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Author response:

Reviewer #1 (Public review):

Summary:

This work by Govorunova et al. identified three naturally blue-shifted channelrhodopsins (ChRs) from ancyromonads, namely AnsACR, FtACR, and NlCCR. The phylogenetic analysis places the ancyromonad ChRs in a distinct branch, highlighting their unique evolutionary origin and potential for novel applications in optogenetics. Further characterization revealed the spectral sensitivity, ionic selectivity, and kinetics of the newly discovered AnsACR, FtACR, and NlCCR. This study also offers valuable insights into the molecular mechanism underlying the function of these ChRs, including the roles of specific residues in the retinal-binding pocket. Finally, this study validated the functionality of these ChRs in both mouse brain slices (for AnsACR and FtACR) and in vivo in Caenorhabditis elegans (for AnsACR), demonstrating the versatility of these tools across different experimental systems.

In summary, this work provides a potentially valuable addition to the optogenetic toolkit by identifying and characterizing novel blue-shifted ChRs with unique properties.

Strengths:

This study provides a thorough characterization of the biophysical properties of the ChRs and demonstrates the versatility of these tools in different ex vivo and in vivo experimental systems. The mutagenesis experiments also revealed the roles of key residues in the photoactive site that can affect the spectral and kinetic properties of the channel.

We thank the Reviewer for his/her positive evaluation of our work.

Weaknesses:

While the novel ChRs identified in this work are spectrally blue-shifted, there still seems to be some spectral overlap with other optogenetic tools. The authors should provide more evidence to support the claim that they can be used for multiplex optogenetics and help potential end-users assess if they can be used together with other commonly applied ChRs. Additionally, further engineering or combination with other tools may be required to achieve truly orthogonal control in multiplexed experiments.

To demonstrate the usefulness of ancyromonad ChRs for multiplex optogenetics as a proof of principle, we co-expressed AnsACR with the red-shifted cation-conducting ChR Chrimson and measured net photocurrent generated by this combination as a function of the wavelength. We found that it is hyperpolarizing in the blue region of the spectrum, and depolarizing at the red region. In the revision, we added a new panel (Figure 1D) showing these results and the following paragraph to the main text:

“To test the possibility of using AnsACR in multiplex optogenetics, we co-expressed it with the red-shifted CCR Chrimson (Klapoetke et al., 2014) fused to an EYFP tag in HEK293 cells. We measured the action spectrum of the net photocurrents with 4 mM Cl^- in the pipette, matching the conditions in the neuronal cytoplasm (Doyon, Vinay et al. 2016). Figure 1D, black shows that the direction of photocurrents was hyperpolarizing upon illumination with λ<500 nm and depolarizing at longer wavelengths. A shoulder near 520 nm revealed a FRET contribution from EYFP (Govorunova, Sineshchekov et al. 2020), which was also observed upon expression of the Chrimson construct alone (Figure 1D, red)”.

In the C. elegans experiments, partial recovery of pharyngeal pumping was observed after prolonged illumination, indicating potential adaptation. This suggests that the effectiveness of these ChRs may be limited by cellular adaptation mechanisms, which could be a drawback in long-term experiments. A thorough discussion of this challenge in the application of optogenetics tools would prove very valuable to the readership.

We added the following paragraph to the revised Discussion:

“One possible explanation of the partial recovery of pharyngeal pumping that we observed after 15-s illumination, even at the highest tested irradiance, is continued attenuation of photocurrent during prolonged illumination (desensitization). However, the rate of AnsACR desensitization (Figure 1 – figure supplement 4A and Figure 1 – figure supplement 5A) is much faster than the rate of the pumping recovery, reducing the likelihood that desensitization is driving this phenomenon. Another possible reason for the observed adaptation is an increase in the cytoplasmic Cl^- concentration owing to AnsACR activity and hence a breakdown of the Cl^- gradient on the neuronal membrane. The C. elegans pharynx is innervated by 20 neurons, 10 of which are cholinergic (Pereira, Kratsios et al. 2015). A pair of MC neurons is the most important for regulation of pharyngeal pumping, but other pharyngeal cholinergic neurons, including I1, M2, and M4, also play a role (Trojanowski, Padovan-Merhar et al. 2014). Moreover, the pharyngeal muscles generate autonomous contractions in the presence of acetylcholine tonically released from the pharyngeal neurons (Trojanowski, Raizen et al. 2016). Given this complexity, further elucidation of pharyngeal pumping adaptation mechanisms is beyond the scope of this study.”

Reviewer #2 (Public review):

Summary:

Govorunova et al present three new anion opsins that have potential applications in silencing neurons. They identify new opsins by scanning numerous databases for sequence homology to known opsins, focusing on anion opsins. The three opsins identified are uncommonly fast, potent, and are able to silence neuronal activity. The authors characterize numerous parameters of the opsins.

Strengths:

This paper follows the tradition of the Spudich lab, presenting and rigorously characterizing potentially valuable opsins. Furthermore, they explore several mutations of the identified opsin that may make these opsins even more useful for the broader community. The opsins AnsACR and FtACR are particularly notable, having extraordinarily fast onset kinetics that could have utility in many domains. Furthermore, the authors show that AnsACR is usable in multiphoton experiments having a peak photocurrent in a commonly used wavelength. Overall, the author's detailed measurements and characterization make for an important resource, both presenting new opsins that may be important for future experiments, and providing characterizations to expand our understanding of opsin biophysics in general.

We thank the Reviewer for his/her positive evaluation of our work.

Weaknesses:

First, while the authors frequently reference GtACR1, a well-used anion opsin, there is no side-by-side data comparing these new opsins to the existing state-of-the-art. Such comparisons are very useful to adopt new opsins.

GtACR1 exhibits the peak sensitivity at 515 nm and therefore is poorly suited for combination with red-shifted CCRs or fluorescent sensors, unlike blue-light-absorbing ancyromonad ACRs. Nevertheless, we conducted side-by-side comparison of ancyromonad ChRs, GtACR1 and GtACR2, the latter of which has the spectral maximum at 470 nm. The results are shown in the new Figures 1E and F, and the new multipanel Figure 1 – figure supplement 4 added in the revision. We also added the following text, describing these results, to the revised Results section:

“Figures 1E and F show the dependence of the peak photocurrent amplitude and reciprocal peak time, respectively, on the photon flux density for ancyromonad ChRs and GtACRs. The current amplitude saturated earlier than the time-to-peak for all tested ChRs. Figure 1 – figure supplement 4A-E shows normalized photocurrent traces recorded at different photon densities. Quantitation of desensitization at the end of 1-s illumination revealed a complex light dependence (Figure 1, Figure Supplement 4F). Figure 1 – figure supplement 5 shows normalized photocurrent traces recorded in response to a 5-s light pulse of the maximal available intensity and the magnitude of desensitization at its end.”

Next, multiphoton optogenetics is a promising emerging field in neuroscience, and I appreciate that the authors began to evaluate this approach with these opsins. However, a few additional comparisons are needed to establish the user viability of this approach, principally the photocurrent evoked using the 2p process, for given power densities. Comparison across the presented opsins and GtACR1 would allow readers to asses if these opsins are meaningfully activated by 2P.

We carried out additional 2P experiments in ancyromonad ChRs, GtACR1 and GtACR2 and added their results to a new main-text Figure 6 and Figure 6 – figure supplement 1. We added the new section describing these results, “Two-photon excitation”, to the main text in the revision:

“To determine the 2P activation range of AnsACR, FtACR, and NlCCR, we conducted raster scanning using a conventional 2P laser, varying the excitation wavelength between 800 and 1,080 nm (Figure 6 – figure supplement 1). All three ChRs generated detectable photocurrents with action spectra showing maximal responses at ~925 nm for AnsACR, 945 nm for FtACR, and 890 nm for NlCCR (Figure 6A). These wavelengths fall within the excitation range of common Ti:Sapphire lasers, which are widely used in neuroscience laboratories and can be tuned between ~700 nm and 1,020-1,300 nm. To assess desensitization, cells expressing AnsACR, FtACR, or NlCCR were illuminated at the respective peak wavelength of each ChR at 15 mW for 5 seconds. GtACR1 and GtACR2, previously used in 2P experiments (Forli, Vecchia et al. 2018, Mardinly, Oldenburg et al. 2018), were included for comparison. The normalized photocurrent traces recorded under these conditions are shown in Figure 6B-F. The absolute amplitudes of 2P photocurrents at the peak time and at the end of illumination are shown in Figure 6G and H, respectively. All five tested variants exhibited comparable levels of desensitization at the end of illumination (Figure 6I).”

Reviewer #3 (Public review):

Summary:

The authors aimed to develop Channelrhodopsins (ChRs), light-gated ion channels, with high potency and blue action spectra for use in multicolor (multiplex) optogenetics applications. To achieve this, they performed a bioinformatics analysis to identify ChR homologues in several protist species, focusing on ChRs from ancyromonads, which exhibited the highest photocurrents and the most blue-shifted action spectra among the tested candidates. Within the ancyromonad clade, the authors identified two new anion-conducting ChRs and one cation-conducting ChR. These were characterized in detail using a combination of manual and automated patch-clamp electrophysiology, absorption spectroscopy, and flash photolysis. The authors also explored sequence features that may explain the blue-shifted action spectra and differences in ion selectivity among closely related ChRs.

Strengths:

A key strength of this study is the high-quality experimental data, which were obtained using well-established techniques such as manual patch-clamp and absorption spectroscopy, complemented by modern automated patch-clamp approaches. These data convincingly support most of the claims. The newly characterized ChRs expand the optogenetics toolkit and will be of significant interest to researchers working with microbial rhodopsins, those developing new optogenetic tools, as well as neuro- and cardioscientists employing optogenetic methods.

We thank the Reviewer for his/her positive evaluation of our work.

Weaknesses:

This study does not exhibit major methodological weaknesses. The primary limitation of the study is that it includes only a limited number of comparisons to known ChRs, which makes it difficult to assess whether these newly discovered tools offer significant advantages over currently available options.

We conducted side-by-side comparison of ancyromonad ChRs and GtACRs, wildly used for optical inhibition of neuronal activity. The results are shown in the new Figures 1E and F, and the new multipanel Figure 1 – figure supplement 4 and Figure 1 – figure supplement 5 added in the revision. We also added the following text, describing these results, to the revised Results section:

“Figures 1E and F show the dependence of the peak photocurrent amplitude and reciprocal peak time, respectively, on the photon flux density for ancyromonad ChRs and GtACRs. The current amplitude saturated earlier than the time-to-peak for all tested ChRs. Figure 1 – figure supplement 4A-E shows normalized photocurrent traces recorded at different photon densities. Quantitation of desensitization at the end of 1-s illumination revealed a complex light dependence (Figure 1, Figure Supplement 4F). Figure 1 – figure supplement 5 shows normalized photocurrent traces recorded in response to a 5-s light pulse of the maximal available intensity and the magnitude of desensitization at its end.”

Additionally, although the study aims to present ChRs suitable for multiplex optogenetics, the new ChRs were not tested in combination with other tools. A key requirement for multiplexed applications is not just spectral separation of the blue-shifted ChR from the red-shifted tool of interest but also sufficient sensitivity and potency under low blue-light conditions to avoid cross-activation of the respective red-shifted tool. Future work directly comparing these new ChRs with existing tools in optogenetic applications and further evaluating their multiplexing potential would help clarify their impact.

As a proof of principle, we co-expressed AnsACR with the red-shifted cation-conducting CCR Chrimson and demonstrated that the net photocurrent generated by this combination is hyperpolarizing in the blue region of the spectrum, and depolarizing at the red region. In the revision, we added a new panel (Figure 1D) showing these results and the following paragraph to the main text:

“To test the possibility of using AnsACR in multiplex optogenetics, we co-expressed it with the red-shifted CCR Chrimson (Klapoetke et al., 2014) fused to an EYFP tag in HEK293 cells. We measured the action spectrum of the net photocurrents with 4 mM Cl^- in the pipette, matching the conditions in the neuronal cytoplasm (Doyon, Vinay et al. 2016). Figure 1D, black shows that the direction of photocurrents was hyperpolarizing upon illumination with λ<500 nm and depolarizing at longer wavelengths. A shoulder near 520 nm revealed a FRET contribution from EYFP (Govorunova, Sineshchekov et al. 2020), which was also observed upon expression of the Chrimson construct alone (Figure 1D, red)”.

Reviewing Editor Comments:

The reviewers suggest that direct comparison to GtACR1 is the most important step to make this work more useful to the community.

We followed the Reviewers’ recommendations and carried out side-by-side comparison of ancyromonad ChRs and GtACR1 as well as GtACR2 (Figure 1E and F, Figure 1 – figure supplement 4, Figure 1 – figure supplement 5, and Figure 6). Note, however, that GtACR1’s spectral maximum is at 515 nm, which makes it poorly suitable for blue light excitation. Also, ChRs are known to perform very differently in different cell types and upon expression of their genes in different vector backbones, so our results cannot be generalized for all experimental systems. Each ChR user needs to select the most appropriate tool for his/her purpose by testing several candidates in his/her own experimental setting.

Reviewer #1 (Recommendations for the authors):

(1) The figure legend for Figure 2D-I appears to be incomplete. Please provide a detailed explanation of the panels.

In the revision, we have expanded the legend of Figure 2 to explain all individual panels.

(2) The meaning of the Vr shift (Y-axis in Figure 2H-I) should be clarified in the main text to aid reader understanding.

In the revision, we added the phrase “which indicated higher relative permeability to NO₃ than to Cl^-“ to explain the meaning of the Vr shift upon replacement of Cl^- with NO₃-.

(3) Adding statistical analysis for the peak and end photocurrent values in Figure 2D-F would strengthen the claim that there is minimal change in relative permeability during illumination.

In the revision, we added the V_r values for the peak photocurrent to Figure 2H-I, which already contained the V_r values for the end photocurrent, and carried out a statistical analysis of their comparison. The following sentence was added to the text in the revision:

“The V_r values of the peak current and that at the end of illumination were not significantly different by the two-tailed Wilcoxon signed-rank test (Fig. 2G), indicating no change in the relative permeability during illumination.”

(4) Figure 4H and I seem out of place in Figure 4, as the title suggests a focus on wild-proteins and AnsACR mutants. The authors could consider moving these panels to Figure 3 for better alignment with the content.

As noted below, we changed the panel order in Figure 4 upon the Reviewer’s request. In particular, former Figure 4I is Figure 4C in the revision, and former Figure 4H is now panel C in Figure 3 – figure supplement 1 in the revision. We rearranged the corresponding section of the text (highlighted yellow in the manuscript).

(5) The characterization section could be strengthened by including data on the pH sensitivity of FtACR, which is currently missing from the main figures.

Upon the Reviewer’s request, we carried out pH titration of FtACR absorbance and added the results as Figure 4B in the revision.

(6) The logic in Figure 4A-G appears somewhat disjointed. For example, Figure 4A shows pH sensitivity for WT AnsACR and the G86E mutant, while Figure 4 B-D shifts to WT AnsACR and the D226N mutant, and Figure 4E returns to the G86E mutant. Reorganizing or clarifying the flow would improve readability.

We followed the Reviewer’s advice and changed the panel order in Figure 4. In the revised version, the upper row (panels A-C) shows the pH titration data of the three WTs, the middle row (panels D-F) shows analysis of the AnsACR_D226N mutant, and the lower row (panels G-I) shows analysis of the AnsACR_G88E mutant. We also rearranged accordingly the description of these panels in the text.

(7) In Figure 5A, "NIACR" should likely be corrected to "NlCCR".

We corrected the typo in the revision.

(8) The statistical significance in Figure 6C and D is somewhat confusing. Clarifying which groups are being compared and using consistent symbols would improve interoperability.

In the revision, we improved the figure panels and legend to clarify that the comparisons are between the dark and light stimulation groups within the same current injection.

(9) The authors pointed out that at rest or when a small negative current was injected, the neurons expressing Cl- permeable ChRs could generate a single action potential at the beginning of photostimulation, as has been reported before. The authors could help by further discussing if and how this phenomenon would affect the applicability of such tools.

We mentioned in the revised Discussion section that activation of ACRs in the axons could depolarize the axons and trigger synaptic transmission at the onset of light stimulation, and this undesired excitatory effect need to be taken into consideration when using ACRs.

Reviewer #2 (Recommendations for the authors):

Govorunova et al present three new anion opsins that have potential applications in silencing neurons. This paper follows the tradition of the Spudich lab, presenting and rigorously characterizing potentially valuable opsins. Furthermore, they explore several mutations of the identified opsin that may make these opsins even more useful for the broader community. In general, I feel positively about this manuscript. It presents new potentially useful opsins and provides characterization that would enable its use. I have a few recommendations below, mostly centered around side-by-side comparisons to existing opsins.

(1) My primary concern is that while there is a reference to GtACR1, a highly used opsin first described by this team, they do not present any of this data side by side.

When evaluating opsins to use, it is important to compare them to the existing state of the art. As a potential user, I need to know where these opsins differ. Citing other papers does not solve this as, even within the same lab, subtle methodological differences or data plotting decisions can obscure important differences.

As we explained in the response to the public comments, we carried out side-by-side comparison of ancyromonad ChRs and GtACRs as requested by the Reviewer. The results are shown in the new Figures 1E and F, and the new multipanel Figure 1 – figure supplement 4 and Figure 1 – figure supplement 5, added in the revision. However, we would like to emphasize a limited usefulness of such comparative analysis, as ChRs are known to perform very differently in different cell types and upon expression of their genes in different vector backbones, so our results cannot be generalized for all experimental systems. Each ChR user needs to select the most appropriate tool for his/her purpose by testing several candidates in his/her own experimental setting.

(2) Multiphoton optogenetics is an emerging field of optogenetics, and it is admirable that the authors address it here. The authors should present more 2p characterization, so that it can be established if these new opsins are viable for use with 2P methods, the way GtACR1 is. The following would be very useful for 2P characterization:

Photocurrents for a given power density, compared to GtACR1 and GtACR2.

The new Figure 6 (B-F) added in the revision shows photocurrent traces recorded from the three ancyromonad ChRs and  two GtACRs upon 2P excitation of a given power density.

Comparing NICCR and FtACR's wavelength specificity and photocurrent. If these opsins are too weak to create reasonable 2P spectra, this difference should be discussed.

The new Figure 6A shows the 2P action spectra of all three ancyromonad ChRs.

A Trace and calculated photocurrent kinetics to compare 1P and 2P. This need not be the flash-based absorption characterization of Figure 3, but a side-by-side photocurrent as in Figure 2.

As mentioned above, photocurrent traces recorded from ancyromonad ChRs and GtACRs upon 2P excitation are shown in the new Figure 6 (B-F). However, direct comparison of the 2P data with the 1P data is not possible, as we used laser scanning illumination for the former and wild-field illumination for the latter.

Characterization of desensitization. As the authors mention, many opsins undergo desensitization, presenting the ratio of peak photocurrent vs that at multiple time points (probably up to a few seconds) would provide evidence for how effectively these constructs could be used in different scenarios.

We conducted a detailed analysis of desensitization under both 1P and 2P excitation. The new Figure 1 – figure supplement 4 and Figure 1 – figure supplement 5 show the data obtained under 1P excitation, and the new Figure 6 shows the data for 2P conditions.

I have to admit, that by the end of the paper, I was getting confused as to which of the three original constructs had which property, and how that was changing with each mutation. I would suggest that a table summarizing each opsin and mutation with its onset and offset kinetics, peak wavelength, photocurrent, and ion selectivity would greatly increase the ability to select and use opsins in the future.

In the revision, we added a table of the spectroscopic properties of all tested mutants as Supplementary File 2. This study did not aim to analyze other parameters listed by the Reviewer. We added the following sentence referring to this table to the main text:

“Supplementary File 2 contains the λ values of the half-maximal amplitude of the long-wavelength slope of the spectrum, which can be estimated more accurately from the action spectra than the λ of the maximum.”

It may be out of the scope of this manuscript, but if a soma localization sequence can be shown to remove the 'axonal spiking' (as described in line 441), this would be a significant addition to the paper.

Our previous study (Messier et al., 2018, doi: 10.7554/eLife.38506) showed that a soma localization sequence can reduce, but not eliminate, the axonal spiking. We plan to test these new ACRs with the trafficking motifs in the future.

NICCR appears to have the best photocurrents of all tested opsins in this paper. It seems odd that it was omitted from the mouse cortical neurons experiments.

We have not included analysis of NlCCR behavior in neurons because we are preparing a separate manuscript on this ChR.

Figure 6 would benefit from more gradation in the light powers used to silence and would benefit from comparison to GtACR. I suggest using a fixed current with a series of illumination intensities to see which of the three opsins (or GtACR) is most effective at silencing. At present, it looks binary, and a user cannot evaluate if any of these opsins would be better than what is already available.

In the revision, we added the data comparing the light sensitivity of AnsACR and FtACR with previously identified GtACR1 and GtACR2 (new Figure 1E and F) to help users compare these ACRs. Although they are less sensitive to light comparing to GtACR1 and GtACR2, they could still be activated by commercially available light sources if the expression levels are similar. Less sensitive ACRs may have less unwanted activation when using with other optogenetic tools.

Reviewer #3 (Recommendations for the authors):

Suggested Improvements to Experiments, Data, or Analyses:

(1) Line 25: "significantly exceeding those by previously known tools" and Line 408: "NlCCR is the most blue-shifted among ancyromonad ChRs and generates larger photocurrents than the earlier known CCRs with a similar absorption maximum." As noted in the public review, this statement applies only to a very specific subgroup of ChRs with spectral maxima below 450 nm. If the goal was to claim that NlCCR is a superior tool among a broader range of blue-light-activated ChRs, direct comparisons with state-of-the-art ChRs such as ChR2 T159C (Berndt et al., 2011), CatCh (Kleinlogel et al., 2014), CoChR (Klapoetke et al., 2014), CoChR-3M (Ganjawala et al., 2019), or XXM 2.0 (Ding et al., 2022) would be beneficial. If the goal was to demonstrate superiority among tools with spectra below 450 nm, I suggest explicitly stating this in the paper.

The Reviewer correctly inferred that we emphasized the superiority of NlCCR among tools with similar spectral maxima, not all blue-light-activated ChRs available for neuronal photoexcitation, most of which exhibit absorption maxima at longer wavelengths. To clarify this, we added “with similar spectral maxima” to the sentence in the original Line 25. The sentence in Line 408 already contains this clarification: “with a similar absorption maximum”.

(2) Lines 111-113: "The absorption spectra of the purified proteins were slightly blue-shifted from the respective photocurrent action spectra (Figure 1D), likely due to the presence of non-electrogenic cis-retinal-bound forms." I would be skeptical of this statement. The spectral shifts in NlCCR and AnsACR are small and may fall within the range of experimental error. The shift in FtACR is more apparent; however, if two forms coexist in purified protein, this should be reflected as two Gaussian peaks in the absorption spectrum (or at least as a broader total peak reflecting two states with close maxima and similar populations). On the contrary, the action spectrum appears to have two peaks, one potentially below 465 nm. Generally, neither spectrum appears significantly broader than a typical microbial rhodopsin spectrum. This question could be clarified by quantifying the widths of the absorption and action spectra or by overlaying them on the same axis. In my opinion, the two spectra seem very similar, and just appearance of the "bump" in the action spectum shifts the apparent maximum of the action spectrum to the red. If there were two states, then they should both be electrogenic, and the slight difference in spectra might be explained by something else (e.g. by a slight difference in the quantum yields of the two states).

As the Reviewer suggested, in the revision we added a new figure (Figure 1 – figure supplement 2), showing the overlay of the absorption and action spectra of each ancyromonad ChR. This figure shows that the absorption spectra are wider than the action spectra (especially in AnsACR and FtACR), which confirms our interpretation (contribution of the non-electrogenic blue-shifted cis-retinal-bound forms to the absorption spectrum). Note that the presence of such forms explaining a blue shift of the absorption spectrum has been experimentally verified in HcKCR1 (doi: 10.1016/j.cell.2023.08.009; 10.1038/s41467-025-56491-9). Therefore, we revised the text as follows:

“The absorption spectra of the purified proteins (Figure 1C) were slightly blue-shifted from the respective photocurrent action spectra (Figure 1 – figure supplement 3), likely due to the presence of non-electrogenic cis-retinal-bound forms. The presence of such forms, explaining the discrepancy between the absorption and the action spectra, was verified by HPLC in KCRs (Tajima et al. 2023, Morizumi et al., 2025).”

(3) Lines 135-136: "The SyncroPatch enables unbiased estimation of the photocurrent amplitude because the cells are drawn into the wells without considering their tag fluorescence." While SyncroPatch does allow unbiased selection of patched cells, it does not account for the fraction of transfected cells. Without a method to exclude non-transfected cells, which are always present in transient transfections, the comparison of photocurrents may be affected by the proportion of untransfected cells, which could vary between constructs. To clarify whether the statistically significant difference in the Kolmogorov-Smirnov test could indicate that the fraction of transfected cells after 48-72h differs between constructs, I suggest analyzing only transfected cells or reporting fractions of transfected cells by each construct.

The Reviewer correctly states that non-transfected cells are always present in transiently transfected cell populations. However, his/her suggestion to “exclude non-transfected cells” is not feasible in the absence of a criterion for such exclusion. As it is evident from our data, transient transfection results in a continuum of the amplitude values, and it is not possible to distinguish a small photocurrent from no photocurrent, considering the noise level. We would like, however, to emphasize that not excluding any cells provides an estimate of the overall potency of each ChR variant, which depends on both the fraction of transfected cells and their photocurrents. This approach mimics the conditions of in vivo experiments, when non-expressing cells also cannot be excluded.

(4) Line 176: "AnsACR and FtACR photocurrents exhibited biphasic rise." The fastest characteristic time is very close to the typical resolution of a patch-clamp experiment (RC = 50 μs for a 10 pF cell with a 5 MΩ series resistance). Thus, I am skeptical that the faster time constant of the biphasic opening represents a protein-specific characteristic time. It may not be fully resolved by patch-clamp and could simply result from low-pass filtering of a specific cell. I suggest clarifying this for the reader.

The Reviewer is right that the patch clamp setup acts as a lowpass filter. Earlier, we directly measured its time resolution (~15 μs) by recording the ultrafast (occurring on the ps time scale) charge movements related to the trans-cis isomerization (doi: 10.1111/php.12558). However, the lowpass filter of the setup can only slow the entire signal, but cannot lead to the appearance of a separate kinetic component (i.e. a monophasic process cannot become biphasic). Therefore, we believe that the biphasic photocurrent rise reflects biphasic channel opening rather than a measurement artifact. Two phases in the channel opening have also been detected in GtACR1 (doi: 10.1073/pnas.1513602112) and CrChR2 (10.1073/pnas.1818707116).

(5) Line 516: "The forward LED current was 900 mA." It would be more informative to report the light intensity rather than the forward current, as many readers may not be familiar with the specific light output of the used LED modules at this forward current.

We have added the light intensity value in the revision:

“The forward LED current was 900 mA (which corresponded to the irradiance of ~2 mW mm^-2)…”

(6) Lines 402-403: "The NlCCR ... contains a neutral residue in the counterion position (Asp85 in BR), which is typical of all ACRs. Yet, NlCCR does not conduct anions, instead showing permeability to Na+." This is not atypical for CCRs and has been demonstrated in previous works of the authors (CtCCR in Govorunova et al. 2021, ChvCCR1 in Govorunova et al. 2022). What is unique is the absence of negatively charged residues in TM2, as noted later in the current study. However, the absence of negatively charged residues in TM2 appears to be rare for ACRs as well. Not as a strong point of criticism, but to enhance clarity, I suggest analyzing the frequency of carboxylate residues in TM2 of ACRs to determine whether the unique finding is relevant to ion selectivity or to another property.

The Reviewer is correct that some CCRs lack a carboxylate residue in the D85 position, so this feature alone cannot be considered as a differentiating criterion. However, the complete absence of glutamates in TM2 is not rare in ACRs and is found, for example, in HfACR1 and CarACR2. We have discussed this issue in our earlier review (doi: 10.3389/fncel.2021.800313) and do not think that repeating this discussion in this manuscript is appropriate.

Recommendations for Writing and Presentation:

(1) Some figures contain incomplete or missing labels:

Figure 2: Panels D to I lack labels.

In the revision, we have expanded the legend of Figure 2 to explain all individual panels.

Figure 3 - Figure Supplement 1: Missing explanations for each panel.

In the revision, we changed the order of panes and explained all individual panels in the legend.

Figure 5 - Figure Supplement 1: Missing explanations for each panel.

No further explanation for individual panels in this Figure is needed because all panels show the action spectra of various mutants, the names of which are provided in the panels themselves. Repeating this information in the figure legend would be redundant.

(2) In Figure 2, "sem" is written in lowercase, whereas "SEM" is capitalized in other figures. Standardizing the format would improve consistency.

In the revision, we changed the font of the SEM abbreviation to the uppercase in all instances.

(3) Line 20: "spectrally separated molecules must be found in nature." There is no proof that they cannot be developed synthetically; rather, it is just difficult. I suggest softening this statement, as the findings of this study, together with others, will probably allow designing molecules with specified spectral properties in the future.

In the revision, we changed the cited sentence to the following:

“Multiplex optogenetic applications require spectrally separated molecules, which are difficult to engineer without disrupting channel function”.

(4) Line 216-219: "Acidification increased the amplitude of the fast current ~10-fold (Figure 4F) and shifted its Vr ~100 mV (Figure 3 - figure supplement 1D), as expected of passive proton transport. The number of charges transferred during the fast peak current was >2,000 times smaller than during the channel opening, from which we concluded that the fast current reflects the movement of the RSB proton." The claim about passive transport of the RSB proton should be clarified, as typically, passive transport is not limited to exactly one proton per photocycle, and the authors observe the increase in the fast photocurrents upon acidification.

We thank the Reviewer for pointing out the confusing character of our description. To clarify the matter, we added a new photocurrent trace to Figure 4I in the revision recorded from AnsACR_G86E at 0 mV and pH 7.4. We have rewritten the corresponding section of Results as follows:

“Its rise and decay τ corresponded to the rise and decay τ of the fast positive current recorded from AnsACR_G86E at 0 mV and neutral pH, superimposed on the fast negative current reflecting the chromophore isomerization (Figure 4I, upper black trace). We interpret this positive current as an intramolecular proton transfer to the mutagenetically introduced primary acceptor (Glu86), which was suppressed by negative voltage (Figure 4I, lower black trace). Acidification increased the amplitude of the fast negative current ~10-fold (Figure 4I, black arrow) and shifted its V_r ~100 mV to more depolarized values (Figure 4 – figure supplement 2A). This can be explained by passive inward movement of the RSB proton along the large electrochemical gradient.”

Minor Corrections:

(1) Line 204: Missing bracket in "phases in the WT (Figure 4D."

The quoted sentence was deleted during the revision.

(2) Line 288: Typo-"This Ala is conserved" should probably be "This Met is conserved."

We mean here the Ala four residues downstream from the first Ala. To avoid confusion, we changed the cited sentence to the following:

“The Ala corresponding to BR’s Gly122 is also found in AnsACR and NlCCR (Figure 5A)…”

(3) Lines 702-704: Missing Addgene plasmid IDs in "(plasmids #XXX and #YYY, respectively)."

In the revision, we added the missing plasmid IDs.

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Reply to the reviewers

Note to all Reviewers:

We would like to thank all the reviewers for their time and insightful feedback. In response to the comments and points raised, we have performed major revisions to our manuscript. We have expanded our analysis on the role of TP53 loss of function in BM activation (Figure 3), investigating human LUAD datasets as well as murine LUAD models. We show that TP53 pathway is significantly negatively correlated with BM, and that loss of TP53 leads to the acquisition of the basal-like phenotype regardless of the type of driver oncogene present (KRAS/EGFR). Furthermore, we added a new figure (Figure 7), where we demonstrate that type I interferon can promote BM activation in LUAD harboring TP53 mutations but not in those with wild type TP53. With this, we propose a mechanism of action of how a subset of LUAD tumors (TP53-mut) upregulate BM, become more aggressive and resistant to therapies.

Finally, we have made the manuscript clearer and transparent by improving the presentation of plots, as well as including source data files and Rmarkdown files for reproducibility.

Reviewer 1:

Major comments

R1-Comment 1: The authors did not submit with the manuscript all the results that they have obtained from their analysis, on which they based their claims. I suggest that the authors submit a SourceData file in Excel format. This file should contain the values and the relevant information for each of the plots presented in the main and supplementary figures. For example, in case of box plots, the five-number summary should be provided. Further, the p-values and the test used for their calculations should be also mentioned. The file could be organized in a way that the data and relevant information for each figure panel are presented in separated data sheets in order that the reader can easily navigate through the file and find the information for each figure panel fast. Similarly, the authors should provide access to the scripts that they have developed or adapted from published scripts to perform the analysis of the datasets and obtain the results presented in the manuscript. The access to the scripts used in the manuscript is important to reproduce analysis. The scripts can be deposited at github, for example.

Reply: We thank the reviewer for their advice in making the presentation of our results and methods more transparent and reproducible. We have now provided the source data file (supplementary file 2), which contains relevant data for each figure. We have also uploaded Rmarkdown files to github and R Markdown HTML reports are compiled in Supplementary File 3, this shows how the analyses were performed and how each figure generated. All datasets required to reproduce the analyses and figures have also been added to Zenodo (10.5281/zenodo.16964654) and will be published when the article is in press.

R1-Comment 2: The results and their interpretations are mainly done based on in silico analysis from publicly available transcriptomic datasets. The confirmation of the results obtained by the in silico analysis is limited to the last figure, in which the authors show results obtained by multiplexed immunohistochemistry and histo-cytometry of tissue microarrays from a curated cohort of FFPE samples. The relevance of the results obtained by the in silico analysis may increase if the authors could present results either in a conditional (lung-specific) Kras mutant mouse model, or patient-derived xenograft (PDX) mouse model of lung cancer. The PDX mouse model will be more suitable in case that access to genetically modified mouse models is not given and/or the time for the experiments is limited. In both cases, the hyperactivation of the small GTPase KRAS should expand the BM gene expression signature in the mouse lung in a Sox9-dependent manner, thereby leading to lung tumors. Further, Sox9 loss-of-function experiments should reduce the BM gene expression signature and favor the ALV gene expression signature. These results would strongly support the interpretation of the in silico results by the authors in the present manuscript, and would significantly increase the impact of the manuscript in the scientific field of lung cancer.

Reply: We thank the reviewer for their insightful feedback on how to improve the impact of our study through further functional validation of in silico findings. To address this comment, we have performed additional analyses, including data and experiments from both murine and human LUAD model systems to elucidate a novel mechanism of BM activation in LUAD. We appreciate the reviewer’s suggestion to pursue analysis of Sox9 involvement in regulating BM activation and agree that both KRAS and SOX9 activation are likely to be involved in at least some elements of the process of disease progression we described in this manuscript. Indeed, previous studies have completed the experiments suggested, demonstrating Sox9 knock-out reduced Kras driven tumour progression and morphological grade in vivo (PMID: 37258742 and 34021911); and was associated with loss of AT2 lineage identity (PMID: 37468622).

Our analysis of human LUAD using scRNA-seq data has demonstrated that this differentiation spectrum in fact extends beyond loss of lineage fidelity and in a subset of cells leads to transdifferentiation to a basal-like cell state. In our revised manuscript, we have more clearly elucidated the role of KRAS and TP53 in these two events during LUAD progression, demonstrating that while oncogenic KRAS (and likely downstream SOX9 activation) can lead to the loss of lineage commitment in LUAD cells, mutations in TP53 are required for acquisition of the basal-like phenotype. We have also expanded on this mechanism identifying a novel role for type-1 interferon signaling in the presence of TP53 loss-of-function as a mechanism that can lead to BM activation and acquisition of a basal-like cell state in LUAD. The data related to these analyses are now presented in figures 3 and 7.

In accordance with the 3Rs principles for ethical use of animals in research we have taken advantage of publicly available data from previous experiments analyzing conditional (lung-specific) Kras mutant mouse model to validate our in-silico findings. This confirmed our in silico analysis of human LUAD, demonstrating an important role for TP53 loss of function in regulating BM activation (presented in Figure 3E&F and Figure S3F&G)

We also showed that the type I interferon signaling is capable of driving BM activation in LUAD but only in the context of TP53 loss-of-function. These experiments were performed using 3D organotypic cultures of H441 cells (human adenocarcinoma cell line with mutant TP53) and A549 cells (human adenocarcinoma cell line with wild-type TP53). These 3D cultures were treated with IFN-alpha, both BM and basal-like marker upregulation (MKI67, CDC20, TOP2A, S100A9, S100A2, SOX9 and KRT17) was observed only in LUAD cells carrying a mutation in TP53. These data are now presented in Figure S7D.

R1-Comment 3: In general, the description of the results in the corresponding section of the manuscript can be improved to facilitate the understanding of the results presented.

As an example, the figure 1B is described on page 13 as follows: "...we first used a publicly available microarray dataset [9] to identify genes differentially expressed between epithelial cells engaged in BM (embryonic day 14 [E14]) or ALV (embryonic day 19 [E19]) (Figure 1B and TABLE S1)." By looking at the plot in figure 1B, this description is not sufficient to understand what the authors present in this figure panel, not even after reading the corresponding figure legend.

Reply: We thank the reviewer for their advice on making our manuscript clearer. Throughout the manuscript we have now edited the result descriptions, we have also provided further detail to the methods sections, figure legends and axes labels to enhance clarity and facilitate understanding of the analyses performed.

In the example cited we have edited the sections referenced above as follows:

“To test this hypothesis, we identified genes that were differentially expressed in epithelial cells engaged in active BM (corresponding to embryonic day 14) vs active ALV (corresponding to embryonic day 19), using a publicly available microarray dataset.”

We have also changed the Y axis label of Figure 1B to: “log2(FC E19 [ALV] – E14[BM])”.

The description in the figure legend has also been modified to provide more context: “Dot plot showing the identification of genes differentially expressed by epithelial cells during murine developmental-BM (embryonic day 14) and ALV (embryonic day 19) [1]. Genes with the highest Fold Change of expression between day 14 (BM) and 19 (ALV) of murine lung development are coloured green or red, respectively. These genes were used to generate ALV/BM signatures [9]”

R1-Comment 5: Another example is the description of the figure 3B on page 16: "This showed low levels of BM activation in tumour cells from residual disease (RD) that was significantly increased in samples with recurrent progressive disease (PD) (Figure 3B)." By looking figure 3B and the corresponding figure legend, one cannot find the group "residual disease (RD)".

__Reply: __We thank the reviewer for their diligent reading and have now corrected the figures to provide clearer labelling of axes and maintain consistency throughout. In the example cited, we have corrected the axis label to Residual disease (RD) and partial response (PR).

R1-Comment 6: Another example is the description of the figure 3C and 3D on page 16: "Single-cell analysis showed that both ALV-BM- and ALV-BM+ LUAD cells were increased in samples from recurrent progressive disease (Figure 3C,D)." By looking at figure 3D and the corresponding legend, I do not find the explanation of "TRUE" and "FALSE". The same is for figures 3J and 3M.

Reply: For this example (Figure 3 in the original manuscript is now figure 4), TRUE/FALSE labels have been replaced by PR (partial response) and PD (progressive disease) in panel D; replaced by “Responder (R)” or “Non-responder (NR)” in panels J&M.

R1-Comment 7: Other figure panels were also poorly described in the results section and in the corresponding legends. Further, the presentation of the results in the main and supplementary figures has to be improved. For example, labeling of the Y-axis in the figures 1H to 1J, 2C, 2D, 2G, 2H, 3B, 3C, 3J, 3L, etc. has to be improved. As a point of reference, I would suggest checking how other authors present similar results in life science journals. These deficiencies in the presentation and description of the results make it difficult for the readers to understand the manuscript.

Reply: These axes labels have been changed throughout to provide more information. “BM” changed to “BM (ssGSEA score)” or “BM (module score)” and “ALV” changed to “ALV (ssGSEA score)” or “ALV (module score)” for figures 1H, 1I, 1J, S1H-L, 2C, 2D, 3B, 3F, S3E, S3F, S3G, 4B, 4C, 4J, 4L, S4C, S4D, S5A, 6A, S6A, S6B, ssGSEA score was applied to bulk RNAseq samples, and modules scores were calculated for single cells.

Additionally:

S2A, S2B – OS label changed to Survival probability/OS probability.

S4H – y axis label changed to PDL1 (RPPA).

S3B – y axis label changed to “Tumour mutational burden (mut/mB).

S3C – y axis label changed to “Tobacco smoking (SBS mutational signature)”.

4F – y axis label changed to “DFS (proportion)”.

4H – y axis label changed to “PFS (proportion)”.

R1-R1-Comment 8: The authors write on page 18 "Despite AT2 cells being well described as the cell of origin for LUAD, this population was significantly less abundant in LUAD samples compared to control, demonstrating a high degree of transcriptomic plasticity within LUAD epithelium (Figure 4D)." How can the authors show that these results are not produced by the process of integration of the four scRNA-seq NSCLC datasets, the implementation of a specific machine learning classifier for the cell type-classification, or the manually filtration to exclude doublets? For example, will the authors achieve the same (or similar) results using a different machine learning classifier? If yes, please include the results in the manuscript.

Reply: The integration was performed using the method described by Stuart et al. (PMID: 31178118), implemented in the Seurat package. The term “machine learning classifier” has now been replaced by “label transfer” to clarify the method used and avoid confusion. Label transfer was only used to identify major cell types in the datasets used, i.e. the whole epithelial population. Doublet removal was performed as follows (and described in the methods section): epithelial cells were clustered using the shared nearest neighbor (SNN) modularity optimization algorithm implemented by the FindClusters function in the Seurat R package, based on 30 principal components and setting the resolution parameter to 0.1. This clustering solution identified multiple small clusters with divergent expression profiles to the majority of cells that were initially classified as epithelial (in the label transfer analysis). Manual examination of the marker genes for these small clusters showed they were characterized by expression of epithelial genes alongside canonical markers for either B cells (CD79A), macrophages (CD68, SPP1, APOE, CD14, MARCO) or Tcells/NK cells (CD3D, NKG7, CXCR4). These cells were therefore classed as heterotypic doublets and excluded from further analysis. All other cell types from the integrated datasets were analyzed in the same way, and no further epithelial clusters (that were not small clusters of doublets) were identified.

Further clustering to identify epithelial subpopulations was performed on the integrated dataset and the results presented from this analysis represent the clustering solution that ensures all subpopulations were identified across datasets to mitigate any potential batch-effects not resolved by the integration process. Furthermore, our results showing that LUAD cells exhibit a high degree of transcriptomic plasticity were also confirmed by the lineage fidelity analysis (Figure 5G&I), which demonstrates this observation is not dependent on a single clustering, integration or machine learning algorithm. This observation is also supported by other studies that have described loss of lineage commitment during LUAD tumorigenesis, where tumour cells become transcriptionally and phenotypically distinct from healthy AT2 cells.

Reviewer 1:

Minor comments:

__R1-Comment 9: __Please introduce the abbreviation for alveogenesis the first time that is used in the abstract, as it was done for branching morphogenesis.

__Reply: __Abbreviation for alveogenesis has now been added to the abstract.

R1-Comment 10: On page 18 the author write: "Consistent with the analyses presented above, pseudo bulk expression profiles for each sample showed that ALV and BM scores were significantly negatively correlated (r = -0.68, p = 4.1e-09)." Where are these results shown? I was not able to find these results. If they are not in the current version of the manuscript, please include the results

Reply: Scatter plot showing the negative correlation has now been added as Figure S5A.

__R1-Comment 11: __The authors should submit a supplementary table containing a list of the different data sets that were used for this manuscript. The table should include accession numbers and links to the different depositories, in which the data sets can be found. This will improve the overview of the datasets used in the study, as well as facilitate the finding of the datasets by the readers.

Reply: The list of all datasets used in this study, together with accession numbers and links are now in Supplementary file1.

R1-Comment 12: In figure 1G, change the color for FALSE in the legend.

Reply: Color for FALSE changed in Figure 1G and Figure S1E.

R1-Comment 13: Provide the complete list of mutated genes for Figure S2C.

Reply: Figure S2C has been replaced by figures 3C (top mutated genes in LUAD-BM) and S3A (top mutated genes in LUAD-ALV).

