-related. This differs from the impact of BrafCA activation along with mouse thyroid development in vivo (Schoultz et al iScience 2023 PMID: 37534159). In the same experimental setup, it appears that mutant Braf prevents follicle formation (Fig. 6I). A control experiment investigating the influence of fibronectin in the absence of oncogene activation should be conclusive. The effect of Braf and fibronectin on thyroid organoid structure and function should be better explained, if necessary based on complementary experiments, and discussed in relation to the claimed association of fibronectin expression to "...low amounts of thyroid differentiation markers...) and "...loss of epithelial structure (PTC7, Figure 6E)." in the previous section of Results.

__Reply plan: __The induction of the mutant Braf allele for 7 days increases the percentage of BrdU+ cells by 1.43 fold (p-value for Wilcoxon test = 0.035). The effects observed by Schoultz et al. are certainly more dramatic, but they result from an oncogenic activity spanning 1 to 6 months (4 to 26 times longer) in an in vivo model. Most importantly, oncogenic activity is initiated in Nkx2.1+ cells and not Tg+ cells, thus much earlier during development. These two models are thus not comparable. As for the effects of fibronectin on thyroid structure, we do not claim that our organoid model recapitulates the complex interactions between cancer cells and their microenvironment that shapes tissue morphology in vivo. This is now clarified in the text.

We presented controls with no oncogene expression and no Fn1, controls with oncogene induction and no FN1 and organoids with oncogene induction and Fn1 treatment. This alone establishes the effect of Fn1 on induced organoids, which was our goal. We regard it as a novel and interesting but non-essential development in our paper.

As the reviewer points out, while our results show an increased proliferation in Braf-mutated organoids treated with Fn1, they do not allow us to conclude on any potential interaction between Fn1 and the oncogenic process. The suggested experiment with Fn1 in absence of oncogene activation would add information, but we cannot follow up for practical lab management reasons detailed in Section 4 below.

* Reviewer #2 wrote: 6. Concerning EMT profiling (Supplementary Fig. 7B) , there is a great similarity of ATC tumor cells and fibroblasts, and as stated in the text the malignant status of the former is indicated by chromosomal aberrations (refering to Suppl fig. 6). However, looking at Suppl. Fig. 7B it is evident that fractions of cells identified as fibroblasts express TG and TSHR suggesting mismatch. How was this comparison done in order to exclude mismatch? Is there no other profiled markers that distinguish cancer cells from stromal cells that can support conclusions?*

Reply plan: TG-a thyrocyte marker-seems expressed by fibroblasts in Supplementary Figure 7B. The reviewer suggests this could be caused by an incomplete distinction between bona fide fibroblasts and thyrocytes in advanced EMT state. We argue that

• Ambient TG RNA leaking out of thyrocytes nuclei contaminates the transcriptomes of all cell types. It is a well-known technical problem, with dedicated software packages to mitigate it. We preprocessed our data with one of them, SoupX, which corrected for most, but not all, ambient RNA contamination.
• The plot below shows that there is nothing special about fibroblasts in that respect. For example, B and T cells are contaminated by TG at levels comparable to fibroblasts, endothelial cells and pericyte to higher levels.
• In addition, the UMAP of Fig. 2A shows that EMT cells and fibroblast form very distinct clusters. Furthermore, the fibroblast cluster but not the two EMT clusters contain cells from PTC, and the PTC cluster do not contain cells with DNA copy number aberration. Thus, although both EMT cells and fibroblasts express the typical mesenchymal marker of Supplementary Fig. 7B, they are easy to distinguish on the basis of their overall transcriptomes.
• The panel below has been added to the Supplementary Figure 7B. [Panel cannot be displayed here]

Reviewer #2 wrote: *In the same figure, it appears there are no clear differences in EMT marker expression among PTC samples regardless of differentiation state, suggesting that the gradual loss of thyroid differentiation in PTC tumor cells and EMT are not parallel and potentially linked phenomena? Please clarify this dissociation of results. Is possible that refocusing on other EMT markers than the top 10, of which almost all concerns various collagen genes, might better reveal partial EMT in PTCs?

*

__Reply plan: __The technical basis of this comment is related to the previous point. Our perception is that the mesenchymal markers in Supplementary Fig. 7B show a binary effect, i.e. strong expression in ATC and no expression in PTC (beyond ambient RNA noise)-not a gradual effect. Thus, there is no correlation of COL1A1 and other mesenchymal markers with dedifferentiation in PTC as these markers are not expressed beyond the noise level of the experiments. A lot has been written about EMT in PTC, but one of the findings of our study is that while ATC undergo full EMT, EMT in PTC is very limited. PTC express FN1 but no other major mesenchymal markers such as collagens I and III, for example.

• *

Reviewer #2 wrote: *7. According to Suppl. Table 1, the ATC2 tumor does not harbor any mutations. What about chromosomal aberrations, was that included in analysis? Considering previous consistent reports of a high mutation burden in ATC, if not supported by other data (clinical, pathological) the diagnosis might be questioned for this particular case included in multiple analyses of the present study.

*

Reply: There is little doubt about the diagnostic of ATC2 by our pathologist collaborators

• The histology of this tumor is strikingly anaplastic, i.e. without structure, as shown in the image below.
• This tumor has a high level of macrophages infiltration typical of ATCs (Supplementary Fig. 4).
• Reviewer #2 wrote: Minor comments: -The logical order of presentation of Results might benefit from first presenting specific PTC data following by ATC dito. I´m thinking of swapping the section of EMT in ATC to end of Results.*

*Reply plan: We miss why the reviewer thinks that way. We believe that discussing the microenvironment, then tumor cells bring conciseness and clarity about how we propose to stratify the latter. By contrast, the suggested tumor type-centered structure entails going back and forth between the microenvironment and tumor cells, diluting the messages about both.

* Reviewer #2 wrote: -Methods paragraph "Mouse ESC-derived thyroid organoids experiments" (starting with "ccc") seems to be missing some essential information.

*Reply plan: A sentence was missing, indeed, and has been re-introduced in the manuscript. We thank the reviewer for catching that error.

Wow ! Franchement, c'est impressionnant à quel point la technologie a évolué. Grâce à cette vidéo, je comprends mieux pourquoi il est important que des personnes "valides" réfléchissent aux problèmes d'accessibilité. Merci pour le partage.

Reviewer #1 (Public review):

Summary:

The NF-kB signaling pathway plays a critical role in the development and survival of conventional alpha beta T cells. Gamma delta T cells are evolutionarily conserved T cells that occupy a unique niche in the host immune system and that develop and function in a manner distinct from conventional alpha beta T cells. Specifically, unlike the case for conventional alpha beta T cells, a large portion of gamma delta T cells acquire functionality during thymic development, after which they emigrate from the thymus and populate a variety of mucosal tissues. Exactly how gamma delta T cells are functionally programmed remains unclear. In this manuscript, Islam et al. use a wide variety of mouse genetic models to examine the influence of the NF-kB signaling pathway on gamma delta T cell development and survival. They find that the inhibitor of kappa B kinase complex (IKK) is critical to the development of gamma delta T1 subsets, but not adaptive/naïve gamma delta T cells. In contrast, IKK-dependent NF-kB activation is required for their long-term survival. They find that caspase 8-deficiency renders gamma delta T cells sensitive to RIPK1-mediated necroptosis, and they conclude that IKK repression of RIPK1 is required for the long-term survival of gamma delta T1 and adaptive/naïve gamma delta T cells subsets. These data will be invaluable in comparing and contrasting the signaling pathways critical for the development/survival of both alpha beta and gamma delta T cells.

The conclusions of the paper are mostly well-supported by the data, but some aspects need to be clarified.

(1) The authors appear to be excluding a significant fraction of the TCRlow gamma delta T cells from their analysis in Figure 1A. Since this population is generally enriched in CD25+ gamma delta T cells, this gating strategy could significantly impact their analysis due to the exclusion of progenitor gamma delta T cell populations.

(2) The overall phenotype of the IKKDeltaTCd2 mice is not described in any great detail. For example, it is not clear if these mice possess altered thymocyte or peripheral T cell populations beyond that of gamma delta T cells. Given that gamma delta T cell development has been demonstrated to be influenced by gamma delta T cells (i.e, trans-conditioning), this information could have aided in the interpretation of the data. Related to this, it would have been helpful if the authors provided a comparison of the frequencies of each of the relevant subsets, in addition to the numbers.

(3) The manner in which the peripheral gamma delta T cell compartment was analyzed is somewhat unclear. The authors appear to have assessed both spleen and lymph node separately. The authors show representative data from only one of these organs (usually the lymph node) and show one analysis of peripheral gamma delta T cell numbers, where they appear to have summed up the individual spleen and lymph node gamma delta T cell counts. Since gamma deltaT17 and gamma deltaT1 are distributed somewhat differently in these compartments (lymph node is enriched in gamma deltaT17, while spleen is enriched in gamma deltaT1), combining these data does not seem warranted. The authors should have provided representative plots for both organs and calculated and analyzed the gamma delta T cell numbers for both organs separately in each of these analyses.

(4) The authors make extensive use of surrogate markers in their analysis. While the markers that they choose are widely used, there is a possibility that the expression of some of these markers may be altered in some of their genetic mutants. This could skew their analysis and conclusions. A better approach would have been to employ either nuclear stains (Tbx21, RORgammaT) or intracellular cytokine staining to definitively identify functional gamma deltaT1 or gamma deltaT17 subsets.

(5) The analysis and conclusion of the data in Figure 3A is not convincing. Because the data are graphed on log scale, the magnitude of the rescue by kinase dead RIPK1 appears somewhat overstated. A rough calculation suggests that in type 1 game delta T cells, there is ~ 99% decrease in gamma delta T cells in the Cre+WT strain and a ~90% decrease in the Cre+KD+ strain. Similarly, it looks as if the numbers for adaptive gamma delta T cells are a 95% decrease and an 85% decrease, respectively. Comparing these data to the data in Figure 5, which clearly show that kinase dead RIPK1 can completely rescue the Caspase 8 phenotype, the conclusion that gamma delta T cells require IKK activity to repress RIPK1-dependent pathways does not appear to be well-supported. In fact, the data seem more in line with a conclusion that IKK has a significant impact on gamma delta T cell survival in the periphery that cannot be fully explained by invoking Caspase8-dependent apoptosis or necroptosis. Indeed, while the authors seem to ultimately come to this latter conclusion in the Discussion, they clearly state in the Abstract that "IKK repression of RIPK1 is required for survival of peripheral but not thymic gamma delta T cells." Clarification of these conclusions and seeming inconsistencies would greatly strengthen the manuscript. With respect to the actual analysis in Figure 3A, it appears that the authors used a succession of non-parametric t-tests here without any correction. It may be helpful to determine if another analysis, such as ANOVA, may be more appropriate.

(6) The conclusion that the alternative pathway is redundant for the development and persistence of the major gamma delta T cell subsets is at odds with a previous report demonstrating that Relb is required for gamma delta T17 development (Powolny-Budnicka, I., et al., Immunity 34: 364-374, 2011). This paper also reported the involvement of RelA in gamma delta T17 development. The present manuscript would be greatly improved by the inclusion of a discussion of these results.

(7) The data in Figures 1C and 3A are somewhat confusing in that while both are from the lymph nodes of IKKdeltaTCD2 mice, the data appear to be quite different (In Figure 3A, the frequency of gamma delta T cells increases and there is a near complete loss of the CD27+ subset. In Figure 1A, the frequency of gamma delta T cells is drastically decreased, and there is only a slight loss of the CD27+ subset.)

Reviewer #3 (Public review):

Summary

The regulation of NF-κB signaling is complex and central to the differentiation and homeostasis of αβT cells, essential to adaptive immunity. γδ T cells are a distinct population that responds to stress/injury-induced cues by producing inflammatory cytokines, representing an important bridge between innate and adaptive immunity. This study from Islam et al. demonstrates that the IKK complex, a central regulator of NF-κB signaling, plays distinct and essential roles in the differentiation and maintenance of γδ T cells. The authors use elegant murine genetic models to generate clear data that disentangle these requirements in vivo.

Although NF-κB activity was found to be dispensable for specification of γδ T cell progenitors and the generation of adaptive γδ T cells, it was required for both the ontogeny of type 1 γδ T cells and the survival of mature adaptive γδ T cells. Subunit-specific analyses revealed parallels with αβ T cells: RELA was necessary for type 1 γδ T cell development, while maintenance of adaptive γδ T cells relied upon redundancy between REL subunits, with cREL and p50 compensating in the absence of RELA but not vice versa. These findings reflect distinct biological requirements for ontogeny versus maintenance, likely driven by differences in receptor signaling, such as TCR and TNFRSF family members. Moreover, IKK also maintained γδ T cell survival through repression of RIPK1-mediated cell death, echoing its dual role in αβ T cells, where it both prevents TNF-induced apoptosis and provides NF-κB-dependent survival signals.

Strengths:

The multiple, unique murine genetic models employed for detailed analysis of in vivo γδ T cell differentiation and homeostasis are a major strength of this paper. NF-κB signaling processes are devilishly complex. The conditional mutants generated for this study disentangle the requirements for the various IKK-regulated pathways in γδ T cell differentiation, cell survival, and homeostasis. Data are clearly presented and suitably interpreted, with a helpful synthesis provided in the Discussion. These data will provide a definitive account of the requirements for NF-κB signaling in γδ T cells and provide new genetic models for the community to further study the upstream signals.

Weaknesses:

The paper would benefit greatly from a graphical abstract that could summarize the key findings, making the key findings accessible to the general immunology or biochemistry reader. Ideally, this graphic would distinguish the requirements for NF-κB signals sustaining thymic γδ T cell differentiation from peripheral maintenance, taking into account the various subsets and signaling pathways required. In addition, the authors should consider adding further literature comparing the requirements for NF-κB /necroptosis pathways in regulating other non-conventional T cell populations, such as iNKT, MAIT, or FOXP3+ Treg cells. These data might help position the requirements described here for γδ T cells compared to other subsets, with respect to homeostatic cues and transcriptional states.

Last and least, there are multiple grammatical errors throughout the manuscript, and it would benefit from further editing. Likewise, there are some minor errors in figures (e.g., Figure 3A, add percentage for plot from IKKDT.RIPK1D138N mouse; Figure 7, "Adative").

DOI: 10.1101/2025.11.03.686384

Resource: (IMSR Cat# JAX_029977,RRID:IMSR_JAX:029977)

Curator: @scibot

SciCrunch record: RRID:IMSR_JAX:029977

What is this?

The DA will absorb ODD, DGA and free flow non-personal data Interesting, as ODD is a Directive now. ODD is based on national access regimes, so might be tricky as Reg, unless the focus is on HVD mostly.

Au delà des LLM, pour une compréhension de ces biais dans le domaine de la santé cf. Nathan, T. (2012). Médecins et sorciers. La Découverte.

Vous montrer dans votre article le contraire car vos analyses du phénomène vous conduise à discuter profondément de ce que sont ces IA. Nous pouvons penser avec mais aussi contre les IA...

Il est inévitable que les "supports cognitifs" imposent un point de vue particulier : ils sont là pour ça. Ce qui importe c'est qu'on est les pouvoirs de discerner ces point de vue, de les raisons et d'exprimer une position en rapport avec ce qu'ils imposent... Les "supports cognitifs" comme les environnements numériques peuvent stimuler ces pouvoirs ou au contraire les confisquer mais dans tous les cas, c'est à chacun de sentir les augmentations et les diminutions de ces pouvoirs pour choisir d'utiliser ou non ces "supports cognitifs".

Pourquoi passe-t-on de l'éthique à la morale ?

Comment médier sans modeler ? Le médiateur influence tout autant que la forme car la médiation est aussi une forme.

Sans doute si c'est personnes le font. Peut-on mener une délibération éthique à la place d'un tiers ?

En quoi n'est-il pas compatible ?

laringea

cornetos

cornetos

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Reply to the reviewers

Detailed point-by-point response

__ __The Reviewers provided suggestions to improve the manuscript, most notably by adding experiments to (1) further support the role of Stim and Orai in epidermal heat-off responses and (2) further characterize the thermosensory responses of epidermal cells. We additionally propose to include a new set of calcium imaging experiments to visualize nociceptor sensitization by epidermal cells.

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

Summary: Drosophila larvae are known to respond to noxious stimuli by rolling. The authors propose that this response arises not only by sensory response of nociceptive neurons but also by direct response of larval epidermal cells. They go onto test this idea by independently manipulating epidermal cells and nociceptive sensory neurons using GAL4 lines, GCAMPs and RNAis. The behavioural data are convincing and presented clearly with good statistical analysis. However the involvement of epidermal cells in evoking the behaviour as well as STIM/Orai mediated Ca2+ entry requires further experiments. Use of another independent GAL4 strain for epidermal cells, alternate RNAi lines for STIM and Orai, mutants for STIM and Orai and overexpression constructs for STIM and Orai would significantly enhance the data. Thus, as of now the key results require more convincing. The following additional experiments would be required to support their claims:

1) Either use a second epidermal GAL4 strain to show key results OR provide images of the epidermal GAL4 expression double-labelled with a ppk driver using a different fluorescent protein to establish NO overlap of the epidermal GAL4 with neurons. These strains should be available free in Bloomington.

We agree that the specificity of the GAL4 driver is an important point. In a recent publication (Yoshino et al, eLife, 2025) we provide the most comprehensive analysis of larval epidermal GAL4 drivers published to date. Included in this study is expression analysis of R38F11-GAL4 demonstrating that it is indeed specifically expressed in the epidermis. Based on the detailed expression analysis and functional analysis provided in that paper, R38F11-GAL4 was chosen for these studies as it is both highly specific for epidermal cells and provides uniform expression across the body wall.

In our revised manuscript, we will more clearly detail how the driver was chosen for this study and provide a citation to the prior work to accompany our description of R38F11-GAL4 as an epidermis-specific driver line.

2) Authors need to provide better data for the involvement of STIM and Orai in the Calcium responses observed. A single RNAi for each gene with marginal change in response is insufficient. The authors also do not state if the RNAis used are validated by them or anyone else. Minimally they should repeat their experiments with at least one other validated RNAi and rescue these with overexpression constructs of STIM and Orai (available in Bloomington). It is well established in literature that overexpression of STIM/Orai can rescue SOCE in Drosophila. Ideally, to be fully convincing they should test a Drosophila knockout for STIM (available in Bloomington). Heterozygotes of this are viable and should be tested. Additionally a UAS Orai dominant negative (OraiDN) strain is available in Bloomington and can be tested.

We appreciate the Reviewer’s perspective on the importance of characterizing the efficacy of the reagents we used in this study. However, we disagree with the characterization of the change in response as “marginal”. Our results demonstrate that epidermal knockdown of Stim or Orai causes a significant reduction in the heat-off response of epidermal cells and heat-induced nociceptive sensitization.

In a prior published study (Yoshino et al, eLife, 2025) we validated for their efficacy of these RNAi lines in combination with the same GAL4 driver at the same developmental stage. Specifically, we demonstrated that R38F11GAL4-mediated expression of UAS-Stim RNAi or UAS-Orai RNAi significantly attenuated store operated calcium entry following story depletion by thapsigargin. In the revised manuscript, we will add a statement referring to this prior validation along with a citation. In light of this prior characterization, we disagree that additional RNAi lines are required to corroborate the results.

The most salient point of the Reviewer’s comment is that additional evidence should be provided to demonstrate more convincingly the requirement of Stim/Orai in epidermal heat-off responses. We detail our plans to address this point below, but first address the specific experimental suggestions the Reviewer provides.

First, the Reviewer suggests the use of a dominant-negative version of Orai, and we agree that this could prove complimentary to our RNAi experiments.

The Reviewer suggests two additional genetic approaches which are well-reasoned but problematic. First, they suggest rescuing the RNAi knockdowns with overexpression approaches. In addition to requiring the generation of new, RNAi-refractory transgenes, this approach is confounded by the effects of overexpressing CRAC channel components. Orai channels exhibit highly cooperative activation by Stim, and we previously showed that epidermal Stim overexpression drove mechanical nociceptive sensitization. Although this dosage effect confounds the rescue assays, we will examine whether epidermal Stim overexpression similarly sensitizes larvae to noxious thermal inputs as we would predict from our model.

The final experiment the Reviewer suggests – phenotypic analysis of Stim knockouts – is not possible due to the lethal phase of the mutants. Furthermore, it is not possible using traditional mosaic analysis to generate mutant epidermal clones that span the entire epidermis. Such an approach might be possible with a newly engineered FLP-out Stim allele, but generating that reagent is beyond the scope of this work. The Reviewer suggests characterization of Stim heterozygotes, but Drosophila genes rarely show strong dosage effects as heterozygotes (though we acknowledge that dosage effects can be amplified in the cases of genetic interactions), hence a negative result (no effect on heat-off responses) would not be meaningful. In principle we could test whether Stim hetorozygosity enhances effects of epidermal Stim RNAi. Although a negative result will not be telling, the experiment is straightforward, and an enhancement of the effect of Stim RNA would support the model that RNAi provides an incomplete functional knockdown of Stim. We will therefore perform this experiment and incorporate the results into the revised manuscript, pending a postitive outcome.

To better define the contributions of Stim and Orai to heat-off responses of epidermal cells, we will incorporate results from the following new experiments into our revised manuscript:

• We will monitor effects of epidermis-specific expression of a dominant negative form of Orai on epidermal heat-off responses (calcium imaging) and heat-induced nociceptive sensitization (behavioral assays).
• We will monitor effects of epidermis-specific co-expression of Stim+Orai RNAi on epidermal heat-off responses (calcium imaging) and heat-induced nociceptive sensitization (behavioral assays)
• Orai channels exhibit highly cooperative activation by Stim, therefore we will examine whether epidermal Stim overexpression increases the amplitude of heat-off responses (calcium imaging) and sensitizes larvae to noxious thermal inputs (behavioral assays) as we would predict from our model.

  Minor comments that can be addressed:

1) Figure 1: Further details required on how the rolling response is measured. Figure is uninformative. A video would be really helpful.

We appreciate the suggestion. We will add a more detailed explanation of how the behaviors were scored along with an annotated video.

2) I could not find Figure 1I described in the text. This section should be explained properly.

Figure 1I is described in the figure legend and we will add an in-text citation.

3) Figure 3: There appears to a small response at 32oC - why is this ignored in the text? It would be useful to have S3 in the main figure.

The small response at 32C is not ignored, though that individual response is better understood in the context of all responses plotted in Figure 3D. We will reword the phrase “At temperature maxima below 35°C epidermal cells rarely exhibited heat-off responses” to reflect the small response that is observed at lower temperatures. We will also replace the trace in the figure – the original submission contained the one outlier sample that exhibited robust responses at 32 C.

We appreciate the suggestion to include Fig S3 in the main text – we initially included it, but moved it to the supplement for space considerations. We will include it as a main figure in our revised submission.

4) Fig 4: The DF/F traces for the two RNAis should be included in this figure.

We appreciate the suggestion; we will add these traces to our revised submission.

5) Extent of knockdown in the epidermis by each RNAi should be shown by RTPCRs.

We note that efficacy of the knockdowns has been validated by us in acutely dissociated epidermal cells. RTPCR validation as described would require FACS-sorting of acutely dissociated, GFP-labeled epidermal cells from each specimen, an extremely time- and resource intensive experiment that provides limited information. The more relevant information is the physiological readout of Stim/Orai functional knockout using these reagents which we previously conducted. As described above, we will add a description of these experiments and the relevant citation.

6) The authors need to explain why only a small change in the Ca2+ response is seen with either RNAi. Are there other Ca2+ channels involved? Ideally they could test mutants/RNAi for the TRP channel family. Loss of SOCE in Drosophila neurons changes the expression of other membrane channels - is this possible here? Minimally, this possibility needs to be discussed.

We agree with the Reviewer that this topic warrants further discussion. Pending the results of our planned experiments (Orai dominan negative, Stim+Orai RNAi), we will incorporate a discussion of other channels that may contribute to the heat-off response. We appreciate the Reviewers point that loss of SOCE in Drosophila neurons can change the expression of membrane channels – that is an intriguing possibility that might explain the modest effects of Stim or Orai knockdown. We have not investigated effects of epidermal Stim/Orai knockdown on expression of other channels, but will incorporate this possibility into our discussion.

7) In the methods section please explain how the % DF/F calculations are done and how are they normalised to the ionomycin response.

We will incorporate these additional details in the methods section.

8) Authors need to look at previous work on STIM and Orai in Drosophila and reference appropriately.

We appreciate the suggestion and will incorporate additional discussion of relevant Drosophila work on STIM and Orai.

**Referees cross-commenting**

Reviewers 2 and 3 have raised some additional queries to what I had mentioned in my review. I agree with their comments. The authors should attempt to address all comments by all three reviewers.

We address their comments below.

Reviewer #1 (Significance (Required)):

This is an interesting study that identifies epidermal cells in Drosophila with the ability to sense a drop in temperature after receiving noxious heat stimuli and invoke appropriate behaviour. Behaviour experiments are well conducted and convincing. So far only nociceptive neurons were thought to control such behavioural responses so the work is significant and important for the field. The mechanism identified needs further convincing and I have suggested experiments that would be of help. With the additional experiments suggested the work will be of interest to neuroethologists, Drosophila neuroscientists and scientists in the field of Ca signaling.

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

Summary:

Noxious heat can have a strong adverse effect on animals, resulting in sensitization when noxious thermal stimuli are applied repeatedly. Noxious heat induces a characteristic rolling behavior in Drosophila melanogaster larvae. This study investigates sensitization, whereby a second heat stimulus evokes this behavior with significantly shorter latency (e.g., 3.4 seconds) than the initial exposure (e.g., 8.79 seconds). While prior research has implicated central and peripheral neurons in this process, recent findings in mammalian systems suggest a role for keratinocytes.

In this manuscript, Yoshino et al. report that epidermal cells are necessary and sufficient to mediate heat sensitization in D. melanogaster larvae. Using an ex vivo epidermal imaging system, the authors demonstrate that calcium influx in epidermal cells is crucial for sensitization. Importantly, this calcium influx was observed only when the temperature was lowered from a dangerously high to a safe temperature. The calcium channel system Orai and Stim facilitates this influx.

Major comments:

(1) The authors clearly demonstrate the heat-off reaction using calcium influx imaging. However, all of the imaging shows the response to the first stimulation. Since the study focuses on sensitization, which shows a quicker response to the second heat stimulus, it would be helpful if the authors showed calcium influx when the second stimulus was applied. It would also be interesting to see how many times the epidermal cells can react to heat stimulation.

We appreciate the suggestion from the Reviewer but note that the calcium influx we show occurs in epidermal cells, which signal to neurons to potentiate future responses in our model. We have emphasized this point in our revised manuscript.

The relevant response to visualize the sensitization is the heat-evoked calcium response in nociceptors, not epidermal cells. We have verified that C4da neurons exhibit calcium responses to the warming stimulus we use in our heat-off paradigm and our preliminary studies suggest that the heat-off stimulus potentiates future responses to noxious heat in nociceptors. We will therefore examine (1) whether epidermal stimulation triggers a sensitization of nociceptors to thermal stimuli by monitoring heat-induced calcium responses using GCaMP, and (2) whether epidermal Stim and Orai are required for this sensitization.

The second comment addresses the response of epidermal cells to repeated rounds of stimuli. We agree that this is an interesting point. We have verified that epidermal cells indeed respond to multiple rounds of heat-off stimuli. We will incorporate results from a paradigm in which epidermal cells are presented with two successive heat-off stimuli, spaced by 5 minutes to allow epidermal cytosolic calcium to return to baseline. We will incorporate new analysis examining the relative magnitude of epidermal cells to the first and second stimulus.

(2) Figure 5 only shows one condition: a 30-second interval between the first and second heat application. While the rolling latency of the Luciferase RNAi control ranges from 4 to 12 seconds (with a median of 5 seconds), Fig. 1E shows a latency ranging from 6 to 12 seconds (with a median of 10 seconds) under the same 30-second interval conditions. This difference makes interpreting the effect of Stim and Orai confusing. The authors need to clarify whether the knockdowns accelerate the first response or delay the second response.

The Reviewer notes that we assayed effects of Stim/Orai RNAi on heat-induced nociceptive sensitization in only one paradigm. Given the kinetics of cytosolic calcium increases following Stim or Orai RNAi in epidermal cells (Fig. 4F), we agree that an additional set of behavior experiments investing sensitization following a 60 sec recovery is warranted. For our revision we will conduct a time-course to assay requirements of epidermal Stim and Orai (using epidermal expression of Stim/Orai RNAi and Orai dominant negative transgenes) on heat-induced nociceptive sensitization. Our preliminary studies indicate that Stim and Orai RNAi significantly reduce heat-induced sensitization following 60 s of recovery (we present results from 30 s of recovery in the original submission).

The Reviewer raises some questions about differences in behavioral latencies in Figure 1E and Figure 5B. We intentionally avoid such comparisons both because the genetic backgrounds are different and the experiments were conducted at very different times (more than 1 year apart). In both experiments the salient feature that we discuss is the presence or absence of sensitization, not the mean latency. We note that we do compare mean latency values in Figure 1B, but that was a distinct experimental paradigm (global heat of variable temperatures followed by focal noxious heat) designed specifically to define heat stimuli that generate the maximum level of sensitization. In that case, the genotype was fixed and all assays were conducted concurrently.

Minor comments:

(i) In Fig. 2C´´, the authors observed clear calcium influx in epidermal cells by combining the GCaMP genetic tool with an ex vivo thermal perfusion system. Although this system applies heat uniformly across the epidermal tissue, calcium influx is spatially restricted, appearing primarily in the head and tail regions of the epidermis. These results suggest that the heat-responsive epidermal cells are localized to these regions or that there are regional differences in sensitivity. The authors should explain the spatial relationship between the heat-applied epidermal cells and the occurrence of calcium influx.

The Reviewer notes that intensity of the epidermal GCaMP signal is particularly intense in the anterior and posterior portions of the fillet preparation (Fig. 1B-1C), and we agree that it would be useful to include an explanation of this result, which is an artifact of the sample preparation.

The specimens we use for calcium preparation are “butterfly” preparations – the body wall is filleted along the long axis with the exception of regions at the head and tail that are pinned down on sylgard plates. Hence, the regions in the head and tail contain intact tissue (including a double layer of skin when we image in widefield), not a single layer of skin (the rest of the prep). More significantly, the head and tail regions are pinned down, creating a wound that triggers lasting local calcium transients (note signal in the absence of temperature stimulus, Figure 1B’ and 1B”, 1C’). We therefore exclude this region from our analysis. We note that our behavior studies relied on stimuli presented to the abdominal segments we sample in the semi-intact calcium imaging. Similarly, we dissociated epidermal cells exclusively from these segments for imaging of acutely isolated epidermal cells.

We do note that there is a periodicity to the signal – within each segment there are local maxima and minima of signal, and we agree with the Reviewer that this spatial segregation is an interesting point for discussion. We will add 1-2 sentences to our discussion of the result to acknowledge this point.

(ii) Related to comment (i) above, if heat stimuli are applied topically using a heat probe under the ex vivo imaging system, how large an area reacts to the stimuli?

The Reviewer raises an interesting question about the local response to heat stimuli. In our dissociated cell experiments we found that the overwhelming majority of isolated epidermal cells exhibit heat-off responses, and we likewise find that the majority of cells in our semi-intact preparation respond to heat-off stimuli. However, our current probe for delivering local heat stimuli is not compatible with our imaging system. We are working to incorporate an IR laser to focally deliver heat stimulus to explore whether epidermal cells signal to neighbors following stimulation, but such studies are beyond the scope of the current work.

(iii) Providing supplementary movie(s) of the calcium live imaging would enhance the reader's understanding.

We agree with the Reviewer that this would be a useful supplement. We will add representative movies as experimental supplements in our revised manuscript.

(iv) The time point of the image in Fig. 2C´ ("before heat") is not the most informative for demonstrating a "heat-off" response. The authors should replace it with an image taken during the heat application to provide a more direct comparison with the post-stimulus influx shown in Fig. 2C´´.

We appreciate the Reviewer’s suggestion and agree this would be a better choice to visually represent the change in fluorescence induced by the heat-off response. We will make this change in our revised manuscript.

(v) The authors state that sensitization occurs "primarily in the 30-45 ºC range." However, the rolling probability and latency developed oppositely at 45 ºC stimulation than at 40 ºC. It would be doubtful that 45 ºC may be approaching a noxious or damaging threshold that engages a different phenomenon. The authors should reconsider including 45 ºC within the optimal sensitization range or provide a justification.

We agree with the Reviewer that a more detailed discussion of the effects of temperature at the end of the range (45 C) is warranted. Exposure to a 45 C global heat stimulus triggered temporary paralysis in some larvae, and we suspect that this accounts for the apparent reduction in roll probability following the second stimulus. We can add a plot depicting the proportion of larvae that exhibited paralysis during 45 C global heat and determine whether these heat-paralyzed larvae exhibited distinct responses from larvae that were not paralyzed and provide a more detailed account of the optimal sensitization range.

Treatment with 45 C stimuli still triggered a significant reduction in roll latency (sensitization), but we did not examine whether the latency was significantly different from what was observed at 40 C. We can add that analysis in the revision.

(vi) In the sentence "To this end, we developed a perfusion system, that would deliver thermal ramps from ~20-45ºC ...," the tilde ~ should be replaced with "approximately".

Noted. We will make the change.

(vii) Throughout the manuscript, please clarify in the figure legends whether the sample size (n) refers to the number of individual animals or the number of cells.

Noted. We will add the relevant details to our sample sizes notations.

(viii) The Key Resources Table does not specify the wild-type (WT) strain used for the control experiments (e.g., in Fig. 1). Please provide the full genotype of the control strain used.

We included the experimental genotypes in each figure legend, which we find more useful than the key resource table, which contains a list of all reagents used in the study (Drosophila alleles included).

Reviewer #2 (Significance (Required)):

General Assessment

This study addresses a fundamental question in sensory biology: whether epidermal cells, long regarded as passive participants in somatosensation, actively contribute to noxious heat detection and avoidance behavior. While previous work has defined the neuronal circuits and TRP channel mechanisms underlying thermal nociception in Drosophila larvae, the potential sensory role of skin cells has remained largely unexplored. The authors integrate behavioral analysis with in vitro and ex vivo calcium imaging to provide a rigorous, multi-level investigation of epidermal thermosensitivity.

Advancement

The work advances the field by revealing that Drosophila epidermal cells are intrinsically thermosensitive and can acutely sensitize larval nociceptive responses to noxious heat through heat-off signaling. This discovery shifts the current paradigm of thermal nociception from a neuron-centric model to one that incorporates epidermal contributions, highlighting a conserved and previously underappreciated role of skin cells in active environmental sensing.

The reviewer's expertise: Molecular genetics, developmental biology, insect physiology and endocrinology.

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

This manuscript describes the temperature responses of Drosophila larval epidermal cells. These cells are activated by cooling and also exhibit strong heat-off responses. Orai and Stim are required in epidermal cells for these heat-off responses. The heat-off responses sensitize the epidermal cells, leading to a greater proportion of animals displaying rolling behaviors and a reduced latency to initiate rolling following noxious heating treatment. The following comments are intended to help improve the manuscript.

Major:

1. In Figure 3A, the conclusion will be strengthened by testing heat-off responses from 10 {degree sign}C to 40 {degree sign}C.

The Reviewer makes an important point. In our original experiment, the lack of response in the 10C – 30C experiment could be due to some cold-induced suppression of the off response. We have found that this is not the case – we have found that off responses following a 10C-40C ramp are indistinguishable from responses to a 20C-40C ramp. In our revised manuscript we will incorporate new results showing epidermal heat off responses to a 10C-40C ramp as well as normalization to 20C-40C responses performed in parallel.

Figure 4C shows that 2-APB suppresses the heat-off response. Since 2-APB blocks both Orai and TRP channels, it is unclear why the authors focused exclusively on the Orai pathway without testing TRP channels.

We found that epidermal cells exhibited minimal responses to warming stimuli, as would be expected for the epidermally expressed TRP channel TRPA1. In addition, the heat-off response we identified was remarkably similar to characteristic heat-off responses of mammalian CRAC channels. Hence, we focused our attention on the Orai pathway. While we agree that contributions of TRP channels could be of interest, especially if our additional analyses (double RNAi and Orai Dominant Negative) support the model that additional channels likely contribute to the heat-off response, the characteristic temperature responses of CRAC channels made them the most plausible candidate.

In parallel to the experiments to further characterize Stim/Orai contributions to the heat-off response, we will assay requirements of TRPA1 to heat-induced nociceptor sensitization.

While 2-APB completely abolishes the heat-off response, Orai and Stim RNAi only slightly (although significantly) reduce calcium responses. The knockdown efficiency of the RNAi constructs should be validated. Furthermore, testing whether combining Orai RNAi and Stim RNAi produces a stronger reduction in calcium responses would be informative.

We addressed the question of knockdown efficiency above, and agree that testing the effects of Orai RNAi and Stim RNAi in combination is worthwhile. We detailed our plans for these experiments above.

The study uses third-instar larvae. Please specify whether early, mid, or late third instar were used.

In our original submission we stated “Third-instar larvae (96-120 AEL) larvae were used in all experiments” We provide additional details on the staging of larvae for all experiments in the methods section of our revised submission. To synchronize cultures, embryos were collected from experimental crosses for 24 h, aged for 96 h, and foraging mid-third instar larvae (96-120 h old) were used for all experiments.

Please provide more details about the thin layer of water used. Specifically, indicate the size of the Peltier plate and the volume of water applied.

We provide additional details on the application of global heat stimulus in the methods section of our revised manuscript. “For assays testing effects of varying the temperature of prior thermal stimuli on thermal nociception, larvae were individually transferred to a pre-warmed Peltier plate (11 x 7 cm; Torrey Pines Scientific). Peltier plates were warmed to the indicated temperatures, a thin layer of water was applied to the surface using a paint brush, and the temperature was verified using an infrared thermometer. Larvae were transferred individually to the Peltier plate, incubated for the indicated time, and recovered to 2% Agar Pads using a paint brush. Following 10 s of recovery, larvae were stimulated with a 41.5°C thermal probe, as above, and latency to the first complete roll was recorded.”

Minor:

1. There is an inconsistency between the text and the figure regarding the sample number in Figure 1D.

We thank the reviewer for identifying the discrepancy. This inconsistency has been corrected in the revised submission.

Please provide the raw representative data for the time course of heat-off calcium responses in Figure 1E.

We will incorporate representative traces for the heat-off responses plotted in Figure 1E.

A period is missing at the end of the sentence: "For curve fitting, sample-averaged fluorescence traces were fitted with a single exponential decay function using R to extract a representative time constant (τ) and assess response kinetics."

We thank the reviewer for identifying the omission. The period has been added.

In the sentence "Behavior Responses were analyzed post-hoc blind to genotype and were plotted according to roll probability and roll latency," the word Responses should begin with a lowercase r.

This has been corrected in the revised submission.

Reviewer #3 (Significance (Required)):

This manuscript describes the heat-off responses of larval epidermal cells and investigates their underlying molecular mechanisms as well as associated behavioral consequences.

The calcium responses and behavioral assays are clearly presented. However, the contribution of Stim and Orai to this process is not convincing.

The study may be of interest to researchers working on Drosophila and temperature sensation, as well as to those studying Orai and Stim function.

I am a researcher specializing in Drosophila thermosensation.

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

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Referee #3

Evidence, reproducibility and clarity

This manuscript describes the temperature responses of Drosophila larval epidermal cells. These cells are activated by cooling and also exhibit strong heat-off responses. Orai and Stim are required in epidermal cells for these heat-off responses. The heat-off responses sensitize the epidermal cells, leading to a greater proportion of animals displaying rolling behaviors and a reduced latency to initiate rolling following noxious heating treatment. The following comments are intended to help improve the manuscript.

Major:

1. In Figure 3A, the conclusion will be strengthened by testing heat-off responses from 10 {degree sign}C to 40 {degree sign}C.
2. Figure 4C shows that 2-APB suppresses the heat-off response. Since 2-APB blocks both Orai and TRP channels, it is unclear why the authors focused exclusively on the Orai pathway without testing TRP channels.
3. While 2-APB completely abolishes the heat-off response, Orai and Stim RNAi only slightly (although significantly) reduce calcium responses. The knockdown efficiency of the RNAi constructs should be validated. Furthermore, testing whether combining Orai RNAi and Stim RNAi produces a stronger reduction in calcium responses would be informative.
4. The study uses third-instar larvae. Please specify whether early, mid, or late third instar were used.
5. Please provide more details about the thin layer of water used. Specifically, indicate the size of the Peltier plate and the volume of water applied.

Minor:

1. There is an inconsistency between the text and the figure regarding the sample number in Figure 1D.
2. Please provide the raw representative data for the time course of heat-off calcium responses in Figure 1E.
3. A period is missing at the end of the sentence: "For curve fitting, sample-averaged fluorescence traces were fitted with a single exponential decay function using R to extract a representative time constant (τ) and assess response kinetics."
4. In the sentence "Behavior Responses were analyzed post-hoc blind to genotype and were plotted according to roll probability and roll latency," the word Responses should begin with a lowercase r.

Significance

This manuscript describes the heat-off responses of larval epidermal cells and investigates their underlying molecular mechanisms as well as associated behavioral consequences.

The calcium responses and behavioral assays are clearly presented. However, the contribution of Stim and Orai to this process is not convincing.

The study may be of interest to researchers working on Drosophila and temperature sensation, as well as to those studying Orai and Stim function.

I am a researcher specializing in Drosophila thermosensation.

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: Drosophila larvae are known to respond to noxious stimuli by rolling. The authors propose that this response arises not only by sensory response of nociceptive neurons but also by direct response of larval epidermal cells. They go onto test this idea by independently manipulating epidermal cells and nociceptive sensory neurons using GAL4 lines, GCAMPs and RNAis. The behavioural data are convincing and presented clearly with good statistical analysis. However the involvement of epidermal cells in evoking the behaviour as well as STIM/Orai mediated Ca2+ entry requires further experiments. Use of another independent GAL4 strain for epidermal cells, alternate RNAi lines for STIM and Orai, mutants for STIM and Orai and overexpression constructs for STIM and Orai would significantly enhance the data. Thus, as of now the key results require more convincing. The following additional experiments would be required to support their claims:

1) Either use a second epidermal GAL4 strain to show key results OR provide images of the epidermal GAL4 expression double-labelled with a ppk driver using a different fluorescent protein to establish NO overlap of the epidermal GAL4 with neurons. These strains should be available free in Bloomington.

2) Authors need to provide better data for the involvement of STIM and Orai in the Calcium responses observed. A single RNAi for each gene with marginal change in response is insufficient. The authors also do not state if the RNAis used are validated by them or anyone else. Minimally they should repeat their experiments with at least one other validated RNAi and rescue these with overexpression constructs of STIM and Orai (available in Bloomington). It is well established in literature that overexpression of STIM/Orai can rescue SOCE in Drosophila. Ideally, to be fully convincing they should test a Drosophila knockout for STIM (available in Bloomington). Heterozygotes of this are viable and should be tested. Additionally a UAS Orai dominant negative (OraiDN) strain is available in Bloomington and can be tested.

Minor comments that can be addressed:

1) Figure 1: Further details required on how the rolling response is measured. Figure is uninformative. A video would be really helpful.

2) I could not find Figure 1I described in the text. This section should be explained properly.

3) Figure 3: There appears to a small response at 32oC - why is this ignored in the text? It would be useful to have S3 in the main figure.

4) Fig 4: The DF/F traces for the two RNAis should be included in this figure.

5) Extent of knockdown in the epidermis by each RNAi should be shown by RTPCRs.

6) The authors need to explain why only a small change in the Ca2+ response is seen with either RNAi. Are there other Ca2+ channels involved? Ideally they could test mutants/RNAi for the TRP channel family. Loss of SOCE in Drosophila neurons changes the expression of other membrane channels - is this possible here? Minimally, this possibility needs to be discussed.

7) In the methods section please explain how the % DF/F calculations are done and how are they normalised to the ionomycin response.

8) Authors need to look at previous work on STIM and Orai in Drosophila and reference appropriately.

Referees cross-commenting

Reviewers 2 and 3 have raised some additional queries to what I had mentioned in my review. I agree with their comments. The authors should attempt to address all comments by all three reviewers.

Significance

This is an interesting study that identifies epidermal cells in Drosophila with the ability to sense a drop in temperature after receiving noxious heat stimuli and invoke appropriate behaviour. Behaviour experiments are well conducted and convincing. So far only nociceptive neurons were thought to control such behavioural responses so the work is significant and important for the field. The mechanism identified needs further convincing and I have suggested experiments that would be of help. With the additional experiments suggested the work will be of interest to neuroethologists, Drosophila neuroscientists and scientists in the field of Ca signaling.

③ due to the high vascularity of these areas, which leads to rapid absorption and peak plasma concentrations similar to intravenous administration. çünkü bu bölgeler yüksek vaskülariteye sahiptir; bu da ilacın hızlı emilmesine ve intravenöz uygulamaya benzer plazma zirve konsantrasyonlarına yol açar.

③ as well as roles in DNA transport in DNA vaccines. ve DNA aşılarında DNA taşınmasında da rol oynarlar.

The book aims for a cultural movement / ecology of knowledge in spite of the toxic platforms. Because those erode thinking well (title). Innovation now disregards the quality of relationships. (Nice, this chimes with my [[Menselijk en digitaal netwerk zijn gelijksoortig 20200810142551]] and the unfulfilled potential of exploring that congruence). The book proposes to review the mediasystem to make it align with democratic values.

Luca compares two books (his and Ferraris') in how they solve that relative value problem. Luca by proposing dismantling the dominant platforms and replace them with a multitude of others (as the volume of personal data aids its exploitation I presume, spreading it out means having to collect it and collection is costly if users don't actively bring it to you already). Ferraris proposes otoh an active redistribution of the value gained as political project a new 'pragmatic' and modern communism. De Biase proposal seems more achievable imo (in the sense that we're already doing it)

Often not acknowledged what Luca says here: that it's obvious that n:: the value of personal data is not intrinsic but w.r.t. to a specific context of use. It's relative (and that is also why data protection of personal data isn't absolute, but weighed against other factors.) Perhaps capture it as Notie.

It seems like Bernard is referring to an event with the Institute for Research and Innovation (IRI) at the Pompidou Centre in 2018: The intelligence of cities and the new urban revolution [L’intelligence des villes et la nouvelle révolution urbaine] as part of talks organised at the Pompidou Centre: The Discussions of New Industrial World' [Les Entretiens du Nouveau Monde Industriel] on December 18–19th, 2018. Description

Y? Para algunas cosas también puedes utilizar gráficos

Instrucciones claras para los alumnos

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

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Reply to the reviewers

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__Reviewer #1 __

Major comments

1. The manuscript posits that the loss of function of MASh components (Ogc1 and Aralar) decreases adrenergic-stimulated lipolysis by altering the cytosolic NAD⁺/NADH ratio, with AMPK/ACC mentioned as possible mediators. However, this remains speculative. Please provide mechanistic data directly linking MASh-dependent NAD⁺/NADH changes to the regulation of lipolysis in brown adipocytes during adrenergic stimulation. Answer 1) The reviewer raises an important point regarding the direct assessment of cytosolic NAD⁺/NADH redox changes as a mechanistic link for altered lipolysis in brown adipocytes lacking MASh components. To address this point, we added new data to the revised manuscript showing lactate/pyruvate ratio as measured by metabolomics. This is a well-established surrogate marker to monitor changes in redox balance. Notably, under basal (non-stimulated) conditions, the lactate/pyruvate ratio did not display any significant differences between Aralar 1 KD and control cells, suggesting preservation of cytosolic NAD⁺/NADH levels in the absence of functional MASh under these conditions. This finding is consistent with reports showing the robustness of NAD⁺ regeneration via multiple shuttles and the possibility of metabolic compensation when one shuttle is compromised (PMID: 40540398; PMID: 37647199).

The results have been added as new supplementary Figure 1 as following:

Our new metabolomics data also revealed substantial reductions in the aspartate/glutamate ratio in Aralar 1 knockdown cells, serving as a metabolomic signature of impaired MASh function and reduced exchange of these amino acids between the cytosol and mitochondria. Given that the MASh is a major mechanism for exporting cytosolic reducing equivalents into the mitochondria under high metabolic demand, its loss would be expected to impact redox homeostasis, particularly under adrenergic stimulation when glycolytic flux and lipolytic activity are elevated (PMID: 40540398).

