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  1. Jan 2025
    1. This two credit hour class = 2 hours per week in the classroom (if it did meet face-to-face)2. The time spent outside of the classroom for this class, then, would be an additional 4-6hours (remember 2-3 hours for every hour spent in class).3. So total time spent on this classper week = 6-8 hoursper day = about 1 hour4. I ask that you not get frustrated, work hard over the next 8 weeks, communicate with usoften, manage your time, and do your best work

      shows myself what i have to do to have the best chances of passing the class.

    1. Course Goals1. Address what stress is, the stress response, and how to manage stress.2. Examine the connection between the mind and the body.3. Explore the impact of nutrition on health and wellness.4. Examine factors that lead to addictive behavior.5. Investigate the importance of each of the health-related fitness components and identify waysto improve each component.6. Examine how to develop a comprehensive personal fitness program.

      Is this class related to psychology?

    1. How much time should be spent on this course?: The recommended ratio of time spent in class totime spent outside of class is as follows: for every hour spent in the classroom, an additional 2-3 hoursper week outside of the classroom should be spent on that same class. This class meets 2 hours perweek in class. As such, the guideline is an additional 4-6 hours should be spent outside of class onthis same course

      This is helpful because it explains how much time you should spend on this class—about 4-6 hours a week outside of class. This is helpful because I will need to do the same in my other classes. Being a student is challenging but that is what it takes to become a successful college student.

  2. notebooksharing.space notebooksharing.space
    1. # Your answers here tp_month_mean=ds.tp.groupby('time.month').mean(dim='time') tp_month_mean=tp_month_mean*1000 #plot levels = [0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40] cmap = 'YlGnBu' # Plot the map for January (month = 1) and August (month = 8) fig, axes = plt.subplots(1, 2, figsize=(14, 6)) january_precip = tp_month_mean.sel(month=1) august_precip = tp_month_mean.sel(month=8) # January Plot january_precip.plot.contourf(ax=axes[0], levels=levels, cmap=cmap, extend='max') axes[0].set_title('Average Daily Precipitation - January') # August Plot august_precip.plot.contourf(ax=axes[1], levels=levels, cmap=cmap, extend='max') axes[1].set_title('Average Daily Precipitation - August') # Adjust layout and show the plots plt.tight_layout() plt.show()

      Ok, this looks a bit like art ;-) , but it is unfortunately very difficult to analyse these figures. What is missing? Robinson projection, coastlines and gridlines. Colorbar labels would also be great. The levels are, howver, correctly represented.

    1. # computing the average daily precipitation for each month of the year avg_pt = ds_tp.tp.groupby('time.month').mean(dim='time') #print(avg_pt) avg_pt_mm= avg_pt*1000 # converting the m/day scale to mm/day #print(avg_pt_mm) # January selection levels= np.array([0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40]) avg_pt_mm_Jan= avg_pt_mm.sel(month=1) # January plot ax= plt.axes(projection= ccrs.Robinson()) avg_pt_mm_Jan.plot.contourf(ax=ax, transform= ccrs.PlateCarree(), levels=levels, cmap= 'YlGnBu', extend='max',cbar_kwargs={'label':'Precipitation [mm/day]','ticks':levels}) ax.coastlines(); ax.gridlines(); ax.set_title('January average precipitation, ERA5 1979-2018');

      Nicely done!

    1. ### Exercise 2.2: # Defining levels and colormap: levels = [0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40] colormap = "YlGnBu" # Creating a figure with 2 subplots: fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(16,9), subplot_kw={'projection': ccrs.Robinson()}) im1 = monthly_avg_pre.sel(month=1).plot(ax=ax1, transform=ccrs.PlateCarree(), cmap=colormap, vmin=0, vmax=40, levels=levels, add_colorbar=False) ax1.coastlines() ax1.gridlines() ax1.set_title("January") im2 = monthly_avg_pre.sel(month=8).plot(ax=ax2, transform=ccrs.PlateCarree(), cmap=colormap, vmin=0, vmax=40, levels=levels, add_colorbar=False) ax2.coastlines() ax2.gridlines() ax2.set_title("August") # Adding a shared colorbar and a title to the plot: cbar = fig.colorbar( im1, ax=[ax1, ax2], orientation='vertical', fraction=0.02, # Adjusting width of the colorbar pad=0.03, # Adjusting the space between colorbar and plots label='Average Daily Precipitation [mm/d]') fig.suptitle("Monthly Average Precipitation (ERA5 1979-2018)", x=0.7, size=12) plt.show()

      Looks great! Though I would prefer mm day-1 (instead of mm/d). But this is a detail. The legend that is shared for both subplots is nicely visualised!