Reviewer 1 (Significance (required)):

__R1-Comment 14: __Conceptually, Bienkowska KJ et al. propose that LUAD tumors undergo reversion from an alveogenic to branching morphogenic phenotype during disease progression, generating inflamed or basal-like cell states that are variably persistent following TKI or ICB treatments. This concept is in line with reports using murine models of Kras-driven LUAD. In addition, there are parallels with findings in idiopathic pulmonary fibrosis (IPF, another hyperproliferative lung disease), in which KRT5-/KRT17+ basaloid cells were transiently found, like the basal-like phenotype that Bienkowska KJ identified in human LUAD. In other words, the concept proposed by the authors is novel and in line with previous publication in LC and IPF.

Response: We are glad the reviewer found our results novel and appreciated how they provide a linkage of previously defined mechanisms seen in murine developmental models to human cancer progression, and how they may be relevant for other diseases such as IPF.

__R1-Comment 15: __The in silico analysis of publicly available transcriptomic datasets presented by Bienkowska KJ et al. is original and comprehensive. It is an interesting contribution to the cancer research field. However, the impact of their findings to this scientific field will significantly increase if the authors could confirm the interpretation of their results using other experimental systems in addition to the one used in the las figure. For example, the experiments that I suggested in point 2., using either conditional Kras transgenic mice or a PDX mouse model for lung cancer will not only confirm the concpet proposed by the authors, but it will also provide further mechanistic insides related to this model at cellular and molecular level.

Response: We thank the reviewer for describing our analysis as original and comprehensive and their suggestion to develop the manuscript further with additional mechanistic analyses. We have comprehensively examined the mechanisms responsible for regulating BM activation using a combination of in vivo models and 3D organotypic cultures, elucidating a novel role for type-1 interferon signaling in the presence of TP53 loss-of-function as a mechanism that can lead to BM activation and acquisition of a basal-like cell state in LUAD. For further information regarding these additions to the revised manuscript, we direct the reviewer to the response provided to R1-comment 2 (above).

__R1-Comment 16: __Overall, the manuscript by Bienkowska KJ et al. addresses topics that are relevant to the field of lung cancer, the leading cause of cancer-related deaths worldwide. The bioinformatic methods implemented are cutting-edge. However, the text of the manuscript and the presentation of the results in the figures have to be improved to better exploit the potential of their findings. In addition, further experiments should be performed to confirm (and perhaps complement) the interpretation of their findings. I hope that my comments support the authors to improve the manuscript to reach the standard of manuscripts recently published at renowned journals in Review COMMONS. I recommend a major revision of the manuscript before publication.

__Reply: __We are pleased to read that the reviewer found the methods implemented by us to be cutting-edge, and that they recognized the relevance of this topic to the lung cancer field.

We thank the reviewer for their comments, which have helped us to significantly improve our manuscript.

We have made changes to how we present our data (as described in responses above) and performed further analyses to support our original findings. We have also now performed further in silico and functional analyses to expand and complement our original findings.

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

R2-Comment 1: __The study is novel and interesting, but the mechanisms how the dysregulation of developmental program was driven by specific oncogene and how to link these signatures to therapy were also not clear. __

__Reply: __We are pleased that the reviewer finds our study to be novel and interesting. We appreciate the reviewer pointing out the need to clarify the role of specific oncogenes to BM activation and response to therapies.

We have now added further analyses and edited the text to examine and explain how the ALV and BM signatures are driven by different oncogenes (Figure 3 and results section “TP53 loss of function is required for BM activation”), which showed that common oncogenic drives (e.g. KRAS and EGFR) can drive reduced ALV signature expression but TP53 mutations (or deletion in murine models) was critical for driving BM activation. Implications for therapy response are shown in (Figure 4). We have shown that BM activation is a key determinant of tyrosine kinase inhibitor (TKI) resistance in LUAD, representing a frequently activated off-target mechanism of resistance that supersedes the presence of an actionable oncogenic driver in terms of response rates; and that the BM signature also identified patients that, although positive for immune checkpoint blockade (ICB) response biomarkers, will likely fail to respond to this treatment. In the manuscript we have now thoroughly revised these sections of the results to clarify the details associated with these conclusions (results sections: “BM activation is associated with targeted-therapy resistance in lung adenocarcinomas” and “BM activation predicts poor response to immune-checkpoint blockade”).

We have also added further data to the manuscript elucidating the molecular mechanisms regulating BM activation (Figure 7), which has identified an important role for aberrant type-I interferon signaling in the context of mutant TP53.

Reviewer #2 (Significance (Required)):

__R2-Comment 2: __The authors in this manuscript aimed to examine the role of developmental programmes, alveogenesis and branching morphogenesis (BM), in regulating phenotypic diversity in NSCLC. They demonstrated that developmental programmes (ALV and BM) frequently become

dysregulated in NSCLC, with BM activation identifying aggressive LUAD that were resistant

to multiple therapies, including TKIs and ICB. They found that BM activation in LUAD was associated with TP53 pathway mutations and required AT2 cells to lose their alveolar identity, acquiring a basallike state. The study is very intriguing, and the findings may pave a link to the disease progression and therapy resistance in LUAD.

__Response: __We are pleased the reviewer found the study intriguing and with the potential to better understand LUAD progression and resistance to therapies.

__R2-Comment 3: __The current results presented, although comprehensively presented, is still many an association study, the mechanisms how these dysregulations of developmental programmes driven by the driver oncogenes or carcinogens are still unknown.

Response: We thank the reviewer for challenging us to further examine the molecular mechanisms underpinning our initial observations. As described above (see response to Reviewer #1 comment 2), we have performed additional in silico and mechanistic experimental analyses, which identified a novel role for type-I IFN signaling and TP53 loss-of-function in the activation of the BM program in LUAD. We hope these additions have enhanced the significance of the manuscript presented.

__R2-Comment 4: __The NSCLC is a heterogeneous disease, LUAD and LUSC are two different diseases in terms of oncogenesis, driver mutations and response to treatment. The manuscript may either just focused on LUAD or describe results carefully to include both LUAD and LUSC. For example, in the result of abstract, only LUAD was described, there was no mention of LUSC.

__Response: __We agree with the reviewer that NSCLC is a heterogeneous and complex disease. Indeed, this was in part what motivated us to investigate the role played by developmental processes in these distinct oncogenic processes. Our analyses showed that LUSC tumors were generally high for the BM signature (Figure 1I), which likely contributed to why this signature did not stratify survival rates for LUSC (Figure S2B). As a result, we opted to focus on LUAD as we found that BM activation was predictive of disease progression and survival in this NSCLC subtype. However, we did not completely remove LUSC from our manuscript to examine the degree to which LUAD tumors upregulating BM become “LUSC-like” and evaluate whether histological transformations occurred in LUAD cases with BM activation (as described in Figure 5 and the “BM activation in LUAD is associated with a basal-like phenotype” results section).

We have also now added a description of results from both LUAD and LUSC analyses to the abstract to clarify these points.

__R2-Comment 5: __The most common driver mutation of LUAD was EGFR, the authors also try to link the BM activation link to TKI resistance. I assumed that the TKIs most of the patients used were EGFR TKI, but the study did not examine the role of EGFR in the dysregulation of developmental programmes.

__Response: __We would like to thank the reviewer for highlighting an important aspect of how our work fits with current clinical practice in LUAD management. Our analyses were carried out over multiple cohorts that include different patient demographics, which have varied prevalence for specific oncogenic driver mutations (with EGFR mutations typically being more prevalent in Asian cohorts and KRAS mutations generally being the most common oncogenic driver in Western cohorts). To examine these two common oncogenic drivers impact on BM activation, we now include a direct analysis of BM level in cases harboring these mutations (Figure S3D-E). This showed that that irrespective of oncogenic driver mutations TP53 loss of function was associated with increased BM. Our new analysis of KRAS driven mouse models has also showed that KRAS activation is sufficient to induce reduced expression of the ALV signature but failed to elicit increased BM activation. Given our analysis of human tumours showed that EGFR mutant LUAD cases with wild-type TP53 had low levels of BM activation (Figure S3D), we have no reason to suspect that EGFR mutations alone would be sufficient to elicit BM activation.

__R2-Comment 6: __The TKI resistance was very complicated, not just EGFR T790M, the results and discussion regarding the activation of BM and TKI resistance seems not adequate. The mouse model used by Dr. Chang was mainly KRAS driven mouse lung cancer model (mice carrying RosatdT, Sox2EGFP, ShhCre, Sox9CKO, Fgfr2CKO, RosamTmG, Sox9CreER, Nkx2.1CreER, and KrasLSL-G12D alleles). It is not clear whether the EGFR driven (the most common driver of LUAD) mouse model also has same genetic signature. At least, the authors should describe or discuss these discrepancies.

__Response: __We thank the reviewer for their comments and advice on making our manuscript clearer. We have now revised the description of BM activation and TKI resistance in the results section (titled “BM activation is associated with targeted-therapy resistance in lung adenocarcinomas”).

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Referee #1

Evidence, reproducibility and clarity

Summary:

Bienkowska KJ et al show in this manuscript a compilation of bioinformatic analysis of publicly available microarray datasets, bulk RNA sequencing (RNA-seq) datasets and single cell RNA sequencing (scRNA-seq) datasets. One transcriptomic data set from mouse (Chang DR et al., Proc Natl Acad Sci USA, 2013) was analyzed in this manuscript to determine the gene expression signatures specific for the developmental processes alveogenesis (ALV) and branching morphogenesis (BM). The rest of the transcriptomic data sets that were analyzed for this manuscript were selected based on different parameters including the involvement of non-small cell lung cancer (NSCLC), lug adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) and various cohorts with different characteristics related to lung cancer (LC), such as mutations related to LC (in EGFR, ALK, BRAF, ROS1 and KRAS), and/or treatments/resistance of LC patients with/to tyrosine kinase inhibitors (TKI), anti-PD1 strategies, immune checkpoint blockade, (ICB) among others. In the last figure, the authors present results obtained by multiplexed immunohistochemistry and histo-cytometry of tissue microarrays from a curated cohort of archival formalin-fixed paraffin-embedded (FFPE) samples to confirm their interpretation of the results obtained by the transcriptomic analysis.

The findings and/or claims of the authors could be summarized in the following bullet points:

• After defining the ALV and BM gene expression signatures, the authors determined the expression of these signatures in bulk RNA-seq data sets from The Cancer Genome Atlas (TCGA). The ALV signature was significantly downregulated in LUAD and LUSC tumour subtypes compared to control samples, whereas BM was upregulated. These findings were validated using a Laser Capture Micro-Dissected (LCMD) microarray dataset (Lin J et al., AM J Pathol, 2014) comparing the epithelial compartment from non-tumour alveoli, non-tumour bronchi, LUAD and LUSC. Interestingly, ALV was suppressed and BM was activated in all LUSC tumours analyzed; whereas in LUAD tumours were heterogeneous for BM activation with some cases exhibiting ALV expression comparable to control tissue. In summary, the mutually antagonistic regulation of ALV and BM was found to account for a significant proportion of transcriptomic variance in human NSCLC bulk tissue datasets.
• BM activation was associated with poor overall survival rates in five independent LUAD cohorts (p=2.04e-13); and was significantly prognostic for resistance to TKIs (p=0.003) and ICBs (p=0.014), in pre-treatment biopsies.
• ScRNA-seq analysis revealed that malignant LUAD cells with loss of alveolar lineage fidelity predominantly acquired inflamed or basal-like cellular states, which were variably persistent in samples from TKI and ICB recurrence.
• The authors conclude from their analysis that LUAD tumours undergo reversion from an alveogenic to branching morphogenic phenotype during disease progression, generating inflamed or basal-like cell states that are variably persistent following TKI or ICB treatments.

Major comments:

1. The authors did not submit with the manuscript all the results that they have obtained from their analysis, on which they based their claims. I suggest that the authors submit a SourceData file in Excel format. This file should contain the values and the relevant information for each of the plots presented in the main and supplementary figures. For example, in case of box plots, the five-number summary should be provided. Further, the p-values and the test used for their calculations should be also mentioned.

The file could be organized in a way that the data and relevant information for each figure panel are presented in separated data sheets in order that the reader can easily navigate through the file and find the information for each figure panel fast.

Similarly, the authors should provide access to the scripts that they have developed or adapted from published scripts to perform the analysis of the datasets and obtain the results presented in the manuscript. The access to the scripts used in the manuscript is important to reproduce analysis. The scripts can be deposited at github, for example. 2. The results and their interpretations are mainly done based on in silico analysis from publicly available transcriptomic datasets. The confirmation of the results obtained by the in silico analysis is limited to the last figure, in which the authors show results obtained by multiplexed immunohistochemistry and histo-cytometry of tissue microarrays from a curated cohort of FFPE samples.

The relevance of the results obtained by the in silico analysis may increase if the authors could present results either in a conditional (lung-specific) Kras mutant mouse model, or patient-derived xenograft (PDX) mouse model of lung cancer. The PDX mouse model will be more suitable in case that access to genetically modified mouse models is not given and/or the time for the experiments is limited. In both cases, the hyperactivation of the small GTPase KRAS should expand the BM gene expression signature in the mouse lung in a Sox9-dependent manner, thereby leading to lung tumors. Further, Sox9 loss-of-function experiments should reduce the BM gene expression signature and favor the ALV gene expression signature. These results would strongly support the interpretation of the in silico results by the authors in the present manuscript, and would significantly increase the impact of the manuscript in the scientific field of lung cancer. 3. In general, the description of the results in the corresponding section of the manuscript can be improved to facilitate the understanding of the results presented. As an example, the figure 1B is described on page 13 as follows:

"...we first used a publicly available microarray dataset [9] to identify genes differentially expressed between epithelial cells engaged in BM (embryonic day 14 [E14]) or ALV (embryonic day 19 [E19]) (Figure 1B and TABLE S1)."

By looking at the plot in figure 1B, this description is not sufficient to understand what the authors present in this figure panel, not even after reading the corresponding figure legend.

Another example is the description of the figure 3B on page 16:

"This showed low levels of BM activation in tumour cells from residual disease (RD) that was significantly increased in samples with recurrent progressive disease (PD) (Figure 3B)."

By looking figure 3B and the corresponding figure legend, one cannot find the group "residual disease (RD)".

Another example is the description of the figure 3C and 3D on page 16:

"Single-cell analysis showed that both ALV-BM- and ALV-BM+ LUAD cells were increased in samples from recurrent progressive disease (Figure 3C,D)."

By looking at figure 3D and the corresponding legend, I do not find the explanation of "TRUE" and "FALSE". The same is for figures 3J and 3M.

Other figure panels were also poorly described in the results section and in the corresponding legends.

Further, the presentation of the results in the main and supplementary figures has to be improved. For example, labeling of the Y-axis in the figures 1H to 1J, 2C, 2D, 2G, 2H, 3B, 3C, 3J, 3L, etc. has to be improved. As a point of reference, I would suggest checking how other authors present similar results in life science journals.

These deficiencies in the presentation and description of the results make it difficult for the readers to understand the manuscript. 4. The authors write on page 18

"Despite AT2 cells being well described as the cell of origin for LUAD, this population was significantly less abundant in LUAD samples compared to control, demonstrating a high degree of transcriptomic plasticity within LUAD epithelium (Figure 4D)."

How can the authors show that these results are not produced by the process of integration of the four scRNA-seq NSCLC datasets, the implementation of a specific machine learning classifier for the cell type-classification, or the manually filtration to exclude doublets? For example, will the authors achieve the same (or similar) results using a different machine learning classifier? If yes, please include the results in the manuscript.

Minor comments:

1. Please introduce the abbreviation for alveogenesis the first time that is used in the abstract, as it was done for branching morphogenesis.
2. On page 18 the author write:

"Consistent with the analyses presented above, pseudo bulk expression profiles for each sample showed that ALV and BM scores were significantly negatively correlated (r = -0.68, p = 4.1e-09)."

Where are these results shown? I was not able to find these results. If they are not in the current version of the manuscript, please include the results 7. The authors should submit a supplementary table containing a list of the different data sets that were used for this manuscript. The table should include accession numbers and links to the different depositories, in which the data sets can be found. Thiy will improve the overview of the datasets used in the study, as well as facilitate the finding of the datasets by the readers. 8. In figure 1G, change the color for FALSE in the legend. 9. Provide the complete list of mutated genes for Figure S2C

Significance

Conceptually, Bienkowska KJ et al. propose that LUAD tumors undergo reversion from an alveogenic to branching morphogenic phenotype during disease progression, generating inflamed or basal-like cell states that are variably persistent following TKI or ICB treatments. This concept is in line with reports using murine models of Kras-driven LUAD. In addition, there are parallels with findings in idiopathic pulmonary fibrosis (IPF, another hyperproliferative lung disease), in which KRT5-/KRT17+ basaloid cells were transiently found, like the basal-like phenotype that Bienkowska KJ identified in human LUAD. In other words, the concept proposed by the authors is novel and in line with previous publication in LC and IPF.

The in silico analysis of publicly available transcriptomic datasets presented by Bienkowska KJ et al. is original and comprehensive. It is an interesting contribution to the cancer research field. However, the impact of their findings to this scientific field will significantly increase if the authors could confirm the interpretation of their results using other experimental systems in addition to the one used in the las figure. For example, the experiments that I suggested in point 2., using either conditional Kras transgenic mice or a PDX mouse model for lung cancer will not only confirm the concpet proposed by the authors, but it will also provide further mechanistic insides related to this model at cellular and molecular level.

Overall, the manuscript by Bienkowska KJ et al. addresses topics that are relevant to the field of lung cancer, the leading cause of cancer-related deaths worldwide. The bioinformatic methods implemented are cutting-edge. However, the text of the manuscript and the presentation of the results in the figures have to be improved to better exploit the potential of their findings. In addition, further experiments should be performed to confirm (and perhaps complement) the interpretation of their findings. I hope that my comments support the authors to improve the manuscript to reach the standard of manuscripts recently published at renowned journals in Review COMMONS. I recommend a major revision of the manuscript before publication.

La fundación de unas 500 colonias griegas fue clave para la expansión del mundo helénico. alrededor del 40% de los griegos vivía en estos nuevos territorios, lo que fortaleció el comercio, difundió la cultura griega y amplió su influencia política y económica.

El comercio mejoró porque los barcos mercantes permitían transportar más productos de forma segura y el camino Diolkos en Corinto facilitaba acortar rutas evitando rodear toda la península.

El prestamo marítimo era un credito usado en el comercio: si el barco llegaba se pagaba con intereses, y si naufragaba no se devolvía.

Acá se demuestra lo importante que fue el comercio para los griegos, no solo para lo económico, sino también en lo cultural.

Debido a su ubicación geográfica que conectaba a Atenas con Europa, Asia y áfrica, este se volvió un punto de encuentro clave para el comercio.

3000 a.C. hasta el 1200 a.C. Fue un periodo marcado por el uso de bronce para herramientas y armas, y la exportacion de aceite de oliva, vino, ceramica y productos artesanales. El crecimiento economico facilito la acumulacion de riqueza y el desarrollo de una clase mercantil.

🌿 Diana de los bosques

Adriano no habla de la diosa literalmente, sino como símbolo de la caza y de un contacto intenso con la naturaleza. Diana es la divinidad de los bosques, los animales salvajes y la luna. Relacionarse con ella es relacionarse con lo salvaje, lo femenino y lo misterioso.

🐗 La caza del jabalí

En la adolescencia, la caza era rito de paso.

Para Adriano, matar un jabalí no era solo deporte, sino un primer contacto con el mando (dirigir a los cazadores, perros, organizar) y con el peligro real (un animal que podía matarlo).

La experiencia mezcla erotismo (“ser amado”), violencia y poder.

⚔️ Formación del carácter

Se entregaba con “furor”, es decir, con pasión casi dionisíaca.

Sus excesos provocaron que el propio Trajano —su tutor y futuro padre adoptivo— lo reprendiera.

En clave literaria, esto muestra a un joven impulsivo, con sed de riesgo, que debía ser domesticado para convertirse en emperador.

Author response:

Reviewer #1 (Public review):

Summary:

The authors of this study propose a model in which NPY family regulators antagonize the activity of the pid mutation in the context of floral development and other auxin-related phenotypes. This is hypothesized to occur through regulation of or by PID and its action on the PIN1 auxin transporter.

Strengths:

The findings are intriguing.

We are pleased that the reviewer found the work interesting!

Weaknesses and Major Comments:

(1) While the findings are indeed intriguing, the mechanism of action and interaction among these components remains poorly understood. The study would benefit from significantly more thorough and focused experimental analyses to truly advance our understanding of pid phenotypes and the interplay among PID, NPYs, and PIN1.

Elucidating the mechanism of action and interaction among these components will require years of additional research. As key steps toward these goals, our work clearly established that 1) NPY1 functions downstream of PID, as overexpression of NPY1 completely suppressed pid phenotypes. This is surprising because the predominant model is that PID functions by directly phosphorylating and activating PINs without the need of NPY1 involvement.  2) In the absence of PID, NPY1 protein accumulated less in the NPY1 OE lines, suggesting that PID plays a role in affecting NPY1 stability/degradation/accumulation. We are not sure what are the exact experiments this reviewer is proposing.

Regarding pid phenotypes, pid is completely sterile in our conditions, while the suppression by NPY1 OE is very clear and the lines are fertile.

(2) The manuscript appears hastily assembled, with key methodological and conceptual details either missing or inconsistent. Although issues with figure formatting and clarity (e.g., lack of scale bars and inconsistent panel layout) may alone warrant revision, the content remains the central concern and must take precedence over presentation.

We did not include scale bars in our figures because the phenotype of interest is presence/absence of flowers. Readers should compare the mutants with the rescued plants and the WT plants.

(3) Given that fertile progeny are obtained from pid-TD pin1/PIN1 and pid NPY OE lines, it would be important to analyze whether mutations and associated phenotypes are heritable. This is especially relevant since CRISPR lines can be mosaic. Comprehensive genotyping and inheritance studies are required.

We only use stable, heritable, Cas9-free mutants in our studies.  We genotype our mutants in every generation.  More details have been added to the Materials and Methods section. We provide the genetic materials we use to the scientific community when requested to enable verification and extension of our results. 

(4) The Materials and Methods section lacks essential information on how the lines were generated, genotyped, propagated, and scored. There is also generally no mention of how reproducible the observations were. These genetic experiments need to be described in detail, including the number of lines analyzed and consistency across replicates.

More details have been added to the Materials and Methods section

The criticism is not fully accurate. For example, we stated in the main text: “We genotyped T2 progenies from two pid-c1 heterozygous T1 plants (#68 and # 83) for the presence of pid-c1 and for pid-c1 zygosity. We used mCherry signal, which was included in the NPY1 OE construct, as a proxy to determine the presence and absence of the NPY1 transgene. For each line, we identified T2 plants without the NPY1 transgene and without the pid-c1 mutation (called WT-68 and WT-83, respectively). We also isolated T2 plants that contained the NPY1 overexpression construct, but did not have the pid-c1 mutation (called NPY1 OE #68 in WT, and NPY1 OE #83 in WT). Finally, we identified T2 plants that were pid-c1 homozygous and that had the NPY1 transgene (called NPY1 OE #68 in pid-c1 and NPY1 OE #83 in pid-c1). These genetic materials enabled us to compare the same NPY1 OE transgenic event in different genetic backgrounds.”

The genetic materials used are freely available to the scientific community.  We would like to point out that we used several pin1 and pid alleles to make sure that the phenotypes are caused by the genes of interest.

(5) The nature of the pid alleles used in the study is not described. This is essential for interpretation.

The mutants were described in a previous paper (M. Mudgett, Z. Shen, X. Dai, S.P. Briggs, & Y. Zhao, Suppression of pinoid mutant phenotypes by mutations in PIN-FORMED 1 and PIN1-GFP fusion, Proc. Natl. Acad. Sci. U.S.A. 120 (48) e2312918120, https://doi.org/10.1073/pnas.2312918120 (2023).  We have added the relevant information to Materials and Methods.

(6) The authors measure PIN1 phosphorylation in response to NPY overexpression and conclude that the newly identified phosphorylation sites are inhibitory because they do not overlap with known activating sites. This conclusion is speculative without functional validation. Functional assays are available and must be included to substantiate this claim.

We concluded that the phosphorylation of PINs in NPY1 OE is inhibitory on the basis of the following: 1) pid is suppressed in pin1 heterozygous backgrounds and by PIN1-GFP_HDR, demonstrating that partial loss of function of PIN1 or a decrease in PIN1 gene dosage, which decreases PIN1 protein expression, caused the suppression of pid. 2) pid is completely suppressed by NPY1 OE, which caused an increase of PIN phosphorylation, suggesting that phosphorylation of PINs in NPY1 OE lines is inhibitory.  It is true that we do not have biochemical data to support the conclusion. We would like to point out that the phosphorylation sites in PINs identified in this work do overlap with previously identified sites.

PIN activity assays are conducted in heterologous systems that do not include NPY proteins. Since NPY is important for PIN activities, we believe that these assays may provide misleading results. Moreover, PIN1 is likely part of a large protein complex.  Without knowing the composition of the complex, functional assays in heterologous systems will not be interpretable.

(7) Figure 5 implies that NPY1 acts downstream of PID, but there is no biochemical evidence supporting this hierarchy. Additional experiments are needed to demonstrate the epistatic or regulatory relationship.

We show that overexpression of NPY1 completely suppressed the pid phenotype, and this epistatic relationship indicates that NPY1 functions downstream of PID. Moreover, we report that PID is required for NPY1 accumulation, indicating that PID is upstream of NPY1.

(8) The authors should align their genetic observations with cell biological data on PIN1, PIN2, and PID localization and distribution.

We are hesitating in using traditional PIN1-GFP, PIN2-GFP lines, as they are not stable in our hands. Localization of PID is still not clear. We have generated PID-GFP_HDR lines, but we could not detect any fluorescent signals (unpublished results).  In addition, maize PINOID (BIF2) localizes to the nucleus, cytoplasm and cell periphery (Skirpan, A., Wu, X. and McSteen, P. (2008), Genetic and physical interaction suggest that BARREN STALK1 is a target of BARREN INFLORESCENCE2 in maize inflorescence development. The Plant Journal, 55: 787-797. https://doi.org/10.1111/j.1365-313X.2008.03546.x)

We would rather wait for the proper genetic materials before devoting our effort to this.

Reviewer #2 (Public review):

Summary:

The study is well-conducted, revealing that NPY1, with previously less-characterized molecular functions, can suppress pid mutant phenotypes with a phosphorylation-based mechanism. Overexpression of NPY1 (NPY1-OE) results in PIN phosphorylation at unique sites and bypasses the requirement for PID for this event. Conversely, a C-terminal deleted form of NPY1 (NPY1-dC) fails to rescue pid despite promoting a certain phospho-profile in PIN proteins.

Strengths:

(1) The careful genetic analyses of pid suppression by NPY1-OE and the inability of NPY1dC to do the same.

(2) Phospho-proteomics approaches reveal that NPY1-OE induces phosphorylation of PINs at non-canonical sites, independent of PID.

Thank you for having accurately summarized the main findings

Weaknesses:

(1) The native role of NPY1 is not tested by phospho-proteomics in loss-of-function npy1 mutants. Such analysis would be crucial to demonstrate that NPY1 is required for the observed phosphorylation events.

This is an excellent point and we agree with the reviewer that analyzing loss-of-function npy mutants is important. The challenge is that we need to knockout NPY1, NPY3, and NPY5 to phenocopy pid. We will also need to find a way to suppress the npy triple mutants, which are sterile, so that we can have meaningful comparisons.

(2) The functional consequences of the newly identified phosphorylation sites in PINs remain speculative. Site-directed mutagenesis (phospho-defective and phospho-mimetic) would help clarify their physiological roles.

We agree with the reviewer on this point as well. However, this is not trivial, as we have uncovered so many phosphorylation sites.

(3) The kinase responsible for NPY1-mediated phosphorylation remains unidentified. Since NPY1 is a non-kinase protein, a model involving recruitment of partner kinases (e.g., PIN-phosphorylating kinases other than PID) should be considered or discussed.

we will add a sentence to mention D6PK and other kinases in the Discussion in the revised version.  We are hoping that the kinases will come out of future forward genetic screens.

Reviewer #3 (Public review):

Summary:

This manuscript from Mudgett et al. explores the relative roles of PID and NPY1 in auxin-dependent floral initiation in Arabidopsis. Micro vectorial auxin flows directed by PIN1 are essential to flower initiation, and loss of PIN1 or two of its regulators, PID and NPY1 (in a yucca-deficient background) phenocopies the pinformed phenotype. This group has previously shown that PID-PIN1 interactions and function are dosage-dependent. The authors pick up this thread by demonstrating that a heterozygote containing a CRISPR deletion of one copy of PIN1 can restore quasi-wild type floral initiation to pid.

The authors then show that overexpression of NPY1 is sufficient to more or less restore wild-type floral initiation to the pid mutant. The authors claim that this result demonstrates that NPY1 functions downstream of PID, as this ectopic abundance of NPY1 resulted in phosphorylation of PIN1 at sites that differ from sites of action of PID. The authors pursue evidence that PID action via NPY1 is analogous to the mode of action by which phot1/2 act on NPH3 in seedling phototropism. Such a model is supported by the evidence presented herein that the C terminus of NPY1, which has abundant Ser/Thr content, is phosphorylated, and that the deletion of this domain prevents overexpression compensation of the pinformed phenotype.

While the results presented support evidence in the literature that PID acts on NPY1 to regulate PIN1 function, it is also possible that NPY1 overexpression results in limited expansion of phosphorylation targets observed with other AGC kinases. And if the phot model is any indication, there may be other PID targets that modulate PIN1-dependent floral initiation.

However, overexpression of the NPY1 C-terminal deletion construct resulted in phosphorylation of both PIN1 and PIN2 and agravitropic root growth similar to what is observed in pin2 mutants. This suggests that direct PID phosphorylation of PINs and action via NPY1 can be distinguished by phosphorylation sites and by growth phenotypes.

Strengths:

A very important effort that places NPY1 downstream of PID in floral initiation.

We thank the reviewer for the comments.

Weaknesses:

As PID has been shown to act on sites that regulate PIN protein polarity as well as PIN protein function, it would be useful if the authors consider how their results would fit/not fit with a model where combinatorial function of NPY1 and PID regulate PIN1 in a manner similar to the way that PID appears to function combinatorially with D6PK on PIN3

We agree with the reviewer that we do not have a complete picture of how NPY, PID, PIN work together to control flower initiation. Some aspects of our results are difficult to reconcile with the model of PIN1 and PID acting in tandem, i.e., by PID directly phosphorylating and activating PIN1. Indeed, our results suggest that PIN1 and PID have opposite effects on organogenesis. For example, heterozygous pin1 (or PIN1-GFP_HDR, which is presumably less active than wild type PIN1) suppresses the pid phenotype.  Moreover, pid and pin1 have opposite effects on cotyledon number and true leaf number. Mutations in PID lead to more cotyledons and more true leaves than WT whereas pin1 mutants make fewer cotyledons and fewer true leaves than WT (Bennett SRM, Alvarez J, Bossinger G, Smyth DR (1995) Morphogenesis in pinoid mutants of Arabidopsis thaliana. The Plant Journal 8: 505-520).  We have elaborated on this point in the last paragraph of the Discussion.

The genetic materials we have generated may allow us to uncover additional components in the pathway from forward genetic screens, which may eventually lead to a clear picture.

Briefing sur l'impact de l'IA sur l'enseignement sur France Culture

Ce document de briefing analyse les thèmes principaux, les idées essentielles et les faits importants issus des discussions sur l'intégration de l'intelligence artificielle dans l'éducation.

1. L'IA dans l'enseignement : omniprésence, défis et opportunités

L'IA, en particulier les IA génératives grand public, est déjà massivement présente dans les pratiques des élèves et, dans une moindre mesure, des enseignants.

Selon le ministère de l'Éducation nationale, 80% des élèves et 20% des professeurs utilisent déjà l'IA.

• Usages des élèves : Les élèves utilisent l'IA pour corriger des textes, reformuler des cours, mieux comprendre des notions, trouver des définitions de mots, et parfois pour tricher.

Un élève témoigne : "Je lui demande quand j'ai besoin d'aide pour faire les dissertations de philosophie ou de français. (...) il te mâche un petit peu le travail."

Cependant, il y a aussi une conscience des limites : "parfois il donne des informations fausses et donc faut quand même vérifier si c'est ça ou pas."

Un exemple concret de triche est cité : une élève utilisant une IA lors d'un devoir surveillé pour obtenir les solutions à l'oreille.

• Problèmes cognitifs : Christophe Caillot, professeur d'histoire, souligne que les IA génératives sont "extrêmement problématiques au point de vue cognitif" car elles agissent comme des "courts circuits dans les apprentissages".

Il explique qu'apprendre est un "chemin, un parcours qu'on doit faire assez long chemin d'embûe" et que l'IA "nous empêche d'accéder au savoir aux apprentissages".

• Perte de sens de l'apprentissage : L'usage de l'IA est vu comme "dévalorisant" les apprentissages et posant un "problème anthropologique" en expliquant "qu'on peut se passer d'apprendre dans la vie", ce qui revient à "se passer de ce qui fait un peu le sel de la vie".

• Rôle des IA conçues pour l'éducation : Orian Ledroit, directrice générale d'EdTech France, distingue les IA grand public (comme ChatGPT) des "autres IA qui sont aussi dans les classes mais qui ont été conçus à des fins éducatives et qui n'ont pas ni les mêmes impacts ni les mêmes modèles technologiques et qui sont (...) utiles à des apprentissages qui sont plus stimulants plus personnalisés".

Elle mentionne des études montrant des effets positifs et négatifs selon le contexte, l'accompagnement et les utilisateurs, notamment sur la motivation à apprendre (réduction de la peur de l'échec).

• Manque de recul et de formation : Jada Pistili, docteure en philosophie spécialisée dans l'éthique de l'IA, souligne le manque de recul scientifique pour évaluer les impacts à long terme de ces technologies.

"On est tous un peu des cobaye en fait," dit-elle, insistant sur l'approche "mitigée" nécessaire. Elle mentionne également le manque de formation des enseignants.

2. Le débat sur la personnalisation et le remplacement des enseignants

• L'argument de la personnalisation (EdTech) : Orian Ledroit défend que l'IA peut "donner les moyens aux enseignants (...) d'identifier encore mieux peut-être encore plus facilement les fragilités d'un élève ou au contraire les facilités de l'autre" et ainsi permettre une "différenciation" ou "personnalisation" de l'apprentissage.

Elle affirme que l'IA ne vise pas à remplacer les enseignants mais à "soutenir leur pratique pédagogique".

• La critique de la personnalisation (Syndicat enseignant) : Christophe Caillot rejette l'argument de la personnalisation comme un "argument marketing", expliquant qu'une IA, n'étant pas une personne, "ne peut pas personnaliser".

Il compare les IA éducatives actuelles aux "teaching machines" de Skinner des années 50, qui n'ont pas abouti à une révolution.

Pour lui, la solution aux difficultés des enseignants réside dans l'embauche de personnel humain ("des enseignants, des CPE des AESH des AED et cetera des humains en fait") plutôt que dans l'adoption d'IA qui posent des "problèmes écologiques monstrueux" et sont "fondées sur le pillage des données".

• La peur du remplacement : Le "spectre du remplacement" est une inquiétude majeure chez les enseignants, comme en témoigne la forte participation aux formations syndicales sur le sujet.

Christophe Caillot cite des "expérimentations déjà aux États-Unis en Angleterre en Corée du Sud de classe voire d'école sans prof", y voyant le véritable objectif de ces entreprises : "si ces tech elles veulent exister (...) elles ont besoin à un moment que de prendre la place des enseignants il y a pas d'autres solutions."

• L'enseignant augmenté : Orian Ledroit évoque l'idée d'"augmenter l'enseignant" en automatisant les tâches chronophages qui "ne relèvent pas de la pratique pédagogique", comme la gestion des emplois du temps, la notation, la correction des copies et la préparation des cours.

Christophe Caillot y voit une vision "transhumaniste" qui suggère que les enseignants actuels sont "insuffisants".

3. IA, service public et modèle économique

• Articulation public-privé : Orian Ledroit rappelle que le secteur de l'éducation travaille déjà avec des entreprises privées (ex: manuels scolaires) et que "quand on développe un outil d'intelligence artificielle à des fins éducatives on fait le pari de on investit on fait de la recherche et développement".

L'État, selon elle, prend moins de risques.

Elle insiste sur le fait que les logiciels éducatifs doivent être "conformes à un cadre qui est défini par l'État et notamment qui prévoit le fait d'être conforme à toutes les réglementations européennes en matière de données personnelles RGPD et cetera".

• Critique de la marchandisation de l'éducation : Christophe Caillot dénonce le fait que la tech considère l'éducation comme un "marché parmi d'autres", ce qui est en contradiction avec la vision de l'école comme "service public" et "bien commun".

Il estime que la "recherche du profit rentre en concurrence s'affronte avec la défense du bien commun", citant l'exemple de la privatisation de l'eau.

• Transparence et biais : Jada Pistili suggère que l'Open Source pourrait être une solution pour la "transparence" des systèmes d'IA, notamment concernant les "données d'entraînement" et les "biais" qui en découlent.

Orian Ledroit affirme que les IA éducatives, développées avec des pédagogues, intègrent la correction des biais dès la conception, contrairement aux IA génératives grand public.

Christophe Caillot contredit cette affirmation en citant l'exemple de ChatGPT produisant des interprétations biaisées de la laïcité française.

• Double discours : Jada Pistili observe une "forme d'hypocrisie" et un "double mesure et double poids" dans les politiques publiques : on interdit aux élèves d'utiliser l'IA pour les devoirs, mais on dote les enseignants d'outils basés sur l'IA, ce qui crée un manque de sens pour les élèves.

Elle insiste sur la nécessité d'un "vrai programme, une vraie pédagogie" pour la formation à l'IA des enseignants, afin de ne pas "dénigrer un peu la figure de l'enseignant".

4. Bilan et perspectives

Le débat révèle une tension fondamentale entre le potentiel de l'IA à "bouleverser l'éducation" et les inquiétudes profondes quant à ses implications cognitives, éthiques et sociétales.

• La rapidité du changement : Jada Pistili conclut que "tout va un peu trop vite" et que la société "tâtonne" face à une technologie qui "va transformer plein de domaines".
• L'autonomie des élèves : Christophe Caillot insiste sur la nécessité de "maintenir la capacité de nos élèves des futures générations à ne pas utiliser les IA" et à "maintenir son autonomie par rapport à ses soi-disants outils", plutôt que de les former à les utiliser "de manière névrotique".
• La crise de l'école : Orian Ledroit souligne les défis actuels de l'école publique (reproduction des inégalités, baisse du niveau, manque de profs) et voit l'IA comme un moyen "pragmatique et concret de s'appuyer sur des outils qui ont fait leurs preuves" pour y répondre, en attendant des investissements massifs.

En somme, l'intégration de l'IA dans l'éducation est une réalité complexe, perçue tantôt comme une solution prometteuse pour une personnalisation de l'apprentissage et un allègement des tâches des enseignants, tantôt comme une menace pour le sens de l'apprentissage, l'autonomie des élèves et la nature du service public d'éducation.

Le manque de recul, de formation et de transparence, ainsi que la question de la marchandisation du savoir, sont au cœur des préoccupations.

Is doomscrolling considered play?

I disagree. People could participate in activities such as tournaments, music, and pageants (which Huizing classifies as play) without necessarily doing it voluntarily. They may have been forced by parents or be forced to participate out of a sense of responsibility, and while they are participating in these forms of play, it's not always voluntarily and it's not always out of joy. Yet, it's still play.

It seems that the author classifies merrymaking as forms of play, including masquerades as play. I'm interested to see how other authors write on similar topics as we read more literature and are exposed to more opinions.

I find it interesting how the author situates play as the foundation of civilization. I never considered that play is involved in language. I feel that the author is classifying anything involving imagination or problem-solving as "play" (language, myths, stories, etc). Where is the line drawn for what is play?

This is the author's definition of what play is, but I feel that play does not necessarily have to be social. Sometimes people play games by themselves to pass the time - is that still considered social?

This makes me wonder if play plays a role in forming culture itself. Similar to the chicken or the egg question, does play form culture or does culture form play?

I find this interesting because I also assumed that play is meant to serve some evolutionary function, such as building skills needed to survive in the world. I'm curious to know what everyone's hypotheses are about the function of play. Furthermore, is there a general consensus people have reached about the function of play or is the community divided across theories about the function of play?

ASA y estatinas se recomienda como tratamiento

¿Por qué importa? Porque con orquestación ya logramos resultados “wow”, pero para que sean editables, colaborativos y sostenibles (no demos de una sola vez), necesitamos: estándares para intercambiar contenidos, traspasos sin fricción y trazabilidad clara. Así el salto desde cosas torpes como el viejo clip de Will Smith comiendo spaghetti a piezas cinematográficas no solo se ve mejor, se produce mejor.

Saber quién creó qué, con qué datos y con qué modelo, y mantener esos créditos/consentimientos incrustados en el archivo. Sirve para dar crédito a artistas, gestionar licencias y evitar uso indebido. Técnicamente: metadatos persistentes, “content credentials”, logs de modelo/dataset y, cuando aplique, marcas de agua.

Poder “pasar la posta” de un paso al siguiente sin hacks: un click para enviar tomas, mantener versionado, conservar la línea de tiempo y permitir round-trips (volver atrás, editar y regresar sin romper nada). Esto implica conectores, APIs y plantillas de proyecto coherentes entre generador → editor → render.

Que las apps hablen el mismo idioma. Ejemplos: un formato estándar para la escena (geometría, materiales, cámaras, luces, capas) y otro para el movimiento (keyframes, curvas, esqueletos). Así, si generas un personaje en la herramienta A, lo animas en la B y lo compones en la C, no pierdes nada al exportar/importar (piensa en cosas tipo USD/glTF para escena o BVH/retargeting para movimiento).

Briefing Document: "La Rentrée 2025 pour les élèves de seconde, première et terminale" au Lycée Louis Vincent Ce document synthétise les informations clés et les thèmes principaux abordés lors du YouTube live de rentrée scolaire 2025-2026 du Lycée Louis Vincent.

Date de l'événement: YouTube live de la rentrée scolaire 2025-2026 Intervenants Principaux:

Olivier Palaise, Proviseur du Lycée Louis Vincent Alexianne Bonasso, Proviseure adjointe (BTS et 1ère) Lauren Fortini, Proviseure adjointe (Terminales et examens) Véronique Lefèvre, CPE (Internat) Janny Deico, Président du Conseil des Parents d'Élèves de Moselle (FCPE Moselle) Lionel René, Directeur Délégué sur les formations technologiques et industrielles Sylvie Bontempli, Secrétariat pédagogique 1. Présentation Générale du Lycée Louis Vincent Le Lycée Louis Vincent est un établissement historique, ouvert en 1920, construit par les Allemands, et qualifié d' "impérial" en raison de son envergure. Initialement un lycée technique avec 80% de formations industrielles, il est aujourd'hui un lycée général et technologique, majoritairement général (80% d'enseignement général).