Importantly, although our redox surrogate marker did not detect alterations, this may be explained by activation of compensatory pathways, most notably the glycerol phosphate shuttle (GPSh), which is highly expressed and active in brown adipocytes. Indirect support for this compensation comes from data shown in figure 4I showing reduced glycerol release in Aralar 1 KD cells upon norepinephrine stimulation and blocked lipolysis. This suggests a redirection of glycolytically derived G3P away from release and toward enhanced cycling within the GPSh, supporting cytosolic NAD⁺ regeneration via mitochondrial FAD-dependent G3PDH and cytosolic NAD⁺-dependent G3PDH activity. This is consistent with studies documenting that the combined action of MASh and GPSh maintains NAD redox homeostasis in brown adipocytes especially during non-thermogenic conditions (PMID: 168075; PMID: 40540398; PMID: 37647199). We have included a discussion about this possibility at page 9, third paragraph as follows:

*“Previous studies have shown that BAT exhibits high activity of mitochondrial FAD-dependent glycerol-3-phosphate dehydrogenase (mG3PDH), which functions as an electron sink to sustain low cytosolic NADH levels essential for continuous glycolytic flux [11]. Accordingly, suppression of the MASh, either genetically or pharmacologically, is likely to induce a compensatory upregulation of the GPSh. This adaptation would enhance G3P turnover, contributing to the maintenance of cytosolic NAD redox balance. Moreover, the increased flux through the GPSh could favor fatty acid esterification and triglyceride synthesis or re-esterification, consistent with our findings in Ogc and/or Aralar 1 KD cells, where (i) triglyceride content rises (Fig. 3), (ii) overall respiratory rates remain largely unaltered (Figs. 2D–G), and (iii) glycerol release declines significantly (Fig. 4I). Notably, the decrease in glycerol release persists even when lipolysis is blocked by ATGlistatin, suggesting that the available G3P pool is rerouted from dephosphorylation and extracellular release toward oxidation to DHAP by mG3PDH to regenerate cytosolic NAD+ under MASh-deficient conditions. We propose that interference with the MASh does not directly impact lipolysis but instead alters the cellular balance between DHAP and G3P owing to enhanced activity of the GPSh. This metabolic shift would favor the esterification of G3P with free fatty acids, thereby promoting triglyceride synthesis. These results support the notion that, even during adrenergic stimulation—when long-chain unsaturated fatty acids and their CoA esters strongly inhibit mG3PDH activity [11]—the residual flux through the glycerophosphate shuttle remains critical for sustaining cytosolic NAD redox equilibrium [11,19,32].” *

• *

At the mechanistic level, adrenergic stimulation in brown adipocytes activates robust lipolysis and thermogenic gene programs, generating high NADH that must be efficiently reoxidized to sustain flux through glycolysis and lipolysis-linked pathways. Our findings are consistent with a model in which the loss of MASh does not prevent cytosolic NAD⁺ regeneration or lipolytic flux during acute adrenergic stimulation, due to compensatory upregulation of the GPSh, as suggested by the glycerol release changes. Thus, while MASh normally acts as a conduit for NADH export and aspartate/glutamate exchange, in its absence, the GPSh maintains cytosolic redox balance, thereby sustaining glycolytic and lipolytic capacity.

We agree that future studies should employ direct measurements of cytosolic NAD⁺/NADH ratios (e.g., genetically-encoded redox sensors) during adrenergic stimulation and specific pharmacological inhibition of both shuttles to dissect these relationships in greater detail. We sincerely appreciate the reviewer's input, which has prompted us to clarify the indirect but robust evidence supporting a role for compensatory redox shuttle activity in preserving brown adipocyte lipolysis in the setting of MASh impairment.

We have further added a new paragraph in the discussion section (page 10)::

*“Mechanistically, the connection between the MASh and lipolysis appears to involve regulation of the cytosolic NAD⁺/NADH redox balance. MASh activity facilitates the regeneration of NAD⁺ from NADH in the cytosol, primarily through the reduction of oxaloacetate to malate by cytosolic malate dehydrogenase (Fig. 1G-H). Despite the theoretical expectation that reductions in MASh activity would disturb redox homeostasis, our metabolomic data show that the lactate/pyruvate ratio remains unchanged under conditions of MASh impairment, indicating that the overall cytosolic NAD⁺/NADH ratio is maintained (Figure S1A-C). While direct measurements of cytosolic NAD⁺/NADH were not performed, the preserved lactate/pyruvate ratio in Aralar 1 KD cells under basal conditions strongly suggests redox stability, likely due to compensatory activity by alternative mitochondrial shuttles or metabolic adaptations that maintain NAD redox homeostasis despite MASh impairment [18,33]. *

Previous evidence indicates that BAT exhibits high activity of mitochondrial FAD-dependent glycerol-3-phosphate dehydrogenase (G3PDH), which acts as an electron sink to sustain low cytosolic NADH levels critical for glycolysis [34]. In this sense, it is conceivable that genetic or pharmacological suppression of MASh triggers compensatory enhancement of the G3P shuttle, increasing G3P availability and facilitating the maintenance of cytosolic NAD redox balance. This adaptation could also promote fatty acid esterification and triglyceride synthesis or re-esterification, aligning with our observations that in Ogc and/or Aralar 1 KD cells: (i) triglyceride levels increase (Fig. 3); (ii) overall respiratory rates are preserved (Figs. 2D–G); and (iii) glycerol release is significantly reduced (Fig 4I).”

• *

__ The absence of in vivo analysis of lipid-droplet size in MASh loss-of-function models is a major concern. In vitro results could be confounded by differences in differentiation stage between groups. Please document equivalent adipogenesis across groups (e.g., Pparg/Cebpa/Plin1/Fabp4 expression).__

Answer 2) We thank the reviewer for the thoughtful and constructive comment regarding potential confounding by differences in differentiation stage, and for highlighting the importance of documenting equivalence between experimental groups. We appreciate the opportunity to clarify and provide additional assurance on this point.

As detailed in our manuscript, we have performed qPCR analysis of multiple well-established markers of brown adipocyte differentiation, including Ucp1, Elovl3, Prdm16, Pparg, Cebpa, Plin1, and Fabp4, in both scramble, aralar1 KD, and Ogc KD cells (see Fig. S1A and accompanying text). Our results show no apparent effect of these genetic interventions on overall differentiation, as the expression levels of these key markers were consistently unaltered across groups. Furthermore, adenoviral-mediated knockdown of Ogc achieved an approximate 80% reduction in Ogc mRNA (see Fig. S1B), yet most differentiation markers remained unaffected. We did observe significant increases in Atgl, Pgc1α, and Tfam mRNA levels, which may indicate a degree of pathway reprogramming without affecting the general differentiation profile. We propose that interference with the MASh does not directly impact lipolysis but instead alters the cellular balance between DHAP and G3P owing to enhanced activity of the GPSh. This metabolic shift would favor the esterification of G3P with free fatty acids, thereby promoting triglyceride synthesis.

Additional experimental support for equivalent differentiation can be drawn from our respirometry data presented in Figures 2E and 2G. These figures demonstrate that respiratory rates upon norepinephrine stimulation, which is a sensitive indicator of brown adipocyte thermogenic capacity, were essentially identical in scramble, aralar1 KD, and Ogc KD cells. Since norepinephrine-stimulated respiration requires both functional mitochondria and the full differentiation of brown adipocytes, these results strongly support the conclusion that silencing either MASh component does not impair the fundamental ability of cells to undergo brown adipocyte differentiation or achieve functional thermogenic competence.

This is consistent with published findings showing that norepinephrine triggers robust respiration and thermogenic activation only in fully differentiated and functional brown adipocytes, making such measurements a widely accepted proxy for differentiation status and mitochondrial integrity. Thus, the equivalent respiratory responses observed in all groups further validate that differentiation was not compromised by the genetic interventions.

We hope this clarifies that equivalent adipogenesis was carefully documented and that any observed phenotypes are unlikely to be attributable to differences in differentiation stages. Thank you again for your rigorous assessment and for helping to ensure the robustness of our study.

__ Please include rescue experiments (add-back OGC1 and Aralar) to rule out siRNA/shRNA off-target effects and verify that the phenotype stems from MASh loss of function.__

Answer 3) We thank the reviewer for this important suggestion regarding the inclusion of rescue experiments with add-back of Ogc and Aralar to definitively exclude off-target effects of the siRNA/shRNA-mediated knockdowns.

We would like to kindly point out that although we did not perform add-back rescue experiments directly, the consistency of phenotypes observed across two independent genetic interventions—aralar 1 KD and Ogc KD—strongly argues against off-target effects being responsible for the observed metabolic and functional alterations. Specifically, both knockdowns yielded remarkably similar phenotypes in multiple assays, including respirometry analyses, mitochondrial morphology, lipid droplet homeostasis, and lipid metabolism, supporting the conclusion that these effects stem from MASh loss of function rather than nonspecific silencing.

Furthermore, our new supplementary data (new Supplementary Figure 1A-F) reveals a significant reduction in the aspartate/glutamate ratio in Aralar 1 KD cells, a compelling functional readout for MASh impairment. This molecular evidence corroborates that our genetic interventions effectively disrupted MASh activity as intended.

We sincerely appreciate the reviewer’s thorough evaluation and understand the importance of rescue experiments. While recognizing their value, we believe the convergent genetic, metabolic, and functional evidence presented across two different MASh components provides strong and consistent support that the phenotypes observed are due to specific loss of MASh function.

__ Please expand on physiological significance: What is the importance of MASh regulation of BAT lipolysis in long-term adaptive thermogenesis?__

Answer 4) This is a very interesting aspect, and we have included a new paragraph in the discussion section (page 14) to address it as follows:

“Our results, supported by recent literature, strongly indicate that the malate–aspartate shuttle (MASh) plays a key role in facilitating fatty acid–dependent thermogenesis in brown adipocytes. Specifically, BAT-targeted overexpression of GOT1 has been shown to enhance β-oxidation and support acute cold-induced thermogenesis (PMID: 40540398). Interestingly, genetic ablation of GOT1—and thus MASh inhibition—preserves cold-induced thermogenesis by promoting a metabolic shift from fatty acid to glucose oxidation. Our findings corroborate and extend these observations by demonstrating that MASh impairment sustains overall respiratory activity in norepinephrine-stimulated brown adipocytes (Figures 2D–2G), while concurrently impairing lipolysis and resulting in an accumulation of small lipid droplets (Figures 3 and 4). Collectively, these data suggest that MASh not only modulates substrate preference towards fatty acid oxidation but also facilitates lipolysis, an essential upstream step that enables lipid oxidation and supports thermogenic heat production.”

Minor comments

1. __ Fig. 4 legend/title contains a typo ("lypolysis" → lipolysis).__ Answer 1) Corrected

__ In Fig. 2 legend line: "Adevirus-mediated" → Adenovirus-mediated; "OCAR" → OCR.__

Answer 2) Corrected

__ For lipolysis imaging, you already show Forskolin/Atglistatin/Etomoxir controls; add a vehicle-only time course overlay in the main figure (currently in text/legend) to aid visual comparison.__

Answer 3) We thank the reviewer for pointing this out. To improve clarity, we have updated the labeling in Figures 3 and 4: “basal” now clearly refers to the unstimulated/untreated condition, and the previously labeled “UT” condition has been clarified as “untransduced.” These changes make the figure legends and data presentation more consistent and easier to interpret.

__ Ensure consistent gene symbols (Atgl/Pnpla2), and protein capitalization.__

Answer 4) Corrected.

__Reviewer #2 __

Major points:

1. __ In the current manuscript, mitochondrial morphology (area, aspect ratio, and roundness) was analyzed in OGC1 KD cells using TMRE, whereas MitoTracker Deep Red (MTDR) was used in Aralar1 KD cells. Notably, TMRE is a ΔΨm-dependent probe. The signal intensity can change, or the distribution may reflect alterations in membrane potential rather than true morphological changes. Therefore, the observed differences in OGC1 KD cells based on TMRE staining may be confounded by the dye's functional dependence, potentially biasing the conclusions. It is recommended to evaluate mitochondrial morphology with consistent trackers across conditions. In addition, in the subsequent OCR analysis, mitochondrial area was used for normalization. Please clarify which staining method was employed, and provide justification for its suitability.__ Answer 1) We thank the reviewer for this insightful comment. Indeed, TMRE is a membrane potential-sensitive dye and could therefore potentially affect measurements of mitochondria.

We would like to point out that mitochondrial morphology was quantified based on mitochondrial area rather than fluorescence intensity. To create an accurate binary map of mitochondria, we used a low threshold, which allowed us to include even weakly stained mitochondria and thereby detect them independently of their membrane potential. In all imaged cells, TMRE signal was sufficient to reliably identify mitochondrial pixels. Moreover, these images were acquired using a confocal microscope, where the risk of pixel expansion due to higher fluorescence intensity is minimized. Lastly, given that overall mitochondrial oxygen consumption in these cells remains largely intact, we do not expect a substantial loss of membrane potential, although minor effects cannot be entirely excluded.

We opted to use TMRE for imaging Ogc KD cells because the scramble control for these shRNA viruses carries an mKate fluorescent tag, which overlaps with the MTDR signal. Since accurate assessment of transduction efficiency relied on detecting mKate, MTDR could not be used in these experiments. Importantly, we only compare mitochondrial morphology within the same staining condition and do not draw conclusions across cells stained with different dyes.

To ensure transparency, we have added a new section at the discussion (page 17, 2nd paragraph) highlighting the potential influence of ΔΨm-dependent dyes on morphological measurements as follows:

“It is also important to note that mitochondrial morphology was quantified using MTDR in Aralar 1 KD cells and TMRE in Ogc KD cells due to experimental constraints (see Methods). TMRE is a membrane potential–dependent dye, which could potentially influence morphology measurements. To minimize this risk, we used confocal microscopy, which reduces the likelihood of pixel expansion due to higher fluorescence intensity, and set thresholds to detect even weakly stained mitochondria. Nonetheless, we cannot fully exclude the possibility that the differences in morphology observed between Aralar 1 and Ogc KD are influenced by the use of different dyes; however, statistical comparisons were never performed across samples stained with different dyes.”

Also, we have expanded the Methods section (page 22, 2nd paragraph) to include a rationale for using these dyes and describe the analysis protocol as following:

“TMRE was used for Ogc KD cells because the scramble control for the shRNA viruses carries an mKate fluorescent tag, which overlaps with MTDR fluorescence, preventing its use. MTDR was used for Aralar KD cells. Image Analysis was performed in FIJI (ImageJ, NIH). For the quantification of mitochondrial morphology and area, images stained with TMRE or MTDR were analyzed. Thresholds were adjusted to ensure that even weakly stained mitochondria were detected and included in the analysis. Only the mitochondrial area was evaluated, independent of fluorescence intensity.”

Minor points:

1. __ In the introduction, the authors state that "LDH activity increases in the context of BAT activation". This point is important for the logic of the manuscript, reference [10] cited here is not sufficient to support this claim. It is recommended to provide appropriate references to support this statement.__ Answer 1) We have substantially changed this paragraph in the revised manuscript to better explain why LDH would not act as a major player in contributing to NAD redox balance in the context of BAT thermogenesis, as follows:

“In mammalian cells, cytosolic NAD⁺ is regenerated through lactate dehydrogenase (LDH), the glycerol-3-phosphate shuttle (GPSh), or the malate-aspartate shuttle (MASh). In BAT, however, lactate production rises only slightly with adrenergic activation and most lactate is oxidized via the TCA cycle, suggesting that LDH primarily consumes NAD⁺ rather than regenerating it [PMID: 30456392; PMID: 37337122; PMID: 30456392; PMID: 37802078; PMID: 40982723]. Consequently, mitochondrial redox shuttles become critical for sustaining cytosolic NAD⁺ supply”.

We have also provided additional references to support this new section at the introduction.

__ In Fig. 1A and B-D, there are inconsistencies and duplications in the abbreviation labels. Please check and revise accordingly. __

Answer 2) We thank the reviewer for this comment. We would like to clarify that Figure 1A is a schematic overview of the system, while Figures 1B–D show protein expression in specific contexts: whole BAT (B), whole liver (C), and BAT mitochondria (D). In Figures 1B and 1C, all components are shown because both cytosolic (MDH1 and GOT1) and mitochondrial proteins (MDH2, GOT2, Aralar 1 and 2 and OGC) are present. In contrast, Figure 1D shows only mitochondrial components (OGC, Aralar1, MDH2, and GOT2). Although Aralar2 is a mitochondrial protein, it was not detected in this study (Forner et al., 2009). Similarly, cytosolic components such as MDH1 and GOT1 are not shown in Figure 1D because they are absent in the mitochondrial fraction. We have revised the figure legend to make these distinctions clearer.

__ In Fig. S1, the number of n indicated does not match the number of data points shown. Please clarify whether these represent technical replicates or biological replicates, and provide a detailed description of the statistical methods used throughout the manuscript.__

Answer 3) We thank the reviewer for catching this and allowing us to correct our mistakes. In the revised version, we have corrected the figure legend of Supplementary Figure 1 so that the number of n matches the data points shown.

__ Please provide details on the normalization strategy used in the BODIPY-C12/BODIPY-493 staining analysis, such as whether fluorescence intensity was quantified as mean or integrated values, and whether the analysis was normalized to lipid droplet area, cell number, or baseline. Since lipolytic stimulation can reduce droplet size and increase droplet number, these factors may bias the results. __

Answer 4) We thank the reviewer for this important comment and apologize for the lack of detail regarding this analysis. The analysis of BODIPY-C12 and BODIPY-493 was performed by quantifying the mean fluorescence intensity of BODIPY-C12 detected within a mask generated from the BODIPY-493 signal. This approach allowed us to define all lipid droplets and measure the release of previously esterified C12. To account for variability across samples, the data were normalized to each sample’s individual baseline at time point 0 and expressed as fold change relative to this baseline. In the revised manuscript we have included this description in the Methods section (page 18, last paragraph) for clarity and reproducibility, as following:

“Lipid Droplet area was defined based on Bodipy 493/503 signal, which was used to generate a mask identifying all lipid droplets. Within this mask, the mean fluorescence intensity of BODIPY C12 was quantified over time to monitor the release of previously esterified C12. To account for variability between samples, data were normalized to each sample’s individual baseline at time point 0 and expressed as fold change relative to this baseline.”

__ The manuscript notes that the unexpected result in Fig. 3K-M in parallel with increased Atgl mRNA expression might be because it does not reflect protein levels or enzymatic activity. To strengthen this point, it is recommended to include data on ATGL and phosphorylation ATGL. __

Answer 5) We thank the reviewer for this constructive comment. We have clarified these aspects in the revised Results and Discussion sections to reflect this interpretation more accurately as follows:

“Notably, Atgl mRNA measurement in our study was primarily used as a marker of brown adipocyte differentiation, rather than as a direct indicator of ATGL protein abundance or enzymatic activity. We detected increased Atgl expression only in Ogc KD cells (Fig. S1H), but not in Aralar 1 KD cells (Fig. S1G). This likely does not reflect a major difference in differentiation status, as other brown adipocyte markers and norepinephrine-stimulated respiration were comparable between scramble and knockdown cells (Fig. 2D-G and 2N-O and S1G-H). Although lipolysis was not evaluated in Ogc KD cells, in Aralar 1 KD cells basal lipolysis remained unchanged (Fig. 4D-E and 4G-I), whereas norepinephrine-stimulated lipolysis was delayed or partially inhibited. Notably, the enhanced fatty acid esterification observed in Ogc KD cells despite elevated Atgl expression is not contradictory, since in brown adipocytes lipolysis and re-esterification occur concurrently to sustain high lipid turnover [34].

__ Red-on-black is not a great color code for IMFs, how about black-and-white? __

Answer 6) We have changed color text for white on figures 2H and K as suggested.

__Reviewer #3 __

Major points;

1. __ Although in the manuscript Veliova and coworkers demonstrated that MAS is functional in brown adipocytes showing kinetic parameters equivalent to that previously described in other tissues, surprisingly, when its components are downregulated, no effect, or very little, on mitochondrial respiration is found (figure 2). This is an intriguing result since MAS disruption has been widely reported to impair respiration in different cell types and tissues. However, since no direct evidence of MAS dysfunction is provided, it is possible that MAS may still remain partially or fully functional under the conditions used by the authors, and therefore this point needs to be clarified to validate these results.__ Answer 1) We thank the reviewer for the insightful comment and the opportunity to clarify these important points regarding MASh dysfunction validation in our study. We acknowledge the reviewer’s observation that mitochondrial respiration was largely unaffected by MASh component knockdown, which is indeed intriguing. Importantly, as already indicated in our responses to Reviewer 1, we have provided new data showing direct molecular evidence of MASh impairment through substantial reductions in the aspartate/glutamate ratio in Aralar 1 KD cells (new Supplementary Figure S1F). This ratio is a well-established functional readout reflecting MASh activity and amino acid exchange between cytosol and mitochondria, as demonstrated in original experimental studies of MASh function in multiple tissues including brown adipocytes (PMID: 4436323). The reduction in the aspartate/glutamate ratio directly confirms loss of MASh functionality even though respiratory rates remained unchanged, likely due to metabolic compensation by robust glycerol phosphate shuttle (GPSh) activity, as further supported by our data showing reduced glycerol release upon norepinephrine stimulation in Aralar 1 KD cells cells (Figure 4I). This metabolic rerouting maintains cytosolic NAD⁺ regeneration and partially preserves respiration and energy metabolism under these experimental conditions (PMID: 168075; PMID: 40540398; PMID: 37647199). Thus, the combination of metabolomic, respirometry, and functional lipid data strongly indicates that MASh activity was disrupted specifically and effectively by our genetic interventions. This molecular evidence was already signposted in our original manuscript and responses, underscoring that MASh loss of function—and not residual or compensatory MASh activity—is responsible for the phenotypes reported. We greatly appreciate the reviewer’s insightful attention to this critical mechanistic issue and hope this provides clear reassurance that MASh impairment was indeed achieved and functionally validated within our study framework.

Furthermore, strategies used to downregulate MAS components produce only a partial reduction in mRNA levels, about 70 %, but its outcome on protein levels has not been determined. and the remaining protein level could be sufficient to maintain shuttle activity. Therefore, the effect of silencing at protein level should be analyzed, because as authors also point out on page 16; "mRNA levels may not reflect actual protein levels or activity".

Answer 2) We thank the reviewer for this important point. Our knockdowns resulted in ~70–80% reduction in mRNA levels. While not complete, this represents a substantial decrease and is sufficient to produce strong functional effects. At the time the experiments were performed, we did not have access to suitable antibodies, and the available antibodies did not provide reliable signals in our samples, which is why we used qPCR to estimate knockdown efficiency. Importantly, we observed clear phenotypic changes in both knockdowns (Aralar and OGC), and both showed very similar phenotypes. This suggests that the level of knockdown was sufficient to significantly impair MAS activity. In the revised version we added new data which further validated the functional impact of Aralar KD (given that this protein has an alternative isoform, as pointed out by the reviewer). We performed metabolomics experiments measuring aspartate and glutamate levels. Our new data shows that the aspartate-to-glutamate ratio is significantly reduced in Aralar KD cells. This ratio serves as a proxy for glutamate catabolism, and the observed decrease suggests reduced glutamate catabolism, likely due to impaired MAS activity. Therefore, the reduced whole-cell aspartate/glutamate ratio serves as a metabolic signature of MAS impairment, consistent with Aralar KD. These data indicate that Aralar is sufficiently downregulated to produce a functional effect, supporting our conclusion that MAS activity is impaired. The results have been added as new supplementary Figure 1 as follows:

__ In the case of aspartate/glutamate carriers (AGCs) the role of citrin/slc25a13, the second AGC paralog, should also be analyzed. This AGC isoform is discarded based on proteomic data from brown adipose tissue, but, as it is shown in figure 1B, its levels are similar those of Aralar/slc25a12, the only AGC silenced. Besides, primary brown adipocytes differentiated for 7 days are used here, and it is possible that factors such as culture conditions or differentiation itself could alter AGC levels. Therefore, it is necessary to determine the protein levels of citrin/AGC2, and, if necessary, downregulate it together with the Aralar/AGC1 isoform. citrin/AGC2 activity may be responsible for the observed difference between the OGC and Aralar/AGC1 KD adipocytes.__

Answer 3) We thank the reviewer for this important point. We chose Aralar1 because it is the isoform predominantly expressed in brown adipose tissue (PMID: 23436904). We acknowledge, however, that compensatory increases in Citrin/AGC2 upon Aralar1 knockdown are possible. To address this, we have included new metabolomics data in the revised manuscript (added as Supplementary Figure 1), which provides additional support that downregulation of Aralar1, even if not complete, is sufficient to cause a metabolic change reflected by a reduced aspartate/glutamate ratio in these cells. This functional change supports that the knockdown of Aralar1 alone is sufficient to study its role in brown adipocytes, although minor compensation by Citrin/AGC2 cannot be entirely excluded.

To address this explicitly, we have added a paragraph to the discussion (page 13, 2nd paragraph) highlighting the potential for partial compensation by Citrin/AGC2 and explaining why the observed metabolic effects are still attributable to Aralar 1 knockdown, as follows:

“Phenotypes observed in Aralar 1 KD cells closely resemble those in Ogc KD cells, particularly in terms of lipid metabolism alterations and energy expenditure. The main difference lies in mitochondrial morphology, which is altered in Ogc KD cells but remains unchanged in Aralar 1-silenced cells (Fig. 2J,M). Unlike Ogc, which lacks an alternative isoform, Aralar 1 has a paralog Aralar 2 (Citrin, or SLC25A13) that may partially compensate for its loss. This potential compensation might explain the preservation of mitochondrial morphology in Aralar 1 KD cells. Nonetheless, our metabolomics data demonstrate that downregulation of Aralar 1 alone significantly reduces the aspartate/glutamate ratio (Fig. S1D-F). Since this ratio reflects glutamate catabolism, its decrease indicates impaired malate-aspartate shuttle activity and reduced glutamate catabolism. Therefore, although compensation by Aralar 2 cannot be entirely excluded, Aralar 1 KD alone suffices to cause substantial impairment of malate-aspartate shuttle function”.

• *

__ OGC and Aralar/AGC1 silencing is associated with the accumulation of smaller lipid droplets and impaired norepinephrine-induced lipolysis, but no mechanistical evidence is provided. The authors discuss a role for AMPK signaling associated with the redox unbalance generated by MAS disfunction but neither of them is proven.__

Answer 4) We thank the reviewer for this insightful question, which was also raised by Reviewer 1 (see Reviewer 1, Question 1 above). Here, we aim to clarify the mechanistic basis by which MASh may regulate lipolysis in BAT in a complementary and refined manner.

Our new data directly addresses this issue by examining cytosolic redox status through the lactate/pyruvate ratio, a well-established indicator of NAD⁺/NADH balance. Under basal conditions, Aralar 1 KD cells showed no change in this ratio compared to controls, indicating preserved cytosolic NAD⁺ regeneration despite reduced MASh activity. This observation is consistent with previous studies demonstrating the resilience of cellular redox homeostasis through overlapping NAD⁺-regenerating systems (PMID: 40540398; PMID: 37647199). The new results are shown in Supplementary Figure 1.

At the same time, we detected a marked decrease in the aspartate/glutamate ratio in Aralar 1 KD cells, confirming impaired MASh function and reduced amino acid exchange between cytosol and mitochondria. The lack of redox imbalance likely reflects compensatory mechanisms, most notably the GPSh, which is highly active in brown adipocytes. Supporting this view, Aralar 1 KD cells displayed significantly reduced glycerol release upon norepinephrine stimulation (Fig. 4I), suggesting enhanced metabolic cycling of G3P through mitochondrial and cytosolic G3PDH, thereby sustaining NAD⁺ regeneration and redox equilibrium.

We therefore propose that, although MASh normally facilitates NADH export and aspartate/glutamate exchange, its loss activates GPSh-mediated compensation that preserves cytosolic NAD⁺/NADH balance and maintains lipolytic flux during adrenergic stimulation. These findings refine our mechanistic understanding of how redox shuttle interplay supports glycolytic and lipolytic processes in BAT. Future studies employing NAD⁺/NADH sensors and simultaneous blockade of both shuttles will be essential to dissect these compensatory mechanisms in greater detail.

Minor points;

1. __ Is pyruvate present in respiration medium? If so, no effect on respiration is expected as pyruvate reverses the respiratory defects caused by MAS inactivation. __ Answer 1) Thanks for this important insight. In fact, as indicated in the methods section (page 17, last paragraph) all respirometry experiments were carried out in the absence of pyruvate in the media. Therefore, preserved overall respiratory rates in Aralar 1 and Ogc KD cannot be explained by compensatory pyruvate oxidation present in the media.

__ In figure 4, only data from Aralar KD cells in relation to norepinephrine-stimulated lipolysis are shown. What happens when OGC is silenced? __

Answer 2) This is a very interesting and relevant question. We did not perform the norepinephrine-stimulated lipolysis experiments in Ogc-silenced cells, since in most of the other experiments presented in the manuscript Ogc and Aralar 1 silencing converged to very similar, if not identical, phenotypes. Based on these consistent overlaps, we anticipate that Ogc KD would likely lead to comparable effects on lipolysis as observed in Aralar 1 KD cells. Nonetheless, we fully agree that direct assessment of lipolysis upon Ogc KD would strengthen this conclusion, and we consider this an important aspect for future studies.

__ Nomenclature used for mitochondrial carriers is confusing. Please do not use OGC1 as there is only one isoform. Furthermore, different names for OGC are used in the manuscript; oxoglutarate carrier, malate-ketoglutarate carrier or OGC1/SLC25A11. In the case of citrin/AGC2, Aralar2 is used and is a uncommon designation.__

Answer 3) We corrected all OGC naming in the revised manuscript. We also changed “aralar 2” for “citrin” since this was more commonly used in the literature.

__ Some panels of figures 3 and 4 should be improved. Panels 3J, 3L and 4G are difficult to see. In panel 3J please clarify UT line from untreated/NE, are they not transduced? No equivalents conditions are assayed in Aralar KD and OGC KO cells.__

Answer 4) We thank the reviewer for giving us the opportunity to improve this figure and apologize for the confusing labeling. In the revised version, we have clarified the labels in panels 3J, 3L, and 4G to improve visibility, and we have added descriptions of all abbreviations to the figure legends, accordingly.

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

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Referee #2

Evidence, reproducibility and clarity

This manuscript presents novel findings on the role of the malate-aspartate shuttle (MASh) in brown adipose tissue (BAT). Building on the recent advances in elucidating the contribution of MASh to BAT metabolism, the present study provides new evidence by offering direct biochemical validation using a reconstituted BAT mitochondrial system and by introducing genetic data on the mitochondrial carriers OGC1 and Aralar1, thereby adding significant new insight. However, the following points require further clarification.

Major points:

1. In the current manuscript, mitochondrial morphology (area, aspect ratio, and roundness) was analyzed in OGC1 KD cells using TMRE, whereas MitoTracker Deep Red (MTDR) was used in Aralar1 KD cells. Notably, TMRE is a ΔΨm-dependent probe. The signal intensity can change, or the distribution may reflect alterations in membrane potential rather than true morphological changes. Therefore, the observed differences in OGC1 KD cells based on TMRE staining may be confounded by the dye's functional dependence, potentially biasing the conclusions. It is recommended to evaluate mitochondrial morphology with consistent trackers across conditions. In addition, in the subsequent OCR analysis, mitochondrial area was used for normalization. Please clarify which staining method was employed, and provide justification for its suitability.

Minor points:

1. In the introduction, the authors state that "LDH activity increases in the context of BAT activation". This point is important for the logic of the manuscript, reference [10] cited here is not sufficient to support this claim. It is recommended to provide appropriate references to support this statement.
2. In Fig. 1A and B-D, there are inconsistencies and duplications in the abbreviation labels. Please check and revise accordingly.
3. In Fig. S1, the number of n indicated does not match the number of data points shown. Please clarify whether these represent technical replicates or biological replicates, and provide a detailed description of the statistical methods used throughout the manuscript.
4. Please provide details on the normalization strategy used in the BODIPY-C12/BODIPY-493 staining analysis, such as whether fluorescence intensity was quantified as mean or integrated values, and whether the analysis was normalized to lipid droplet area, cell number, or baseline. Since lipolytic stimulation can reduce droplet size and increase droplet number, these factors may bias the results.
5. The manuscript notes that the unexpected result in Fig. 3K-M in parallel with increased Atgl mRNA expression might be because it does not reflect protein levels or enzymatic activity. To strengthen this point, it is recommended to include data on ATGL and phosphorylation ATGL.
6. Red-on-black is not a great color code for IMFs, how about black-and-white?

Referees cross-commenting

To my opinion, all three reviewers have provided constructive criticism of the work.

Significance

The work dives deeper into mitochondrial function and metabolism of brown adipocytes and, thus, advances our understanding of thermogenesis in an incremental fashion. The work will be relevant to brown adipose tissue researchers and mitochondrial biologist.

Author response:

Reviewer 1:

Comment 1. The reviewer was under the impression that that we did not perform biological replicates of our ChIP-seq experiments. All ChIP-seq (and ATAC-seq) experiments were performed with biological replicates and the Pearson’s correlations (all >0.9) between replicates were provided in Supplementary Table 1. We had indicated this in the text and methods but will try to make this even clearer.

Reviewer 2:

Comment 2. The reviewer states that our claim of H3K115ac being associated with fragile nucleosomes is based solely on MNase sensitivity and fragment length. This is not correct. Figure 3C and D show the results of sucrose gradient sedimentation experiments, followed by ChIP-seq clearly showing that H3K115ac fractionates with chromatin particles that are enriched for fragile nucleosomes and subnucleosomes. By contrast, H3K115ac is not enriched in stable mononucleosome

Comment 3. The reviewer states that our H3K122ac and H3K64ac comparison rely on publicly available datasets. We would emphasize that these are our own datasets generated and published previously (Pradeepa et. al., 2016) but using exactly the same native MNase ChIP protocol as used here for H3K115ac and processed with identical computational pipelines.

Reviewer 3:

Reviewer 3 is mistaken in thinking our ChIP experiments are performed under cross-linked conditions. As clearly stated in the main text and methods, all our ChIP-seq for histone modifications is done on native MNase-digested chromatin – with no cross-linking. This includes the spike-in experiment shown in Fig S1B to test H3K115ac antibody specificity against the bar-coded SNAP-ChIP® K-AcylStat Panel from Epicypher. We could not include H3K115ac bar-coded nucleosomes in that experiment since they are not available in the panel. 

Following that, we would propose to make minor revisions in response to specific reviewer recommendations before posting a version of record. These would include:

(1) Figure 2: title needs change: "H3K115ac marks CpG island promoters poised for activation". this is to make sure it reads with the title for the corresponding section in the main text. Also see: Reviewer 1 comment 7 in Recommendations part. 

(2) Figure S2B: legend should read: "Gene ontology analysis for the set of genes analysed in Figure 2C"

(3) Figure F4D: Provide the replicates for western blot 

(4) Figure 4A,B: Corrected formatting issues.

Author response:

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

Reviewer #1 (Public review): 

The manuscript by Bru et al. focuses on the role of vacuoles as a phosphate buffering system for yeast cells. The authors describe here the crosstalk between the vacuole and the cytosol using a combination of in vitro analyses of vacuoles and in vivo assays. They show that the luminal polyphosphatases of the vacuole can hydrolyse polyphosphates to generate inorganic phosphate, yet they are inhibited by high

concentrations. This balances the synthesis of polyphosphates against the inorganic phosphate pool. Their data further show that the Pho91 transporter provides a valve for the cytosol as it gets activated by a decline in inositol pyrophosphate levels. The authors thus demonstrate how the vacuole functions as a phosphate buffering system to maintain a constant cytosolic inorganic phosphate pool. 

This is a very consistent and well-written manuscript with a number of convincing experiments, where the authors use isolated vacuoles and cellular read-out systems to demonstrate the interplay of polyphosphate synthesis, hydrolysis, and release. The beauty of this system the authors present is the clear correlation between product inhibition and the role of Pho91 as a valve to release Pi to the cytosol to replenish the cytosolic pool. I find the paper overall an excellent fit and only have a few issues, including: 

(1) Figure 3: The authors use in their assays 1 mM ZnCl2 or 1mM MgCl2. Is this concentration in the range of the vacuolar luminal ion concentration? Did they also test the effect of Ca2+, as this ion is also highly concentrated in the lumen? 

The concentrations inside vacuoles reach those values. However, given that polyP can chelate divalent metal ions, what would matter are the concentrations of free Zn²⁺ or Mg²⁺ inside the organelle. These are not known. This is not critical since we use those two conditions only as a convenient tool to differentiate Ppn1 and Ppn2 activity in vitro. In our initial characterisation of Ppn2 (10.1242/jcs.201061), we had also tested Mn, Co, Ca, Ni, Cu. Only Zn and Co supported activity. Ca did not. Andreeva et al. (10.1016/j.biochi.2019.06.001) reached similar conclusions and extended our results.

(2) Regarding the concentration of 30 mM K-PI, did the authors also use higher and lower concentrations? I agree that there is inhibition by 30 mM, but they cannot derive conclusions on the luminal concentration if they use just one in their assay. A titration is necessary here. 

The concentration of 30 mM was not chosen arbitrarily. It is the luminal Pⁱ concentration that the vacuoles reached through polyP synthesis and hydrolysis when they entered a plateau of luminal Pⁱ. We consider this as an upper limit because polyP kept increasing which luminal Pⁱ did not. Thus, there is no physiological motivation for trying higher values. We have nevertheless added a titration to the revised version (new Fig. 3A).

(3) What are the consequences on vacuole morphology if the cells lack Pho91? 

We had not observed significant abnormalities during a screen of the genome-wide deletion collection of yeast (10.1371/journal.pone.0054160), nor in other experiments with pho91 mutants, which we have not included in this manuscript due to a lack of effect.

(4) Discussion: The authors do not refer to the effect of calcium, even though I would expect that the levels of the counterion should affect the phosphate metabolism. I would appreciate it if they would extend their discussion accordingly. 

The situation is much more complex because Ca2+ is not the only counterion. Major pools of counterions (up to hundreds of mM) are constituted by vacuolar lysine, arginine, polyamines, Mg, Zn etc. Their interplay with polyP is probably complex and worth to be treated in a dedicated project. If we wanted to limit the discussion of this complexity not to the simple statement that it is not understood, which is not very useful, we would have to engage in a lot of speculation. We feel that this would make the discussion lose focus and not contribute concrete insights.

(5) I would appreciate a brief discussion on how phosphate sensing and control are done in human cells. Do they use a similar lysosomal buffer system? 

Mammalian cells have their Pi exporter XPR1 mainly on a lysosome-like compartment (10.1016/j.celrep.2024.114316). Whether and how it functions there for Pi export from the cytosol is not entirely clear. We have addressed this situation in the revised discussion section.

Reviewer #2 (Public review): 

Summary: 

This manuscript presents a well-conceived and concise study that significantly advances our understanding of polyphosphate (polyP) metabolism and its role in cytosolic phosphate (Pi) homeostasis in a model unicellular eukaryote. The authors provide evidence that yeast vacuoles function as dynamic regulatory buffers for Pi homeostasis, integrating polyP synthesis, storage, and hydrolysis in response to cellular metabolic demands. The work is methodologically sound and offers valuable insights into the conserved mechanisms of phosphate regulation across eukaryotes. 

Strengths: 

The results demonstrate that the vacuolar transporter chaperone (VTC) complex, in conjunction with luminal polyphosphatases (Ppn1/Ppn2) and the Pi exporter Pho91, establishes a finely tuned feedback system that balances cytosolic Pi levels. Under Pi-replete conditions, inositol pyrophosphates (InsPPs) promote polyP synthesis and storage while inhibiting polyP hydrolysis, leading to vacuolar Pi accumulation. 

Conversely, Pi scarcity triggers InsPP depletion, activating Pho91-mediated Pi export and polyP mobilization to sustain cytosolic phosphate levels. This regulatory circuit ensures metabolic flexibility, particularly during critical processes such as glycolysis, nucleotide synthesis, and cell cycle progression, where phosphate demand fluctuates dramatically. 

From my viewpoint, one of the most important findings is the demonstration that vacuoles act as a rapidly accessible Pi reservoir, capable of switching between storage (as polyP) and release (as free Pi) in response to metabolic cues. The energetic cost of polyP synthesis-driven by ATP and the vacuolar proton gradient-highlights the evolutionary importance of this buffering system. The study also draws parallels between yeast vacuoles and acidocalcisomes in other eukaryotes, such as Trypanosoma and Chlamydomonas, suggesting a conserved role for these organelles in phosphate homeostasis. 

Weaknesses: 

While the manuscript is highly insightful, referring to yeast vacuoles as "acidocalcisome-like" may warrant further discussion. Canonical acidocalcisomes are structurally and chemically distinct (e.g., electrondense, in most cases spherical, and not routinely subjected to morphological changes, and enriched with specific ions), whereas yeast vacuoles have well-established roles beyond phosphate storage. A comment on this terminology could strengthen the comparative analysis and avoid potential confusion in the field.  

Yeast vacuoles show all major chemical features of acidocalcisomes. They are acidified, contain high concentrations of Ca, polyP (which make them electron-dense, too), other divalent ions, such as Mg, Zn, Mn etc, and high concentrations of basic amino acids. Thus, they clearly have an acidocalcisome-like character. In addition, they have hydrolytic, lysosomelike functions and, depending on the strain background, they can be larger than acidocalcisomes described e.g. in protists. We have elaborated on this point in the introduction of the revised version.

Reviewer #3 (Public review): 

Bru et al. investigated how inorganic phosphate (Pi) is buffered in cells using S. cerevisiae as a model. Pi is stored in cells in the form of polyphosphates in acidocalcisomes. In S. cerevisiae, the vacuole, which is the yeast lysosome, also fulfills the function of Pi storage organelle. Therefore, yeast is an ideal system to study Pi storage and mobilization. 

They can recapitulate in their previously established system, using isolated yeast vacuoles, findings from their own and other groups. They integrate the available data and propose a working model of feedback loops to control the level of Pi on the cellular level. 

This is a solid study, in which the biological significance of their findings is not entirely clear. The data analysis and statistical significance need to be improved and included, respectively. The manuscript would have benefited from rigorously testing the model, which would also have increased the impact of the study. 

It is not clear to us what the reviewer would see as a more rigorous test of the model.  

Reviewer #1 (Recommendations for the authors): 

(1) Figure 2: Why do the authors label the blue curve in A and B as BY and in C and D as WT? Is this a different genetic background they used here? This should be specified in the legend. 

No, it is the same background. The figures had been reshuffled before submission and we overlooked to replace "BY" by "WT". This has been corrected. Now we consistently use WT in all figures

(2) Figure 4 has different scaling for the two panels, which should be labeled as A and B. I am aware that the authors do this for comparison, but it is rather confusing at first glance. I recommend having them at the same scale. 

We chose this representation on two separate scales because this figure shall primarily illustrate that the shift between pho91 and WT curves vanishes in the presence of IP7. We now highlight in the figure legend that the scales are different to avoid confusion.  

(3) Figure 8: I would appreciate a model with normal and low Pi concentrations in comparison, as this is what the authors worked out. 

We have modified the figure. It now compares Pi-rich and Pi-limited scenarios.

(4) Minor issue: Wouldn't it make more sense to show the molar concentration in the Figures rather than the nmol of Pi/ug of protein? I am aware that this would require information on the vacuole volume rather than the reaction volume, and the authors do this calculation later on. 

It depends. We often chose this representation because it illustrates the price to pay (metabolic input in terms of protein that must be dedicated to this task) to sequester a certain quantity of Pⁱ. But, as we provide the corresponding Pⁱ concentration in the text, this information is accessible to the reader, too.

Reviewer #2 (Recommendations for the authors): 

As stated above in the weaknesses section, while functional parallels exist, canonical acidocalcisomes are structurally and chemically distinct, typically smaller, electron-dense, and enriched with cations. Whereas yeast vacuoles are larger, multifunctional organelles with well-established roles beyond phosphate storage. Explicitly addressing these differences would strengthen the comparative framework and prevent potential confusion in interpreting the evolutionary relationships between these organelles. 

We agree to some degree, which is the reason why we refer to vacuoles as acidocalcisome-like organelles. In fact, vacuoles share virtually all defining chemical traits of acidocalcisomes. They just have a second functional domain as hydrolytic, lysosome-like organelles. Given the plasticity of endo-lysosomal compartments, and acidocalcisomes belong to this group because of their biogenesis through the AP3 pathway, this is not shocking to us. But the reviewer's comment made us realize that it is better to explicitly address this point. We have added a section to the introduction to do this.

Reviewer #3 (Recommendations for the authors): 

(1) Page 8: It is unclear why the authors only estimated the Pi concentration in wild-type vacuoles. This should also be done for vacuoles from other strains. 

This information is inherent in Figure 2. PolyP hyperaccumulating strains show the same plateau as the wildtype, meaning that they also reach around 30 mM luminal Pi concentration, whereas vtc4 vacuoles reach only around 1/10th of that increase, indicating that they remain at 3 mM. We mention this now in the text.

(2) The attempts of the localization of Pho91 through tagging are not satisfactory. The author described different localizations for Pho91 depending on whether it was tagged on the N- or C-terminus or when Nterminally tagged and overexpressed using two strong promoters. While it is not uncommon that proteins show different localization patterns, depending on where the tag is inserted, it is possible that one of the tags would reflect the localization of the endogenous protein. There is an easy way to test this, in particular when Pho91 is endogenously tagged. pho91∆ has reported phenotypes such as abnormal vacuolar morphology or increased autophagy. They could also measure PI content in vacuoles. The authors could compare the phenotypes of the endogenously tagged strains with WT and a pho91∆ strain. 

Indeed, the attempts to localise the protein through fluorescent tags are unsatisfactory, in our hands as in the hands of others. We would not have created a series of many different tagged versions (we present only a selection of these in the manuscript) if the creation of a faithful reporter for Pho91 localisation were so straightforward. Expression from the endogenous promoter yields quite low signals (which is why others have overexpressed their GFP fusion from strong promotors). But overexpression brings at least a significant part of the protein to the cell surface, where it can then function as Pi importer and suffice to restore much of the maximal Pi uptake capacity that genuine plasma membrane transporters provide and support normal growth of the cells (Wykoff & O’Shea, 2001). But the localisation pattern of Pho91-GFP, likewise overexpressed from a strong promotor, does not reflect this plasma membrane localisation (see the references that the reviewer mentioned under (3)). The published overexpressed GFP-fusions localise only to the vacuole, suggesting that even in this case the GFP tag may create an artefact. Therefore, we went through a large variety of Pho91 gene fusions, which led us to the conclusion that the protein is very sensitive to tags at both ends and that fusion proteins hence are unlikely to reliably report the correct location of the protein. Given this, we resorted to quantitative proteomics to clarify the issue. This quantitative experiment goes beyond previously published proteomics analyses that the reviewer mentions under (3), which found the protein in the vacuolar fraction but did not calculate the enrichment factors, which is crucial. 

A strong phenotype of abnormal vacuolar morphology is not apparent in our cultures. 

(3) Moreover, Pho91 has been identified as a component enriched in vacuolar-mitochondria contact sites (vCLAMP), and this localization was confirmed with GFP-Pho91 (PMID: 25026036). Likewise, PMID: 35175277 also detected Pho91 by mass spectrometry as a vacuolar protein and showed endogenously tagged GFP-Pho91 on the vacuole (co-staining with Vph1). The authors may request the strains from the authors of these papers and use them for their experiments. PMID: 17804816, the oldest of the three reports (from 2007) reports a GFP-Pho91 under either TEF or ADH promoter that localizes to the vacuole. They also showed that the fusion protein is functional. These and other experiments led them to conclude that Pho91 exports phosphate from the vacuolar lumen to the cytoplasma. 

We have now included these references. As argued above, we have analysed also the strains from PMID17804816. The observed clear localisation of the fusion protein to vacuoles is only visible upon overexpression, not upon expression from the endogenous locus. Apparently also this construct is unlikely to report Pho91 localisation reliably (though, by chance, overexpression leads it to the correct location). Thus, we maintain our conclusion that C- or N-terminally GFP-tagged versions of Pho91 are unreliable tools for localising the protein.

(4) The impact of pho91∆ on Pho4-GFP nuclear localization is modest at best (increase from 5% of cells showing Pho4-GFP in the nucleus in WT vs 10% in pho91∆), and only somewhat stronger in ppn1∆/ppn2∆. This means 90% of pho91∆ cells do not respond, and Pho4-GFP stays cytoplasmic. It is unclear how the author can derive a meaningful conclusion from these data. Moreover, are these data really supporting the model, or do these data rather indicate that there are additional factors/pathways needed? What is the biological significance of the marginal increase from 5% to 10% of cells that would respond? What happens to the cells that cannot respond? Will they die or at least have a growth disadvantage? It would be useful to provide some functional studies. 

We should have explained the nature of the assay better. The experiment exploits the fact that dividing yeast cells transiently fall into a state of Pi scarcity during S-phase. Since S-phase is less than a quarter of the cell cycle, only a small fraction of the cells transiently activates the PHO pathway. These cannot be well characterised by ensemble assays, but microscopy circumvents this background of the whole population and picks them up very clearly, allowing to quantify them. We have adapted the respective chapter in the results section to improve the description of this experiment.

(5) The quantification of the data is suboptimal, as in most assays the mean and standard error of the mean (SEM) are given. SEM is not really appropriate in these cases because it gives only the error of the mean and not of the entire data. Therefore, the standard deviation (SD) is needed, which reports on the variability of the data, and which is usually much larger than the SEM. Using the SD, would also allow the authors to do proper statistical analysis, which is missing entirely in this manuscript. 

SEM also comprises the variability of the data. It is linked with the SD (SEM=SD/SQRT(n)), but SEM also considers the number of the experiments n. The main goal is to compare the means, and SEM is an appropriate and frequently used tool for this because it illustrates how well the arithmetic mean may estimate the true mean of the population. Therefore, we kept the SEM but have added tests of significance for the differences shown.

(6) Statistical testing in Figure 7 is essential as the effects are very small. Again, are these changes big enough for a biologically meaningful response? The authors should at least discuss this. 

Our previous time course analyses of InsPP dynamics, performed under comparable conditions as in this study, showed that InsP8 decreases by around 50% in the first 30 min after transfer to Pi starvation (DOI: https://doi.org/10.7554/eLife.87956) and that this decline is already sufficient to trigger the PHO starvation program, as assessed by Pho4-GFP translocation into the nucleus. Thus, a 50% decrease, which is observed in ppn1 ppn2 mutants, is functionally significant. We have now also evaluated statistical significance in Fig. 7, which is given for the 50% reduction of InsP8 and 1-InsP7 in ppn1 ppn2. 

Minor points: 

(1) There are a number of smaller edits (use of italic or better the absence thereof, lacking information in the reference list, and some typos). 

Thank you. We have corrected those.

(2) The exact n should be given in the Figure legend. 

Corrected.

(3) Page 8, line 8: it would be nice to have a picture of the wild-type vacuoles and what you measured. 

We now present a sample image in the new Suppl. Fig. 1.

(4) PMID: 11779791 showed already that Pho91 cannot rescue the absence of the plasma membrane Pi transporters. This study should be at least cited. 

This is not quite correct. The study that the reviewer mentions showed that Pho91 supports slower growth and the authors concluded that "A synthetic lethal phenotype was observed when (all) five phosphate transporters were inactivated...". We had cited the same group and the same first author, just using their later study (Wykoff et al., 2007) that had recapitulated the results from PMID11779791 and showed in addition quite good growth of the PHO91 expressing strain on YPD (Suppl. Fig. 2). We had obtained the strains from this group. In reproducing their experiments, we noticed that the growth of Pho91 that these authors had observed is due to incomplete repression of Pho84. They had overexpressed Pho84 from a galactose inducible promotor to generate a background with a regulatable Pi transporter. This trick allowed them to conveniently manipulate the strain and reduce (but not abolish) Pho84 expression by transferring the cells from galactose to glucose for their experiments. Therefore, we chose a more rigorous plasmid shuffling strategy to test the individual P_i transporter, which allows an assessment without the leaky background expression of Pho84 on glucose. In contrast to O'Shea and colleagues, we observed zero growth of a strain expressing only PHO91. We have revised the results section to make this discrepancy more evident and provide a better motivation for our experiment.

(5) It would be nice to see the actual data in Figure 6; not only a quantification. 

We illustrate the phenotype of nuclear Pho4-GFP in panel A. Showing all the images necessary to appreciate the differences between the strains would require including many dozens of images into the figure, which would not be useful.

Synthèse du Webinaire : « Mon enfant est différent. Et alors ? »

Résumé

Ce document de synthèse analyse les informations clés du webinaire « Mon enfant est différent. Et alors ? », organisé par la Fédération des Conseils de Parents d'Élèves (FCPE).

L'événement visait à informer, dédramatiser et fournir des outils concrets aux familles d'enfants présentant des spécificités neurodéveloppementales.

En partenariat avec trois associations expertes — **HyperSupers -

• TDAH France**,
• la Fédération Française des DYS (FFDYS) et
• l'Association Nationale Pour les Enfants Intellectuellement Précoces (ANPEIP) —,

le webinaire a abordé le

• Trouble du Déficit de l'Attention avec ou sans Hyperactivité (TDAH),
• les troubles DYS, et
• le Haut Potentiel Intellectuel (HPI).

Les points essentiels qui en ressortent sont :

1. Prévalence et Normalisation : Les troubles et spécificités abordés sont courants, représentant en moyenne plus d'un élève par classe en France.

Il est crucial de comprendre qu'il s'agit de conditions neurodéveloppementales, et non de conséquences d'une mauvaise éducation parentale ou d'un manque d'efforts de la part de l'enfant.

2. Importance du Diagnostic : Un repérage précoce et un diagnostic précis et différentiel sont fondamentaux. Ils permettent de mettre en place un accompagnement adapté, d'éviter les interprétations erronées des comportements de l'enfant (paresse, provocation) et de prévenir la dégradation de l'estime de soi.

3. Vers une École Inclusive : L'inclusion scolaire est un droit et une nécessité. La clé réside dans une collaboration étroite entre les parents, les équipes éducatives et les associations.

La FCPE réaffirme que « l'école inclusive, ce n'est pas une école à part, c'est l'école pour toutes et tous ».

4. Ressources et Soutien : Des dispositifs d'accompagnement scolaire (PAI, PAP, PPS) existent pour répondre aux besoins spécifiques des élèves.

Les associations jouent un rôle indispensable en offrant une expertise, des ressources documentaires, une formation et un soutien par les pairs, brisant ainsi l'isolement souvent ressenti par les familles.

Contexte et Objectifs du Webinaire

Organisé par la FCPE et animé par Aline, secrétaire générale adjointe, le webinaire a été conçu comme un « moment d'échange utile, bienveillant et concret ».

L'objectif principal était de répondre à la préoccupation de nombreux parents : « Mon enfant ne rentre pas tout à fait dans les cases, comment l'aider à s'épanouir à l'école ? ».

Le constat de départ est que ces différences, bien que faisant « partie du paysage ordinaire de l'école », sont trop souvent « ni suffisamment repérées ni suffisamment accompagnées ».

Prévalence des Troubles et Spécificités en Milieu Scolaire

Catégorie

Prévalence

Représentation en Classe

Troubles DYS

5 à 8 % des enfants

Environ 1 à 2 élèves par classe

TDAH

Environ 5 % des enfants

Environ 1 élève par classe

Haut Potentiel Intellectuel (HPI)

2 à 3 % des enfants

Environ 1 élève par classe

Total combiné

> 10 % des élèves

Plus d'un enfant par classe en moyenne

Analyse des Troubles et Spécificités

1. Le Trouble du Déficit de l’Attention avec ou sans Hyperactivité (TDAH)

Présenté par Daniel de HyperSupers - TDAH France, le TDAH est un trouble du neurodéveloppement (TND) qui affecte les fonctions cérébrales liées à l'organisation de la pensée, la mémoire, la communication et l'apprentissage.

• Symptômes Cardinaux : Le TDAH se manifeste à travers trois axes principaux dont l'intensité varie selon les individus :

◦ Inattention : Difficulté à maintenir son attention, oublis fréquents, tendance à être distrait ("dans la lune"), évitement des tâches exigeant une concentration soutenue.

C'est le symptôme le plus persistant à l'âge adulte.  

◦ Hyperactivité : Agitation motrice incessante chez l'enfant, qui se transforme souvent en hyperactivité mentale (idées qui fusent) à l'adolescence et à l'âge adulte.  

◦ Impulsivité : Difficulté à attendre son tour, tendance à interrompre les autres, réponses précipitées avant la fin d'une question.

• Prévalence et Comorbidités :

◦ Touche environ 5 % des enfants (350 000 en France) et 3 % des adultes.  

◦ Les garçons sont deux fois plus fréquemment diagnostiqués, mais le trouble est sous-diagnostiqué chez les filles, où l'inattention est souvent le symptôme prédominant.  

◦ 50 % des personnes avec TDAH présentent au moins un trouble associé (comorbidité), comme des troubles DYS, un trouble du spectre de l'autisme, des troubles anxieux ou dépressifs, ou un trouble oppositionnel avec provocation.

• Diagnostic et Prise en Charge :

◦ Le diagnostic est clinique et se base sur des questionnaires validés (ex: DSM-5), qui exigent que les symptômes soient présents avant 12 ans, dans au moins deux sphères de vie (école, famille), et qu'ils aient un impact significatif sur la qualité de vie.  

◦ La prise en charge est multimodale : psychoéducation (expliquer le trouble à l'enfant et aux parents), aménagements scolaires (PAP, PPS), guidance parentale (ex: méthode Barkley), et éventuellement un traitement médicamenteux.

• Impact Scolaire : L'élève avec TDAH peut être perçu comme rêveur, perturbateur ou paresseux.

Il a du mal à suivre les consignes, perd ses affaires et fournit un rendement scolaire faible malgré une grande dépense d'énergie, ce qui entraîne une fatigue importante et une baisse de l'estime de soi.

2. Les Troubles Spécifiques des Apprentissages (Troubles DYS)

Présentés par Fabienne de la Fédération Française des DYS (FFDYS), les troubles DYS sont également des troubles du neurodéveloppement.

• Principes Fondamentaux :

◦ Ils ne sont ni une maladie (on n'en guérit pas), ni un trouble psychique, ni une déficience intellectuelle ou sensorielle. L'intelligence est préservée.  

◦ Ils ne sont pas dus à un manque de stimulation ou à un environnement socioculturel défavorable.  

◦ Leur caractéristique centrale est une difficulté à automatiser certaines fonctions cognitives, ce qui oblige l'enfant à être en surcharge cognitive permanente, provoquant une grande lenteur et une fatigue intense.

• Les Différents Troubles DYS :

◦ Dyslexie / Dysorthographie : Trouble de l'identification des mots écrits. La lecture est lente, hachée (déchiffrage), ce qui entrave l'accès au sens.

Il s'accompagne quasi systématiquement d'une dysorthographie (difficulté à automatiser les règles orthographiques).  

◦ Dysphasie (Trouble Développemental du Langage) : Trouble de la communication orale, affectant la compréhension et/ou l'expression. L'enfant doit faire un effort majeur pour comprendre les consignes orales et pour se faire comprendre.  

◦ Dyscalculie : Trouble de la cognition logico-mathématique, affectant la compréhension du sens du nombre, des quantités et des opérations.  

◦ Dyspraxie (Trouble Développemental de la Coordination) / Dysgraphie : Trouble de la planification et de l'automatisation des gestes.

L'enfant est qualifié de "maladroit", a des difficultés avec la motricité fine (écriture, laçage, utilisation des couverts), l'organisation spatiale (géométrie, lecture de tableaux) et la gestion du temps.

3. Le Haut Potentiel Intellectuel (HPI)

Présenté par Frédéric de l'ANPEIP, le HPI n'est pas un trouble mais une spécificité reconnue par l'Éducation Nationale comme un "besoin éducatif particulier".

• Définition et Identification :

◦ Il se caractérise par un fonctionnement intellectuel qualitativement différent, validé par des études en neuro-imagerie.   

◦ L'identification repose sur un bilan psychologique complet réalisé par un professionnel, et ne se résume pas à un chiffre de QI (supérieur à 130). Le bilan analyse l'estime de soi, l'anxiété, les relations sociales, etc.  

◦ Un individu ne se résume pas à un chiffre.

• Caractéristiques :

◦ Questionnements incessants sur des sujets existentiels (vie, mort), grande curiosité.   

◦ Compréhension très rapide, capacité à faire des liens et des raccourcis.  

◦ Grande sensibilité et sens critique développé très tôt.

• Concepts Clés :

◦ Dyssynchronie : Un décalage entre le développement intellectuel (souvent en avance) et les développements affectif, social ou psychomoteur (qui correspondent à l'âge réel).

Un enfant de 6 ans peut avoir une pensée très mature mais la motricité d'un enfant de son âge, rendant l'écriture difficile.  

◦ Double ou Triple Spécificité : Un enfant HPI peut également présenter un TDAH et/ou des troubles DYS.

Le HPI peut alors masquer les troubles pendant un temps, rendant le diagnostic complexe et souvent tardif (fin de collège ou lycée).

• Impact Scolaire : Le décalage peut mener à l'ennui, à un désinvestissement et à des difficultés de socialisation. L'appréciation "peut mieux faire, a des capacités mais ne les exploite pas" est fréquente.

L'Accompagnement des Enfants et le Soutien aux Familles

Le Rôle de la FCPE

La FCPE, en tant qu'association nationale de parents d'élèves, est présente à toutes les strates du système éducatif.

• Représentation : Elle siège dans les instances nationales, régionales, départementales et locales (conseil d'école, conseil d'administration, CESCE, commissions d'appel, etc.).

• Partenariats : Elle collabore avec les municipalités, les académies, les ministères, mais aussi avec des organismes comme la CDAPH (Commission des droits et de l'autonomie des personnes handicapées), la CPAM, l'ARS et la MDA (Maison des Adolescents).

• Missions : Elle porte une attention particulière aux droits de l'enfant et au respect des besoins éducatifs particuliers. Elle fait partie de collectifs comme le Réseau Éducation Sans Frontières (RESF) pour accompagner les familles en situation de précarité.

Le Soutien des Associations Partenaires

Chaque association offre un soutien crucial basé sur l'expertise et la pair-aidance.

Association

Actions et Ressources Clés

HyperSupers - TDAH France

• - Soutien par les pairs : Groupes de parole (GSP), forums en ligne, hotline "SOS Rentrée Scolaire".<br>\
• • Ressources : Site internet (tdah-france.fr), brochures, livres, web-documentaires, chaîne YouTube.<br>\
• • Formation : Modules de formation en ligne pour les adhérents.<br>\
• • Plaidoyer : Représentation dans les instances nationales de santé et du handicap.

Fédération Française des DYS (FFDYS)

• - Réseau Local : Fédération de 150 associations locales accessibles via une carte sur le site ffdys.com.<br>\
• • Événements : Journée Nationale des DYS, colloques scientifiques (disponibles en replay).<br>\
• • Information : Podcasts, vidéos, guides pratiques (orientation, emploi).<br>\
• • Formation : Organisme de formation pour les professionnels de l'éducation, de la santé et de l'emploi.

ANPEIP

• - Réseau Régional : Fédération de 14 associations régionales.<br>\
• • Rupture de l'isolement : Cafés parents, sorties, ateliers pour enfants et adolescents pour qu'ils se retrouvent entre pairs.<br>\
• • Information : Conférences et ateliers pour démystifier le HPI.<br>\
• • Plaidoyer : Partenaire de l'Éducation Nationale, travaille à l'harmonisation des pratiques et à la mise à jour des documents officiels (Vade-mecum HPI).

Citations Clés

Aline (FCPE) : « Une école inclusive, ce n'est pas une école à part, c'est l'école pour toutes et tous. »

Fabienne (FFDYS) : « [Les troubles DYS] ce ne sont pas des maladies, ce qui veut dire qu'on n'en guérit pas. On va garder ces troubles tout au long de sa vie. »

Frédéric (ANPEIP) : « Un individu ne se résume pas à un chiffre. »

Daniel (TDAH France), à propos des adultes diagnostiqués tardivement : « Croyez-moi, c'est une libération pour ces adultes là, ils repartent d'un pied nouveau. »

DOI: 10.1080/21505594.2025.2580132

Resource: (WB Cat# WBStrain00041969,RRID:WB-STRAIN:WBStrain00041969)

Curator: @sonofthor

SciCrunch record: RRID:WB-STRAIN:WBStrain00041969

What is this?

DOI: 10.1002/cpz1.70210

Resource: None

Curator: @olekpark

SciCrunch record: RRID:Addgene_199726

What is this?

There aren’t strict rules for teaching with translanguaging, but the authors suggest things like pairing students by skill level, grouping them by language background, using words that sound similar in both languages, and using different ways to communicate. They stress the importance of being open, taking risks, and focusing on fairness and justice in the classroom. However, schools rarely teach or test translanguaging directly.

The authors argue that just talking about ‘languaging’ isn’t enough. Translanguaging means using all your language skills in flexible ways, depending on the situation, and recognizing that language and bilingualism are shaped by society.

The authors explain that the way people think about language has changed over time. They mention that languages are not natural categories but are created by society, often to support things like colonialism or national identity we see even today.

García and Wei base their ideas on newer theories about language. They disagree with older thinkers who saw language as fixed and separate. Instead, they support the view that language is always changing and shaped by its social context

The book “Translanguaging: language, bilingualism and education” by Ofelia García and Li Wei introduces the idea of translanguaging. The authors believe it’s more than just a teaching trick it should be seen as a powerful classroom tool that can change how we think about language and challenge old rules about which languages matter most.

It could be a cognitive distortion (a faulty way of processing social cues) that develops in response to the chronic negative feedback from peers.

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5.

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Náhled na Zápis ze Strategického dne

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Synthèse du Webinaire : Concilier les Enjeux de l'Alimentation Durable et la Précarité

Résumé

Ce document de synthèse résume les échanges du webinaire "Comment concilier les 4 enjeux de l'alimentation durable et la précarité ?", organisé par le CRES et le GRAINE PACA.

Il met en lumière la complexité de la précarité alimentaire, un phénomène hétérogène et difficile à quantifier, qui toucherait environ 8 millions de personnes en France.

La région PACA se distingue par un taux de pauvreté élevé, le troisième plus important de France, exacerbant les inégalités d'accès à une alimentation de qualité.

Les interventions scientifiques ont démontré que les quatre piliers de l'alimentation durable (nutrition/santé, environnement, socio-économique, socio-culturel) ne convergent pas naturellement.

Cependant, des études approfondies révèlent qu'un régime alimentaire à la fois sain et à faible impact environnemental peut être moins coûteux.

La clé réside dans une "végétalisation saine" de l'alimentation : une réduction de la consommation de produits animaux, notamment la viande de ruminant, compensée par un apport accru en céréales complètes, légumineuses, fruits et légumes.

La région PACA dispose d'un écosystème structuré pour aborder ces défis, avec des instances de coordination comme la COALIM et des réseaux thématiques (Précalim, Éducalim, Régalim, PAT) visant à décloisonner les approches.

Des programmes nationaux comme "Mieux Manger Pour Tous" et des réglementations telles que la loi EGalim offrent des cadres financiers et légaux pour transformer les systèmes alimentaires, y compris l'aide alimentaire.

Enfin, l'étude de cas de l'épicerie sociale de Mouans-Sartoux illustre une transition réussie d'un modèle d'aide basé sur les invendus à une offre de produits frais, bio et locaux.

Cette transformation, rendue possible par la volonté politique, des partenariats stratégiques (Biocoop, producteurs locaux) et l'accès à des financements dédiés, prouve qu'il est possible d'améliorer radicalement la qualité et la durabilité de l'aide alimentaire tout en respectant la dignité des bénéficiaires.

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1. Introduction et Contexte du Webinaire

Organisé par le CRES PACA (Comité Régional d'Éducation pour la Santé) et le GRAINE PACA (Réseau Régional pour l'Éducation à l'Environnement et au Développement Durable), ce webinaire a bénéficié du soutien financier de la DREAL, et a été mené en partenariat avec la DRAF et l'ADEME Provence-Alpes-Côte d'Azur.

Il s'inscrit dans le cadre du programme Mieux Manger Pour Tous et fait partie d'un cycle de deux webinaires portés par deux réseaux régionaux majeurs :

• Précalim : Réseau régional de lutte contre la précarité alimentaire.

• Éducalim : Réseau régional de l'éducation à l'alimentation durable et au goût.

Les objectifs principaux du webinaire étaient les suivants :

• Approfondir les connaissances sur la notion d'alimentation durable et les leviers pour concilier ses enjeux chez les personnes en situation de précarité.

• Identifier les principales réglementations liées à l'alimentation durable pour tous.

• Découvrir une action de terrain inspirante et reproductible.

2. Le Cadre Stratégique et les Réseaux d'Acteurs en Région PACA

2.1. L'Écosystème Régional pour une Alimentation Durable

Présenté par Peggy Bucas (DRAF), le maillage régional en PACA est conçu pour maximiser l'efficacité des actions en faveur de l'alimentation durable.

• La COALIM : Cette instance réunit les institutions régionales (DRAF, DREAL, DREETS, ARS, ADEME, Région) qui pilotent des missions et des financements liés à l'alimentation durable. Elle assure une concertation et une complémentarité des actions.

• Les Réseaux Thématiques Régionaux : Quatre réseaux principaux apportent un soutien thématique et méthodologique aux porteurs de projet.

◦ Précalim : Focalisé sur la lutte contre la précarité alimentaire.    ◦ Éducalim : Centré sur l'éducation à l'alimentation durable et au goût.    ◦ Régalim : Dédié à la lutte contre le gaspillage et les pertes alimentaires.    ◦ Réseau des PAT : Anime les 29 Projets Alimentaires Territoriaux (PAT) de la région.

Les PAT sont des leviers essentiels pour favoriser les coopérations, casser les fonctionnements en silo et développer une approche systémique. Ils ont pour mission d'intégrer un volet "justice sociale" pour réduire la précarité alimentaire.

2.2. Le Réseau Précalim et le Programme "Mieux Manger Pour Tous"

Présentés par Sandrine Fort (DREETS), le réseau Précalim et le programme MMPT sont des piliers de la lutte contre la précarité alimentaire dans la région.

Le Réseau Précalim :

• Membres : Près de 600 membres (institutions, associations, collectivités). Un appel est lancé pour intégrer davantage d'acteurs agricoles.

• Objectifs :

◦ Créer de l'interconnaissance entre les acteurs.  

◦ Favoriser le partage d'initiatives et les retours d'expérience.  

◦ Promouvoir les synergies et les coopérations.  

◦ Valoriser les actions et les acteurs.

• Actions : Journées de rencontre, webinaires thématiques, ateliers "accélérateurs de projets" et une plateforme collaborative sur l'espace de l'ADEME.

Le Programme "Mieux Manger Pour Tous" (MMPT) :

• Origine : Issu du plan d'action pour la transformation de l'aide alimentaire.

• Budget national : 60 millions d'euros en 2023, avec une progression de 10 millions par an prévue jusqu'en 2027.

• Objectifs :

1. Améliorer la qualité nutritionnelle et gustative de l'aide alimentaire.   

2. Soutenir la participation et l'accompagnement des personnes précaires.   

3. Transformer les dispositifs locaux de lutte contre la précarité alimentaire (ex: paniers solidaires, groupements d'achat).   

4. Réduire l'impact environnemental du système d'aide alimentaire.

• Chiffres du programme en PACA :

◦ 2023 : 51 projets financés pour 1,7 million d'euros.    ◦ 2024 : 62 projets financés pour 2,5 millions d'euros.    ◦ 2025 : Enveloppe de 3,3 millions d'euros, avec 46 projets supplémentaires en cours d'instruction.

3. La Précarité Alimentaire : Définitions et Chiffres Clés

3.1. Définitions Fondamentales

Terme

Définition

Alimentation Durable (FAO)

Régimes alimentaires qui contribuent à protéger la biodiversité, sont culturellement acceptables, économiquement équitables et accessibles, et nutritionnellement sûrs et sains. Elle repose sur quatre enjeux : Nutrition/Santé, Environnement, Socio-économique, et Socio-culturel.

Lutte contre la Précarité Alimentaire

Favoriser l'accès à une alimentation sûre, diversifiée, de bonne qualité et en quantité suffisante pour les personnes en situation de vulnérabilité, dans le respect de leur dignité et en développant leur capacité d'agir.

Aide Alimentaire

Fourniture de denrées alimentaires aux personnes vulnérables, assortie d'une proposition d'accompagnement.

Insécurité Alimentaire (FAO)

Situation dans laquelle une personne n'a pas un accès régulier à suffisamment d'aliments sains et nutritifs pour une croissance et une vie active et saine. Elle est mesurée par l'échelle FIES (Food Insecurity Experience Scale).

3.2. État des Lieux de la Précarité Alimentaire

La mesure de la précarité alimentaire en France est complexe en raison de l'absence de méthode de recensement homogène et régulière.

Les données sont issues du croisement de plusieurs sources (statistiques publiques, études ponctuelles comme INCA 3, données des associations).

Chiffres nationaux (estimations) :

• Personnes en insécurité alimentaire : 8 millions, soit 11% de la population (Anses).

• Insatisfaction alimentaire : 16% des personnes déclarent ne pas avoir assez à manger et 45% ne pas avoir les aliments souhaités (CRÉDOC, 2022).

• Bénéficiaires de l'aide alimentaire : Entre 2 et 9 millions. La DGCS recense 5,3 millions de personnes inscrites auprès des associations habilitées.

• Non-recours à l'aide alimentaire : 75% des personnes en insécurité alimentaire n'ont pas recours à l'aide alimentaire (étude INCA 3, 2015).

• Difficultés financières : 38% des Français rencontrent des difficultés financières pour consommer des fruits et légumes frais tous les jours (Baromètre Ipsos/Secours Populaire, 2024).

Impacts sur la santé :

• La prévalence de l'obésité est près de quatre fois plus élevée chez les adultes les plus pauvres.

• La consommation de fruits et légumes est deux fois plus faible chez les personnes en insécurité alimentaire (230g/jour en moyenne contre une recommandation de 400g/jour).

Situation en région PACA :

• Taux de pauvreté : 3ème plus élevé de France, touchant environ 850 000 personnes.

• Niveau de vie médian des personnes pauvres : 10 600 € par an, soit plus de deux fois inférieur au niveau de vie médian de l'ensemble de la population de la région (22 000 €).

• Département le plus pauvre : Le Vaucluse, avec un taux de pauvreté de 20% (5ème plus élevé de France).

• Groupes les plus touchés :

◦ Les ménages dont le référent a moins de 30 ans (25% de taux de pauvreté).   

◦ Les familles monoparentales (30,2%).  

◦ Les seniors (la part des retraités parmi les ménages pauvres est de 30,4%).

4. Éclairages Scientifiques : Vers une Alimentation Durable et Abordable

Florent Vieux (MS-Nutrition) a présenté plusieurs études visant à quantifier les dimensions de l'alimentation durable (nutrition, environnement, coût) à partir de bases de données de référence (INCA 3, Ciqual, Agribalyse, Kantar).

4.1. Hiérarchie des Groupes Alimentaires

Cette étude montre que le classement des aliments en termes de coût et d'impact environnemental dépend fortement de l'unité fonctionnelle choisie.

Unité Fonctionnelle

Constats Clés

Par kilogramme (€/kg)

- Les plus chers/impactants : Viande de ruminant, produits de la mer. <br> - Les moins chers/impactants : Fruits, légumes, légumineuses.

Par 100 kilocalories (€/100 kcal)

- Les fruits et légumes deviennent très chers et impactants en raison de leur faible densité énergétique. <br> - Les produits laitiers et les œufs restent en position intermédiaire.

Par unité de qualité nutritionnelle

- Les produits de la mer redeviennent plus "abordables". <br>

• Les fruits, légumes et légumineuses restent des choix très pertinents (faible coût/impact rapporté à leur densité nutritionnelle).

Conclusion principale : Le classement du coût et de l'impact environnemental des catégories d'aliments est très similaire.

Certains aliments comme les légumineuses, les pommes de terre et les céréales complètes sont systématiquement peu coûteux et peu impactants, quelle que soit l'unité fonctionnelle.

4.2. Approche par "Déviance Positive"

Cette étude a comparé les régimes alimentaires d'individus ayant une bonne qualité nutritionnelle mais des impacts environnementaux différents.

• Le groupe "plus durable" (bonne nutrition, faible impact) présentait également un coût alimentaire plus faible.

• Marqueurs d'une bonne qualité nutritionnelle (communs aux deux groupes) :

◦ Consommation élevée de fruits et légumes.  

◦ Consommation élevée de produits laitiers.  

◦ Faible consommation de boissons sucrées.

• Ce qui distingue le groupe à faible impact environnemental :

◦ Une consommation beaucoup plus faible de viande de ruminant.  

◦ Une consommation nettement plus élevée de céréales complètes pour compenser.

4.3. Conclusion et Recommandations

L'ensemble des études convergent vers un message principal : la "végétalisation saine".

Il s'agit de réduire la consommation de produits animaux (surtout la viande) et de la substituer par des choix végétaux éclairés (céréales complètes, légumineuses, fruits et légumes).

• Enjeu spécifique pour les personnes précaires : L'augmentation de la consommation de fruits et légumes est prioritaire, car leur niveau de consommation de départ est particulièrement bas.

• Empreinte carbone : Si les plus pauvres ont une empreinte carbone globale bien plus faible que les plus riches, la différence est moins marquée pour le poste "alimentation". Agir sur ce levier reste donc pertinent pour tous.

5. Cadre Réglementaire et Levier d'Action

5.1. La Loi EGalim comme Modèle

Clara Vigan (DRAF) a présenté la loi EGalim, appliquée à la restauration collective, comme un levier puissant pouvant inspirer des actions au-delà de ce secteur.

• Objectifs de la loi :

◦ 50% de produits de qualité et durables, dont au moins 20% de produits bio.  

◦ Diversification des sources de protéines avec l'introduction de menus végétariens, ce qui permet de réduire les coûts.  

◦ Lutte contre le gaspillage alimentaire.    ◦ Réduction de l'usage du plastique.

Ces principes peuvent être transposés à l'aide alimentaire pour améliorer la qualité de l'offre tout en maîtrisant les budgets.

5.2. L'Impératif de la Sécurité Sanitaire des Aliments

Peggy Bucas (DRAF) a rappelé les règles fondamentales du "Paquet Hygiène", cruciales pour toute structure distribuant des denrées.

• Principes clés : traçabilité des dons, respect de la chaîne du froid/chaud, hygiène des locaux et du personnel.

• Distinction essentielle :

◦ DLC (Date Limite de Consommation) : Dépassement impérativement interdit.    ◦ DDM (Date de Durabilité Minimale) : "à consommer de préférence avant", le produit reste consommable sans risque sanitaire après la date.

6. Étude de Cas : La Transformation de l'Épicerie Sociale de Mouans-Sartoux

Rémy Georgon (CCAS de Mouans-Sartoux) a partagé le retour d'expérience de la transformation de l'épicerie sociale de la commune.

• Le déclic : Une prise de conscience collective en 2020 face à la baisse de qualité des dons issus des invendus. La structure réalisait qu'elle distribuait "des produits que personne n'a achetés".

• La stratégie de transformation :

1. Partenariats stratégiques : Une collaboration avec le magasin Biocoop local a permis d'instaurer une offre de produits en vrac (alimentaire et hygiène) et de créer un rayon de produits bio achetés.  

2. Recherche de financements : Mobilisation des appels à projets "France Relance" (pour renouveler les équipements de froid) et "Mieux Manger Pour Tous".   

3. Approvisionnement local et de saison : Mise en place d'un système de commande groupée de légumes frais et de saison auprès d'un producteur local.  

4. Synergie avec la politique de la ville : Le projet MMPT a permis de financer l'embauche d'un maraîcher par le CCAS, mis à disposition de la régie agricole municipale pour augmenter la production de légumes bio à destination de l'épicerie.  

5. Implication des bénéficiaires : Les usagers ont été consultés pour définir les produits frais prioritaires à acheter (produits laitiers).

• Résultats quantitatifs :

◦ En 2024, les produits bio représentaient 7% du stock (avec 0% de fruits et légumes).   

◦ Au premier semestre 2025, ce chiffre est passé à 46% de produits bio en poids, dont 62% sont des fruits et légumes.  

◦ Le budget d'achat de denrées est passé de 4 000 € à 25 000 €, soutenu par des subventions.

• Facteurs clés de succès :

◦ La conviction et l'engagement du responsable.  

◦ Une forte volonté politique et le soutien de la mairie.    ◦ La capacité à chercher des partenaires et des financements externes.  

◦ Le choix de privilégier la qualité sur la quantité.

The "insecure/avoidant-anxious" cluster (b) is mostly BPD, not ADHD. The "insecure/avoidant" cluster (a) has 11 of the 20 ADHD patients. This separates the two disorders.

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Cette phrase renforce l’idée centrale de mon devoir : Internet ne détruit pas le lien, il transforme notre manière d’être ensemble.

Rinaudo conclut en insistant sur la subjectivité face au numérique.

Cette phrase résume la nécessité de garder l’humain au centre du lien. Internet ne doit pas remplacer la rencontre réelle.

Rinaudo (via Méloni) parle ici du danger d’un savoir sans sujet. Cela rejoint l’idée que les relations numériques peuvent perdre leur dimension incarnée.

Ce passage montre que le numérique peut accentuer les tensions psychiques chez les jeunes — un écho à la “dépendance relationnelle” dont parle Janssen.

Cette référence à Bion met en évidence que les outils numériques jouent un rôle symbolique dans la construction du lien psychique.

Rinaudo montre que le numérique peut aussi soutenir la créativité et l’identité professionnelle — une vision plus positive proche de celle de Tisseron.

Certains professionnels ressentent le numérique comme une menace pour le lien. Cela illustre la “déliaison psychique” évoquée dans le débat sur la solitude numérique.

Certains professionnels ressentent le numérique comme une menace pour le lien. Cela illustre la “déliaison psychique” évoquée dans le débat sur la solitude numérique.

Rinaudo évoque la crainte du remplacement humain. Cela rejoint l’idée d’une relation déshumanisée, proche de la solitude émotionnelle décrite par Janssen.

Rinaudo souligne l’ambivalence du numérique : il peut soutenir la construction du sujet (subjectivation) ou, au contraire, aliéner. C’est l’idée du pharmakon.

Rinaudo montre que le numérique est devenu omniprésent, ce qui fait écho à l’hyperconnexion évoquée par Janssen dans la “solitude du lien”.

Cette expression montre que nos usages numériques ont une dimension psychique. On peut relier cela à l’idée de solitude connectée : Internet influence notre manière de vivre les relations.

Synthèse d'une Recherche sur les Associations et leurs Territoires

Synthèse

Ce document de synthèse présente les principaux enseignements d'un travail de recherche doctoral analysant les relations complexes entre les associations et leurs territoires.

La recherche démontre que le territoire d'une association n'est pas une simple donnée géographique, mais une construction dynamique et relationnelle façonnée par les interactions, les ressources mobilisées et les proximités (géographique, organisationnelle, institutionnelle) avec un écosystème d'acteurs.

L'étude distingue une zone d'activité, souvent locale, d'une zone d'influence (liée au projet associatif) beaucoup plus large, soulignant que ces deux dimensions sont complémentaires.

Il ressort que la coopération, centrale dans ce processus, est fortement guidée par l'appartenance sectorielle et le partage de valeurs, ce qui a des implications directes sur la recherche de financements et la légitimité des associations.

La méthodologie mixte, combinant une analyse quantitative nationale de 1600 bassins de vie et une étude qualitative approfondie de huit territoires, confère une robustesse significative à ces conclusions.

Ces travaux offrent des arguments concrets pour le plaidoyer, permettant aux associations de mieux valoriser leur contribution multidimensionnelle au développement et à l'attractivité des territoires.

1. Contexte et Problématique de la Recherche

Un Contexte Institutionnel en Tension

La recherche s'inscrit dans un contexte institutionnel marqué par un "vrai questionnement aujourd'hui et mise en péril du monde associatif". Cette tension est illustrée par une dichotomie fondamentale :

• D'une part, une reconnaissance croissante de l'importance des associations. Un rapport de la Cour des comptes de septembre souligne que "les associations mettent en œuvre des activités sociales relevant du périmètre de l'État", attestant de leur rôle crucial dans la "soutenabilité et la durabilité voir l'inclusion de notre société".

• D'autre part, une remise en cause systématique de leurs financements et de leur existence même.

Cette situation crée un paradoxe entre la vision nationale, qui reconnaît leur apport systémique, et les réalités territoriales, où la légitimité des associations à agir et à être financées est constamment interrogée.

L'Enjeu de la Relation au Territoire

La question centrale qui motive la recherche est de qualifier la relation entre les associations et les territoires. Le financement et la légitimité d'une association sur un territoire sont souvent liés à son périmètre géographique d'influence et d'activité. La recherche vise donc à dépasser l'idée que les associations sont simplement "non délocalisables". En effet, une association peut fermer des postes dans une ville pour en ouvrir dans une autre, ce qui constitue une forme de délocalisation. Le travail de recherche se propose de déconstruire la notion de "local" pour analyser comment une association passe de la simple localisation (présence dans un espace) à l'ancrage (relations établies) et à la territorialisation (devenir une composante spécifique et indissociable du territoire).

2. Le Cadre du Projet de Recherche Doctoral

Cette recherche est menée dans le cadre d'une thèse en CIFRE (Convention Industrielle de Formation par la Recherche) au sein du Réseau National des Maisons des Associations (RNMA), débutée en 2022.

Le Réseau National des Maisons des Associations (RNMA)

Le RNMA est un réseau national dont les membres sont des Maisons des Associations (MDA), qu'elles soient de statut associatif ou des services municipaux. Ses missions incluent :

• Faire remonter les problématiques du niveau local au niveau national.

• Accompagner le métier d'accompagnateur de la vie associative.

• Développer l'ingénierie, notamment en accompagnant la mise en place d'observatoires locaux de la vie associative, considérés comme des outils de co-construction de politiques publiques.

Les Objectifs de la Thèse

La thèse vise à qualifier et interpréter les relations entre les associations et le territoire à travers trois objectifs principaux :

1. Identifier et qualifier les variables socio-économiques qui expliquent la présence des établissements associatifs employeurs sur un territoire (approche quantitative).

L'hypothèse est que le tissu associatif est lié aux caractéristiques historiques, géographiques et culturelles d'un lieu.

2. Tester et démontrer les relations entre les caractéristiques du territoire et les caractéristiques organisationnelles et sectorielles des associations (approche qualitative).

3. Identifier les facteurs de diversité des associations, en analysant le processus qui mène de la localisation à la territorialisation.

3. Cadre Conceptuel et Méthodologie

Définitions Opérationnelles : Association et Territoire

La recherche s'appuie sur des définitions précises pour structurer son analyse :

• L'Association :

Elle est appréhendée non pas par sa définition juridique (loi 1901), mais comme une "forme organisationnelle construite" qui associe de manière intrinsèque une activité (réponse à des besoins) et un projet collectif.

Elle mobilise pour cela des moyens humains (bénévoles, militants, salariés) et matériels.

• Le Territoire : Il n'est pas considéré comme un espace géographique statique, mais comme "une construction qui vient de l'histoire de la fondation de la structure [...] et surtout des interactions qu'elle va avoir avec d'autres organisations". Le territoire est donc le produit des relations entre les acteurs.

Une Approche Méthodologique Mixte

La robustesse de l'étude repose sur une méthodologie en deux temps :

1. Phase Quantitative :

◦ Périmètre : Environ 1600 "bassins de vie" (définition INSEE) en France métropolitaine.   

◦ Analyse : Une méthode statistique a été utilisée pour croiser les caractéristiques socio-démographiques des bassins de vie (pyramide des âges, revenus, types d'emplois) avec la présence d'établissements associatifs employeurs (données INSEE Floress 2021).  

◦ Résultat : L'analyse a permis de répartir l'ensemble des bassins de vie en trois grands groupes ("clusters"), c'est-à-dire trois familles partageant des caractéristiques similaires dans l'articulation entre leur profil socio-économique et la présence associative.

2. Phase Qualitative :

◦ Échantillon : Huit bassins de vie ont été sélectionnés, représentatifs des trois clusters et caractérisés par la présence d'une Maison des Associations (associative ou municipale).

Les territoires étudiés sont : Grenoble, Dijon, Amiens, Concarneau, Montrevault-sur-Èvre, Niort, Crayon et Mauguio.   

◦ Collecte de données : 28 entretiens semi-directifs ont été menés (3 à 4 par bassin de vie) avec des associations de tous secteurs, employeuses comme non employeuses.

Le choix de se concentrer initialement sur les associations employeuses pour la partie quantitative s'explique par la disponibilité de données statistiques fiables et consolidées au niveau national (via les déclarations URSSAF), ce qui n'est pas le cas pour les associations non employeuses.

4. Étude de Cas : Le Bassin de Vie de Dijon

Pour illustrer la démarche d'analyse, le cas d'une association culturelle dans le bassin de vie de Dijon est présenté.

Caractéristiques Socio-économiques du Territoire

Indicateur

Donnée

Département

Côte-d'Or

Évolution de la population (2016-2021)

+2,5 %

Structure démographique

23 % de moins de 20 ans, 26 % de retraités

Catégories socio-professionnelles

11 % de cadres

Économie

83 % de l'emploi dans le secteur tertiaire

Tissu associatif employeur

947 établissements, générant près de 13 000 salaires

Le territoire est perçu par les acteurs locaux comme offrant une bonne qualité de vie ("bon vivre"), avec une université, une offre culturelle importante, mais aussi un côté "un petit peu bourgeois".

Modélisation d'une Association Culturelle

• Objet : Association de musique électronique, créée en 2004 par des passionnés suite à la fermeture d'un club.

• Structuration : D'abord bénévole, elle se professionnalise à partir de 2012 et compte aujourd'hui 3 salariés et une gouvernance de 8 personnes.

• Activités :

◦ Programmation/Production : Concerts, festivals.    ◦ Création : Studios de mixage.   

◦ Militantisme : Promotion de la musique électronique, professionnalisation du secteur, et mise en avant des valeurs de tolérance et de diversité.  

◦ Publics diversifiés : Ateliers en EHPAD, sensibilisation pour les jeunes en MJC, "booms" pour enfants.

• Écosystème : L'association interagit avec de multiples acteurs à différentes échelles (commune, métropole, département, national) :

• autres associations (culturelles, environnementales),
• la MDA municipale,
• les financeurs institutionnels (Ville, DRAC, Conseil Régional), et
• des réseaux (Ligue de l'enseignement, fédérations culturelles).

Analyse via le Prisme des Proximités

La relation entre l'association et son écosystème est analysée à travers trois types de proximités :

• Proximité Géographique : Évidente avec ses salariés, son public local, les EHPAD, les MJC et les autres associations locales. Elle facilite la rencontre et la coopération.

• Proximité Organisationnelle : Le partage de modes de fonctionnement.

Elle existe avec toutes les associations (gouvernance démocratique, non-lucrativité) mais est beaucoup plus forte avec les associations du même secteur culturel, qui partagent des règles et des logiques d'action communes (ex: organiser un festival).

• Proximité Institutionnelle : Le partage de valeurs et de normes. De même, si des valeurs comme la solidarité sont partagées largement dans le monde associatif, cette proximité est nettement plus marquée au niveau sectoriel.

5. Principaux Résultats et Conclusions Transversales

L'étude de cas et les autres entretiens permettent de dégager des conclusions plus générales.

Le Territoire : Une Construction Dynamique et Relationnelle

Les résultats montrent que les associations ne sont pas simplement "localisées".

Leur capacité à s'ancrer et à se territorialiser repose sur des mécanismes complexes où la coopération occupe une place centrale.

Le territoire n'est donc "pas du tout figé ni fixe, il est tout à fait dynamique" ; il est multi-scalaire, multi-acteurs, et incarné par la capacité des associations à mobiliser des ressources et des proximités.

Distinction entre Zone d'Activité et Zone d'Influence

Une distinction fondamentale est établie :

• La Zone d'Activité : L'espace où se déploient les activités concrètes de l'association. Dans le cas de Dijon, elle est principalement concentrée sur la commune et la métropole.

• La Zone d'Influence : L'espace beaucoup plus large sur lequel rayonne le projet associatif (le militantisme, les valeurs, la reconnaissance du mouvement). Elle "dépasse largement tous ces périmètres là".

Ces deux zones sont complémentaires et dynamiques.

Le Rôle Central des Proximités et du Secteur d'Activité

• La Proximité Géographique est structurante : Elle est la condition première de la rencontre et de la connaissance mutuelle.

Les MDA jouent un rôle clé de "lieu ressources" et de "facilitateurs".

• Le Secteur d'Activité est déterminant : Les proximités organisationnelle et institutionnelle sont décuplées au sein d'un même secteur.

Les associations d'un même domaine partagent des règles, des logiques et surtout des valeurs spécifiques beaucoup plus fortes.

• Les Valeurs comme guide de l'action : La proximité institutionnelle (le partage de valeurs) est un facteur crucial pour la coopération et la recherche de financement.

Comme l'indique un verbatim marquant de l'étude : "On travaille pas avec quelqu'un tout court si on n'a pas les mêmes valeurs".

6. Implications pour le Plaidoyer Associatif

Les résultats de cette recherche offrent des pistes concrètes pour que les associations valorisent leurs activités auprès des acteurs publics et des financeurs.

1. Dépasser la logique de l'activité seule : Il est crucial de montrer que l'association ne se résume pas à son activité (qui contribue à l'attractivité et au développement local), mais qu'elle possède également un projet et une zone d'influence qui rayonnent bien au-delà.

2. Démontrer l'effet de levier : Un financement local (par exemple, "1 € d'un acteur d'une commune") n'est pas une simple subvention.

Il a un effet levier qui permet d'aller chercher d'autres financements à d'autres échelles (régionale, nationale), contribuant ainsi au rayonnement global de l'association et du territoire.

3. Valoriser l'attraction de ressources externes : Les associations, par leur réseau et leur zone d'influence, attirent des ressources extérieures (artistes, expertises, financements) qu'elles mettent à disposition des habitants et du territoire, renforçant ainsi son attractivité.

DOI: 10.1038/s41598-020-77910-5

Resource: RRID:BDSC_6020

Curator: @bdscstockkeepers

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DOI: 10.1158/2643-3230.BCD-24-0176

Resource: (CLS Cat# 300297/NA, RRID:CVCL_0092)

Curator: @scibot

SciCrunch record: RRID:CVCL_0092

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DOI: 10.1016/j.immuni.2025.10.008

Resource: (BioLegend Cat# 329929, RRID:AB_11218984)

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What is this?

regular expression

Note de Synthèse sur le Bizutage : Définition, Risques et Actions

Synthèse

Le bizutage est un délit grave et non une simple tradition étudiante, défini par l'article 225-16-1 du Code pénal.

Il se caractérise par le fait d'amener une personne, consentante ou non, à subir ou commettre des actes humiliants ou dégradants, souvent accompagnés d'une consommation excessive d'alcool.

Ce phénomène touche principalement l'enseignement supérieur et les internats, et est généralement orchestré par les étudiants des années supérieures (deuxième ou troisième année) sur les nouveaux arrivants.

Les conséquences du bizutage sont profondes et peuvent être psychologiques (traumatismes durables, dépression), physiques (blessures, handicaps à vie) et parfois mortelles.

Les actes vont de l'ingestion forcée de substances à des simulations sexuelles, des insultes et la diffusion d'images dégradantes sur les réseaux sociaux.

La dynamique de groupe et la pression sociale rendent le refus extrêmement difficile pour les victimes, invalidant toute notion de consentement.

Les parents ont un rôle crucial à jouer dans la prévention, en identifiant les signaux d'alerte avant les week-ends d'intégration (questionnaires déplacés, demande d'apporter de l'alcool, décharges de responsabilité) et en maintenant le dialogue avec leurs enfants.

En cas de bizutage avéré, il est impératif de soutenir la victime sans la juger, de recueillir des preuves (certificats médicaux, témoignages, photos) et de contacter la direction de l'établissement, qui a l'obligation légale de saisir le procureur.

Le Comité National Contre le Bizutage (CNCB) constitue une ressource essentielle pour l'écoute, le conseil et la médiation.