Effectifs: Le lycée compte entre 1500 et 1600 élèves chaque année, avec environ 1580 élèves cette année. 485-486 élèves de seconde Environ 450 élèves de première Environ 450 élèves de terminale Formations BTS et Classes Préparatoires (TSI1, TSI2) Spécificité: Le lycée est réputé pour sa rigueur dans son fonctionnement. Accès: L'entrée principale pour les élèves se fait par le portail métallique bleu de la rue Toule. Les entrées et sorties sont contrôlées, les sacs vérifiés, et les élèves doivent présenter leur livret d'accueil avec photo. Historique Technologique: Le lycée célèbre les 200 ans des formations industrielles de Metz cette année, soulignant son héritage technique et son adaptation aux enjeux actuels (STI2D, STL). 2. Organisation de la Rentrée et Informations Pratiques La rentrée est échelonnée pour les différents niveaux afin de faciliter l'accueil:

Horaires de Rentrée:Secondes: 8h00 Premières: 9h00 Terminales: 9h30 Techniciens supérieurs / Classes prépa TSI1, TSI2: 10h00 / 8h30 Internat: Les internes sont attendus le dimanche soir (sauf rares exceptions le lundi matin). Une réunion pour les parents d'internes est prévue le dimanche soir à 20h30 en salle d'honneur. Pour l'internat d'excellence, l'accueil des parents est à partir de 16h, avec une réunion à 16h30 en présence de l'adjoint du commandant de la caserne CRS. Affichage des classes: Les classes seront affichées dans la cour. Il est noté que des "fuites" informatiques permettent parfois aux élèves et parents de connaître les classes à l'avance. Premières Réunions de Parents:Terminales: 8 septembre à 18h en salle d'honneur Premières Générales: Mercredi 10 septembre à 18h en salle d'honneur Premières et Terminales Technologiques: Vendredi 12 septembre à 18h en salle d'honneur Secondes: Réunion générale en salle d'honneur à 18h, suivie d'une répartition par classe avec les professeurs principaux à 18h30 pour discuter des attentes du lycée. Réunion d'explication de fonctionnement du lycée (ouverte à tous les parents): Vendredi 5 septembre à 18h en salle d'honneur. Emplois du temps: Les emplois du temps standard sont opérationnels dès le lundi 14h. Les parents sont invités à les consulter régulièrement via Pronote. Casiers: Attribution limitée, réservée aux demandes particulières (difficultés à porter des charges lourdes, problèmes médicaux). 3. Le Projet Lycée 4.0 et le Numérique La Région Grand Est met en œuvre le projet "Lycée 4.0", un projet pédagogique sur l'informatique et le numérique.

Distribution d'ordinateurs: Tous les nouveaux élèves (secondes, et autres classes s'ils ne proviennent pas d'un lycée de la région) recevront un ordinateur portable offert par la Région. La distribution aura lieu dès le lundi de la rentrée pour les secondes. Il est recommandé de ne pas ouvrir l'ordinateur immédiatement pour éviter tout dommage et de conserver le carton d'emballage pour la garantie. L'ordinateur est prêté pour les trois années (seconde, première, terminale) et pourra être conservé à l'issue de la 3ème année, sauf si l'élève quitte la Région Grand Est. Usage de l'ordinateur:Le lycée est entièrement équipé de Wifi. Les manuels scolaires sont numériques et fournis gratuitement par la Région (licences incluses). L'installation des logiciels et manuels sera encadrée par les professeurs de SNT (Sciences Numériques et Technologiques) durant la première semaine. Mise en garde: Il est fortement déconseillé d'installer des jeux sur l'ordinateur, car "c'est pas un ordinateur qui est prévu pour jouer, c'est un ordinateur qui est prévu pour les manuels scolaires pour aller faire des recherches pour internet et cetera". Tests de Positionnement: Les ordinateurs devront être opérationnels dès la deuxième semaine pour les tests de positionnement. Autres ressources numériques:Compte EduConnect: Permet l'accès à "Mon Bureau Numérique", aux notes (Pronote), au cahier de texte, aux procédures d'orientation et aux bourses. Les comptes EduConnect sont les mêmes que ceux utilisés au collège. Il est annoncé que les classes et emplois du temps seront accessibles via "Mon Bureau Numérique" dès le lendemain de la réunion. Compte Wifi Grand Est: Sera distribué aux élèves à la rentrée. Office de Microsoft: Fourni gratuitement avec des comptes spécifiques. Application Pronote et ScolenGo: Pronote sera la référence pour les emplois du temps. Les informations du cahier de texte seront sur Mon Bureau Numérique (ScolenGo). Les notes seront également sur Pronote. 4. Résultats Scolaires et Exigences Le lycée affiche de "très bons voire excellents" résultats, fruit du travail des élèves et des équipes éducatives.

Résultats BTS (session 2025):Métiers de la Chimie: 100% de réussite (en augmentation constante depuis 4 ans). SIRA: 67% CPI: 91% CPRP: 80% CRSA: 90% Moyenne des BTS: environ 88% de réussite. La classe prépa technologique (STI2D, STL SPCL) permet l'intégration en écoles d'ingénieurs. Résultats Baccalauréat (session juin 2025):Baccalauréat Général: Supérieur à 95% de réussite, 74% de mentions. Filières Technologiques (STI2D, STL): Supérieur à 95% de réussite. STI2D: 57% de mentions. STL: 66% de mentions. Parcoursup: Tous les élèves ont obtenu une réponse sur Parcoursup. Calculatrices: Une calculatrice spécifique et programmable est requise pour les épreuves de baccalauréat (mathématiques, physique). Une procédure de commande groupée est mise en place via les professeurs de mathématiques, avec un lien disponible sur le site du lycée jusqu'au 10 septembre. Épreuve Anticipée de Mathématiques (EAM) en Première: Nouveauté cette année, cette épreuve aura lieu en juin (2h écrite, avec une partie orale). Les sujets sont adaptés selon que l'élève suit la spécialité mathématiques ou l'enseignement mathématique obligatoire. Exigence et Bienveillance: Le lycée insiste sur la "certaine exigence au niveau travail [et] au niveau cadre de vie scolaire". Respect des adultes, pas de cris dans les couloirs. Téléphones portables: Interdits d'utilisation dans les bâtiments, sauf autorisation d'un adulte. L'ordinateur portable sera privilégié en classe. Absences et Retards: Une rigueur est demandée. Les retards dus aux transports scolaires sont à anticiper. Les absences doivent être justifiées, mais une vigilance est demandée aux parents sur les motifs réels. "on est exigeant tout en étant bienveillant". Ouverture du Lycée: Du lundi au vendredi de 7h30 à 18h30. Les cours commencent à 8h. Samedi Matin: Le lycée est ouvert 24 samedis par an pour "devoirs de rattrapage, rattrapage de devoirs, colle, etc." En cas de non-respect du règlement (ex: utilisation du portable dans les couloirs), des "colles" de 3h le samedi matin sont appliquées. 5. Soutien Scolaire et Orientation Accompagnement Personnalisé (AP): Des séances (environ 27 par an) sont proposées en mathématiques, physique et français (ou philosophie en terminale) en seconde, première et terminale. Ces aides ciblent des groupes d'environ 5 élèves. Préparation aux examens: Des exercices de simulation, notamment pour le "Grand Oral" (avec sollicitation des parents pour faire partie des jurys, ex: avocats). Accompagnement à l'Orientation: Réalisé par les professeurs principaux en seconde, première et terminale, axé sur la méthodologie et les informations Parcoursup. Psy-EN: Il est fortement recommandé aux élèves de terminale de prendre rendez-vous avec les psychologues de l'Éducation Nationale ("psy-EN") dès le premier trimestre, car leur planning est très chargé en fin d'année. Parcoursup: Présenté comme un "outil" et non comme la source de la complexité de l'orientation. Les élèves sont encouragés à créer leurs comptes Parcoursup dès la seconde et à explorer les formations. Pix: Certification d'usage du numérique, obligatoire pour toutes les terminales avant le baccalauréat, utile pour Parcoursup. SNU (Service National Universel): Les élèves de seconde peuvent y participer et cela peut remplacer les stages de seconde. 6. Restauration Scolaire et Aides Financières Accès Cantine: Possible dès la rentrée pour les demi-pensionnaires inscrits. Les élèves externes pourront également manger, mais la procédure administrative sera "un peu plus complexe". Tarifs: Complexité des tarifs en raison des aides régionales. Internat: L'hébergement est "gratuit" (coût de 10€, mais équivaut à une aide de 1200€), mais les repas sont payants (environ 1400€ pour l'internat complet). Demi-pension: Coût global d'environ 650€ à l'année pour un élève standard. Aides Régionales (ARS): Une aide de 20 centimes par repas est proposée aux familles non boursières mais dont les revenus sont juste au-dessus du seuil, ce qui représente environ 100€ de réduction annuelle. Fonds Sociaux: Disponibles pour les familles en difficulté (pré-bac). S'adresser aux professeurs, CPE, proviseures adjointes, gestionnaires, ou au secrétariat élève. Une adresse mail dédiée: fondsocial@ellvmes.fr. 7. Communication et Événements Info Parents: Toutes les informations sont régulièrement envoyées par mail via ce canal. Projet d'établissement et Plan d'évaluation: Documents communiqués aux parents pour présenter les objectifs et le fonctionnement des évaluations. Journée du Patrimoine: 20 septembre, occasion de visiter l'établissement (ateliers, vue depuis le clocher). Fête de la Science: Octobre. 8. Représentants de Parents d'Élèves L'importance de la participation des parents est fortement soulignée, à tous les niveaux: conseils de classe et conseil d'administration. Les élections se feront par voie numérique (Pronote).

Deux associations présentes: FCPE et PEEP. Réunions d'information pour les associations:PEEP: Mardi 9 septembre à 18h30 en salle d'honneur. FCPE: Jeudi 11 septembre à 18h30 en salle d'honneur. Rôle des Parents Élus:Accompagner les enfants dans leur parcours scolaire. Faire valoir les droits et représenter les parents et les enfants. Donner un avis sur les décisions pédagogiques et financières. Rôle de médiateur. FCPE (Janny Deico, Président FCPE Moselle): Association de 75 ans, défend les valeurs d'une "école publique gratuite, inclusive et laïque". Propose des formations aux parents élus pour les aider à intervenir efficacement. Participation aux Conseils de Classe: Il est essentiel d'avoir des parents formés et de représenter tous les enfants. Deux parents par conseil de classe sont nécessaires (84 parents pour 42 classes). 9. Infrastructures et Projets Abri Vélo Connecté: Un nouvel abri vélo autonome et connecté a été installé, équipé de panneaux solaires photovoltaïques pour recharger les vélos électriques et trottinettes. Il s'intègre à l'architecture en bois et permet de suivre la production et consommation d'énergie, promouvant la mobilité douce et le développement durable (STID2D). Il comprend également un espace personnel pour les élèves avec tables en bois pour recharger téléphones et ordinateurs. Travaux futurs: Des travaux sont prévus devant l'établissement dans le cadre du projet "Métis", visant à créer un espace piéton plus grand, moins de parkings et de voitures. L'ancien site de l'hôpital Bonsecours a déjà été transformé en appartements. Dangérosité du carrefour: Vigilance demandée aux élèves concernant le carrefour devant le lycée, très fréquenté. Interdiction de fumer: Il est interdit de fumer aux abords de l'établissement, y compris sur la placette de la rue Toule. Visite virtuelle: Une vidéo montre les locaux intérieurs (escalier monumental, loge, bureaux de la vie scolaire, CPE, secrétariat élèves, proviseures adjointes, salle des professeurs, CDI, salle de permanence, salle d'honneur, couloirs des salles de classe, bureau des Psy-EN, service informatique). Il est précisé que le lycée est entièrement accessible aux PMR (ascenseur). 10. Conclusion Le Lycée Louis Vincent se présente comme un établissement à la fois historique et moderne, axé sur la réussite de chaque élève, l'exigence bienveillante, l'innovation numérique et la collaboration avec les familles. Les équipes se tiennent à disposition pour accompagner les élèves et les parents tout au long de l'année scolaire.

Document de Synthèse : Réflexions sur l'Éducation, le Savoir et l'Intelligence selon Bernard Lahire

• Ce document de synthèse présente les idées principales et les faits marquants des extraits de l'interview de Bernard Lahire, sociologue et directeur de recherche au CNRS, à l'occasion de la publication de son livre "Savoir ou périr".

L'entretien explore la nature de l'apprentissage, le rôle de l'école et de l'évaluation, la définition de l'intelligence, la recherche scientifique et la transmission du savoir dans nos sociétés contemporaines.

1. Le Savoir comme Condition de Survie et l'Origine de l'École

Bernard Lahire insiste sur une perspective fondamentale : l'apprentissage et la transmission des savoirs sont intrinsèquement liés à la survie de toute espèce vivante, y compris l'espèce humaine.

• Survie et Adaptation : "Nos sociétés ne fonctionneraient pas, ne survivraient pas si elle n'organisait pas cet apprentissage."

L'apprentissage est une capacité d'adaptation essentielle, présente chez toutes les espèces. Un animal qui n'apprend pas à reconnaître ses prédateurs ne survit pas.

• L'Apprentissage Humain : Chez l'homme, l'apprentissage est extrêmement développé, allant de l'apprentissage social par imitation à l'enseignement organisé, complété par le langage.

• L'Émergence de l'École : L'école, en tant qu'institution dédiée à l'apprentissage, est une invention relativement tardive dans l'histoire de l'humanité (XVIe siècle au sens moderne).

Avant, la transmission se faisait "par voir faire et ouï-dire", via la culture orale.

L'écriture, apparue il y a environ 5000 ans, a permis d'objectiver et d'accumuler le savoir, rendant possible son organisation pédagogique et l'institutionnalisation de l'école.

• La Sophistication du Savoir : La complexification et la division des savoirs dans nos sociétés modernes ont rendu l'école indispensable et allongé les parcours scolaires.

La survie collective repose sur une masse considérable de savoirs sophistiqués, gérés par des corps de professionnels divers.

2. La Recherche de la Vérité et la Vulnérabilité du Savoir

Lahire aborde la nécessité de la vérité et les dangers de l'affaiblissement des institutions du savoir.

• La Vérité comme Nécessité Vitale : La vérité n'est pas qu'une question philosophique, c'est une condition de survie.

"Si nos savoirs d'ailleurs avant même les savoirs scientifiques… avaient été faux… ça fait longtemps qu'on aurait disparu."

Même les savoirs empiriques anciens devaient avoir un rapport minimal à la vérité pour permettre aux sociétés de survivre face aux fléaux naturels et aux maladies.

• Le Suprême Pouvoir et la Vulnérabilité : La division du travail et des connaissances a rendu l'humanité "surpuissante" en permettant des réalisations complexes comme le téléphone portable.

Cependant, attaquer les lieux de transmission et de création culturelle (recherche, éducation) est une forme de "suicide collectif".

• L'Attaque contre la Recherche : Des coupes budgétaires dans la recherche, la limitation du nombre de chercheurs ou l'exigence de rentabilité immédiate sont des freins à la production de nouveaux savoirs.

"À chaque fois qu'on affaiblit ces secteurs bah on se rend pas compte de tout ce qui serait possible."

La recherche, par nature, est imprévisible et ses applications ne peuvent pas toujours être anticipées à court terme.

3. L'École et la Destruction de la Curiosité et de l'Intelligence

Lahire critique vivement le système scolaire actuel, qui, selon lui, entrave les dispositions naturelles des enfants.

• La Curiosité Innée : Les enfants sont naturellement curieux, testant et explorant leur environnement par l'expérimentation et les questions.

Cette "pulsion exploratrice" est une disposition naturelle.

• L'École, Frein à la Curiosité : Le système scolaire, avec sa discipline collective, ses programmes surchargés et surtout l'évaluation constante, tend à étouffer cette curiosité.

"L'évaluation devient quelque chose qui bloque en fait la curiosité des enfants."

• Le Piège de l'Évaluation : L'évaluation est censée vérifier l'apprentissage, mais elle est devenue un objectif en soi, inversant la logique.

Les élèves apprennent "pour pouvoir passer un contrôle", ce qui nuit à un apprentissage profond et désintéressé.

• Les Mathématiques, Instrument de Sélection : Les mathématiques, une discipline intrinsèquement incroyable, sont devenues un "instrument de torture", un "perfouettard" pour la sélection scolaire, ce qui génère de l'aversion chez les élèves.

• Nuire à la Créativité : L'école, en privilégiant la reproduction des connaissances transmises, laisse peu de place à l'imagination et à la créativité.

Les artistes, par exemple, ont souvent un rapport "très contrarié à l'école", perçue comme un lieu de mémorisation rigide plutôt que de stimulation créative.

• La Docilité des Bons Élèves : Le système sélectionne des élèves qui sont de bons reproducteurs des savoirs scolaires, mais paradoxalement, ils ne sont pas toujours les mieux placés pour la recherche qui demande de la rébellion intellectuelle.

"Quand on a été trop bon élève, on est aussi très docile."

4. L'Intelligence au-delà du QI et les Voies de la Recherche

Lahire propose une vision plus large de l'intelligence et met en lumière les qualités du "vrai chercheur".

• L'Intelligence comme Capacité d'Adaptation : L'intelligence n'est "certainement pas ce que mesure un quotient intellectuel".

C'est avant tout "des capacités d'adaptation, c'est résoudre des problèmes".

Cette forme d'intelligence est présente "un peu partout dans le vivant", des plantes aux unicellulaires.

• L'Intelligence Créatrice : L'intelligence créatrice, notamment artistique, implique d'inventer des formes et des regards nouveaux, ce qui ne correspond pas aux critères d'évaluation académiques standards.

• Le Vrai Chercheur : Un vrai chercheur est "un sale gosse", "un peu rebelle", qui ose poser des questions "stupides" et aller au-delà des demandes.

Il faut "retrouver l'enfant qui est en nous" et ne pas se laisser impressionner, comme le souligne le mathématicien Alexandre Grothendieck.

• Exemples Notables : Des figures comme Einstein ou Grothendieck, malgré leur génie, ont eu un rapport difficile avec l'école ou le système académique, qui pouvait freiner leur curiosité et leur capacité à prendre du recul.

Grothendieck distinguait les mathématiciens "caseurs" (qui travaillent à l'intérieur d'une maison déjà faite) des "bâtisseurs" (qui reconstruisent les fondations).

5. Une Éducation Rationnelle et Collective : Propositions et Défis

Lahire esquisse des pistes pour une réforme de l'éducation.

• Respecter la Curiosité : Il faut s'appuyer sur la curiosité naturelle des enfants, l'accompagner et l'alimenter, plutôt que de la briser.

Des pédagogies comme celle de Freinet, avec des "leçons de choses" concrètes, sont des exemples positifs.

• Alléger les Programmes et Donner du Temps : Les programmes scolaires sont surchargés, rendant impossible un apprentissage approfondi.

Il est crucial de donner "le temps" aux enseignants et aux élèves pour l'approfondissement, car l'assimilation des connaissances demande du temps. "Terminer un programme ça n'a aucun sens."

• Lutter contre les Inégalités Sociales : Les enfants ne sont pas égaux devant l'école, car les "déterminismes sociaux" jouent un rôle majeur.

Les enfants de milieux favorisés bénéficient d'interactions culturelles et pédagogiques précoces qui les avantagent considérablement.

Il faut des politiques de compensation, donner "plus à ceux qui ont moins", en réduisant par exemple la taille des groupes pour les élèves en difficulté.

• Recherche de Synthèse : La spécialisation excessive des sciences, notamment sociales, rend difficile une vision systémique.

Il est nécessaire de développer des pôles de "synthétisation" et de faire des liens entre les différentes branches du savoir, à l'image des grands "synthétiseurs" comme Newton, Einstein ou Darwin.

• Critique des Classements : Les classements comme PISA ou Shanghai sont jugés peu pertinents.

Ils alimentent une "concurrence internationale" mais "n'ont jamais servi à améliorer en de quelque manière que ce soit le système éducatif", car ils ne s'attaquent pas aux causes profondes des problèmes.

6. L'Altricialité Secondaire et le Développement Culturel

Lahire fait le lien entre la biologie humaine et la nécessité de l'apprentissage.

• Dépendance Prolongée : L'espèce humaine se caractérise par une "altricialité dite secondaire", c'est-à-dire une longue période de dépendance des petits envers les parents. Cette vulnérabilité prolongée a accru la durée de l'apprentissage.

• Entrelacement Biologique et Culturel : Le développement physiologique de l'enfant est intimement lié à son développement culturel et social.

Apprendre à grandir dans une société humaine ne se limite pas à la maturité biologique, mais englobe l'acquisition d'une grande quantité de savoirs, notamment la lecture, l'écriture et le calcul, bases essentielles de la scolarisation précoce.

• En conclusion, Bernard Lahire dresse un tableau critique mais lucide du système éducatif actuel, en le replaçant dans une perspective biologique et historique.

Il plaide pour une réorientation profonde, qui remette la curiosité, l'approfondissement et la justice sociale au cœur des processus d'apprentissage et de création du savoir, conditions essentielles à la survie et à l'épanouissement collectif de l'humanité.

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Los principales sistemas que se encargan del metabolismo de los fármacos son las enzimas, y estas pueden ser activadas o inducidas, así mismo, otros fármacos pueden influenciar la actividad de dicha enzima, ya sea mejorándola o disminuyendo su capacidad enzimática si otro fármaco usa la misma enzima para metabolizarse

El sistema que se encarga de metabolizarlo se satura. Esto significa que, sin importar cuánto fármaco haya, el cuerpo solo puede metabolizar una cantidad fija y constante por unidad de tiempo

La concentración del fármaco en su sitio de acción llega a saturarse, lo que hace que el resto del fármaco suspendido en la sangre se redistribuye en los tejidos a manera de "reserva" y una vez las concentraciones en el sitio diana disminuyen de nuevo, se liberan del tejido a la circulación para poder ser absorbido en el sitio diana, lo que prolonga el efecto a lo largo del tiempo.

En los pacientes con obesidad, el fármaco puede almacenarse durante periodos más largos, en el caso de anestésicos generales, como por ejemplo el propofol, el periodo durante el que se libera el fármaco se extiende notablemente, causado en parte por el gran almacenamiento en tejido graso y por las altas dosis ponderadas administradas.

Author response:

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

Reviewer #1 (Public review):

Summary:

In this manuscript, Liu et al have tried to dissect the neural and molecular mechanisms that C. elegans use to avoid digestion of harmful bacterial food. Liu et al show that C. elegans use the ON-OFF state of AWC olfactory neurons to regulate the digestion of harmful gram-positive bacteria S. saprophyticus (SS). The authors show that when C. elegans are fed on SS food, AWC neurons switch to OFF fate which prevents digestion of S. saprophyticus and this helps C. elegans avoid these harmful bacteria. Using genetic and transcriptional analysis as well as making use of previously published findings, Liu et al implicate the p38 MAPK pathway (in particular, NSY-1, the C. elegans homolog of MAPKKK ASK1) and insulin signaling in this process.

Strengths:

The authors have used multiple approaches to test the hypothesis that they present in this manuscript.

Weaknesses:

Overall, I am not convinced that the authors have provided sufficient evidence to support the various components of their hypothesis. While they present data that loosely align with their hypothesis, they fail to consider alternative explanations and do not use rigorous approaches to strengthen their overall hypothesis. The selective picking of genes from the RNA sequencing data and forcing the data to fit the proposed hypothesis based on previously published findings, without exploring other approaches, indicates a lack of thoroughness and rigor. These critical shortcomings significantly diminish enthusiasm for the manuscript in its totality. In my opinion, this is the biggest weakness in this manuscript.

We appreciate the reviewer’s all the suggestions which help us to improve this paper. We now addressed reviewer’s comments at the section of “Reviewer #1 (Recommendations for the authors)”

Reviewer #2 (Public review):

Summary:

Using C. elegans as a model, the authors present an interesting story demonstrating a new regulatory connection between olfactory neurons and the digestive system.

Mechanistically, they identified key factors (NSY-1, STR-130 et.al) in neurons, as well as critical 'signaling factors' (INS-23, DAF-2) that bridge different cells/tissues to execute the digestive shutdown induced by poor-quality food (Staphylococcus saprophyticus, SS).

Strengths:

The conclusions of this manuscript are mostly well supported by the experimental results shown.

Weaknesses:

Several issues could be addressed and clarified to strengthen their conclusions.

(1) The word "olfactory" should be carefully used and checked in this manuscript. Although AWCs are classic olfactory neurons in C. elegans, no data in this manuscript supports the idea that olfactory signals from SS drive the responses in the digestive system. To validate that it is truly olfaction, the authors may want to check the responses of worms (e.g. AWC, digestive shutdown, INS-23 expression) to odors from SS.

We appreciate the reviewer’s careful attention to terminology. We agree that the term "olfactory" requires direct experimental validation. However, in this paper, we only used "olfactory" to specific define the AWC neurons. As reviewer’s suggestion, we now deleted the word “olfactory”.

(2) In line 113, what does "once the digestive system is activated" mean? The authors need to provide a clearer statement about 'digestive activation' and 'digestive shutdown'.

Previously, we observed that activating larval digestion with heat-killed E. coli or E. coli cell wall peptidoglycan (PGN) enabled the digestion of SS as food (Hao et al., 2024). Additionally, when animals reached the L2 stage by feeding normal OP50 diet, they could utilize SS as a food source to support growth (Figure 1—figure supplement 1D). These findings suggest that once digestion is activated (via E. coli components or L2-stage maturation), worms gain the capacity to process SS as a viable food source, abolishing SS-induced growth impairment (Hao et al., 2024) ( Figure 1—figure supplement 1D).

(3) No control data on OP50. This would affect the conclusions generated from Figures 2A, 2B, 2D, 3B, 3C, 3G, 4D-G, 5D-E, 6B-D.

We appreciate  this point. The central goal of the experiments listed (Figures 2A,B,D; 3B,C,G; 4D-G; 5D-E; 6B-D) was not to compare growth or behavior between SS and OP50 under standard conditions, but rather to understand the genetic basis of the C. elegans response specifically to SS, as identified through our nsy-1 mutant screen.

Our data in Figure 1 clearly establishes the fundamental difference in growth and feeding behavior when larvae encounter SS compared to OP50 (Figures 1A,B). Having established SS as an unfavorable food source that triggers a specific protective response (digestive shutdown), the subsequent experiments focus on deciphering how this response is mediated.

Therefore, within these specific experimental contexts under SS feeding: The primary comparison is between wild-type (N2) and nsy-1 mutant animals. All assays (growth, behavior, survival) are performed under the same SS feeding conditionsfor both genotypes.

This design allows us to directly assess the functional role of NSY-1 in mediating the SS-specific response pathway we are investigating. Including an OP50 control for every figure would not address this core genetic question and could introduce confounding variables given the established difference in how C. elegans treats these two food sources. The critical internal control for these specific experiments is the performance of the wild-type under SS versus the mutant under SS.

(4) Do the authors know which factors are released from AWC neurons to drive the digestive shutdown?

Enrichment analysis revealed that genes related to extracellular functions, such as insulin-related genes, are induced in nsy-1 mutant animals (Figure 5—figure supplement 1A, Supplementary file 4). Further analysis of insulin-related genes from the RNA-seq data showed that ins-23 is predominantly induced in nsy-1 mutant animals (Figure 5—figure supplement 1B), suggesting its potential role in promoting SS digestion. We found that knockdown of ins-23 in nsy-1 mutants inhibited SS digestion (Figure 5D). Given that INS-23 is expressed in AWC neurons (Figure 5—figure supplement 3A, CeNGEN), this suggests increased production and likely enhanced release of INS-23 from AWC neurons in the nsy-1 mutant background, which promotes SS digestion.

The insulin/insulin-like growth factor signaling (IIS) pathway, particularly through the DAF-2 receptor, integrates nutritional signals to regulate various behavioral and physiological responses related to food (Kodama et al., 2006; Ryu et al., 2018). It has been shown that INS-23 acts as an antagonist for the DAF-2 receptor to promote larval diapause (Matsunaga et al., 2018). To test whether ins-23 induction in nsy-1 mutants promotes SS digestion through its receptor, DAF-2, we constructed a nsy-1; daf-2 double mutant. We found that the SS digestion ability of the nsy-1 mutant was inhibited by the daf-2 mutation. This suggests that the nsy-1 mutation induces the insulin peptide ins-23, which promotes SS digestion through its potential receptor, DAF-2.

The data supports a model where AWC neurons regulate digestion via the release of INS-23. Loss of nsy-1 function increases INS-23 release from AWC, activating DAF-2 signaling and promoting digestion. Conversely, in wild-type animals, reduced INS-23 release from AWC contributes to digestive shutdown in response to SS food.

Reviewer #3 (Public review):

Summary:

The study explores a molecular mechanism by which C. elegans detects low-quality food through neuron-digestive crosstalk, offering new insights into food quality control systems. Liu and colleagues demonstrated that NSY-1, expressed in AWC neurons, is a key regulator for sensing Staphylococcus saprophyticus (SS), inducing avoidance behavior and shutting down the digestive system via intestinal BCF-1. They further revealed that INS-23, an insulin peptide, interacts with the DAF-2 receptor in the gut to modulate SS digestion. The study uncovers a food quality control system connecting neural and intestinal responses, enabling C. elegans to adapt to environmental challenges.

Strengths:

The study employs a genetic screening approach to identify nsy-1 as a critical regulator in detecting food quality and initiating adaptive responses in C. elegans. The use of RNA-seq analysis is particularly noteworthy, as it reveals distinct regulatory pathways involved in food sensing (Figure 4) and digestion of Staphylococcus saprophyticus (Figure 5). The strategic application of both positive and negative data mining enhances the depth of analysis. Importantly, the discovery that C. elegans halts digestion in response to harmful food and employs avoidance behavior highlights a physiological adaptation mechanism.

Weaknesses:

Major points:

(1) While NSY-1 positively regulates str-130 expression in AWC neurons and is critical for SS avoidance and survival, the authors should examine whether similar phenotypes are observed in str-130 mutants.

In this study, we mainly focused on how worms sense adverse food sources (SS food) and shutdown digestion (not growth as digestion shutdown readout). We found that nsy-1 in AWC play key roles in response SS food, once nsy-1 mutation, mutant animals cannot detect SS food and digest it, therefore growth under SS food. From RNA-seq, we found that nsy-1 positively regulates several sensory perception related genes (sra-32, str-87, str-112, str-130, str-160, str-230) (Figure 4—figure supplement 1A, Supplementary file 2). After screen, we found that we found that knockdown of str-130 in wild-type animals promoted SS digestion, thereby supporting animal growth (Figure 4D), and the proportion of animals with two AWC^OFF neurons decreased (Figure 4E). Secondly, we found that overexpression of str-130 in nsy-1 mutant animals inhibited SS digestion, thereby slowing animal growth (Figure 4F), and the proportion of animals with two AWC^OFF neurons increased (Figure 4G). These results demonstrate that NSY-1 promotes the AWC^OFF state by inducing str-130 expression, which in turn inhibits SS digestion in C. elegans.

(2) NSY-1 promotes the AWC-OFF state through str-130, inhibiting SS digestion. The authors should investigate whether STR-130 in AWC neurons regulates bcf-1 expression levels in the intestine.

We agree with the reviewer's suggestion regarding the potential role of STR-130 in AWC neurons regulating intestinal bcf-1 expression. To address this, we generated transgenic worms with AWC-specific knockdown of str-130, achieved by rescuing sid-1 cDNA expression under the ceh-36 promoter (AWC-specific) in sid-1(qt9);BCF-1::GFP background worms.

We observed that AWC neuron-specific RNAi of str-130 elevated intestinal BCF-1::GFP expression (Figure 6—figure supplement 1B). This demonstrates that STR-130 functions cell-non-autonomously in AWC neurons to repress BCF-1 expression in the intestine.

(3) The current results rely on str-2 expression levels to indicate the AWC state. Ablating AWC neurons and testing the effects on digestion would provide stronger evidence for their role in digestive regulation.

To confirm the important of AWC state in SS digestion, we performed AWC-specific neuron ablation experiments using previously validated transgenic strain that expresses cleaved caspase under the AWC-specific promoter, ceh-36 (ceh-36p::caspase). Critically, worms with ablated AWC neurons completely failed to digest SS food (Figure 3—figure supplement 4), phenocopying the non-digesting state of wild-type worms on SS when AWC-OFF signaling is impaired. This result directly confirms that functional AWC neurons are essential for initiating SS digestion, aligning with our model where the AWC-OFF state (induced by SS) inhibits digestion while the AWC-ON state promotes it.

Furthermore, we previously study discovered that AWC ablation activates the intestinal mitochondrial unfolded protein response and inhibits food digestion, mechanistically linking neuronal integrity to gut stress responses and digestive inhibition.

Together, these functional ablation studies provide compelling physiological evidence that AWC neurons act as central regulators of food-state sensing and gut function.

(4) The claim that NSY-1 inhibits INS-23 and that INS-23 interacts with DAF-2 to regulate bcf-1 expression (Line 339-340) requires further validation. Neuron-specific disruption of INS-23 and gut-specific rescue of DAF-2 should be tested.

We agree with the reviewer that the proposed NSY-1 ⊣ INS-23 → DAF-2 → BCF-1 signaling axis requires tissue-specific validation. To address this, we conducted compartment-specific functional dissection of INS-23 and DAF-2:

AWC neuronal role of INS-23:

To test whether INS-23 acts in AWC neurons to regulate intestinal BCF-1, we generated AWC-specific knockdown strains which was achieved by rescuing sid-1 cDNA expression under the ceh-36 promoter in a sid-1(qt9);BCF-1::GFP background. We found that AWC-restricted ins-23 knockdown significantly reduced intestinal BCF-1::GFP expression (Figure 6—figure supplement 1A). This confirms that INS-23 functions cell-non-autonomously within AWC sensory neurons to activate intestinal BCF-1, consistent with NSY-1’s upstream inhibition of INS-23 in this neuronal  subtype

Intestinal role of DAF-2 as INS-23 receptor:

To investigate weather DAF-2 acts as the gut-localized receptor for neuronal INS-23 signaling, we performed tissue-specific rescue experiments in the nsy-1(ag3);daf-2(e1370) double mutant. When DAF-2 was re-introduced specifically in the intestine (using the ges-1 promoter), we observed a significant suppression of SS digestion (Figure 5—figure supplement 3B), but not rescue digestive defect. This indicates that INS-23 induction in nsy-1 mutants promotes digestion independently of intestinal DAF-2 function.

(5) Figure Reference Errors: Lines 296-297 mention Figure 6E, which does not exist in the main text. This appears to refer to Figure 5E, which has not been described.

We corrected this.

Reviewer #1 (Recommendations for the authors):

I would like the authors to address the following comments in a resubmission.

(1) The hallmark of the activated p38 MAPK pathway is the phosphorylation of most downstream kinase p38 (PMK-1/PMK2 in C. elegans) of this kinase cascade. Previous work from Bergmann lab showed that the most downstream kinase of this pathway, PMK-1/PMK-2, is not required for AWC asymmetry. I wonder whether that is the case also for the model that Liu et al have presented in this manuscript. Since p38/PMK-1 undergoes activation (phosphorylation) in response to pathogenic bacteria like P. aeruginosa, it is worth testing whether PMK-1 plays a role downstream of NSY-1 in the model that Liu et al present in this manuscript. It would be worth testing whether there is increased phosphorylation of p38 when C. elegans are fed SS and whether that phosphorylation regulates downstream components that Liu et al have identified in this manuscript.

We thank the reviewer for raising this important point regarding PMK-1/p38 MAPK signaling. As established in our prior work (Reference 1), SS exposure triggers phosphorylation of PMK-1 (P-PMK-1) in C. elegans, and pmk-1 mutants exhibit enhanced growth on SS (Figure-1, Figure-2). This confirms that PMK-1-mediated innate immune signaling actively regulates SS responsiveness and digestion.

To address whether PMK-1 functions downstream of NSY-1 within our proposed model, we performed critical epistasis analyses. While we observed that nsy-1 mutation elevates ins-23 (indicating NSY-1 suppression of ins-23), knockdown of pmk-1 did not alter ins-23 expression levels (Figure 5-figure supplement 3C). This demonstrates that PMK-1 does not operate through the ins-23 pathway to regulate SS digestion. Thus, although both pathways respond to SS, the PMK-1-mediated innate immune response and the NSY-1/INS-23 axis constitute distinct regulatory mechanisms governing digestive adaptation.

Reference 1: Geng, S., Li, Q., Zhou, X., Zheng, J., Liu, H., Zeng, J., Yang, R., Fu, H., Hao, F., Feng, Q., & Qi, B. (2022). Gut commensal E. coli outer membrane proteins activate the host food digestive system through neural-immune communication. Cell host & microbe, 30(10), 1401–1416.e8. https://doi.org/10.1016/j.chom.2022.08.004

(2) Since p38 MAPK pathway has a well-established role in host defense in the C. elegans intestine, it is important to show that NSY-1 does not function in the intestine in the model that Liu et al present. I would like the authors to reintroduce nsy-1 in C. elegans intestine in nsy-1 mutant animals and then test whether it has any effect on worm length on SS food (similar to what is done in Figure 3 for AWC-specific nsy-1).

Beyond its  established  role  in  AWC  neurons,  we  detected  NSY-1 expression in the intestine (Figure 3-figure supplement 2A). To assess intestinal NSY-1 function, we performed tissue-specific rescue experiments in nsy-1 mutants using the intestinal-specific vha-1 promoter. Intestinal expression of NSY-1 significantly suppressed the enhanced SS digestion phenotype in nsy-1 mutants (Figure 3-figure supplement 2B), demonstrating functional involvement of gut-localized NSY-1 in regulating digestive responses. We propose intestinal NSY-1 mediates this effect through innate immune signaling, consistent with its known pathway components. As previously established (Reference 1), the canonical PMK-1/p38 MAPK pathway functions downstream of NSY-1, with both sek-1 and pmk-1 knockdown enhancing SS digestion through immune modulation. This indicates intestinal NSY-1 suppresses digestion may act through PMK-1-mediated immune responses. Since neuronal NSY-1's role in digestive control was previously undefined, we prioritized mechanistic analysis of its neuronal function in digestion regulation.

Notably, this immune-mediated mechanism operates independently of NSY-1's neuronal regulation pathway. In AWC neurons, NSY-1 controls digestion exclusively through the neuropeptide signaling axis (INS-23/DAF-2/BCF-1) without engaging innate immune components.

Reference 1: Geng, S., Li, Q., Zhou, X., Zheng, J., Liu, H., Zeng, J., Yang, R., Fu, H., Hao, F., Feng, Q., & Qi, B. (2022). Gut commensal E. coli outer membrane proteins activate the host food digestive system through neural-immune communication. Cell host & microbe, 30(10), 1401–1416.e8. https://doi.org/10.1016/j.chom.2022.08.004

(3) At multiple places, wild-type (WT) controls have been labeled as N2. It is better to label all controls as WT (and not as N2).

Corrected.

(4) In Figure 2B, the aversion response should be scored at multiple time points, like Figure 1C, rather than at just one timepoint.

We thank the reviewer for suggesting multi-timepoint analysis of aversion behavior. In accordance with this recommendation, we have now quantified SS avoidance at multi-timepoint. As shown in the revised Figure 2B, nsy-1 mutants exhibited significantly impaired avoidance responses at both 4h and 6h but not at 8h, confirming that NSY-1 is essential for sustained aversion to SS food in the early response. This data demonstrates that the critical role of NSY-1 in food discrimination at initial sensory responses.

(5) Does the re-introduction of nsy-1 in AWC neurons in nsy-1 mutant background help animals avoid SS in dwelling and food-choice assays? Along the same lines, does the CRISPR-generated AWC-specific mutant of NSY-1 fail to avoid SS in dwelling and food-choice assays similar to the whole-animal mutant? These behavioral data are missing in Figure 3.

We thank the reviewer for prompting behavioral validation of AWC-specific nsy-1 functions. To determine whether NSY-1 in AWC neurons mediates SS sensory perception, we performed dwelling (avoidance) and food-choice assays using AWC-specific nsy-1 knockout and AWC-rescued strains (nsy-1(ag3); Podr-1::nsy-1). In dwelling assays, AWC-specific nsy-1 KO mutants exhibited significantly impaired SS avoidance at 6h (Figure 3-figure supplement 3A), while AWC-rescued strains restored avoidance capacity at 2-6h (Figure 3-figure supplement 3B). Food-choice assays further revealed that AWC nsy-1 KO mutants preferentially migrated toward SS (Figure 3-figure supplement 3C), whereas AWC-rescued showed no preference between SS and HK-E. coli (Figure 3-figure supplement 3D). These data conclusively demonstrate that NSY-1 acts in AWC neurons to mediate SS recognition and aversion behaviors.

(6) In Figure 3E and F, the number of animals that were used for scoring AWC str-2p::GFP expression should be specified.

we added the number of animals in the figure.

(7)  RNA seq analysis identified multiple GPCRs (including STR-130) that are upregulated in an NSY-1-dependent manner when animals are fed with SS bacteria. However, the authors decided to only characterize STR-130 because of previously published findings. It is important to rule out the role of other GPCRs since all are upregulated on SS food as shown in Figure S4 B. I would like the authors to knock down other GPCRs in the same manner as they did for STR-130 and demonstrate that only str-130 knockdown behaves similarly to the nsy-1 mutant (if that is the case) using the assay presented in Figure 4 D.

We appreciate the reviewer’s suggestion to comprehensively evaluate NSY-1-regulated GPCRs. In response, we extended our functional analysis to all six GPCRs (str-130, str-230, str-87, str-112, str-160, and sra-32) identified as NSY-1-dependent and SS-induced in RNA-seq (Figure 4—figure supplement 1).

Using RNAi knockdown and the SS growth assay, we observed that RNAi of str-130, str-230, str-87, or str-112 significantly enhanced SS growth (Figure 4—figure supplement 2A), with str-130 RNAi exhibiting the most robust phenotype—phenocopying nsy-1 mutants. Crucially, none of these GPCR knockdowns further enhanced growth in nsy-1(ag3) mutants (Figure 4—figure supplement 2B), confirming their position downstream of NSY-1. These data establish str-130 as the dominant effector of NSY-1-mediated SS response regulation, while suggesting minor contributions from other GPCRs (str-230, str-87, str-112).

(8) In Figure 4E and G, the number of animals that were used for scoring GFP expression should be specified.

we added the number of animals in the figure.

(9) When comparing Figure 3E and Figure 4E, it appears that the loss of str-130 RNAi does not phenocopy nsy-1 mutant. This raises the question of whether the inefficiency of RNAi targeting str-130 is the cause, or if STR-130 is not the only GPCR regulated by NSY-1 on SS food. I would like the authors to address this discrepancy. If RNAi inefficiency is indeed the cause, using an RNAi-sensitive background, such as an eri- 1 mutant, could help strengthen the data presented in Figure 4E. Conversely, if RNAi inefficiency is not responsible for the discrepancy, I suggest that the authors investigate the roles of other GPCRs that were identified by RNA sequencing.

We appreciate the reviewer’s observation regarding the phenotypic difference between nsy-1 mutants and str-130 (RNAi) animals on SS food (Fig. 3E vs Fig. 4E).

While both genetic perturbations significantly enhance SS growth and increase the proportion of animals exhibiting AWC^ON states compared to wild type (indicating enhanced digestion), the specific AWC^ON neuron configurations differ: nsy-1 mutants predominantly show 2 AWC^ON animals, whereas str-130(RNAi) animals primarily exhibit the 1 AWC^ON /1 AWC^OFF configuration (Fig. 3E vs Fig. 4E).

This difference likely arises because STR-130 is the key GPCR mediating NSY-1's inhibitory effect on SS digestion, but it is not the sole GPCR involved, as evidenced by our RNAi screen identifying several additional NSY-1-regulated GPCRs (str-230, str-87, str-112) whose depletion also enhanced SS growth (Fig. 4A-D).

The robust SS growth enhancement and AWC^ON state increase caused by str-130 (RNAi) (phenocopying the nsy-1 mutant’s functional outcome of enhanced digestion) (Figure 4D, 4E) indicate effective RNAi knockdown for this specific assay. Therefore, the distinct neural configurations reflect the partial redundancy among GPCRs downstream of NSY-1, rather than an inherent inefficiency of the str-130 RNAi.

The nsy-1 mutant phenotype represents the complete loss of all inhibitory GPCR signaling coordinated by NSY-1, while str-130(RNAi) represents the loss of its major component. Investigating the roles of other identified GPCRs (str-230, str-87, str-112) in modulating AWC^ON neuron states is an important direction for future research.

(10) In Figure 4 F and 4 G, the authors show that the overexpression of STR-130 rescues the nsy-1 mutant phenotype suggesting that NSY-1 might function through STR-130 to control digestion on SS food. These data place STR-130 downstream of NSY-1. To further strengthen these epistasis data, authors should knock down str-130 in nsy-1 mutant animals and show that the combined loss of both genes produces the same effect as the loss of either gene alone.