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1. Définition Juridique et Caractéristiques du Bizutage

Le bizutage n'est pas une pratique anodine mais un délit formellement interdit et sanctionné par la loi française. Sa compréhension passe par une analyse de sa définition légale et de ses distinctions avec d'autres phénomènes comme le harcèlement.

1.1. Le Cadre Légal : Article 225-16-1 du Code Pénal

Le bizutage est défini comme le fait, pour une personne, "d'amener autrui, contre son gré ou non, à subir ou à commettre des actes humiliants ou dégradants ou à consommer de l'alcool de manière excessive" dans le cadre de manifestations ou réunions liées aux milieux scolaire, sportif et socio-éducatif.

• Sanctions : Ce délit est puni de six mois d'emprisonnement et de 7 500 euros d'amende.

• Auteur de la loi : Le Comité National Contre le Bizutage (CNCB) a participé à l'élaboration de cette loi en 1998.

1.2. Concepts Fondamentaux

Deux notions clés de la loi méritent une attention particulière :

• "Actes humiliants ou dégradants" : La perception de l'humiliation est subjective. Un acte peut être vécu comme profondément dégradant par une personne et pas par une autre.

Il n'existe pas d'échelle pour mesurer l'humiliation. Un acte est considéré comme tel dès lors qu'il met la personne mal à l'aise ou porte atteinte à sa dignité.

• "Contre son gré ou non" : C'est l'élément le plus crucial. La notion de consentement n'existe pas dans le bizutage.

Un jeune qui participe aux épreuves, même en donnant l'impression de s'amuser, n'est pas considéré comme consentant au regard de la loi. La pression du groupe, le désir d'intégration et la consommation d'alcool annihilent le libre arbitre.

1.3. Distinction avec le Harcèlement

Il est essentiel de ne pas confondre le bizutage et le harcèlement :

• Le Harcèlement : Vise une seule personne (ou un groupe restreint) pour des motifs spécifiques (physique, origine, etc.). Il s'agit d'un ou plusieurs harceleurs contre une victime ciblée.

• Le Bizutage : Vise un groupe entier, les "nouveaux", par un autre groupe, les "anciens".

La seule et unique raison du bizutage est le statut de nouvel arrivant. L'objectif affiché, bien que perverti, est un rite de passage pour "intégrer" la promotion.

2. Manifestations et Contexte du Bizutage

Le bizutage se déroule selon des schémas récurrents, impliquant des acteurs spécifiques dans des environnements propices à l'abus de pouvoir.

2.1. Acteurs et Lieux Concernés

• Les Bizuteurs : Généralement les étudiants de deuxième ou troisième année, souvent organisés par le Bureau des Élèves (BDE).

Leurs motivations sont diverses : se venger d'un bizutage subi, ou un sentiment de toute-puissance et de perversité.

• Les Bizutés : Les nouveaux arrivants (premières années).

• Lieux : Le phénomène touche tous les types d'établissements de l'enseignement supérieur (universités, écoles de commerce, médecine, architecture, BTS), les centres sportifs (CREPS) et est particulièrement prévalent dans les internats, qui sont des lieux clos et propices aux abus.

2.2. Formes et Exemples d'Actes de Bizutage

Les pratiques sont variées mais suivent souvent une escalade, une "spirale" qui commence de manière prétendument "amusante" avant de dégénérer.

Catégorie d'actes

Exemples concrets issus de témoignages

Humiliation Physique

- Se faire couvrir d'un mélange "collant et puant" (œufs, farine, litière pour lapin, soupe de poisson).<br>- Être attaché à d'autres, parfois dans des positions dégradantes.<br>- Passer dans un tuyau rempli d'huile ou une bassine de soda.

Consommation Forcée

- Obligation de boire de l'alcool en grande quantité (la vodka est très fréquente).<br>- Ingurgiter de la nourriture ou des boissons dégoûtantes.

Atteintes Sexuelles

- Obliger une fille à simuler une fellation ou à faire un strip-tease.<br>- Chanter des chansons obscènes.<br>- Insultes à caractère sexiste pour les filles et homophobe pour les garçons.

Cyber-violence

- Déshabiller les bizutés, les filmer ou les photographier.<br>- Diffuser les images sur les réseaux sociaux.

Menaces

- Menacer ceux qui refusent de participer, les qualifier de "nuls" ou de "pas drôles".

2.3. La Psychologie du Bizuteur

La justification principale avancée par les bizuteurs est de "souder la promotion" et de créer des liens.

En réalité, la logique sous-jacente est une relation de dominant-dominé.

Un témoignage d'un ancien bizuteur est particulièrement éclairant :

"Je retiens du bizutage, un sentiment enivrant de pouvoir. C'est en criant 'bois et ferme ta gueule' à une première année [...] que j'ai compris le plaisir d'être tyran d'un jour. J'ai adoré soumettre des premières années."

3. Conséquences Graves et Dégâts Humains

La formule du CNCB résume l'impact du bizutage : "Il tue parfois, il traumatise souvent et il humilie toujours."

3.1. Conséquences Psychologiques

• Traumatismes à long terme : Des victimes contactent le CNCB 5, 10, voire 30 ans après les faits, n'ayant jamais réussi à oublier.

• Dépression et décrochage : De nombreux jeunes développent une dépression et abandonnent leurs études pour ne plus avoir à croiser leurs "bourreaux" dans les couloirs.

• Honte et culpabilité : Les victimes ressentent une profonde honte d'avoir accepté, de ne pas avoir su dire non, ce qui les empêche souvent de parler.

3.2. Conséquences Physiques et Mortelles

Le bizutage peut causer des blessures graves, voire la mort.

• Blessures graves : Un jeune est resté aveugle pendant trois semaines après avoir été baigné dans des liquides toxiques ; un autre est handicapé à vie après une chute de trois étages lors d'un bizutage à Lille en 2012.

• Décès : Plusieurs décès directement liés à des bizutages ont été recensés.

Année

Lieu

Contexte

2012

Saint-Cyr

Noyade

2013

École des Mines

Décès

2017

Fac de Nanterre / Dentaire de Rennes

Décès

2021

Lille

Décès de Simon Monray

Message de prévention crucial : Ne jamais laisser seul un jeune fortement alcoolisé. Il faut appeler les secours (pompiers, SAMU) et rester avec lui. Un jeune est décédé à Rennes d'un coma éthylique après avoir été laissé seul pour "cuver son vin".

4. Rôle des Parents et Stratégies d'Action

Les parents sont en première ligne pour prévenir le bizutage et agir s'il survient.

4.1. Prévention en Amont (Avant un week-end d'intégration)

• Dialoguer : Profiter de la demande de financement pour le week-end pour aborder le sujet du bizutage, sans effrayer mais en prévenant.

• Analyser l'invitation et la liste de matériel : Certains signes doivent alerter.

◦ Questionnaire "bizarre" avec des questions intimes ou sur l'alcool.  

◦ Demande de prévoir des vêtements "qui ne craignent rien".    ◦ Demande d'apporter de l'alcool.  

◦ Demande de signer une décharge de responsabilité, qui n'a aucune valeur juridique.

• Exiger des informations claires : Les parents doivent connaître le lieu et le programme précis du week-end. Un lieu tenu secret est un signal d'alarme majeur.

• Assurer la communication : Le jeune doit toujours conserver son téléphone portable.

La confiscation des téléphones vise à couper les victimes du monde extérieur et doit déclencher une alerte immédiate auprès de la direction de l'établissement.

• Conseiller le refus : Inciter le jeune à dire non s'il se sent mal à l'aise et à se regrouper avec d'autres qui partagent ses réticences.

4.2. Réaction Après un Bizutage

• Identifier les signaux de détresse :

◦ Refus de parler du week-end, malaise.  

◦ Changement de comportement : isolement, anxiété, sommeil perturbé.  

◦ Volonté de quitter l'établissement.   

◦ Marques physiques ou blessures.

• Écouter et soutenir :

◦ Rester calme, ne pas paniquer.    ◦ Écouter sans porter de jugement sur l'incapacité du jeune à dire non.  

◦ Ne jamais minimiser les faits subis.   

◦ Déculpabiliser la victime : les seuls coupables sont les bizuteurs.

• Recueillir des preuves :

◦ Faire établir des certificats médicaux (physiques et psychologiques).    ◦ Conserver toutes les preuves : messages, photos, noms des organisateurs et des autres victimes, dates, lieux.

4.3. Démarches Institutionnelles et Judiciaires

• Contacter l'établissement : Informer le chef d'établissement, les services de la vie étudiante ou le référent bizutage.

Le CNCB peut servir de médiateur en garantissant l'anonymat.

• Obligation de l'établissement : Le chef d'établissement a l'obligation légale de saisir le procureur de la République lorsqu'il a connaissance de faits délictueux.

Il doit aussi engager des poursuites disciplinaires.

• Porter plainte : Il est conseillé de consulter un avocat avant d'engager une procédure judiciaire.

La justice est souvent très lente et de nombreuses plaintes sont classées sans suite.

Le processus peut être long (l'affaire de 2012 s'est terminée en 2025) et coûteux.

• Objectif des sanctions : Les sanctions doivent être rapides et exemplaires pour dissuader de futures tentatives, car les bizuteurs ne sont généralement pas récidivistes.

5. Le Comité National Contre le Bizutage (CNCB)

Le CNCB est un acteur central de la lutte contre ce phénomène en France.

• Composition : Il regroupe des adhérents directs et des personnes morales comme les fédérations de parents d'élèves, des syndicats enseignants, la Conférence des présidents d'universités et la Conférence des grandes écoles.

• Missions :

1. Recueillir les témoignages, écouter et conseiller les victimes.  

2. Interpeller les responsables d'établissements et les ministères.   

3. Intervenir dans les établissements pour prévenir et éradiquer le bizutage.  

4. Réfléchir avec les jeunes à des formes d'accueil respectueuses et bienveillantes.

• Partenariats : Le CNCB travaille en étroit partenariat avec le Ministère de l'Enseignement Supérieur et le Ministère des Sports, qui le subventionnent.

En revanche, la collaboration avec le Ministère de l'Éducation Nationale est décrite comme inexistante ("c'est un mur").

• Ressources : Le site web du CNCB met à disposition de nombreux outils (diaporamas, brochures) pour permettre à d'autres acteurs (parents, enseignants) de mener des actions de sensibilisation.

6. Citations Clés

Sur la nature du bizutage : "Le bizutage, il tue parfois, il traumatise souvent et il humilie toujours."

Sur le consentement : "Les visiteurs nous disent 'mais madame, on a obligé personne. Tout le monde était d'accord.' [...] Et là, il faut vraiment remettre les pendules à l'heure et réfléchir avec eux parce que c'est faux. Le nouveau, il n'a pas le choix."

Sur la motivation du bizuteur : "Je retiens du bizutage, un sentiment enivrant de pouvoir. [...] J'ai compris le plaisir d'être tyran d'un jour. J'ai adoré soumettre des premières années."

Témoignage d'une victime : "Je me sentais sale dans tous les sens du terme. On est obligé parce qu'on nous dit en gros, si vous ne le faites pas, vous n'êtes pas drôle. Vous êtes des nuls."

Sur l'importance de dénoncer : "Dénoncer un bizutage, c'est dénoncer un délit et que de dénoncer un délit, c'est le devoir de tout citoyen. Et que si on ne dénonce pas les faits, eh bien, c'est tout simple, ils se reproduiront l'année d'après."

This as well, look into how ECS and DA effect it: How does ECS effect the limbic system?

Nicotine and alcohol also follow this pattern

dopamine anergic system

it may feel like an extra step along the way but the final draft process is ay easier when you prep for it.

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

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Reply to the reviewers

Response to Reviewer’s Comments

We thank all three reviewers for their thoughtful and detailed comments, which will help us to improve the quality and clarity of our manuscript.

__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __ Summary: In this work, Tripathi et al address the open question of how the Fat/Ds pathway affects organ shape, using the Drosophila wing as a model. The Fat/Ds pathway is a conserved but complex pathway, interacting with Hippo signalling to affect growth and providing planar cell polarity that can influence cellular dynamics during morphogenesis. Here, authors use genetic perturbations combined with quantification of larval, pupal, and adult wing shape and laser ablation to conclude that the Ft/Ds pathway affects wing shape only during larval stages in a way that is at least partially independent of its interaction with Hippo and rather due to an effect on tissue tension and myosin II distribution. Overall the work is clearly written and well presented. I only have a couple major comments on the limitations of the work.

Major comments: 1. Authors conclude from data in Figures 1 and 2 that the Fat/Ds pathway only affects wing shape during larval stages. When looking at the pupal wing shape analysis in Figure 2L, however, it looks there is a difference in wt over time (6h-18h, consistent with literature), but that difference in time goes away in RNAi-ds, indicating that actually there is a role for Ds in changing shape during pupal stages, although the phenotype is clearly less dramatic than that of larval stages. No statistical test was done over time (within the genotype), however, so it's hard to say. I recommend the authors test over time - whether 6h and 18h are different in wild type and in ds mutant. I think this is especially important because there is proximal overgrowth in the Fat/Ds mutants, much of which is contained in the folds during larval stages. That first fold, however, becomes the proximal part of the pupal wing after eversion and contracts during pupal stages to elongate the blade (Aiguoy 2010, Etournay 2015). Also, according to Trinidad Curr Biol 2025, there is a role for Fat/Ds pathway in pupal stages. All of that to say that it seems likely that there would be a phenotype in pupal stages. It's true it doesn't show up in the adult wing in the experiments in Fig 1, but looking at the pupal wing itself is more direct - perhaps the very proximal effect is less prominent later, as there is potential for further development after 18hr before adulthood and the most proximal parts are likely anyway excluded in the analysis.

Response: Our main purpose in examining pupal wing shape was to emphasize that wings lacking ds are visibly abnormal even at early pupal stages. The reviewer makes the point that the change in shape from 6h to 18h APF is greater in control wings than in RNAi-ds wings. We have added quantitation of this to the revised manuscript as suggested. This difference could be interpreted as indicating that Ds-Fat signaling actively contributes to wing shape during pupal morphogenesis. However, given the genetic evidence that Ds-Fat signaling influences wing shape only during larval growth, we favor the interpretation that it reflects consequences of Ds-Fat action during larval stages – eg, overgrowth of the wing, particularly the proximal wing and hinge as occurs in ds and fat mutants, could result in relatively less elongation during the pupal hinge contraction phase. This wouldn’t change our key conclusions, but it is something that we discuss in a revised manuscript.

I think there needs to be a mention and some discussion of the fact that the wing is not really flat. While it starts out very flat at 72h, by 96h and beyond, there is considerable curvature in the pouch that may affect measurements of different axis and cell shape. It is not actually specified in the methods, so I assume the measurements were taken using a 2D projection. Not clear whether the curvature of the pouch was taken into account, either for cell shape measurements presented in Fig 4 or for the wing pouch dimensional analysis shown in Fig 3, 6, and supplements. Do perturbations in Ft/Ds affect this curvature? Are they more or less curved in one or both axes? Such a change could affect the results and conclusions. The extent to which the fat/ds mutants fold properly is another important consideration that is not mentioned. For example, maybe the folds are deeper and contain more material in the ds/fat mutants, and that's why the pouch is a different shape? At the very least, this point about the 3D nature of the wing disc must be raised in discussion of the limitations of the study. For the cell shape analysis, you can do a correction based on the local curvature (calculated from the height map from the projection). For the measurement of A/P, D/V axes of the wing pouch, best would be to measure the geodesic distance in 3D, but this is not reasonable to suggest at this point. One can still try to estimate the pouch height/curvature, however, both in wild type and in fat/ds mutants.

Response: The wing pouch measurements were done on 2D projections of wing discs that were already slightly flattened by coverslips, so there is not much curvature outside of the folds. We will revise the methods to make sure this is clear. While we recognize that the absolute values measured can be affected by this, our conclusions are based on the qualitative differences in proportions between genotypes and time points, and we wouldn’t expect these to differ significantly even if 3D distances were measured. Obtaining accurate 3D measures is technically more challenging - it requires having spacers matching the thickness of the wing disc, which varies at different time points and genotypes, and then measuring distances across curved surfaces. What we propose to address this is to do a limited set of 3D measures on wild-type and dsmutant wing discs at early and late stages and which we expect will confirm our expectation that the conclusions of our analysis are unaffected, while at the same time providing an indication of how much curvature affects the values obtained. We will also make sure the issue of wing disc curvature and folds is discussed in the text.

Minor comments: 1. The analysis of the laser ablation is not really standard - usually one looks at recoil velocity or a more complicated analysis of the equilibrium shape using a model (e.g Shivakumar and Lenne 2016, Piscitello-Gomez 2023, Dye et al 2021). One may be able to extract more information from these experiments - nevertheless, I doubt the conclusions would change, given that that there seems to be a pretty clear difference between wt and ds (OPTIONAL).

Response: We will add measurements of recoil velocities to complement our current analysis of circular cuts.

Figure 7G: I think you also need a statistical test between RNAi-ds and UAS-rokCA+RNAi-ds.

Response: We include this statistical test in the revised manuscript (it shows that they are significantly different).

In the discussion, there is a statement: "However, as mutation or knock down of core PCP components, including pk or sple, does not affect wing shape... 59." Reference 59 is quite old and as far as I can tell shows neither images nor quantifications of the wing shape phenotype (not sure it uses "knockdown" either - unless you mean hypomorph?). A more recent publication Piscitello-Gomez et al Elife 2023 shows a very subtle but significant wing shape phenotype in core PCP mutants. It doesn't change your logic, but I would change the statement to be more accurate by saying "mutation of core PCP components has only subtle changes in adult wing shape"

Response: Thank-you for pointing this out, we have revised the manuscript accordingly.

**Referee cross-commenting**

Reviewer2: Reviewer 2 makes the statement: "The distance along the AP boundary from the pouch border to DV midline is topologically comparable to the PD length of the adult wing. The distance along the DV boundary from A border to P border is topologically comparable to the AP length of the adult wing."

I disagree - the DV boundary wraps around the entire margin of the adult wing (as correctly drawn with the pink line in Fig 2A). It is not the same as the wide axis of the adult wing (perpendicular to the AP boundary). It is not trivial to map the proximal-distal axis of the larval wing to the proximal-distal axis of the adult, due to the changes in shape that occur during eversion. Thus, I find it much easier to look at the exact measurement that the authors make, and it is much more standard in the field, rather than what the reviewer suggests. Alternatively, one could I guess measure in the adult the ratio of the DV margin length (almost the circumference of the blade?) to the AP boundary length. That may be a more direct comparison. Actually the authors leave out the term "boundary" - what they call AP is actually the AP boundary, not the AP axis, and likewise for the DV - what they measure is DV boundary, but I only noticed that in the second read-through now. Just another note, these measurements of the pouch really only correspond to the very distal part of the wing blade, as so much of the proximal blade comes from the folds in the wing disc. Therefore, a measurement of only distal wing shape would be more comparable.

Response: We thank Reviewer 1 for their comments here. In terms of the region measured, we measure to the inner Wg ring in the disc, the location of this ring in the adult is actually more proximal than described above (eg see Fig 1B of Liu, X., Grammont, M. & Irvine, K. D. Roles for scalloped and vestigial in regulating cell affinity and interactions between the wing blade and the wing hinge. Developmental Biology 228, 287–303 (2000)), and this defines roughly the region we have measured in adult wings (with the caveat noted above that the measurements in the disc can be affected by curvature and the hinge/pouch fold, which we will address).

Reviewer 2 states that authors cannot definitively conclude anything about mechanical tension from their reported cutting data because the authors have not looked at initial recoil velocity. I strongly disagree. __The wing disc tissue is elastic on much longer timescales than what's considered after laser ablation (even hours), and the shape of the tissue after it equilibrates from a circular cut (1-2min) can indeed be used to infer tissue stresses (see Dye et al Elife 2021, Piscitello-Gomez et al eLife 2023, Tahaei et al arXiv 2024).__ In the wing disc, the direction of stresses inferred from initial recoil velocity are correlated with the direction of stresses inferred from analysing the equilibrium shape after a circular cut. Rearrangements, a primary mechanism of fluidization in epithelia, does not occur within 1'. Analysing the equilibrium shape after circular ablation may be more accurate for assessing tissue stresses than initial recoil velocity - in Piscitello-Gomez et al 2023, the authors found that a prickle mutation (PCP pathway) affected initial recoil velocity but not tissue stresses in the pupal wing. Such equilibrium circular cuts have also been used to analyze stresses in the avian embryo, where it correlates with directions of stress gathered from force inference methods (Kong et al Scientific Reports 2019). The Tribolium example noted by the reviewer is on the timescale of tens to hundreds of minutes - much longer than the timescale of laser ablation retraction. It is true the analysis of the ablation presented in this paper is not at the same level as those other cited papers and could be improved. But I don't think the analysis would be improved by additional experiments doing timelapse of initial retraction velocity.

Response: Thank-you, we agree with Reviewer 1 here.

Reviewer 2 states "If cell anistropy is caused by polarized myosin activity, that activity is typically polarized along the short edges not long edges" Not true in this case. Myosin II accumulates along long boundaries (Legoff and Lecuit 2013). "Therefore, interpreting what causes the cell anistropy and how DS regulates it is difficult," Agreed - but this is well beyond the scope of this manuscript. The authors clearly show that there is a change of cell shape, at least in these two regions. Better would be to quantify it throughout the pouch and across multiple discs. Similar point for myosin quantifications - yes, polarity would be interesting and possible to look at in these data, and it would be better to do so on multiple discs, but the lack of overall myosin on the junctions shown here is not nothing. Interpreting what Ft/Ds does to influence tension and myosin and eventually tissue shape is a big question that's not answered here. I think the authors do not claim to fully understand this though, and maybe further toning down the language of the conclusions could help.

Response: We agree with Reviewer 1 here and will also add quantitation of myosin across multiple discs and will include higher magnification myosin images and polarity tests.

Reviewer 3: I agree with many of the points raised by Reviewer 3, in particular that relevant for Fig 1. The additional experiments looking at myosin II localization and laser ablation in the other perturbations (Hippo and Rok mutants/RNAi) would certainly strengthen the conclusions.

Response: Reviewer 3 comment on Fig 1 requests Ab stains to assess recovery of expression after downshift, which we will do.

We will add examination of myosin localization in hpo RNAi wing discs, and in the ds/rok combinations. We note that the effects of Rok manipulations on myosin and on recoil velocity have been described previously (eg Rauskolb et al 2014).

Reviewer #1 (Significance (Required)): I think the work provides a clear conceptual advance, arguing that the Ft/Ds pathway can influence mechanical stress independently of its interaction with Hippo and growth. Such a finding, if conserved, could be quite important for those studying morphogenesis and Fat function in this and other organisms. For this point, the genetic approach is a clear strength. Previous work in the Drosophila wing has already shown an adult wing phenotype for Ft/Ds mutations that was attributed to its role in the larval growth phase, as marked clones show aberrant growth in mutants. The novelty of this work is the dissection of the temporal progression of this phenotype and how it relates to Hippo and myosin II activation. It remains unclear exactly how Ft/Ds may affect tissue tension, except that it involves a downregulation of myosin II - the mechanism of that is not addressed here and would involve considerable more work. I think the temporal analysis of the wing pouch shape was quite revealing, providing novel information about how the phenotype evolves in time, in particular that there is already a phenotype quite early in development. As mentioned above, however, the lack of consideration of the wing disc as a 3D object is a potential limitation. While the audience is likely mostly developmental biologists working in basic research, it may also interest those studying the pathway in other contexts, including in vertebrates given its conservation and role in other processes.

__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __ The manuscript begins with very nice data from a ts sensitive period experiment. Instead of a ts mutation, the authors induced RNAi in a temperature dependent manner. The results are striking and strong. Knockdown of FT or DS during larval stages to late L3 changed shape while knockdown of FT or DS during later pupal stages did not. This indicates they are required during larval, not pupal stages of wing development for this shape effect. They did shift-up or shift-down at "early pupa stage" but precisely what stage that means was not described anywhere in the manuscript. White prepupal? Time? Likewise a shift-down was done at "late L3" but that meaning is also vague. Moreover, I was surprised to see they did not do a shift-up at the late L3 stage, to give completeness to the experiment. Why?

Response: We have added more precise descriptions of the timing, and we will also add the requested late L3 shift-up experiment.

Looking at the "shape" of the larval wing pouch they see a difference in the mutants. The pouch can be approximated as an ellipse, but with differing topology to the adult wing. Here, they muddled the analysis. The adult wing surface is analogous to one hemisphere of the larval wing pouch, ie., either dorsal or ventral compartment. The distance along the AP boundary from the pouch border to DV midline is topologically comparable to the PD length of the adult wing. The distance along the DV boundary from A border to P border is topologically comparable to the AP length of the adult wing. They confusingly call this latter metric the "DV length" and the former metric the "AP length" , and in fact they do not measure the PD length but PD+DP length. Confusing. Please change to make this consistent with earlier analysis of the adult and invert the reported ratio and divide by two.

Then you would find the larval PD/AP ratio is smaller in the FT and DS mutants than wildtype, which resembles the smaller PD/AP ratio seen in the mutant adult wings. Totally consistent and also provides further evidence with the ts experiments that FT and DS exert shape effects in the larval phase of life.

Response: As noted by Reviewer 1 in cross-referencing, some of the statements made by Reviewer 2 here are incorrect, eg “The distance along the DV boundary from A border to P border is topologically comparable to the AP length of the adult wing.” They are correct where they note that the A-P length we measure in the discs is actually equivalent to 2x the adult wing length, since we are measuring along both the dorsal and ventral wing, but this makes no difference to the analysis as the point is to compare shape between time points and genotypes, not to make inferences based on the absolute numbers obtained. The numerical manipulations suggested are entirely feasible but we think they are unnecessary.

The remainder of the manuscript has experimental results that are more problematic, and really the authors do not figure out how the shape effect in larval stages is altered. I outline below the main problems.

1. They compare the FT DS shape phenotypes to those of mutants or knockdowns in Hippo pathway genes (Hippo is known to be downstream of FT and DS). They find these Hippo perturbations do have shape effects trending in same direction as FT and DS effects. Knockdown reduces the PD/AP ratio while overexpressing WARTS increases the PD/AP ratio. The effect magnitudes are not as strong, but then again, they are using hypomorphic alleles and RNAi, which often induces partial or hypomorphic phenotypes. The effect strength is comparable when wing pouches are young but then dissipates over time, while FT and DS effects do not dissipate over time. The complexity of the data do not negate the idea that Hippo signaling is also playing some role and could be downstream of FT and DS in all of this. But the authors really downplay the data to the point of stating "These results imply that Ds-Fat influences wing pouch shape during wing disc growth separately from its effects on Hippo signaling." I think a more expansive perspective is needed given the caveats of the experiments.

Response: Our results emphasize that the effects of Ds-Fat on wing shape cannot be explained solely by effects on Hippo signaling, eg as we stated on page 7 “These observations suggest that Hippo signaling contributes to, but does not fully explain, the influence of ds or fat on adult wing shape.” We also note that impairment of Hippo signaling has similar effects in younger discs, but very different effects in older discs, which clearly indicates that they are having very different effects during disc growth; we will revise the text to make sure our conclusions are clear.

              The reviewer wonders whether some of the differences could be due to the nature of the alleles or gene knockdown. First, the *ex*, *ds*, and *fat* alleles that we use are null alleles (eg see FlyBase), so it is not correct to say that we use only hypomorphic alleles and RNAi. We do use a hypomorphic allele for wts, and RNAi for hpo, for the simple reason that null alleles in these genes are lethal, so adult wings could not be examined. A further issue that is not commented on by the reviewer, but is more relevant here, is that there are multiple inputs into Hippo signaling, so of course even a null allele for ex, ds or fat is not a complete shutdown of Hippo signaling. Nonetheless, one can estimate the relative impairment of Hippo signaling by measuring the increased size of the wings, and from this perspective the knockdown conditions that we use are associated with roughly comparable levels of Hippo pathway impairment, so we stand by our results. We do however, recognize that these issues could be discussed more clearly in the text, and will do so in a revised manuscript.

Puzzlingly, this lack of taking seriously a set of complex results does not transfer to another set of experiments in which they inhibit or activate ROK, the rho kinase. When ROK is perturbed, they also see weak effects on shape when compared to FT or DS perturbation. This weakness is seen in adults, larvae, clones and in epistasis experiments. The epistasis experiment in particular convincingly shows that constitutuve ROK activation is not epistatic to loss of DS; in fact if anything the DS phenotype suppresses the ROK phenotype. These results also show that one cannot simply explain what FT and DS are doing with some single pathway or effector molecule like ROK. It is more complex than that.

What I really think was needed were experiments combining FT and DS knockdown with other mutants or knockdowns in the Hippo and Rho pathways, and even combining Hippo and Rho pathway mutants with FT or DS intact, to see if there are genetic interactions (additive, synergistic, epistatic) that could untangle the phenotypic complexity.

Response: We’re puzzled by these comments. First, we never claimed that what Fat or Ds do could be explained simply by manipulation of Rok (eg, see Discussion). Moreover, examination of wings and wing discs where ds is combined with Rho manipulations is in Fig 7, and Hippo and Rho pathway manipulation combinations are in Fig S5. We don’t think that combining ds or fat mutations with other Hippo pathway mutations would be informative, as it is well established that Ds-Fat are upstream regulators of Hippo signaling.

Laser cutting experiments were done to see if there is anisotropy in tissue tension within the wing pouch. This was to test a favored idea that FT and DS activity generates anisotropy in tissue tension, thereby controlling overall anisotropic shape of the pouch. However there is a fundamental flaw to their laser cutting analysis. Laser cutting is a technique used to measure mechanical tension, with initial recoil velocity directly proportional to the tissue's tension. By cutting a small line and observing how quickly the edges of the cut snap apart, people can quantify the initial recoil velocity and infer the stored mechanical stress in the tissue at the time of ablation. Live imaging with high-speed microscopy is required to capture the immediate response of the tissue to the cut since initial recoil velocity occurs in the first few seconds. A kymograph is created by plotting the movement of the tissue edges over this time scale, perpendicular to the cut. The initial recoil velocity is the slope of the kymograph at time zero, representing how fast the severed edges move apart. A higher recoil velocity indicates higher mechanical tension in the tissue. However, the authors did not measure this initial recoil velocity but instead measured the distance between the severed edges at one time point: 60 seconds after cutting. This is much later than the time point at which the recoil usually begins to dissipate or decay. This decay phase typically lasts a minute or two, during which time the edges continue to separate but at a progressively slower rate. This time-dependent decay of the recoil reveals whether the tissue behaves more like a viscous fluid or an elastic solid. Therefore, the distance metric at 60 seconds is a measurement of both tension and the material properties of the cells. One cannot know then whether a difference in the distance is due to a difference in tension or fluidity of the cells. If the authors made measurements of edge separation at several time points in the first 10 seconds after ablation, they can deconvolute the two. Otherwise their analysis is inconclusive. Anisotropy in recoil could be caused by greater tissue fluidity along one axis. Observing a gradient of cell fluidity in a tissue along one axis of a tissue has been observed in the amnioserosa of Tribolium for example. (Related and important point - was the anisotropy of recoil oriented along the PD or AP axis or not oriented to either axis, this key point was never stated)..

The authors cannot definitiviely conclude anything about mechanical tension from their reported cutting data.

Response: As noted by Reviewer 1 in cross-commenting, there is no fluidity on a time scale of 1 minute in the wing disc, and circular ablations are an established methods to investigate tissue stress. We choose the circular ablation method in part because it interrogates stress over a larger area, whereas cutting individual junctions is subject to more variability, particularly as the orientation of the junction (eg radial vs tangential) impacts the tension detected in the wing disc. Nonetheless, we will add recoil measurements to the revised manuscript to complement our circular ablations, which we expect will provide independent confirmation of our results and address the Reviewer’s concern here.

They measured the eccentricity of wing pouch cells near the pouch border, and found they were highly anisotropic compared to DS mutant cells at comparable locations. Cells were elongated but again what if either axis (PD or AP) they were elongated along was never stated. If cell anistropy is caused by polarized myosin activity, that activity is typically polarized along the short edges not long edges. Thus, recoil velocity after laaser cutting would be stonger along the axis aligned with short cell edges. It looks like the cutting anisotropy they see is greater along the axis aligned with long cell edges. Of course, if the cell anisotropy is caused by a pulling force exerted by the pouch boundary, then it would stretch the cells. This would in fact fit their cutting data. But then again, the observed cell anisotropy could also be caused by variation in the fluid-solid properties of the wing cells as discussed earlier. Compression of the cells then would deform them anisotropically and produce the anisotropic shapes that were observed, Therefore, interpreting what causes the cell anistropy and how DS regulates it is difficult,

Response: As noted by Reviewer 1 in cross-commenting, it is well established that tension and myosin are higher along long edges in the proximal wing. However, we acknowledge that we could do a better job of making the location and orientation of the regions shown in these experiments clear and, we will address this in a revised manuscript.

The imaging and analysis of the myosin RLC by GFP tagging is also flawed. SQH-GFP is a tried and true proxy for myosin activity in Drosophila. Although the authors image the wing pouch of wildtype and DS mutants. they did so under low magnification to image the entire pouch. This gives a "low-res" perspective of overall myosin but what they needed to do was image at high magnification in that proximal region of the pouch and see if Sqh-GFP is polarized in wildtype cells along certain cell edges aligned with an axis. And if such a polarity is observed, is it present or absent in the DS mutant. From the data shown in Figure 5, I cannot see any significant difference between wildtype and knocked down samples at this low resolution. Any difference, if there is any, is not really interpretable.

Response: We agree that examination of myosin localization at high resolution to see if it is polarized is a worthwhile experiment. We did in fact do this, and myosin (Sqh:GFP) appeared unpolarized in ds mutants. However, the levels of myosin were so low that we didn’t feel confident in our assessment, so we didn’t include it. We now recognize that this was a mistake, and we will include high resolution myosin images and assessments of (lack of) polarity in a revised manuscript to address this comment.

In conclusion, the manuscript has multiple problems that make it imposiible for the authors to make the claims they make in the current manuscript. And even if they calibrated their interpretations to fit the data, there is not much of a simple clear picture as to how FT and DS regulate pouch eccentricity in the larval wing.

Response: We think that the legitimate issues raised are addressable, as described above, while some of the criticisms are incorrect (as noted by Reviewer 1).

Reviewer #2 (Significance (Required)): This manuscript describes experiments studying the role that the protocadherins FAT and DACHSOUS play in determining the two dimensional "shape" of the fruit fly wing. By "shape", the manuscript really means how much the wing's outline, when approximated as an ellipse, deviates from a circle. The elliptical approximations of FT and DS mutant wings more closely resemble a circle compared to the more eccentric wildtype wings. This suggests the molecules contribute to anisotropic growth in some way. A great deal of attention has been paid on how FT and DS regulate overall organ growth and planar cell polarity, and the Irvine lab has made extensive contributions to these questions over the years. Somewhat understudied is how FT and DS regulate wing shape, and this manuscript focuses on that. It follows up on an interesting result that the Irvine lab published in 2019, in which mud mutants randomized spindle pole orientation in wing cells but did not change the eccentricity of wings, ruling out biased cell division orientation as a mechanism for the anisotropic growth.

__Reviewer #3 (Evidence, reproducibility and clarity (Required)): __ Summary The authors investigate the mechanisms underlying epithelial morphogenesis using the Drosophila wing as a model system. Specifically, they analyze the contribution of the conserved Fat/Ds pathway to wing shape regulation. The main claim of the manuscript is that Ds/Fat controls wing shape by regulating tissue mechanical stress through MyoII levels, independently of Hippo signaling and tissue growth.

Major Comments To support their main conclusions, the authors should address the following major points and consider additional experiments where indicated. Most of the suggested experiments are feasible within a reasonable timeframe, while a few are more technically demanding but would substantially strengthen the manuscript's central claims.

Figure 1: The authors use temperature-sensitive inactivation of Fat or Ds to determine the developmental window during which these proteins regulate wing shape. To support this claim, it is essential to demonstrate that upon downshift during early pupal stages, Ds or Fat protein levels are restored to normal. For consistency, please include statistical analyses in Figure 1P and ensure that all y-axis values in shape quantifications start at 1.

Response: We will do the requested antibody stains for Fat (Ds antibody is unfortunately no longer available, but the point made by the reviewer can be addressed by Fat as the approach and results are the same for both genes). We have also added the requested statistical analysis to Fig 1P, and adjusted the scales as requested.

Figure 2: The authors propose that wing shape is regulated by Fat/Ds during larval development. However, Figure 2L suggests that wing elongation occurs in control conditions between 6 and 12 h APF, while this elongation is not observed upon Ds RNAi. The authors should therefore perform downshift experiments while monitoring wing shape during the pupal stage to substantiate their main claim. In addition, equivalent data for Fat loss of function should be included to support the assertion that Fat and Ds act similarly.

Response: As noted in our response to point 1 of Reviewer 1, we agree that there does seem to be relatively more elongation in control wings than in ds RNAi wings, but we think this likely reflects effects of ds on growth during larval stages, and we will revise the manuscript to comment on this.

We will also add the suggested examination of fat RNAi pupal wings.

The suggested examination of pupal wing shape in downshift experiments is unfortunately not feasible. Our temperature shift experiments expressing ds or fat RNAi are done using the UAS-Gal4-Gal80tssystem. We also use the UAS-Gal4 system to mark the pupal wing. If we do a downshift experiment, then expression of the fluorescent marker will be shut down in parallel with the shut down of ds or fat RNAi, so the pupal wings would no longer be visible.

Figure 3: The authors state that "These observations indicate that Ds-Fat signaling influences wing shape during the initial formation of the wing pouch, in addition to its effects during wing growth." This conclusion is not fully supported, as the authors only examine wing shape at 72 h AEL. At this stage, fat or ds mutant wings already display altered morphology. The authors could only make this claim if earlier time points were fully analyzed. In fact, the current data rather suggest that Ds function is required before 72 h AEL, as a rescue of wing shape is observed between 72 and 120 h AEL.

Response: First, I think we are largely in agreement with the Reviewer, as the basis for our saying that DS-Fat are likely required during initial formation of the wing pouch is that our data show they must be required before 72 h AEL. Second, 72 h is the earliest that we can look using Wg expression as a marker, as at earlier stages it is in a ventral wedge rather than a ring around the future wing pouch + DV line (eg see Fig 8 of Tripathi, B. K. & Irvine, K. D. The wing imaginal disc. Genetics (2022) doi:10.1093/genetics/iyac020.). We can revise the text to make sure this is clear.

Figure 4: The authors state that "The influence of Ds-Fat on wing shape is not explained by Hippo signaling." However, this conclusion is not supported by their data, which show that partial loss of ex or hippo causes clear defects in wing shape. In addition, the initial wing shape is affected in wts and ex mutants, and hypomorphic alleles were used for these experiments. Therefore, the main conclusion requires revision. It would be useful to include a complete dataset for hippo RNAi, ex, and wts conditions in Figure S1. The purpose and interpretation of the InR^CA experiments are also unclear. While InR^CA expression can increase tissue growth, Hippo signaling has functions beyond growth control. Whether Hippo regulates tissue shape through InR^CA-dependent mechanisms remains to be clarified.

Response: As noted in our response to point 1 of Reviewer 2 - our results emphasize that the effects of Ds-Fat on wing shape cannot be explained solely by effects on Hippo signaling, eg as we stated on page 7 “These observations suggest that Hippo signaling contributes to, but does not fully explain, the influence of ds or fat on adult wing shape.” We also note that impairment of Hippo signaling has similar effects in younger discs, but very different effects in older discs, which clearly indicates that they are having very different effects during disc growth. We will make some revisions to the text to make sure that our conclusions are clear throughout.

While we used a hypomorphic allele for wts, because null alleles are lethal, the ex allele that we used is described in Flybase as an amorph, not a hypomorph, and as noted in our response to Reviewer 2, we will add some discussion about relative strength of effects on Hippo signaling.

In Fig S1, we currently show adult wings for ex[e1] and RNAi-Hpo, and wing discs for wts[P2]/wts[x1], and for ex[e1]. The wts combination does not survive to adult so we can’t include this. We will however, add hpo RNAi wing discs as requested.

              The purpose of including InR^CA experiments is to try to separate effects of Hippo signaling from effects of growth, because InR signaling manipulation provides a distinct mechanism for increasing growth. We will revise the text to try to make sure this is clearer.

Figure 5: This figure presents images of MyoII distribution, but no quantification across multiple samples is provided. Moreover, the relationship between changes in tissue stress and MyoII levels remains unclear. Performing laser ablation and MyoII quantification on the same samples would provide stronger support for the proposed conclusions.

Response: We will revise the quantitation so that it presents analysis of averages across multiple discs, rather than representative examples of single discs.

Both the myosin imaging, and the laser ablation were done on the same genotypes (wildtype and ds) at the same ages (108 h AEL) so we think it is valid to directly compare them. Moreover, the imaging conditions for laser ablation and myo quantification are different, so it’s not feasible to do them at the same time (For ablations we do a single Z plane and a single channel (has to include Ecad, or an equivalent junctional marker) on live discs, so that fast imaging can be done. For Myo imaging we do multiple Z stacks and multiple channels (eg Ecad and Myo), which is not compatible with the fast imaging needed for analysis of laser ablations).

Figure 6: It is unclear when Rok RNAi and Rok^CA misexpression were induced. To substantiate their claims, the authors should measure both MyoII levels and mechanical tension under the different experimental conditions in which wing shape was modified through Rok modulation (i.e. the condition shown in Fig. 7G). For comparison, fat and ds data should be added to Fig 6H. Overall, the effects of Rok modulation appear milder than those of Fat manipulation. Given that Dachs has been shown to regulate tension downstream of Fat/Ds, it would be informative to determine whether tissue tension is altered in dachs mutant wings and to assess the relative contribution of Dachs- versus MyoII-mediated tension to wing shape control. It would also be interesting to test whether Rok activation can rescue dachs loss-of-function phenotypes.

Response: In these Rok experiments there was no separate temporal control of Rok RNAi or Rok^CA expression, they were expressed under nub-Gal4 control throughout development.

We will add examination of myosin in combinations of ds RNAi and rok manipulation as in Fig 7G to a revised manuscript.

Data for fat and ds comparable to that shown in Fig 6H is already presented in Fig 3D, and we don’t think its necessary to reproduce this again in Fig 6H.

We agree that the effects of Rok manipulations are milder than those of Fat manipulations; as we try to discuss, this could be because the pattern or polarity of myosin is also important, not just the absolute level, and we will add assessment of myosin polarity.

The suggestion to also look at dachs mutants is reasonable, and we will add this. In addition, we plan to add an "activated" Dachs (a Zyxin-Dachs fusion protein previously described in Pan et al 2013) that we anticipate will provide further evidence that the effects of Ds-Fat are mediated through Dachs. We will also add the suggested experiment combining Rok activation with dachs loss-of-function.

Figure 7: The authors use genetic interactions to support their claim that Fat controls wing shape independently of Hippo signaling. However, these interactions do not formally exclude a role for Hippo. Moreover, previous work has shown that tissue tension regulates Hippo pathway activity, implying that any manipulation of tension could indirectly affect Hippo and growth. To provide more direct evidence, the authors should further analyze MyoII localization and tissue tension under the various experimental conditions tested (as also suggested above).

Response: As discussed above, our data clearly show that Fat has effects independently of Hippo signaling that are crucial for its effects on wing shape, but we did not mean to imply that the regulation of Hippo signaling by Fat makes no contribution to wing shape control, and we will revise the text to make this clearer. We will also add additional analysis of Myosin localization , as described above.

Reviewer #3 (Significance (Required)): How organ growth and shape are controlled remains a fundamental question in developmental biology, with major implications for our understanding of disease mechanisms. The Drosophila wing has long served as a powerful and informative model to study tissue growth and morphogenesis. Work in this system has been instrumental in delineating the conserved molecular and mechanical processes that coordinate epithelial dynamics during development. The molecular regulators investigated by the authors are highly conserved, suggesting that the findings reported here are likely to be of broad biological relevance.

Previous studies have proposed that anisotropic tissue growth regulates wing shape during larval development and that such anisotropy induces mechanical responses that promote MyoII localization (Legoff et al., 2013, PMID: 24046320; Mao et al., 2013, PMID: 24022370). The Ds/Fat system has also been shown to regulate tissue tension through the Dachs myosin, a known modulator of the Hippo/YAP signaling pathway. As correctly emphasized by the authors, the respective contributions of anisotropic growth and mechanical tension to wing shape control remain only partially understood. The current study aims to clarify this issue by analyzing the role of Fat/Ds in controlling MyoII localization and, consequently, wing shape. This represents a potentially valuable contribution. However, the proposed mechanistic link between Fat/Ds and MyoII localization remains insufficiently explored. Moreover, the role of MyoII is not fully discussed in the broader context of Dachs function and its known interactions with MyoII (Mao et al., 2011, PMID: 21245166; Bosveld et al., 2012, PMID: 22499807; Trinidad et al., 2024, PMID: 39708794). Most importantly, the experimental evidence supporting the authors' conclusions would benefit from further strengthening. It should also be noted that disentangling the relative contributions of anisotropic growth and MyoII polarization to tissue shape and size remains challenging, as MyoII levels are known to increase in response to anisotropic growth (Legoff et al., 2013; Mao et al., 2013), and mechanical tension itself can modulate Hippo/YAP signaling (Rauskolb et al., 2014, PMID: 24995985).

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Referee #3

Evidence, reproducibility and clarity

Summary

The authors investigate the mechanisms underlying epithelial morphogenesis using the Drosophila wing as a model system. Specifically, they analyze the contribution of the conserved Fat/Ds pathway to wing shape regulation. The main claim of the manuscript is that Ds/Fat controls wing shape by regulating tissue mechanical stress through MyoII levels, independently of Hippo signaling and tissue growth.

Major Comments

To support their main conclusions, the authors should address the following major points and consider additional experiments where indicated. Most of the suggested experiments are feasible within a reasonable timeframe, while a few are more technically demanding but would substantially strengthen the manuscript's central claims.

Figure 1:

The authors use temperature-sensitive inactivation of Fat or Ds to determine the developmental window during which these proteins regulate wing shape. To support this claim, it is essential to demonstrate that upon downshift during early pupal stages, Ds or Fat protein levels are restored to normal. For consistency, please include statistical analyses in Figure 1P and ensure that all y-axis values in shape quantifications start at 1.

Figure 2:

The authors propose that wing shape is regulated by Fat/Ds during larval development. However, Figure 2L suggests that wing elongation occurs in control conditions between 6 and 12 h APF, while this elongation is not observed upon Ds RNAi. The authors should therefore perform downshift experiments while monitoring wing shape during the pupal stage to substantiate their main claim. In addition, equivalent data for Fat loss of function should be included to support the assertion that Fat and Ds act similarly.

Figure 3:

The authors state that "These observations indicate that Ds-Fat signaling influences wing shape during the initial formation of the wing pouch, in addition to its effects during wing growth." This conclusion is not fully supported, as the authors only examine wing shape at 72 h AEL. At this stage, fat or ds mutant wings already display altered morphology. The authors could only make this claim if earlier time points were fully analyzed. In fact, the current data rather suggest that Ds function is required before 72 h AEL, as a rescue of wing shape is observed between 72 and 120 h AEL.

Figure 4:

The authors state that "The influence of Ds-Fat on wing shape is not explained by Hippo signaling." However, this conclusion is not supported by their data, which show that partial loss of ex or hippo causes clear defects in wing shape. In addition, the initial wing shape is affected in wts and ex mutants, and hypomorphic alleles were used for these experiments. Therefore, the main conclusion requires revision. It would be useful to include a complete dataset for hippo RNAi, ex, and wts conditions in Figure S1. The purpose and interpretation of the InR^CA experiments are also unclear. While InR^CA expression can increase tissue growth, Hippo signaling has functions beyond growth control. Whether Hippo regulates tissue shape through InR^CA-dependent mechanisms remains to be clarified.

Figure 5:

This figure presents images of MyoII distribution, but no quantification across multiple samples is provided. Moreover, the relationship between changes in tissue stress and MyoII levels remains unclear. Performing laser ablation and MyoII quantification on the same samples would provide stronger support for the proposed conclusions.

Figure 6:

It is unclear when Rok RNAi and Rok^CA misexpression were induced. To substantiate their claims, the authors should measure both MyoII levels and mechanical tension under the different experimental conditions in which wing shape was modified through Rok modulation (i.e. the condition shown in Fig. 7G). For comparison, fat and ds data should be added to Fig 6H.<br /> Overall, the effects of Rok modulation appear milder than those of Fat manipulation. Given that Dachs has been shown to regulate tension downstream of Fat/Ds, it would be informative to determine whether tissue tension is altered in dachs mutant wings and to assess the relative contribution of Dachs- versus MyoII-mediated tension to wing shape control. It would also be interesting to test whether Rok activation can rescue dachs loss-of-function phenotypes.

Figure 7:

The authors use genetic interactions to support their claim that Fat controls wing shape independently of Hippo signaling. However, these interactions do not formally exclude a role for Hippo. Moreover, previous work has shown that tissue tension regulates Hippo pathway activity, implying that any manipulation of tension could indirectly affect Hippo and growth. To provide more direct evidence, the authors should further analyze MyoII localization and tissue tension under the various experimental conditions tested (as also suggested above).

Significance

How organ growth and shape are controlled remains a fundamental question in developmental biology, with major implications for our understanding of disease mechanisms. The Drosophila wing has long served as a powerful and informative model to study tissue growth and morphogenesis. Work in this system has been instrumental in delineating the conserved molecular and mechanical processes that coordinate epithelial dynamics during development. The molecular regulators investigated by the authors are highly conserved, suggesting that the findings reported here are likely to be of broad biological relevance.

Previous studies have proposed that anisotropic tissue growth regulates wing shape during larval development and that such anisotropy induces mechanical responses that promote MyoII localization (Legoff et al., 2013, PMID: 24046320; Mao et al., 2013, PMID: 24022370). The Ds/Fat system has also been shown to regulate tissue tension through the Dachs myosin, a known modulator of the Hippo/YAP signaling pathway. As correctly emphasized by the authors, the respective contributions of anisotropic growth and mechanical tension to wing shape control remain only partially understood. The current study aims to clarify this issue by analyzing the role of Fat/Ds in controlling MyoII localization and, consequently, wing shape. This represents a potentially valuable contribution. However, the proposed mechanistic link between Fat/Ds and MyoII localization remains insufficiently explored. Moreover, the role of MyoII is not fully discussed in the broader context of Dachs function and its known interactions with MyoII (Mao et al., 2011, PMID: 21245166; Bosveld et al., 2012, PMID: 22499807; Trinidad et al., 2024, PMID: 39708794). Most importantly, the experimental evidence supporting the authors' conclusions would benefit from further strengthening. It should also be noted that disentangling the relative contributions of anisotropic growth and MyoII polarization to tissue shape and size remains challenging, as MyoII levels are known to increase in response to anisotropic growth (Legoff et al., 2013; Mao et al., 2013), and mechanical tension itself can modulate Hippo/YAP signaling (Rauskolb et al., 2014, PMID: 24995985).

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Referee #1

Evidence, reproducibility and clarity

Summary:

In this work, Tripathi et al address the open question of how the Fat/Ds pathway affects organ shape, using the Drosophila wing as a model. The Fat/Ds pathway is a conserved but complex pathway, interacting with Hippo signalling to affect growth and providing planar cell polarity that can influence cellular dynamics during morphogenesis. Here, authors use genetic perturbations combined with quantification of larval, pupal, and adult wing shape and laser ablation to conclude that the Ft/Ds pathway affects wing shape only during larval stages in a way that is at least partially independent of its interaction with Hippo and rather due to an effect on tissue tension and myosin II distribution. Overall the work is clearly written and well presented. I only have a couple major comments on the limitations of the work.

Major comments:

1. Authors conclude from data in Figures 1 and 2 that the Fat/Ds pathway only affects wing shape during larval stages. When looking at the pupal wing shape analysis in Figure 2L, however, it looks there is a difference in wt over time (6h-18h, consistent with literature), but that difference in time goes away in RNAi-ds, indicating that actually there is a role for Ds in changing shape during pupal stages, although the phenotype is clearly less dramatic than that of larval stages. No statistical test was done over time (within the genotype), however, so it's hard to say. I recommend the authors test over time - whether 6h and 18h are different in wild type and in ds mutant. I think this is especially important because there is proximal overgrowth in the Fat/Ds mutants, much of which is contained in the folds during larval stages. That first fold, however, becomes the proximal part of the pupal wing after eversion and contracts during pupal stages to elongate the blade (Aiguoy 2010, Etournay 2015). Also, according to Trinidad Curr Biol 2025, there is a role for Fat/Ds pathway in pupal stages. All of that to say that it seems likely that there would be a phenotype in pupal stages. It's true it doesn't show up in the adult wing in the experiments in Fig 1, but looking at the pupal wing itself is more direct - perhaps the very proximal effect is less prominent later, as there is potential for further development after 18hr before adulthood and the most proximal parts are likely anyway excluded in the analysis.
2. I think there needs to be a mention and some discussion of the fact that the wing is not really flat. While it starts out very flat at 72h, by 96h and beyond, there is considerable curvature in the pouch that may affect measurements of different axis and cell shape. It is not actually specified in the methods, so I assume the measurements were taken using a 2D projection. Not clear whether the curvature of the pouch was taken into account, either for cell shape measurements presented in Fig 4 or for the wing pouch dimensional analysis shown in Fig 3, 6, and supplements. Do perturbations in Ft/Ds affect this curvature? Are they more or less curved in one or both axes? Such a change could affect the results and conclusions. The extent to which the fat/ds mutants fold properly is another important consideration that is not mentioned. For example, maybe the folds are deeper and contain more material in the ds/fat mutants, and that's why the pouch is a different shape? At the very least, this point about the 3D nature of the wing disc must be raised in discussion of the limitations of the study. For the cell shape analysis, you can do a correction based on the local curvature (calculated from the height map from the projection). For the measurement of A/P, D/V axes of the wing pouch, best would be to measure the geodesic distance in 3D, but this is not reasonable to suggest at this point. One can still try to estimate the pouch height/curvature, however, both in wild type and in fat/ds mutants.

Minor comments:

1. The analysis of the laser ablation is not really standard - usually one looks at recoil velocity or a more complicated analysis of the equilibrium shape using a model (e.g Shivakumar and Lenne 2016, Piscitello-Gomez 2023, Dye et al 2021). One may be able to extract more information from these experiments - nevertheless, I doubt the conclusions would change, given that that there seems to be a pretty clear difference between wt and ds (OPTIONAL).
2. Figure 7G: I think you also need a statistical test between RNAi-ds and UAS-rokCA+RNAi-ds.
3. In the discussion, there is a statement: "However, as mutation or knock down of core PCP components, including pk or sple, does not affect wing shape... 59." Reference 59 is quite old and as far as I can tell shows neither images nor quantifications of the wing shape phenotype (not sure it uses "knockdown" either - unless you mean hypomorph?). A more recent publication Piscitello-Gomez et al Elife 2023 shows a very subtle but significant wing shape phenotype in core PCP mutants. It doesn't change your logic, but I would change the statement to be more accurate by saying "mutation of core PCP components has only subtle changes in adult wing shape"

Referee cross-commenting

Reviewer2:

Reviewer 2 makes the statement: "The distance along the AP boundary from the pouch border to DV midline is topologically comparable to the PD length of the adult wing. The distance along the DV boundary from A border to P border is topologically comparable to the AP length of the adult wing."

I disagree - the DV boundary wraps around the entire margin of the adult wing (as correctly drawn with the pink line in Fig 2A). It is not the same as the wide axis of the adult wing (perpendicular to the AP boundary). It is not trivial to map the proximal-distal axis of the larval wing to the proximal-distal axis of the adult, due to the changes in shape that occur during eversion. Thus, I find it much easier to look at the exact measurement that the authors make, and it is much more standard in the field, rather than what the reviewer suggests. Alternatively, one could I guess measure in the adult the ratio of the DV margin length (almost the circumference of the blade?) to the AP boundary length. That may be a more direct comparison. Actually the authors leave out the term "boundary" - what they call AP is actually the AP boundary, not the AP axis, and likewise for the DV - what they measure is DV boundary, but I only noticed that in the second read-through now. Just another note, these measurements of the pouch really only correspond to the very distal part of the wing blade, as so much of the proximal blade comes from the folds in the wing disc. Therefore, a measurement of only distal wing shape would be more comparable.

Reviewer 2 states that authors cannot definitively conclude anything about mechanical tension from their reported cutting data because the authors have not looked at initial recoil velocity. I strongly disagree. The wing disc tissue is elastic on much longer timescales than what's considered after laser ablation (even hours), and the shape of the tissue after it equilibrates from a circular cut (1-2min) can indeed be used to infer tissue stresses (see Dye et al Elife 2021, Piscitello-Gomez et al eLife 2023, Tahaei et al arXiv 2024). In the wing disc, the direction of stresses inferred from initial recoil velocity are correlated with the direction of stresses inferred from analysing the equilibrium shape after a circular cut. Rearrangements, a primary mechanism of fluidization in epithelia, does not occur within 1'. Analysing the equilibrium shape after circular ablation may be more accurate for assessing tissue stresses than initial recoil velocity - in Piscitello-Gomez et al 2023, the authors found that a prickle mutation (PCP pathway) affected initial recoil velocity but not tissue stresses in the pupal wing. Such equilibrium circular cuts have also been used to analyze stresses in the avian embryo, where it correlates with directions of stress gathered from force inference methods (Kong et al Scientific Reports 2019). The Tribolium example noted by the reviewer is on the timescale of tens to hundreds of minutes - much longer than the timescale of laser ablation retraction. It is true the analysis of the ablation presented in this paper is not at the same level as those other cited papers and could be improved. But I don't think the analysis would be improved by additional experiments doing timelapse of initial retraction velocity.

Reviewer 2 states "If cell anistropy is caused by polarized myosin activity, that activity is typically polarized along the short edges not long edges" Not true in this case. Myosin II accumulates along long boundaries (Legoff and Lecuit 2013). "Therefore, interpreting what causes the cell anistropy and how DS regulates it is difficult," Agreed - but this is well beyond the scope of this manuscript. The authors clearly show that there is a change of cell shape, at least in these two regions. Better would be to quantify it throughout the pouch and across multiple discs. Similar point for myosin quantifications - yes, polarity would be interesting and possible to look at in these data, and it would be better to do so on multiple discs, but the lack of overall myosin on the junctions shown here is not nothing. Interpreting what Ft/Ds does to influence tension and myosin and eventually tissue shape is a big question that's not answered here. I think the authors do not claim to fully understand this though, and maybe further toning down the language of the conclusions could help.

Reviewer 3:

I agree with many of the points raised by Reviewer 3, in particular that relevant for Fig 1. The additional experiments looking at myosin II localization and laser ablation in the other perturbations (Hippo and Rok mutants/RNAi) would certainly strengthen the conclusions.

Significance

I think the work provides a clear conceptual advance, arguing that the Ft/Ds pathway can influence mechanical stress independently of its interaction with Hippo and growth. Such a finding, if conserved, could be quite important for those studying morphogenesis and Fat function in this and other organisms. For this point, the genetic approach is a clear strength. Previous work in the Drosophila wing has already shown an adult wing phenotype for Ft/Ds mutations that was attributed to its role in the larval growth phase, as marked clones show aberrant growth in mutants. The novelty of this work is the dissection of the temporal progression of this phenotype and how it relates to Hippo and myosin II activation. It remains unclear exactly how Ft/Ds may affect tissue tension, except that it involves a downregulation of myosin II - the mechanism of that is not addressed here and would involve considerable more work. I think the temporal analysis of the wing pouch shape was quite revealing, providing novel information about how the phenotype evolves in time, in particular that there is already a phenotype quite early in development. As mentioned above, however, the lack of consideration of the wing disc as a 3D object is a potential limitation. While the audience is likely mostly developmental biologists working in basic research, it may also interest those studying the pathway in other contexts, including in vertebrates given its conservation and role in other processes.

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Reply to the reviewers

Overall Response.

We would like to thank the reviewers for their analysis of the manuscript. From their comments it is clear that our manuscript was not. We completely rewrote the manuscript to focus on the central core question which was how does Adam13 regulates gene expression in general and TFap2a in particular leading to the expression of Calpain8 a protein required for CNC migration.

The following model will be the central line of our story. It will address all of the proteins involved and mechanistical evidences that link Adam13 to one of its proven effector target Calpain8.

• *

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

In this manuscript, Pandey et al. show that the ADAM13 protein modulates histone modifications in cranical neural crest and that the Arid3a protein binds the Tfap2a promoter in an Adam13-dependent manner and has promoter-specific effects on transcription. Furthermore, they show that the Adam13 and human ADAM9 proteins associated with histone modifiers as well as proteins involved in RNA splicing. Although the manuscript is mostly clearly written and the figures well assembled, it reads like a couple of separate and unfinished stories.*

I believe that our story line was not clear and that the overarching questions was not well stated. We have made every effort to change this in the revised manuscript. I would like to include a figure that explains the story.

In short:

1 We knew that Adam13 could regulate gene expression in CNC via its cytoplasmic domain.

2 We also knew that this required Adam13 interaction with Arid3a and that a direct target with the transcription factor TFAP2a which in turn regulates functional targets that we had identified including the protocadherin PCNS and the protease Calpain8.

Our goal was to understand the mechanism allowing Adam13 to regulate gene expression.

3 This first part of this manuscript shows how Adam13 modulates Histone modification in vivo in the CNC globally as well as specifically on the Tfap2a promoter. This results I an Open chromatin.

4 Using Chip we show that Adam13 and Arid3a both bind to the Tfap2a promoter and that Arid3a binding to the first ATG depends on Adam13.

5 Using Luciferase reporter we show that both Adam13 and Arid3a can induce expression at the first ATG.

*They show using immunocytochemistry and qPCR that ADAM13 knockouts in CNCs afffects histone modifications. Here ChIP-seq or Cut-n-Run experiments would be more appropriate and would result in a more comprehensive understanding of the changes mediated. *

I agree but we did not have the fund and now I have nobody working in the lab to do this experiment. These are also likely to overlap with the RNAseq data that we have and would simply add more open leads. We selected to go after the only direct target that we know which is TFAP2a and focus on this gene to understand the mechanism.

We believe that the Chip PCR experiment are sufficient for this story.

*The immunohistochemistry assays should at least be verified further using western blotting or other more quantiative methods. *

Immunofluorescence and statistical analysis is a valid quantification method. Western blot of CNC explants is not trivial and requires a large amount of material. Given the small overall change we also would not expect to be able to detect the change over the noise of western blot. The Chip PCR confirms our finding in a completely independent manner.

*The authors then show that ADAM13 interacts with a number of histone modifiers such as KDM3B, KDM4B and KMT2A but strangely they do not follow up this interesting observation to map the interactions further (apart from a co-ip with KMT2A), the domains involved, the functional role of the interactions or how they mediate the changes in chromatin modifications. *

We selected KMT2a because it is expressed in the Hek293T cells. KMT2D has been shown to regulate CNC development in Xenopus and is responsible for the Kabuki syndrome in human. We used aphafold to predict interaction and found that Adam13 interact with the Set domain. In addition we see multiple Set- containing domain protein in our mass spec data. The mass spec is done on Human hek293T cells that express a subset of KMT proteins. We now include evidence that Adam13 interact with the KMT2D SET domain (new figure 5D)

The authors then show that ADAM13 affects expression of the TFAP2a gene in a promoter specific manner - affecting expression from S1 but not S2.

It is the S1 but not S3. Adam13 has no effect on S2.

• They further show that ADAM13 affects the binding of the Arid3 transcription fator to the S1-promoter but not to the S3 promoter. However, ADAM13 was present at both promoters. Absence of ADAM13 resulted in increased H3K9me2/3 and decreased H3K4me3 at the S1 promoter whereas only H3K4me3 was changed at the S2 promoter*

S3 not S2*. Unfortunately, they do not show how this is mediated or through which binding elements this takes place. Why is ADAM13 present at both promoters but only affects Arid3 binding at S1? *

We agree this is a very interesting question that could be the subject of an entire publication. Promoter deletion and mutation to identify which site are bound by and modulated by Adam13/Arid3a is not trivial.

*The authors claim that transfecting Arid3a and Adam13 together further increases expression from a reporter (Fig 4E) but this is not true as no statistical comparison is done between the singly transfected and double transfected cells. *

This is correct, there is a small increase that is not significant with both. The fact that both proteins can induce the promoter suggest but does not prove that they can have additive roles. The loss of function experiment shows that the human Arid3a expressed in Hek293T cells is important for Adam13 increases of S1. It is possible that the dose of the endogenous Arid3a is sufficient to get full activity of Adam13.* Then the authors surprisingly start investigating association of proteins with the two isoforms of TFAP2a which in the mind of this reviewer is a different question entirely. *

We agree and have removed this part of the manuscript.

*They find a number of proteins involved in splicing. And the observation that ADAM13 also interacts with splicing factors is really irrelevant in terms of the story that they are trying to tell. Transcription regulation and splicing are different processes and although both affect the final outcome, mRNA, they need to be investigated separately. The link is at least not very clear from the manuscript. Again, the effects on splicing are not further investigated through functional analysis and as presented the data presented is too open-ended and lacking in clarity. *

We agree that beside the different activities of the TFap2a isoform, the rest of the splicing regulation could be a separate study. We were interested to understand how these two isoforms could activate Calpain8 so differently this is why we looked at LC/MS/MS. We have removed this part of the story from the manuscript.*

Additional points: 1. In the abstract they propose that the ADAMs may act as extracellular sensors. This is not substantiated by the results. *

As an extracellular protein translocating into the nucleus it is a possibility that we propose, but I agree this is not investigated in this manuscript. We will modify the text.* 2. Page 5, line 16: what is referred to by 6 samples 897 proteins? Were 6 samples analyzed for each condition? The number of repeats for the mass spec analysis is not clear from the text nor are the statistical parameters used to analyse the data. This is also true for the mass spec presented in the part on TFAP2aL-S1 and Adam13 regulate splicing. Statistics and repeats are not presented. *

In general we provide biological triplicate and use the statistical function of Scaffold to identify proteins that are significantly enriched or absent in each samples.

When we specify 6 samples it means 6 independent proteins samples were analyzed and used for our statistic. We use Scafold T-test with a p value less than 0.05. Peptides were identified with 95% confidence and proteins with 99% confidence.* 3. Page 6, line 19: set domain should be SET domain. *

Yes* 4. The number of repeats in the RNA sequencing of the CNCs is not clear from the text. *

Three biological replicates (Different batch of embryos from different females).* 5. The explanation of Figure C is a bit lacking. There are two forms of TFAP2a, L and S, but only one is presented in the figure. Do both forms have the extra S1-3 exons? Also, at the top of the figure it is not clear that the boxes are part of a continuous DNA sequence. Also, it is not clear which codon is not coding. *

Xenopus laevis are pseudo tetraploid giving in most cases L and S genes in addition to the 2 alleles from being diploid. The TFAP2a gene structure is conserved between both aloalleles and is similar to the human gene. For promoter analysis and Chip PCR we chose one of the alloallele (L), given that the RNAseq data showed that both genes and variant behave the same in response to Adam13. This only becomes important in loss of function experiment in which both L and S version need to be knock down or Knock out.

* In the sashimi plot there are green and pink shaded areas. What do they denote? What exactly is lacking in the MO13 mutant - seems that a particular exon is missing suggesting skipping?*

MO13 is a morpholino that bocks the translation of Adam13 (Already characterized with >90% of the protein absent) but does not affect Adam13 mRNA expression.* 7. Page 11, line 9: „with either MbC or MbC and MO13" needs to be rephrased. *

Will do *8. Page 11, line 19: „the c-terminus of....and S3) and" should be „the C-terminus of...and S3 and". ** 9. Page 15, line 10: substrateS 10. Page 16, line 23: the sentence „increases H3K9 to the promoter of the most upstream" needs revision. 11. Page 26, line 12: Here the authors say: „for two samples two-tail unpaired". What does this mean? Statistics should not be performed on fewer than three samples. In legnd to Figure 6 it indicates that T-test was performed on two samples. 12. The discussion should be shortened and simplified. 13. Figure 1 legend. How many images were quantitated for each condition? *

At least 3 images per condition. For 3 independent experiments. (9 images per condition).* 14. Figure 2 has a strange order of panels where G is below B. 15. Figure 6 legend, line 12. „proteins that were significantly enriched in either of the 2 samples" is not very clear. What exactly does this mean?

Reviewer #1 (Significance (Required)):

If the authors follow up on either the transcription-part of the story, or the splicing part of the story, they are likely to have important results to present. However, in the present format the paper is lacking in focus as both issues are mixed together without a clear end-result. *

We have entirely changed the paper according to these comments.

*

• *

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

Panday et al seeks to determine the function of ADAM13 in regulating histone modifications, gene expression and splicing during cranial neural crest development. Specifically, the authors tested how Adam13, a metalloprotease, could modify chromatin by interaction with Arid3a and Tfap2a and RNA splicing and gene expression. They then utilize knockouts in Xenopus and HEK293T cells followed by immunofluorescence, IPs, BioID, luciferase assays, Mass spec and RNA assays. Although there is some strong data in the BioID and luciferase experiments, the manuscript tells multiple stories, linking together too many things to make a compelling story. The result is a paper that is very difficult to read and understand the take home message. In addition, some of the conclusions are not supported by the data. This unfortunately means it is not ready for publication. However, I have added below some suggestions that would strengthen the manuscript. My comments are below: *

Clarity is clearly an issue here. The new version is entirely re-written.

Here is the take home message:

We knew that Adam13 could regulate gene expression via its cytoplasmic domain. One of the key targets was identified as Calpain8, a protein critical for CNC migration. We subsequently showed that Adam13 and Arid3a regulated Tfap2a expression which in turn regulated Calpain8.

In this manuscript we investigated 1) how Adam13 regulates TFAP2a and 2) how Tfap2a controls Calpain8 expression.

The take home message is that Adam13 bind to Histone methyl transferase and changes the histone methylation code overall in the CNC and in particular at the TFAP2a promoter. This results in more open chromatin. We further find that Adam13 binds to the Tfap2a promoter in vivo and is important for Arid3a binding to the first start. Tfap2a that include this N-terminus sequence regulates Capn8 expression.*

Major comments: 1. I think it would be better to split out the chromatin modification function from the splicing in two separate papers. While there is a connection, having it all together makes the story difficult to follow. *

Agree but I believe that the S1 vs S3 story of Tfap2a is important for the overall story. The new paper does not emphasize splicing.* 2. The immunofluorescence of H3K9me2/3, in Figure 1, 2, 3 following Adam13 knockdown is not convincing. There seems to be a strong edge effect especially in Figure 2 and 3. *

The statistical analysis shows that the results, while modest, are significant (Three independent experiments using 3 different females and 3 explants for each condition were analyzed). The edge effect observed is eliminated by the mask that we use that normalize the expression to either DAPI or Snai2. The edge effect is seen in both control and KD as well. These are further confirmed by the Chip PCR on one direct target.

Similarly the Arid3a expression in Supp Figure 1 if anything seems increased.

We have previously shown that Arid3a expression is not affected by Adam13 KD (Khedgikar et al). Our point here is simply that the difference in Tfap2a cannot be explained by a decrease in Arid3a expression. It is not a critical figure and was eliminated in the new manuscript.

*It would be better to quantify by western blot and not by fluorescent intensity since it is difficult to determine what a small change in fluorescent intensity means in vivo. *

Not all antibodies used here work by western blot and the quantity of material required for western blot is much larger than IF. Given the small overall changes and the variability observed in Western blot it is not a viable alternative.

IF is a quantitative method that has been used widely to assert increase or decrease of protein level or post translational modification. The fact that the same post translational modification that we see in cranial neural crest explants can also be seen by ChipPCR on the Tfap2a promoter confirm this observation.

*Also, it does not say in the text or the figure legend what these are, Xenopus explants of CNC? *

These are CNC explants. It is now clearly stated in the figure legend.* 3. The rationale for isolating KMT2A from the other chromatin modifiers in the dataset is not clear. *

The new manuscript is clarifying that point. Because we are using Hek293T cells in this assay, which are human embryonic kidney derived instead of Xenopus Cranial neural crest cells, we are not interested in a specific protein but rather a family of protein that can modify histones (KMT and KDM). Our rational is if Adam13 can bind to KMT2 via the SET domain, it is likely to interact with KTM2 that are expressed in the CNC. KMT2A and D are expressed in the CNC. This is why we selected KMT2a here (Hek293T). We now include 1 co-IP with the Set domain of Xenopus KMT2D (new figure 5D)

From the RNA-seq in Supp Figure 2 it is not changed as much as likely some of the others.

The new manuscript addresses this point. We did not show or expect that the loss of Adam13 would affect mRNA expression of Kmt2.

*Also, the arrow seems to indicate that it is right above the cutoff. What about other proteins with ATPase activity? That is the top hit in the Dot plot nuclear function. Would be helpful to write out Adam13 cytoplasm/nucleus here. *

We have used another set of proteomics data that does not include the cytoplasmic/nuclear extract to simplify the results. We hope that the changes make it more obvious.

Given that we are looking at Chromatin remodeling enzyme here we did not chose to investigate further in this report the ATPase. This is such a wide category that it could lead us away from the main story here.* 4. The splicing information, while interesting would be better as a different manuscript. The sashimi plot requires more explanation as written. *

We agree and think that a simple representation of the fold change of the different isoform is more obvious. It is now a minor part of figure 1 and the legend has been improved to describe the method here.

How do you tell if the interactions are changed from this?

I do not understand this question. The sashimi plot indicate the read through from the mRNA that goes from one exon to the next quantifying the specific exon usage. It can therefore be quantified and compared between different conditions.

• The authors argue there is a reduction of Tfap2a in Figure 3H but half the explant is not expressing sox9 in the Adam13 knockdown. How is this kind of experiment controlled when measure areas that don't have any fluorescence because of the nature of the explants? *

We have removed this figure as we had already shown previously by western blot that Tfap2a protein decreased in MO13 embryos. As noted on the histogram, the fluorescence is only measured in Sox9 positive cells in each explant. Three independent experiments with 3 explants for each. We also have seen a decrease by Western blot and mRNA expression (Both RNAseq and realtime PCR). In most of our explants, the vast majority of the cells are positive for Snai2 and Sox9, while those that are negative are positive for Sox3 (data not shown here). There is always less signal in the center of the explant possibly due to the penetration of antibody or interference with the signal by the cells pigment or yolk autofluorescence. Our control explants have the same effect so our quantification is valid.* 5. The use of a germ line Xenopus mutant for Adam13 is great but how were these knockouts validated? *

All of the KO were validated by sequencing, RNAseq and protein expression. These are now included in the supplemental figure 1.

*More information is required here. The Chip-qPCR has a lot of variability between the samples, especially in the H3K9me2/3. *

All ChipPCR were performed on Xenopus embryos. The variability is tested by statistical analysis and is either significant or not.

Because these are in cell lines, this should be more consistent.

They are not in cell lines but in Xenopus embryos.

• In addition, it is difficult to understand what this means for cranial neural crest cells when assaying in HEK293T cells with the luciferase assay. *

We use Luciferase assay in Hek293T cells to test if Xenopus protein can induce a specific reporter (Gain of function). We also use luciferase reporter in Xenopus to test if they can perceive the loss of a specific protein (For example Adam13).

Our result show that Adam13 or Arid3a expression in Hek293T cells can induce the TFAP2S1 reporter. * 6. The migration assay shows only an example of what it looks like to have defective migration. But it would be better to show control embryos, embryos with Adam13 knockdown and what the rescues look like so the reader can make their own conclusion.*

We can certainly include this but have published this assay in multiple publication before. The picture is a single example, the histogram shows that statistical validation.

• The argument from the section above suggests the S1 isoform is the primary one but S3 in this assay also rescues, please explain what this result means since it seems to suggest that even though these isoforms have different activity the function is similar in terms of the ability to rescue defective migration. *

The result in Hek293T cells shows that only TFAP2aS1 can induce Calpain8, while both S1 and S3 can partially rescue CNC migration in embryos lacking Adam13. The issue here is the dose of mRNA injected for each variant might be too high. Adam13 proteolytic activity is also critical, so we do not expect a complete rescue. The fact that S1 is significantly better at rescuing than S3 is relevant here. It is possible that if we were to decrease the dose of each mRNA we would find one in which S3 no longer rescues but S1 does.

* The next section again talks about yet another protein Calpain-8. Here the authors use MO13 for luciferase assays instead of HEK293 cells. The authors do not explain why they decided to switch from cells to MO.*

Calpain8 is one of the validate target of Adam13 that can rescue CNC migration (Cousin et al Dev Cell). We use the luciferase reporter corresponding to the Xenopus Capn8 reporter to show 1 in vivo that loss of Adam13 reduce its expression (Similar to the Capn8 gene). We then went in vitro using Hek293T cells for gain of function experiment that shows that only the Tfaps2S1 variant can induce it while S3 does not.

We hope that the graphical summary and the new manuscript make this clear.* 8. The experiment to IP RNA supports only the correlation that Adam9 and Adam13 bind RNA and RNA binding proteins to regulate splicing. This conclusion presented is not supported by the data presented here. While there is a sentence about why Adam9 was chosen here, it would be preferred to focus on Adam13 as the rest of the manuscript is focused on Adam13. The conclusions are generalized to all ADAMs, but ADAM13 and ADAM9 are the only ADAMs investigated in the manuscript *

This figure is no longer included. For each of the protein classes that we identify by Masspec we try to find a validation. RNA-IP is simply a validation that Adam13 and Adam9 can bind to complexes that include RNA in a cytoplasmic domain dependent fashion. The conclusion that Adam13 and possibly ADAM9 might be involved in regulating splicing is 1) that the protein associated with Adam13 are include multiple splicing factors, 2) that the RNAseq analysis shows abnormal splicing in CNC missing Adam13 and 3) that the form of TFAP2a induced by Adam13 (S1) associate significantly more with splicing factor than the S3 isoform.

We agree that the generalization to other ADAM is not demonstrated here but only suggested. We selected ADAM9 and ADAM19 because we have shown that they can each rescue Adam13 function in the CNC. Unfortunately there are no ADAM19 antibody that work by IP on the market. We have tested multiple company and multiple cell lines.

We believe that the ADAM9 experiment is critical to show that the protein associated with Adam13 are not simply the result of overexpressing a different species protein sin ADAM9 is the endogenous protein.*

Minor comments 1. The manuscript using a lot of abbreviations (PCNS, NI, MO, SH3) and lingo that are unclear to a general reader. Please define acronyms when first used, as well as be clear on which model is being used in each experiment. *

We have corrected this* 2. Similarly, the figures are not labeled such that a reader would be able to understand ie MO13 should be Adam13 knockdown etc. *

We have corrected this in the legend

• Please identify the genes on the heatmap and some highlighted genes from volcano plot from the RNA-seq.*

The volcano plot is from MS/MS not RNAseq. We have list of all of the genes and/or proteins corresponding to each figure in tables

We now have a figure from the RNAseq and a subset of genes of interest are show. *4. Why use the flag tag in Figure 5? *

We used Flag-tagged construct to only immunoprecipitated the variants and not the endogenous TFPA2a in these experiments. Also we used RFP-Flag to eliminate any protein that bound to the tag or the antibody.

This figure is no longer in the manuscript.* 5. Is the data in figure 4A-D the same as Supp. Figure 4A-D? *

These are independent biological replicates of the same experiment.* 6. Please italicize gene symbols - e.g. "key transcription factors that exemplify CNC, such as the SOX9, FOXD3, SNAI1, SNAI2, and TFAP2 family". *

We clearly have missed some, we are using italicized for gene, and regular for proteins. It might not be clear in the text when we are referring to genes and proteins. We will correct this in the rewrite. 7. Please review the manuscript for grammatical and typographical errors. * We have used all available software including Word and Grammarly. We will try to improve on the next version. **Cross-commenting**

I think the two reviewers on one the same page on this manuscript.

Reviewer #2 (Significance (Required)):

If more solid, would be a conceptual advance in role of Adam13 in mediating chromatin modification and transcription factors, adds to exiting work from this lab, good for a specialize audience, my expertise is in in neural crest development, non-mammalian modes, epigenetic regulators.*

• *

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Referee #2

Evidence, reproducibility and clarity

Panday et al seeks to determine the function of ADAM13 in regulating histone modifications, gene expression and splicing during cranial neural crest development. Specifically, the authors tested how Adam13, a metalloprotease, could modify chromatin by interaction with Arid3a and Tfap2a and RNA splicing and gene expression. They then utilize knockouts in Xenopus and HEK293T cells followed by immunofluorescence, IPs, BioID, luciferase assays, Mass spec and RNA assays. Although there is some strong data in the BioID and luciferase experiments, the manuscript tells multiple stories, linking together too many things to make a compelling story. The result is a paper that is very difficult to read and understand the take home message. In addition, some of the conclusions are not supported by the data. This unfortunately means it is not ready for publication. However, I have added below some suggestions that would strengthen the manuscript. My comments are below:

Major comments:

1. I think it would be better to split out the chromatin modification function from the splicing in two separate papers. While there is a connection, having it all together makes the story difficult to follow.
2. The immunofluorescence of H3K9me2/3, in Figure 1, 2, 3 following Adam13 knockdown is not convincing. There seems to be a strong edge effect especially in Figure 2 and 3. Similarly the Arid3a expression in Supp Figure 1 if anything seems increased. It would be better to quantify by western blot and not by fluorescent intensity since it is difficult to determine what a small change in fluorescent intensity means in vivo. Also, it does not say in the text or the figure legend what these are, Xenopus explants of CNC?
3. The rationale for isolating KMT2A from the other chromatin modifiers in the dataset is not clear. From the RNA-seq in Supp Figure 2 it is not changed as much as likely some of the others. Also, the arrow seems to indicate that it is right above the cutoff. What about other proteins with ATPase activity? That is the top hit in the Dot plot nuclear function. Would be helpful to write out Adam13 cytoplasm/nucleus here.
4. The splicing information, while interesting would be better as a different manuscript. The sashimi plot requires more explanation as written. How do you tell if the interactions are changed from this? The authors argue there is a reduction of Tfap2a in Figure 3H but half the explant is not expressing sox9 in the Adam13 knockdown. How is this kind of experiment controlled when measure areas that don't have any fluorescence because of the nature of the explants?
5. The use of a germ line Xenopus mutant for Adam13 is great but how were these knockouts validated? More information is required here. The Chip-qPCR has a lot of variability between the samples, especially in the H3K9me2/3. Because these are in cell lines, this should be more consistent. In addition, it is difficult to understand what this means for cranial neural crest cells when assaying in HEK293T cells with the luciferase assay.
6. The migration assay shows only an example of what it looks like to have defective migration. But it would be better to show control embryos, embryos with Adam13 knockdown and what the rescues look like so the reader can make their own conclusion. The argument from the section above suggests the S1 isoform is the primary one but S3 in this assay also rescues, please explain what this result means since it seems to suggest that even though these isoforms have different activity the function is similar in terms of the ability to rescue defective migration.
7. The next section again talks about yet another protein Calpain-8. Here the authors use MO13 for luciferase assays instead of HEK293 cells. The authors do not explain why they decided to switch from cells to MO.
8. The experiment to IP RNA supports only the correlation that Adam9 and Adam13 bind RNA and RNA binding proteins to regulate splicing. This conclusion presented is not supported by the data presented here. While there is a sentence about why Adam9 was chosen here, it would be preferred to focus on Adam13 as the rest of the manuscript is focused on Adam13. The conclusions are generalized to all ADAMs, but ADAM13 and ADAM9 are the only ADAMs investigated in the manuscript

Minor comments

1. The manuscript using a lot of abbreviations (PCNS, NI, MO, SH3) and lingo that are unclear to a general reader. Please define acronyms when first used, as well as be clear on which model is being used in each experiment.
2. Similarly, the figures are not labeled such that a reader would be able to understand ie MO13 should be Adam13 knockdown etc.
3. Please identify the genes on the heatmap and some highlighted genes from volcano plot from the RNA-seq.
4. Why use the flag tag in Figure 5?
5. Is the data in figure 4A-D the same as Supp. Figure 4A-D?
6. Please italicize gene symbols - e.g. "key transcription factors that exemplify CNC, such as the SOX9, FOXD3, SNAI1, SNAI2, and TFAP2 family".
7. Please review the manuscript for grammatical and typographical errors.

Cross-commenting

I think the two reviewers on one the same page on this manuscript.

Significance

If more solid, would be a conceptual advance in role of Adam13 in mediating chromatin modification and transcription factors, adds to exiting work from this lab, good for a specialize audience, my expertise is in in neural crest development, non-mammalian modes, epigenetic regulators

It looks like there might still be some oscillatory patterns as a function of run order in panel 2a. It could be useful to plot a spline for quick visual inspection. Also, I wonder if a window- rather than a point-based correction might better remove this confound?

Author response:

The following is the authors’ response to the previous reviews

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors describe a new computational method (SegPore), which segments the raw signal from nanopore direct RNA-Seq data to improve the identification of RNA modifications. In addition to signal segmentation, SegPore includes a Gaussian Mixture Model approach to differentiate modified and unmodified bases. SegPore uses Nanopolish to define a first segmentation, which is then refined into base and transition blocks. SegPore also includes a modification prediction model that is included in the output. The authors evaluate the segmentation in comparison to Nanopolish and Tombo (RNA002) as well as f5c and Uncalled 4 (RNA004), and they evaluate the impact on m6A RNA modification detection using data with known m6A sites. In comparison to existing methods, SegPore appears to improve the ability to detect m6A, suggesting that this approach could be used to improve the analysis of direct RNA-Seq data.

Strengths:

SegPore address an important problem (signal data segmentation). By refining the signal into transition and base blocks, noise appears to be reduced, leading to improved m6A identification at the site level as well as for single read predictions. The authors provide a fully documented implementation, including a GPU version that reduces run time. The authors provide a detailed methods description, and the approach to refine segments appears to be new.

Weaknesses:

The authors show that SegPore reduces noise compared to other methods, however the improvement in accuracy appears to be relatively small for the task of identifying m6A. To run SegPore, the GPU version is essential, which could limit the application of this method in practice.

As discussed in Paragraph 4 of the Discussion, we acknowledge that the improvement of SegPore combined with m6Anet over Nanopolish+m6Anet in bulk in vivo analysis is modest. This outcome is likely influenced by several factors, including alignment inaccuracies caused by pseudogenes or transcript isoforms, the presence of additional RNA modifications that can affect signal baselines, and the fact that m6Anet is specifically trained on Nanopolish-derived events. Additionally, the absence of a modification-free (in vitro transcribed) control sample in the benchmark dataset makes it challenging to establish true k-mer baselines.

Importantly, these challenges do not exist for in vitro data, where the signal is cleaner and better defined. As a result, SegPore achieves a clear and substantial improvement at the single-molecule level, demonstrating the strength of its segmentation approach and its potential to significantly enhance downstream analyses. These results indicate that SegPore is particularly well suited for benchmarking and mechanistic studies of RNA modifications under controlled experimental conditions, and they provide a strong foundation for future developments.

We also recognize that the current requirement for GPU acceleration may limit accessibility in some computational environments. To address this, we plan to further optimize SegPore in future versions to support efficient CPU-only execution, thereby broadening its applicability and impact.

Reviewer #2 (Public review):

Summary:

The work seeks to improve detection of RNA m6A modifications using Nanopore sequencing through improvements in raw data analysis. These improvements are said to be in the segmentation of the raw data, although the work appears to position the alignment of raw data to the reference sequence and some further processing as part of the segmentation, and result statistics are mostly shown on the 'data-assigned-to-kmer' level.

As such, the title, abstract and introduction stating the improvement of just the 'segmentation' does not seem to match the work the manuscript actually presents, as the wording seems a bit too limited for the work involved.

The work itself shows minor improvements in m6Anet when replacing Nanopolish' eventalign with this new approach, but clear improvements in the distributions of data assigned per kmer. However, these assignments were improved well enough to enable m6A calling from them directly, both at site-level and at read-level.

A large part of the improvements shown appear to stem from the addition of extra, non-base/kmer specific, states in the segmentation/assignment of the raw data, removing a significant portion of what can be considered technical noise for further analysis. Previous methods enforced assignment of (almost) all raw data, forcing a technically optimal alignment that may lead to suboptimal results in downstream processing as datapoints could be assigned to neighbouring kmers instead, while random noise that is assigned to the correct kmer may also lead to errors in modification detection.

For an optimal alignment between the raw signal and the reference sequence, this approach may yield improvements for downstream processing using other tools.

Additionally, the GMM used for calling the m6A modifications provides a useful, simple and understandable logic to explain the reason a modification was called, as opposed to the black models that are nowadays often employed for these types of tasks.

Weaknesses:

The manuscript suggests the eventalign results are improved compared to Nanopolish. While this is believably shown to be true (Table 1), the effect on the use case presented, downstream differentiation between modified and unmodified status on a base/kmer, is likely limited for during downstream modification calling the noisy distributions are often 'good enough'. E.g. Nanopolish uses the main segmentation+alignment for a first alignment and follows up with a form of targeted local realignment/HMM test for modification calling (and for training too), decreasing the need for the near-perfect segmentation+alignment this work attempts to provide. Any tool applying a similar strategy probably largely negates the problems this manuscript aims to improve upon. Should a use-case come up where this downstream optimisation is not an option, SegPore might provide the necessary improvements in raw data alignment.

Thank you for this thoughtful comment. We agree that many current state-of-the-art (SOTA) methods perform well on benchmark datasets, but we believe there is still substantial room for improvement. Most existing benchmarks are based on limited datasets, primarily focusing on DRACH motifs in human and mouse transcriptomes. However, m6A modifications can also occur in non-DRACH motifs, where current models tend to underperform. Furthermore, other RNA modifications, such as pseudouridine, inosine, and m5C, remain less studied, and their detection is likely to benefit from more accurate and informative signal modeling.

It is also important to emphasize that raw signal segmentation and RNA modification detection are fundamentally distinct tasks. SegPore focuses on improving the segmentation step by producing a cleaner and more interpretable signal, which provides a stronger foundation for downstream analyses. Even if RNA modification detection algorithms such as m6Anet can partially compensate for noisy segmentation in specific cases, starting from a more accurate signal alignment can still lead to improved accuracy, robustness, and interpretability—particularly in challenging scenarios such as non-canonical motifs or less characterized modifications.

Scientific progress in this field is often incremental, and foundational improvements can have a significant long-term impact. By enhancing raw signal segmentation, SegPore contributes an essential building block that we expect will enable the development of more accurate and generalizable RNA modification detection algorithms as the community integrates it into more advanced workflows.

Appraisal:

The authors have shown their methods ability to identify noise in the raw signal and remove their values from the segmentation and alignment, reducing its influences for further analyses. Figures directly comparing the values per kmer do show a visibly improved assignment of raw data per kmer. As a replacement for Nanopolish' eventalign it seems to have a rather limited, but improved effect, on m6Anet results. At the single read level modification modification calling this work does appear to improve upon CHEUI.

Impact:

With the current developments for Nanopore based modification calling largely focusing on Artificial Intelligence, Neural Networks and the likes, improvements made in interpretable approaches provide an important alternative that enables deeper understanding of the data rather than providing a tool that plainly answers the question of wether a base is modified or not, without further explanation. The work presented is best viewed in context of a workflow where one aims to get an optimal alignment between raw signal data and the reference base sequence for further processing. For example, as presented, as a possible replacement for Nanopolish' eventalign. Here it might enable data exploration and downstream modification calling without the need for local realignments or other approaches that re-consider the distribution of raw data around the target motif, such as a 'local' Hidden Markov Model or Neural Networks. These possibilities are useful for a deeper understanding of the data and further tool development for modification detection works beyond m6A calling.

Reviewer #3 (Public review):

Summary:

Nucleotide modifications are important regulators of biological function, however, until recently, their study has been limited by the availability of appropriate analytical methods. Oxford Nanopore direct RNA sequencing preserves nucleotide modifications, permitting their study, however many different nucleotide modifications lack an available base-caller to accurately identify them. Furthermore, existing tools are computationally intensive, and their results can be difficult to interpret.

Cheng et al. present SegPore, a method designed to improve the segmentation of direct RNA sequencing data and boost the accuracy of modified base detection.

Strengths:

This method is well described and has been benchmarked against a range of publicly available base callers that have been designed to detect modified nucleotides.

Weaknesses:

However, the manuscript has a significant drawback in its current version. The most recent nanopore RNA base callers can distinguish between different ribonucleotide modifications, however, SegPore has not been benchmarked against these models.

The manuscript would be strengthened by benchmarking against the rna004_130bps_hac@v5.1.0 and rna004_130bps_sup@v5.1.0 dorado models, which are reported to detect m5C, m6A_DRACH, inosine_m6A and PseU.

A clear demonstration that SegPore also outperforms the newer RNA base caller models will confirm the utility of this method.

Thank you for highlighting this important limitation. While Dorado, the new ONT basecaller, is publicly available and supports modification-aware basecalling, suitable public datasets for benchmarking m5C, inosine, m6A, and PseU detection on RNA004 are currently lacking. Dorado’s modification-aware models are trained on ONT’s internal data, which is not publicly released. Therefore, it is currently not feasible to directly evaluate or compare SegPore’s performance against Dorado for these RNA modifications.

We would also like to emphasize that SegPore’s primary contribution lies in raw signal segmentation, which is an upstream and foundational step in the RNA modification detection pipeline. As more publicly available datasets for RNA004 modification detection become accessible, we plan to extend our work to benchmark and integrate SegPore with modification detection tasks on RNA004 data in future studies.

Recommendations for the authors:

Reviewer #2 (Recommendations for the authors):

Comments based on Author Response

“However, it is valid to compare them on the segmentation task, where SegPore exhibits better performance (Table 1).”

This dodges the point of the actual use case of this approach, as Nanopolish indeed does not support calling modifications for this kind of data, but the general approach it uses might, if adapted for this data, nullify the gains made in the examples presented.

We respectfully disagree with the comment that the advantages demonstrated by SegPore could be “nullified”. Although SegPore’s performance is indeed more modest in in vivo datasets, it shows substantially better performance than CHEUI in in vitro data, clearly demonstrating that improved segmentation directly contributes to more accurate RNA modification estimation.

It is worth noting that CHEUI relies on Nanopolish’s segmentation results for m6A detection. Despite this, SegPore outperforms CHEUI, further supporting the conclusion that segmentation quality has a meaningful impact on downstream modification calling.

In conclusion, based on our current experimental results, SegPore is particularly well suited for RNA modification analysis from in vitro transcribed data, where its improved segmentation provides a clear advantage over existing methods.

Further comments

(2) “(2) Page 3  employ models like Hidden Markov Models (HMM) to segment the signal, but they are prone to noise and inaccuracies”

“That's the alignment/calling part, not the segmentation?”

“Current methods, such as Nanopolish, employ models like Hidden Markov Models (HMM) to segment the signal”

I get the impression the word 'segment' has a different meaning in this work than what I'm used to based on my knowledge around Nanopolish and Tombo, see the deeper code examples further down below.

Additionally, in Nanopolish there is a clear segmentation step (or event detection) without any HMM, then a sort of dynamic timewarping step that aligns the segments and re-combines some segments into a single segment where necessary afterwards. I believe the HMM in Nanopolish is not used at all unless modification calling, but if you can point out otherwise I'm open for proof.

Now I believe it is the meaning of 'segmenting the signal' that confuses me, and now the clarification makes it a bit odd as well:

“Nanopolish and Tombo align the raw signal to the reference sequence to determine which portion of the signal corresponds to each k-mer. We define this process as the segmentation task, referred to as "eventalign" in Nanopolish.”

So now it's clearly stated the raw signal is being 'aligned' and then the process is suddenly defined as the 'segmentation task', and again referred to as "eventalign". Why is it not referred to as the 'alignment task' instead?

I understand the segmentation and alignment parts are closely connected but to me, it seems this work picks the wrong word for the problem being solved.