We thank the reviewer for the insightful suggestion to further define the genetic relationship between nsy-1 and str-130. To strengthen our epistasis analysis, we performed RNAi knockdown of str-130 in the nsy-1(ag3) mutant background and assessed development on SS food. Consistent with STR-130 acting downstream of NSY-1, the loss of str-130 via RNAi did not further enhance the developmental capacity (i.e., growth phenotype) of nsy-1(ag3) mutant animals on SS. This lack of enhancement indicates that str-130 and nsy-1 function within the same genetic pathway, with str-130 acting epistatically downstream of nsy-1 (Figure 4—figure supplement 3). This finding reinforces the model proposed from our overexpression data (Fig. 4F-G) – that NSY-1 primarily exerts its inhibitory effect on SS digestion by inducing the expression GPCR STR-130.

(11) In Figure 5C, please mention "ins-23 transcript levels" on the top of the graph so that it is clear what these data represent.

We appreciate the reviewer’s suggestion.

(12) Since all ins genes were upregulated in nsy-1 mutants (though ins-23 was indeed the most highly upregulated gene) on SS food from RNA seq analysis (Figure S5 B), it is important to first phenotypically characterize all of them using "worm length assay". If this analysis shows that ins-23 has the most robust phenotype, it would make more sense to just focus on ins-23.

We agree with the reviewer that initial phenotypic characterization of candidate genes identified through transcriptomic analysis is valuable.Our RNA-seq data revealed that several insulin-like peptide genes, including ins-22, ins-23, ins-24, and ins-27, were significantly upregulated in the nsy-1 mutant on SS food (Figure 5—figure supplement 1B). We prioritized these insulin-like peptide genes for functional validation because they are known to act as neuropeptides capable of mediating non-cell autonomous signaling in previous studies (Shao et al 2016).

To determine if any were functionally responsible for the enhanced SS growth observed in nsy-1 mutants, we performed functional phenotypic screening using the SS growth assay (worm length assay). We individually knocked down each of these candidates (ins-22, ins-23, ins-24, ins-27) in the nsy-1(ag3) mutant background. Among these, only RNAi targeting ins-23 significantly attenuated (i.e., suppressed) the enhanced development of the nsy-1(ag3) mutant on SS (Figure 5—figure supplement 2). This targeted functional screening revealed that ins-23 has the most robust and specific role in mediating the enhanced digestion phenotype downstream of NSY-1 loss, providing the critical justification for our subsequent focus on this particular insulin-like peptide.

Ref:

Shao, L. W., Niu, R., & Liu, Y. (2016). Neuropeptide signals cell non-autonomous mitochondrial unfolded protein response. Cell research, 26(11), 1182–1196. https://doi.org/10.1038/cr.2016.118

Reviewer #2 (Recommendations for the authors):

There are several minor errors and typos in the manuscript

(1) A number of typos in the figures, like "length".

Corrected.

(2) The 'axis labels' are inconsistent from panel to panel, like "relative body length" and "relative worm length".

Corrected.

(3) The fonts are inconsistent from panel to panel.

Corrected.

(4) There is no Ex unique number for transgenic lines.

Corrected.

Reviewer #3 (Recommendations for the authors):

Minor points:

(1)  Figure 3B, 3C, 3G, 4D, 4F, 5D, 5E, and 6C: Replace "lenth" with "length" (consistent with Figure 2A).

Corrected.

(2) Figure 4D: Correct "ctontrol" to "control."

Corrected.

(3) Figure 4G: Update the co-injection marker to Podr-1::GFP instead of Pstr-2::GFP.

Corrected.

(4) Figure 5C: This figure is missing from the Results section.

Corrected.

(5) Figure 6A: Label the graph with Pbcf-1::bcf-1::GFP, as in Figure 6D.

Corrected.

(6) Italicization: Lines 588 and 603-italicize nsy-1.

Corrected.

(7) Supplementary Figure S2A: Correct "Screeng" to "Screening."

Corrected.

(8) Spelling/Proofreading: Ensure consistent spelling and grammar, such as correcting "mutan" to "mutant" in Figure 4A.

Corrected.

Author response:

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

Reviewer #1 (Public review):

In the manuscript, Aldridge and colleagues investigate the role of IL-27 in regulating hematopoiesis during T. gondii infection. Using loss-of-function approaches, reporter mice, and the generation of serial chimeric mice, they elegantly demonstrate that IL-27 induction plays a critical role in modulating bone marrow myelopoiesis and monocyte generation to the infection site. The study is well-designed, with clear experimental approaches that effectively adddress the mechanisms by which IL-27 regulates bone marrow myelopoiesis and prevents HSC exhaustion.

Reviewer #2 (Public review):

Summary:

Aldridge et al. aim to demonstrate the role of IL27 in limiting emergency myelopoiesis in response to Toxoplasma gondii infection by acting directly at the level of early haematopoietic progenitors.

They used different mouse genetic models, such as HSC lineage tracing, IL27 and IL27R-deficient mice, to show that:

(1) HSCs actively participate in emergency myelopoiesis during Toxoplasma gondii infection.

(2) The absence of IL27 and IL27R increases monocyte progenitors and monocytes, mainly inflammatory monocytes CCR2hi.

(3) At steady state, loss of IL27 impairs HSC fitness as competitive transplantation shows long-term engraftment deficiency of IL27 BM cells. This impairment is exacerbated after infection.

(4) IL27 is produced by various BM and other tissue cells at steady state, and its expression increases with infection, mainly by increasing the number of monocytes producing it.

Although it is indisputable that IL27 has a role in emergency myelopoiesis by limiting the number of proinflammatory monocytes in response to infection, the authors' claim that it acts only on HSCs and not on more committed progenitors (CMP, GMP, MP) is not supported by the quality of the data presented here, as described below in the weakness section. In addition, this study highlights a role for IL27 during infection, but does not focus on trained immunity, which is the focus of the targeted elife issue.

We thank the reviewer for these comments. We did try (and perhaps failed) to highlight that all cells within the HSPC category, which includes HSCs and MPPs, have the potential to contribute. The lack of IRGM1-RFP reporter expression in CMPs (Supp Fig5C) suggests that only HSCs and MPPs are progenitors that respond to IL-27 within the bone marrow, and thus that IL-27 signaling on these contributes to the effects observed on monopoiesis and peripheral monocyte populations. We have emphasized this in the revised manuscript, particularly in the introduction (line 82) and discussion (lines 469-472). While this manuscript does not focus solely on trained immunity, the impacts of infection regulating HSC differentiation and having a long-term impact on this compartment are a central theme of trained immunity. For example, Figure 6 and the supporting supplemental figures almost exclusively focus on the differentiation potential that is programed into LTHSCs by infection and the role of IL-27 in regulating this programing. Additionally, Figure 7 shows the long-term consequences of such training. The introduction      and discussion have been modified  to emphasize these connections to trained immunity.         

Weakness

(1) In Figure 4, MFI quantification is required. This figure also shows the expression level (FACS and RNA) in progenitors (GMP and CMP, GP, MP), which is quite similar to that of HSC at this level, so it is really surprising that CMP does not respond at all to IL27 (S5C).

As requested, we have included the MFIs, calculated as a fold change over control FMOs, in the revised manuscript. While HSPCs and CMPs show relatively similar RNA expression of Il27ra (Supp. Fig. 5 A), the levels of surface IL-27R expression by CMPs is lower than HSPCs (Fig. 4C, revised). Additional downstream progenitors (including GMPs) show highly reduced RNA expression and a corresponding low expression of the receptor protein. This is now more apparent with the quantified MFIs (Fig 4-5).

(2) Total BM was used to test the direct effect of IL27 on HSC. There could be an indirect effect from other more mature BM cells, even if they show lower receptor expression than HSC. This should be done on a different sorted population to prove the direct effect of IL27 on HSC. The authors need to look more closely at some stat-dependent genes or stat itself in different sorted cell populations, not just irgm1. It is also known that Stat is associated with increased HSC proliferation in response to IFN, which is the opposite of what is observed here.

We thank the reviewer for this question. We have found that the methanol fixation required to detect pSTAT disrupted the ability to stain for HSPCs by flow cytometry. Thus, we used the IRGM1 reporter, which we have found to be a sensitive and high-fidelity reporter of STAT1 activity while preserving epitope markers of HSPCs.

We agree that the use of bulk bone marrow in the in vitro stimulations could allow for the activation of non-HSPC cell types that are IL-27R+. This is now emphasized in the text. However, there are advantages to this bulk approach as it allows simultaneous analysis of all HSPC populations and downstream progenitors in the same cultures, allowing the ability to assess how the small numbers of IL-27R expressing lymphocytes present in these cultures respond (data that are now included, Supp. Fig. 5C). These cultures also allow a direct comparison of our IL-27R expression analysis with responsiveness to IL-27. Only a selection of the populations analyzed are shown in these data; however, all populations in Figure 4A were also analyzed in Supp. Fig. 5C. These data sets directly correlate receptor expression with sensitivity to IL-27. If this effect was indirect (i.e the ability of IL-27 to induce IFN-γ) then we would expect more robust expression of the IRGM1 reporter across other cell populations. However, while IFN-γ stimulates broad expression of IRGM1, the effects of IL-27 are restricted to HSPC and mature lymphocytes (Supp. Fig. 5C). In other words, the cells that express the highest levels of the IL-27R are most responsive to IL-27.

While we do not directly measure HSPC proliferation in these cultures, we agree with the reviewer that the decreased proportions of proliferating HSPCs seen in the absence of IL-27 during infection (Fig. 7A) is a complex data set. The reviewer is also correct that interferons can promote HSC proliferations; however, they can also promote cell stress, DNA damage, and even cell death of HSCs during chronic exposure (reviewed extensively in Demerdash, Y., et al. Exp Hematol. 2021. PMID: 33571568). Thus IFNs, much like IL-27, appear to regulate HSPCs with contextual importance, inducing their proliferation but also death. The activation of STAT1 and STAT3 by IL-27 may be at the core of some of these effects observed in our data, and we point out that IL-10, another activator of STAT1+3, has been shown to limit HSC responses to inflammation (lined 58-62), but we have also presented other possibilities in the discussion.

(3) The decrease in HSC fitness in IL27R KO at steady state could be an indirect effect of the increase in proinflammatory monocytes contributing to high levels of inflammatory cytokines in the BM and thus chronic HSC activation that is enhanced in response to infection. What is the pro-Inflammatory cytokine profile of the BM of IL27 OR IL27R deficient mice and of mixed chimera mice.

We thank the reviewer for this insightful comment. This was part of our stated rationale in generating the mixed WT:IL-27R-/- BM chimeras presented in Figure 2. In this mixed setting, there remained differences between the ability of the IL-27R sufficient and deficient stem cells to generate inflammatory macrophages. These results suggest that differences in the inflammatory environment do not account for the differences observed. This conclusion is further supported by the observation that the infection-induced levels of IFN-γ in the bone marrow are equivalent in the presence or absence of IL-27 (now included in the revised manuscript, Supp. Fig. 1F).

(4) Furthermore, the FACS profile of KI67/brdu of Figure 7 is doubtful, as it is shown in different literature that KSL are not predominantly quiescent as shown here, but about 50% are KI67-. This is also inconsistent with the increase of HSC observed in Figure 1. Quantification of total BruDU+ HSC and other progenitors is also important to quantify all cells that have proliferated during infection. As the repopulation of IL27-deficient BM is also lower in the absence of infection the proliation  of HSC in IL27R KO mice in the absence of infection is also important.

The comment indicates that the reviewer is concerned that our staining for Ki67 is on the low end of reported literature (~10-50% of LSKs, depending on age of the mice and simulation (Thapa R, et al. Stem Cell Res Ther. 2023. PMID: 37280691; Nies KPH, et al. Cytometry A. 2018. PMID: 30176186)). Our stains were performed on cells from infected mice, which does alter the classic markers used to identify HSPCs. For this reason, we are stringent with our gating strategy and may be excluding more HSPCs than are included in other reports. We have included our FMO control in the revised manuscript to indicate our gating approach (Supp. Fig. 9A). While the population of Ki67+ HSPCs is low, these results were consistent between our experiments and provide data sets that are interpretable.

(5) The immunofluorescence in Figure 3 shows a high level of background and it is difficult to see the GFP and tomato positive cells. In this sense, the number of HSCs quantified as Procr+ (more than 8000 on a single BM section) is inconsistent with the total number of HSCs that a BM can contain (i.e., around 6000 per BM as quantified in Figure 1).

We agree with the reviewer and have found that there is a high level of background in these stains. We have thresholded these images, as described in our methods, to minimize this. Additionally, the increased numbers of Procr+ cells in the imaging vs our flow data is expected, and has been reported by others (Steinert, EM, et al. Cell. 2015. PMID: 25957682).

(6) The addition of arrows to the figure will help to visualise positive cells. It is also not clear why the author normalised the GFP+ cells to the tomato+ cells in Figure 3D.

We thank the reviewer for this comment and have added the suggested arrows. We have also included a more detailed explanation for our normalization strategy.

(7) Furthermore, even if monocytes represent a high proportion of IL27-producing cells, they are only 50% of the cells at 5dpi, as shown in Figure 3 and S4. Without other monocyte markers, line 307 is incorrect.

We thank the reviewer for this clarification and have adjusted the text accordingly.

(8) How do the authors explain that in Figure 1, 5-10% of labelled precursors and monocytes can give 100% of monocytes? This would mean that only labelled HSC can differentiate into PEC monocytes. 5

We thank the reviewer for their interest in this result. Monocytes and macrophages are some

Reviewer #1 (Recommendations for the authors):

I have two minor comments that could enhance the conceptual framework of this study:

(1) The authors indirectly show that IL-27R expression on HSPCs is necessary for regulating HSC proliferation and preventing exhaustion. However, given that they have access to IL-27RFlox mice, they could cross these with Fgd5Cre mice to specifically delete IL-27R on long-term HSCs. This would provide direct evidence for the role of IL-27 signaling in LTHSCs during infection.

We appreciate this comment and did attempt this experiment with several HSPC specific Cres, including the Procr-cre (used elsewhere in the manuscript) and the MDS1-cre-ERT2 (Jackson Laboratory Strain #:032863). Unfortunately, validation revealed that deletion efficiency of the IL-27R with these HSCspecific Cre lines was inefficient, and so experiments are ongoing to enhance efficiency of the deletion and test alternative Cre lines (such as the Fgd5-cre).

(2) Since memory T and B cells often home to the bone marrow, it would be interesting to consider the potential cross-talk between these cells, HSPCs, and IL-27 signaling during secondary T. gondii infection. A brief discussion of this possibility would strengthen the study's broader implications.

We thank the reviewer for this opportunity. We have previously investigated the interplay between immune cells in the bone marrow (Glatman Zaretsky A, et al. Cell Rep. 2017. PMID: 28228257) and now include these possibilities in the discussion (line 465-470).

Reviewer #2 (Recommendations for the authors):

Minor points:

(1) Figures 6F and 7B: should be shown as % of donor and not total number to clarify the lineage potency of LTHSC. The fact that the results of transplantation are separated into different figures makes it not easy to follow. To see if the increase in monocyte production by IL27 KO BM is specific, the percent of donorderived cells for other populations, such as lymphoid, but also in MP, and inflammatory monocytes, is necessary to confirm Figure 2.

Perhaps there has been a misunderstanding? In these plots, we are not analyzing mixed chimeras but single transfer chimeras into lethally irradiated hosts. Thus, the % of donor reaches ~80- 90%. However, to measure the actual output of the HSPCs, the cell number was necessary to compare amongst groups. Additional description is provided in the figure legends and in the text of the manuscript (lines 391-392, 434-436, 651-653, and 680-682).

(2) The heavy UMAP description is unnecessary. Responses As requested, we have reduced this description of how the UMAPs were derived.

As requested, we have reduced this description of how the UMAPs were derived

Author response:

The following is the authors’ response to the previous reviews

Reviewer #1 (Public review): 

Summary:

This fundamental work employed multidisciplinary approaches and conducted rigorous experiments to study how a specific subset of neurons in the dorsal striatum (i.e., "patchy" striatal neurons) modulates locomotion speed depending on the valence of the naturalistic context. 

Strengths: 

The scientific findings are novel and original and significantly advance our understanding of how the striatal circuit regulates spontaneous movement in various contexts.  Response: We appreciate the reviewer’s positive evaluation.

Weaknesses: 

This is extensive research involving various circuit manipulation approaches. Some of these circuit manipulations are not physiological. A balanced discussion of the technical strengths and limitations of the present work would be helpful and beneficial to the field. Minor issues in data presentation were also noted. 

We have incorporated the recommended discussion of technical limitations and addressed the physiological plausibility of our manipulations on Page 33 of the revised Discussion section. Specifically, we wrote: 

“Judicious interpretation of the present data must consider the technical limitations of the various methods and circuit-level manipulations applied. Patchy neurons are distributed unevenly across the extensive structure of the striatum, and their targeted manipulation is constrained by viral spread in the dorsal striatum. Somatic calcium imaging using single-photon microscopy captures activity from only a subset of patchy neurons within a narrow focal plane beneath each implanted GRIN lens. Similarly, limitations in light diffusion from optical fibers may reduce the effective population of targeted fibers in both photometry and optogenetic experiments. For example, the more modest locomotor slowing observed with optogenetic activation of striatonigral fibers in the SNr compared to the stronger effects seen with Gq-DREADD activation across the dorsal striatum could reflect limited fiber optic coverage in the SNr.Alternatively, it may suggest that non-striatonigral mechanisms also contribute to generalized slowing. Our photometry data do not support a role for striatopallidal projections from patchy neurons in movement suppression. The potential contribution of intrastriatal mechanisms, discussed earlier, remains to be empirically tested. Although the behavioral assays used were naturalistic, many of the circuit-level interventions were not. Broad ablation or widespread activation of patchy neurons and their efferent projections represent non-physiological manipulations. Nonetheless, these perturbation results are interpreted alongside more naturalistic observations, such as in vivo imaging of patchy neuron somata and axon terminals, to form a coherent understanding of their functional role”.

Reviewer #2 (Public review):

Hawes et al. investigated the role of striatal neurons in the patch compartment of the dorsal striatum. Using Sepw1-Cre line, the authors combined a modified version of the light/dark transition box test that allows them to examine locomotor activity in different environmental valence with a variety of approaches, including cell-type-specific ablation, miniscope calcium imaging, fiber photometry, and opto-/chemogenetics. First, they found ablation of patchy striatal neurons resulted in an increase in movement vigor when mice stayed in a safe area or when they moved back from more anxiogenic to safe environments. The following miniscope imaging experiment revealed that a larger fraction of striatal patchy neurons was negatively correlated with movement speed, particularly in an anxiogenic area. Next, the authors investigated differential activity patterns of patchy neurons' axon terminals, focusing on those in GPe, GPi, and SNr, showing that the patchy axons in SNr reflect movement speed/vigor. Chemogenetic and optogenetic activation of these patchy striatal neurons suppressed the locomotor vigor, thus demonstrating their causal role in the modulation of locomotor vigor when exposed to valence differentials. Unlike the activation of striatal patches, such a suppressive effect on locomotion was absent when optogenetically activating matrix neurons by using the Calb1-Cre line, indicating distinctive roles in the control of locomotor vigor by striatal patch and matrix neurons. Together, they have concluded that nigrostriatal neurons within striatal patches negatively regulate movement vigor, dependent on behavioral contexts where motivational valence differs.

We are grateful for the reviewer’s thorough summary of our main findings.

In my view, this study will add to the important literature by demonstrating how patch (striosomal) neurons in the striatum control movement vigor. This study has applied multiple approaches to investigate their functionality in locomotor behavior, and the obtained data largely support their conclusions. Nevertheless, I have some suggestions for improvements in the manuscript and figures regarding their data interpretation, accuracy, and efficacy of data presentation

We appreciate the reviewer’s overall positive assessment and have made substantial improvements to the revised manuscript in response to reviewers’ constructive suggestions.

(1) The authors found that the activation of the striatonigral pathway in the patch compartment suppresses locomotor speed, which contradicts with canonical roles of the direct pathway. It would be great if the authors could provide mechanistic explanations in the Discussion section. One possibility is that striatal D1R patch neurons directly inhibit dopaminergic cells that regulate movement vigor (Nadal et al., Sci. Rep., 2021; Okunomiya et al., J Neurosci., 2025). Providing plausible explanations will help readers infer possible physiological processes and give them ideas for future follow-up studies.

We have added the recommended data interpretation and future perspectives on Page 30 of the revised Discussion section. Specifically, we wrote:

“Potential mechanisms by which striatal patchy neurons reduce locomotion involve the supression of dopamine availability within the striatum. Dopamine, primarily supplied by neurons in the SNc and VTA,broadly facilitates locomotion (Gerfen and Surmeier 2011, Dudman and Krakauer 2016). Recent studies have shown that direct activation of patchy neurons leads to a reduction in striatal dopamine levels, accompanied by decreased walking speed (Nadel, Pawelko et al. 2021, Dong, Wang et al. 2025, Okunomiya, Watanabe et al. 2025). Patchy neuron projections terminate in structures known as “dendron bouquets”, which enwrap SNc dendrites within the SNr and can pause tonic dopamine neuron firing (Crittenden, Tillberg et al. 2016, Evans, Twedell et al. 2020). The present work highlights a role for patchy striatonigral inputs within the SN in decelerating movement, potentially through GABAergic dendron bouquets that limit dopamine release back to the striatum (Dong, Wang et al. 2025). Additionally, intrastriatal collaterals of patch spiny projection neurons (SPNs) have been shown to suppress dopamine release and associated synaptic plasticity via dynorphin-mediated activation of kappa opioid receptors on dopamine terminals (Hawes, Salinas et al. 2017). This intrastriatal mechanism may further contribute to the reduction in striatal dopamine levels and the observed decrease in locomotor speed, representing a compelling avenue for future investigation.”

(2) On page 14, Line 301, the authors stated that "Cre-dependent mCheery signals were colocalized with the patch marker (MOR1) in the dorsal striatum (Fig. 1B)". But I could not find any mCherry on that panel, so please modify it.

We have included representative images of mCherry and MOR1 staining in Supplementary Fig. S1 of the revised manuscript.

(3) From data shown in Figure 1, I've got the impression that mice ablated with striatal patch neurons were generally hyperactive, but this is probably not the case, as two separate experiments using LLbox and DDbox showed no difference in locomotor vigor between control and ablated mice. For the sake of better interpretation, it may be good to add a statement in Lines 365-366 that these experiments suggest the absence of hyperactive locomotion in general by ablating these specific neurons.

As suggested by the reviewer, we have added the following statement on Page 17 of the revised manuscript: “These data also indicate that PA elevates valence-specific speed without inducing general hyperactivity”.

(4) In Line 536, where Figure 5A was cited, the author mentioned that they used inhibitory DREADDs (AAV-DIO-hM4Di-mCherrry), but I could not find associated data on Figure 5. Please cite Figure S3, accordingly.

We have added the citation for the now Fig. S4 on Page 25 of the revised manuscript.

(5) Personally, the Figure panel labels of "Hi" and "ii" were confusing at first glance. It would be better to have alternatives.

As suggested by the reviewer, we have now labeled each figure panel with a distinct single alphabetical letter.

(6) There is a typo on Figure 4A: tdTomata → tdTomato

We have made the correction on the figure.

Reviewer #3 (Public review):

Hawes et al. combined behavioral, optical imaging, and activity manipulation techniques to investigate the role of striatal patch SPNs in locomotion regulation. Using Sepw1-Cre transgenic mice, they found that patch SPNs encode locomotion deceleration in a light-dark box procedure through optical imaging techniques. Moreover, genetic ablation of patch SPNs increased locomotion speed, while chemogenetic activation of these neurons decreased it. The authors concluded that a subtype of patch striatonigral neurons modulates locomotion speed based on external environmental cues. Below are some major concerns:

The study concludes that patch striatonigral neurons regulate locomotion speed. However, unless I missed something, very little evidence is presented to support the idea that it is specifically striatonigral neurons, rather than striatopallidal neurons, that mediate these effects. In fact, the optogenetic experiments shown in Fig. 6 suggest otherwise. What about the behavioral effects of optogenetic stimulation of striatonigral versus striatopallidal neuron somas in Sepw1-Cre mice?

Our photometry data implicate striatonigral neurons in locomotor slowing, as evidenced by a negative cross-correlation with acceleration and a negative lag, indicating that their activity reliably precedes—and may therefore contribute to—deceleration. In contrast, photometry results from striatopallidal neurons showed no clear correlation with speed or acceleration.

Figure 6 demonstrates that optogenetic manipulation within the SNr of Sepw1-Cre⁺ striatonigral axons recapitulated context-dependent locomotor changes seen with Gq-DREADD activation of both striatonigral and striatopallidal Sepw1-Cre⁺ cells in the dorsal striatum but failed to produce the broader locomotor speed change observed when targeting all Sepw1-Cre⁺ cells in the dorsal striatum using either ablation or Gq-DREADD activation. The more subtle speed-restrictive phenotype resulting from ChR activation in the SNr could, as the reviewer suggests, implicate striatopallidal neurons in broad locomotor speed regulation. However, our photometry data indicate that this scenario is unlikely, as activity of striatopallidal Sepw1-Cre⁺ fibers is not correlated with locomotor speed. Another plausible explanation is that the optogenetic approach may have affected fewer striatonigral fibers, potentially due to the limited spatial spread of light from the optical fiber within the SNr. Broad locomotor speed change in LDbox might require the recruitment of a larger number of striatonigral fibers than we were able to manipulate with optogenetics. We have added discussion of these technical limitations to the revised manuscript. Additionally, we now discuss the possibility that intrastriatal collaterals may contribute to reduced local dopamine levels by releasing dynorphin, which acts on kappa opioid receptors located on dopamine fibers (Hawes, Salinas et al. 2017), thereby suppressing dopamine release.

The reviewer also suggests an interesting experiment involving optogenetic stimulation of striatonigral versus striatopallidal somata in Sepw1-Cre mice. While we agree that this approach would yield valuable insights, we have thus far been unable to achieve reliable results using retroviral vectors. Moreover, selectively targeting striatopallidal terminals optogenetically remains technically challenging, as striatonigral fibers also traverse the pallidum, and the broad anatomical distribution of the pallidum complicates precise targeting. This proposed work will need to be pursued in a future study, either with improved retrograde viral tools or the development of additional mouse lines that offer more selective access to these neuronal populations as we documented recently (Dong, Wang et al. 2025).

In the abstract, the authors state that patch SPNs control speed without affecting valence. This claim seems to lack sufficient data to support it. Additionally, speed, velocity, and acceleration are very distinct qualities. It is necessary to clarify precisely what patch neurons encode and control in the current study.

We believe the reviewer’s interpretation pertains to a statement in the Introduction rather than the Abstract: “Our findings reveal that patchy SPNs control the speed at which mice navigate the valence differential between high- and low-anxiety zones, without affecting valence perception itself.” Throughout our study, mice consistently preferred the dark zone in the Light/Dark box, indicating intact perception of the valence differential between illuminated areas. While our manipulations altered locomotor speed, they did not affect time spent in the dark zone, supporting the conclusion that valence perception remained unaltered. We appreciate the reviewer’s insight and agree it is an intriguing possibility that locomotor responses could, over time, influence internal states such as anxiety. We addressed this in the Discussion, noting that while dark preference was robust to our manipulations, future studies are warranted to explore the relationship between anxious locomotor vigor and anxiety itself. We report changes in scalar measures of animal speed across Light/Dark box conditions and under various experimental manipulations. Separately, we show that activity in both patchy neuron somata and striatonigral fibers is negatively correlated with acceleration—indicating a positive correlation with deceleration. Notably, the direction of the cross-correlational lag between striatonigral fiber activity and acceleration suggests that this activity precedes and may causally contribute to mouse deceleration, thereby influencing reductions in speed. To clarify this, we revised a sentence in the Results section:

“Moreover, patchy neuron efferent activity at the SNr may causally contribute to deceleration, asindicated by the negative cross-correlational lag, thereby reducing animal speed.”. We also updated the Discussion to read: “Together, these data specifically implicate patchy striatonigral neurons in slowing locomotion by acting within the SNr to drive deceleration.”

One of the major results relies on chemogenetic manipulation (Figure 5). It would be helpful to demonstrate through slice electrophysiology that hM3Dq and hM4Di indeed cause changes in the activity of dorsal striatal SPNs, as intended by the DREADD system. This would support both the positive (Gq) and negative (Gi) findings, where no effects on behavior were observed.

We were unable to perform this experiment; however, hM3Dq has previously been shown to be effective in striatal neurons (Alcacer, Andreoli et al. 2017). The lack of effect observed in GiDREADD mice serves as an unintended but valuable control, helping to rule out off-target effects of the DREADD agonist JHU37160 and thereby reinforcing the specificity of hM3Dq-mediated activation in our study. We have now included an important caveat regarding the Gi-DREADD results, acknowledging the possibility that they may not have worked effectively in our target cells:

“Potential explanations for the negative results in Gi-DREADD mice include inherently low basal activity among patchy neurons or insufficient expression of GIRK channels in striatal neurons, which may limit the effectiveness of Gicoupling in suppressing neuronal activity (Shan, Fang et al. 2022).”

Finally, could the behavioral effects observed in the current study, resulting from various manipulations of patch SPNs, be due to alterations in nigrostriatal dopamine release within the dorsal striatum?

We agree that this is an important potential implication of our work, especially given that we and others have shown that patchy striatonigral neurons provide strong inhibitory input to dopaminergic neurons involved in locomotor control (Nadel, Pawelko et al. 2021, Lazaridis, Crittenden et al. 2024, Dong, Wang et al. 2025, Okunomiya, Watanabe et al. 2025). Accordingly, we have expanded the discussion section to include potential mechanistic explanations that support and contextualize our main findings.

Reviewer #1 (Recommendations for the authors):

Here are some minor issues for the authors' reference:

(1) This work supports the motor-suppressing effect of patchy SPNs, and >80% of them are direct pathway SPNs. This conclusion is not expected from the traditional basal ganglia direct/indirect pathway model. Most experiments were performed using nonphysiological approaches to suppress (i.e., ablation) or activate (i.e., continuous chemo-optogenetic stimulation). It remains uncertain if the reported observations are relevant to the normal biological function of patchy SPNs under physiological conditions. Particularly, under what circumstances an imbalanced patch/matrix activity may be induced, as proposed in the sections related to the data presented in Figure 6. A thorough discussion and clarification remain needed. Or it should be discussed as a limitation of the present work.

We have added discussion and clarification of physiological limitations in response to reviewer feedback. Additionally, we revised the opening sentence of an original paragraph in the discussion section to emphasize that it interprets our findings in the context of more physiological studies reporting natural shifts in patchy SPN activity due to cognitive conflict, stress, or training. The revised opening sentence now reads: “Together with previous studies of naturally occurring shifts in patchy neuron activation, these data illustrate ethologically relevant roles for a subgroup of genetically defined patchy neurons in behavior.”

(2) Lines 499-500: How striato-nigral cells encode speed and deceleration deserves a thorough discussion and clarification. These striatonigral cells can target both SNr GABAergic neurons and dendrites of the dopaminergic neurons. A discussion of microcircuits formed by the patchy SPNs axons in the SNr GABAergic and SNC DAergic neurons should be presented.

We have added this point at lines 499–500, including a reference to a relevant review of microcircuitry. Additionally, we expanded the discussion section to address microcircuit mechanisms that may underlie our main findings.

(3) Line 70: "BNST" should be spelled out at the first time it is mentioned.

This has been done.

(4) Line 133: only GCaMP6 was listed in the method, but GCaMP8 was also used (Figure 4). Clarification or details are needed.

Thank you for your careful attention to detail. We have corrected the typographical errors in the Methods section. Specifically, in the Stereotaxic Injections section, we corrected “GCaMP83” to “GCaMP8s.” In the Fiber Implant section, we removed the incorrect reference to “GCaMP6s” and clarified that GCaMP8s was used for photometry, and hChR2 was used for optogenetics.

(5) Line 183: Can the authors describe more precisely what "a moment" means in terms of seconds or minutes?

This has been done.

(6) Line 288: typo: missing / in ΔF

Thank you this has been fixed

(7) Line 301-302: the statement of "mCherry and MOR1 colocalization" does not match the images in Figure 1B.

This has been corrected by proving a new Supplementary Figure S1.

(8) Related to the statement between Lines 303-304: Figure 1c data may reflect changes in MOR1 protein or cell loss. Quantification of NeuN+ neurons within the MOR1 area would strengthen the conclusion of 60% of patchy cell loss in Figure 1C

Since the efficacy of AAV-FLEX-taCasp3 in cell ablation has been well established in our previous publications and those of others (Yang, Chiang et al. 2013, Wu, Kung et al. 2019), we do not believe the observed loss of MOR1 staining in Fig. 1C merely reflects reduced MOR1 expression. Moreover, a general neuronal marker such as NeuN may not reliably detect the specific loss of patchy neurons in our ablation model, given the technical limitations of conventional cell-counting methods like MBF’s StereoInvestigator, which typically exhibit a variability margin of 15–20%.

(9) Lines 313-314: "Similarly, PA mice demonstrated greater stay-time in the dark zone (Figure 1E)." Revision is needed to better reflect what is shown in Figure 1E and avoid misunderstandings.

Thank you this has been addressed.

(10) The color code in Figure 2Gi seems inconsistent with the others? Clarifications are needed

Color coding in Figure 2Gi differs from that in 2Eii out of necessity. For example, the "Light" cells depicted in light blue in 2Eii are represented by both light gray and light red dots in 2Gi. Importantly, Figure 2G does not encode specific speed relationships; instead, any association with speed is indicated by a red hue.

(11) Lines 538-539: the statement of "Over half of the patch was covered" was not supported by Figure 5C. Clarification is needed.

Thank you. For clarity, we updated the x-axis labels in Figures 1C and 5C from “% area covered” to “% DS area covered,” and defined “DS” as “dorsal striatal” in the corresponding figure legends. Additionally, we revised the sentence in question to read: “As with ablation, histological examination indicated that a substantial fraction of dorsal patch territories, identified through MOR1 staining, were impacted (Fig. 5C).”

(12) Figure 3: statistical significance in Figure 3 should be labeled in various panels.

We believe the reviewer's concern pertains to the scatter plot in panel F—specifically, whether the data points are significantly different from zero. In panel 3F, the 95% confidence interval clearly overlaps with zero, indicating that the results are not statistically significant.

(13) Figures 6D-E: no difference in the speed of control mice and ChR2 mice under continuous optical stimulation was not expected. It was different from Gq-DRADDS study in Figure 5E-F. Clarifications are needed.

For mice undergoing constant ChR2 activation of Sepw1-Cre+ SNr efferents, overall locomotor speed does not differ from controls. However, the BIL (bright-to-illuminated) effect on zone transitions isdisrupted: activating Sepw1-Cre⁺ fibers in the SNr blunts the typical increase in speed observed when mice flee from the light zone toward the dark zone. This impaired BIL-related speed increase upon exiting the light was similarly observed in the Gq-DREADD cohort. The reviewer is correct that this optogenetic manipulation within the SNr did not produce the more generalized speed reductions seen with broader Gq-DREADD activation of all Sepw1-Cre⁺ cells in the dorsal striatum. A likely explanation is the difference in targeting—ChR2 specifically activates SNr-bound terminals, whereas Gq-DREADD broadly activates entire Sepw1-Cre⁺ cells. Notably, many of the generalized speed profile changes observed with chemogenetic activation are opposite to those resulting from broad ablation of Sepw1-Cre⁺ cells. The more subtle speed-restrictive phenotype observed with ChR2 activation targeted to the SNr may suggest that fewer striatonigral fibers were affected by this technique, possibly due to the limited spread of light from the fiber optic. Broad locomotor speed change in LDbox might require the recruitment of a larger number of striatonigral fibers than we were able to manipulate with an optogenetic approach. Alternatively, it could indicate that non-striatonigral Sepw1-Cre⁺ projections—such as striatopallidal or intrastriatal pathways—play a role in more generalized slowing. If striatopallidal fibers contributed to locomotor slowing, we would expect to see non-zero cross-correlations between neural activity and speed or acceleration, along with negative lag indicating that neural activity precedes the behavioral change. However, our fiber photometry data do not support such a role for Sepw1-Cre⁺ striatopallidal fibers. We have also referenced the possibility that intrastriatal collaterals could suppress striatal dopamine levels, potentially explaining the stronger slowing phenotype observed when the entire striatal population is affected, as opposed to selectively targeting striatonigral terminals. These technical considerations and interpretive nuances have been incorporated and clarified in the revised discussion section.

(14) Lines 632: "compliment": a typo?

Yes, it should be “complement”.

(15) Figure 4 legend: descriptions of panels A and B were swapped

Thank you. This has been corrected.

(16) Friedman (2020) was listed twice in the bibliography (Lines 920-929).

Thank you. This has been corrected.

Reviewer #3 (Recommendations for the authors):

It will be helpful to label and add figure legends below each figure.

Thank you for the suggestion.

Editor's note:

Should you choose to revise your manuscript, if you have not already done so, please include full statistical reporting including exact p-values wherever possible alongside the summary statistics (test statistic and df) and, where appropriate, 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05 in the main manuscript. We noted some instances where only p values are reported.

Readers would also benefit from coding individual data points by sex and noting N/sex

We have included detailed statistical information in the revised manuscript. Both male and female mice were used in all experiments in approximately equal numbers. Since no sex-related differences were observed, we did not report the number of animals by sex.

References

Alcacer, C., L. Andreoli, I. Sebastianutto, J. Jakobsson, T. Fieblinger and M. A. Cenci (2017). "Chemogenetic stimulation of striatal projection neurons modulates responses to Parkinson's disease therapy." J Clin Invest 127(2): 720-734.

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Active reading is more than just going through the words. It is about paying attention to what is being said and how it is being said. This conscious effort to pay attention helps you notice the patterns in the text and the choices the writer makes, helping you discern what they mean when making such choices. It definitely takes focus. For example, when you are tired and reading the same paragraph over and over again, you are not taking in the text and reading actively. This is a mostly universal experience that stresses the importance of active reading.

Author response:

Reviewer 1 (Public review):

The manuscript by Choi and colleagues investigates the impact of variation in cortical geometry and growth on cortical surface morphology. Specifically, the study uses physical gel models and computational models to evaluate the impact of varying specific features/parameters of the cortical surface. The study makes use of this approach to address the topic of malformations of cortical development and finds that cortical thickness and cortical expansion rate are the drivers of differences in morphogenesis.

The study is composed of two main sections. First, the authors validate numerical simulation and gel model approaches against real cortical postnatal development in the ferret. Next, the study turns to modelling malformations in cortical development using modified tangential growth rate and cortical thickness parameters in numerical simulations. The findings investigate three genetically linked cortical malformations observed in the human brain to demonstrate the impact of the two physical parameters on folding in the ferret brain.

This is a tightly presented study that demonstrates a key insight into cortical morphogenesis and the impact of deviations from normal development. The dual physical and computational modeling approach offers the potential for unique insights into mechanisms driving malformations. This study establishes a strong foundation for further work directly probing the development of cortical folding in the ferret brain. One weakness of the current study is that the interpretation of the results in the context of human cortical development is at present indirect, as the modelling results are solely derived from the ferret. However, these modelling approaches demonstrate proof of concept for investigating related alterations more directly in future work through similar approaches to models of the human cerebral cortex.

We thank the reviewer for the very positive comments. While the current gel and organismal experiments focus on the ferret only, we want to emphasize that our analysis does consider previous observations of human brains and morphologies therein (Tallinen et al., Proc. Natl. Acad. Sci. 2014; Tallinen et al., Nat. Phys. 2016), which we compare and explain. This allows us to analyze the implications of our study broadly to understand the explanations of cortical malformations in humans using the ferret to motivate our study. Further analysis of normal human brain growth using computational and physical gel models can be found in our companion paper (Yin et al., 2025), also submitted to eLife:

S. Yin, C. Liu, G. P. T. Choi, Y. Jung, K. Heuer, R. Toro, L. Mahadevan, Morphogenesis and morphometry of brain folding patterns across species. bioRxiv 2025.03.05.641692.

In future work, we plan to obtain malformed human cortical surface data, which would allow us to further investigate related alterations more directly.

Reviewer 2 (Public review):

Summary:

Based on MRI data of the ferret (a gyrencephalic non-primate animal, in whom folding happens postnatally), the authors create in vitro physical gel models and in silico numerical simulations of typical cortical gyrification. They then use genetic manipulations of animal models to demonstrate that cortical thickness and expansion rate are primary drivers of atypical morphogenesis. These observations are then used to explain cortical malformations in humans.

Strengths:

The paper is very interesting and original, and combines physical gel experiments, numerical simulations, as well as observations in MCD. The figures are informative, and the results appear to have good overall face validity.

We thank the reviewer for the very positive comments.

Weaknesses:

On the other hand, I perceived some lack of quantitative analyses in the different experiments, and currently, there seems to be rather a visual/qualitative interpretation of the different processes and their similarities/differences. Ideally, the authors also quantify local/pointwise surface expansion in the physical and simulation experiments, to more directly compare these processes. Time courses of eg, cortical curvature changes, could also be plotted and compared for those experiments. I had a similar impression about the comparisons between simulation results and human MRI data. Again, face validity appears high, but the comparison appeared mainly qualitative.

We thank the reviewer for the comments. Besides the visual and qualitative comparisons between the models, we would like to point out that we have included the quantification of the shape difference between the real and simulated ferret brain models via spherical parameterization and the curvature-based shape index as detailed in main text Fig. 4 and SI Section 3. We have also utilized spherical harmonics representations for the comparison between the real and simulated ferret brains at different maximum order N. In our revision, we plan to further include the curvature-based shape index calculations for the comparison between the real and simulated ferret brains at more time points.

As for the comparison between the malformation simulation results and human MRI data in the current work, since the human MRI data are two-dimensional while our computational models are threedimensional, we focus on the qualitative comparison between them. In future work, we plan to obtain malformed human cortical surface data, from which we can then perform the parameterization-based and curvature-based shape analysis for a more quantitative assessment.

I felt that MCDs could have been better contextualized in the introduction.

We thank the reviewer for the comment and will include a more detailed introduction to MCDs in our revision.

DOI: 10.1038/s41467-019-10269-y

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @maulamb

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1038/s41467-019-10285-y

Resource: RRID:BDSC_51309

Curator: @scibot

SciCrunch record: RRID:BDSC_51309

What is this?

Author response:

General Statements

We are grateful for constructive reviewers’ comments and criticisms and have thoroughly addressed all major and minor comments in the revised manuscript.

Summary of new data.

We have performed the following additional experiments to support our concept:

(1) The kinetcs of ROS production in B6 and B6.Sst1S macrophages after TNF stimulation (Fig. 3I and J, Suppl. Fig. 3G);

(2) Time course of stress kinase activation (Fig.3K) that clearly demonstrated the persistent stress kinase (phospho-ASK1 and phospho-cJUN) activation exclusively in. the B6.Sst1S macrophages;

(3) New Fig.4 C-E panels include comparisons of the B6 and B6.Sst1S macrophage responses to TNF and effects of IFNAR1 blockade in both backgrounds.

(4) We performed new experiments demonstrating that the synthesis of lipid peroxidation products (LPO) occurs in TNF-stimulated macrophages earlier than the IFNβ super-induction (Suppl.Fig.4A and B).

(5) We demonstrated that the IFNAR1 blockade 12, 24 and 32 h after TNF stimulation still reduced the accumulation of LPO product (4-HNE) in TNF-stimulated B6.Sst1S BMDMs (Suppl.Fig.4 E-G).

(6) We added comparison of cMyc expression between the wild type B6 and B6.Sst1S BMDMs during TNF stimulation for 6-24 h (Fig.5I-J).

(7) New data comparing 4-HNE levels in Mtb-infected B6 wild type and B6.Sst1S macrophages and quantification of replicating Mtb was added (Fig.6B, Suppl.Fig.7C and D).

(8) In vivo data described in Fig.7 was thoroughly revised and new data was included. We demonstrated increased 4-HNE loads in multibacillary lesions (Fig.7A, Suppl. Fig.9A) and the 4-HNE accumulation in CD11b+ myeloid cells (Fig.7B and Suppl.Fig.9B). We demonstrated that the Ifnb – expressing cells are activated iNOS+ macrophages (Fig.7D and Suppl.Fig.13A). Using new fluorescent multiplex IHC, we have shown that stress markers phopho-cJun and Chac1 in TB lesions are expressed by Ifnb- and iNOS-expressing macrophages (Fig.7E and Suppl.Fig.13D-F).