“Unlike Nanopolish and Tombo, which directly align the raw signal to the reference sequence,…”

Looking at their code, I believe both Nanopolish and Tombo actually do segment the data first (or "event detection"), then they align the segments/events they found, and finally multiple events aligned to the same section are merged. See for yourself:

Nanopolish:

https://github.com/jts/nanopolish/blob/master/src/nanopolish_squiggle_read.cpp<br /> Line 233:

cpp

trim_and_segment_raw(fast5_data.rt, trim_start, trim_end, varseg_chunk, varseg_thresh);

event_table et = detect_events(fast5_data.rt, *ed_params);

Line 270:

cpp

// align events to the basecalled read

std::vector event_alignment = adaptive_banded_simple_event_align(*this, *this->base_model[strand_idx], read_sequence);

Where event detection is further defined at line 268 here:

https://github.com/jts/nanopolish/blob/master/src/thirdparty/scrappie/event_detection.c

Tombo:

https://github.com/nanoporetech/tombo/blob/master/tombo/resquiggle.py

line 1162 and onwards shows a ‘segment_signal’ call and the results are used in a ‘find_adaptive_base_assignment’ call, where ‘segment_signal’ starting at line 1057 tries to find where the signal jumps from a series of similar values to another (start of a base change in the pore), stored in ‘valid_cpts’, and the ‘find_adaptive_base_assignment’ tries to align the resulting segment values to the expected series of values:

python

valid_cpts, norm_signal, new_scale_values = segment_signal(

map_res, num_events, rsqgl_params, outlier_thresh, const_scale)

event_means = ts.compute_base_means(norm_signal, valid_cpts)

dp_res = find_adaptive_base_assignment(

valid_cpts, event_means, rsqgl_params, std_ref, map_res.genome_seq,

start_clip_bases=map_res.start_clip_bases,

seq_samp_type=seq_samp_type, reg_id=map_res.align_info.ID)

These implementations are also why I find the choice of words for what is segmentation and what is alignment a bit confusing in this work, as both Tombo and Nanopolish do a similar, clear segmentation step (or an "event detection" step), followed by the alignment of the segments they determined. The terminology in this work appears to deviate from these.

We thank the reviewer for the detailed comments!

First of all, we sincerely apologize for our earlier misunderstanding regarding how Nanopolish and Tombo operate. Based on a closer examination of their source codes, we now recognize that both tools indeed include a segmentation step based on change-point detection methods, after which the resulting segments are aligned to the reference sequence. We have revised the relevant text in the manuscript accordingly:

- “Current methods, such as Nanopolish, employ change-point detection methods to segment the signal and use dynamic programming methods and HMM to align the derived segments to the reference sequence,”

- “We define this process as the segmentation and alignment task (abbreviated as the segmentation task), which is referred to as “eventalign” in Nanopolish.”

- “In SegPore, we segment the raw signal into small fragments using a Hierarchical Hidden Markov Model (HHMM) and align the mean values of these fragments to the reference, where each fragment corresponds to a sub-state of a k-mer. By contrast, Nanopolish and Tombo use change-point–based methods to segment the signal and employ dynamic programming approaches together with profile HMMs to align the resulting segments to the reference sequence.”

Regarding terminology, we originally borrowed the term “segmentation” from speech processing, where it refers to dividing continuous audio signals into meaningful units. In the context of nanopore signal analysis, segmentation and alignment are often tightly coupled steps. Because of this and because our initial focus was on methodological development rather than terminology, we used the term “segmentation task” to describe the combined process of signal segmentation and alignment.

However, we now recognize that this terminology may cause confusion. Changing every instance of “segmentation” to “segmentation and alignment” or “alignment” would require substantial rewriting of the manuscript. Therefore, in this revision, we have clearly defined “segmentation task” as referring to the combined process of segmentation and alignment. We apologize for any earlier confusion and will adopt the term “alignment” in future work for greater clarity.

(3) I think I do understand the meaning, but I do not understand the relevance of the Aj bit in the last sentence. What is it used for?

Based on the response and another close look at Fig1, it turns out the j refers to extremely small numbers 1 and 2 in step 3. You may want in improve readability for these.

Thank you for the suggestion. We have added subscripts to all nucleotides in the reference sequence in Figure 1A and revised the legend to clarify the notation and improve readability. Specifically, we now include the following explanation:

“For example, A_j denotes the base ‘A’ at the j-th position on the reference sequence. In this example, A₁ and A₂ refer to the first and second occurrences of ‘A’ in the reference sequence, respectively. Accordingly, μ₁ and μ₂ are aligned to A₁, while μ₃ is aligned to A₂”.

(6) “We chose to use the poly(A) tail for normalization because it is sequence-invariant- i.e., all poly(A) tails consist of identical k-mers, unlike transcript sequences which vary in composition. In contrast, using the transcript region for normalization can introduce biases: for instance, reads with more diverse k-mers (having inherently broader signal distributions) would be forced to match the variance of reads with more uniform k-mers, potentially distorting the baseline across k-mers.”

While the next part states there was a benchmark showing SegPore still works without this normalization, I think this answer does not touch upon the underlying issue I'm trying to point out here.

- The biases mentioned here due to a more diverse (or different) subsets of k-mers in a read indeed affects the variance of the signal overall.

- As I pointed out in my earlier remark here, this can be resolved using an approach of 'general normalization', 'mapping to expected signal', 'theil-sen fitting of scale and offset', 're-mapping to expected signal', as Tombo and Nanopolish have implemented.<br /> - Alternatively, one could use the reference sequence (using the read mapping information) and base the expected signal mean and standard deviation on that instead.

- The polyA tail stability as an indicator for the variation in the rest of the signal seems a questionable assumption to me. A 'noisy' pore could introduce a large standard deviation using the polyA tail without increasing the deviations on the signal induced by the variety of k-mers, rather it would be representative for the deviations measured within a single k-mer segment. I thought this possible discrepancy is to be expected from a worn out pore, hence I'd imagine reads sequenced later in a run to provide worse results using this method.

In the current version it is not the statement that is unclear, it is the underlying assumption of how this works that I question.

We thank the reviewer for raising this important point and for the insightful discussion. Our choice of using the poly(A) tail for normalization is based on the working hypothesis that the poly(A) signal reflects overall pore-level variability and provides a stable reference for signal scaling. We find this to be a practical and effective approach in most experimental settings.

We agree that more sophisticated strategies, such as “general normalization” or iterative fitting to the expected signal (as implemented in Tombo and Nanopolish), could in principle generate a "better" normalization. However, these approaches are significantly more challenging to implement in practice. This is because signal normalization and alignment are mutually dependent processes: baseline estimates for k-mers influence alignment accuracy, while alignment accuracy, in turn, affects baseline calculation. This interdependence becomes even more complex in the presence of RNA modifications, which alter signal distributions and further confound model fitting.

It is worth noting that this limitation is already evident in our results. As shown in Figure 4B (first and second k-mers), Nanopolish produces more dispersed baselines than SegPore, even for these unmodified k-mers, suggesting inherent limitations in its normalization strategy. Ideally, baselines for the same k-mer should remain highly consistent across different reads.

In contrast, poly(A)-based normalization offers a simpler and more robust solution that avoids this circular dependency. Because poly(A) sequences are compositionally homogeneous, they enable reliable estimation of scaling parameters without assumptions about k-mer composition or modification state. Regarding the reviewer’s concern about pore instability, we mitigate this issue by including only high-quality, confidently mapped reads in our analysis, which reduces the likelihood of incorporating signals from degraded or “noisy” pores.

We fully agree that exploring more advanced normalization strategies is an important direction for future work, and we plan to investigate such approaches as the field progresses.

(8) “In the remainder of this paper, we refer to these resulting events as the output of eventalign analysis or the segmentation task.”

Picking only one descriptor rather than two alternatives would be easier to follow (and I'd prefer the first).

Thank you for the suggestion. We have revised the sentence to:

“In the remainder of this paper, we refer to these resulting events as the output of eventalign analysis, which also represents the final output of the segmentation and alignment task.”

(9) “Additionally, a complete explanation of how the weighted mean is computed is provided in Section 5.3 of Supplementary Note 1. It is derived from signal points that are assigned to a given 5mer.”

I believe there's no more mention of a weighted mean, and I don't get any hits when searching for 'weight'. Is that intentional?

We apologize for the misplacement of the formulas. We have updated Section 5.3 of Supplementary Note 1 to clarify the definition of the weighted mean. Because multiple current signal segments may be aligned to a single k-mer, we computed the weighted mean for each k-mer across these segments, where the weight corresponds to the number of data points assigned to “curr” state in each event.

(17) Response: We revised the sentence to clarify the selection criteria: "For selected 5mers “that exhibit both a clearly unmodified and a clearly” “modified signal component”, “SegPore reports the modification rate at each site,” “as well as the modification state of that site on individual reads.””

So is this the same set described on page 13 ln 343 or not?

“Due to the differences between human (Supplementary Fig. S2A) and mouse (Supplementary Fig. S2B), only six 5mers were found to have m6A annotations in the test data's ground truth (Supplementary Fig. S2C). For a genomic location to be identified as a true m6A modification site, it had to correspond to one of these six common 5mers and have a read coverage of greater than 20.”

I struggle to interpret the 'For selected 5mers' part, as I'm not sure if this is a selection I'm supposed to already know at this point in the text or if it's a set just introduced here. If the latter, removing the word 'selected' would clear it up for me.

We apologize for the confusion. What we mean is that when pooling signals aligned to the same k-mer across different genomic locations and reads, only a subset of k-mers exhibit a bimodal distribution — one peak corresponding to the unmodified state and another to the modified state. Other k-mers show a unimodal distribution, making it impossible to reliably estimate modification levels. We refer to the subset of k-mers that display a bimodal distribution as the “selected” k-mers.

The “selected k-mers” described on page 13, line 343, must additionally have ground truth labels available in both the training and test datasets. There are 10 k-mers with ground truth annotations in the training data and 11 in the test data, and only 6 of these k-mers are shared between the two datasets, therefore only those 6 overlapping k-mers are retained for evaluation. These 6 k-mers satisfy both criteria: (1) exhibiting a bimodal distribution and (2) having ground truth annotations in both training and test sets.

To improve clarity, we have removed the term “selected” from the sentence.

(21) "Tombo used the "resquiggle" method to segment the raw signals, and we standardized the segments using the “poly(A)” tail to ensure a fair comparison “(See” “preprocessing section in Materials and Methods)."”

In the Materials and Methods:

“The raw signal segment corresponding to the poly(A) tail is used to standardize the raw signal for each read.”

I cannot find more detailed information here on what the standardization does, do you mean to refer to Supplementary Note 1, Section 3 perhaps?

Thank you for pointing this out. Yes, the standardization procedure is described in detail in Supplementary Note 1, Section 3. Tombo itself does not segment and align the raw signal on the absolute pA scale, which can result in very large variance in the derived events if the raw signal is used directly. To ensure a fair comparison, we therefore applied the same preprocessing steps to Tombo’s raw signals as we did for SegPore, using only the event boundary information from Tombo while standardizing the signal in the same way.

We have revised the sentence for clarity as follows:

“Tombo used the "resquiggle" method to segment the raw signals, but the resulting signals are not reported on the absolute pA scale. To ensure a fair comparison with SegPore, we standardized the segments using the poly(A) tail in the same way as SegPore (See preprocessing section in Materials and Methods).”

(22A) The table shown does help showing the benchmark is unlikely to be 'cheated'. However I am suprised to see the Avg std for Nanopolish and Tombo going up instead of down, as I'd expect the transition values to increase the std, and hence, removing them should decrease these values. So why does this table show the opposite?

I believe this table is not in the main text or the supplement, would it not be a good idea to cover this point somewhere in the work?

Thank you for this insightful comment. In response, we carefully re-examined our analysis and identified a bug in the code related to boundary removal for Nanopolish. We have now corrected this issue and included the updated results in Supplementary Table S1 of the revised manuscript. As shown in the updated table, the average standard deviations decrease after removing the boundary regions for both Nanopolish and Tombo.

We have now included this table in Supplementary Table S1 in the revised manuscript and added the following clarification:

“It is worth noting that the data points corresponding to the transition state between two consecutive 5-mers are not included in the calculation of the standard deviation in SegPore’s results in Table 1. However, their exclusion does not affect the overall conclusion, as there are on average only ~6 points per 5-mer in the transition state (see Supplementary Table S1 for more details).”

(22B) As mentioned in 2), I'm happy there's a clear definition of what is meant but I found the chosen word a bit odd.

We apologize for the earlier unclear terminology. We now refer to it as the segmentation and alignment task, abbreviated as the segmentation task.

(23) Reading back I can gather that from the text earlier, but the summation of what is being tested is this:

“including Tombo, MINES (31), Nanom6A (32), m6Anet, Epinano (33), and CHEUI (20). “

next, the identifier "Nanopolish+m6Anet" is, aside from the figure itself, only mentioned in the discussion. Adding a line that explains that "Nanopolish+m6Anet" is the default method of running m6Anet and "SegPore+m6Anet" replaces the Nanopolish part for m6Anet with Segpore, rather than jumping straight to "SegPore+m6Anet", would clarify where this identifier came from.

Thank you for the helpful suggestion. We have added the identifier to the revised manuscript as follows:

“Given their comparable methodologies and input data requirements, we benchmarked SegPore against several baseline tools, including Tombo, MINES (31), Nanom6A (32), m6Anet, Epinano (33), and CHEUI (20). By default, MINES and Nanom6A use eventalign results generated by Tombo, while m6Anet, Epinano, and CHEUI rely on eventalign results produced by Nanopolish. In Fig. 3C, ‘Nanopolish+m6Anet’ refers to the default m6Anet pipeline, whereas ‘SegPore+m6Anet’ denotes a configuration in which Nanopolish’s eventalign results are replaced with those from SegPore.”

(24) For completeness I'd expect tickmarks and values on the y-axis as well.

Thank you for the suggestion. We have updated Figures 3A and 3B in the revised manuscript to include tick marks and values on the y-axis as requested.

(25) Considering this statement and looking back at figure 3a and 3b, wouldn't this be easier to observe if the histograms/KDE's were plotted with overlap in a single figure?

We appreciate the suggestion. However, we believe that overlaying Figures 3A and 3B into a single panel would make the visualization cluttered and more difficult to interpret.

(29) Please change the sentence in the text to make that clear. As it is written now (while it's the same number of motifs, so one might guess it) it does not seem to refer to that particular set of motifs and could be a new selection of 6 motifs.

We appreciate the suggestion and have revised the sentence for clarity as follows:

“We evaluated m6A predictions using two approaches: (1) SegPore’s segmentation results were fed into m6Anet, referred to as SegPore+m6Anet, which works for all DRACH motifs and (2) direct m6A predictions from SegPore’s Gaussian Mixture Model (GMM), which is limited to the six selected 5-mers shown in Supplementary Fig. S2C that exhibit clearly separable modified and unmodified components in the GMM (see Materials and Methods for details). ”

(31) I think we have a different interpretation of the word 'leverage', or perhaps what it applies to. I'd say it leverages the jiggling if there's new information drawn from the jiggling behaviour. It's taking it into account if it filters for it. The HHMM as far as I understand tries to identify the jiggles, and ignore their values for the segmentation etc. So while one might see this as an approach that "leverages the hypothesis", I don't see how this HHMM "leverages the jiggling property" itself.

Thank you for the helpful suggestion. We have replaced the word “leverages” with “models” in the revised manuscript.

New points

pg6ln166: “…we extract the aligned raw signal segment and reference sequence segment from Nanopolish's events [...] we extract the raw signal segment corresponding to the transcript region for each input read based on Nanopolish's poly(A) detection results.”

It is not clear as to why this different approach is applied for these two cases in this part of the text.

Thank you for pointing this out. The two approaches refer to different preprocessing strategies for in vivo and in vitro data.

For in vivo data, a large proportion of reads do not span the full-length transcript and often map only to a portion of the reference sequence. Moreover, because a single gene can generate multiple transcript isoforms, a read may align equally well to several possible transcripts. Therefore, we extract only the raw signal segment that corresponds to the mapped portion of the transcript for each read.

In contrast, for in vitro data, the transcript sequence is known precisely. As a result, we can directly extract all raw signals following the poly(A) tail and align them to the complete reference sequence.

pg10ln259: An important distinction from classical global alignment algorithms is that one or multiple base blocks may align with a single 5mer.”

If there was usually a 1:1 mapping the alignment algorithm would be more or less a direct match, so I think the multiple blocks aligning to a 5mer thing is actually quite common.

Thank you for the comment. The “classical global alignment algorithm” here refers to the Needleman–Wunsch algorithm used for sequence alignment. Our intention was to highlight the conceptual difference between traditional sequence alignment and nanopore signal alignment. In classical sequence alignment, each base typically aligns to a single position in the reference. In contrast, in nanopore signal alignment, one or multiple signal segments — corresponding to varying dwell times of the motor protein — can align to a single 5-mer.

We have revised the sentence as follows:

“An important distinction from classical global alignment algorithms (Needleman–Wunsch algorithm)……”

pg13ln356: "dwell time" is not defined or used before, I guess it's effectively the number of raw samples per segment but this should be clarified.

Thank you for pointing this out. We have now added a clear definition of dwell time in the text as follows:

"such as the normalized mean μ_i, standard deviation σ_i, dwell time l_i (number of data points in the event)."

pg13ln358: “Feature vectors from 80% of the genomic locations were used for training, while the remaining 20% were set aside for validation.”

I assume these are selected randomly but this is not explicitly stated here and should be.

Yes, they are randomly selected. We have revised the sentence as follows:

“Feature vectors from a randomly selected 80% of the genomic locations were used for training, while the remaining 20% were set aside for validation.”

pg18ln488: The manuscript now evaluates RNA004 and compares against f5c and Uncalled4. It mentions the differences between RNA004 and RNA002, namely kmer size and current levels, but does not explain where the starting reference model values for the RNA004 model come from: In pg18ln492 they state "RNA004 provides reference values for 9mers", then later they seem to use a 5mer parameter table (pg19ln508), are they re-using the same table from RNA002 or did they create a 5mer table from the 9mer reference table?

We apologize for the confusion. The reference model table for RNA004 9-mers is obtained from f5c (the array named ‘rna004_130bps_u_to_t_rna_9mer_template_model_builtin_data’in  https://raw.githubusercontent.com/hasindu2008/f5c/refs/heads/master/src/model.h).

Author response image 1.

We have revised the subsection header “5-mer parameter table” in the Method to “5-mer & 9-mer parameter table” to highlight this and added a paragraph about how to obtain the 9-mer parameter table:

“In the RNA004 data analysis (Table 2), we obtained the 9-mer parameter table from the source code of f5c (version 1.5). Specifically, we used the array named ‘rna004_130bps_u_to_t_rna_9mer_template_model_builtin_data’ from the following file: https://raw.githubusercontent.com/hasindu2008/f5c/refs/heads/master/src/model.h (accessed on 17 October 2025).”

Also, in page 18 line 195, we added the following sentence:

“The 9-mer parameter table in pA scale for RNA004 data provided by f5c (see Materials and Methods) was used in the analysis.”

pg19ln520: “Additionally, due to the differences of the k-mer motifs between human and mouse (Supplementary Fig. S2), six shared 5mers were selected to demonstrate SegPore's performance in modification prediction directly.”

"the differences" - in occurrence rates, as I gather from the supplementary figure, but it would be good to explicitly state it in this sentence itself too.

Thank you for the helpful suggestion. We agree that the original sentence was vague. The main reason for selecting only six 5-mers is the difference in the availability of ground truth labels for specific k-mer motifs between human and mouse datasets. We have revised the sentence accordingly:

“Additionally, due to the differences in the availability of ground truth labels for specific k-mer motifs between human and mouse (Supplementary Fig. S2), six shared 5-mers were selected to directly demonstrate SegPore’s performance in modification prediction.”

pg24ln654: “SegPore codes current intensity levels”

"codes" is meant to be "stores" I guess? Perhaps "encodes"?

Thank you for the suggestion. We have now replaced it with “encodes” in the revised manuscript.

Lastly, looking at the feedback from the other reviewers comment:

The 'HMM' mentioned in line 184 looks fine to me, the HHMM is 2 HMM's in a hierarchical setup and the text now refers to one of these HMM layers. If this is to be changed it would need to state the layer (e.g. "the outer HHMM layer") throughout the text instead.

We agree with this assessment and believe that the term “inner HMM” is accurate in this context, as it correctly refers to one of the two HMM layers within the HHMM structure. Therefore, we have decided to retain the current terminology.

Reviewer #3 (Recommendations for the authors):

I recommend the publication of this manuscript, provided that the following comments are addressed.

Page 5, Preprocessing: You comment that the poly(A) tail provides a stable reference that is crucial for the normalisation of all reads. How would this step handle reads that have interrupted poly(A) tails (e.g. in the case of mRNA vaccines that employ a linker sequence)? Or cell types that express TENT4A/B, which can include transcripts with non-A residues in the poly(A) tail: https://www.science.org/doi/full/10.1126/science.aam5794.

It depends on Nanopolish’s ability to reliably detect the poly(A) tail. In general, the poly(A) region produces a long stretch of signals fluctuating around a current level of ~108.9 pA (RNA002) with relatively stable variation, which allows it to be identified and used for normalization.

For in vivo data, if the poly(A) tail is interrupted (e.g., due to non-A residues or linker sequences), two scenarios are possible:

(1) The poly(A) tail may not be reliably detected, in which case the corresponding read will be excluded from our analysis.

(2) Alternatively, Nanopolish may still recognize the initial uninterrupted portion of the poly(A) signal, which is typically sufficient in length and stability to be used for signal normalization.

For in vitro data, the poly(A) tails are uninterrupted, so this issue does not arise.

All analyses presented in this study are based exclusively on reads with reliably detected poly(A) tails.

Page 7, 5mer parameter table: r9.4_180mv_70bps_5mer_RNA is an older kmer model (>2 years). How does your method perform with the newer RNA kmer models that do permit the detection of multiple ribonucleotide modifications? Addressing this comment would be beneficial, however I understand that it would require the generation of new data, as limited RNA004 datasets are available in the public domain.

“r9.4_180mv_70bps_5mer_RNA” is the most widely used k-mer model for RNA002 data. Regarding the newer k-mer models, we believe the reviewer is referring to the “modification basecalling” models available in Dorado, which are specifically designed for RNA004 data. At present, SegPore can perform RNA modification estimation only on RNA002 data, as this is the platform for which suitable training data and ground truth annotations are available. Evaluating SegPore’s performance with the newer RNA004 modification models would require new datasets containing known modification sites generated with RNA004 chemistry. Since such data are currently unavailable, we have not yet been able to assess SegPore under these conditions. This represents an important future direction for extending and validating our method.

The Methods and Results sections contain redundant information -please streamline the information in these sections and reduce the redundancy.

We thank the reviewer for this suggestion and acknowledge that there is some overlap between the Methods and Results sections. However, we feel that removing these parts could compromise the clarity and readability of the manuscript, especially given that Reviewer 2 emphasized the need for clearer explanations. We therefore decided to retain certain methodological descriptions in the Results section to ensure that key steps are understandable without requiring the reader to constantly cross-reference the Methods.

Minor comments

Please be consistent when referring to k-mers and 5-mers (sometimes denoted as 5mers - please change to 5-mers throughout).

We have revised the manuscript to ensure consistency and now use “5-mers” throughout the text.

Introduction

Lines 80 - 112: Please condense this section to roughly half the length (1-2 paragraphs). In general, the results described in the introduction should be very brief, as they are described in full in the results section.

Thank you for the suggestion. We have condensed the original three paragraphs into a single, more concise paragraph as follows:

"SegPore is a novel tool for direct RNA sequencing (DRS) signal segmentation and alignment, designed to overcome key limitations of existing approaches. By explicitly modeling motor protein dynamics during RNA translocation with a Hierarchical Hidden Markov Model (HHMM), SegPore segments the raw signal into small, biologically meaningful fragments, each corresponding to a k-mer sub-state, which substantially reduces noise and improves segmentation accuracy. After segmentation, these fragments are aligned to the reference sequence and concatenated into larger events, analogous to Nanopolish’s “eventalign” output, which serve as the foundation for downstream analyses. Moreover, the “eventalign” results produced by SegPore enhance interpretability in RNA modification estimation. While deep learning–based tools such as m6Anet classify RNA modifications using complex, non-transparent features (see Supplementary Fig. S5), SegPore employs a simple Gaussian Mixture Model (GMM) to distinguish modified from unmodified nucleotides based on baseline current levels. This transparent modeling approach improves confidence in the predictions and makes SegPore particularly well-suited for biological applications where interpretability is essential."

Line 104: Please change "normal adenosine" to "adenosine".

We have revised the manuscript as requested and replaced all instances of “normal adenosine” with “adenosine” throughout the text.

Materials and Methods

Line 176: Please reword "...we standardize the raw current signals across reads, ensuring that the mean and standard deviation of the poly(A) tail are consistent across all reads." To "...we standardize the raw current signals for each read, ensuring that the mean and standard deviation are consistent across the poly(A) tail region."

We have changed sentence as requested.

“Since the poly(A) tail provides a stable reference, we standardize the raw current signals for each read, ensuring that the mean and standard deviation are consistent across the poly(A) tail region.”

Line 182: Please describe the RNA translocation hypothesis, as this is the first mention of it in the text. Also, why is the Hierachical Hidden Markov model perfect for addressing the RNA translocation hypothesis? Explain more about how the HHMM works and why it is a suitable choice.

We have revised the sentence as requested:

“The RNA translocation hypothesis (see details in the first section of Results) naturally leads to the use of a hierarchical Hidden Markov Model (HHMM) to segment the raw current signal.”

The motivation of the HHMM is explained in detail in the the first section “RNA translocation hypothesis” of Results. As illustrated in Figure 2, the sequencing data suggest that RNA molecules may translocate back and forth (often referred to as jiggling) while passing through the nanopore. This behavior results in complex current fluctuations that are challenging to model with a simple HMM. The HHMM provides a natural framework to address this because it can model signal dynamics at two levels. The outer HMM distinguishes between two major states — base states (where the signal corresponds to a stable sub-state of a k-mer) and transition states (representing transitions from one base state to the next). Within each base state, an inner HMM models finer signal variation using three states — “curr”, “prev”, and “next” — corresponding to the current k-mer sub-states and its neighboring k-mer sub-states. This hierarchical structure captures both the stable signal patterns and the stochastic translocation behavior, enabling more accurate and biologically meaningful segmentation of the raw current signal.

Line 184: do you mean HHMM? Please be consistent throughout the text.

As explained in the previous response, the HHMM consists of two layers: an outer HMM and an inner HMM. The term “HMM” in line 184 is meant to be read together with “inner” at the end of line 183, forming the phrase “inner HMM.” It seems the reviewer may have overlooked this when reading the text.

Line 203: please delete: "It is obviously seen that".

We have removed the phrase “It is obviously seen that” from the sentence as requested. The revised sentence now reads:

“The first part of Eq. 2 represents the emission probabilities, and the second part represents the transition probabilities.”

Line 314, GMM for 5mer parameter table re-estimation: "Typically, the process is repeated three to five times until the5mer parameter table stabilizes." How is the stabilisation of the 5mer parameter table quantified? What is a reasonable cut-off that would demonstrate adequate stabilisation of the 5mer parameter table? Please add details of this to the text.

We have revised the sentence to clarify the stabilization criterion as follows:

“Typically, the process is repeated three to five times until the 5-mer parameter table stabilizes (when the average change of mean values of all 5-mers is less than 5e-3).”

Results

Line 377: Please edit to read "Traditional base calling algorithms such as Guppy and Albacore assume that the RNA molecule is translocated unidirectionally through the pore by the motor protein."

We have revised the sentence as:

“In traditional basecalling algorithms such as Guppy and Albacore, we implicitly assume that the RNA molecule is translocated through the pore by the motor protein in a monotonic fashion, i.e., the RNA is pulled through the pore unidirectionally.”

Line 555, m6A identification at the site level: "For six selected m6A motifs, SegPore achieved an ROC AUC of 82.7% and a PR AUC of 38.7%, earning the third best performance compared with deep leaning methods m6Anet and CHEUI (Fig. 3D)." So SegPore performs third best of all deep learning methods. Do you recommend its use in conjunction with m6Anet for m6A detection? Please clarify in the text. This will help to guide users to possible best practice uses of your software.

Thank you for the suggestion. We have added a clarification in the revised manuscript to guide users.

“For practical applications, we recommend taking the intersection of m6A sites predicted by SegPore and m6Anet to obtain high-confidence modification sites, while still benefiting from the interpretability provided by SegPore’s predictions.”

Figures.

Figure 1A please refer to poly(A) tail, rather than polyA tail.

We have updated it to poly(A) tail in the revised manuscript.

Perhaps these SNPs are silent based on when they are transcribed, meaning when the trauma happens depends on whether or not the SNP is in transcription and then reflected in translation?

Author response:

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

Reviewer #1 (Public review): 

Summary: 

The study by Pinho et al. presents a novel behavioral paradigm for investigating higher-order conditioning in mice. The authors developed a task that creates associations between light and tone sensory cues, driving mediated learning. They observed sex differences in task acquisition, with females demonstrating faster-mediated learning compared to males. Using fiber photometry and chemogenetic tools, the study reveals that the dorsal hippocampus (dHPC) plays a central role in encoding mediated learning. These findings are crucial for understanding how environmental cues, which are not directly linked to positive/negative outcomes, contribute to associative learning. Overall, the study is well-designed, with robust results, and the experimental approach aligns with the study's objectives. 

Strengths: 

(1) The authors develop a robust behavioral paradigm to examine higher-order associative learning in mice. 

(2) They discover a sex-specific component influencing mediated learning, with females exhibiting enhanced learning abilities. 

(3) Using fiber photometry and chemogenetic techniques, the authors identify the dorsal hippocampus but not the ventral hippocampus, which plays a crucial for encoding mediated learning.

We appreciate the strengths highlighted by the Reviewer and the valuable and complete summary of our work.

Weaknesses: 

(1) The study would be strengthened by further elaboration on the rationale for investigating specific cell types within the hippocampus.  

We thank the Reviewer for highlighting this important point. In the revised manuscript, we have added new information (Page 11, Lines 27-34) to specifically explain the rational of studying the possible cell-type specific involvement in sensory preconditioning.

(2) The analysis of photometry data could be improved by distinguishing between early and late responses, as well as enhancing the overall presentation of the data.  

According to the Reviewer comment, we have included new panels in Figure 3E and the whole Supplementary Figure 4, which separates the photometry data across different preconditioning and conditioning sessions, respectively. Overall, this data suggests that there are no major changes on cell activity in both hippocampal regions during the different sessions as similar light-tone-induced enhancement of activity is observed. These findings have been incorporated in the Results Section (Page 12, Lines 13-15, 19-20 and 35-36).

(3) The manuscript would benefit from revisions to improve clarity and readability.

Based on the fair comment, we have gone through the text to increase clarity and readability.

Reviewer #2 (Public review): 

Summary: 

Pinho et al. developed a new auditory-visual sensory preconditioning procedure in mice and examined the contribution of the dorsal and ventral hippocampus to learning in this task. Using photometry they observed activation of the dorsal and ventral hippocampus during sensory preconditioning and conditioning. Finally, the authors combined their sensory preconditioning task with DREADDs to examine the effect of inhibiting specific cell populations (CaMKII and PV) in the DH on the formation and retrieval/expression of mediated learning. 

Strengths: 

The authors provide one of the first demonstrations of auditory-visual sensory preconditioning in male mice. Research on the neurobiology of sensory preconditioning has primarily used rats as subjects. The development of a robust protocol in mice will be beneficial to the field, allowing researchers to take advantage of the many transgenic mouse lines. Indeed, in this study, the authors take advantage of a PV-Cre mouse line to examine the role of hippocampal PV cells in sensory preconditioning. 

We acknowledge the Reviewer´s effort and for highlighting the strengths of our work.

Weaknesses: 

(1) The authors report that sensory preconditioning was observed in both male and female mice. However, their data only supports sensory preconditioning in male mice. In female mice, both paired and unpaired presentations of the light and tone in stage 1 led to increased freezing to the tone at test. In this case, fear to the tone could be attributed to factors other than sensory preconditioning, for example, generalization of fear between the auditory and visual stimulus.

We thank the comment raised by the Reviewer. At first, we were hypothesizing that female mice were somehow able to associate light and tone although they were presented separately during the preconditioning sessions. Thus, we designed new experiments (shown in Supplementary Figure 2D) to test if we would observe data congruent with our initial hypothesis or with fear generalization as proposed by the reviewer. We have performed a new experiment comparing a Paired group with two additional control groups that are (i) an Unpaired group where we increased the time between the light and tone presentations and (ii) an experimental group where the light was absent during the conditioning. Clearly, the new results indicate the presence of fear generalization in female mice aswe found a significant cue-induced increase on freezing responses in all the experimental groups tested. In accordance with the Reviewer’s suggestion, we can conclude that mediated learning is not correctly observed in female mice using the protocol described (i.e. with 2 conditioning sessions). All these new results forced us to reorganize the structure and the figures of the manuscript to focus more in male mice in the Main Figures whereas showing the data with female mice in Supplementary Figures. Overall, our data clearly revealed the necessity to have adapted behavioral protocols for each sex demonstrating sex differences in sensory preconditioning, which was added in the Discussion Section (Page 15, lines 12-37).

(2) In the photometry experiment, the authors report an increase in neural activity in the hippocampus during both phase 1 (sensory preconditioning) and phase 2 (conditioning). In the subsequent experiment, they inhibit neural activity in the DH during phase 1 (sensory preconditioning) and the probe test, but do not include inhibition during phase 2 (conditioning). It was not clear why they didn't carry forward investigating the role of the hippocampus during phase 2 conditioning. Sensory preconditioning could occur due to the integration of the tone and shock during phase two, or retrieval and chaining of the tonelight-shock memories at test. These two possibilities cannot be differentiated based on the data. Given that we do not know at which stage the mediate learning is occurring, it would have been beneficial to additionally include inhibition of the DH during phase 2. 

Following the Reviewer’s valuable comment, we have conducted a new experiment where we have chemogenetically inhibited the CaMKII-positive neurons of the dHPC during the conditioning to explore their involvement in mediated learning formation. Notably, the inhibition of principal neurons of the dHPC during conditioning does not impair the formation ofthe mediated learning in our hands. These new results are now shown in Supplementary Figure 7G and added in the Results section (Page 13, Lines 19-23).

(3) In the final experiment, the authors report that inhibition of the dorsal hippocampus during the sensory preconditioning phase blocked mediated learning. While this may be the case, the failure to observe sensory preconditioning at test appears to be due more to an increase in baseline freezing (during the stimulus off period), rather than a decrease in freezing to the conditioned stimulus. Given the small effect, this study would benefit from an experiment validating that administration of J60 inhibited DH cells. Further, given that the authors did not observe any effect of DREADD inhibition in PV cells, it would also be important to validate successful cellular silencing in this protocol.  

According to the Reviewer comments, we have performed new experiments to validate the use of J60 to inhibit hippocampal cells that are shown in Supplementary Figure 7 E-F for CaMKII-positive neurons, in which J60 administration tends to decrease the frequency of calcium events both in the dHPC and vHPC. Furthermore, in Supplementary Figure 8 B-C we show that J60 is also able to modify calcium events in PV-positive interneurons. Although,the best method to validate the use of DREADD (i.e. to inhibit hippocampal cell activity) could be electrophysiology recordings, we lack this technique in our laboratory. Thus, in order to adress the reviewer comment, we decided to combine the DREADD modulation through J60 administration with photometry recordings, where several tendencies are confirmed. In addition, a similar approach has been used in another preprint of the lab (https://doi.org/10.1101/2025.08.29.673009), where there is an increase of phospho-PDH, a marker of neuronal inhibition upon J60 administration in the dHPC, as well as in other experiments conducted from a collaborator lab where they were able to observe a modulation of SOM-positive interneurons activity upon J60 administration (PhD defense of Miguel Sabariego, University Pompeu Fabra, Barcelona). 

Reviewer #3 (Public review): 

Summary: 

Pinho et al. investigated the role of the dorsal vs ventral hippocampus and the gender differences in mediated learning. While previous studies already established the engagement of the hippocampus in sensory preconditioning, the authors here took advantage of freely-moving fiber photometry recording and chemogenetics to observe and manipulate sub-regions of the hippocampus (dorsal vs. ventral) in a cell-specific manner. The authors first found sex differences in the preconditioning phase of a sensory preconditioning procedure, where males required more preconditioning training than females for mediating learning to manifest, and where females displayed evidence of mediated learning even when neutral stimuli were never presented together within the session. 

After validation of a sensory preconditioning procedure in mice using light and tone neutral stimuli and a mild foot shock as the unconditioned stimulus, the authors used fiber photometry to record from all neurons vs. parvalbumin_positive_only neurons in the dorsal hippocampus or ventral hippocampus of male mice during both preconditioning and conditioning phases. They found increased activity of all neurons, as well as PV+_only neurons in both sub-regions of the hippocampus during both preconditioning and conditioning phases. Finally, the authors found that chemogenetic inhibition of CaMKII+ neurons in the dorsal, but not ventral, hippocampus specifically prevented the formation of an association between the two neutral stimuli (i.e., light and tone cues), but not the direct association between the light cue and the mild foot shock. This set of data: (1) validates the mediated learning in mice using a sensory preconditioning protocol, and stresses the importance of taking sex effect into account; (2) validates the recruitment of dorsal and ventral hippocampi during preconditioning and conditioning phases; and (3) further establishes the specific role of CaMKII+ neurons in the dorsal but not ventral hippocampus in the formation of an association between two neutral stimuli, but not between a neutralstimulus and a mild foot shock. 

Strengths: 

The authors developed a sensory preconditioning procedure in mice to investigate mediated learning using light and tone cues as neutral stimuli, and a mild foot shock as the unconditioned stimulus. They provide evidence of a sex effect in the formation of light-cue association. The authors took advantage of fiber-photometry and chemogenetics to target sub-regions of the hippocampus, in a cell-specific manner and investigate their role during different phases of a sensory conditioning procedure. 

We thank the Reviewer for the extensive summary of our work and for giving interesting value to some of our findings.

Weaknesses: 

The authors went further than previous studies by investigating the role of sub-regions of the hippocampus in mediated learning, however, there are several weaknesses that should be noted: 

(1) This work first validates mediated learning in a sensory preconditioning procedure using light and tone cues as neutral stimuli and a mild foot shock as the unconditioned stimulus, in both males and females. They found interesting sex differences at the behavioral level, but then only focused on male mice when recording and manipulating the hippocampus. The authors do not address sex differences at the neural level. 

We appreciate the comment of the Reviewer. Indeed, thanks to other Reviewer comments during this revision process (see Point 1 of Reviewer #2), we performed an additional experiment that reveals that using the described protocol in female mice we observed fear generalization rather than mediated learning responding. This data pointed to the need of sex-specific changes in the behavioral protocols to measure sensory preconditioning. The revised version of the manuscript, although highlighting these sex differences in behavioral performance (see Supplementary Figure 2), is more focused in male mice and, accordingly, all photometry or chemogenetic experiments are performed using male mice. In future studies, once we are certain to have a sensory preconditioning paradigm working in female mice, it will be very interesting to study if the same hippocampal mechanisms mediating this behavior in male mice are also observed in female mice.  

(2) As expected in fear conditioning, the range of inter-individual differences is quite high. Mice that didn't develop a strong light-->shock association, as evidenced by a lower percentage of freezing during the Probe Test Light phase, should manifest a low percentage of freezing during the Probe Test Tone phase. It would interesting to test for a correlation between the level of freezing during mediated vs test phases. 

Thanks to the comment raised by the reviewer, we generated a new set of data correlating mediated and direct fear responses. As it can be observed in Supplementary Figure 3, there is a significant correlation between mediated and direct learning in male mice (i.e. the individuals that freeze more in the direct learning test, correlate with the individuals that express more fear response in the mediated learning test). In contrast, this correlation is absent in female mice, further confirming what we have explained above. We have highlighted this new analysis in the Results section (Page 11, Lines 20-24).

(3) The use of a synapsin promoter to transfect neurons in a non-specific manner does not bring much information. The authors applied a more specific approach to target PV+ neurons only, and it would have been more informative to keep with this cell-specific approach, for example by looking also at somatostatin+ inter-neurons. 

The idea behind using a pan neuronal promoter was to assess in general terms how neuronal activity in the hippocampus is engaged during different phases of the lighttone sensory preconditioning. However, the comment of the Reviewer is very pertinent and, as suggested, we have generated some new data targeting CaMKII-positive neurons (see Point 4 below). Finally, although it could be extremely interesting, we believe that targeting different interneuron subtypes is out of the scope of the present work. However, we have added this in the Discussion Section as a future perspective/limitation of our study (Page 17, Lines 9-24).   

(4) The authors observed event-related Ca2+ transients on hippocampal pan-neurons and PV+ inter-neurons using fiber photometry. They then used chemogenetics to inhibit CaMKII+ hippocampal neurons, which does not logically follow. It does not undermine the main finding of CaMKII+ neurons of the dorsal, but not ventral, hippocampus being involved in the preconditioning, but not conditioning, phase. However, observing CaMKII+ neurons (using fiber photometry) in mice running the same task would be more informative, as it would indicate when these neurons are recruited during different phases of sensory preconditioning. Applying then optogenetics to cancel the observed event-related transients (e.g., during the presentation of light and tone cues, or during the foot shock presentation) would be more appropriate.  

We have generated new photometry data to analyze the activity of CaMKII-positive neurons during the preconditioning phase to confirm their engagement during the light-tone pairings. Thus, we infused a CaMKII-GCAMP calcium sensor into the dHPC and vHPC of mice and we recorded its activity during the 6 preconditioning sessions. The new results can be found in Figure 3 and explained in the Results section (Page 12, Lines 26-36). The results clearly show an engagement of CaMKII-positive neurons during the light-tone pairing observed both in the dHPC and vHPC. Finally, although the suggestion of performing optogenetic manipulations would be very elegant, we expect to have convinced the reviewer that our chemogenetic results clearly show and are enough to demonstrate the involvement of dHPC in the formation of mediated learning in the Light-Tone sensory preconditioning paradigm. However, we have added this in the Discussion Section as a future perspective/limitation of our study (Page 17, Lines 9-24).  

(5) Probe tests always start with the "Probe Test Tone", followed by the "Probe Test Light". "Probe Test Tone" consists of an extinction session, which could affect the freezing response during "Probe Test Light" (e.g., Polack et al. (http://dx.doi.org/10.3758/s13420-013-0119-5)). Preferably, adding a group of mice with a Probe Test Light with no Probe Test Tone could help clarify this potential issue. The authors should at least discuss the possibility that the tone extinction session prior to the "Probe Test Light" could have affected the freezing response to the light cue. 

We appreciate the comment raised by the reviewer. However, we think that our direct learning responses are quite robust in all of our experiments and, thus, the impact of a possible extinction based on the tone presentation should not affect our direct learning. However, as it is an important point, we have discussed it in the Discussion Section (Page 17, Lines 12-14).  

Reviewer #4 (Public review): 

Summary 

Pinho et al use in vivo calcium imaging and chemogenetic approaches to examine the involvement of hippocampal sub-regions across the different stages of a sensory preconditioning task in mice. They find clear evidence for sensory preconditioning in male but not female mice. They also find that, in the male mice, CaMKII-positive neurons in the dorsal hippocampus: (1) encode the audio-visual association that forms in stage 1 of the task, and (2) retrieve/express sensory preconditioned fear to the auditory stimulus at test. These findings are supported by evidence that ranges from incomplete to convincing. They will be valuable to researchers in the field of learning and memory. 

We appreciate the summary of our work and all the constructive comments raised by the Reviewer, which have greatly improved the clarity and quality of our manuscript.  

Abstract 

Please note that sensory preconditioning doesn't require the stage 1 stimuli to be presented repeatedly or simultaneously. 

The reviewer is right, and we have corrected and changed that information in the revised abstract.  

"Finally, we combined our sensory preconditioning task with chemogenetic approaches to assess the role of these two hippocampal subregions in mediated learning."  This implies some form of inhibition of hippocampal neurons in stage 2 of the protocol, as this is the only stage of the protocol that permits one to make statements about mediated learning. However, it is clear from what follows that the authors interrogate the involvement of hippocampal sub-regions in stages 1 and 3 of the protocol - not stage 2. As such, most statements about mediated learning throughout the paper are potentially misleading (see below for a further elaboration of this point). If the authors persist in using the term mediated learning to describe the response to a sensory preconditioned stimulus, they should clarify what they mean by mediated learning at some point in the introduction. Alternatively, they might consider using a different phrase such as "sensory preconditioned responding". 

Considering the arguments of the Reviewer, we have modified our text in the Abstract and through the main text. Moreover, based on a comment of Reviewer #2 (Point 2) we have generated new data demonstrating that dHPC does not seem to be involved in mediated learning formation during Stage 2, as its inhibition does not impair sensory preconditioning responding. This new data can be seen in Supplementary Figure 7G.  

Introduction 

"Low-salience" is used to describe stimuli such as tone, light, or odour that do not typically elicit responses that are of interest to experimenters. However, a tone, light, or odour can be very salient even though they don't elicit these particular responses. As such, it would be worth redescribing the "low-salience" stimuli in some other terms. 

Through the revised version of the manuscript, we have replaced the term “lowsalience” by “innocuous stimuli” or avoiding any adjective as we think is not necessary.  

"These higher-order conditioning processes, also known as mediated learning, can be captured in laboratory settings through sensory preconditioning procedures2,6-11."  Higher-order conditioning and mediated learning are not interchangeable terms: e.g., some forms of second-order conditioning are not due to mediated learning. More generally, the use of mediated learning is not necessary for the story that the authors develop in the paper and could be replaced for accuracy and clarity. E.g., "These higher-order conditioning processes can be studied in the laboratory using sensory preconditioning procedures2,6-11." 

According to the Reviewer proposal, we have modified the text. 

In reference to Experiment 2, it is stated that: "However, when light and tone were separated on time (Unpaired group), male mice were not able to exhibit mediated learning response (Figure 2B) whereas their response to the light (direct learning) was not affected (Figure 2D). On the other hand, female mice still present a lower but significant mediated learning response (Figure 2C) and normal direct learning (Figure 2E). Finally, in the No-Shock group, both male (Figure 2B and 2D) and female mice (Figure 2C and 2E) did not present either mediated or direct learning, which also confirmed that the exposure to the tone or light during Probe Tests do not elicit any behavioral change by themselves as the presence of the electric footshock is required to obtain a reliable mediated and direct learning responses."  The absence of a difference between the paired and unpaired female mice should not be described as "significant mediated learning" in the latter. It should be taken to indicate that performance in the females is due to generalization between the tone and light. That is, there is no sensory preconditioning in the female mice. The description of performance in the No-shock group really shouldn't be in terms of mediated or direct learning: that is, this group is another control for assessing the presence of sensory preconditioning in the group of interest. As a control, there is no potential for them to exhibit sensory preconditioning, so their performance should not be described in a way that suggests this potential. 

All these comments are very pertinent and also raised by Reviewer #2 (Point 1, see above). In the revised version of the manuscript, we have carefully changed, when necessary, our interpretation of the results (e.g. in the case of the No-Shock group). In addition, we have generated new data that confirm that using similar conditions (i.e. 2 conditioning sessions in our SPC) in female mice we observe fear generalization and not a confident sensory preconditioning responding. In our opinion, this is not discarding the presence of mediated learning in female mice but suggesting that adapted protocols must be used in each sex. These results forced us to change the organization of the Figures but we hope the reviewer would agree with all the changes proposed. In addition, we have re-wrote a paragraph in the Discussion Section to explain these sex differences (see Page 15, lines 12-37). 

Methods - Behavior 

I appreciate the reasons for testing the animals in a new context. This does, however, raise other issues that complicate the interpretation of any hippocampal engagement: e.g., exposure to a novel context may engage the hippocampus for exploration/encoding of its features - hence, it is engaged for retrieving/expressing sensory preconditioned fear to the tone. This should be noted somewhere in the paper given that one of its aims is to shed light on the broader functioning of the hippocampus in associative processes. 

This general issue - that the conditions of testing were such as to force engagement of the hippocampus - is amplified by two further features of testing with the tone. The first is the presence of background noise in the training context and its absence in the test context. The second is the fact that the tone was presented for 30 s in stage 1 and then continuously for 180s at test. Both changes could have contributed to the engagement of the hippocampus as they introduce the potential for discrimination between the tone that was trained and tested. 

We have now added these pertinent comments in a “Study limitations” paragraph found in the Discussion Section (Page 17, Lines 9-24). Indeed, the different changes of context (including the presence of background noise) have been implemented by the fact that during the setting up of the paradigm we had problems of fear generalization (also in male mice). Similarly, differences in cue exposure between the preconditioning phase and the test phase were also decided based on important differences between previous protocols used in rats compared to how mice are responding. Certainly, mice were not able to adapt their behavioral responses when shorter time windows exposing the cue were used as it clearly happens with rats [1].

Results - Behavior 

The suggestion of sex differences based on differences in the parameters needed to generate sensory preconditioning is interesting. Perhaps it could be supported through some set of formal analyses. That is, the data in supplementary materials may well show that the parameters needed to generate sensory preconditioning in males and females are not the same. However, there needs to be some form of statistical comparison to support this point. As part of this comparison, it would be neat if the authors included body weight as a covariate to determine whether any interactions with sex are moderated by body weight.  

Regarding the comparison between male and female mice, although the comments of the Reviewer are pertinent and interesting, we think that with the new data generated is not appropriate to compare both sexes as we still have to optimize the SPC protocol for female mice. 

What is the value of the data shown in Figure 1 given that there are no controls for unpaired presentations of the sound and light? In the absence of these controls, the experiment cannot have shown that "Female and male mice show mediated learning using an auditory-visual sensory preconditioning task" as implied by its title. Minimally, this experiment should be relabelled. 

Based on the new data generated with female mice, we have decided to remove Figure 1 and re-organize the structure of the manuscript. We hope that the Reviewer would agree that this has improved the clarity of the manuscript.  

"Altogether, this data confirmed that we successfully set up an LTSPC protocol in mice and that this behavioral paradigm can be used to further study the brain circuits involved in higherorder     conditioning."  Please insert the qualifier that LTSPC was successfully established in male mice. There is no evidence of LTSPC in female mice. 

We fully agree with the Reviewer and our new findings further confirm this issue. Thus, we have changed the statement in the revised version of the manuscript.  

Results - Brain 

"Notably, the inhibition of CaMKII-positive neurons in the dHPC (i.e. J60 administration in DREADD-Gi mice) during preconditioning (Figure 4B), but not before the Probe Test 1 (Figure 4B), fully blocked mediated, but not direct learning (Figure  4D)." The right panel of Figure 4B indicates no difference between the controls and Group DPC in the percent change in freezing from OFF to ON periods of the tone. How does this fit with the claim that CaMKII-positive neurons in the dorsal hippocampus regulate associative formation during the session of tone-light exposures in stage 1 of sensory preconditioning? 

To improve the quality of the figures and to avoid possible redundancies between panels, in the new version of the manuscript, we have decided to remove all the panels regarding the percentage of change. However, in our opinion regarding the issue raised by the Reviewer, the inhibition of the dHPC clearly induced an impairment of mediated learning as animals do not change their behavior (i.e. there is no significant increase of freezing between OFF and ON periods) when the tone appears in comparison with the other two groups. The graphs indicating the percentage of change (old version of the manuscript) was a different manner to show the presence of tone- or light-induced responses in each experimental group. Thus, a significant effect (shown by # symbol) meant that in that specific experimental group there was a significant change in behavior (freezing) when the cue (tone or light) appeared compared when there was no cue (OFF period). Thus, in the old panel 4B commented by the Reviewer, in our opinion, the absence of significance in the group where the dHPC has been inhibited during thepreconditioning, compared to the other groups, where a clear significant effect can be observed, indicate an impairment of mediated learning formation. However, to avoid any confusion, we have slightly modified the text to strictly mention what is being analyzed and/or shown in the graphs and, as mentioned, the graphs of percentage of change have been removed.  

Discussion 

"When low salience stimuli were presented separated on time or when the electric footshock was absent, mediated and direct learning were abolished in male mice. In female mice, although light and tone were presented separately during the preconditioning phase, mediated learning was reduced but still present, which implies that female mice are still able to associate the two low-salience stimuli." 

This doesn't quite follow from the results. The failure of the female unpaired mice to withhold their freezing to the tone should not be taken to indicate the formation of a light-tone association across the very long interval that was interpolated between these stimulus presentations. It could and should be taken to indicate that, in female mice, freezing conditioned to the light simply generalized to the tone (i.e., these mice could not discriminate well between the tone and light). 

As discussed above, we fully agree with the Reviewer and all the manuscript has been modified as described above. 

"Indeed, our data suggests that when hippocampal activity is modulated by the specific manipulation of hippocampal subregions, this brain region is not involved during retrieval."  Does this relate to the results that are shown in the right panel of Figure 4B, where there is no significant difference between the different groups? If so, how does it fit with the results shown in the left panel of this figure, where differences between the groups are observed? 

"In line with this, the inhibition of CaMKII-positive neurons from the dorsal hippocampus, which has been shown to project to the restrosplenial cortex56, blocked the formation of mediated learning." 

Is this a reference to the findings shown in Figure 4B and, if so, which of the panels exactly? That is, one panel appears to support the claim made here while the other doesn't. In general, what should the reader make of data showing the percent change in freezing from stimulus OFF to stimulus ON periods? 

In our opinion, as pointed above, the graphs indicating the percentage of change were a different manner to show the presence of tone- or light-induced behavioral responses in each experimental group. Thus, a significant effect (shown by # symbol) meant that in this specific experimental group there was a significant change in behavior (freezing) when the cue (tone or light appear) compared when there was no cue (OFF period). Thus, in the old panel 4B commented by the Reviewer, in our opinion, the absence of significance in the group where the dHPC has been inhibited during the preconditioning, compared to the other groups where a clear significant effect can be observed, indicates an impairment of mediated learning formation. In the revised version of the manuscript, we have rephrased these sentences to stick to what the graphs are showing and, as explained, the graphs of percentage of change have been removed.

Reviewer #1 (Recommendations for the authors): 

The authors may address the following questions: 

(1) The study identifies major sex differences in the conditioning phase, with females showing faster learning. Since hormonal fluctuations can influence learning and behavior, it would be helpful for the authors to comment on whether they tracked the estrous cycle of the females and whether any potential effects of the cycle on mediated learning were considered. 

This is a relevant and important point raised by the Reviewer. In our study we did not track the estrous cycle to investigate whether it exists any effect of the cycle on mediated learning, which could be an interesting project by itself. Although in the revised version of the manuscript we provide new information regarding the mediated learning performance in male and female mice, we agree with the reviewer that sex hormones may account for the observed sex differences. However, the aim of the present work was to explore potential sex differences in mediated learning responding rather than to investigate the specific mechanisms behind these potential sex differences. 

For this reason and to avoid adding further complexity to our present study, we did not check the estrous cycle in the female mice, the testosterone levels in male mice or analyze the amount of sex hormones during different phases of the sensory preconditioning task. Indeed, we think that checking the estrous cycle in female mice would still not be enough to ascertain the role of sex hormones because checking the androgen levels in male mice would also be required. In line with this, meta-analysis of neuroscience literature using the mouse model as research subjects [2-4]  has revealed that data collected from female mice (regardless of the estrous cycle) did not vary more than the data from males. In conclusion, we think that using randomized and mixed cohorts of male and female mice (as in the present study) would provide the same degree of variability in both sexes. Nevertheless, we have added a sentence to point to this possibility in the Discussion Section (Page 15, lines 32-37). 

(2) The rationale for including parvalbumin (PV) cells in the study could be clarified. Is there prior evidence suggesting that this specific cell type is involved in mediated learning? This could apply to sensory stimuli not used in the current study.

In the revised version of the manuscript, we have better clarified why we targeted PV interneurons, specifically mentioning previous studies [5] (see Page 11, Lines 27-34). 

(3) The photometry recordings from the dHPC during the preconditioning phase, shown in Figure 3, are presented as average responses. It would be beneficial to separate the early vs. late trials to examine whether there is an increase in hippocampal activity as the associative learning progresses, rather than reporting the averaged data. Additionally, to clarify the dynamics of the dHPC in associative learning, the authors could compare the magnitude of photometry responses when light and tone stimuli are presented individually in separate sessions versus when they are presented closely in time to facilitate associative learning.

As commented above, according to the Reviewer’s comment, we have now included a new Supplementary Figure 4, which splits the photometry data by the different preconditioning and conditioning sessions. Overall, this data suggests that there are no major changes on cell activity in both hippocampal regions during the different sessions as similar light-tone-induced enhancement of activity is observed. There is only an interesting trend in the activity of Pan-Neurons over the onset of light during conditioning sessions. All this is included now in the Results Section (Page 12, Line 13-15).

(4) The authors note that PV cell responses recorded with GCaMP were similar to general hippocampal neurons, yet chemogenetic manipulations of PV cells did not impact behavior. A more detailed discussion of this discrepancy would be helpful. 

As suggested by the Reviewer, we have included additional Discussion to explain the potential discrepancy between the activity of PV interneurons assessed by photometry and its modulation by chemogenetics (see Page 16, Lines 27-33).   

(5) All fiber photometry recordings were conducted in male mice. Given the sex differences observed in associative learning, the authors could expand the study to include dHPC responses in females during both preconditioning and conditioning sessions. 

We appreciate the comment of the Reviewer. Indeed, thanks to other comments made by other Reviewers in this revision (see Point 1 of Reviewer #2), we are not still sure that we have an optimal protocol to study mediated learning in female mice due to sexspecific changes related to fear generalization. Thus, the revised version of the manuscript, although highlighting these sex differences in behavioral performance (see Supplementary Figure 2), is more focused in male mice and, accordingly, all photometry or chemogenetic experiments are performed exclusively using male mice. In future studies, once we would be sure to have a sensory preconditioning paradigm working in female mice, it will be very interesting to study if the same hippocampal mechanisms mediating this behavior in male mice are also observed in female mice. 

Minor Comments: 

(1) In the right panel of Figure 2A, females received only one conditioning session, so the "x2" should be corrected to "x1" conditioning to accurately reflect the data. 

We thank the Reviewer for the comment that has been addressed in the revised version of the manuscript.  

(2) The overall presentation of Figure 3 could be improved. For example, the y-axis in Panel B could be cut to a maximum of 3 rather than 6, which would better highlight the response data. Alternatively, including heatmap representations of the z-score responses could enhance clarity and visual impact.  

We thank the Reviewer for the comment that has been addressed providing a new format for Figures 2 and 3 in the revised version of the manuscript.   

(3) There are several grammatical errors throughout the manuscript. It is recommended that the authors use a grammar correction tool to improve the overall writing quality and readability.  

We have tried to correct the grammar through all the manuscript.  

Reviewer #2 (Recommendations for the authors):  

(1) In the abstract the authors write that sensory preconditioning requires the "repeated and simultaneous presentation of two low-salience stimuli such as a light and a tone". Previous research has shown that sensory preconditioning can still occur if the two stimuli are presented serially, rather than simultaneously. Further, the tone and the light are not necessarily "low-salience", for example, they can be loud or bright. It would be better to refer to them as innocuous. 

In the revised version of the abstract, we have included the modifications suggested by the Reviewer.   

(2) The authors develop a novel automated tool for assessing freezing behaviour in mice that correlates highly with both manual freezing and existing, open-source freeze estimation software (ezTrack). The authors should explain how the new program differs from ezTrack, or if it provides any added benefit over this existing software. 

We have added new information in the Results Section (Page 10, Lines 13-20 to better explain how the new tool to quantify freezing could improve existing software.  

(3) In Experiment 1, the authors report a sex difference in levels of freezing between male and female mice when they are only given one session of sensory preconditioning. This should be supported by a statistical comparison of levels of freezing between male and female mice. 

Based on the new results obtained with female mice, we have decided to remove the original Figure 1 of the manuscript as it is not meaningful to compare male and female mediated learning response if we do not have an optimal protocol in female mice.  

(4) Why did the authors choose to vary the duration of the stimuli across preconditioning, conditioning, and testing? During preconditioning, the light-tone compound was 30s, in conditioning the light was 10s, and at test both stimuli were presented continuously for 3 min. Did the level of freezing vary across the three-minute probe session? There is some evidence that rodents can learn the timing of stimuli and it may be the case that freezing was highest at the start of the test stimulus, when it most closely resembled the conditioned stimulus. 

Differences in cue exposure between the preconditioning phase and the test phase were decided based on important differences between previous protocols used in rats compared to how mice are responding. Indeed, mice were not able to adapt their behavioral responses when shorter time windows exposing the cue were used as it clearly happens with rats1. In addition, we have added a new graph to show the time course of the behavioral responses (see Figure 1 and 4 and Supplementary Figure 2) that correlate with the quantification of freezing responses shown by the percentage of freezing during ON and OFF periods.   

(5) The title of Experiment 1 "Female and male mice show mediated learning using an auditory-visual sensory preconditioning task" - this experiment does not demonstrate mediated learning; it merely shows that animals will freeze more in the presence of a stimulus as compared with no stimulus. This experiment lacks the necessary controls to claim mediated learning (which are presented in Experiment 2) and should therefore be retitled something more appropriate.

As stated above, based on the new results obtained with female mice, we have decided to remove the original Figure 1 of the manuscript as it is not meaningful to compare male and female mediated learning response if we do not have an optimal protocol in female mice.   

(6) In Figure 2, why does the unpaired group show less freezing to the tone than the paired group given that the tone was directly paired with the shock in both groups? 

We believe the Reviewer may have referred to the tone in error (i.e. there are no differences in the freezing observed to the tone) and (s)he might be talking about the freezing induced by the Light in the direct learning test. In this case, it is true that the direct learning (e.g. percentage of freezing) seems to be slightly lower in the unpaired group compared to the paired one, which could be due to a latent inhibition process caused by the different exposure of cues between paired and unpaired experimental groups. However, the direct learning in both groups is clear and significant and there are no significant differences between them, which makes difficult to extract any further conclusion. 

(7) The stimuli in the design schematics are quite small and hard to see, they should be enlarged for clarity. The box plots also looked stretched and the colour difference between the on and off periods is difficult to discern. 

We have included some important modification to the Figures in order to address the comments made by the Reviewer and improve its quality.   

(8) The authors do not include labels for the experimental groups (paired, unpaired, no shock) in Figures 2B, 2D, 2C, and 2E. This made it very difficult to interpret the figure.  

According to this suggestion, Figure 2 has been changed accordingly. 

(9) The levels of freezing during conditioning should be presented for all experiments.  

We have generated a new Supplementary Figure 9 to show the freezing levels during conditioning sessions. 

(10) In the final experiment, the authors wrote that mice were injected with J60 or saline, but I could not find the data for the saline animals.  

In the Results and Methods section, we have included a sentence to better explain this issue. In addition, we have added a new Supplementary Figure 7 to show the performance of all control groups.  

(11) Please list the total number of animals (per group, per sex) for each experiment.  

In the revised version of the manuscript, we have added this information in each Figure Legend.  

Reviewer #3 (Recommendations for the authors): 

I found this study very interesting, despite a few weaknesses. I have several minor comments to add, hoping that it would improve the manuscript: 

(1) The terminology used is not always appropriate/consistent. I would use "freely moving fiber photometry" or simply "fiber photometry" as calcium imaging conventionally refers to endoscopic or 2-photon calcium imaging. 

We thank the Reviewer for this comment that has been addressed and corrected in the revised version of the manuscript. 

(2) "Dorsal hippocampus mediates light-tone sensory preconditioning task in mice" suggests that a brain region mediates a task. I would rather suggest, e.g. "Dorsal hippocampus mediates light-tone association in mice" 

We thank the Reviewer for this comment that has been addressed and corrected in the revised version of the manuscript.

(3) As you are using low-salience stimuli, it would be better to also inform the readership with the light intensity used for the light cue, for replicability purposes. 

In the Methods section (Page 5, Line 30), we have added new information regarding the visual stimuli used. 

(4) If the authors didn't use a background noise during the probe tests, the tone cue could have been perceived as being louder/clearer by mice. Couldn't it have inflated the freezing response for the tone cue?  

This is an interesting comment made by the Reviewer although we do not have any data to directly answer his/her suggestion. However, the presence of the Background noise resulted necessary to set up the protocol and to change different aspects of the context through all the paradigm, which was necessary to avoid fear generalization in mice. In addition, as demonstrated before [6] , the presence of background noise is important to avoid that other auditory cue (i.e. tone) could induce fear responses by itself as the transition of noise to silence is a signal to danger for animals. 

(5) "salience" is usually used for the intensity of a stimulus, not for an association or pairing. Rather, we usually refer to the strength of an association. 

We thank the Reviewer for this comment that has been addressed and corrected in the revised version of the manuscript.

(6) Figure 3, panel A. "RCaMP Neurons", maybe "Pan-Neurons" would be more appropriate, as PV+ inter-neurons are also neurons. 

We thank the Reviewer for this comment that has been corrected accordingly.

(7) Figure 4, panel A, please add the AAV injected, and the neurons labelled in your example slice. 

We thank the Reviewer for this comment that has been corrected accordingly.

References

(1) Wong, F. S., Westbrook, R. F. & Holmes, N. M. 'Online' integration of sensory and fear memories in the rat medial temporal lobe. Elife 8 (2019). https://doi.org:10.7554/eLife.47085

(2) Prendergast, B. J., Onishi, K. G. & Zucker, I. Female mice liberated for inclusion in neuroscience and biomedical research. Neurosci Biobehav Rev 40, 1-5 (2014). https://doi.org:10.1016/j.neubiorev.2014.01.001

(3) Becker, J. B., Prendergast, B. J. & Liang, J. W. Female rats are not more variable than male rats: a meta-analysis of neuroscience studies. Biol Sex Differ 7, 34 (2016). https://doi.org:10.1186/s13293-016-0087-5

(4) Shansky, R. M. Are hormones a "female problem" for animal research? Science 364,  825-826 (2019). https://doi.org:10.1126/science.aaw7570

(5) Busquets-Garcia, A. et al. Hippocampal CB1 Receptors Control Incidental Associations. Neuron 99, 1247-1259 e1247 (2018). https://doi.org:10.1016/j.neuron.2018.08.014

(6) Pereira, A. G., Cruz, A., Lima, S. Q. & Moita, M. A. Silence resulting from the cessation of movement signals danger. Curr Biol 22, R627-628 (2012). https://doi.org:10.1016/j.cub.2012.06.015

Author response:

The following is the authors’ response to the original reviews

Reviewer #1 (Public review):

SMC5/6 is a highly conserved complex able to dynamically alter chromatin structure, playing in this way critical roles in genome stability and integrity that include homologous recombination and telomere maintenance. In the last years, a number of studies have revealed the importance of SMC5/6 in restricting viral expression, which is in part related to its ability to repress transcription from circular DNA. In this context, Oravcova and colleagues recently reported how SMC5/6 is recruited by two mutually exclusive complexes (orthologs of yeast Nse5/6) to SV40 LT-induced PML nuclear bodies (SIMC/SLF2) and DNA lesions (SLF1/2). In this current work, the authors extend this study, providing some new results. However, as a whole, the story lacks unity and does not delve into the molecular mechanisms responsible for the silencing process. One has the feeling that the story is somewhat incomplete, putting together not directly connected results.

Please see the introductory overview above.

(1) In the first part of the work, the authors confirm previous conclusions about the relevance of a conserved domain defined by the interaction of SIMC and SLF2 for their binding to SMC6, and extend the structural analysis to the modelling of the SIMC/SLF2/SMC complex by AlphaFold. Their data support a model where this conserved surface of SIMC/SLF2 interacts with SMC at the backside of SMC6's head domain, confirming the relevance of this interaction site with specific mutations. These results are interesting but confirmatory of a previous and more complete structural analysis in yeast (Li et al. NSMB 2024). In any case, they reveal the conservation of the interaction. My major concern is the lack of connection with the rest of the article. This structure does not help to understand the process of transcriptional silencing reported later beyond its relevance to recruit SMC5/6 to its targets, which was already demonstrated in the previous study.

Demonstrating the existence of a conserved interface between the Nse5/6-like complexes and SMC6 in both yeast and human is foundationally important, not confirmatory, and was not revealed in our previous study. It remains unclear how this interface regulates SMC5/6 function, but yeast studies suggest a potential role in inhibiting the SMC5/6 ATPase cycle. Nevertheless, the precise function of Nse5/6 and its human orthologs in SMC5/6 regulation remain undefined, largely due to technical limitations in available in vivo analyses. The SIMC1/SLF2/SMC6 complex structure likely extends to the SLF1/2/SMC6 complex, suggesting a unifying function of the Nse5/6-like complexes in SMC5/6 regulation, albeit in the distinct processes of ecDNA silencing and DNA repair. There have been no studies to date (including this one) showing that SIMC1-SLF2 is required for SMC5/6 recruitment to ecDNA. Our previous study showed that SIMC1 was needed for SMC5/6 to colocalize with SV40 LT antigen at PML NBs. Here we show that SIMC1 is required for ecDNA repression, in the absence of PML NBs, which was not anticipated.

(2) In the second part of the work, the authors focus on the functionality of the different complexes. The authors demonstrate that SMC5/6's role in transcription silencing is specific to its interaction with SIMC/SLF2, whereas SMC5/6's role in DNA repair depends on SLF1/2. These results are quite expected according to previous results. The authors already demonstrated that SLF1/2, but not SIMC/SLF2, are recruited to DNA lesions. Accordingly, they observe here that SMC5/6 recruitment to DNA lesions requires SLF1/2 but not SIMC/SLF2. Likewise, the authors already demonstrated that SIMC/SLF2, but not SLF1/2, targets SMC5/6 to PML NBs. Taking into account the evidence that connects SMC5/6's viral resistance at PML NBs with transcription repression, the observed requirement of SIMC/SLF2 but not SLF1/2 in plasmid silencing is somehow expected. This does not mean the expectation has not to be experimentally confirmed. However, the study falls short in advancing the mechanistic process, despite some interesting results as the dispensability of the PML NBs or the antagonistic role of the SV40 large T antigen. It had been interesting to explore how LT overcomes SMC5/6-mediated repression: Does LT prevent SIMC/SLF2 from interacting with SMC5/6? Or does it prevent SMC5/6 from binding the plasmid? Is the transcription-dependent plasmid topology altered in cells lacking SIMC/SLF2? And in cells expressing LT? In its current form, the study is confirmatory and preliminary. In agreement with this, the cartoons modelling results here and in the previous work look basically the same.

Our previous study only examined the localization of SLF1 and SIMC1 at DNA lesions. The localization of these subcomplexes alone should not be used to define their roles in SMC5/6 localization. Indeed, the field is split in terms of whether Nse5/6-like complexes are required for ecDNA binding/loading, or regulation of SMC5/6 once bound. 

We agree, determining the potential mechanism of action of LT in overcoming SMC5/6-based repression is an important next step. We believe it is unlikely due to blocking of the SMC5/6SIMC1/SLF2 interface, since SIMC1-SLF2 is required for SMC5/6 to localize at LT-induced foci. It will require the identification of any direct interactions with SMC5/6 subunits, and better methods for assessing SMC5/6 loading and activity on ecDNAs. Unlike HBx, Vpr, and BNRF1 it does not appear to induce degradation of SMC5/6, making it a more complex and interesting challenge. Also, the dispensability of PML NBs in plasmid silencing versus viral silencing raises multiple important questions about SMC5/6’s repression mechanism. 

(3) There are some points about the presented data that need to be clarified.

Thank you, we have addressed these points below, within the Recommendations for authors section.

Reviewer #2 (Public review):

Oracová et al. present data supporting a role for SIMC1/SLF2 in silencing plasmid DNA via the SMC5/6 complex. Their findings are of interest, and they provide further mechanistic detail of how the SMC5/6 complex is recruited to disparate DNA elements. In essence, the present report builds on the author's previous paper in eLife in 2022 (PMID: 36373674, "The Nse5/6-like SIMC1-SLF2 complex localizes SMC5/6 to viral replication centers") by showing the role of SIMC1/SLF2 in localisation of the SMC5/6 complex to plasmid DNA, and the distinct requirements as compared to recruitment to DNA damage foci. Although the findings of the manuscript are of interest, we are not yet convinced that the new data presented here represents a compelling new body of work and would better fit the format of a "research advance" article. In their previous paper, Oracová et al. show that the recruitment of SMC5/6 to SV40 replication centres is dependent on SIMC1, and specifically, that it is dependent on SIMC1 residues adjacent to neighbouring SLF2.

We agree. We submitted this manuscript as a “Research Advance”, not as a standalone research article, given that it is an extension of our previous “Research Article” (1).

Other comments

(1) The mutations chosen in Figure 1 are quite extensive - 5 amino acids per mutant. In addition, they are in many cases 'opposite' changes, e.g., positive charge to negative charge. Is the effect lost if single mutations to an alanine are made?

The mutations were chosen to test and validate the predicted SIMC1-SLF2-SMC6 structure i.e. the contact point between the conserved patch of SIMC1-SLF2 and SMC6. Multiple mutations and charge inversions increased the chance of disrupting the extensive interface. In this respect, the mutations were successful and informative, confirming the requirement of this region in specifically contacting SMC6. Whilst alanine scanning mutations are possible, we believe that they would not add to, or detract from, our validation of the predicted SIMC1-SLF2-SMC6 interface.

(2) In Figure 2c, it isn't clear from the data shown that the 'SLF2-only' mutations in SMC6 result in a substantial reduction in SIMC1/SLF2 binding.

To clarify the difference between wild-type and SLF2-only mutations in SIMC1-SLF2 interaction, we have performed an image volume analysis. This shows that the SLF2-facing SMC6 mutant reduces its interaction with SIMC1 (to 44% of WT) and SLF2 (to 21% of WT). The reduction in both SIMC1 and SLF2 interaction with SMC6 SLF2-facing mutant is expected, since SIMC1 and SLF2 are an interdependent heterodimer.  

Author response table 1.

(3) In the GFP reporter assays (e.g. Figure 3), median fluorescence is reported - was there any observed difference in the percentage of cells that are GFP positive?

Yes, as expected when the GFP plasmid is not actively repressed, the percent of GFP positive cells differs in each cell line – in the same trend as GFP intensity

(4) The potential role of the large T antigen as an SMC5/6 evasion factor is intriguing. However, given the role of the large T antigen as a transcriptional activator, caution is required when interpreting enhanced GFP fluorescence. Antagonism of the SMC5/6 complex in this context might be further supported by ChIP experiments in the presence or absence of large T. Can large T functionally substitute for HBx or HIV-Vpr?

We agree, the potential role of LT in SMC5/6 antagonism is interesting. We did state in the text “While LT is known to be a promiscuous transcriptional activator (2,3) that does not rule out a co-existing role in antagonizing SMC5/6. Indeed, these findings are reminiscent of HBx from HBV and Vpr of HIV-1, both of which are known promiscuous transcriptional activators that also directly antagonize SMC5/6 to relieve transcriptional repression (4-10).“ We have tried ChIP experiments, but found these to be unreliable in assessing SMC5/6 association with plasmid DNA. Given the many disparate targets of LT, HBx and Vpr (other than SMC5/6), it seems unlikely that LT could functionally substitute for HBx and Vpr in supporting HBV and HIV-1 infections. Whilst certainly an interesting future question, we believe it is beyond the scope of this study.

(5) In Figure 5c, the apparent molecular weight of large T and SMC6 appears to change following transfection of GFP-SMC5 - is there a reason for this?

We are not certain as to what causes the molecular weight shift, but it is not specifically related to GFPSMC5 transfection. Rather, it appears to be a general effect of the pulldown. Indeed, a very weak “background” band of LT is seen in the GFP only pulldown, which also runs at a “higher” molecular weight, as in the GFP-SMC5 pulldown. We believe that the effect is instead related to gel mobility in the wells that contain post pulldown proteins and different buffers. We have also seen similar effects using different protein-protein interaction pairs. 

Reviewer #3 (Public review):

Summary:

This study by the Boddy and Otomo laboratories further characterizes the roles of SMC5/6 loader proteins and related factors in SMC5/6-mediated repression of extrachromosomal circular DNA. The work shows that mutations engineered at an AlphaFold-predicted protein-protein interface formed between the loader SLF2/SIMC1 and SMC6 (similar to the interface in the yeast counterparts observed by cryo-EM) prevent co-IP of the respective proteins. The mutations in SLF2 also hinder plasmid DNA silencing when expressed in SLF2-/- cell lines, suggesting that this interface is needed for silencing. SIMC1 is dispensable for recruitment of SMC5/6 to sites of DNA damage, while SLF1 is required, thus separating the functions of the two loader complexes. Preventing SUMOylation (with a chemical inhibitor) increases transcription from plasmids but does not in SLF2-deleted cell lines, indicating the SMC5/6 silences plasmids in a SUMOylation dependent manner. Expression of LT is sufficient for increased expression, and again, not additive or synergistic with SIMC1 or SLF2 deletion, indicating that LT prevents silencing by directly inhibiting 5/6. In contrast, PML bodies appear dispensable for plasmid silencing.

Strengths:

The manuscript defines the requirements for plasmid silencing by SMC5/6 (an interaction of Smc6 with the loader complex SLF2/SIMC1, SUMOylation activity) and shows that SLF1 and PML bodies are dispensable for silencing. Furthermore, the authors show that LT can overcome silencing, likely by directly binding to (but not degrading) SMC5/6.

Weaknesses:

(1) Many of the findings were expected based on recent publications.

There have been no manuscripts describing the role of SIMC1-SLF2 in ecDNA silencing. There have been studies describing SLF2’s roles in ecDNA silencing, but these suggested SLF2 had an SLF1 independent role, with no mention of an alternate Nse5-like cofactor. Our earlier study in eLife (1) described the identification of SIMC1 as an Nse5-like cofactor for SLF2 but did not test potential roles of the complex in ecDNA silencing. Also, the apparent dispensability of PML NBs in plasmid silencing (in U2OS cells) was unexpected based on recent publications. Finally, SV40 LT has not previously been implicated in SMC5/6 inhibition, which may occur through novel mechanisms.

(2) While the data are consistent with SIMC1 playing the main function in plasmid silencing, it is possible that SLF1 contributes to silencing, especially in the absence of SIMC1. This would potentially explain the discrepancy with the data reported in ref. 50. SLF2 deletion has a stronger effect on expression than SIMC1 deletion in many but not all experiments reported in this manuscript. A double mutant/deletion experiments would be useful to explore this possibility.

It is interesting to note that the data in ref. 50 (11) is also at odds with that in ref. 45 (8) in terms of defining a role for SLF1 in the silencing of unintegrated HIV-1 DNA. The Irwan study showed that SLF1 deficient cells exhibit increased expression of a reporter gene from unintegrated HIV-1, whereas the Dupont study found that SLF1 deletion, unlike SLF2 deletion, has no effect. It is unclear what the basis of this discrepancy is. In line with the Dupont study, we found no effect of SLF1 deletion on plasmid expression (Figure 4B), whereas SLF2 deletion increased reporter expression (Figure 3A/B). It is possible that SLF1 could support some plasmid silencing in the absence of SIMC1, especially considering the gross structural similarity in their C-terminal Nse5-like domains. However, we have been unable to generate double-knockout SIMC1 and SLF1 cells to test such a possibility, and shSLF1 has been ineffective. 

(3) SLF2 is part of both types of loaders, while SLF1 and SIMC1 are specific to their respective loaders. Did the authors observe differences in phenotypes (growth, sensitivities to DNA damage) when comparing the mutant cell lines or their construction? This should be stated in the manuscript.

We have not observed significant differences in the growth rates of each cell line, and DNA damage sensitivities are as yet untested.   

(4) It would be desirable to have control reporter constructs located on the chromosome for several experiments, including the SUMOylation inhibition (Figures 5A and 5-S2) and LT expression (Figure 5D) to exclude more general effects on gene expression.

We have repeated all GFP reporter assays using integrated versus episomal plasmid DNA. A seminal study by Decorsière et al. (6) showed that SMC5/6 degradation by HBx of HBV increased transcription of episomal but not chromosomally integrated reporters. In line with this data, the deletion of SLF2 does not notably impact the expression of our GFP reporter construct when it is genomically integrated (Figure 3—figure supplement 1C).  

Somewhat surprisingly, given the generally transcriptionally repressive roles of SUMO, inhibition of the SUMO pathway with SUMOi did not significantly impact the expression of our genomically integrated GFP reporter, versus the episomal plasmid (Figure 5—figure supplement 1C). Finally, the expression of SV40 LT, which enhances plasmid reporter expression (Figure 5D), also did not notably affect expression of the same reporter when located in the genome (Figure 5—figure supplement 3B). This is an interesting result, which is in line with an early study showing that HBx of HBV induces transcription from episomal, but not chromosomally integrated reporters (12). This further suggests that SV40 LT acts similarly to other early viral proteins like HBx and Vpr to counteract or bypass SMC5/6 restriction, amongst their multifaceted functions. Clearly, further analyses are needed to define mechanisms of LT in counteracting SMC5/6, but they do not appear to include complex degradation as seen with HBx and Vpr.  

(5) Figure 5A: There appears to be an increase in GFP in the SLF2-/- cells with SUMOi? Is this a significant increase?

No significant difference was found between WT, SIMC1-/- or SLF2-/- when treated with SUMOi (p>0.05). The p-value is 0.0857 (when comparing SLF2-/- to WT in the SUMOi condition) This is described in the figure legend to Figure 5.

(6) The expression level of SFL2 mut1 should be tested (Figure 3B).

Full length SLF2 (WT or mutants) has been undetectable by western analyses. However, truncated SLF2 mut1 expresses well and binds SIMC1 but not SMC6 (Figure 1C). Moreover, full length SLF2 mut1 expression was confirmed by qPCR – showing a somewhat higher expression level than SLF2 WT (Figure 3—figure supplement 1B).  

Reviewer #1 (Recommendations for the authors):

There are some points about the presented data that need to be clarified.

(1) Figures 3, 4B, and 5. The authors should rule out the possibility that the reported effects on transcription were due to alterations in plasmid number. This is particularly important, taking into account the importance of SMC5/6 in DNA replication.

We used qPCR to assess plasmid copy number versus genomic DNA in our cell lines, testing at 72 hours post transfection to avoid any impact of cytosolic DNA (13). Our qPCR data show that there is no significant impact on plasmid copy number across our cell lines i.e. WT and SLF2 null.  SMC5/6 has a positive role in DNA replication progression on the genome (e.g. (14)), so loss of SMC5/6 “targeting” in SIMC1 and SLF2 null cells would be unlikely to promote replication fork progression per se. 

(2) Figure S1A. In contrast to the statement in the text, the SIMC1-combo control is affected in its binding to SLF2; however, it is not affected in its binding to SMC6. This is somehow unexpected because it suggests that the solenoid-like structure is not required for SMC6 binding, just specific patches at either SIMC or SLF2. This should be commented on.

We appreciate the reviewer’s observation regarding the discrepancy between Figure S1A and the text. This was our oversight. The data show that SLF2 recovery was reduced in the pull-down with the SIMC1 combo control mutant, while SLF2 expression was unchanged. Because SLF2 or SIMC1 variants that fail to associate typically show poor expression (1), these findings suggest that the SIMC1 combo control mutant associates with SLF2, albeit more weakly. Since the mutations were introduced into surface residues of SIMC1, it is not immediately clear how they would weaken the interaction or destabilize the complex. In contrast, SMC6 was fully recovered with the SIMC1 combo control mutant, indicating that the SIMC1–SMC6 interaction remains stable without stoichiometric SLF2. This may reflect direct recognition of a SIMC1 binding epitope or stabilization of its solenoid structure by SMC6, although this interpretation remains uncertain given the unstable nature of free SIMC1 and SLF2. Alternatively, SMC6 may have co-sedimented with the SIMC1 combo control mutant together with SLF2, which was initially retained but subsequently lost during washing, whereas SMC6 remained due to its limited solubility in the absence of other SMC5/6 subunits. While further mechanistic analysis will require purified SMC5/6 components, our data support the AlphaFold-based model by demonstrating that SIMC1 mutations on the non–SMC6-contacting surface retain association with SMC6. The text has been revised accordingly.

(3) The SLF2-only mutant has alterations that affect interactions with both SLF2 and SIMC1. Is it not another Mixed mutant?

We appreciate the reviewer’s observation regarding the discrepancy between the mutant name (“SLF2only”) and its description (“while N947 forms salt bridges with SIMC1”). The previous statement was inaccurate due to a misinterpretation of several AlphaFold models. Across these models, the SIMC1– SLF2 interface residues remain largely consistent, but the SIMC1 residue R470 exhibits positional variability—contacting N947 in some models but not in others. Given this variability and the absence of an experimental structure, we have revised the text to avoid overinterpretation. Because the N947 side chain is oriented toward SLF2 and consistently forms polar contacts with the H1148 side chain and G1149 backbone, we have renamed this mutant “SLF2-facing,” which more accurately describes its modeled environment. The other mutants are likewise renamed “SIMC1-facing” and “SIMC1–SLF2groove-facing,” providing a clearer and more consistent description of the interface.

(4) The SLF2-only mutant still displays clear interactions with SMC6. Can this be explained with the AlphaFold model?

SIMC1 may contribute more substantially to SMC6 binding than SLF2, consistent with our mutagenesis results. However, the energetic contributions of individual residues or proteins cannot be quantitatively inferred from structural models alone. Comprehensive experimental and computational analyses would be required to address this point.

(5) The conclusions about the role of SUMOylation are vague; it is already known that its general effect on transcription repression, and the authors already demonstrated that SIMC interacts with SUMO pathway factors. Concerning the epistatic effect, the experiment should be done at a lower inhibitor concentration; at 100 nM there is not much margin to augment according to the kinetics analysis in Figure S5.

The SUMO pathway is indeed thought to be generally repressive for transcription. Notably, in response to a suggestion from Reviewer 3 (public review point 4), we have repeated several of our GFP expression assays using cells with the GFP reporter plasmid integrated into the genome (please see Figure 3—figure supplement 1C; Figure 5—figure supplement 1C; Figure 5—figure supplement 3B). This type of integrated reporter does not show elevated expression following inhibition of the SMC5/6 complex, unlike ecDNAs (6,10). Interestingly, SUMOi, LT expression, and SLF2 knockout also did not notably impact the expression of our integrated GFP reporter (Figure 3—figure supplement 1C; Figure 5—figure supplement 1C; Figure 5—figure supplement 3B, unlike that of the plasmid (ecDNA) reporter. Given the “general” inhibitory effect of SUMO on transcription, the SUMOi result was not expected, and it opens further interesting avenues for study. 

In Figure 5—figure supplement 1A, 100 nM SUMOi increases reporter expression well below the highest SUMOi dose. We believe that the ~3-4 fold induction of GFP expression in SLF2 null cells, if independent of SUMOylation, should further increase GFP expression. The impact of SUMOylation on GFP reporter expression remains “vague”, but our data indicate that SMC5/6 operates within SUMO’s “umbrella” function and provides a starting point for more mechanistic dissection. 

(6) Figure 5C. Why is the size different between Input versus GFP-PD?

Please see our response to this question above: reviewer 2, point (5)

Reviewer #2 (Recommendations for the authors):

If further data could be provided to extend on that which is presented, then publication as a 'standalone research article' may be appropriate, but not in its present form.

We submitted this manuscript as a “Research Advance” not as a standalone research article, given that it was an extension of our previous research article (1).

Reviewer #3 (Recommendations for the authors):

(1) The term 'LT' should be defined in the title

We have updated the title accordingly.  

(2) This reviewer found the nomenclature of the SMC6 mutants confusing (SIMC1-only...). Either rephrase or define more clearly in the text and the figures.

We agree with the reviewer and have renamed the mutants as “SIMC1-facing”, “SLF2-facing,”, and “SIMC1–SLF2-groove-facing”.

(3) The authors could better emphasize that LT blocks silencing in trans (not only on its cognate target sequence in cis). This is consistent with the observed direct binding to SMC5/6.

We appreciate the suggestion to further emphasize the impact of LT on plasmid silencing. We did not want to overstate its impact at this time because we do not know if it directly binds SMC5/6 or indeed affects SMC5/6 function more broadly. LT expression like HBx, does cause induction of a DNA damage response, but we cannot at this point tie that response to SMC5/6 inhibition alone.

(4) Figure 5 S1: the merge looks drastically different. Is DAPI omitted in the wt merge image?

Thank you for noting this issue. We have corrected the image, which was impacted by the use of an underexposed DAPI image.  

(5) Figure 1: how is the structure in B oriented relative to A? A visual guide would be helpful.

We have added arrows to indicate the view orientation and rotational direction to turn A to B.

(6) Line 126, unclear what "specificity" here means.

We have revised the sentence without this word, which now starts with “To confirm the SIMC1-SMC6 interface, we introduced….”

(7) Line 152, The statement implies that the conserved residues are needed for loader subunits interactions ('mediating the SIMC1-SLF2 interaction"). Does Figure 1C not show that the residues are not important? Please clarify.

Thank you for noting this writing error. We have corrected the sentence to provide the intended meaning. It now reads "Collectively, these results confirm that the conserved surface patch of SIMC1SLF2 is essential for SMC6 binding.” 

References

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(2) Sullivan CS, Pipas JM. T antigens of simian virus 40: molecular chaperones for viral replication and tumorigenesis. Microbiol Mol Biol Rev. 2002;66(2):179-202. PMCID: PMC120785

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(5) Aufiero B, Schneider RJ. The hepatitis B virus X-gene product trans-activates both RNA polymerase II and III promoters. EMBO J. 1990;9(2):497-504. PMCID: PMC551692

(6) Decorsiere A, Mueller H, van Breugel PC, Abdul F, Gerossier L, Beran RK, Livingston CM, Niu C, Fletcher SP, Hantz O, Strubin M. Hepatitis B virus X protein identifies the Smc5/6 complex as a host restriction factor. Nature. 2016;531(7594):386-9. 

(7) Murphy CM, Xu Y, Li F, Nio K, Reszka-Blanco N, Li X, Wu Y, Yu Y, Xiong Y, Su L. Hepatitis B Virus X Protein Promotes Degradation of SMC5/6 to Enhance HBV Replication. Cell Rep. 2016;16(11):2846-54. PMCID: PMC5078993

(8) Dupont L, Bloor S, Williamson JC, Cuesta SM, Shah R, Teixeira-Silva A, Naamati A, Greenwood EJD, Sarafianos SG, Matheson NJ, Lehner PJ. The SMC5/6 complex compacts and silences unintegrated HIV-1 DNA and is antagonized by Vpr. Cell Host Microbe. 2021;29(5):792-805 e6. PMCID: PMC8118623

(9) Felzien LK, Woffendin C, Hottiger MO, Subbramanian RA, Cohen EA, Nabel GJ. HIV transcriptional activation by the accessory protein, VPR, is mediated by the p300 co-activator. Proc Natl Acad Sci U S A. 1998;95(9):5281-6. PMCID: PMC20252

(10) Diman A, Panis G, Castrogiovanni C, Prados J, Baechler B, Strubin M. Human Smc5/6 recognises transcription-generated positive DNA supercoils. Nat Commun. 2024;15(1):7805. PMCID: PMC11379904

(11) Irwan ID, Bogerd HP, Cullen BR. Epigenetic silencing by the SMC5/6 complex mediates HIV-1 latency. Nat Microbiol. 2022;7(12):2101-13. PMCID: PMC9712108

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Author response:

The following is the authors’ response to the previous reviews

Reviewer #1 (Public Review): 

Summary: 

This paper by Schommartz and colleagues investigates the neural basis of memory reinstatement as a function of both how recently the memory was formed (recent, remote) and its development (children, young adults). The core question is whether memory consolidation processes as well as the specificity of memory reinstatement differ with development. A number of brain regions showed a greater activation difference for recent vs. remote memories at the long versus shorter delay specifically in adults (cerebellum, PHG, LOC). A different set showed decreases in the same comparison, but only in children (precuneus, RSC). The authors also used neural pattern similarity analysis to characterize reinstatement, though still in this revised paper I have substantive concerns about how the analyses were performed. While scene-specific reinstatement decreased for remote memories in both children and adults, claims about its presence cannot be made given the analyses. Gist-level reinstatement was observed in children but not adults, but I also have concerns about this analysis. Broadly, the behavioral and univariate findings are consistent with the idea memory consolidation differs between children and adults in important ways, and takes a step towards characterizing how.

Strengths: 

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

Weaknesses: 

As noted above and in my review of the original submission, the pattern similarity analysis for both item and category-level reinstatement were performed in a way that is not interpretable given concerns about temporal autocorrelation within scanning run.Unfortunately these issues remain of concern in this revision because they were not rectified. Most of my review focuses on this analytic issue, though I also outline additional concerns. 

(1) The pattern similarity analyses are largely uninterpretable due to how they were performed. 

(a) First, the scene-specific reinstatement index: The authors have correlated a neural pattern during a fixation cross (delay period) with a neural pattern associated with viewing a scene as their measure of reinstatement. The main issue with this is that these events always occurred back-to-back in time. As such, the two patterns will be similar due simply to the temporal autocorrelation in the BOLD signal. Because of the issues with temporal autocorrelation within scanning run, it is always recommended to perform such correlations only across different runs. In this case, the authors always correlated patterns extracted from the same run, and which moreover have temporal lags that are perfectly confounded with their comparison of interest (i.e., from Fig 4A, the "scene-specific" comparisons will always be back-to-back, having a very short temporal lag; "set-based" comparisons will be dispersed across the run, and therefore have a much higher lag). The authors' within-run correlation approach also yields correlation values that are extremely high - much higher than would be expected if this analysis was done appropriately. The way to fix this would be to restrict the analysis to only cross-run comparisons, which is not possible given the design. 

To remedy this, in the revision the authors have said they will refrain from making conclusions about the presence of scene-specific reinstatement (i.e., reinstatement above baseline). While this itself is an improvement from the original manuscript, I still have several concerns. First, this was not done thoroughly and at times conclusions/interpretations still seem to imply or assume the presence of scene reinstatement (e.g., line 979-985, "our research supports the presence of scene-specific reinstatement in 5-to-7-year-old children"; line 1138). 

We thank the reviewers for pointing out that there are inconsistencies in our writing. We agree that we cannot make any claims about the baseline level of scene-specific reinstatement. To reiterate, our focus is on the changes in reinstatement over time (30 minutes, 24 hours, and two weeks after learning), which showed a robust decrease. Importantly, scenespecific reinstatement indices for recent items — tested on different days — did not significantly differ, as indicated by non-significant main effects of Session (all p > .323) and Session x ROI interactions (all p > .817) in either age group. This supports our claim that temporal autocorrelation is stable and consistent across conditions and that the observed decline in scene-specific reinstatement reflects a time-dependent change in remote retrieval. We have revised the highlighted passages, accordingly, emphasizing the delay-related decrease in scene-specific reinstatement rather than its absolute magnitude. 

Second, the authors' logic for the neural-behavioural correlations in the PLSC analysis involved restricting to regions that showed significant reinstatement for the gist analysis, which cannot be done for the analogous scene-specific reinstatement analysis. This makes it challenging to directly compare these two analyses since one was restricted to a small subset of regions and only children (gist), while scene reinstatement included both groups and all ROIs. 

We thank the reviewer for pointing this out and want to clarify that it was not our intention to directly compare these analyses. For the neural-behavioral correlations, we included only those regions identified based on gist-like representations baseline, whereas for scene-specific reinstatement, we included all regions due to the absence of such a baseline. The primary aim of the PLSC analysis was to identify a set of regions that, after a stringent permutation and bootstrapping procedure, form a latent variable that explains a significant proportion of variance in behavioral performance across all participants. 

Third, it is also unclear whether children and adults' values should be directly comparable given pattern similarity can be influenced by many factors like motion, among other things. 

We thank the reviewer for raising this important point. In our multivariate analysis, we included confounding regressors specifically addressing motion-related artefacts. Following recent best practices for mitigating motion-related confounding factors in both adult and pediatric fMRI data (Ciric et al., 2017; Esteban et al., 2020; Jones et al., 2021; Satterthwaite et al., 2013), we implemented the most effective motion correction strategies. 

Importantly, our group × session interaction analysis focuses on relative changes in reinstatement over time rather than comparing absolute levels of pattern similarity between children and adults. This approach controls for potential baseline differences and instead examines whether the magnitude of delay-related changes differs across groups. We believe this warrants the comparison and ensures that our conclusions are not driven by group-level differences in baseline similarity or motion artifacts.

My fourth concern with this analysis relates to the lack of regional specificity of the effects. All ROIs tested showed a virtually identical pattern: "Scene-specific reinstatement" decreased across delays, and was greater in children than adults. I believe control analyses are needed to ensure artifacts are not driving these effects. This would greatly strengthen the authors' ability to draw conclusions from the "clean" comparison of day 1 vs. day 14. (A) The authors should present results from a control ROI that should absolutely not show memory reinstatement effects (e.g., white matter?). Results from the control ROI should look very different - should not differ between children and adults, and should not show decreases over time. 