(9) We performed additional experiment to demonstrate that naïve (non-BCG vaccinated) lymphocytes did not improve Mtb control by Mtb-infected macrophages in agreement with previously published data (Suppl.Fig.7H).

Summary of updates

Following reviewers requests we updated figures to include isotype control antibodies, effects of inhibitors on non-stimulated cells, positive and negative controls for labile iron pool, additional images of 4-HNE and live/dead cell staining.

Isotype control for IFNAR1 blockade were included in Fig.3M, Fig.4C -E, Fig.6L-M Suppl.Fig.4F-G, 7I.

Positive and negative controls for labile iron pool measurements were added to Fig.3E, Fig.5D, Suppl.Fig.3B

Cell death staining images were added Suppl.Fig.3H

Co-staining of 4-HNE with tubulin was added to Suppl.Fig.3A.

High magnification images for Figure 7 were added in Suppl.Fig.8 to demonstrate paucibacillary and multibacillary image classification.

Single-channel color images for individual markers were provided in Fig.7E and Suppl.Fig.13B-F.

Inhibitor effects on non-stimulated cells were included in Fig.5 D-H, Suppl.Fig.6A and B. Titration of CSF1R inhibitors for non-toxic concentration determination are included in Suppl.Fig.6D.

In addition, we updated the figure legends in the revised manuscript to include more details about the experiments. We also clarified our conclusions in the Discussion. Responses to every major and minor comment of the reviewers are provided below.

Point-by-point description of the revisions

Reviewer #1 (Evidence, reproducibility and clarity:

Summary

The study by Yabaji et al. examines macrophage phenotypes B6.Sst1S mice, a mouse strain with increased susceptibility to M. tuberculosis infection that develops necrotic lung lesions. Extending previous work, the authors specifically focus on delineating the molecular mechanisms driving aberrant oxidative stress in TNF-activated B6.Sst1S macrophages that has been associated with impaired control of M. tuberculosis. The authors use scRNAseq of bone marrow-derived macrophages to further characterize distinctions between B6.Sst1S and control macrophages and ascribe distinct trajectories upon TNF stimulation. Combined with results using inhibitory antibodies and small molecule inhibitors in in vitro experimentation, the authors propose that TNF-induced protracted c-Myc expression in B6.Sst1S macrophages disables the cellular defense against oxidative stress, which promotes intracellular accumulation of lipid peroxidation products, fueled at least in part by overexpression of type I IFNs by these cells. Using lung tissue sections from M. tuberculosis-infected B6.Sst1S mice, the authors suggest that the presence of a greater number of cells with lipid peroxidation products in lung lesions with high counts of stained M. tuberculosis are indicative of progressive loss of host control due to the TNF-induced dysregulation of macrophage responses to oxidative stress. In patients with active tuberculosis disease, the authors suggest that peripheral blood gene expression indicative of increased Myc activity was associated with treatment failure.

Major comments

The authors describe differences in protein expression, phosphorylation or binding when referring to Fig 2A-C, 2G, 3D, 5B, 5C. However, such differences are not easily apparent or very subtle and, in some cases, confounded by differences in resting cells (e.g. pASK1 Fig 3L; c-Myc Fig 5B) as well as analyses across separate gels/blots (e.g. Fig 3K, Fig 5B). Quantitative analyses across different independent experiments with adequate statistical analyses are required to strengthen the associated conclusions.

We updated our Western blots as follows:

(1) Densitometery of normalized bands is included above each lane (Fig.2A-C; Fig.3C-D and 3K; Fig.4A-B; Fig.5B,C,I,J). New data in Fig.3K is added to highlight differences between B6 and B6.Sst1S at individual timepoints after TNF stimulation. In Fig.5I we added new data comparing Myc levels in B6 and B6.Sst1S with and without JNK inhibitor and updated the results accordingly. New Fig.3K clearly demonstrates the persistent activation of p-cJun and pAsk1 at 24 and 36h of TNF stimulation. In Fig.5B we clearly demonstrate that Myc levels were higher in B6.Sst1S after 12 h of TNF stimulation. At 6h, however, the basal differences in Myc levels are consistently higher in B6.Sst1S and the induction by TNF is 1.6-fold similar in both backgrounds. We noted this in the text.

(2) A representative experiment is shown in individual panels and the corresponding figure legend contains information on number of biological repeats. Each Western blot was repeated 2 – 4 times.

The representative images of fluorescence microscopy in Fig 3H, 4H, 5H, S3C, S3I, S5A, S6A seem to suggest that under some conditions the fluorescence signal is located just around the nucleus rather than absent or diminished from the cytoplasm. It is unclear whether this reflects selective translocation of targets across the cell, morphological changes of macrophages in culture in response to the various treatments, or variations in focal point at which images were acquired. Control images (e.g. cellular actin, DIC) should be included for clarification. If cell morphology changes depending on treatments, how was this accounted for in the quantitative analyses? In addition, negative controls validating specificity of fluorescence signals would be warranted.

Our conclusion of higher LPO production is based on several parameters: 4-HNE staining, measurements of MDA in cell lysates and oxidized lipids using BODIPY C11. Taken together they demonstrate significant and reproducible increase in LPO accumulation in TNFstimulated B6.Sst1S macrophages. This excludes imaging artefact related to unequal 4-HNE distribution noted by the reviewer. In fact, we also noted that the 4-HNE was spread within cell body of B6.Sst1S macrophages and confirmed it using co-staining with tubulin, as suggested by the reviewer (new Suppl.Fig.3A). Since low molecular weight LPO products, such as MDA and 4-HNE, traverse cell membranes, it is unlikely that they will be strictly localized to a specific membrane bound compartment. However, we agree that at lower concentrations, there might be some restricted localization, explaining a visible perinuclear ring of 4-HNE staining in B6 macrophages. This phenomenon may be explained just by thicker cytoplasm surrounding nucleus in activated macrophages spread on adherent plastic surface or by proximity to specific organelles involved in generation or clearance of LPO products and definitively warrants further investigation.

We also included images of non-stimulated cells in Fig.3H, Suppl.Fig.3A and 3E. We used multiple fields for imaging and quantified fluorescence signals (Suppl. Fig.3D and 3F, Suppl.Fig.4G, Suppl.Fig.6A and B).

We used negative controls without primary antibodies for the initial staining optimization, but did not include it in every experiment.

To interpret the evaluation on the hierarchy of molecular mechanisms in B6.Sst1S macrophages, comparative analyses with B6 control cells should be included (e.g. Fig 4C-I, Fig 5, Fig 6B, E-M, S6C, S6E-F). This will provide weight to the conclusions that the dysregulated processes are specifically associated with the susceptibility of B6.Sst1S macrophages.

Understanding the sst1-mediated effects on macrophage activation is the focus of our previously published studies Bhattacharya et al., JCI, 2021) and this manuscript. The data comparing B6 and B6.Sst1S macrophage are presented in Fig.1, Fig.2, Fig.3, Fig.4, Fig.5A-C, I and J, Fig.6A-C, 6J and corresponding supplemental figures 1, 2, 3, 4A and B, Suppl.Fig.5, Suppl.Fig.6C, Suppl.Fig.7A-D,7F.

Once we identified the aberrantly activated pathways in the B6.Sst1S, we used specific inhibitors to correct the aberrant response in B6.Sst1S.

All experiments using inhibitory antibodies require comparison to the effect of a matched isotype control in the same experiment (e.g. Fig 3J, 4F, G, I; 6L, 6M, S3G, S6F).

Isotype control for IFNAR1 blockade were included in Fig.3M, Fig.4C-E, Fig.6L-M Suppl.Fig.4F-G, 7I.

Experiments using inhibitors require inclusion of an inhibitor-only control to assess inhibitor effects on unstimulated cells (e.g. Fig 4I, 5D-I)

Inhibitor effects on non-stimulated cells were included in Fig.5 D-H, Suppl.Fig.6A and B.

Fig 3K and Fig 5J appear to contain the same images for p-c-Jun and b-tubulin blots.

Fig.3K and 5J partially overlapped but had different focus – 3K has been updated to reflect the time course of stress kinase activation. Fig.5J is updated (currently Fig.5I and J) to display B6 and B6.Sst1S macrophage data including cMyc and p-cJun levels.

Data of TNF-treated cells in Fig 3I appear to be replotted in Fig 3J.

Currently these data is presented in Fig.3L and 3M and has been updated to include comparison of B6 and B6.Sst1S cells (Fig.3L) and effects of inhibitors in Fig.3M.

It is stated that lungs from 2 mice with paucibacillary and 2 mice with multi-bacillary lesions were analyses. There is contradicting information on whether these tissues were collected at the same time post infection (week 14?) or whether the pauci-bacillary lesions were in lungs collected at earlier time points post infection (see Fig S8A). If the former, how do the authors conclude that multi-bacillary lesions are a progression from paucibacillary lesions and indicative of loss of M. tuberculosis control, especially if only one lesion type is observed in an individual host? If the latter, comparison between lesions will likely be dominated by temporal differences in the immune response to infection.

In either case, it is relevant to consider density, location, and cellular composition of lesions (see also comments on GeoMx spatial profiling). Is the macrophage number/density per tissue area comparable between pauci-bacillary and multi-bacillary lesions?

We did not collect lungs at the same time point. As described in greater detail in our preprints (Yabaji et al., https://doi.org/10.1101/2025.02.28.640830 and https://doi.org/10.1101/2023.10.17.562695) pulmonary TB lesions in our model of slow TB progression are heterogeneous between the animals at the same timepoint, as observed in human TB patients and other chronic TB animal models. Therefore, we perform analyses of individual TB lesions that are classified by a certified veterinary pathologist in a blinded manner based on their morphology (H&E) and acid fast staining of the bacteria, as depicted in Suppl.Fig.8. Currently it is impossible to monitor progression of individual lesions in mice. However, in mice TB is progressive disease and no healing and recovery from the disease have been observed in our studies or reported in literature. Therefore, we assumed that paucibacillary lesions preceded the multibacillary ones, and not vice versa, thus reflecting the disease progression. In our opinion, this conclusion most likely reflects the natural course of the disease. However, we edited the text : instead of disease progression we refer to paucibacillary and multibacillary lesions.

Does 4HNE staining align with macrophages and if so, is it elevated compared to control mice and driven by TNF in the susceptible vs more resistant mice?

We performed additional staining and analyses to demonstrate the 4-HNE accumulation in CD11b+ myeloid cells of macrophage morphology. Non-necrotic lesions contain negligible proportion of neutrophils (Fig.7B, Suppl.Fig.9B). B6 mice do not develop advanced multibacillary TB lesions containing 4-HNE+ cells. Also, 4-HNE staining was localized to TB lesions and was not found in uninvolved lung areas of the infected mice, as shown in Suppl.Fig.9A (left panel).

It is well established that TNF plays a central role in the formation and maintenance of TB granulomas in humans and in all animal models. Therefore, TNF neutralization would lead to rapid TB progression, rapid Mtb growth and lesions destruction in both B6 and B6.Sst1S genetic backgrounds.

Pathway analysis of spatial transcriptomic data (Suppl.Fig.11) identified TNF signaling via NFkB among dominant pathways upregulated in multibacillary lesions, suggesting that the 4-HNE accumulation paralleled increased TNF signaling. In addition, in vivo other cytokines, including IFN-I, could activate macrophages and stimulate production of reactive oxygen and nitrogen species and lead to the accumulation of LPO products as shown in this manuscript.

It would be relevant to state how many independent lesions per host were sampled in both the multiplex IHC as well as the GeoMx data. Can the authors show the selected regions of interest in the tissue overview and in the analyses to appreciate within-host and across-host heterogeneity of lesions. The nature of the spatial transcriptomics platform used is such that the data are derived from tissue areas that contain more than just Iba1+ macrophages. At later stages of infection, the cellular composition of such macrophage-rich areas will be different when compared to lesions earlier in the infection process. Hence, gene expression profiles and differences between tissue regions cannot be attributed to macrophages in this tissue region but are more likely a reflection of a mix of cellular composition and per-cell gene expression.

We used Iba1 staining to identify macrophages in TB lesions and programmed GeoMx instrument to collect spatial transcriptomics probes from Iba1+ cells within ROIs. Also, we selected regions of interest (ROI) avoiding necrotic areas (depicted in Suppl.Fig.10). We agree that Iba1+ macrophage population is heterogenous – some Iba1+ cells are activated iNOS+ macrophages, other are iNOS-negative (Fig.7C and D, and Suppl.Fig.13A). Multibacillary lesions contain larger areas occupied by activated (iNOS+) macrophages (Fig.7D,

Suppl.Fig.13B and 13F). Although the GeoMx spatial transcriptomic platform does not provide single cell resolution, it allowed us to compare populations of Iba1+ cells in paucibacillary and multibacillary TB lesions and to identify a shift in their overall activation pattern.

It is stated that loss of control of M. tuberculosis in multibacillary lesions was associated with "downregulation of IFNg-inducible genes". If the authors base this on the tissue expression of individual genes, this requires further investigation to support such conclusion (also see comment on GeoMx above). Furthermore, how might this conclusion be compatible with significantly elevated iNOS+ cells (Fig 7D) in multibacillary lesions?

We demonstrated that Ciita gene expression is specifically induced by IFN-gamma and is suppressed by IFN-I (Fig.6M). The expression of Ciita in paucibacillary lesions suggest the presence of the IFN-gamma activated cells and its disappearance in the multibacillary lesion is consistent with massive activation of IFN-I pathway (Fig.7C).

It is appreciated that the human blood signature analyses contain Myc-signatures but the association with treatment failure is not very strong based on the data in Fig 13B and C (Suppl.Fig.15B and C now). The authors indicate that they have no information on disease severity, but it should perhaps not be assumed that treatment failure is indicative of poor host control of the infection. Perhaps independent analyses in separate cohort/data set can add strength and provide -additional insights (e.g. PMID: 35841871; PMID: 32451443, PMID: 17205474, PMID: 22872737). In addition, the human data analyses could be strengthened by extension to additional signatures such as IFN, TNF, oxidative stress. Details of the human study design are not very clear and are lacking patient demographics, site of disease, time of blood collection relative to treatment onset, approving ethics committees.

X axis of Suppl.Fig.15A represent pre-defined molecular signature gene sets (MSigDB) in Gene Set Enrichment Analysis (GSEA) database (https://www.gseamsigdb.org/gsea/msigdb). On Y axis is area under curve (AUC) score for each gene set. The Myc upregulated gene set myc_up was identified among top gene sets associated with treatment failure using unbiased ssGSEA algorithm. The upregulation of Myc pathway in the blood transcriptome associated with TB treatment failure most likely reflects greater proportion of immature cells in peripheral blood, possibly due to increased myelopoiesis.

Pathway analysis of the differentially expressed genes revealed that treatment failures were associated with the following pathways relevant to this study: NF-kB Signaling, Flt3 Signaling in Hematopoietic Progenitor Cells (indicative of common myeloid progenitor cell proliferation), SAPK/JNK Signaling and Senescence (indicative of oxidative stress). The upregulation of these pathways in human patients with poor TB treatment outcomes correlates with our findings in TB susceptible mice. The detailed analysis of differentially regulated pathways in human TB patients is beyond the scope of this study and is presented in another manuscript entitled “ Tuberculosis risk signatures and differential gene expression predict individuals who fail treatment” by Arthur VanValkenburg et al., submitted for publication.

Blood collection for PBMC gene expression profiling of TB patients was prior to TB treatment or within a first week of treatment commencement. Boxplot of bootstrapped ssGSEA enrichment AUC scores from several oncogene signatures ranked from lowest to highest AUC score, with myc_up and myc_dn genes highlighted in red.

We agree with the reviewer that not every gene in the myc_up gene set correlates with the treatment outcome. But the association of the gene set is statistically significant, as presented in Suppl.Fig.15B – C.

We updated the details of the study, including study sites and the ethics committee approval statement and references describing these cohorts.

Other comments

It is excellent that the authors provide individual data points. Choosing a colour other than black would increase clarity when black bars are used.

We followed this useful suggestion and selected consistent color codes for B6 and B6.Sst1S groups to enhance clarity throughout the revised manuscript.

Error bars are inconsistently depicted as either bi-directional or just unidirectional.

We used bi-directional error bars in the revised manuscript.

Fig 1E, G, H - please include a scale to clarify what the heat map is representing.

We have included the expression key in Fig.1E,G and H and Suppl.Fig.1C and D in the revised version.

Fig 2K, Fig S10A gene information cannot be deciphered.

We increased the font in previous Fig.2K and moved to supplement to keep larger fonts (current Suppl.Fig.2G).

Fig S4A,B please add error bars.

These data are presented as Suppl.Fig.5 in the revised version. We performed one experiment to test the hypothesis. Because the data indicated no clear increase in transposon small RNAs in the sst1S macrophages, we did not pursue this hypothesis further, and therefore, the error bars were not included. However, we decided to include these negative data because it rejects a very attractive and plausible hypothesis.

Please use gene names as per convention (e.g. Ifnb1) to distinguish gene expression from protein expression in figures and text.

We addressed the comment in the revised manuscript.

Fig S8B. Contrary to the description of results, there seems to be minimal overlap between the signal for YFP and the Ifnb1 probe. Is the Ifnb1 reporter mouse a legacy reporter? If so, it is worth stating this and including such considerations in the data interpretation.

The YFP reporter expresses YFP protein under the control of the Ifnb1 promoter. The YFP protein accumulates within the cells and while Ifnb protein is rapidly secreted and does not accumulate in the producing cells in appreciable amounts. So YFP is not a lineage tracing reporter, but its accumulation marks the Ifnb1 promoter activity in cells, although the YFP protein half-life is longer than that of the Ifnb1 mRNA that is rapidly degraded (Witt et al., BioRxiv, 2024; doi:10.1101/2024.08.28.61018). Therefore, there is no precise spatiotemporal coincidence of these readouts.

Please clarify what is meant by "normal interstitium" ? If the tissue is from uninfected mice, please state clearly.

In this context we refer to the uninvolved lung areas of the infected lungs. In every sample we compare uninvolved lung areas and TB lesions of the same animal. Also, we performed staining of lung of non-infected mice as additional controls.

If macrophage cultures underwent media changes every 48h, how was loss of liberated Mtb taken into account especially if differences in cell density/survival were noted? The assessment of M. tuberculosis load by qPCR is not well described. In particular, the method of normalization applied within the experiments (not within the qPCR) here remains unclear, even with reference to the authors' prior publication.

Our lab has many years of experience working with macrophage monolayers infected with virulent Mtb and uses optimized protocols to avoid cell losses and related artifacts. Recently we published a detailed protocol for this methodology in STAR Protocols (Yabaji et al., 2022; PMID 35310069). In brief, it includes preparation of single cell suspensions of Mtb by filtration to remove clumps, use of low multiplicity of infection, preparation of healthy confluent monolayers and use of nutrient rich culture medium and medium change every 2 days. We also rigorously control for cell loss using whole well imaging and quantification of cell numbers and live/dead staining.

Please add citation for the limma package.

The references has been added (Ritchie et al, NAR 2015; PMID 25605792).

The description of methodology relating to the "oncogene signatures" is unclear.

This signature was described in Bild etal, Nature, 2006 and McQuerry JA, et al, 2019 “Pathway activity profiling of growth factor receptor network and stemness pathways differentiates metaplastic breast cancer histological subtypes”. BMC Cancer 19: 881 and is cited in Methods section Oncogene signatures

Please clearly state time points post infection for mouse analyses.

We collected lung samples from Mtb infected mice 12 – 20 weeks post infection. The lesions were heterogeneous and were individually classified using criteria described above.

Reference is made to "a list of genes unique to type I [interferon] genes [....]" (p29). Can the authors indicate the source of the information used for compiling this list?

The lists were compiled from Reactome, EMBL's European Bioinformatics Institute and GSEA databases. The links for all datasets are provided in Suppl.Table 8 “Expression of IFN pathway genes in Iba1+ cells from pauci- and multi-bacillary lesions of Mtb infected B6.Sst1S mouse lungs” in the “Pool IFN I & II gene sets” worksheet.

The discussion at present is very long, contains repetition of results and meanders on occasion.

Thank you for this suggestion, We critically revised the text for brevity and clarity.

Reviewer #1 (Significance):  

Strengths and limitations  

Strengths: multi-pronged analysis approaches for delineating molecular mechanisms of macrophage responses that might underpin susceptibility to M. tuberculosis infection; integration of mouse tissues and human blood samples  

Weaknesses: not all conclusions supported by data presented; some concerns related to experimental design and controls; links between findings in human cohort and the mechanistic insights gained in mouse macrophage model uncertain

The revised manuscript addresses every major and minor comment of the reviewers, including isotype controls and naïve T cells, to provide additional support for our conclusions. Our study revealed causal links between Myc hyperactivity with the deficiency of anti-oxidant defense and type I interferon pathway hyperactivity. We have shown that Myc hyperactivity in TNF-stimulated macrophages compromises antioxidant defense leading to autocatalytic lipid peroxidation and interferon-beta superinduction that in turn amplifies lipid peroxidation, thus, forming a vicious cycle of destructive chronic inflammation. This mechanism offers a plausible mechanistic explanation of for the association of Myc hyperactivity with poorer treatment outcomes in TB patients and provide a novel target for host-directed TB therapy.

Advance

The study has the potential to advance molecular understanding of the TNF-driven state of oxidative stress previously observed in B6.Sst1S macrophages and possible implications for host control of M. tuberculosis in vivo.

Audience

Experts seeking understanding of host factors mediating M. tuberculosis control, or failure thereof, with appreciation for the utility of the featured mouse model in assessing TB diseases progression and severe manifestation. Interest is likely extended to audience more broadly interested in TNF-driven macrophage (dys)function in infectious, inflammatory, and autoimmune pathologies.

Reviewer expertise

In preparing this review, I am drawing on my expertise in assessing macrophage responses and host defense mechanisms in bacterial infections (incl. virulent M. tuberculosis) through in vitro and in vivo studies. This includes but is not limited to macrophage infection and stimulation assays, microscopy, intra-macrophage replication of M. tuberculosis, analyses of lung tissues using multi-plex IHC and spatial transcriptomics (e.g. GeoMx). I am familiar with the interpretation of RNAseq analyses in human and mouse cells/tissues, but can provide only limited assessment of appropriateness of algorithms and analysis frameworks.

Reviewer #2 (Evidence, reproducibility and clarity):

Yabaji et al. investigated the effects of BMDMs stimulated with TNF from both WT and B6.Sst1S mice, which have previously been identified to contain the sst1 locus conferring susceptibility to Mycobacterium tuberculosis. They identified that B6.Sst1S macrophages show a superinduction of IFNß, which might be caused by increased c-Myc expression, expanding on the mechanistic insights made by the same group (Bhattacharya et al. 2021). Furthermore, prolonged TNF stimulation led to oxidative stress, which WT BMDMs could compensate for by the activation of the antioxidant defense via NRF2. On the other hand, B6.Sst1S BMDMs lack the expression of SP110 and SP140, co-activators of NRF2, and were therefore subjected to maintained oxidative stress. Yabaji et al. could link those findings to in vivo studies by correlating the presence of stressed and aberrantly activated macrophages within granulomas to the failure of Mtb control, as well as the progression towards necrosis. As the knowledge regarding Mtb progression and necrosis of granulomas is not yet well understood, findings that might help provide novel therapy options for TB are crucial. Overall, the manuscript has interesting findings with regard to macrophage responses in Mycobacteria tuberculosis infection.

However, in its current form there are several shortcomings, both with respect to the precision of the experiments and conclusions drawn.

In particular a) important controls are often missing, e.g. T-cells form non-immune mice in Fig. 6J, in F, effectivity of BCG in B6 mice in 6N; b) single experiments are shown throughout the manuscript, in particular western blots and histology without proper quantification and statistics, this is absolutely not acceptable; c) very few repetitions are shown in in vitro experiments, where there is no evidence for limitation in resources (usually not more than 3), it is not clear what "independent experiment means" - i.e. the robustness of the findings is questionable; d) data are often normalized multiple times, e.g. in the case of qPCR, and the methods of normalization are not clear (what house-keeping gene exactly?);

Moreover, experiments regarding IFN I signaling (e.g. short term TNF treatment of BMDMs to analyze LPO, making sure that the reporter mouse for IFNß works in vivo) and c-Myc (e.g. the increase after M-CSF addition might impact on other analysis as well and the experiments should be adjusted to control for this effect; MYC expression in the human samples) should be carefully repeated and evaluated to draw correct conclusions.

In addition, we would like to strongly encourage the authors to more precisely outline the experimental set-ups and figure legends, so that the reader can easily understand and follow them. In other words: The legends are - in part very - incomplete. In addition, the authors should be mindful of gene names vs. protein names and italicize where appropriate.

We appreciate a very thorough evaluation of our manuscript by this reviewer. Their insightful comments helped us improve the manuscript. As outlined below in point-by-point responses (1) we added important controls including isotype control antibodies in IFNAR blocking experiments and non-vaccinated T cells in T cell – macrophage interactions experiments; updated figure legends to indicate number of repeated experiment where a representative experiment is shown, numbers of mouse lungs and individual lesions, methods of data normalization, where it was missing. We also explained our in vitro experimental design and how we analyzed and excluded effects of media change and fresh CSF1 addition, by using a rest period before TNF stimulation and Mtb infection. The data shown in Suppl. Fig. 6C (previously Suppl. Fig. 5B) demonstrate that Myc levels induced by CSF1 return to the basal level at 12 h after media change. Our detailed in vitro protocol that contains these details has been published (Yabaji et al., STAR Protocols, 2022). We added new data demonstrating the ROS and LPO production at 6h of TNF stimulation, while the Ifnb1 mRNA super-induction occurred at 16 – 18 h, and edited the text to highlight these dynamics. The upregulation of Myc pathway in human samples does not necessarily mean the upregulation of Myc itself, it could be due to the dysregulation of downstream pathways. The upregulation of Myc pathway in the blood transcriptome associated with TB treatment failure most likely reflects greater proportion of immature cells in peripheral blood, possibly due to increased myelopoiesis. The detailed analysis of this cell populations in human patients is suggested by our findings but it is beyond the scope of this study.

The reviewer’s comments also suggested that a summary of our findings was necessary. The main focus of our study was to untangle connections between oxidative stress and Ifnb1 superinduction. It revealed that Myc hyperactivity caused partial deficiency of antioxidant defense leading to type I interferon pathway hyperactivity that in turn amplifies lipid peroxidation, thus establishing a vicious cycle driving inflammatory tissue damage.

Our laboratory worked on mechanisms of TB granuloma necrosis over more than two decades using genetic, molecular and immunological analyses in vitro and in vivo. It provided mechanistic basis for independent studies in other laboratories using our mouse model and further expanding our findings, thus supporting the reproducibility and robustness of our results and our lab’s expertise.

Specific comments to the experiments and data:

- Fig. 1E: Evaluation of differences in up- and downregulation between B6 and B6.Sst1S cells should highlight where these cells are within the heatmap, as it is only labelled with the clusters, or it should be depicted differently (in particular for cluster 1 and 2). Furthermore, a more simple labelling of the pathways would increase the readability of the data.

For our scRNAseq data presentation, we used formats accepted by computational community. To clarify Fig.1E, we added labels above B6 and B6.Sst1S-specific clusters.

- Fig. 2D, E: The staining legend is missing. For the quantification it is not clear what % total means. Is this based on the intensity or area? What do the dots represent in the bar chart? Is one data point pooled from several pictures? If not, the experiments need to be repeated, as three pictures might not be representative for evaluation.

- Fig. 2E: Statistics comparing B6/ B6,SsT1S with TNF (different) is required: Absence of induction is not a proof for a difference!

We included staining with NRF2-specific antibodies and performed area quantification per field using ImageJ to calculate the NRF2 total signal intensity per field. Each dot in the graph represents the average intensity of 3 fields in a representative experiment. The experiment was repeated 3 times. We included pairwise comparison of TNF-stimulated B6 and B6.Sst1S macrophages and updated the figure legend.

- Fig. 3E: Positive and negative control need to be depicted in the figure (see legend).

We have added the positive and negative controls for the determination of labile iron pool to the data in Fig. 3E and related Suppl. Fig. 3B and to Fig. 5D that also demonstrates labile iron determination.

- Fig. 3I: A quantification by flow cytometry or total cell counts are important, as 6% cell death in cell culture is a very modest observation. Otherwise, confocal images of the quantification would be a good addition to judge the specificity of the viability staining.

To validate the specificity of the viability staining method, we have provided fluorescent images as Suppl.Fig.3H. The main point of this experiment was to demonstrate a modest, but reproducible, increase in cell death in the sst1-mutant macrophages that suggested an IFNdependent oxidative damage. In our study, we did not focus on mechanisms of cell death, but on a state of chronic oxidative stress in the sst1 mutant live cells during TNF stimulation.

- Fig. 3I, J: What does one dot represent?

We performed this assay in 96 well format and each dot represent the % cell death in an individual well.

- Fig. 3K,L: For the B6 BMDMs it seems that p-cJun is highly increased at 12h in (L), while it is not in (K). On the other hand, for the B6.Sst1S BMDMs it peaks at 24h in (K), while in (L) it seems to at 12h. According to the data in (L) it seems that p-cJun is rather earlier and stronger activated in B6 BMDMs and has a weakened but prolonged activation in the B6.Sst1S BMDMs, which would not fit with your statement in the text that B6.Sst1S BMDMs show an upregulation.

These experiments need repetitions and quantification and statistiscs.

Fig. 3L: ASK1 seems to be higher at 12h for the B6 BMDMs and similar for both lines at 24h, which is not fitting to the statement in the text. ("Also, the ASK1 - JNK - cJun stress kinase axis was upregulated in B6.Sst1S macrophages, as compared to B6, after 12 - 36 h of TNF stimulation")

These experiments were repeated, and new data were added to highlight differences in ASK1 and c-Jun phosphorylation between B6 and B6.Sst1S at individual timepoints after TNF stimulation (presented in new Fig.3K). It demonstrated that after TNF stimulation the activation of stress kinases ASK1 and c-Jun initially increased in both genetic backgrounds. However, their upregulation was maintained exclusively in the sst1-susceptible macrophages from 24 to 36 h of TNF stimulation, while in the resistant macrophages their upregulation was transient. Thus, during prolonged TNF stimulation, B6.Sst1S macrophages experience stress that cannot be resolved, as evidenced by this kinetic analysis. The quantification of the band intensity was added to Western blot images above individual lanes.

Reviewer 2 pointed to missing isotype control antibodies in Fig.3 and Fig.4:

- Figure 3J: the isotype control for the IFNAR antibody is missing

- Figure 4E: It seems the isotype control itself has already an effect in the reduction of IFNb.

- Fig. 4H: It seems that the Isotype control antibody had an effect to increase 4-HNE (compared to TNF stimulated only).

We always include isotype control antibodies in our experiments because antibodies are known to modulate macrophage activation via binding to Fc receptor. To address the reviewer’s comments, we updated all panels that present the effects of IFNAR1 blockade with isotypematched non-specific control antibodies in the revised manuscript. Specifically, we included isotype control in Fig. 3M (previously Fig.3J), Fig.4I, Suppl.4E-G, Fig.6L-M), Suppl.Fig.7I (previously Suppl.Fig.6F).

- Fig.4A - C: "IFNAR1 blockade, however, did not increase either the NRF2 and FTL protein levels, or the Fth, Ftl and Gpx1 mRNA levels above those treated with isotype control antibodies"

Maybe not above the isotype but it is higher than the TNF alone stimulation at least for NRF2 at 8h and for Ftl at both time points. Why does the isotype already cause stimulation/induction of the cells? !These experiments need repetitions and quantification and statistics!

To determine specific effects of IFNAR blockade we compared effects of non-specific isotype control and IFNAR1-specific antibodies. In our experiments, the isotype control antibody modestly increased of Nrf2 and Ftl protein levels and the Fth and Ftl mRNA levels, but their effects were similar to the effect of IFNAR-specific antibody. The non-IFN -specific effects of antibodies, although are of potential biological significance, are modest in our model and their analysis is beyond the scope of this study.

- Fig.4H Was the AB added also at 12h post stimulation? Figure legend should be adjusted.

The IFNAR1 blocking antibodies and isotype control antibodies were added at 2 h after TNF stimulation in Fig.4H and 4I, as described in the corresponding figure legend. The data demonstrating effects of IFNAR blockade after 12, 24,and 33h of TNF stimulation are presented in Suppl.Fig.4 E-G.

- Figure 4I: How was the data measured here, i.e. what is depicted? The isotype control is missing. It seems a two-way ANOVA was used, yet it is stated differently. The figure legend should be revised, as Dunnett's multiple comparison would only check for significances compared to the control.

The microscopy images and bar graphs were updated to include isotype control and presented in Suppl. Fig.4E - G of the revised version. We also revised the statistical analysis to include correction for multiple comparisons.

- Figure 4C and subsequent: How exactly was the experiment done (house-keeping gene)?

We included the details in the figure legends of revised version. We quantified the gene expression by DDCt method using b-actin (for Fig. 4C-E) and 18S (For Fig. 4F and G) as internal controls.

- Figure 4D,E: Information on cells used is missing. Why the change in stimulation time? Did it not work after 12h? Then the experiments in A-C should be repeated for 16h.

The updated Fig. 4D and E present comparison of B6 and B6.Sst1S BMDMs clearly demonstrating significant difference between these macrophages in Ifnb1 mRNA expression 16 h after TNF stimulation, in agreement with our previous publication(Bhattacharya, et al., 2021). There we studied the time course of responses of B6 and B6.Sst1S macrophages to TNF at 2h intervals and demonstrated the divergence between their activation trajectories starting at 12 h of TNF stimulation Therefore, to reveal the underlying mechanisms we focus our analyses on this critical timepoint, i.e. as close to the divergence as possible. However, the difference between the strains in Ifnb1 mRNA expression achieved significance only by 16h of TNF stimulation. That is why we have used this timepoint for the Ifnb1 and Rsad2 analyses. It clearly shows that the superinduction was not driven by the positive feedback via IFNAR, as has been shown by the Ivashkiv lab for B6 wild type macrophages previously PMID 21220349.

- Figure 4E: It would be helpful to see if these transcripts are actually translated into protein levels, e.g. perform an ELISA. Authors state that IFNAR blockages does not alter the expression but you statistic says otherwise.

- The data for Ifnb expression (or better protein level) should be provided for B6 BMDMs as well.

We have previously reported the differences in Ifnb protein secretion (He et al., Plos Pathogens, 2013 and Bhattacharya et al., JCI 2021). We use mRNA quantification by qRT-PCR as a more sensitive and direct measurement of the sst1-mediated phenotype. The revised Fig.4D and E include responses of B6 in addition to the B6.Sst1S to demonstrate that the IFNAR blockade does not reduce the Ifnb1 mRNA levels in TNF-stimulated B6.Sst1S mutant to the B6 wild type levels. A slight reduction can be explained by a known positive feedback loop in the IFN-I pathway (see above). In this experiment we emphasized that the effect of the sst1 locus is substantially greater, as compared to the effect of the IFNAR blockade (Fig.4D), and updated the text accordingly.

- Fig. 4F: To what does the fold induction refer to? If it is again to unstimulated cells, then why is the induction now so much higher than in (E) where it was only 50x (now to 100x).

- Figure 4G: Again to what is the fold induction referring to? It seems your Fer-1 treatment only contains 2 data points. This needs to be fixed.

Yes, the fold induction was calculated by normalizing mRNA levels to untreated control incubated for the same time. Regarding the variation in Ifnb1 mRNA levels - a two-fold variation is not unusual in these experiments that may result in the Ifnb1 mRNA superinduction ranging from 50 -200-fold at this timepoint (16h). The graph in Fig.4G was modified to make all datapoints more visible.

- "These data suggest that type I IFN signaling does not initiate LPO in our model but maintains and amplifies it during prolonged TNF stimulation that, eventually, may lead to cell death". Data for a short term TNF stimulation are not shown, however, so it might impact also on the initiation of LPO.

- The overall conclusion drawn from Fig. 3 and 4 is not really clear with regard that IFN does not initiate LPO. Where is that shown? Data on earlier stimulation time points should be added to make this clear.

We demonstrated ROS production (new Suppl.Fig.3G) and the rate of LPO biosynthesis (new Suppl.Fig.4E-F) at 6 h post TNF stimulation, while the Ifnb1 superinduction occurs between 12-18 h post TNF stimulation. This temporal separation supports our conclusion that IFN-β superinduction does not initiate LPO. We clarified it in the text:

“Thus, Ifnb1 super-induction and IFN-I pathway hyperactivity in B6.Sst1S macrophages follow the initial LPO production, and maintain and amplify it during prolonged TNF stimulation”. (Previously: These data suggest that type I IFN signaling does not initiate LPO in our model). We also edited the conclusion in this section to explain the hierarchy of the sst1-regulated AOD and IFN-I pathways better:

“Taken together, the above experiments allowed us to reject the hypothesis that IFN-I hyperactivity caused the sst1-dependent AOD dysregulation. In contrast, they established that the hyperactivity of the IFN-I pathway in TNF-stimulated B6.Sst1S macrophages was itself driven by the initial dysregulation of AOD and iron-mediated lipid peroxidation. During prolonged TNF stimulation, however, the IFN-I pathway was upregulated, possibly via ROS/LPOdependent JNK activation, and acted as a potent amplifier of lipid peroxidation”.

We believe that these additional data and explanation strengthen our conclusions drawn from Figures 3 and 4.

- "A select set of mouse LTR-containing endogenous retroviruses (ERV's) (Jayewickreme et al, 2021), and non-retroviral LINE L1 elements were expressed at a basal level before and after TNF stimulation, but their levels in the B6.Sst1S BMDMs were similar to or lower than those seen in B6". This sentence should be revised as the differences between B6 and B6.Sst1S BMDMs seem small and are not there after 48h anymore. Are these mild changes really caused by the mutation or could they result from different housing conditions and/or slowly diverging genetically lines. How many mice were used for the analysis? Is there already heterogeneity between mice from the same line?

We agree with the reviewer that the data presented in Suppl.Fig.4 (Suppl.Fig.5 in the revised version) indicated no increase in single- and double-stranded transposon RNAs in the B6.Sst1S macrophages. The purpose of these experiment was to test the hypothesis that increased transposon expression might be responsible for triggering the superinduction of type I interferon response in TNF-stimulated B6.Sst1S macrophages. In collaboration with a transposon expert Dr. Nelson Lau (co-author of this manuscript) we demonstrated that transposon expression was not increased above the B6 level and, thus, rejected this attractive hypothesis. We explained the purpose of this experiment in the text and adequately described our findings as “the levels in the B6.Sst1S BMDMs were similar to or lower than those seen in B6”…and concluded that ” the above analyses allowed us to exclude the overexpression of persistent viral or transposon RNAs as a primary mechanism of the IFN-I pathway hyperactivity” in the sst1-mutant macrophages.

- Fig. 5A: Indeed, it even seems that Myc is upregulated for the mutant BMDMs. Yet, there are only 2 data points for B6 12h.

These experiments need repetitions and quantification and statistics.

We observed these differences in c-Myc mRNA levels by independent methods: RNAseq and qRT-PCR. The qRT-PCR experiments were repeated 3 times. A representative experiment in Fig.5A shows 3 data points for each condition. We reformatted the panel to make all data points clearly visible.

- Fig. 5B: Why would the protein level decrease in the controls over 6h of additional cultivation? Is this caused by fresh M-CSF? In this case maybe cells should be left to settle for one day before stimulating them to properly compare c-Myc induction. Comment on two c-Myc bands is needed. At 12h only the upper one seems increased for TNF stimulated mutant BMDMs compared to B6 BMDMs.

We agree with the reviewer’s point that cells need to be rested after media change that contains fresh CSF-1. Indeed, in Suppl.Fig.6C, we show that after media change containing 10% L929 supernatant (a source of CSF1) there is an increase in c-Myc protein levels that takes approximately 12 hours to return to baseline.

Our protocol includes resting period of 18-24 h after medium change before TNF stimulation.

We updated Methods to highlight this detail. Thus, the increase in c-Myc levels we observe at 12 h of TNF stimulation (Fig.5B) is induced by TNF, not the addition of growth factors, as further discussed in the text.

The two c-Myc bands observed in Fig.5B,I and J, are similar to patterns reported in previous studies that used the same commercial antibodies (PMIDs: 24395249, 24137534, 25351955). Whether they correspond to different c-Myc isoforms or post-translational modifications is unknown.

- Fig. 5A,B: It seems that not all the RNA is translated into protein, as c-Myc at 12h in the mutant BMDMs seems to be lower than at 6h, while the gene expression implicates it vice versa.

In addition to Fig.5B, the time course of Myc protein expression up to 24 h is presented in new panels Fig. 5I-5J. It demonstrates the gradual decrease of Myc protein levels. The observed dissociation between the mRNA and protein levels in the sst1-mutant BMDMs at 12 and 24 h is most likely due to translation inhibition as a result of the development of the integrated stress response, ISR (as shown in our previous publication by Bhattacharya et al., JCI, 2021). Translation of Myc is known to be particularly sensitive to the ISR (PMID18551192, PMID25079319, PMID28490664). Perhaps, the IFN-driven ISR may serve as a backup mechanism for Myc downregulation. We are planning to investigate these regulatory mechanisms in greater detail in the future.

- Fig. 5J: Indeed, the inhibitor seems to cause the downregulation of the proteins. Explanation?

This experiment was repeated twice and the average normalized densitometry values are presented in the updated Fig.5J. The main question addressed in this experiment was whether hyperactivity of JNK in TNF-stimulated sst1 mutant macrophages contributed to Myc upregulation, as had been previously shown in cancer. Comparing effects of JNK inhibition on phospho-cJun and c-Myc protein levels in TNF stimulated B6.Sst1S macrophages (updated Fig.5J), we rejected the hypotghesis that JNK activity might have a major role in c-Myc upregulation in sst1 mutant macrophages.

- "TNF stimulation tended to reduce the LPO accumulation in the B6 macrophages and to increase it in the B6.Sst1S ones" However, this is not apparent in Sup. Fig. 6B. Here it seems that there might be a significant increase.

Suppl.Fig.6B (currently Suppl.Fig.7B) shows the 4-HNE accumulation at day 3 post infection. The data obtained after 5 days of Mtb infection are shown in Fig.6A. We clarified this in the text: “By day 5 post infection, TNF stimulation induced significant LPO accumulation only in the B6.Sst1S macrophages (Fig.6A)”.

- Fig. 6B: Mtb and 4-HNE should be shown in two different channels in order to really assign each staining correctly.

What time point is this? Are the mycobacteria cleared at MOI1, since it looks that there are fewer than that? How does this look like for the B6 BMDMs? Are there even less mycobacteria?

We included B6 infection data to the updated Fig.6B and added Suppl.Fig.7C and 7D that address this reviewer’s comment. The data represent day 5 of Mtb infection as indicated in the updated Fig.6B and Suppl.Fig.7C and 7D legends. New Suppl.Fig.7D shows quantification of replicating Mtb using Mtb replication reporter stain expressing single strand DNA binding protein GFP fusion, as described in Methods. We observed fewer Mtb and a lower percentage of replicating Mtb in B6 macrophages, but we did not observe a complete Mtb elimination in either background.

We used red fluorescence for both Mtb::mCherry and 4-HNE staining to clearly visualize the SSB-GFP puncta in replicating Mtb DNA. In the revised manuscript, we have included the relevant channels in Suppl. Fig.7C and D to demonstrate clearly distinct patterns of Mtb::mCherry and 4-HNE signals. We did not aim to quantify the 4-HNE signal intensity in this experiment. For the 4-HNE quantification we use Mtb that expressed no reporter proteins (Fig.6A-B and Suppl.Fig.7A-B).

- Fig 6E: In the context of survival a viability staining needs to be included, as well as the data from day 0. Then it needs to be analyzed whether cell numbers remain the same from D0 or if there is a change.

We updated Fig.6 legend to indicate that the cell number percentages were calculated based on the number of cells at Day 0 (immediately after Mtb infection). We routinely use fixable cell death staining to enumerate cell death to exclude artifacts due to cell loss. Brief protocol containing this information is included in Methods section. The detailed protocol including normalization using BCG spike has been published – Yabaji et al, STAR Protocols, 2022. Here we did not present dead cell percentage as it remained low and we did not observe damage to macrophage monolayers. The fold change of Mtb was calculated after normalization using Mtb load at Day 0 after infection and washes.

"The 3D imaging demonstrated that YFP-positive cells were restricted to the lesions, but did not strictly co-localize with intracellular Mtb, i.e. the Ifnb promoter activity was triggered by inflammatory stimuli, but not by the direct recognition of intracellular bacteria. We validated the IFNb reporter findings using in situ hybridization with the Ifnb probe, as well as anti-GFP antibody staining (Suppl.Fig.8B - E)." The colocalization is not present within the tissue sections. It seems that the reporter line does not show the same staining pattern in vivo as the IFNß probe or the anti GFP antibody staining. The reporter line has to be tested for the specificity of the staining. Furthermore, to state that it was restricted to the lesions, an uninvolved tissue area needs to be depicted.

The Ifnb secreting cells are notoriously difficult to detect in vivo using direct staining of the protein. Therefore, lineage tracing of reporter expression are used as surrogates. The Ifnb reporter used in our study has been developed by the Locksley laboratory (Scheu et al., PNAS, 2008, PMID: 19088190) and has been validated in many independent studies. The reporter mice express the YFP protein under the control of the Ifnb1 promoter. The YFP protein accumulates within the cells, while Ifnb protein is rapidly secreted and does not accumulate in the producing cells in appreciable amounts. Also, the kinetics of YFP protein degradation is much slower as compared to the endogenous Ifnb1 mRNA that was detected using in situ hybridization. Thus, there is no precise spatiotemporal coincidence of these readouts in Ifnb expressing cells in vivo. However, this methodology more closely reflect the Ifnb expressing cells in vivo, as compared to a Cre-lox mediated lineage tracing approach. In the revised manuscript we demonstrate that both YFP and mRNA signals partially overlap (Suppl.Fig.12B). In Suppl.Fig.12B. we also included a new panel showing no YFP expression in the uninvolved area of the reporter mice infected with Mtb. The YFP expression by activated macrophages is demonstrated by co-staining with Iba1- and iNOS-specific antibodies (new Fig.7D and Suppl.Fig.13A). Our specificity control also included TB lesions in mice that do not carry the YFP reporter and did not express the YFP signal, as reported elsewhere (Yabaji et al., BioRxiv, https://doi.org/10.1101/2023.10.17.562695).

- Are paucibacillary and multibacillary lesions different within the same animal or does one animal have one lesion phenotype? If that is the case, what is causing the differences between mice? Bacterial counts for the mice are required.

The heterogeneity of pulmonary TB lesions has been widely acknowledged in clinic and highlighted in recent experimental studies. In our model of chronic pulmonary TB (described in detail in Yabaji et al., https://doi.org/10.1101/2025.02.28.640830 and https://doi.org/10.1101/2023.10.17.562695) the development of pulmonary TB lesions is not synchronized, i.e. the lesions are heterogeneous between the animals and within individual animals at the same timepoint. Therefore, we performed a lesion stratification where individual lesions were classified by a certified veterinary pathologist in a blinded manner based on their morphology (H&E) and acid fast staining of the bacteria, as depicted in Suppl.Fig.8.

- "Among the IFN-inducible genes upregulated in paucibacillary lesions were Ifi44l, a recently described negative regulator of IFN-I that enhances control of Mtb in human macrophages (DeDiego et al, 2019; Jiang et al, 2021) and Ciita, a regulator of MHC class II inducible by IFNy, but not IFN-I (Suppl.Table 8 and Suppl.Fig.10 D-E)." Why is Sup. Fig. 10 D, E referred to? The figure legend is also not clear, e.g. what means "upregulated in a subset of IFN-inducible genes"? Input for the hallmarks needs to be defined.

These data is now presented in Suppl.Fig.11 and following the reviewer’s comment, we moved reference to panels 11D – E up to previous paragraph in the main text, where it naturally belongs . We also edited the figure legend to refer to the list of IFN-inducible genes compiled from the literature that is discussed in the text. We appreciate the reviewer’s suggestion that helped us improve the text clarity. The inputs for the Hallmark pathway analysis are presented in Suppl.Tables 7 and 8, as described in the text.

- Fig. 7C: Single channel pictures are required as it is hard to see the differences in staining with so many markers. Why is there no iNOS expression in the bottom row? What does the rectangle indicate on the bottom right? As black is chosen for DAPI, it is not visible at all. In case the signal is needed a visible a color should be chosen.

We thoroughly revised this figure to address the reviewer’s concern about the lack of clarity. We provide individual channels for each marker in Fig.7D – E and Suppl.Fig.13F. We have to use DAPI in these presentation in gray scale to better visualize other markers.

- "In the advanced lesions these markers were primarily expressed by activated macrophages (Iba1+) expressing iNOS and/or Ifny (YFP+)(Fig.7D)" Iba1 is needed in the quantification. Based on the images, iNOS seems to be highly produced in Iba1 negative cells. Which cells do produce it then? Flow cytometry data for this quantification are required. This would allow you to specifically check which cells express the markers and allow for a more precise analysis of double positive cells.

Currently these data demonstrating the co-localization of stress markers phospho-c-Jun and Chac1 with YFP are presented in Fig.7E (images) and Suppl.Fig.13D (quantification). The co-localization of stress markers phospho-cJun and Chac1 with iNOS is presented in Suppl.Fig.13F (images) and Suppl.Fig.13E (quantification). We agree that some iNOS+ cells are Iba1-negative (Fig.7D). We manually quantified percentages of Iba1+iNOS+ double positive cells and demonstrated that they represent the majority of the iNOS+ population(Suppl.Fig.13A). Regarding the required FACS analysis, we focus on spatial approaches because of the heterogeneity of the lesions that would be lost if lungs are dissociated for FACS. We are working on spatial transcriptomics at a single cell resolution that preserves spatial organization of TB lesions to address the reviewer’s comment and will present our results in the future.

- Results part 6: In general, can you please state for each experiment at what time point mice were analyzed? You should include an additional macrophage staining (e.g. MerTK, F4/80), as alveolar macrophages are not staining well for Iba1 and you might therefore miss them in your IF microscopy. It would be very nice if you could perform flow cytometry to really check on the macrophages during infection and distinguish subsets (e.g. alveolar macrophages, interstitial macrophages, monocytes).

We have included the details of time post infection in figure legends for Fig.7, Suppl.Figures 8, 9, 12B, 13, 14A of the revised manuscript. We have performed staining with CD11b, CD206 and CD163 to differentiate the recruited and lung resident macrophages and determined that in chronic pulmonary TB lesions in our model the vast majority of macrophages are recruited CD11b+, but not resident (CD206+ and CD163+) macrophages. These data is presented in another manuscript (Yabaji et al., BioRxiv https://doi.org/10.1101/2023.10.17.562695).

- Spatial sequencing: The manuscript would highly profit from more data on that. It would be very interesting to check for the DEGs and show differential spatial distribution. Expression of marker genes should be inferred to further define macrophage subsets (e.g. alveolar macrophages, interstitial macrophages, recruited macrophages) and see if these subsets behave differently within the same lesion but also between the lesions. Additional bioinformatic approaches might allow you to investigate cell-cell interactions. There is a lot of potential with such a dataset, especially from TB lesions, that would elevate your findings and prove interesting to the TB field.

- "Thus, progression from the Mtb-controlling paucibacillary to non-controlling multibacillary TB lesions in the lungs of TB susceptible mice was mechanistically linked with a pathological state of macrophage activation characterized by escalating stress (as evidenced by the upregulation phospho-cJUN, PKR and Chac1), the upregulation of IFNβ and the IFN-I pathway hyperactivity, with a concurrent reduction of IFNγ responses." To really show the upregulation within macrophages and their activation, a more detailed IF microscopy with the inclusion of additional macrophage markers needs to be provided. Flow cytometry would enable analysis for the differences between alveolar and interstitial macrophages, as well as for monocytes. As however, it seems that the majority of iNOS, as well as the stress associated markers are not produced by Iba1+ cells. Analyzing granulocytes and T lymphocytes should be considered.

We appreciate the reviewer’s suggestion. Indeed, our model provides an excellent opportunity to investigate macrophage heterogeneity and cell interactions within chronic TB lesions. We are working on spatial transcriptomics at a single cell resolution that would address the reviewer’s comment and will present our results in the future.

In agreement with classical literature the overwhelming majority of myeloid cells in chronic pulmonary TB lesions is represented by macrophages. Neutrophils are detected at the necrotic stage, but our study is focused on pre-necrotic stages to reveal the earlier mechanisms predisposing to the necrotization. We never observed neutrophils or T cells expressing iNOS in our studies.

- It's mentioned in the method section that controls in the IF staining were only fixed for 10min, while the infected cells were fixed for 30min. Consistency is important as the PFA fixation might impact on the fluorescence signal. Therefore, controls should be repeated with the same fixation time.

We have carefully considered the impact of fixation time on fluorescence and have separately analyzed the non-infected and infected samples to address this concern. For the non-infected samples, we examined the effect of TNF in both B6 and B6.Sst1S backgrounds, ensuring that a consistent fixation protocol (10 min) was applied across all experiments without Mtb infection.

For the Mtb infection experiments, we employed an optimized fixation protocol (30 min) to ensure that Mtb was killed before handling the plates, which is critical for preserving the integrity of the samples. In this context, we compared B6 and B6.Sst1S samples to evaluate the effects of fixation and Mtb infection on lipid peroxidation (LPO) induction.

We believe this approach balances the need for experimental consistency with the specific requirements for handling infected cells, and we have revised the manuscript to reflect this clarification.

- Reactive oxygen species levels should be determined in B6 and B6.Sst1S BMDMs (stimulated and unstimulated), as they are very important for oxidative stress.

We have conducted experiments to measure ROS production in both B6 and B6.Sst1S BMDMs and demonstrated higher levels of ROS in the susceptible BMDMs after prolonged TNF stimulation (new Fig.3I-J and Suppl. Fig. 3G). Additionally, we have previously published a comparison of ROS production between B6 and B6.Sst1S by FACS (PMID: 33301427), which also supports the findings presented here.

- Sup. Fig 2C: The inclusion of an unstimulated control would be advisable in order to evaluate if there are already difference in the beginning.

We have included the untreated control to the Suppl. Fig. 2C (currently Suppl. Fig. 2D) in the revised manuscript.

- Sup. Fig. 3F: Why is the fold change now lower than in Fig. 4D (fold change of around 28 compared to 120 in 4D)?

The data in Fig.4D (Fig.4E in the revised manuscript) and Suppl.Fig.3F (currently Suppl.Fig.4C) represent separate experiments and this variation between experiments is commonly observed in qRT-PCR that is affected by slight variations in the expression in unsimulated controls used for the normalization and the kinetics of the response. This 2-4 fold difference between same treatments in separate experiments, as compared to 30 – 100 fold and higher induction by TNF does not affect the data interpretation.

- Sup. Fig. 5C, D: The data seems very interesting as you even observe an increase in gene expression. Data for the B6 mice should be evaluated for increase to a similar level as the TNF treated mutants. Data on the viability of the cells are necessary, as they no longer receive MCSF and might be dying at this point already.

To ensure that the observed effects were not confounded by cytotoxicity, we determined non-toxic concentrations of the CSF1R inhibitors during 48h of incubation and used them in our experiments that lasted for 24h. To address this valid comment, we have included cell viability data in the revised manuscript to confirm that the treatments did not result in cell death (Suppl. Fig. 6D). This experiment rejected our hypothesis that CSF1 driven Myc expression could be involved in the Ifnb superinduction. Other effects of CSF1R inhibitors on type I IFN pathway are intriguing but are beyond the scope of this study.

- Sup. Fig 12: the phospho-c-Jun picture for (P) is not the same as in the merged one with Iba1. Double positive cells are mentioned to be analyzed, but from the staining it appears that P-c-Jun is expressed by other cells. You do not indicate how many replicates were counted and if the P and M lesions were evaluated within the same animal. What does the error bar indicate? It seems unlikely from the plots that the double positive cells are significant. Please provide the p values and statistical analysis.

We thank the reviewer for bringing this inadvertent field replacement in the single phospho-cJun channel to our attention. However, the quantification of Iba1+phospho-cJun+ double positive cells in Suppl.Fig.12 and our conclusions were not affected. In the revised manuscript, images and quantification of phospho-cJun and Iba1 co-expression are shown in new Suppl.Fig.13B and C, respectively. We have also updated the figure legends to denote the number of lesions analyzed and statistical tests. Specifically, lesions from 6–8 mice per group (paucibacillary and multibacillary) were evaluated. Each dot in panels Suppl.Fig.13 represent individual lesions.

- Sup. Fig. 13D (suppl.Fig.15D now): What about the expression of MYC itself? Other parts of the signaling pathway should be analyzed(e.g. IFNb, JNK)?

The difference in MYC mRNA expression tended to be higher in TB patients with poor outcomes, but it was not statistically significant after correction for multiple testing. The upregulation of Myc pathway in the blood transcriptome associated with TB treatment failure most likely reflects greater proportion of immature cells in peripheral blood, possibly due to increased myelopoiesis. Pathway analysis of the differentially expressed genes revealed that treatment failures were associated with the following pathways relevant to this study: NF-kB Signaling, Flt3 Signaling in Hematopoietic Progenitor Cells (indicative of common myeloid progenitor cell proliferation), SAPK/JNK Signaling and Senescence (possibly indicative of oxidative stress). The upregulation of these pathways in human patients with poor TB treatment outcomes correlates with our findings in TB susceptible mice.

- In the mfIHC you he usage of anti-mouse antibodies is mentioned. Pictures of sections incubated with the secondary antibody alone are required to exclude the possibility that the staining is not specific. Especially, as this data is essential to the manuscript and mouse-antimouse antibodies are notorious for background noise.

We are well aware of the technical difficulties associated with using mouse on mouse staining. In those cases, we use rabbit anti-mouse isotype specific antibodies specifically developed to avoid non-specific background (Abcam cat#ab133469). Each antibody panel for fluorescent multiplexed IHC is carefully optimized prior to studies. We did not use any primary mouse antibodies in the final version of the manuscript and, hence, removed this mention from the Methods.

- In order to tie the story together, it would be interesting to treat infected mice with an INFAR antibody, as well as perform this experiment with a Myc antibody. According to your data, you might expect the survival of the mice to be increased or bacterial loads to be affected.

In collaboration with the Vance laboratory, we tested effects of type I IFN pathway inhibition in B6.Sst1S mice on TB susceptibility: either type I receptor knockout or blocking antibodies increased their resistance to virulent Mtb (published in Ji et al., 2019; PMID 31611644). Unfortunately, blocking Myc using neutralizing antibodies in vivo is not currently achievable. Specifically blocking Myc using small molecule inhibitors in vivo is notoriously difficult, as recognized in oncology literature. We consider using small molecule inhibitors of either Myc translation or specific pathways downstream of Myc in the future.

- It is surprising that you not even once cite or mention your previous study on bioRxiv considering the similarity of the results and topic (https://doi.org/10.1101/2020.12.14.422743). Is not even your Figure 1I and Figure 2 J, K the same as in that study depicted in Figure 4?

The reviewer refers to the first version of this manuscript uploaded to BioRxiv, but it has never been published. We continued this work and greatly expanded our original observations, as presented in the current manuscript. Therefore, we do not consider the previous version as an independent manuscript and, therefore, do not cite it.

- Please revise spelling of the manuscript and pay attention to write gene names in italics

Thank you, we corrected the gene and protein names according to current nomenclature.

Minor points:

- Fig. 1: Please provide some DEGs that explain why you used this resolution for the clustering of the scRNAseq data and that these clusters are truly distinct from each other.

Differential gene expression in clusters is presented in Suppl.Fig.1C (interferon response) and Suppl.Fig.1D (stress markers and interferon response previously established in our studies).

- Fig. 1F: What do the two lines represent (magenta, green)?

The lines indicate pseudotime trajectories of B6 (magenta) and B6.Sst1S (green) BMDMs.

- Fig. 1F, G: Why was cluster 6 excluded?

This cluster was not different between B6 and B6.Sst1S, so it was not useful for drawing the strain-specific trajectories.

- Fig. 1E, G, H: The intensity scales are missing. They are vital to understand the data.

We have included the scale in revised manuscript (Fig.1E,G,H and Suppl.Fig.1C-D).

- Fig. 2G-I: please revise order, as you first refer to Fig. 2H and I

We revised the panels’ order accordingly

- Fig. 5: You say the data represents three samples but at least in D and E you have more. Please revise. Why do you only include at (G) the inhibitor only control?

We added the inhibitor only controls to Fig. 5D - H. We also indicated the number of replicates in the updated Fig.5 legend.

- Figure 7A, Sup. Fig. 8: Are these maximum intensity projection? Or is one z-level from the 3D stack depicted?

The Fig. 7A shows 3D images with all the stacks combined.

- Fig. 7B: What do the white boxes indicate?

We have removed this panel in the revised version and replaced it with better images.

- Sup. Fig. 1A: The legend for the staining is missing

The Suppl. Fig.1A shows the relative proportions of either naïve (R and S) or TNFstimulated (RT and ST) B6 or B6.Sst1S macrophages within individual single cell clusters depicted in Fig.1B. The color code is shown next to the graph on the right.

- Sup. Fig. 1B: The feature plots are not clear: The legend for the expression levels is missing. What does the heading means?

We updated the headings, as in Fig.1C. The dots represent individual cells expressing Sp110 mRNA (upper panels) and Sp140 mRNA (lower panels).

- Sup. Fig. 3C: The scale bar is barely visible.

We resized the scale bar to make it visible and presented in Suppl. Fig.3E (previously Suppl. Fig.3C).

- Sup. Fig. 3D: There is not figure legend or the legend to C-E is wrong.

- Sup. Fig. 3F, G: You do not state to what the data is relative to.

We identified an error in the Suppl.Fig.3 legend referring to specific panels. The Suppl.Fig.3 legend has been updated accordingly. New panels were added and Suppl.Fig.3-G panels are now Suppl.Fig.4C-D.

- Sup. Fig. 3H: It seems you used a two-way ANOVA, yet state it differently. Please revise the figure legend, as Dunnett's multiple comparison would only check for significances compared to the control.

Following the reviewer’s comment, we repeated statistical analysis to include correction for multiple comparisons and revised the figure and legend accordingly.

- Sup. Fig. 4A, B: It is not clear what the lines depict as the legend is not explained. Names that are not required should be changed to make it clear what is depicted (e.g. "TE@" what does this refer to?)

This previous Sup. Fig 4 is now Sup. Fig. 5. The “TE@” is a leftover label from the bioinformatics pipeline, referring to “Transposable Element”. We apologize for this confusion and have removed these extraneous labels. We have also added transposon names of the LTR (MMLV30 and RTLV4) and L1Md to Suppl.Fig.5A and 5B legend, respectively.

- Sup. 4B: What does the y-scale on the right refer to?

We apologize for the missing label for the y-scale on the right which represents the mRNA expression level for the SetDB1 gene, which has a much lower steady state level than the LINE L1Md, so we plotted two Y-scales to allow both the gene and transposon to be visualized on this graph.

- Sup. 4C: Interpretation of the data is highly hindered by the fact that the scales differ between the B6 and B6.Sst1. The scales are barely visible.

We apologize for the missing labels for the y-scales of these coverage plots, which were originally meant to just show a qualitative picture of the small RNA sequencing that was already quantitated by the total amounts in Sup. 4B. We have added thee auto-scaled Y-scales to Sup. 4C and improved the presentation of this figure.

- Sup. Fig. 5A, B: Is the legend correct? Did you add the antibody for 2 days or is the quantification from day 3?

We recognize that the reviewer refers to Suppl.Fig.6A-B (Suppl.Fig.7A-B in the revised manuscript). We did not add antibodies to live cells. The figure legend describes staining with 4HNE-specific antibodies 3 days post Mtb infection.

- Sup. Fig. 8A: Are the "early" and "intermediate" lesions from the same time points? What are the definitions for these stages?

We discussed our lesion classification according to histopathology and bacterial loads above. Of note, in the revised manuscript we simplified our classification to denote paucibacillary and multibacillary lesions only. We agree with reviewers that designation lesions as early, intermediate and advanced lesions were based on our assumptions regarding the time course of their progression from low to high bacterial loads.

- Sup. Fig. 8E: You should state that the bottom picture is an enlargement of an area in the top one. Scale bars are missing.

We replaced this panel with clearer images in Suppl.Fig.12B.

- Sup. Fig. 11A: The IF staining is only visible for Iba and iNOS. Please provide single channels in order to make the other staining visible.

Suppl.Fig.11A (now Suppl.Fig.13B) shows the low-magnification images of TB lesions. In the Fig. 7 and Suppl. Fig. 13F of the revised manuscript we provided images for individual markers.

- Sup. Fig. 13A (Suppl.Fig.15A now): Your axis label is not clear. What do the numbers behind the genes indicate? Why did you choose oncogene signatures and not inflammatory markers to check for a correlation with disease outcome?

X axis of Suppl.Fig.15A represent pre-defined molecular signature gene sets MSigDB) in Gene Set Enrichment Analysis (GSEA) database (https://www.gseamsigdb.org/gsea/msigdb). On Y axis is area under curve (AUC) score for each gene set.

- Sup. 13D(Suppl.Fig.15D now): Maybe you could reorder the patients, so that the impression is clearer, as right now only the top genes seem to show a diverging gene signature, while the rest gives the impression of an equal distribution.

The Myc upregulated gene set myc_up was identified among top gene sets associated with treatment failure using unbiased ssGSEA algorithm. We agree with the reviewer that not every gene in the myc_up gene set correlates with the treatment outcome. But the association of the gene set is statistically significant, as presented in Suppl.Fig.15B – C.

- The scale bars for many microscopy pictures are missing.

We have included clearly visible scale bars to all the microscopy images in the revised version.

- The black bar plots should be changed (e.g. in color), since the single data points cannot be seen otherwise.

- It would be advisable that a consistent color scheme would be used throughout the manuscript to make it easier to identify similar conditions, as otherwise many different colours are not required and lead right now rather to confusion (e.g. sometimes a black bar refers to BMDMs with and sometimes without TNF stimulation, or B6 BMDMs). Furthermore, plot sizes and fonts should be consistent within the manuscript (including the supplemental data)

We followed this useful suggestion and selected consistent color codes for B6 and B6.Sst1S groups to enhance clarity throughout the revised manuscript.

Within the methods section:

- At which concentration did you use the IFNAR antibody and the isotype?

We updated method section by including respective concentrations in the revised manuscript.

- Were mice maintained under SPF conditions? At what age where they used?

Yes, the mice are specific pathogen free. We used 10 - 14 week old mice for Mtb infection.

- The BMDM cultivation is not clear. According to your cited paper you use LCCM but can you provide how much M-CSF it contains? How do you make sure that amounts are the same between experiments and do not vary? You do not mention how you actually obtain this conditioned medium. Is there the possibility of contamination or transferred fibroblasts that would impact on the data analysis? Is LCCM also added during stimulation and inhibitor treatment?

We obtain LCCM by collecting the supernatant from L929 cell line that form confluent monolayer according to well-established protocols for LCCM collection. The supernatants are filtered through 0.22 micron filters to exclude contamination with L929 cells and bacteria. The medium is prepared in 500 ml batches that are sufficient for multiples experiments. Each batch of L929-conditioned medium is tested for biological activity using serial dilutions.

- How was the BCG infection performed? How much bacteria did you use? Which BCG strain was used?

We infected mice with M. bovis BCG Pasteur subcutaneously in the hock using 10⁶ CFU per mouse.

- At what density did you seed the BMDMs for stimulation and inhibitor experiments?

In 96 well plates, we seed 12,000 cells per well and allow the cells to grow for 4 days to reach confluency (approximately 50,000 cells per well). For a 6-well plate, we seed 2.5 × 10⁵ cells per well and culture them for 4 days to reach confluency. For a 24-well plate, we seed 50,000 cells per well and keep the cells in media for 4 days before starting any treatments. This ensures that the cells are in a proliferative or near-confluent state before beginning the stimulation or inhibitor treatments. Our detailed protocol is published in STAR Protocols (Yabaji et al., 2022; PMID 35310069).

- What machine did you use to perform the bulk RNA sequencing? How many replicates did you include for the sequencing?

For bulk sequencing we used 3 RNA samples for each condition. The samples were sequenced at Boston University Microarray & Sequencing Resource service using Illumina NextSeq^TM 2000 instrument.

- How many replicates were used for the scRNA sequencing? Why is your threshold for the exclusion of mitochondrial DNA so high? A typical threshold of less than 5% has been reported to work well with mouse tissue.

We used one sample per condition. For the mitochondrial cutoff, we usually base it off of the total distribution. There is no "universal" threshold that can be applied to all datasets. Thresholds must be determined empirically.

- You do not mention how many PCAs were considered for the scRNA sequencing analysis.

We considered 50 PCAs, this information was added to Methods

- You should name all the package versions you used for the scRNA sequencing (e.g. for the slingshot, VAM package)

The following package versions were used: Seurat v4.0.4, VAM v1.0.0, Slingshot v2.3.0, SingleCellTK v2.4.1, Celda v1.10.0, we added this information to Methods.

- You mention two batches for the human samples. Can you specify what the two batches are?

Human blood samples were collected at five sites, as described in the updated Methods section and two RNAseq batches were processed separately that required batch correction.

- At which temperature was the IF staining performed?

We performed the IF at 4oC. We included the details in revised version.

Reviewer #2 (Significance):

Overall, the manuscript has interesting findings with regard to macrophage responses in Mycobacteria tuberculosis infection.

However, in its current form there are several shortcomings, both with respect to the precision of the experiments and conclusions drawn.

Reviewer #3 (Evidence, reproducibility and clarity):

Summary

The authors use a mouse model designed to be more susceptible to M.tb (addition of sst1 locus) which has granulomatous lesions more similar to human granulomas, making this mouse highly relevant for M.tb pathogenesis studies. Using WT B6 macrophages or sst1B6 macrophages, the authors seek to understand the how the sst1 locus affects macrophage response to prolonged TNFa exposure, which can occur during a pro-inflammatory response in the lungs. Using single cell RNA-seq, revealed clusters of mutant macrophages with upregulated genes associated with oxidative stress responses and IFN-I signaling pathways when treated with TNF compared to WT macs. The authors go on to show that mutant macrophages have decreased NRF2, decreased antioxidant defense genes and less Sp110 and Sp140. Mutant macrophages are also more susceptible to lipid peroxidation and ironmediated oxidative stress. The IFN-I pathway hyperactivity is caused by the dysregulation of iron storage and antioxidant defense. These mutant macrophages are more susceptible to M.tb infection, showing they are less able to control bacterial growth even in the presence of T cells from BCG vaccinated mice. The transcription factor Myc is more highly expressed in mutant macs during TNF treatment and inhibition Myc led to better control of M.tb growth. Myc is also more abundant in PBMCs from M.tb infected humans with poor outcomes, suggesting that Myc should be further investigated as a target for host-directed therapies for tuberculosis.

Major Comments

Isotypes for IF imaging and confocal IF imaging are not listed, or not performed. It is a concern that the microscopy images throughout the manuscript do not have isotype controls for the primary antibodies.

Fig 4 (and later) the anti-IFNAR Ab is used along with the Isotype antibody, Fig 4I does not show the isotype. Use of the isotype antibody is also missing in later figures as well as Fig 3J. Why was this left off as the proper control for the Ab?

We addressed the comment in revised manuscript as described above in summary and responses to reviewers 1 and 2. Isotype controls for IFNAR1 blockade were included in Fig.3M (previously 3J), Fig. 4I, Suppl.Fig.4G (previously Fig.4I), and updated Fig.4C-E, Fig.6L-M, Suppl.Fig.4F-G, 7I.

Conclusions drawn by the authors from some of the WB data are worded strongly, yet by eye the blots don't look as dramatically different as suggested. It would be very helpful to quantify the density of bands when making conclusions. (for example, Fig 4A).

We added the densitometry of Western blot values after normalization above each lane in Fig.2A-C, Fig.3C-D and 3K; Fig.4A-B, Fig.5B,C,I,J.

Fig 5A is not described clearly. If the gene expression is normalized to untreated B6 macs, then the level of untreated B6 macs should be 1. In the graph the blue bars are slightly below 1, which would not suggest that levels "initially increased and subsequently downregulated" as stated in the text. It seems like the text describes the protein expression but not the RNA expression. Please check this section and more clearly describe the results.

We appreciate the reviewer’s comment and modified the text to specify the mRNA and protein expression data, as follows:

“We observed that Myc was regulated in an sst1-dependent manner: in TNF-stimulated B6 wild type BMDMs, c-Myc mRNA was downregulated, while in the susceptible macrophages c-Myc mRNA was upregulated (Fig.5A). The c-Myc protein levels were also higher in the B6.Sst1S cells in unstimulated BMDMs and 6 – 12 h of TNF stimulation (Fig.5B)”.

Also, why look at RNA through 24h but protein only through 12h? If c-myc transcripts continue to increase through 24h, it would be interesting to see if protein levels also increase at this later time point.

The time-course of Myc expression up to 24 h is presented in new panels Fig. 5I-5J It demonstrates the decrease of Myc protein levels at 24 h. In the wild type B6 BMDMs the levels of Myc protein significantly decreased in parallel with the mRNA suppression presented in Fig.5A. In contrast , we observed the dissociation of the mRNA and protein levels in the _sst1_mutant BMDMs at 12 and 24 h, most likely, because the mutant macrophages develop integrated stress response (as shown in our previous publication by Bhattacharya et al., JCI, 2021) that is known to inhibit Myc mRNA translation.

Fig 5J the bands look smaller after D-JNK1 treatment at 6 and 12h though in the text is says no change. Quantifying the bands here would be helpful to see if there really is no difference.

This experiment was repeated twice, and the average normalized densitometry values are presented in the updated Fig.5J. The main question addressed in this experiment was whether the hyperactivity of JNK in TNF-stimulated sst1 mutant macrophages contributed to Myc upregulation, as was previously shown in cancer. Comparing effects of JNK inhibition on phospho-cJun and c-Myc protein levels in TNF stimulated B6.Sst1S macrophages (updated Fig.5J), we concluded that JNK did not have a major role in c-Myc upregulation in this context.

Section 4, third paragraph, the conclusion that JNK activation in mutant macs drives pathways downstream of Myc are not supported here. Are there data or other literature from the lab that supports this claim?

This statement was based on evidence from available literature where JNK was shown to activate oncogens, including Myc. In addition, inhibition of Myc in our model upregulated ferritin (Fig.Fig.5C), reduced the labile iron pool, prevented the LPO accumulation (Fig.5D - G) and inhibited stress markers (Fig.5H). However, we do not have direct experimental evidence in our model that Myc inhibition reduces ASK1 and JNK activities. Hence, we removed this statement from the text and plan to investigate this in the future.

Fig 6N Please provide further rationale for the BCG in vivo experiment. It is unclear what the hypothesis was for this experiment.

In the current version BCG vaccination data is presented in Suppl.Fig.14B. We demonstrate that stressed BMDMs do not respond to activation by BCG-specific T cells (Fig.6J) and their unresponsiveness is mediated by type I interferon (Fig.6L and 6M). The observed accumulation of the stressed macrophages in pulmonary TB lesions of the sst1-susceptible mice (Fig.7E, Suppl.Fig.13 and 14A) and the upregulation of type I interferon pathway (Fig.1E,1G, 7C), Suppl.Fig.1C and 11) suggested that the effect of further boosting T lymphocytes using BCG in Mtb-infected mice will be neutralized due to the macrophage unresponsiveness. This experiment provides a novel insight explaining why BCG vaccine may not be efficient against pulmonary TB in susceptible hosts.

The in vitro work is all concerning treatment with TNFa and how this exposure modifies the responses in B6 vs sst1B6 macrophages; however, this is not explored in the in vivo studies. Are there differences in TNFa levels in the pauci- vs multi-bacillary lesions that lead to (or correlate with) the accumulation of peroxidation products in the intralesional macrophages. How to the experiments with TNFa in vitro relate back to how the macrophages are responding in vivo during infection?

Our investigation of mechanisms of necrosis of TB granulomas stems from and supported by in vivo studies as summarized below.

This work started with the characterization necrotic TB granulomas in C3HeB/FeJ mice in vivo followed by a classical forward genetic analysis of susceptibility to virulent Mtb in vivo.

That led to the discovery of the sst1 locus and demonstration that it plays a dominant role in the formation of necrotic TB granulomas in mouse lungs in vivo. Using genetic and immunological approaches we demonstrated that the sst1 susceptibility allele controls macrophage function in vivo (Yan, et al., J.Immunol. 2007) and an aberrant macrophage activation by TNF and increased production of Ifn-b in vitro (He et al. Plos Pathogens, 2013). In collaboration with the Vance lab we demonstrated that the type I IFN receptor inactivation reduced the susceptibility to intracellular bacteria of the sst1-susceptible mice in vivo (Ji et al., Nature Microbiology, 2019). Next, we demonstrated that the Ifnb1 mRNA superinduction results from combined effects of TNF and JNK leading to integrated stress response in vitro (Bhattacharya, JCI, 2021). Thus, our previous work started with extensive characterization of the in vivo phenotype that led to the identification of the underlying macrophage deficiency that allowed for the detailed characterization of the macrophage phenotype in vitro presented in this manuscript. In a separate study, the Sher lab confirmed our conclusions and their in vivo relevance using Bach1 knockout in the sst1-susceptible B6.Sst1S background, where boosting antioxidant defense by Bach1 inactivation resulted in decreased type I interferon pathway activity and reduced granuloma necrosis. We have chosen TNF stimulation for our in vitro studies because this cytokine is most relevant for the formation and maintenance of the integrity of TB granulomas in vivo as shown in mice, non-human primates and humans. Here we demonstrate that although TNF is necessary for host resistance to virulent Mtb, its activity is insufficient for full protection of the susceptible hosts, because of altered macrophages responsiveness to TNF. Thus, our exploration of the necrosis of TB granulomas encompass both in vitro and extensive in vivo studies.

Minor comments

Introduction, while well written, is longer than necessary. Consider shortening this section. Throughout figures, many graphs show a fold induction/accumulation/etc, but it is rarely specified what the internal control is for each graph. This needs to be added.

Paragraph one, authors use the phrase "the entire IFN pathway was dramatically upregulated..." seems to be an exaggeration. How do you know the "entire" IFN pathway was upregulated in a dramatic fashion?

(1) We shortened the introduction and discussion; (2) verified that figure legends internal controls that were used to calculate fold induction; (3) removed the word “entire” to avoid overinterpretation.

Figures 1E, G and H and supp fig 1C, the heat maps are missing an expression key Section 2 second paragraph refers to figs 2D, E as cytoplasmic in the text, but figure legend and y-axis of 2E show total protein.

The expression keys were added to Fig.1E,G,H, Fig.7C, Suppl.Fig.1C and 1D and Suppl.Fig.11A of the revised manuscript.

Section 3 end of paragraph 1 refers to Fig 3h. Does this also refer to Supp Fig 3E?

Yes, Fig.3H shows microscopy of 4-HNE and Suppl.Fig.3H shows quantification of the image analysis. In the revised manuscript these data are presented in Fig.3H and Suppl.Fig.3F. The text was modified to reflect this change.

Supplemental Fig 3 legend for C-E seems to incorrectly also reference F and G.

We corrected this error in the figure legend. New panels were added to Suppl.Fig.3 and previous Suppl.Fig.3F and G were moved to Suppl.Fig.4 panels C and D of the revise version.

Fig 3K, the p-cJun was inhibited with the JNK inhibitor, however it’s unclear why this was done or the conclusion drawn from this experiment. Use of the JNK inhibitor is not discussed in the text.

The JNK inhibitor was used to confirm that c-Jun phosphorylation in our studies is mediated by JNK and to compare effects of JNK inhibition on phospho-cJun and Myc expression. This experiment demonstrated that the JNK inhibitor effectively inhibited c-Jun phosphorylation but not Myc upregulation, as shown in Fig.5I-J of the revised manuscript.

Fig 4 I and Supp Fig 3 H seem to have been swapped? The graph in Fig 4I matches the images in Supp Fig 3I. Please check.

We reorganized the panels to provide microscopy images and corresponding quantification together in the revised the panels Fig. 4H and Fig. 4I, as well as in Suppl. Fig. 4F and Suppl. Fig. 4G.

Fig 6, it is unclear what % cell number means. Also for bacterial growth, the data are fold change compared to what internal control?

We updated Fig.6 legend to indicate that the cell number percentages were calculated based on the number of cells at Day 0 (immediately after Mtb infection). We routinely use fixable cell death staining to enumerate cell death. Brief protocol containing this information is included in Methods section. The detailed protocol including normalization using BCG spike has been published – Yabaji et al, STAR Protocols, 2022. Here we did not present dead cell percentage as it remained low and we did not observe damage to macrophage monolayers. This allows us to exclude artifacts due to cell loss. The fold change of Mtb was calculated after normalization using Mtb load at Day 0 after infection and washes.

Fig 7B needs an expression key

The expression keys was added to Fig.7C (previously Fig. 7B).

Supp Fig 7 and Supp Fig 8A, what do the arrows indicate?

In Suppl.Fig.8 (previously Suppl.Fig.7) the arrows indicate acid fast bacilli (Mtb). In figures Fig.7A and Suppl.Fig.9A arrows indicate Mtb expressing fluorescent reporter mCherry. Corresponding figure legends were updated in the revised version.

Supp Fig 9A, two ROI appear to be outlined in white, not just 1 as the legend says Methods:

We updated the figure legend.

Certain items are listed in the Reagents section that are not used in the manuscript, such as necrostatin-1 or Z-VAD-FMK. Please carefully check the methods to ensure extra items or missing items does not occur.

These experiments were performed, but not included in the final manuscript. Hence, we removed the “necrostatin-1 or Z-VAD-FMK” from the reagents section in methods of revised version.

Western blot, method of visualizing/imaging bands is not provided, method of quantifying density is not provided, though this was done for fig 5C and should be performed for the other WBs.

We used GE ImageQuant LAS4000 Multi-Mode Imager to acquire the Western blot images and the densitometric analyses were performed by area quantification using ImageJ. We included this information in the method section. We added the densitometry of Western blot values after normalization above each lane in Fig.2A-C, Fig.3C-D and 3K; Fig.4A-B, Fig.5B,C,I,J.

Reviewer #3 (Significance):

The work of Yabaji et al is of high significance to the field of macrophage biology and M.tb pathogenesis in macrophages. This work builds from previously published work (Bhattacharya 2021) in which the authors first identified the aberrant response induced by TNF in sst1 mutant macrophages. Better understanding how macrophages with the sst1 locus respond not only to bacterial infection but stimulation with relevant ligands such as TNF will aid the field in identifying biomarkers for TB, biomarkers that can suggest a poor outcome vs. "cure" in response to antibiotic treatment or design of host-directed therapies.

This work will be of interest to those who study macrophage biology and who study M.tb pathogenesis and tuberculosis in particular. This study expands the knowledge already gained on the sst1 locus to further determine how early macrophage responses are shaped that can ultimately determine disease progression.

Strengths of the study include the methodologies, employing both bulk and single cell-RNA seq to answer specific questions. Data are analyze using automated methods (such as HALO) to eliminated bias. The experiments are well planned and designed to determine the mechanisms behind the increased iron-related oxidative stress found in the mutant macrophages following TNF treatment. Also, in vivo studies were performed to validate some of the in vitro work. Examining pauci-bacillary lesions vs multi-bacillary lesions and spatial transcriptomics is a significant strength of this work. The inclusion of human data is another strength of the study, showing increased Myc in humans with poor response to antibiotics for TB.

Limitations include the fact that the work is all done with BMDMs. Use of alveolar macrophages from the mice would be a more relevant cell type for M.tb studies. AMs are less inflammatory, therefore treatment with TNF of AMs could result in different results compared to BMDMs. Reviewer's field of expertise: macrophage activation, M.tb pathogenesis in human and mouse models, cell signaling.

Limitations: not qualified to evaluate single cell or bulk RNA-seq technical analysis/methodology or spatial transcriptomics analysis.

DEVUELVE EL MAXIMO ENTRE a y b, EL NEUTRO NO ES DEVULETO NUNCA

Question three

Author response:

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

Reviewer #1 (Public review): 

Filamentous fungi are established workhorses in biotechnology, with Aspergillus oryzae as a prominent example with a thousand-year history. Still, the cell biology and biochemical properties of the production strains is not well understood. The paper of the Takeshita group describes the change in nuclear numbers and correlates it to different production capacities. They used microfluidic devices to really correlate the production with nuclear numbers. In addition, they used microdissection to understand expression profile changes and found an increase in ribosomes. The analysis of two genes involved in cell volume control in S. pombe did not reveal conclusive answers to explain the phenomenon. It appears that it is a multi-trait phenotype. Finally, they identified SNPs in many industrial strains and tried to correlate them to the capability of increasing their nuclear numbers. 

The methods used in the paper range from high-quality cell biology, Raman spectroscopy, to atomic force and electron microscopy, and from laser microdissection to the use of microfluidic devices to

study individual hyphae. 

This is a very interesting, biotechnologically relevant paper with the application of excellent cell biology. I have only minor suggestions for improvement. 

We sincerely appreciate your fair and positive evaluation of our work. Thank you for your suggestions for improvement. We respond to each of them appropriately.

Reviewer #2 (Public review): 

Summary: 

In the study presented by Itani and colleagues, it is shown that some strains of Aspergillus oryzae - especially those used industrially for the production of sake and soy sauce - develop hyphae with a significantly increased number of nuclei and cell volume over time. These thick hyphae are formed by branching from normal hyphae and grow faster and therefore dominate the colonies. The number of nuclei positively correlates with the thicker hyphae and also the amount of secreted enzymes. The addition of nutrients such as yeast extract or certain amino acids enhanced this effect. Genome and transcriptome analyses identified genes, including rseA, that are associated with the increased number of nuclei and enzyme production. The authors conclude from their data involvement of glycosyltransferases, calcium channels, and the tor regulatory cascade in the regulation of cell volume and number of nuclei. Thicker hyphae and an increased number of nuclei were also observed in high-production strains of other industrially used fungi such as Trichoderma reesei and Penicillium chrysogenum, leading to the hypothesis that the mentioned phenotypes are characteristic of production strains, which is of significant interest for fungal biotechnology. 

Strengths: 

The study is very comprehensive and involves the application of diverse state-of-the-art cell biological, biochemical, and genetic methods. Overall, the data are properly controlled and analyzed, figures and

movies are of excellent quality. 

The results are particularly interesting with regard to the elucidation of molecular mechanisms that regulate the size of fungal hyphae and their number of nuclei. For this, the authors have discovered a very good model: (regular) strains with a low number of nuclei and strains with a high number of nuclei. Also, the results can be expected to be of interest for the further optimization of industrially relevant filamentous

fungi. 

Weaknesses: 

There are only a few open questions concerning the activity of the many nuclei in production strains (active versus inactive), their number of chromosomes (haploid/diploid), and whether hyper-branching always leads to propagation of nuclei. 

We are very grateful for your recognition of our findings, the proposed model, and their significance for future applications. We are grateful for the questions, which contribute to a more accurate understanding. 

Our responses to each are provided below.  

Reviewer #3 (Public review): 

Summary: 

The authors seek to determine the underlying traits that support the exceptional capacity of Aspergillus oryzae to secrete enzymes and heterologous proteins. To do so, they leverage the availability of multiple domesticated isolates of A. oryzae along with other Aspergillus species to perform comparative imaging and genomic analysis. 

Strengths: 

The strength of this study lies in the use of multifaceted approaches to identify significant differences in hyphal morphology that correlate with enzyme secretion, which is then followed by the use of genomics to identify candidate functions that underlie these differences. 

Weaknesses: 

There are aspects of the methods that would benefit from the inclusion of more detail on how experiments were performed and data interpreted. 

Overall, the authors have achieved their aims in that they are able to clearly document the presence of two distinct hyphal forms in A. oryzae and other Aspergillus species, and to correlate the presence of the thicker, rapidly growing form with enhanced enzyme secretion. The image analysis is convincing. The discovery that the addition of yeast extract and specific amino acids can stimulate the formation of the novel hyphal form is also notable. Although the conclusions are generally supported by the results, this is perhaps less so for the genetic analysis as it remains unclear how direct the role of RseA and the calcium transporters might be in supporting the formation of the thicker hyphae. 