(C) If the same analysis was performed comparing the object cue and immediately following fixation (rather than the fixation and the immediately following scene), the results should look very different. I would argue that this should not be an index of reinstatement at all since it involves something presented visually rather than something reinstated (i.e., the scene picture is not included in this comparison). If this control analysis were to show the same effects as the primary analysis, this would be further evidence that this analysis is uninterpretable and hopelessly confounded. 

We appreciate the reviewer’s suggestion to strengthen the interpretation of our findings by including appropriate control analyses to rule out non-memory-related artifacts. In response, we conducted several control analyses, detailed below, which collectively support the specificity of the observed reinstatement effects. The report of the results is included in the manuscript (line 593-619).

We checked that item reinstatement for incorrectly remembered trial did not show any session-related decline for any ROI. This indicates that the reinstatement for correctly remembered items is memory-related (see Fig. S5 for details). 

We conducted additional analyses on three subregions of the corpus callosum (the body, genu, and splenium). The results of the linear mixed-effects models revealed no significant group effect (all p > .426), indicating no differences between children and adults. In contrast, all three ROIs showed a significant main effect of Session (all p < .001). However, post hoc analyses indicated that this effect was driven by differences between the recent and the Day 14 remote condition. The main contrasts of interest – recent vs. Day 1 remote and Day 1 remote vs. Day 14 remote – were not significant (all p > .080; see Table S10.4), suggesting that, unlike in other ROIs, there was no delay-related decrease in scene-specific reinstatement in these white matter regions.

Then we repeated our analysis using the same procedure but replaced the “scene” time window with the “object” time window. The rationale for this control is that comparing the object cue to the immediately following fixation period should not reflect scene reinstatement, as the object and the reinstated scene rely on distinct neural representations. Accordingly, we did not expect a delay-related decrease in the reinstatement index. Consistent with this expectation, the analysis using the object – fixation similarity index – though also influenced by temporal autocorrelation – did not reveal any significant effect of session or delay in any ROI (all p > .059; see Table S9, S9.1).

Together, these control analyses provide converging evidence that our findings are not driven by global or non-specific signal changes. We believe that these control analyses strengthen our interpretation about delay-related decrease in scene-specific reinstatement index. 

(B) Do the recent items from day 1 vs. day 14 differ? If so, this could suggest something is different about the later scans (and if not, it would be reassuring). 

The recent items tested on day 1 and day14 do not differ (all p. > .323). This effect remains stable across all ROIs.

(b) For the category-based neural reinstatement: (1) This suffers from the same issue of correlations being performed within run. Again, to correct this the authors would need to restrict comparisons to only across runs (i.e., patterns from run 1 correlated with patterns for run 2 and so on). The authors in their response letter have indicated that because the patterns being correlated are not derived from events in close temporal proximity, they should not suffer from the issue of temporal autocorrelation. This is simply not true. For example, see the paper by Prince et al. (eLife 2022; on GLMsingle). This is not the main point of Prince et al.'s paper, but it includes a nice figure that shows that, using standard modelling approaches, the correlation between (same-run) patterns can be artificially elevated for lags as long as ~120 seconds (and can even be artificially reduced after that; Figure 5 from that paper) between events. This would affect many of the comparisons in the present paper. The cleanest way to proceed is to simply drop the within-run comparisons, which I believe the authors can do and yet they have not. Relatedly, in the response letter the authors say they are focusing mainly on the change over time for reinstatement at both levels including the gist-type reinstatement; however, this is not how it is discussed in the paper. They in fact are mainly relying on differences from zero, as children show some "above baseline" reinstatement while adults do not, but I believe there were no significant differences over time (i.e., the findings the authors said they would lean on primarily, as they are arguably the most comparable).  

We thank the reviewer for this important comment regarding the potential inflation of similarity values due to within-run comparisons.

To address the reviewer’s concern, we conducted an additional cross-run analysis for all correctly retrieved trials. The approach restricted comparisons to non-overlapping runs (run1run2, run2-run3, run1-run3). This analysis revealed robust gist-like reinstatement in children for remote Day 14 memories in the mPFC (p = .035) and vlPFC (p = .0007), in adults’ vlPFC remote Day 1 memories (p = .029), as well as in children and adults remote Day 1 memories in LOC (p < .02). A significant Session effect in both regions (mPFC: p = .026; vlPFC: p = .002) indicated increased reinstatement for long delay (Day 14) compared to short-delay and recent session (all p < .05). Given that the cross-run results largely replicate and reinforce the effects found previously with within-run, we believe that combining both sources of information is methodologically justified and statistically beneficial. Specifically, both approaches independently identified significant gist-like reinstatement in children’s mPFC and vlPFC (although within-run vlPFC effect (short delay: p = .038; long delay p = .047) did not survive multiple comparisons), particularly for remote memories. Including both withinrun and between-run comparisons increases the number of unique, non-repeated trial pairs, improving statistical power without introducing redundancy. While we acknowledge that same-run comparisons may be influenced by residual autocorrelation (as shown by Prince et al. 2022, eLife), we believe that our design mitigates this risk through consistency between within-run and cross-run results, long inter-trial intervals, and trial-wise estimation of activation. We have adjusted the manuscript, accordingly, reporting the combined analysis. We also report cross-run and within-run analysis separately in supplementary materials (Tables S12.1, S12.2, showing that they converge with the cross-run results and thus strengthen rather than dilute the findings. 

As suggested, we now explicitly highlight the change over time as the central finding. We observe a clear increase in gist-like reinstatement from recent to remote memories in children, particularly in mPFC and vlPFC. These effects based on combined within- and cross-run comparisons, are now clearly stated in the main results and interpreted in the discussion accordingly. 

(2) This analysis uses a different approach of comparing fixations to one another, rather than fixations to scenes. In their response letter and the revised paper, the authors do provide a bit of reasoning as to why this is the most sensible. However, it is still not clear to me whether this is really "reinstatement" which (in my mind) entails the re-evoking of a neural pattern initially engaged during perception. Rather, could this be a shared neural state that is category specific? 

We thank the reviewer for raising this important conceptual point about whether our findings reflect reinstatement in the classical sense — namely, the reactivation of perceptual neural patterns — or a shared, category-specific state.

While traditional definitions of reinstatement emphasize item-specific reactivation (e.g., Ritchey et al., 2013; Xiao et al., 2017) it is increasingly recognized that memory retrieval can also involve the reactivation of abstracted, generalized, or gist-like representations, especially as memories consolidate. Our analysis follows this view, aimed to capture how memory representations evolve over time, particularly in development.

Several studies support this broader notion of gist-like reinstatement. For instance, Chen et al. (2017) showed that while event-specific patterns were reinstated across the default mode network and medial temporal lobe, inter-subject recall similarity exceeded encodingretrieval similarity, suggesting transformation and abstraction beyond perceptual reinstatement. Zhuang et al. (2021) further showed that loss of neural distinctiveness in the

MTL over time predicted false memories, linking neural similarity to representational instability. This aligns with our finding that greater gist-like reinstatement is associated with lower memory accuracy.

Ye et al. (2020) discuss how memory representations are reshaped post-encoding — becoming more differentiated, integrated, or weakened depending on task goals and neural resources. While their work focuses on adults, our previous findings (Schommartz et al., 2023) suggest that children’s neural systems (the same sample) are structurally immature, making them more likely to rely on gist-based consolidation (see Fandakova et al., 2019). Adults, by contrast, may retain more item-specific traces.

Relatedly, St-Laurent & Buchsbaum (2019) show that with repeated encoding, neural memory representations become increasingly distinct from perception, suggesting that reinstatement need not mimic perception. We agree that reinstatement does not always reflect reactivation of low-level sensory patterns, particularly over long delays or in developing brains.

Finally, while we did not correlate retrieval patterns directly with perceptual encoding patterns, we assessed neural similarity among retrieved items within vs. between categories, based on non-repeated, independently sampled trials. This approach is intended to capture the structure and delay-related transformation of mnemonic representations, especially in terms of how they become more schematic or gist-like over time. Our findings align conceptually with the results of Kuhl et al. (2012), who used MVPA to show that older and newer visual memories can be simultaneously reactivated during retrieval, with greater reactivation of older memories interfering with retrieval accuracy for newer memories. Their work highlights how overlapping category-level representations in ventral temporal cortex can reflect competition among similar memories, even in the absence of item-specific cues. In our developmental context, we interpret the increased neural similarity among category members in children as possibly reflecting such representational overlap or competition, where generalized traces dominate over item-specific ones. This pattern may reflect a shift toward efficient but less precise retrieval, consistent with developmental constraints on memory specificity and consolidation.

In this context, we view our findings as evidence of memory trace reorganization — from differentiated, item-level representations toward more schematic, gist-like neural patterns (Sekeres et al., 2018), particularly in children. Our cross-run analyses further confirm that this is not an artifact of same-run correlations or low-level confounds. We have clarified this distinction and interpretation throughout the revised manuscript (see lines 144-158; 1163-1170).

In any case, I think additional information should be added to the text to clarify that this definition differs from others in the literature. The authors might also consider using some term other than reinstatement. Again (as I noted in my prior review), the finding of no category-level reinstatement in adults is surprising and confusing given prior work and likely has to do with the operationalization of "reinstatement" here. I was not quite sure about the explanation provided in the response letter, as category-level reinstatement is quite widespread in the brain for adults and is robust to differences in analytic procedures etc. 

We agree that our operationalization of "reinstatement" differs from more conventional uses of the term, which typically involve direct comparisons between encoding and retrieval phases, often with item-level specificity. As our analysis is based on similarity among retrieval-phase trials (fixation-based activation patterns) and focuses on within- versus between-category neural similarity, we agree that the term reinstatement may suggest a stronger encoding–retrieval mapping than we are claiming.

To avoid confusion and overstatement, we have revised the terminology throughout the manuscript: we now refer to our measure as “gist-like representations” rather than “gist-like reinstatement.” This change better reflects the nature of our analysis — namely, that we are capturing shared neural patterns among category-consistent memories that may reflect reorganized or abstracted traces, especially after delay and in development.

As the reviewer rightly points out, category-level reinstatement is well documented in adults (e.g., Kuhl & Chun, 2014; Tompary et al., 2020; Tompary & Davachi, 2017). The absence of such effects in our adult group may indeed reflect differences in study design, particularly our use of non-repeated, cross-trial comparisons based on fixation events. It may also reflect different consolidation strategies, with adults preserving more differentiated or item-specific representations, while children form more schematic or generalizable representations — a pattern consistent with our interpretation and supported by prior work (Fandakova et al., 2019; Sekeres et al., 2018) 

We have updated the relevant sections of the manuscript (Results, Discussion (particularly lines 1163- 1184), and Figure captions) to clarify this terminology shift and explicitly contrast our approach with more standard definitions of reinstatement. We hope this revision provides the needed conceptual clarity while preserving the integrity of our developmental findings.

(3) Also from a theoretical standpoint-I'm still a bit confused as to why gist-based reinstatement would involve reinstatement of the scene gist, rather than the object's location (on the screen) gist. Were the locations on the screen similar across scene backgrounds from the same category? It seems like a different way to define memory retrieval here would be to compare the neural patterns when cued to retrieve the same vs. similar (at the "gist" level) vs. different locations across object-scene pairs. This is somewhat related to a point from my review of the initial version of this manuscript, about how scene reinstatement is not necessary. The authors state that participants were instructed to reinstate the scene, but that does not mean they were actually doing it. The point that what is being measured via the reinstatement analyses is actually not necessary to perform the task should be discussed in more detail in the paper. 

We appreciate the reviewer’s thoughtful theoretical question regarding whether our measure of “gist-like representations” might reflect reinstatement of spatial (object-location) gist, rather than scene-level gist. We would like to clarify several key points about our task design and interpretation:

(1) Object locations were deliberately varied and context dependent.

In our stimulus set, each object was embedded in a rich scene context, and the locations were distributed across six distinct possible areas within each scene, with three possible object placements per location. These placements were manually selected to ensure realistic and context-sensitive positioning of objects within the scenes. Importantly, locations were not fixed across scenes within a given category. For example, objects placed in “forest” scenes could appear in different screen locations across different scene exemplars (e.g., one in the bottom-left side, another floating above). Therefore, the task did not introduce a consistent spatial schema across exemplars from the same scene category that could give rise to a “location gist.”

(2) Scene categories provided consistent high-level contextual information.

By contrast, the scene categories (e.g., farming, forest, indoor, etc.) provided semantically coherent and visually rich contextual backgrounds that participants could draw upon during retrieval. This was emphasized in the instruction phase, where participants were explicitly encouraged to recall the whole scene based on the stories they created during learning (not just the object or its position). While we acknowledge that we cannot directly verify the reinstated content, this instruction aligns with prior studies showing that scene and context reinstatement can occur even without direct task relevance (e.g., Kuhl & Chun, 2014; Ritchey et al., 2013).

(3) Our results are unlikely to reflect location-based reinstatement.

If participants had relied on a “location gist” strategy, we would have expected greater neural similarity across scenes with similar spatial layouts, regardless of category. However, our design avoids this confound by deliberately varying locations across exemplars within categories. Additionally, our categorical neural similarity measure contrasted within-category vs. between-category comparisons — making it sensitive to shared contextual or semantic structure, not simply shared screen positions.

Considering this, we believe that the neural similarity observed in the mPFC and vlPFC in children at long delay reflects the emergence of scene-level, gist-like representations, rather than low-level spatial regularities. Nevertheless, we now clarify this point in the manuscript and explicitly discuss the limitation that reinstatement of scene context was encouraged but not required for successful task performance.

Future studies could dissociate spatial and contextual components of reinstatement more directly by using controlled spatial overlap or explicit location recall conditions. However, given the current task structure, location-based generalization is unlikely to account for the category-level similarity patterns we observe.

(2) Inspired by another reviewer's comment, it is unclear to me the extent to which age group differences can be attributed to differences in age/development versus memory strength. I liked the other reviewer's suggestions about how to identify and control for differences in memory strength, which I don't think the authors actually did in the revision. They instead showed evidence that memory strength does seem to be lower in children, which indicates this is an interpretive confound. For example, I liked the reviewer's suggestion of performing analyses on subsets of participants who were actually matched in initial learning/memory performance would have been very informative. As it is, the authors didn't really control for memory strength adequately in my opinion, and as such their conclusions about children vs. adults could have been reframed as people with weak vs. strong memories. This is obviously a big drawback given what the authors want to conclude. Relatedly, I'm not sure the DDM was incorporated as the reviewer was suggesting; at minimum I think the authors need to do more work in the paper to explain what this means and why it is relevant. (I understand putting it in the supplement rather

than the main paper, but I still wanted to know more about what it added from an interpretive perspective.) 

We appreciate the reviewer’s thoughtful concerns regarding potential confounding effects of memory strength on the observed age group differences. This is indeed a critical issue when interpreting developmental findings.

While we agree that memory strength differs between children and adults — and our own DDM-based analysis confirms this, mirroring differences observed in accuracy — we would like to emphasize that these differences are not incidental but rather reflect developmental changes in the underlying memory system. Given the known maturation of both structural and functional memory-related brain regions, particularly the hippocampus and prefrontal cortex, we believe it would be theoretically inappropriate to control for memory strength entirely, as doing so would remove variance that is central to the age-related neural effects we aim to understand.

To address the reviewer's concern empirically, we conducted an additional control analysis in which we subsampled children to include only those who reached learning criterion after two cycles (N = 28 out of 49 children, see Table S1.1, S1.2, Figure S1, Table S9.1), thereby selecting a high-performing subgroup. Importantly, this subsample replicated behavioral and neural results to the full group. This further suggests that the observed age group differences are not merely driven by differences in memory strength.

As abovementioned, the results of the DDM support our behavioral findings, showing that children have lower drift rates for evidence accumulation, consistent with weaker or less accessible memory representations. While these results are reported in the Supplementary Materials (section S2.1, Figure S2, Table S2), we agree that their interpretive relevance should be more clearly explained in the main text. We have therefore updated the Discussion section to explicitly state how the DDM results provide converging evidence for our interpretation that developmental differences in memory quality — not merely strategy or task performance — underlie the observed neural differences (see lines 904-926).

In sum, we view memory strength not as a confound to be removed, but as a meaningful and theoretically relevant factor in understanding the emergence of gist-like representations in children. We have clarified this interpretive stance in the revised manuscript and now discuss the role of memory strength more explicitly in the Discussion.

(3) Some of the univariate results reporting is a bit strange, as they are relying upon differences between retrieval of 1- vs. 14-day memories in terms of the recent vs. remote difference, and yet don't report whether the regions are differently active for recent and remote retrieval. For example in Figure 3A, neither anterior nor posterior hippocampus seem to be differentially active for recent vs. remote memories for either age group (i.e., all data is around 0). Precuneus also interestingly seems to show numerically recent>remote (values mostly negative), whereas most other regions show the opposite. This difference from zero (in either direction) or lack thereof seems important to the message. In response to this comment on the original manuscript, the authors seem to have confirmed that hippocampal activity was greater during retrieval than implicit baseline. But this was not really my question - I was asking whether hippocampus is (and other ROIs in this same figure are) differently engaged for recent vs. remote memories.

We thank the reviewer for bringing up this important point. Our previous analysis showed that both anterior and posterior regions of the hippocampus, anterior parahippocampal gyrus and precuneus exhibited significant activation from zero in children and adults for correctly remembered items (see Fig. S2, Table S7 in Supplementary Materials). Based on your suggestion, our additional analysis showed: 

(i) The linear mixed-effects model for correctly remembered items showed no significant interaction effects (group x session x memory age (recent, remote)) for the anterior hippocampus (all p > .146; see Table S7.1).

(ii) For the posterior hippocampus, we observed a significant main effect of group (F(1,85),   = 5.62, p = .038), showing significantly lower activation in children compared to adults (b = .03, t = -2.34, p = .021). No other main or interaction effects were significant (all p > .08; see Table S7.1).

(iii) For the anterior PHG, that also showed no significant remote > recent difference, the model showed that there was indeed no difference between remote and recent items across age groups and delays (all p > .194; Table S7.1). 

Moreover, when comparing recent and remote hippocampal activation directly, there were no significant differences in either group (all FDR-adjusted p > .116; Table S7.2), supporting the conclusion that hippocampal involvement was stable across delays for successfully retrieved items. 

In contrast, analysis of unsuccessfully remembered items showed that hippocampal activation was not significantly different from zero in either group (all FDR-adjusted p > .052; Fig. S2.1, Table S7.1), indicating that hippocampal engagement was specific to successful memory retrieval.

To formally test whether hippocampal activation differs between remembered and forgotten items, we ran a linear mixed-effects model with Group, Memory Success (remembered vs. forgotten), and ROI (anterior vs. posterior hippocampus) as fixed effects. This model revealed a robust main effect of memory success (F(1,1198) = 128.27, p < .001), showing that hippocampal activity was significantly higher for remembered compared to forgotten items (b = .06, t(1207) = 11.29, p < .001; Table S7.3). 

As the reviewer noted, precuneus activation was numerically higher for recent vs. remote items, and this was confirmed in our analysis. While both recent and remote retrieval elicited significantly above-zero activation in the precuneus (Table S7.2), activation for recent items was significantly higher than for remote items, consistent across both age groups.

Taken together, these analyses support the conclusion that hippocampal involvement in successful retrieval is sustained across delays, while other ROIs such as the precuneus may show greater engagement for more recent memories. We have now updated the manuscript text ( lines 370-390) and supplementary materials to reflect these findings more clearly, as well as to clarify the distinction between activation relative to baseline and memory-agerelated modulation.

(4) Related to point 3, the claims about hippocampus with respect to multiple trace theory feel very unsupported by the data. I believe the authors want to conclude that children's memory retrieval shows reliance on hippocampus irrespective of delay, presumably because this is a detailed memory task. However the authors have not really shown this; all they have shown is that hippocampal involvement (whatever it is) does not vary by delay. But we do not have compelling evidence that the hippocampus is involved in this task at all. That hippocampus is more active during retrieval than implicit baseline is a very low bar and does not necessarily indicate a role in memory retrieval. If the authors want to make this claim, more data are needed (e.g., showing that hippocampal activity during retrieval is higher when the upcoming memory retrieval is successful vs. unsuccessful). In the absence of this, I think all the claims about multiple trace theory supporting retrieval similarly across delays and that this is operational in children are inappropriate and should be removed. 

We thank the reviewer for pointing this out. We agree that additional analysis of hippocampal activity during successful and unsuccessful memory retrieval is warranted. This will provide stronger support for our claim that strong, detailed memories during retrieval rely on the hippocampus in both children and adults. Our previously presented results on the remote > recent univariate signal difference in the hippocampus (p. 14-18; lines 433-376, Fig. 3A) show that this difference does not vary between children and adults, or between Day 1 and Day 14. Our further analysis showed that both anterior and posterior regions of the hippocampus exhibited significant activation from zero in children and adults for correctly remembered items (see Fig. S2, Table S7 in Supplementary Materials). Based on your suggestion, our recent additional analysis showed:

(i) For forgotten items, we did not observe any activation significantly higher than zero in either the anterior or posterior hippocampus for recent and remote memory on Day 1 and Day 14 in either age group (all p > .052 FDR corrected; see Table S7.1, Fig. S2.1).

(ii) After establishing no difference between recent and remote activation across and between sessions (Day 1, Day 14), we conducted another linear mixed-effects model with group x memory success (remembered, forgotten) x region (anterior hippocampus, posterior hippocampus), with subject as a random effect. The model showed no significant effects for the memory success x region interaction (F = 1.12(1,1198), p = .289) and no significant group x memory success x region interaction (F = .017(1,1198), p = .895). However, we observed a significant main effect of memory success (F = 128.27(1,1198), p < .001), indicating significantly higher hippocampal activation for remembered compared to forgotten items (b = .06, t = 11.29, p <.001; see Table S7.3).

(iii) Considering the comparatively low number of incorrect trials for recent items in the adult group, we reran this analysis only for remote items. Similarly, the model showed no significant effects for the memory success x region interaction (F = .72(1,555), p = .398) and no significant group x memory success x region interaction (F = .14(1,555), p = .705). However, we observed a significant main effect of memory success (F = 68.03(1,555), p < .001), indicating significantly higher hippocampal activation for remote remembered compared to forgotten items (b = .07, t = 8.20, p <.001; see Table S7.3).

Taken together, our results indicate that significant hippocampal activation was observed only for correctly remembered items in both children and adults, regardless of memory age and session. For forgotten items, we did not observe any significant hippocampal activation in either group or delay. Moreover, hippocampal activation was significantly higher for remembered compared to forgotten memories. This evidence supports our conclusions regarding the Multiple Trace and Trace Transformation Theories, suggesting that the hippocampus supports retrieval similarly across delays, and provides novel evidence that this process is operational in both children and adults. This aligns also with Contextual Bindings Theory, as well as empirical evidence by Sekeres, Winokur, & Moscovitch (2018), among others. We have added this information to the manuscript.

(5) There are still not enough methodological details in the main paper to make sense of the results. Some of these problems were addressed in the revision but others remain. For example, a couple of things that were unclear: that initially learned locations were split, where half were tested again at day 1 and the other half at day 14; what specific criterion was used to determine to pick the 'well-learned' associations that were used for comparisons at different delay periods (object-scene pairs that participants remembered accurately in the last repetition of learning? Or across all of learning?). 

We thank the reviewer for pointing this out. The initially learned object-scene associations on Day 0 were split in two halves based on  their categories before the testing. Specifically, half of the pairs from the first set and half of the pairs from the second set of 30 object-scene associations were used to create the set 30 remote pair for Day 1 testing. A similar procedure was repeated for the remaining pairs to create a set of remote object-scene associations for Day 14 retrieval. We tried to equally distribute the categories of pairs between the testing sets. We added this information to the methods section of the manuscript (see p. 47, lines 12371243). In addition, the sets of association for delay test on Day 1 and Day 14 were not based on their learning accuracy. Of note, the analysis of variance revealed that there was no difference in learning accuracy between the two sets created for delay tests in either age group (children: p = .23; adults  p = .06). These results indicate that the sets were comprised of items learned with comparable accuracy in both age groups. 

(6) In still find the revised Introduction a bit unclear. I appreciated the added descriptions of different theories of consolidation, though the order of presented points is still a bit hard to follow. Some of the predictions I also find a bit confusing as laid out in the introduction. (1) As noted in the paper multiple trace theory predicts that hippocampal involvement will remain high provided memories retained are sufficiently high detail. The authors however also predict that children will rely more on gist (than detailed) memories than adults, which would seem to imply (combined with the MTT idea) that they should show reduced hippocampal involvement over time (while in adults, it should remain high). However, the authors' actual prediction is that hippocampus will show stable involvement over time in both kids and adults. I'm having a hard time reconciling these points. (2) With respect to the extraction of gist in children, I was confused by the link to Fuzzy Trace Theory given the children in the present study are a bit young to be showing the kind of gist extraction shown in the Brainerd & Reyna data. Would 5-7 year olds not be more likely to show reliance on verbatim traces under that framework? Also from a phrasing perspective, I was confused about whether gist-like information was something different from just gist in this sentence: "children may be more inclined to extract gist information at the expense of detailed or gist-like information." (p. 8) - is this a typo? 

We thank the reviewer for this thoughtful observation. 

Our hypothesis of stable hippocampal engagement over time was primarily based on Contextual Binding Theory (Yonelinas et al., 2019), and the MTT, supported by the evidence provided by Sekeres et al., 2018, which posits that the hippocampus continues to support retrieval when contextual information is preserved, even for older, consolidated memories. Given that our object-location associations were repeatedly encoded and tied to specific scene contexts, we believe that retrieval success for both recent and remote memories likely involved contextual reinstatement, leading to sustained hippocampal activity. Also in accordance with the MTT and related TTT, different memory representations may coexist, including detailed and gist-like memories. Therefore, we suggest that children may not rely on highly detailed item-specific memory, but rather on sufficiently contextualized schematic traces, which still engage the hippocampus. This distinction is now made clearer in the Introduction (see lines 223-236).

We appreciate the reviewer’s point regarding Fuzzy Trace Theory (Brainerd & Reyna, 2002). Indeed, in classic FTT, young children are thought to rely more on verbatim traces due to immature gist extraction mechanisms (primarily from verbal material). However, we use the term “gist-like representations” to refer to schematic or category-level retrieval that emerges through structured, repeated learning (as in our task). This form of abstraction may not require full semantic gist extraction in the FTT sense but may instead reflect consolidation-driven convergence onto shared category-level representations — especially when strategic resources are limited. We now clarify this distinction and revise the ambiguous sentence with typo (“at the expense of detailed or gist-like information”) to better reflect our intended meaning (see p.8).

(7) For the PLSC, if I understand this correctly, the profiles were defined for showing associations with behaviour across age groups. (1) As such, is it not "double dipping" to then show that there is an association between brain profile and behaviour-must this not be true by definition? If I am mistaken, it might be helpful to clarify this in the paper. (2) In addition, I believe for the univariate and scene-specific reinstatement analyses these profiles were defined across both age groups. I assume this doesn't allow for separate definition of profiles across the two group (i.e., a kind of "interaction"). If this is the case, it makes sense that there would not be big age differences... the profiles were defined for showing an association across all subjects. If the authors wanted to identify distinct profiles in children and adults they may need to run another analysis. 

We thank the reviewer for this thoughtful comment. 

(1) We agree that showing the correlation between the latent variable and behavior may be redundant, as the relationship is already embedded in the PLSC solution and quantified by the explained variance. Our intention was merely to visualize the strength of this relationship. In hindsight, we agree that this could be misinterpreted, and we have removed the additional correlation figure from the manuscript.

We also see the reviewer’s point that, given the shared latent profile across groups, it is expected that the strength of the brain-behavior relationship does not differ between age groups. Instead, to investigate group differences more appropriately, we examined whether children and adults differed in their expression of the shared latent variable (i.e., brain scores). This analysis revealed that children showed significantly lower brain scores than adults both in short delay, t(83) = -4.227, p = .0001, and long delay, t(74) = -5.653, p < .001, suggesting that while the brain-behavior profile is shared, its expression varies by group. We have added this clarification to the Results section (p. 19-20) of the revised manuscript. 

(2) Regarding the second point, we agree with the reviewer that defining the PLS profiles across both age groups inherently limits the ability to detect group-specific association, as the resulting latent variables represent shared pattern across the full sample. To address this, we conducted additional PLS analyses separately within each age group to examine whether distinct neural upregulation profiles (remote > recent) emerge for short and long delay conditions.

These within-group analyses, however, were based on smaller subsamples, which reduced statistical power, especially when using bootstrapping to assess the stability of the profiles. For the short delay, although some regions reached significance, the overall latent variables did not reach conventional thresholds for stability (all p > .069), indicating that the profiles were not robust. This suggests that within-group PLS analyses may be underpowered to detect subtle effects, particularly when modelling neural upregulation (remote > recent), which may be inherently small.

Nonetheless, when we exploratively applied PLSC separately within each group using recent and remote activity levels against the implicit baseline (rather than the contrast remote > recent) and its relation to memory performance, we observed significant and stable latent variables in both children and adults. This implies that such contrasts (vs. baseline) may be more sensitive and better suited to detect meaningful brain–behavior relationships within age groups. We have added this clarification to the Results sections of the manuscript to highlight the limitations of within-group contrasts for neural upregulation. 

Author response image 1.

(3) Also, as for differences between short delay brain profile and long delay brain profile for the scene-specific reinstatement - there are 2 regions that become significant at long delay that were not significant at a short delay (PC, and CE). However, given there are ceiling effects in behaviour at the short but not long delay, it's unclear if this is a meaningful difference or just a difference in sensitivity. Is there a way to test whether the profiles are statistically different from one another?

We thank the reviewer for this comment. To better illustrate differential profiles also for high memory accuracy after immediate delay (30 minutes delay), we added the immediate (30 minutes delay) condition as a third reference point, given the availability of scene-specific reinstatement data at this time point. Interestingly, the immediate reinstatement profile revealed a different set of significant regions, with distinct expression patterns compared to both the short and long delay conditions. This supports the view that scene-specific reinstatement is not static but dynamically reorganized over time.

Regarding the ceiling effect at short delay, we acknowledge this as a potential limitation. However, we note that our primary analyses were conducted across both age groups combined, and not solely within high-performing individuals. As such, the grouping may mitigate concerns that ceiling-level performance in a subset of participants unduly influenced the overall reinstatement profile. Moreover, we observed variation in neural reinstatement despite ceiling-level behavior, suggesting that the neural signal retains sensitivity to consolidation-related processes even when behavioral accuracy is near-perfect.

While we agree that formal statistical comparisons of reinstatement profiles across delays (e.g., using representational profile similarity or interaction tests) could be an informative direction, we feel that this goes beyond the scope of the current manuscript. 

(4) As I mentioned above, it also was not ideal in my opinion that all regions were included for the scene-specific reinstatement due to the authors' inability to have an appropriate baseline and therefore define above-chance reinstatement. It makes these findings really challenging to compare with the gist reinstatement ones. 

We appreciate the reviewer’s comment and agree that the lack of a clearly defined baseline for scene-specific reinstatement limits our ability to determine whether these values reflect above-chance reinstatement. However, we would like to clarify that we do not directly compare the magnitude of scene-specific reinstatement to that of gist-like reinstatement in our analyses or interpretations. These two analyses serve complementary purposes: the scenespecific analysis captures trial-unique similarity (within-item reinstatement), while the gistlike analysis captures category-level representational structure (across items). Because they differ not only in baseline assumptions but also in analytical scope and theoretical interpretation, our goal was not to compare them directly, but rather to explore distinct but co-existing representational formats that may evolve differently across development and delay.

(8) I would encourage the authors to be specific about whether they are measuring/talking about memory representations versus reinstatement, unless they think these are the same thing (in which case some explanation as to why would be helpful). For example, especially under the Fuzzy Trace framework, couldn't someone maintain both verbatim and gist traces of a memory yet rely more on one when making a memory decision? 

We thank the reviewer for pointing out the importance of conceptual clarity when referring to memory representations versus reinstatement. We agree that these are distinct but related concepts: in our framework, memory representations refer to the neural content stored as a result of encoding and consolidation, whereas reinstatement refers to the reactivation of those representations during retrieval. Thus, reinstatement serves as a proxy for the underlying memory representation — it is how we measure or infer the nature (e.g., specificity, abstraction) of the stored content.

Under Fuzzy Trace Theory, it is indeed possible for both verbatim and gist representations to coexist. Our interpretation is not that children lack verbatim traces, but rather that they are more likely to rely on schematic or gist-like representations during retrieval, especially after a delay. Our use of neural pattern similarity (reinstatement) reflects which type of representation is being accessed, not necessarily which traces exist in parallel.

To avoid ambiguity, we have revised the manuscript to more explicitly distinguish between reinstatement (neural reactivation) and the representational format (verbatim vs. gist-like), especially in the framing of our hypotheses and interpretation of age group differences.

(9) With respect to the learning criteria - it is misleading to say that "children needed between two to four learning-retrieval cycles to reach the criterion of 83% correct responses" (p. 9). Four was the maximum, and looking at the Figure 1C data it appears as though there were at least a few children who did not meet the 83% minimum. I believe they were included in the analysis anyway? Please clarify. Was there any minimum imposed for inclusion?

We thank the reviewer for pointing this out. As stated in Methods Section (p. 50, lines 13261338) “These cycles ranged from a minimum of two to a maximum of four.<…> The cycles ended when participants provided correct responses to 83% of the trials or after the fourth cycle was reached.” We have corrected the corresponding wording in the Results section (line 286-289) to reflect this more accurately. Indeed, five children did not reach the 83% criterion but achieved final performance between 70 and 80% after the fourth learning cycle. These participants were included in this analysis for two main reasons:

(1) The 83% threshold was established during piloting as a guideline for how many learningretrieval cycles to allow, not a strict learning criterion. It served to standardize task continuation, rather than to exclude participants post hoc.

(2) The performance of these five children was still well above chance level (33%), indicating meaningful learning. Excluding them would have biased the sample toward higherperforming children and reduced the ecological validity of our findings. Including them ensures a more representative view of children’s performance under extended learning conditions.

(10) For the gist-like reinstatement PLSC analysis, results are really similar a short and long delays and yet some of the text seems to implying specificity to the long delay. One is a trend and one is significant (p. 31), but surely these two associations would not be statistically different from one another?  

We agree with the reviewer that the associations at short and long delays appeared similar. While a formal comparison (e.g., using a Z-test for dependent correlations) would typically be warranted, in the reanalyzed dataset only the long delay profile remains statistically significant, which limits the interpretability of such a comparison. 

(11) As a general comment, I had a hard time tying all of the (many) results together. For example adults show more mature neocortical consolidation-related engagement, which the authors say is going to create more durable detailed memories, but under multiple trace theory we would generally think of neocortical representations as providing more schematic information. If the authors could try to make more connections across the different neural analyses, as well as tie the neural findings in more closely with the behaviour & back to the theoretical frameworks, that would be really helpful.  

We thank the reviewer for this valuable suggestion. We have revised the discussion section to more clearly link the behavioral and neural findings and to interpret them in light of existing consolidation theories for better clarity. 

Reviewer #2 (Public Review): 

Schommartz et al. present a manuscript characterizing neural signatures of reinstatement during cued retrieval of middle-aged children compared to adults. The authors utilize a paradigm where participants learn the spatial location of semantically related item-scene memoranda which they retrieve after short or long delays. The paradigm is especially strong as the authors include novel memoranda at each delayed time point to make comparisons across new and old learning. In brief, the authors find that children show more forgetting than adults, and adults show greater engagement of cortical networks after longer delays as well as stronger item-specific reinstatement. Interestingly, children show more category-based reinstatement, however, evidence supports that this marker may be maladaptive for retrieving episodic details. The question is extremely timely both given the boom in neurocognitive research on the neural development of memory, and the dearth of research on consolidation in this age group. Also, the results provide novel insights into why consolidation processes may be disrupted in children. 

We thank the reviewer for the positive evaluation.

Comments on the revised version: 

I carefully reviewed not only the responses to my own reviews as well as those raised by the other reviewers. While they addressed some of the concerns raised in the process, I think many substantive concerns remain. 

Regarding Reviewer 1: 

The authors point that the retrieval procedure is the same over time and similarly influenced by temporal autocorrelations, which makes their analysis okay. However, there is a fundamental problem as to whether they are actually measuring reinstatement or they are only measuring differences in temporal autocorrelation (or some non-linear combination of both). The authors further argue that the stimuli are being processed more memory wise rather than perception wise, however, I think there is no evidence for that and that perception-memory processes should be considered on a continuum rather than as discrete processes. Thus, I agree with reviewer 1 that these analyses should be removed. 

We thank the reviewer for raising this important question. We would like to clarify a few key points regarding temporal autocorrelation and reinstatement.

During the fixation window, participants were instructed to reinstate the scene and location associated with the cued object from memory. This task was familiar to them, as they had been trained in retrieving locations within scenes. Our analysis aims to compare the neural representations during this retrieval phase with those when participants view the scene, in order to assess how these representations change in similarity over time, as memories become less precise.

We acknowledge that temporal proximity can lead to temporal autocorrelation. However, evidence suggests that temporal autocorrelation is consistent and stable across conditions (Gautama & Van Hulle, 2004; Woolrich et al., 2004). Shinn & Lagalwar (2021)further demonstrated that temporal autocorrelation is highly reliable at both the subject and regional levels. Given that we analyze regions of interest (ROIs) separately, potential spatial variability in temporal autocorrelation is not a major concern.

No difference between item-specific reinstatement for recent items on day 1 and day 14 (which were merged) for further delay-related comparison also suggests that the reinstatement measure was stable for recent items even sampled at two different testing days. 

Importantly, we interpret the relative change in the reinstatement index rather than its absolute value.

In addition, when we conducted the same analysis for incorrectly retrieved memories, we did not observe any delay-related decline in reinstatement (see p. 25, lines 623-627). This suggests that the delay-related changes in reinstatement are specific to correctly retrieved memories. 

Finally, our control analysis examining reinstatement between object and fixation time points (as suggested by Reviewer 1) revealed no delay-related effects in any ROI (see p.24, lines 605-612), further highlighting the specificity of the observed delay-related change in item reinstatement.

We emphasize that temporal autocorrelation should be similar across all retrieval delays due to the identical task design and structure. Therefore, any observed decrease in reinstatement with increasing delay likely reflects a genuine change in the reinstatement index, rather than differences in temporal autocorrelation. Since our analysis includes only correctly retrieved items, and there is no perceptual input during the fixation window, this process is inherently memory-based, relying on mnemonic retrieval rather than sensory processing.

We respectfully disagree with the reviewer's assertion that retrieval during the fixation period cannot be considered more memory-driven than perception-driven. At this time point, participants had no access to actual images of the scene, making it necessary for them to rely on mnemonic retrieval. The object cue likely triggered pattern completion for the learned object-scene association, forming a unique memory if remembered correctly(Horner & Burgess, 2013). This process is inherently mnemonic, as it is based on reconstructing the original neural representation of the scene (Kuhl et al., 2012; Staresina et al., 2013).

While perception and memory processes can indeed be viewed as a continuum, some cognitive processes are predominantly memory-based, involving reconstruction rather than reproduction of previous experiences (Bartlett, 1932; Ranganath & Ritchey, 2012). In our task, although the retrieved material is based on previously encoded visual information, the process of recalling this information during the fixation period is fundamentally mnemonic, as it does not involve visual input. Our findings indicate that the similarity between memorybased representations and those observed during actual perception decreases over time, suggesting a relative change in the quality of the representations. However, this does not imply that detailed representations disappear; they may still be robust enough to support correct memory recall. Previous studies examining encoding-retrieval similarity have shown similar findings(Pacheco Estefan et al., 2019; Ritchey et al., 2013).

We do not claim that perception and memory processes are entirely discrete, nor do we suggest that only perception is involved when participants see the scene. Viewing the scene indeed involves recognition processes, updating retrieved representations from the fixation period, and potentially completing missing or unclear information. This integrative process demonstrates the interrelation of perception and memory, especially in complex tasks like the one we employed.

In conclusion, our task design and analysis support the interpretation that the fixation period is primarily characterized by mnemonic retrieval, facilitated by cue-triggered pattern completion, rather than perceptual processing. We believe this approach aligns with the current understanding of memory retrieval processes as supported by the existing literature.

The authors seem to have a design that would allow for across run comparisons, however, they did not include these additional analyses. 

Thank you for pointing this out. We ran as additional cross-run comparison. This results and further proceeding are reported in the comment for reviewer 1. 

To address the reviewer’s concern, we conducted an additional cross-run analysis for all correctly retrieved trials. The approach restricted comparisons to non-overlapping runs (run1run2, run2-run3, run1-run3). This analysis revealed robust gist-like reinstatement in children for remote Day 14 memories in the mPFC (p = .035) and vlPFC (p = .0007), in adults’ vlPFC remote Day 1 memories (p = .029), as well as in children and adults remote Day 1 memories in LOC (p < .02). A significant Session effect in both regions (mPFC: p = .026; vlPFC: p = .002) indicated increased reinstatement for long delay (Day 14) compared to short-delay and recent session (all p < .05). Given that the cross-run results largely replicate and reinforce the effects found previously with within-run, we believe that combining both sources of information is methodologically justified and statistically beneficial. Specifically, both approaches independently identified significant gist-like reinstatement in children’s mPFC and vlPFC (although within-run vlPFC effect (short delay: p = .038; long delay p = .047) did not survive multiple comparisons), particularly for remote memories. Including both withinrun and between-run comparisons increases the number of unique, non-repeated trial pairs, improving statistical power without introducing redundancy. While we acknowledge that same-run comparisons may be influenced by residual autocorrelation(Prince et al., 2022), we believe that our design mitigates this risk through consistency between within-run and crossrun results, long inter-trial intervals, and trial-wise estimation of activation. We have adjusted the manuscript, accordingly, reporting the combined analysis. We also report cross-run and within-run analysis separately in supplementary materials (Tables S12.1, S12.2, showing that they converge with the cross-run results and thus strengthen rather than dilute the findings. 

As suggested, we now explicitly highlight the change over time as the central finding. We observe a clear increase in gist-like reinstatement from recent to remote memories in children, particularly in mPFC and vlPFC. These effects based on combined within- and cross-run comparisons, are now clearly stated in the main results and interpreted in the discussion accordingly. 

(1) The authors did not satisfy my concerns about different amounts of re-exposures to stimuli as a function of age, which introduces a serious confound in the interpretation of the neural data. 

(2) Regarding Reviewer 1's point about different number of trials being entered into analysis, I think a more formal test of sub-sampling the adult trials is warranted. 

(1) We thank the reviewer for pointing this out. Overall, children needed 2 to 4 learning cycles to improve their performance and reach the learning criteria, compared to 2 learning cycles in adults. To address the different amounts of re-exposure to stimuli between the age groups, we subsampled the child group to only those children who reached the learning criteria after 2 learning cycles. For this purpose, we excluded 21 children from the analysis who needed 3 or 4 learning cycles. This resulted in 39 young adults and 28 children being included in the subsequent analysis. 

(i) We reran the behavioral analysis with the subsampled dataset (see Supplementary Materials,  Table S1.1, Fig. S1, Table S1.2). This analysis replicated the previous findings of less robust memory consolidation in children across all time delays. 

(ii) We reran the univariate analysis (see in Supplementary Materials, Table S9.1). This analysis also replicated fully the previous findings. This indicates that the inclusion of child participants with greater material exposure during learning in the analysis of neural retrieval patterns did not affect the group differences in univariate neural results. 

These subsampled results demonstrated that the amount of re-exposure to stimuli during encoding does not affect consolidation-related changes in memory retrieval at the behavioral and neural levels in children and adults across all time delays. We have added this information to the manuscript (line 343-348, 420-425). 

(2) We appreciate Reviewer 1's suggestion to perform a formal test by sub-sampling the adult trials to match the number of trials in the child group. However, we believe that this approach may not be optimal for the following reasons:

(i) Loss of Statistical Power: Sub-sampling the adult trials would result in a reduced sample size, potentially leading to a significant loss of statistical power and the ability to detect meaningful effects, particularly in a context where the adult group is intended to serve as a robust control or comparison group.

(ii) Introducing sub-sampling could introduce variability that complicates the interpretation of results, particularly if the trial sub-sampling process does not fully capture the variability inherent in the original adult data.

(iii) Robustness of Existing Findings: We have already addressed potential concerns about unequal trial numbers by conducting analyses that control for the number of learning cycles, as detailed in our supplementary materials. These analyses have shown that the observed effects are consistent, suggesting that the differences in trial numbers do not critically influence our findings.

Given these considerations, we hope the reviewer understands our rationale and agrees that the current analysis is robust and appropriate for addressing the research questions.

I also still fundamentally disagree with the use of global signals when comparing children to adults, and think this could very much skew the results. 

We thank the reviewer for raising this important issue. To address this concern comprehensively, we have taken the following steps:

(1) Overview of the literature support for global signal regression (GSR). A growing body of methodological and empirical research supports the inclusion of global signal repression as part of best practice denoising pipelines, particularly when analyzing pediatric fMRI data. Studies such as (Ciric et al., 2017; Parkes et al., 2018; J. D. Power et al., 2012, 2014; Power et al., 2012), and (Thompson et al., 2016) show that  GSR improves motion-related artifact removal. Critically, pediatric-specific studies (Disselhoff et al., 2025; Graff et al., 2022) conclude that pipelines including GSR are most effective for signal recovery and artifact removal in younger children. Graff et al. (2021) demonstrated that among various pipelines, GSR yielded the best noise reduction in 4–8-year-olds. Additionally, (Li et al., 2019; Qing et al., 2015) emphasized that GSR reduces artifactual variance without distorting the spatial structure of neural signals. (Ofoghi et al., 2021)demonstrated that global signal regression helps mitigate non-neuronal noise sources, including respiration, cardiac activity, motion, vasodilation, and scanner-related artifacts. Based on this and other recent findings, we consider GSR particularly beneficial for denoising paediatric  fMRI data in our study.

(2) Empirical comparison of pipelines with and without GSR. We re-run the entire first-level univariate analysis using the pipeline that excluded the global signal regression. The resulting activation maps (see Supplementary Figure S3.2, S4.2, S5.2, S9.2) differed notably from the original pipeline. Specifically, group differences in cortical regions such as mPFC, cerebellum, and posterior PHG no longer reached significance, and the overall pattern of results appeared noisier. 

(3) Evaluation of the pipeline differences. To further evaluate the impact of GSR, we conducted the following analyses:

(a) Global signal is stable across groups and sessions. A linear mixed-effects model showed no significant main effects or interactions involving group or session on the global signal (F-values < 2.62, p > .11), suggesting that the global signal was not group- or session-dependent in our sample. 

(b) Noise Reduction Assessment via Contrast Variability. We compared the variability (standard deviation and IQR) of contrast estimates across pipelines. Both SD (b = .070, p < .001) and IQR (b = .087, p < .001) were significantly reduced in the GSR pipeline, especially in children (p < .001) compared to adults (p = .048). This suggests that GSR reduces inter-subject variability in children, likely reflecting improved signal quality.

(c) Residual Variability After Regressing Global Signal. We regressed out global signal post hoc from both pipelines and compared the residual variance. Residual standard deviation was significantly lower for the GSR pipeline (F = 199, p < .001), with no interaction with session or group, further indicating that GSR stabilizes the signal and attenuates non-neuronal variability.

Conclusion

In summary, while we understand the reviewer’s concern, we believe the empirical and theoretical support for GSR, especially in pediatric samples, justifies its use in our study. Nonetheless, to ensure full transparency, we provide full results from both pipelines in the Supplementary Materials and have clarified our reasoning in the revised manuscript.

Reviewer #1 (Recommendations For The Authors): 

(1) Some figures are still missing descriptions of what everything on the graph means; please clarify in captions. 

We thank the reviewer for pointing this out. We undertook the necessary adjustments in the graph annotations. 

(2) The authors conclude they showed evidence of neural reorganization of memory representations in children (p. 41). But the gist is not greater in children than adults, and also does not differ over time-so, I was confused about what this claim was based on? 

We thank the reviewer for raising this question. Our results on gist-like reinstatements suggest that gist-like reinstatement was significantly higher in children compared to adults in the mPFC in addition to the child gist-like reinstatement indices being significantly higher than zero (see p.27-28). These results support our claim on neural reorganization of memory represenations in children. We hope this clarifies the issue. 

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