The results presented here will impact the field. The complexity of hyphal morphology and how it affects secretion is not well understood despite the importance of these processes for the fungal lifestyle. In addition, the description of approaches that can be used to facilitate the study of these different hyphal forms (i.e., stimulation using yeast extract or specific amino acids) will benefit future efforts to understand the molecular basis of their formation. 

We are very grateful for your fair and thoughtful evaluation of our work. We agree that the genetic analysis in the latter part is relatively weaker compared to the imaging analysis in the first half. Rather than a single mutation causing a dramatic phenotypic change, we believe that the accumulation of various mutations through breeding leads to the observed phenotype, making it difficult to clearly demonstrate causality. Since transcriptome and SNP analyses have revealed key pathways and phenotypes, it would be gratifying if these insights could contribute to future applications utilizing filamentous fungi.

Reviewer #1 (Recommendations for the authors): 

I was wondering what happens if thick hyphae were taken as inoculum for a new colony or thin hyphae. Is it possible to enrich for one or the other type of hyphae? Perhaps in the presence of yeast extract or certain amino acids. 

Added an explanation in the discussion.

L304-306. When thick hyphae were cultured on fresh medium, thin hyphae initially emerged, suggesting that sustained metabolic activity is required for the formation of thick hyphae with a high number of nuclei.    

L120-121. In some cases, thick hyphae emerged by branching from thick hyphae (Fig. 2D, left), while in other cases, thin hyphae emerged from thick hyphae (Fig. 2D, right). Thin hyphae emerge in the early stage of cultivation even in the presence of yeast extract or certain amino acids.

In the Discussion, they hypothesize that the primary effect could be on cell wall rigidity. I am wondering if that hypothesis could be tested by adding, for instance, sublethal concentrations of cytochalasin to hyphae of A. nidulans to weaken the cell wall. 

The question is reasonable. To ensure accurate understanding, we moved Fig. S6 to Fig. 6 and revised the discussion as follows. 

L294-295. In our model, cell wall loosening at a branching site and regulation of cell volume by turgor pressure constitute necessary conditions for increasing cell volume and maintaining thick hyphae. L306-309. Weakening the cell wall by treatment with a low concentration of calcofluor white did not lead to hyphal thickening or an increase in nuclear number. On the contrary, thick hyphae have thicker cell walls (Fig. 2H-K), which are necessary to maintain the increased cell volume.

I recommend including some older literature. It was described already 20 years ago that A. nigerdifferentiates hyphae with different capacities to secrete proteins (PMID: 16238620). In addition, there are old reports in A. nidulans reporting high numbers of nuclei (https://doi.org/10.1099/00221287-60-1-133). Perhaps it is worth trying to reproduce those cultural conditions. At least this should be discussed. In the same line, the number of nuclei increases a lot in the stalk of conidiophores in A. nidulans. These observations could be used as examples that the phenomenon observed in A. oryzae may be of general importance. 

Thank you for the suggestion. It is a very interesting proposal. We checked the nuclei distribution of A. nidulans on the media and added the following discussion.

L328-334. A previous study reported an increase in the number of nuclei in A. nidulans (62, 63). Here, we examined the nuclear distribution of A. nidulans grown on the culture media, however, did not find class III hyphae as observed in A. oryzae. Even in A. nidulans, conidiophore stalks contain a high number of nuclei. It has been shown that A. oryzae has a taller conidiophore stalk (64). In the thick hyphae of A. oryzae, the expression level of flbA, an early regulator of conidiophore development (65), was elevated. This suggests that differentiation to aerial hyphae may be involved in the increase of hyphal volume and nuclear number. 

(62) Clutterbuck A.J. Synchronous Nuclear Division and Septation in Aspergillus nidulans. J Gen Microbiol 60, 133-135 (1970).

(63) Vinck, A., Terlou, M., Pestman, W.R., Martens, E.P., Ram, A.F., van den Hondel, C.A., Wösten, H.A. Hyphal differentiation in the exploring mycelium of Aspergillus niger. Mol Microbiol 58, 693-9 (2005).

(64) Wada R, Maruyama J, Yamaguchi H, Yamamoto N, Wagu Y, Paoletti M, Archer DB, Dyer PS, Kitamoto K. Presence and functionality of mating type genes in the supposedly asexual filamentous fungus Aspergillus oryzae. Appl Environ Microbiol 78, 2819-29 (2012).

(65) Lee, B.N., Adams, T.H. Overexpression of flbA, an early regulator of Aspergillus asexual sporulation, leads to activation of brlA and premature initiation of development. Mol Microbiol 14, 323-34 (1994).

Reviewer #2 (Recommendations for the authors): 

I suggest addressing the following questions to strengthen the manuscript: 

(1) Do the authors have an explanation for their result that with an increase in the number of nuclei the individual nucleus is smaller? Have the authors checked whether all the nuclei are haploid or diploid?

Thank you for the very important question. We added new results to Fig. S5D and S5E and the following discussion.

L335-340. We investigated whether the reduction in nuclear size observed in thick hyphae was due to a change from diploid to haploid status. However, no difference in GFP-histone fluorescence intensity was detected between thick and thin hyphae (Fig. S5D). In both RIB40 and RIB915 strains, no significant difference in conidial spore size was observed despite the large difference in the number of nuclei within the hyphae (Fig. S5E). These results suggest that both thick and thin hyphae remain haploid, and that the smaller nuclear size observed in thick hyphae is likely due to a higher nuclear density.

(2) In this context, the biological relevance of the increase in the number of nuclei should also be discussed in more detail. It remains to be clarified whether in hyphae with a high number of nuclei all nuclei are functionally active or whether many nuclei are possibly "inactive". Studies on the transcriptional activity of individual nuclei or on DNA replication (e.g., by EdU labeling) could clarify this. 

Added the explanation below.

L102-105. The transcriptional activity of each nucleus is unknown. However, a previous study (Yasui et al., FBB 2020) demonstrated that nuclear division is synchronized even when there are more than 200 nuclei. This suggests that DNA replication occurs similarly in most nuclei. Furthermore, since the germination rate of conidia and the colonies formed from individual conidia show no significant abnormalities, it is suggested that nearly all nuclei possess normal genomes and chromosomes.

(3) It becomes not entirely clear what the underlying signal is that causes a thin hypha to branch into a thick multinucleated cell. This needs to be discussed in more detail. 

Thanks for the suggestion. We clarified the signal to increase nuclear number and cell volume.

L294-309. Although it is speculative, we propose a model to aid interpretation in the discussion. We have clarified that both genetic potential and environmental signals such as nutrients are important.

(4) Is increased branching always correlated with an increased number of nuclei? 

It is not an increase in branching, but rather the thickening of hyphae and an increase in cell volume that is consistently associated with an increase in nuclear number. Approximately 40 hours after inoculation, within 400 μm from the tip, the number of branches was 3.4 (SD=2.4) in thin hyphae and 2.6 (SD=0.5) in thick hyphae, suggesting that branching does not increase (n=4). Since thick hyphae elongate faster, it seems that fewer branches are present near the tip, even if the branching frequency itself remains unchanged.

(5) The abstract does not summarize the many findings of the manuscript in an adequate way. 

abstract change

Minor: 

(1) Lines 49-50: Why italics? 

corrected.

(2) Line 179: process. 

corrected.

(3) Lines 313-314: Do not forget (and discuss) in this context mycorrhiza fungi with up to thousands of nuclei that were apparently selected during evolution for this high number of nuclei. 

Thank you for the very interesting suggestion. We have added the following discussion.

L339-351. The regulation of nuclear number and its ecological strategy are intriguing in other fungi such as N. crassa, which rapidly spreads after wildfires (68), and arbuscular mycorrhiza fungi that form symbiotic relationships with plants and contain thousands of nuclei within hyphae lacking septa (69).

(68) Jacobson, D. J. et al. Neurospora in temperate forests of western North America. Mycologia 96, 66–74 (2004).

(69) Kokkoris V, Stefani F, Dalpé Y, Dettman J, Corradi N. Nuclear Dynamics in the Arbuscular Mycorrhizal Fungi. Trends Plant Sci. 25, 765-778 (2020).

(4) Lines 356-358: many typos.

corrected.

Reviewer #3 (Recommendations for the authors): 

Specific suggestions or clarifications for the authors include: 

(1) Lines 49-50: Is this sentence italicized for a reason? 

It was a mistake, so we have corrected it.

(2) Line 83: More detail on the specific characteristics of the different classes of hyphae would be helpful. Perhaps include a schematic drawing that emphasizes the differences between class I,II, and III hyphae. 

L398-400. The classification is described in the Methods section: Class I – nuclei are distributed at regular intervals without overlapping; Class II – nuclei are aligned but occasionally overlap; Class III – nuclei are scattered throughout the hyphae without alignment. Representative images are shown in a previous study (Yasui et al., FBB 2020). 

L82-84. We have added this information to clarify the classification.

(3) Lines 102-103: It was not very clear how this experiment was done. Are you counting nuclei within 100 um of the tip? Are these all in one hyphal compartment? These details could be provided in a drawing that would make it easier for the reader to understand how this was done. 

L109. Due to variation in the distance from the hyphal tip to the septum, we counted the number of nuclei within 100 μm from the hyphal tip. When septa were present, nuclei were counted in the same manner, so multiple compartments may be included. Changed the explanation.

(4) Lines 134-140: Is there a way to calibrate levels of secreted protein or amylase activity per nucleus? That is, if the ratio of cytoplasmic volume per nucleus is constant, does the same apply to the secreted product? Knowing this would help to clarify whether the key feature in enhanced secretion is nuclear (e.g., gene expression) versus a cytoplasmic trait (e.g., vesicle trafficking). 

Enzyme activity was measured across the entire mycelium, which includes a mixture of hyphae with high and low numbers of nuclei. Therefore, it is difficult to assess the correlation between enzyme activity and nuclear number. Enzyme activity was normalized by fungal biomass. The size of each colony is shown in Fig. 1B. Additionally, the correlation between the proportion of hyphae with increased nuclear number and enzyme activity is shown in Fig. 3H. In the experiment where enzyme activity was measured in a single hypha, we attempted to measure the number of nuclei; however, we could not use the nuclear GFP strain because the substrate exhibits green fluorescence. DAPI staining also failed due to limited dye access to the microfluidic channel. Changed the section title, ‘Increase in nuclear number and enzyme secretion’ from ‘Correlation between nuclear number and enzyme secretion’.

(5) Line 151 and Figure 3F: YE also triggered a ~5-fold enhancement of secretion in A. nidulans without a concomitant increase in hyphal width. This merits some comment in the text.  

Added an explanation, L156-157.

In A. nidulans, the addition of yeast extract did not cause a dramatic increase in nuclear number, but hyphal width increased by 1.4-times and protein secretion increased by 5.1-times.

(6) Line 252: Were nimE levels detected or altered in thick hyphae? The levels of this cycling might play a more important role in a shortened cell cycle than the authors have considered, especially as NimE functions during both G1 and G2. 

Added an explanation below, L260-262.

The expression level of nimE (AO090003000993) was low in both thick and thin hyphae, with no significant difference observed. As known in other organisms, its function is likely regulated through phosphorylation and the protein degradation.

(7) Line 254: Please provide a citation for the statement that branches emerge as a result of cell wall loosening. 

rephrased and added citation, L263.

Branching is thought to occur through the degradation and reconstruction of the cell wall at the branching site (54).

Harris SD. Branching of fungal hyphae: regulation, mechanisms and comparison with other branching systems. Mycologia 100, 823-32 (2008).   

(8) Lines 275-277: It would be interesting to know whether the addition of rapamycin also suppressed the ability of amino acids to trigger greater numbers of class III hyphae. 

We added new results at Fig. S2G.

L168. Rapamycin decreased the ratio of hyphae with increased nuclei even in the medium with yeast extract (Fig. S2G).

(9) Lines 282-289: My sense is that this model is too speculative at this time. The role of RseA seems very broad based on the strong deletion phenotype. How would the removal of RseA be regulated to limit its effect to the branch site? Also, the msyA deletion phenotype isn't entirely consistent with what you would expect if it were necessary to maintain thick hyphae. Lastly, the authors do not show that translational capacity is enhanced in thick hyphae. I would suggest that these statements be tempered to some degree. 

Thank you for your comment. We agree that it was too speculative, whereas we believe that some explanatory interpretation is necessary. Therefore, we have revised the text as follows, L294-300. In our model, cell wall loosening during branching and regulation of cell volume by turgor pressure constitute necessary conditions for increasing cell volume and maintaining thick hyphae. RseA and MsyA may be involved in these processes. At the same time, enhanced translational capacity by increased expression of ribosomal genes, possibly due to associated with TOR activation by specific amino acids, and mechanisms that accelerate the cell cycle represent another essential condition that enables an increase in nuclear number.

(10) General: how do the authors reconcile the observation that YE and amino acids stimulate the formation of thicker hyphae, yet the time lapse imaging (Figure 2E) suggests that these hyphae arise at a later time during colony development when these resources might be limiting? The authors should consider providing some insight into this in the Discussion. 

L300-305. Added a discussion below.

Both genetic potential and nutritional environmental signals are likely required for the formation of thick hyphae with a high number of nuclei. When thick hyphae were cultured on fresh medium, thin hyphae initially emerged, suggesting the necessity of sustained high metabolic activity.

DOI: 10.1016/j.isci.2025.113460

Resource: RRID:IMSR_JAX:000664

Curator: @scibot

SciCrunch record: RRID:IMSR_JAX:000664

What is this?

Author response:

The following is the authors’ response to the original reviews

We would like to express our sincere gratitude to the reviewers for their thorough analysis of the manuscript and their extremely helpful comments. We have taken all the suggestions into consideration and conducted a range of additional experiments to address the points raised. We have also extensively revised the manuscript to clarify descriptions, correct inaccuracies and remove inconsistencies. We have modified the figures for clarity and content.

Overall, we expanded the description of the EBH structure to emphasise its dimeric nature and the impact of the two binding sites on interpreting the binding data, including cooperativity. Using ITC, we tested the effect of the pre-SxIP residues on the binding affinity with additional peptides. We found that these residues had a significant effect, albeit much smaller than that of the post-SxIP residues. We analysed the binding of the 11MACF-VLL mutant with EBH-ΔC and evaluated the exchange rates. In agreement with our model, we found that the EBH affinity for the SxIP peptide from CK5P2 (KKSRLPRILIKRSR), which has a C-terminal sequence similar to that of the 11MACF-VLLRK mutant, is 21nM, which is similar to the affinity of the mutant itself. This demonstrates the significant variation in affinity observed among natural SxIP ligands, as predicted by our study. Our responses to the specific points raised by the reviewers are provided below.

Reviewer #1 (Public Review):

There is no direct experimental evidence for independent dock and lock steps. The model is certainly plausible given their structural data, but all titration and CEST measurements are fully consistent with a simple one-step binding mechanism. Indeed, it is acknowledged that the results for the VLL peptide are not consistent with the predictions of this model, as affinity and dissociation rates do not co-vary. The model may still be a helpful way to interpret and discuss their results, and may indeed be the correct mechanism, but this has not yet been proven.

Unfortunately, it is not possible to obtain direct experimental evidence because the folding of the C-terminus is too fast to influence the NMR parameters. However, as the reviewer pointed out, our structural data support the two-step model, since folding of the C-terminus is only possible once the ligand containing the post-SxIP residues has bound. By adopting a mechanistically supported model, we can analyse the contributions to binding and relate them to the structural characteristics of the complex. This provides a clearer insight into the roles of the various regions in the interaction and allows to modify them rationally to enhance the ligand affinity.

In the revised version, we restate the equations in terms of comparing the on-rates. This provides a clearer view of the effect of the additional stage, which cannot increase the overall on-rate since the two stages are sequential. If the forward rate of the second stage is comparable to or slower than the off-rate of the first stage, the overall on-rate decreases. Conversely, if the forward rate is much faster, the overall on-rate remains unchanged. For the wild-type 11MACF peptide, we observed that the presence of the EBH C-terminus does not affect the on-rate of binding, which is in perfect agreement with the two-step model and indicates that the C-terminus folds very quickly.

Additionally, we evaluated the binding of the 11MACF-VLL mutant to EBH-ΔC and observed a twofold decrease in Kd compared to WT 11MAC, primarily due to an increase in the on-rate. Interestingly, this rate is approximately twice as low as the overall on-rate for EBH/11MACF-VLL binding, contradicting the sequential two-step model. This suggests a more complex binding process where binding is accelerated by additional hydrophobic interactions with the unfolded C-terminus. However, given the difficulty of quantifying very slow exchange rates, it is more likely that the discrepancy is due to the accuracy of the rate measurements. Therefore, the model allows the rational analysis of changes in binding parameters due to mutations.

There is little discussion of the fact that binding occurs to EBH dimers -  either in terms of the functional significance of this or in the  acquisition and analysis of their data. There is no discussion of  cooperation in binding (or its absence), either in the analysis of NMR  titrations or in ITC measurements. Complete ITC fit results have not  been reported so it is not possible to evaluate this for oneself.

We added information about the dimer to the introduction, emphasising its role in enhancing interaction with microtubules (MTs) and its structural role in SxIP binding. The ITC data do not exhibit any biphasic behaviour and can be fitted to a single-site model with 1:1 stoichiometry relative to the EB1c monomer. This corresponds to two independent binding sites in the dimer. We have added the stoichiometry to Table 1 and the description. The NMR titration data for the 11MACF and 11MACF-VLL interactions were fitted to the TITAN dimer model, which includes cooperativity parameters. For WT 11MACF, both cooperativity parameters were zero, corresponding to independent binding sites in the ITC model. For 11MACF-VLL, the fitting suggests weak negative cooperativity, with a ~3-fold increase in Kd for binding to the second site and no change in the off-rate. This difference in Kd is likely to be too small to induce a biphasic shape to the ITC curve. As the cooperativity effect on the NMR spectra is small and absent in the ITC, we used the independent sites model for data analysis, as there is insufficient justification for introducing extra parameters into the model. Crucially, fitting to this model did not alter the off-rate value obtained by NMR or affect the conclusions. We added a description of cooperativity to the results and discussion.

Three peptides are used to examine the role of C-terminal residues in SxIP motifs: 4-MACF (SKIP), 6-MACF (SKIPTP), and 11-MACF (KPSKIPTPQRK). The 11-mer demonstrates the strongest binding, but this has added residues to the N-terminal as well. It has also introduced charges at both termini, further complicating the interpretation of changes in binding affinities. Given this, I do not believe the authors can reasonably attribute increased affinities solely to post-SxIP residues.

We tested the 9MACF peptide SKIPTPQRK, which has the same N-terminus as the 4- and 6-MACF peptides, and found that its binding affinity is ~10-fold weaker than that of 11MACF. This demonstrates the contribution of both the pre- and post-SxIP residues. This is likely due to electrostatic interactions between the positively charged N-terminus and the negatively charged EBH surface, similar to those involving the positive charges at the peptide C-terminus. Although significant, the contribution of the N-terminal peptide region is approximately one order of magnitude lower than that of the post-SxIP residues, meaning the post-SxIP region is the main affinity modulator. We have added the binding data on 9MACF and a discussion of the contributions to the manuscript.

Experimental uncertainties are, with exceptions, not reported.

Uncertainties added to the number in Table 1 and the text. Information on how uncertainties were calculated added to Table 1.

Reviewer #1 (Recommendations For The Authors):

(1) Have you tested the binding of the WT dimer in your cell model?

We haven’t tested the WT dimer because it has already been reported in the 2009 Cell paper by Honappa et al. In the cell experiments, our main focus was on recruiting the high-affinity mutant to MTs. The low level of recruitment, despite the mutant's high affinity, highlights the importance of dimerisation or additional contributions to binding.

(2) Please deposit all NMR dynamics measurements (relaxation rates and derived model-free parameters) alongside structural data in the BMRB.

The relaxation data have been submitted to BMRB, IDs 53187 and 53188

(3) Please report complete fitting results, e.g. for ITC, including stoichiometries. Clarify what this means for binding to a dimer, and if there is any evidence of cooperativity. Figure 3C, right hand panel, shows an unusual stoichiometry, can the authors comment on this?

We have added more information on stoichiometry and cooperativity; please refer to our response to the above comment for details. We repeated the titration for the VLLRK mutant using fresh peptide stock. As expected, the stoichiometry was close to 1:1 relative to the EB1c monomer. The new data are now included in the table and figure.

(4) Please report uncertainties for all measurements of Kd, koff, kon, ∆G, ∆H, ∆S, and explain whether these are determined from statistical analysis, technical or biological repeats (and where reported, clarify between standard deviation/standard error). Please also be aware of standard guidelines for reporting significant figures for data with uncertainties, as these have not been followed in Table 1.

Uncertainties added to the number in Table 1 and the text. Information on how uncertainties were calculated added to Table 1.

(5) The construct design for the cell model is unclear - given the importance of flanking residues, please report and discuss how the sequences are attached to venus: which termini is attached, and what is the linker composition?

We cloned the peptides at the C-terminus of mTFP, after the GS linker of the vector. The peptide itself contains a GS sequence at the N-terminus, creating a highly flexible GSGS linker that separates the SxIP region from mTFP and minimises the potential effect of mTFP on binding. We followed the design of Honappa et al. to enable direct comparison with the published results. We have added this information to the 'Methods' section..

(6) Which HSQC pulse sequence was used for 2D lineshape analysis? The authors mention non-linear chemical shift changes, presumably associated with the dimer interface - this would be useful to expand upon and clarify.

For the lineshape analysis, we used the standard Bruker sequence hsqcfpf3gpphwg with soft-pulse watergate water suppression and flip-back. This sequence is included in the TITAN model. We added the description of the non-linear chemical shift changes and connection of these changes to the allosteric effect of the binding to the supplementary information describing details of the lineshape analysis.

(7) Figure 1A could usefully highlight the dimer interface in the surface representation also.

We believe that including the interface would make the figure too complicated. The dimer configuration is shown in different colours for the two subunits, clearly demonstrating their involvement in forming the binding site.

(8) Figures 1C and 1D could usefully show a secondary structure schematic to assist the reader. The x-axis in these figures is not linear and this should be corrected. The calculation of combined chemical shift perturbations should be described.

Thank you for the helpful suggestion. We changed the scale of the figures and added the diagram of the secondary structure.

(9) Units are missing from many figure axes.

We added missing units to the axes. Thank you for highlighting this.

(10) What peptide concentrations are used in Figure 1C? Presumably, these should be reported at saturation for this to be a fair comparison, this should be clarified.

The protein concentration was 50 µM. Peptides 4MACF and 6MACF were added at a 100-fold molar excess and peptide 11MACF was added at a 4-fold excess. Saturation was achieved for 11MACF. This was impossible for the short peptides due to their mM affinity. This information has been added to the figure legend. The figure's main aim is to illustrate the differences in the chemical shift perturbation profiles, which can be achieved even if full saturation is not attained. Although the absolute value of the chemical shifts is proportional to the degree of saturation, the distribution of the largest chemical shift changes is independent of this degree. Therefore, we can draw conclusions about the distribution of changes by comparing under non-saturation conditions.

(11) The presentation of raw peak intensities in Figure 1D shows primarily the flexibility of the C-terminal region associated with high intensities. Beyond this, when comparing the binding of peptides it would be much more informative to show relative peak intensities. Residues around 210-225 appear to show strong broadening in the presence of peptide, but this is masked by the low initial intensity. Can the authors clarify and discuss this? Also, what peptide concentrations were used for this comparison? For a fair comparison, it should be close to saturation - particularly to exclude exchange broadening contributions.

The protein concentration was 50 µM. 6MACF and 6MACF peptides were added at a 100-fold excess and 11MACF at a 4-fold excess. Saturation was achieved for 11MACF. This was impossible to achieve for the short peptide due to its mM affinity. This information has been added to the figure legend. Upon checking the data, we found a small systematic offset in the coiled-coil region of some of the complexes, as the integral intensity had been used in the initial plot. While this does not change the conclusion regarding the high dynamics of the C-terminus, it does create an inaccurate perception of the relative intensities of the folded regions in the different complexes, as noted by the reviewer. We have now plotted the amplitudes at the maximum of the peaks, which do not exhibit any systematic offset as they are much less susceptible to baseline distortions. We are grateful to the reviewer for highlighting this apparent discrepancy.

(12) Figure 2 - the scale for S2 order parameters appears to be backwards, given the caption, but its range should be indicated. Similarly, the range of values for Rex should also be indicated. These data should also be tabulated/plotted in supporting information.

We have corrected the figure legend and added S2 and Rex plots to the supplementary material. The figure aims to highlight regions of increased mobility, while the plots provide full quantitative information on the values. We thank the reviewer for pointing out the error in the figure legend and for the suggestions regarding the plots.

(13) The scale in Figure 3B is illegible. Indeed, the whole structure is quite small and could usefully be expanded.

We increased the size of the structure panels and added a scale.

(14) Figure 4 does not show a decrease in exchange rates, as per the caption - no comparison of exchange rates is shown, only thermodynamic information in panel E. Panel C shows CEST measurements, but it is not clear what system this is for - please clarify, and consider showing the comparable data for the ∆C construct for comparison.

We have amended the figure legend to clarify that the figure shows binding parameters. We added information about the CEST profiles for the EBH/11MACF interaction to the figure legend (Figure 4C). Exchange with the ∆C construct is too fast for CEST measurements. We used lineshape analysis to evaluate the exchange rates for this construct.

(15) The schematics shown in Figure 4D, and elsewhere, are really quite difficult to understand. They may pose additional challenges to colourblind readers. Please consider ways that this could be clarified.

We simplified the colour scheme in the model to make the colours easier to see and to highlight SxIP and non-SxIP regions. We believe that this improved the clarity of the figure.

(16) Figures S1D/E - the x-axes are unclear and units are missing from the y-axes.

We re-labelled the axes to clarify the scale and units. Thank you for pointing this.

Reviewer #2 (Public Review):

The C-terminal tail of EB1, which is adjacent to EBH and is not analyzed in this study, is highly acidic and plays an important role in protein interactions. If the authors discuss the C-terminus of EB1, they should analyze the whole C-terminus of EB1, which would strengthen the conclusion they have made.

Honapa et al., Cell, 2009, reported chemical shift perturbations (CSPs) on the peptide binding for the full EB1c fragment, which includes the negatively charged C-terminus. Similar to our study, they observed significant CSPs in the FVIP region but negligible CSPs at the negatively charged EEY end. They concluded that the final eight EB1c residues did not contribute to binding and used a truncated EB1c construct for their structural analysis. Building on that study, we used the same EEY-truncated construct to analyse the contribution of the C-terminus in more detail. We believe that conducting additional experiments with the full C-terminus with respect to SxIP binding would be superfluous, as it would merely replicate the findings of Honapa EA. We have added the rationale for selecting the truncated EB1c construct to the text, referencing Honapa et al.

Reviewer #2 (Recommendations For The Authors):

(1) Figure 2C: The authors can analyze the 11MACF peptide as well, to provide more assurance to their argument. It would be easier to distinguish the sequences of "SKIP" and "FVIP" by changing their colors.

Our relaxation analysis (Fig. 2C) focuses on the dynamics of the unstructured C-terminal region in both the free and complex forms. Further relaxation analysis of the peptide would not provide additional information on this, and would be complicated by the presence of free peptide in solution.

(2) Figure 3B: Acidic residues in EBH should be labeled.<br /> Page 6, line 11: If the authors insist that the acidic patch will influence the interactions between EB1 and the peptide, the data of the analysis using the entire EB1 C-terminus should be included, given that the C-terminal tail of EB1 is highly acidic.

To test the contribution of charge to binding, we conducted an ITC experiment at increasing salt concentrations. We observed a significant increase in Kd values when the concentration of NaCl increased from 50 to 150 mM, which supports our conclusion regarding the significant electrostatic contribution. This conclusion is independent of the presence or absence of the C-terminus.

As we explained earlier, Honapa et al., Cell 2009, conducted an NMR experiment on the full EB1c and observed no CPSs in the EEY region, indicating a negligible contribution from the EEY region to SxIP binding. Therefore, we think that additional experiments involving the entire C-terminus are unnecessary, as they would simply replicate the results of Honapa et al. We have added the rationale for selecting the truncated EB1c to the text, referencing Honapa et al.

It would be very difficult to label the acidic residues without enlarging 3B considerably. However, we do not think this is necessary as we are not discussing any specific residues. The current figure shows the distribution of the surface charge, which is sufficient for our purposes.

(3) Figure 2B (Page 4, line 27): The side chain of S5477 should be drawn. The authors should include a figure of the crystal structure of EBH and SxIP as a comparison (Honnappa et al., Cell, 2009). In their paper, Honnappa et al. performed chemical shift perturbation titrations by NMR. From their analysis, I imagine that the EB1 tail may not be critical for the EB1 C-terminus:SxIP interactions, since the signals in the tail are not significantly perturbed. The authors should cite this paper.

We are grateful to the reviewer for highlighting this. CSP analysis of the Honapa EA revealed significant changes in the FVIP region, which we also observed. They also reported negligible CSPs at the EEY end, demonstrating that this part of the tail is non-critical and can be removed. We have added text to the manuscript to highlight the similarity between CSPs and those observed in Honapa EA. Figure 2B shows the side chains for the residues with the strongest detected contacts. These do not include S5477.

(4) Figure 3C (ITC data): The stoichiometric ratios in the ITC data look strange. EBH vs KPSKIPVLLRKRK, is it 1:1?

We repeated the ITC experiments using a new stock of the peptide and a new batch of the protein, checking the concentrations using UV spectroscopy. The new experiments produced a stoichiometry close to 1, as shown in the table.

(5) Page 10, line 27: "The TPQ sequence of 11MACF is not optimal...": What is the meaning of "optimal"? The transient interaction between EB1 and its binding partner is responsible for the dynamics of the microtubule cytoskeleton. In a sense, the relatively weak interaction is "optimal" for the system. The authors should rephrase the word.

We agree that weak interactions are optimal from a functional perspective, as they have been selected through evolution. In our case, 'optimal' refers to the hydrophobic interaction with the C-terminus. We replaced 'optimal' with 'ideal' to draw more attention to the second part of the sentence, which clarifies the context.

(6) Page 11, line 2: "small number of comets enriched in the peptide that were too faint for the quantitative analysis, comparable to the reported previously (Honnappa, Gouveia et al. 2009)." Honnappa et al. used EGFP-fusion constructs in their study: EGFP forms a weak dimer, which presumably gave different results from the authors' mTFP-constructs. The authors can note this point in the text.

We are grateful to the reviewer for highlighting this. This aligns well with our conclusion that dimerisation is important for localisation to comets. We have added this point to the text.

(7) Page 10, line 21: The authors calculate the free energy of complex formation between EBH and MACF peptide and explain in the text, but it is hard to follow.

We simplified and clarified the description of the energy contributions by focusing on the SxIP and non-SxIP regions of the peptide, as well as the EBH C-terminus.

Minor points:

Page 2, line 9: IP motifs are not usually located in the C-terminus. For example, SxIP in Tastin is located in the N-terminal region, and SxIPs in CLASP are in the middle.

We corrected this statement, removing C-terminal.

Page 3, line 4: The authors should note the residue numbers of SKIP.

We think that in this context the residue number of the SxIP region are not important and would be distracting.

Figure 3D and Figure S3F: Make the colors and the order the same between the two figures.

We changed the colour scheme and the order of ITC parameters in S3F to match the main figure.

Figure 1A, 2B, Figure S5: Change the color of SKIP from other residues in the same chain, otherwise the readers cannot distinguish. Likewise, change the color of FVIP in Figure 2B.

We think that changing the colours will complicate the figures unnecessary. The corresponding residues are clearly labelled in the figures.

Figure 3, Figure S5, S6, S7: Box the letters of SKIP for clarity.

We boxed the SxIP region in S5 (new S6) and underlined in S6 (new S7). In S7 (new S8) the location of SxIP is very clear from the homology.

Figure 3B; Figure S2: Hard to recognize the peptide (MACF in green).

We increased the size of 3D and S2, making it easier to see the peptide.

Figure 1C and D: Make the residual numbers of the x-axes the same between the two graphs.

We made new plots with a linear scale for the residue numbers.

Figure 2A: The structures shown are not EB1. It should be described as EBH or EB1(191-260 a.a.).

Corrected.

Page 5, line 17: "the S2 values of the C-terminus" should be "the S2 values of the C-terminal loop in EBH", otherwise it is confusing.

Corrected.

Page 6, line 27; Figure S3C and S6: Please indicate the assignments of the resonances from "253FVI255" in the Figures.

We labelled the peaks corresponding to the 253FVI255 region in figure S6 (new S7). Figure S3 shows EBH-ΔC that does not include this region.

Page 7, line 25: Figure S7 should be S8.

Corrected

Page 12, line 6: "sulfatrahsferases" must by a typo.

Corrected.

Reviewer #1 (Public review):

This paper presents a computational model of the evolution of two different kinds of helping ("work," presumably denoting provisioning, and defense tasks) in a model inspired by cooperatively breeding vertebrates. The helpers in this model are a mix of previous offspring of the breeder and floaters that might have joined the group, and can either transition between the tasks as they age or not. The two types of help have differential costs: "work" reduces "dominance value," (DV), a measure of competitiveness for breeding spots, which otherwise goes up linearly with age, but defense reduces survival probability. Both eventually might preclude the helper from becoming a breeder and reproducing. How much the helpers help, and which tasks (and whether they transition or not), as well as their propensity to disperse, are all evolving quantities. The authors consider three main scenarios: one where relatedness emerges from the model, but there is no benefit to living in groups, one where there is no relatedness, but living in larger groups gives a survival benefit (group augmentation, GA), and one where both effects operate. The main claim is that evolving defensive help or division of labor requires the group augmentation; it doesn't evolve through kin selection alone in the authors' simulations.

This is an interesting model, and there is much to like about the complexity that is built in. Individual-based simulations like this can be a valuable tool to explore the complex interaction of life history and social traits. Yet, models like this also have to take care of both being very clear on their construction and exploring how some of the ancillary but potentially consequential assumptions affect the results, including robust exploration of the parameter space. I think the current manuscript falls short in these areas, and therefore, I am not yet convinced of the results.

In this round, the authors provided some clarity, but some questions still remain, and I remain unconvinced by a main assumption that was not addressed.

Based on the authors' response, if I understand the life history correctly, dispersers either immediately join another group (with 1-the probability of dispersing), or remain floaters until they successfully compete for a breeder spot or die? Is that correct? I honestly cannot decide because this seems implicit in the first response but the response to my second point raises the possibility of not working while floating but can work if they later join a group as a subordinate. If it is the case that floaters can have multiple opportunities to join groups as subordinates (not as breeders; I assume that this is the case for breeding competition), this should be stated, and more details about how.

So there is still some clarification to be done, and more to the point, the clarification that happened only happened in the response. The authors should add these details to the main text. Currently, the main text only says vaguely that joining a group after dispersing " is also controlled by the same genetic dispersal predisposition" without saying how.

In response to my query about the reasonableness of the assumption that floaters are in better condition (in the KS treatment) because they don't do any work, the authors have done some additional modeling but I fail to see how that addresses my point. The additional simulations do not touch the feature I was commenting on, and arguably make it stronger (since assuming a positive beta_r -which btw is listed as 0 in Table 1- would make floaters on average be even more stronger than subordinates). It also again confuses me with regard to the previous point, since it implies that now dispersal is also potentially a lifetime event. Is that true?

Meanwhile, the simplest and most convincing robustness check, which I had suggested last round, is not done: simply reduce the increase in the R of the floater by age relative to subordinates. I suspect this will actually change the results. It seems fairly transparent to me that an average floater in the KS scenario will have R about 15-20% higher than the subordinates (given no defense evolves, y_h=0.1 and H_work evolves to be around 5, and the average lifespan for both floaters and subordinates are in the range of 3.7-2.5 roughly, depending on m). That could be a substantial advantage in competition for breeding spots, depending on how that scramble competition actually works. I asked about this function in the last round (how non-linear is it?) but the authors seem to have neglected to answer.

More generally, I find that the assumption (and it is an assumption) floaters are better off than subordinates in a territory to be still questionable. There is no attempt to justify this with any data, and any data I can find points the other way (though typically they compare breeders and floaters, e.g.: https://bioone.org/journals/ardeola/volume-63/issue-1/arla.63.1.2016.rp3/The-Unknown-Life-of-Floaters--The-Hidden-Face-of/10.13157/arla.63.1.2016.rp3.full concludes "the current preliminary consensus is that floaters are 'making the best of a bad job'."). I think if the authors really want to assume that floaters have higher dominance than subordinates, they should justify it. This is driving at least one and possibly most of the key results, since it affects the reproductive value of subordinates (and therefore the costs of helping).

Regarding division of labor, I think I was not clear so will try again. The authors assume that the group reproduction is 1+H_total/(1+H_total), where H_total is the sum of all the defense and work help, but with the proviso that if one of the totals is higher than "H_max", the average of the two totals (plus k_m, but that's set to a low value, so we can ignore it), it is replaced by that. That means, for example, if total "work" help is 10 and "defense" help is 0, total help is given by 5 (well, 5.1 but will ignore k_m). That's what I meant by "marginal benefit of help is only reduced by a half" last round, since in this scenario, adding 1 to work help would make total help go to 5.5 vs. adding 1 to defense help which would make it go to 6. That is a pretty weak form of modeling "both types of tasks are necessary to successfully produce offspring" as the newly added passage says (which I agree with), since if you were getting no defense by a lot of food, adding more food should plausibly have no effect on your production whatsoever (not just half of adding a little defense). This probably explains why often the "division of labor" condition isn't that different than the no DoL condition.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public review):

This study examined the effect of blood pressure variability on brain microvascular function and cognitive performance. By implementing a model of blood pressure variability using an intermittent infusion of AngII for 25 days, the authors examined different cardiovascular variables, cerebral blood flow, and cognitive function during midlife (12-15-month-old mice). Key findings from this study demonstrate that blood pressure variability impairs baroreceptor reflex and impairs myogenic tone in brain arterioles, particularly at higher blood pressure. They also provide evidence that blood pressure variability blunts functional hyperemia and impairs cognitive function and activity. Simultaneous monitoring of cardiovascular parameters, in vivo imaging recordings, and the combination of physiological and behavioral studies reflect rigor in addressing the hypothesis. The experiments are well-designed, and the data generated are clear. I list below a number of suggestions to enhance this important work:

(1) Figure 1B: It is surprising that the BP circadian rhythm is not distinguishable in either group. Figure 2, however, shows differences in circadian rhythm at different timepoints during infusion. Could the authors explain the lack of circadian effect in the 24-h traces?

The circadian rhythm pattern is apparent in Figure 2 (Active BP higher than Inactive BP), where BP is presented as 12hour averages. When the BP data is expressed as one-hour averages (rather than minute-to-minute) over 24hours, now included in the revised manuscript as Supplemental Figure 3C-D, the circadian rhythm becomes noticeable. In addition, we have included one-hour average BP data for all mice in the control and BPV groups, Supplemental Figure 3A-B.

Notably, the Ang-II induced pulsatile BP pattern remains evident in the one-hour averages for the BPV group, Supplemental Figure 3B. To minimize bias and validate variability, pump administrations start times were randomized for both control and BPV groups, Supplemental Figure 3A-B. Despite these adjustments, the circadian rhythm profile of BP is consistently maintained across individual mice and in the collective dataset, Supplemental Figure 3C-D.

(2) While saline infusion does not result in elevation of BP when compared to Ang II, there is an evident "and huge" BP variability in the saline group, at least 40mmHg within 1 hour. This is a significant physiological effect to take into consideration, and therefore it warrants discussion.

Thank you for this comment. The large variations in BP in the raw traces during saline infusion reflects transient BP changes induced by movement/activity, which is now included in Figure 1B (maroon trace). The revised manuscript now includes Line 222 “Note that dynamic activity-driven BP changes were apparent during both saline- and Ang II infusions, Figure 1B”.

(3) The decrease in DBP in the BPV group is very interesting. It is known that chronic Ang II increases cardiac hypertrophy, are there any changes to heart morphology, mass, and/or function during BPV? Can the decrease in DBP in BPV be attributed to preload dysfunction? This observation should be discussed.

The lower DBP in the BPV group was already present at baseline, while both groups were still infused with saline, and was a difference beyond our control. However, this is an important and valid consideration, particularly considering the minimal yet significant increase in SBP within the BPV group (Figure 1D). Our goal was to induce significant transient blood pressure responses (BPV) and investigate the impact on cardiovascular and neurovascular outcomes in the absence of hypertension. We did not anticipate any major cardiac remodeling at this early time point (considering the absence of overt hypertension) and thus cardiac remodeling was not assessed and this is now discussed in the revised manuscript (Line 443-453).

(4) Examining the baroreceptor reflex during the early and late phases of BPV is quite compelling. Figures 3D and 3E clearly delineate the differences between the two phases. For clarity, I would recommend plotting the data as is shown in panels D and E, rather than showing the mathematical ratio. Alternatively, plotting the correlation of ∆HR to ∆SBP and analyzing the slopes might be more digestible to the reader. The impairment in baroreceptor reflex in the BPV during high BP is clear, is there any indication whether this response might be due to loss of sympathetic or gain of parasympathetic response based on the model used?

We appreciate the reviewer’s suggestion and have accordingly generated new figures displaying scatter plots of SBP vs HR with linear regression analysis (Figure 3D-G). Our goal is to further investigate which branch of the autonomic nervous system is affected in this model. The loss of a bradycardic response suggests either an enhancement of sympathetic activity, a reduction in parasympathetic activity, or a combination of both. This is briefly discussed in the revised manuscript (Line 486-496).

Heart rate variability (HRV) serves as an index of neurocardiac function and dynamic, non-linear autonomic nervous system processes, as described in Shaffer and Ginsber[1]. However, given that our data was limited to BP and HR readings collected at one-minute intervals, our primary assessment of autonomic function is limited to the bradycardic response. Further studies will be necessary to fully characterize the autonomic parameters influenced by chronic BPV.

(5) Figure 3B shows a drop in HR when the pump is ON irrespective of treatment (i.e., independent of BP changes). What is the underlying mechanism?

We apologize for any lack of clarity. These observed heart rate (HR) changes occurred during Ang II infusion, when blood pressure (BP) was actively increasing. In the control group, the pump solution was switched to Ang II during specific periods (days 3-5 and 21-25 of the treatment protocol) to induce BP elevations and a baroreceptor response, allowing direct comparisons between the control and BPV group.

To clarify this point, we have revised Line 260-263 of the manuscript: “To compare pressure-induced bradycardic responses between BPV and control mice at both early and later treatment stages, a cohort of control mice received Ang II infusion on days 3-5 (early phase) (Supplemental Figure 4) and days 21-25 (late phase) thereby transiently increasing BP”.

Additionally, a detailed description has been added to the Methods section (Line 96-101): “Controls receiving Ang II: To facilitate between-group comparisons (control vs BPV), a separate cohort of control mice were subjected to the same pump infusion parameters as BPV mice but for a brief period receiving Ang II infusions on days 3-5 and 21-25 for experiments assessing pressure-evoked responses, including bradycardic reflex, myogenic response, and functional hyperemia at high BP.”

(6) The correlation of ∆diameter vs MAP during low and high BP is compelling, and the shift in the cerebral autoregulation curve is also a good observation. I would strongly recommend that the authors include a schematic showing the working hypothesis that depicts the shift of the curve during BPV.

Thank you for this insightful comment. The increase in vessel reactivity to BP elevations in parenchymal arterioles of BPV mice suggests that chronic BPV induces a leftward shift and a potential narrowing of the cerebral autoregulation range (lower BP thresholds for both the upper and lower limits of autoregulation). This has been incorporated (and discussed) into the revised manuscript (see Figure 5N).

One potential explanation for these changes is that the absence of sustained hypertension, a prominent feature in most rodent models of hypertension, limits adaptive processes that protect the cerebral microcirculation from large BP fluctuations (e.g., vascular remodeling). While this study does not specifically address arteriole remodeling, the lack of such adaptation may reduce pressure buffering by upstream arterioles, thereby rendering the microcirculation more vulnerable to significant BP fluctuations.

The unique model allows for measurements of parenchymal arteriole reactivity to acute dynamic changes in BP (both an increase and decrease in MAP). Our findings indicate that chronic BPV enhances the reactivity of parenchymal arterioles to BP changes—both during an increase in BP and upon its return to baseline, Supplemental Figure 5C, F. The data suggest an increased myogenic response to pressure elevation, indicative of heightened contractility, a common adaptive process observed in rodent models of hypertension[2-4]. However, our model also reveals a notable tendency for greater dilation when the BP drops, Supplemental Figure 5F. This intriguing observation may suggest ischemia during the vasoconstriction phase (at higher BP), leading to enhanced release of dilatory signals, which subsequently manifest as a greater dilation upon BP reduction. This phenomenon bears similarities to chronic hypoperfusion models[5,6], where vasodilatory mechanisms become more pronounced in response to sustained ischemic conditions. Future studies investigating the effects of BPV on myogenic responses and brain perfusion will be a priority for our ongoing research.

(7) Functional hyperemia impairment in the BPV group is clear and well-described. Pairing this response with the kinetics of the recovery phase is an interesting observation. I suggest elaborating on why BPV group exerts lower responses and how this links to the rapid decline during recovery.

Based on the heightened reactivity of BPV parenchymal arterioles to intravascular pressure (Figure 5), we anticipate that the reduction of sensory-evoked dilations results from an increased vasoconstrictive activity and/or a decreased availability of vasodilatory signaling pathways (NO, EETs, COX-derived prostaglandins)[7,8]. Consequently, the magnitude of the FH response is blunted during periods of elevated BP in BPV mice.

Additionally, upon termination of the stimulus-induced response−when vasodilatory signals would typically dominate−vasoconstrictive mechanisms are rapidly engaged (or unmasked), leading to quicker return to baseline. This shift in the balance between vasodilatory and vasoconstrictive forces favors vasoconstriction, contributing to the altered recovery kinetics observed in BPV mice. This has been included in the Discussion section of the revised manuscript.

(8) The experimental design for the cognitive/behavioral assessment is clear and it is a reasonable experiment based on previous results. However, the discussion associated with these results falls short. I recommend that the authors describe the rationale to assess recognition memory, short-term spatial memory, and mice activity, and explain why these outcomes are relevant in the BPV context. Are there other studies that support these findings? The authors discussed that no changes in alternation might be due to the age of the mice, which could already exhibit cognitive deficits. In this line of thought, what is the primary contributor to behavioral impairment? I think that this sentence weakens the conclusion on BPV impairing cognitive function and might even imply that age per se might be the factor that modulates the various physiological outcomes observed here. I recommend clarifying this section in the discussion.

We thank the reviewer for this comment. Clinical studies have demonstrated that patients with elevated BPV exhibit impairments across multiple cognitive domains, including declines in processing speed[9] and episodic memory[10]. To evaluate memory function, we utilized behavioral tests: the novel object recognition (NOR) task to assess episodic memory[11] and the spontaneous Y-maze to evaluate short-term spatial memory[12].

Previous research indicates that older C57Bl6 mice (14-month-old) exhibit cognitive deficits compared to younger counterparts (4- and 9-month-old)[13]. To ensure rigorous selection for behavioral testing, we conducted preliminary NOR assessment, evaluating recognition memory at the one-hour delay but observing failures at the four-, and 24-hour delays, indicating age-related deficits. Based on these results, animals failing recognition criteria were excluded from subsequent behavioral assessment. However, because no baseline cognitive testing was conducted for the spontaneous Y-maze, it is possible that some mice with aged-related deficits were included in this test, which may have influenced data interpretation.

Additionally, the absence of differences in the Y-maze performance may suggest that short-term spatial memory remains intact following 25 days of BPV, a point that is now discussed in the revised manuscript.

(9) Why were only male mice used?

We appreciate this comment and acknowledge the importance of conducting experiments in both male and female mice. Studies involving female mice are currently ongoing, with telemetry data collection approximately halfway completed and two-photon imaging studies on functional hyperemia also partially completed. However, using middleaged mice for these experiments has proven challenging due to high mortality rates following telemetry surgeries. As a result, we initially limited our first cohort to male mice.

(10) In the results for Figure 3: "Ang II evoked significant increases in SBP in both control and BPV groups;...". Also, in the figure legend: "B. Five-minute average HR when the pump is OFF or ON (infusing Ang II) for control and BPV groups...." The authors should clarify this as the methods do not state a control group that receives Ang II.

Please refer to response to comment 5.

Reviewer #2 (Public review):

Summary:

Blood pressure variability has been identified as an important risk factor for dementia. However, there are no established animal models to study the molecular mechanisms of increased blood pressure variability. In this manuscript, the authors present a novel mouse model of elevated BPV produced by pulsatile infusions of high-dose angiotensin II (3.1ug/hour) in middle-aged male mice. Using elegant methodology, including direct blood pressure measurement by telemetry, programmable infusion pumps, in vivo two-photon microscopy, and neurobehavioral tests, the authors show that this BPV model resulted in a blunted bradycardic response and cognitive deficits, enhanced myogenic response in parenchymal arterioles, and a loss of the pressure-evoked increase in functional hyperemia to whisker stimulation.

Strengths:

As the presentation of the first model of increased blood pressure variability, this manuscript establishes a method for assessing molecular mechanisms. The state-of-the-art methodology and robust data analysis provide convincing evidence that increased blood pressure variability impacts brain health.

Weaknesses:

One major drawback is that there is no comparison with another pressor agent (such as phenylephrine); therefore, it is not possible to conclude whether the observed effects are a result of increased blood pressure variability or caused by direct actions of Ang II.

We acknowledge this limitation and have attempted to address the concern by introducing an alternative vasopressor, norepinephrine (NE), Figure 4. A subcutaneous dose of 45 µg/kg/min was titrated to match Ang II-induced transient BP pulse (Systolic BP ~150-180 mmHg), Figure 4A. Similar to Ang II treated mice, NE-treated mice exhibited no significant changes in average mean arterial pressure (MAP) throughout the 20-day treatment period (Figure 4B). Although there was a trend (P=0.08) towards increased average real variability (ARV) (Figure 4C left), it did not reach statistical significance. The coefficient of variation (CV) (Figure 4C right) was significantly increased by day 3-4 of treatment (P=0.02).

Notably, unlike the bradycardic response observed during Ang II-induced BP elevations, NE infusions elicited a tachycardic response (Figure 4A), likely due to β-1 adrenergic receptor activation. However, significant mortality was observed within the NE cohort: three of six mice died prematurely during the second week of treatment, and two additional mice required euthanasia on days 18 and 20 due to lethargy, impaired mobility, and tachypnea.

While we recognize the importance of comparing results across vasopressors, further investigation using additional vasopressors would require a dedicated study, as each agent may induce distinct off-target effects, potentially generating unique animal models. Alternatively, a mechanical approach−such as implanting a tethered intra-aortic balloon[14] connected to a syringe pump−could be explored to modulate blood pressure variability without pharmacological intervention. However, such an approach falls beyond the scope of the present study.

Ang II is known to have direct actions on cerebrovascular reactivity, neuronal function, and learning and memory. Given that Ang II is increased in only 15% of human hypertensive patients (and an even lower percentage of non-hypertensive), the clinical relevance is diminished. Nonetheless, this is an important study establishing the first mouse model of increased BPV.

We agree that high Ang II levels are not a predominant cause of hypertension in humans, which is why it is critical that our pulsatile Ang II dosing did not cause overt hypertension, (no increase in 24-hour MAP). Ang II was solely a tool to produce controlled, transient increases in BP to yield a significant increase in BPV.

Regarding BPV specifically, prior studies indicate that primary hypertensive patients with elevated urinary angiotensinogen-to-creatinine ratio exhibit significantly higher mean 24-hour systolic ARV compared to those with lower ratios[15]. However, the fundamental mechanisms driving these harmful increases in BPV remain poorly defined. A central theme across clinical BPV studies is impaired arterial stiffness, which has been proposed to contribute to BPV through reduced arterial compliance and diminished baroreflex sensitivity. Moreover, increased BPV can exert mechanical stress on arterial walls, leading to arterial remodeling and stiffness−ultimately perpetuating a detrimental feed-forward cycle[16].

In our model, male BPV mice exhibited a minimal yet significant elevation in SBP without corresponding increases in DBP, potentially reflecting isolated systolic hypertension, which is strongly associated with arterial stiffness[17,18]. Our initial goal was to establish controlled rapid fluctuations in BP, and Ang II was selected as the pressor due to its potent vasoconstrictive properties and short half-life[19].

We appreciate the reviewer’s insightful comment and acknowledge the necessity of exploring alternative mechanisms underlying BPV, and independent of Ang II. It is our long-term goal to investigate these factors in further studies.

Recommendations for the authors:

Reviewer #2 (Recommendations for the authors):

(1) How was the dose of Ang II determined? It seems that this dose (3.1ug/hr) is quite high.

The Ang II dose was titrated in a preliminary study to one that induced a significant and transient BP response without increasing 24-hour blood pressure (i.e. no hypertension).

Ang II was delivered subcutaneously at 3.1 μg/hr, a concentration comparable to high-dose Ang II administration via mini-osmotic pumps (~1700 ng/kg/min)[20], with one-hour pulses occurring every 3-4 hours. With 6 pulses per day, the total daily dose equates to 18.6 µg/day in a ~30 gram mouse.

For comparison, if the same 18.6 µg/day dose were administered continuously via a mini-osmotic pump (18.6 µg/0.03kg/1440min), the resulting dosage would be approximately 431 ng/kg/min[21,22], aligning with subpressor dose levels. Thus, while the total dose may appear high, it is not delivered in a constant manner but rather intermittently, allowing for controlled, rapid variations in blood pressure.

(2) Were behavioral studies performed on the same mice that were individually housed? Individual housing causes significant stress in mice that can affect learning and memory tasks (PMC6709207). It's not a huge issue since the control mice would have been housed the same way, but it is something that could be mentioned in the discussion section.

Behavioral studies were performed on mice that were individually housed following the telemetry surgery. The study was started once BP levels stabilized, as mice required several days to achieve hemodynamic stability post-surgery. Consequently, all mice were individually housed for several days before undergoing behavioral assessment.

To account for potential cognitive variability, earlier novel object recognition (NOR) tests were conducted to established cognitive capacity, and mice that did not meet criteria were excluded from further behavioral testing. However, we acknowledge that individual housing induces stress, which can influence learning and memory, and this is a factor we were unable to fully control. Given that both experimental and control groups experienced the same housing conditions, this stress effect should be comparable across cohorts. A discussion on this limitation is now included in the text.

(3) It looks like one control mouse that was included in both Figures 1 and 2 (control n=12) but was excluded in Table 1 (control n=11), this isn't mentioned in the text - please include the exclusion criteria in the manuscript.

We apologize for the typo−12 control animals were consistently utilized across Figure 1-2, Table 1, Supplemental Table 1, Figure 6C, and Supplemental Figure 2B. Since the initial submission, one control mouse was completed and included into the telemetry control cohort. Thus, in the updated manuscript, we have corrected the control sample size to 13 mice across these figures ensuring consistency.

Additionally, exclusion criteria have now been explicitly included in the manuscript (Line 173-175). Mice were excluded from the study if they died prematurely (died prior to treatment onset) or mice exhibited abnormally elevated pressure while receiving saline, likely due to complications from telemetry surgery.

(4) Please include a statement on why female mice were not included in this study.

As discussed in our response to Reviewer #1, our initial intention was to include both male and female mice in this study. However, high mortality rates following telemetry surgeries significantly constrained our ability to advance all aspects of the study. As a result, we limited our first cohort to males to establish the basics of the model. A statement is now included in the manuscript, Line 50-53: “Female mice were not included in the present study due to high post-surgery mortality observed in 12-14-month-old mice following complex procedures. To minimized confounding effects of differential survival and to establish foundational data for this model, we restricted the investigation to male mice.”

Potential sex differences might be complex and warrants a separate future research to comprehensively assess sex as a biological variable, which are currently ongoing.

(5) On page 14, "experiments from control vs experimental mice were not equally conducted in the same season raising the possibility for a seasonal effect" - does this mean that control experiments were not conducted at the same time as the Ang II infusions in BPV mice? This has huge implications on whether the effects observed are induced by treatment or just batch seasonal effects.

We fully acknowledge the reviewer’s concern, and our statement aims to provide transparency regarding the study’s limitations. Several challenges contributed to this outcome, including high mortality rates following surgeries (primarily telemetry implantation) and technical issues related to instrumentation, particularly telemetry functionality.

Differences between BPV and saline mice emerge primarily due to mortality or telemetry failures−some mice did not survive post-surgery, while others remain healthy but had non-functional telemeters. This issue was particularly pronounced in 14-month-old mice, as their fragile vasculature occasionally prevented proper BP readings.

Each experiment required a minimum of two and a half months per mouse to complete, with a cost (also per mouse) exceeding $1500 USD ($300 pump, $175 mouse, $900 telemeters, per diem, drugs, reagents etc.). Despite our best effort to ensure comparable seasonal/batch data, these logistical and technical constraints prevented perfect synchronization.

To evaluate whether seasonal differences influenced our results, we incorporated additional telemetry data into the control cohort. Of the seven included control mice, six underwent the same treatment but were allocated to a separate branch of the study, which endpoints did not require a chronic cranial window. We found no significant differences in 24-hour average MAP during the baseline period between control mice with or without a cranial window, Supplemental Figure 2A. Additionally, we grouped mice into seasonal categories based on Georgia’s climate: “Spring-Summer” (May-September) and “Fall-Winter” (October-April) but observed no BP differences between these periods, Supplemental Figure 2B.

Given the absence of seasonal effects on BP and the fact that mice were sourced from two independent suppliers (Jackson Laboratory and NIA), we anticipate that the observed results are driven by treatment rather than seasonal or batch effects.

(6) Methods, two-photon imaging: did the authors mean "retro-orbital" instead of "intra-orbital" injection of the Texas red dye? Also, is this a Texas red-dextran? If so, what molecular weight?

Thank you for this comment. The correct terminology is “retro-orbital” rather than “intra-orbital” injection. Additionally, we utilized Texas Red-dextran (70 kDa, 5% [wt/vol] in saline) for the imaging experiments. These details have now been incorporated into the Methods section.

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What is this?

Muy bien todo a mi parecer. Faltaría ahora reportar los graficos y datos con ELSOC.

Entiendo que aquí empieza la relación cohesión y migración, pero lo haría más explicito en el topic sentence. Tipo: Los niveles y formas de la cohesión social dependen fuertemente de la inmigración. Algo así

Esto podría fusionarse pues dicen lo mismo

Unificar parrafos en caracterizacion de la pob migrante

https://www.youtube.com/watch?v=trdxrBVknXg

Synthèse : Le Malaise de l'Éducation Nationale Française Ce dossier de briefing examine les multiples facettes du malaise qui ronge l'Éducation Nationale française, révélant une institution en crise, tiraillée entre violence, surcharge de travail, manque de reconnaissance, inégalités et un rôle éducatif élargi qui dépasse largement sa mission d'instruction.

Le suicide tragique de Christine Renon, directrice d'école, sert de catalyseur pour explorer ces problèmes systémiques.

I. Une Institution Ébranlée : Violence, Incivilités et Perte de Repères

L'éducation nationale, pilier de la République française, est confrontée à une perte de repères.

La violence et les incivilités, bien que rares en leur forme extrême (comme l'incident filmé dans un lycée de Seine-et-Marne), contribuent à ce sentiment.

Violences et Incivilités : Le document s'ouvre sur l'image choc d'un élève violentant un personnel enseignant, un "geste rare mais pas isolé". Ce phénomène n'est pas la seule raison du malaise, mais il est significatif.

Au collège Côrousse en REP (Réseau d'Éducation Prioritaire) à Chambéry, les mesures de sécurité sont renforcées : "ils doivent présenter leur carnet à chaque entrée et à chaque sortie, enlever capuche et tout ce qui pourrait couvrir leur visage".

Perception du Public : Un sondage Ipsos révèle que "94 % des parents souhaitent le retour de l'autorité à l'école", illustrant une inquiétude généralisée.

Compréhension des Codes : Les enseignants en REP se heurtent à la difficulté que "les élèves ici n'ont pas les codes", conduisant à des malentendus profonds.

Isabelle Dumet, professeure d'histoire-géographie, cite un élève lui ayant dit "Madame tu me casses les couilles", et un autre qui a explosé de colère après qu'elle lui ait dit "arrête de m'aboyer dessus", l'interprétant comme une insulte grave : "Vous me dites que je suis un chien mais qu'est-ce que c'est ça ?".

II. Surcharge de Travail, Isolement et Souffrance des Directeurs d'École

Le suicide de Christine Renon, directrice d'école primaire à Pantin en septembre 2019, est l'illustration la plus tragique de la surcharge et de l'isolement des directeurs.

Sa lettre, envoyée à ses collègues, dépeint un tableau accablant : "je n'ai pas confiance au soutien et à la protection que devrait nous apporter notre institution et pour finir je me demande si je ne ferai pas une petite déprime".

Un "Geste Politique" : Sabine, syndicaliste, affirme que le suicide de Christine est "un geste politique, il est marqué par la lourdeur de ses conditions de travail, par son épuisement général lié à son à son travail".

Poste "d'Hommes et de Femmes à Tout Faire" : Les directeurs d'école primaire sont décrits comme des "hommes et des femmes à tout faire sans équipe pour les épauler comme dans le secondaire", ce qui génère un profond "isolement".

Missions Débordantes : La fonction de directeur dépasse largement la seule mission d'instruction. L'école devient un "point de ressources pour les familles" qui viennent chercher de l'aide pour "remplir des papiers", résoudre des "problèmes de logement". Sandrine Delmas, directrice à Pantin, confirme : "tout ça ça fait partie aussi des choses en plus des questions de l'école qu'on retrouve dans ce quartier".

L'Effet Miroir de la Lettre : La lettre de Christine a eu un "effet miroir" pour de nombreux collègues, les aidant à prendre conscience de la surcharge de travail et de la solitude.

Sandrine exprime ce sentiment : "notre métier c'est tout ça c'est tout ça et c'est pas tout à fait normal que tout ça pèse sur les épaules d'une seule personne".

Réponse Insuffisante de l'Institution : Deux ans après le suicide de Christine, "peu de choses ont changé" selon Sabine.

Le rectorat a tenté d'"étouffer l'affaire" et les "améliorations" promises pour alléger les tâches administratives ne se sont pas concrétisées.

III. Inégalités Territoriales et de Moyens

Le système éducatif français est paradoxal : il revendique l'égalité des chances tout en présentant de profondes inégalités de moyens.

Pantin, Ville à Deux Vitesses : Pantin, en Seine-Saint-Denis (93), est coupée en deux : d'un côté "les quartiers pauvres, parfois insalubres" où "les 3/4 des familles sont au chômage, certaines parlent à peine le français", et de l'autre "les quartiers bobo" en pleine expansion. Sur 11 écoles primaires, six sont en REP, "c'est énorme".

L'Origine Sociale : "La France est l'un des pays développés où l'origine sociale pèse le plus sur les trajectoires scolaires", résumant la situation par "dis-moi quel est le salaire de tes parents et je te dirai si tu réussiras".

Budgets Inégaux : Annabelle, ancienne directrice d'école, dénonce les "inégalités au niveau des territoires" et les budgets "qui varient du simple au double au triple" par enfant.

Elle souligne : "l'égalité des chances elle passe aussi parce qu'on va apporter en terme de moyen à l'école".

"Mixité Sociale" : Cédric Pusser, jeune directeur à Saint-Paul (Haute-Vienne), dans une école privilégiée, s'interroge sur la préparation de ses élèves à la vie en dehors de leur "environnement tellement protégé" et souligne l'importance d'une "mixité sociale".

IV. Désenchantement de la Profession Enseignante

Les conditions de travail et la faible reconnaissance salariale contribuent à un désenchantement croissant et à une crise des vocations.

Salaires Insuffisants : Avec un Bac+5, un instituteur débutant gagne en moyenne 1800 € net par mois, comparé au SMIC à 1200 € net. La France est en "20e position des pays développés" pour la revalorisation des salaires. Les témoignages révèlent une stagnation, voire une baisse du pouvoir d'achat : "j'ai pas vu bouger mon salaire du tout j'ai vu mon pouvoir d'achat baisser".

Crise des Vocations et Démissions : "Qui veut être enseignant aujourd'hui en France ? Je crois ceux qui ont la foi, ceux qui ont la vocation". Cependant, de plus en plus de personnes "rentrent dans le métier qui n'y restent pas, qui démissionnent, qui s'en vont parce que les conditions de travail ne sont pas forcément celle auxquelles ils s'attendaient".

En 2018, "1400 enseignants ont démissionné, c'est quatre fois plus qu'il y a 10 ans".

Non-Remplacement des Enseignants : Le document pointe un problème grave : "entre la rentrée des vacances des grandes vacances [...] jusqu'aux vacances d'automne, on a quand même 107 jours de classes qui n'ont pas été remplacés", ce qui représente "au moins un jour sans enseignant dans la classe".

Manque de Reconnaissance : Sandrine exprime le sentiment que les parents ne voient pas les enseignants comme des "professionnels de l'enseignement", attribuant cette perception aux "politiques éducatives" et aux clichés sur les fonctionnaires "toujours en vacances".

Elle insiste sur le "travail qu'on ne voit pas mais qui se fait à la maison".

V. Entre Instruire et Éduquer : Un Débat Central

Le débat entre "instruire ou éduquer" est au cœur des préoccupations et de la campagne présidentielle. Si la droite insiste sur le "retour au savoirs fondamentaux", la réalité du terrain est plus complexe.

La Priorité en REP : La directrice du collège Côrousse affirme que "quand on travaille en collège en REP la priorité c'est l'éducation".

Elle va plus loin en disant : "l'éducation nationale n'a jamais été aussi bien nommée que maintenant éducation nationale".

Pour elle, l'instruction n'est qu'un "prétexte" pour "poser les fondamentaux d'un citoyen éclairé autonome".

Former le Futur Citoyen : La mission du collège est de former "un futur citoyen", de lui donner un "esprit critique, une liberté" et de lui "remplir leur besace" pour qu'il puisse "choisir ce qu'ils en font ou pas".

Le Conseil de Discipline comme Acte Éducatif : Le conseil de discipline de Karim, un élève ayant dégradé une porte, est présenté comme un "acte éducatif" plutôt qu'une simple sanction.

La directrice explique à l'élève : "l'objectif du jour c'est de poser un acte éducatif c'est pas de sanctionner pour sanctionner c'est que tu comprennes ce que tu as fait".

Elle insiste sur la gravité de l'acte en comparant la situation à un "début de tribunal".

VI. L'Omerta et le Déni des Responsables Politiques

Le document met en lumière une résistance des autorités à aborder les problèmes de front.

Refus de Coopération : Le rectorat de Créteil a "refusé d'entrer dans les écoles de Pantin", le ministre de l'Éducation nationale a "décommandé une interview à la dernière minute", et la mairie de Pantin n'a "jamais répondu à nos sollicitations".

Sandrine Delmas pense que c'est lié à "la peur de d'encore étiqueter le 93 comme un département compliqué" et au "suicide de Christine" qui a suscité des "paroles qui ont dérangé l'institution".

Promesses Électorales Récurrentes : Les candidats à la présidentielle s'emparent de la question de l'éducation nationale avec des promesses de réformes, mais le document souligne que c'est une constante "à chaque élection présidentielle depuis 20 ans".

Conclusion

Le système éducatif français est à un point de rupture. Entre la violence en milieu scolaire, la détresse des personnels due à la surcharge et au manque de reconnaissance, les inégalités criantes entre territoires et la crise des vocations, l'urgence est réelle.

L'école, traditionnellement un lieu d'instruction, est devenue un acteur social et éducatif majeur, souvent sans les moyens nécessaires.

Le silence et le déni des autorités face à ces problématiques exacerbent le sentiment d'abandon des acteurs de terrain.

Le suicide de Christine Renon n'est pas un cas isolé, mais le symbole d'un "malaise bien plus répandu qu'on l'imagine".

Si "l'institution n'est pas encore en danger, il y a urgence".

Author response:

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

Reviewer #1 (Public review): 

Summary: 

In this work, the authors apply TDCS to awake and anesthetized macaques to determine the effect of this modality on dynamic connectivity measured by fMRI. The question is to understand the extent to which TDCS can influence conscious or unconscious states. Their target was the PFC. During the conscious states, the animals were executing a fixation task. Unconsciousness was achieved by administering a constant infusion of propofol and a continuous infusion of the muscle relaxant cisatracurium. They observed the animals while awake receiving anodal or cathodal hd-TDCS applied to the PFC. During the cathodal stimulation, they found disruption of functional connectivity patterns, enhanced structure-function correlations, a decrease in Shannon entropy, and a transition towards patterns that were more commonly anatomically based. In contrast under propofol anesthesia anodal hd-TDCS stimulation appreciably altered the brain connectivity patterns and decreased the correlation between structure and function. The PFC stimulations altered patterns associated with consciousness as well as those associated with unconsciousness.

Strengths: 

The authors carefully executed a set of very challenging experiments that involved applying tDCS in awake and anesthetized non-human primates while conducting functional imaging.

We thank the Reviewer for summarising our study and for his appreciation of the highly challenging experiments we performed.

Weaknesses:

The authors show that tDCS can alter functional connectivity measured by fMRI but they do not make clear what their studies teach the reader about the effects of tDCS on the brain during different states of consciousness. No important finding is stated contrary to what is stated in the abstract. It is also not clear what the work teaches us about how tDCS works nor is it clear what are the "clinical implications for disorders of consciousness." The deep anesthesia is akin to being in a state of coma. This was not discussed.  

While the authors have executed a set of technically challenging experiments, it is not clear what they teach us about how tDCS works, normal brain neurophysiology, or brain pathological states such as disorders of consciousness.

We thank the reviewer for his comments. We agree that we could better highlight the value and implications of our work, and we take this opportunity to improve our manuscript according to the suggestions.

Actions in the text: We have added several new paragraphs in the Discussion section, considering these comments and other related remarks from the Reviewing Editor (see below our answer to the first comment of the Reviewing Editor: REC#1).

Reviewer #2 (Public review): 

General comments: 

The authors investigated the effects of tDCS on brain dynamics in awake and anesthetized monkeys using functional MRI. They claim that cathodal tDCS disrupts the functional connectivity pattern in awake monkeys while anodal tDCS alters brain patterns in anesthetized monkeys. This study offers valuable insight into how brain states can influence the outcomes of noninvasive brain stimulation. However, there are several aspects of the methods and results sections that should be improved to clarify the findings.

We thank the Reviewer for the summary and appreciation of our study.  

Major comments 

For the anesthetized monkeys, the anode location differs between subjects, with the electrode positioned to stimulate the left DLFPC in monkey R and the right DLPFC in monkey N. The authors mention that this discrepancy does not result in significant differences in the electric field due to the monkeys' small head size. However, this is incorrect, as placing the anode on the left hemisphere would result in a much lower EF in the right DLPFC than placing the anode on the right side. Running an electric field simulation would confirm this. Additionally, the small electrode size suggested by the Easy cap configuration for NHP appears sufficient to stimulate the targeted regions focally. If this interpretation is correct, the authors should provide additional evidence to support their claim, such as a computational simulation of the EF distribution.

We thank the Reviewer for the comments. First, regarding the reviewer’s statement that placing the anode on the left hemisphere would result in a much lower EF in the right DLPFC than placing the anode on the right side, we would like to clarify that we did not use a typical 4 x 1 concentric ring high-definition setup (which consists of a small centre electrode surrounded by four return electrodes), but a two-electrode montage, with one electrode over the left or right PFC and the other one over the contralateral occipital cortex. According to EF modelling papers, a 4 x 1 high-definition setup would produce an EF that is focused and limited to the cortical area circumscribed by the ring of the return electrodes (Datta et al. 2009; Alam et al. 2016). Therefore, targeting the left or right DLPFC with a 4 x 1 setup would produce an EF confined to the targeted hemisphere of the PFC. In contrast, we expect the brain current flow generated with our 2-electrode setup to be broader, despite the small size of the electrodes,  because there is no constraint from return electrodes. Thus, with our setup, the current is expected to flow between the PFC and the occipital cortex (see also our responses to comments R3.3., R.E.C.#2.1. and R.E.C.#2.2.). 

Second, we would like to point out that in awake experiments, in which we stimulated the right PFC of both monkeys, there was no gross evidence of left or right asymmetry in the computed functional connectivity patterns (Figure 3A, Figure 3 - figure supplement 2A; Figure 5A). These results, showing that our stimulation montages did not induce asymmetric dynamic FC changes in NHPs, support the idea that our setups did not generate EFs that were spatially focused enough to alter brain activity in one hemisphere substantially more than the other.

Third, it is also worth noting that current evidence suggests that human brains are significantly more lateralized than those of macaques. Macaque monkeys have been found to have some degree of lateralized networks, but these are of lower complexity, and the lateralization is less pronounced and functionally organized than in humans. (Whey et al., 2014; Mantini et al., 2013). This suggests that, even if the stimulation were focal enough to stimulate the left or the right part of the PFC only, the behavioural effects would likely be similar.

We strongly agree with the reviewer that conducting an EF simulation would be valuable to confirm our expectations and to gain a comprehensive view of the characteristics of the EFs generated with our different setups in NHPs. However, the challenge is in the fact that EF computational models have been developed for humans, and their use in NHPs is not straightforward due to significant anatomical differences. For example, macaque monkeys are distinct from humans in terms of brain size, shape and cortical organisation, skull thickness, and the presence of muscles, as well as different tissue conductivities (Lee et al. 2015; Datta et al.2016; Mantell et al. 2023). We plan to address this in future work.

Actions in the text: In the Materials and Methods section, we have modified the sentence: “Because of the small size of the monkey's head and because we did not use return electrodes to restrict the current flow (as is achieved with typical high-definition montages (Datta et al. 2009; Alam et al. 2016)), we expected that tDCS stimulation with the two symmetrical montages would result in nearly equivalent electric fields across the monkey’s head and produce roughly similar effects on brain activity.” 

We also added a new sentence about EF simulation: 

“This would need to be confirmed by running an electric field simulation. However, computational electric field models have been developed for humans, and their use in NHPs is not straightforward due to anatomical specificities. Indeed, monkeys differ from humans in terms of brain size, shape and cortical organization, skull thickness, tissue conductivities and the presence of muscles (Lee et al. 2015; Datta et al. 2016; Mantell et al. 2023). Modelling of EFs generated with the specific tDCS montages employed in this study will be performed in future work.”

For the anesthetized monkeys, the authors applied 1 mA tDCS first, followed by 2 mA tDCS. A 20-minute stimulation duration of 1 mA tDCS is strong enough to produce after-effects that could influence the brain state during the 2 mA tDCS. This raises some concerns. Previous studies have shown that 1 mA tDCS can generate EF of over 1 V/m in the brain, and the effects of stimulation are sensitive to brain state (e.g., eye closed vs. eye open). How do the authors ensure that there are no after-effects from the 1 mA tDCS? This issue makes it challenging to directly compare the effects of 1 mA and 2 mA stimulation.

We agree with the reviewer's comment that 1 mA tDCS may induce aftereffects, as has been observed in several human studies (e.g., (Jamil et al. 2017, 2020). Although the differences between the 1 mA post-stimulation and baseline conditions were not significant in our analyses, it's still possible that the stimulation produced some effects below the threshold of significance that may contribute, albeit weakly, to the changes observed during and after 2 mA stimulation. We have, therefore, amended the paper in line with the reviewer's comments.

Actions in the text: We have added the following text in the Result section: 

“While several human studies have reported that 1 mA transcranial stimulation induces aftereffects (e.g., (Jamil et al. 2017, 2020; Monte-Silva et al. 2010), the differences between the 1 mA post-stimulation and baseline conditions were not significant in our analyses. However, it is still possible that the 1 mA stimulation produced some effects below the threshold of significance that may contribute to the changes observed during and after the 2 mA stimulation.”

The occurrence rate of a specific structural-functional coupling pattern among random brain regions shows significant effects of tDCS. However, these results seem counterintuitive. It is generally understood that noninvasive brain stimulation tends to modulate functional connectivity rather than structural or structural-functional connectivity. How does the occurrence rate of structural-functional coupling patterns provide a more suitable measure of the effectiveness of tDCS than functional connectivity alone? I would recommend that the authors present the results based on functional connectivity itself. If there is no change in functional connectivity, the relevance of changes in structural-functional coupling might not translate into a meaningful alteration in brain function, making it unclear how significant this finding is without corresponding functional evidence.

First, of all, we would like to make it clear that the occurrence rate of patterns as a function of their SFC is not intended to be used or seen as a ‘better’ measure of the efficacy of tDCS. Instead, it is one aspect of the effects of tDCS on whole-brain functional cortical dynamics, obtained from refined measures (phase-coherences), that specifically addresses the coupling between structure and function. This type of analysis is further motivated by its increasing use in the literature due to its suspected relationship to wakefulness (e.g., (Barttfeld et al. 2015, Demertzi et al. 2019; Castro et al. 2023)). Also, in our analysis, the structure is kept constant: the connectivity matrix used to correlate the functional brain states is always the same (CoCoMac82). Thus, the influence of tDCS on the structure-function side can only be explained by modulating the functional aspects, as suggested by intuition and previous results.

Then, we agree with the reviewer that studying the functional changes induced by tDCS alone could be valuable. However, usual metrics used in FC analysis are usually done statistically: FC-states are either computed through averaging spatial correlations over time, then analyzed through graph-theoretical properties for instance (or by just directly computing the element-wise differences), or either by considering the properties of the different visited FC-states by computing spatial correlations over a sliding time-window, and then similar analysis can be done as previously explained. But these are static metrics, if the states visited are essentially the same (which is expected from non-invasive neuromodulations that haven’t already demonstrated strong and/or characteristic impact), but the dynamical process of visiting said states changes, one would see no difference in that regard. As such, in the case of resting-state fMRI, differences in FCs are hard to interpret given that between-sessions within-condition differences are usually found with some degree of variance for the respective conditions. Trying then to interpret between-condition differences is quite tricky in the case of subtle modulations of the system’s activity. On the other hand, more subtle differences can be captured by considering more detailed analysis, such as using phase-based methods like we did,  by incorporating some statistical learning component with regard to the dynamicity of the system (supervised learning for instance like we did followed by temporal & transition-based methodology), and by adding some dimensions along which one will be able to give some interpretation to the analysis.  In our case we were interested in characterizing resting-state differences between stimulation conditions, which have nuanced and subtle interactions with the biological system. 

As such, classical measures of differences between FC states are likely to not be refined and precise enough. In fact, we propose additional files investigating those classically used measures such as differences in average FC matrices, or changes in functional graph properties (like modularity, efficiency and density) of the visited FC states. These figures show that, for the first case, comparing region-to-region specific FCs provides very few statistically significant results. With respect to the second part, we show that virtually no differences are observed in the properties of the functional states visited. 

These results suggest, as expected, that the actual brain states visited across the different stimulation conditions are topologically quite similar, and that only very few region-specific pairwise functional connectivities are particularly modulated by specific tDCS montages while, on the other hand, the actual dynamical process dictating how the brain activity passes from one state to another is in fact being influenced as shown by the dynamical analysis presented in the main figures in a more apparent and meaningful way (in that it is dependent on the montage, somewhat consistent with regard to the post-stimulations conditions, and can be made sense of by considering the theoretical effect of near-anodal versus near-cathodal neuromodulatory effects).

Actions in the text: We have added new supplementary files showing the effects of the stimulations on FC matrices and on classical functional graph properties in awake and anesthesia datasets (Supplementary Files 3 & 4).

We have added new sentences about these new analyses on the effects of the stimulations on FC matrices and on classical functional graph properties in the Results section:

“In addition, we performed the main analyses separately for the two monkeys, explored the inter-condition variability (Supplementary File 2), and computed classical measures of functional connectivity such as average FC matrices and functional graph properties (modularity, efficiency and density) of the visited FC states (Supplementary File 3).... In contrast, classical FC metrics did not show significant differences across stimulation conditions, highlighting the value of dynamic FC metrics to capture the neuromodulatory effects of tDCS.”

“Analyses of the two monkeys separately showed that the changes in slope and Shannon entropy were bigger in one of the two monkeys but went in the same direction (Supplementary File 2), while classical FC metrics did not capture any statistical differences between the different stimulation conditions (Supplementary File 3).”

The authors recorded data from only two monkeys, which may limit the investigation of the group effects of tDCS. As the number of scans for the second monkey in each consciousness condition is lower than that in the first monkey, there is a concern that the main effects might primarily reflect the data from a single monkey. I suggest that the authors should analyze the data for each monkey individually to determine if similar trends are observed in both subjects.

We agree that the small number of subjects is a limitation of our study. However, we have already addressed these aspects by reporting statistical analyses that consider them, using linear models of such variables, and running them through ANOVA tests. In addition, we experimentally ensured that we recorded a relatively high number of sessions over a period of several years. Regardless, we agree that our study would benefit from further investigation into this matter. We have therefore prepared complementary figures showing the main analysis performed separately for the two monkeys as proposed, as well as further investigations into the inter-condition variability outmatching the inter-individual variability, itself being also outmatched by intra-individual changes. 

Actions in the text: We have added a supplementary file showing the main analyses performed separately for the two monkeys (Supplementary File 2) and further investigations into the inter-condition variability (Supplementary Files 3 & 4).

We have added new sentences about these analyses performed separately for the two monkeys in the Results section:

“In addition, we performed the main analyses separately for the two monkeys, explored the inter-condition variability (Supplementary File 2), and computed classical measures of functional connectivity such as average FC matrices and functional graph properties (modularity, efficiency and density) of the visited FC states (Supplementary File 3). The separate analyses showed that the changes in slope and Shannon entropy were substantially more pronounced in one of the two monkeys, corroborating some of the effects captured in the ANOVA tests.”

“Analyses of the two monkeys separately showed that the changes in slope and Shannon entropy were bigger in one of the two monkeys but went in the same direction (Supplementary

File 2)”.

Anodal tDCS was only applied to anesthetized monkeys, which limits the conclusion that the authors are aiming for. It raises questions about the conclusion regarding brain state dependency. To address this, it would be better to include the cathodal tDCS session for anesthetized monkeys. If cathodal tDCS changes the connectivity during anesthesia, it becomes difficult to argue that the effects of cathodal tDCS vary depending on the state of consciousness as discussed in this paper. On the other hand, if cathodal tDCS would not produce any changes, the conclusion would then focus on the relationship between the polarity of tDCS and consciousness. In that case, the authors could maintain their conclusion but might need to refine it to reflect this specific relationship more accurately. 

We agree with the reviewer that it would have been interesting to investigate the effects of cathodal tDCS in anesthetized monkeys. However, due to the challenging nature of the experimental procedures under anesthesia, we had to limit the investigations to only one stimulation modality. We chose to deliver anodal stimulation because, from a translational point of view, we aimed to provide new information on the effects of tDCS under anesthesia as a model for disorders of consciousness. It also made much more sense to increase the cortical excitability of the prefrontal cortex in an attempt to wake up the sedated monkeys rather than doing the opposite.

Actions in the text: We have added a new sentence in the Results section:

“Due to the challenging nature of the experimental procedures under anesthesia, we limited the investigations to only one stimulation modality. We chose to deliver anodal stimulation to provide new information on the effects of tDCS under anesthesia as a model for disorders of consciousness and to increase the cortical excitability of the PFC in an attempt to wake up the sedated monkeys.”

Reviewer #3 (Public review): 

Summary: 

This study used transcranial direct current stimulation administered using small 'high-definition' electrodes to modulate neural activity within the non-human primate prefrontal cortex during both wakefulness and anaesthesia. Functional magnetic resonance imaging (fMRI) was used to assess the neuromodulatory effects of stimulation. The authors report on the modification of brain dynamics during and following anodal and cathodal stimulation during wakefulness and following anodal stimulation at two intensities (1 mA, 2 mA) during anaesthesia. This study provides some possible support that prefrontal direct current stimulation can alter neural activity patterns across wakefulness and sedation in monkeys. However, the reported findings need to be considered carefully against several important methodological limitations. 

Strengths: 

A key strength of this work is the use of fMRI-based methods to track changes in brain activity with good spatial precision. Another strength is the exploration of stimulation effects across wakefulness and sedation, which has the potential to provide novel information on the impact of electrical stimulation across states of consciousness.

We thank the Reviewer for the summary and for highlighting the strengths of our study. 

Weaknesses: 

The lack of a sham stimulation condition is a significant limitation, for instance, how can the authors be sure that results were not affected by drowsiness or fatigue as a result of the experimental procedure?

We agree with the reviewer that adding control conditions could have strengthened our study. Control conditions usually consist of a sham condition or active control conditions. However, as mentioned in response to one of Reviewer 2 comments (R.2.5), we had to make choices as we could not perform as many experiments due to their demanding nature, especially under anesthesia. 

In the awake state, we acquired data with two experimental conditions; the monkeys were exposed to either anodal (F4/O1) or cathodal (O1/F4) PFC tDCS. As anodal tDCS of the PFC induced only minor changes in brain dynamics, it could be considered as an active control condition for the cathodal condition, which had striking effects on the cortical dynamics. It is also worth noting that doubts have been raised about the neurobiological inertia of certain sham protocols. Indeed, different sham protocols have been employed in the literature, some of which may produce unintended effects (Fonteneau et al. 2019). Therefore, active control conditions, such as reversing the polarity of the stimulation or targeting a different brain region, have been proposed to provide better control (Fonteneau et al. 2019). Furthermore, in the context of experiments performed under anesthesia, the relevance of a sham control condition typically used to achieve adequate blinding is questionable. 

With regard to drowsiness and fatigue as a result of the experimental procedure, we agree with the reviewer that this is a common problem in functional imaging due to the length of the recording sessions. We assumed, as was done in previous work (Uhrig, Dehaene, and Jarraya 2014; Wang et al. 2015), that the monkeys' performance on the fixation task during acquisition would capture these periods of fatigue. Therefore, only sessions with fixation rates above 85% were included in our analysis. 

Actions in the text: We have now specified, in the Materials and Methods section, the fact that only runs with a high fixation rate (> 85%) were included in the study: 

“To ensure that the results were not biased by fatigue or drowsiness due to the lengthy

In the anaesthesia condition, the authors investigated the effects of two intensities of stimulation (1 mA and 2 mA). However, a potential confound here relates to the possibility that the initial 1 mA stimulation block might have caused plasticity-related changes in neural activity that could have interfered with the following 2 mA block due to the lack of a sufficient wash-out period. Hence, I am not sure any findings from the 2 mA block can really be interpreted as completely separate from the initial 1 mA stimulation period, given that they were administered consecutively. Several previous studies have shown that same-day repeated tDCS stimulation blocks can influence the effects of neuromodulation (e.g., Bastani and Jaberzadeh, 2014, Clin Neurophysiol; Monte-Silva et al., J. Neurophysiology). 

We agree with the reviewer’s comment that the initial 1 mA stimulation block might have induced changes in neural activity and that the 20-minute post 1 mA block would not be long enough to wash out these changes. This comment is very similar to the second comment made by Reviewer 2 (R.2.2). Although our experimental data do not support this possibility (as the differences between the 1 mA post-stimulation and baseline conditions were not significant), it is still conceivable that the stimulation produced some effects below the threshold of significance and that these might weakly contribute to the changes observed during and after the 2 mA stimulation. 

Actions in the text: We have modified the paper according to the reviewers' comments (please see our answer and actions in the text to R.2.2.).

The different electrode placement for the two anaesthetised monkeys (i.e., Monkey R: F3/O2 montage, Monkey N: F4/O1 montage) is problematic, as it is likely to have resulted in stimulation over different brain regions. The authors state that "Because of the small size of the monkey's head, we expected that tDCS stimulation with these two symmetrical montages would result in nearly equivalent electric fields across the monkey's head and produce roughly similar effects on brain activity"; however, I am not totally convinced of this, and it really would need E-field models to confirm. It is also more likely that there would in fact be notable differences in the brain regions stimulated as the authors used HD-tDCS electrodes, which are generally more focal.

We thank the Reviewer for the remark, which is very similar to the second comment from Reviewer 2. Please see our answer to the first comment of Reviewer 2 

Actions in the text: We have modified the paper according to the reviewers' comments (please see the actions taken in response to R.2.1.).