    1. # Compute the monthly climatology (average precipitation for each month) precip_monthly_mean = tp_mm.groupby('time.month').mean() # Define the color levels and colormap levels = [0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40] cmap = 'YlGnBu' # Create a figure with two subplots (January and August) fig, axes = plt.subplots(1, 2, subplot_kw={'projection': ccrs.Robinson()}, figsize=(14, 6)) # January precipitation map ax = axes[0] january_precip = precip_monthly_mean.sel(month=1) im1 = january_precip.plot.contourf( ax=ax, transform=ccrs.PlateCarree(), levels=levels, cmap=cmap, cbar_kwargs={'shrink': 0.6, 'label': 'Precipitation (mm/day)'} ) ax.coastlines() ax.set_title('Average Daily Precipitation - January') # August precipitation map ax = axes[1] august_precip = precip_monthly_mean.sel(month=8) im2 = august_precip.plot.contourf( ax=ax, transform=ccrs.PlateCarree(), levels=levels, cmap=cmap, cbar_kwargs={'shrink': 0.6, 'label': 'Precipitation (mm/day)'} ) ax.coastlines() ax.set_title('Average Daily Precipitation - August') # Add a title for the whole figure plt.suptitle('Monthly Average Daily Precipitation (mm/day)', fontsize=16) # Adjust spacing plt.tight_layout() plt.show()

      Looks great! Just one small detail is missing, the gridlines. This helps to later interpret the location of the ITCZ compared to the equator. You can add for that: ax.gridlines()

    2. # Compute the monthly climatology (average temperature for each month) T_monthly_mean = t2m_c.groupby('time.month').mean() # Plot the monthly average temperature maps fig, axes = plt.subplots(3, 4, subplot_kw={'projection': ccrs.Robinson()}, figsize=(15, 10)) # Loop over the 12 months and plot each month's mean temperature for i, ax in enumerate(axes.flat): # Select the temperature for month i+1 month_data = T_monthly_mean.isel(month=i) # Plot the 2D data im = month_data.plot.pcolormesh( ax=ax, transform=ccrs.PlateCarree(), cmap='coolwarm', add_colorbar=False ) ax.coastlines() ax.set_title(f'Month {i+1}') # Add a single vertical colorbar on the right-hand side cbar_ax = fig.add_axes([0.92, 0.15, 0.02, 0.7]) # [left, bottom, width, height] fig.colorbar(im, cax=cbar_ax, orientation='vertical', label='Temperature (°C)') # Adjust spacing between subplots plt.subplots_adjust(hspace=0.3, wspace=0.05, top=0.9, bottom=0.1, right=0.9) # Add a title and show the figure plt.suptitle('Monthly Average Temperature (°C)', fontsize=16) plt.show()

      Great way to show the entire monthly average temperature time series. ;-)

  3. notebooksharing.space notebooksharing.space
    1. # Your answers here # Konvertiere die Einheiten (m pro Tag -> mm pro Tag) precipitation = ds['tp'] * 1000 # Konvertiere von Meter auf Millimeter (1m = 1000mm) # Berechne den durchschnittlichen Niederschlag pro Monat monthly_precipitation = precipitation.groupby('time.month').mean(dim='time') # Monate Januar (1) und August (8) months = [1, 8] # Setze das Colormap für die Karte cmap = 'YlGnBu' # Levels für die Farbabstufung levels = [0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40] # Erstelle die Plots für Januar und August untereinander, mit der Robinson-Projektion fig, axs = plt.subplots(2, 1, figsize=(10, 12), subplot_kw={'projection': ccrs.Robinson()}) for i, month in enumerate(months): # Wähle die Achse für den jeweiligen Plot ax = axs[i] # Erstelle die Karte für den entsprechenden Monat data = monthly_precipitation.sel(month=month) # Plot der Niederschlagskarte data.plot(ax=ax, transform=ccrs.PlateCarree(), cmap=cmap, levels=levels, cbar_kwargs={'label': 'Precipitation (mm/day)'}) # Füge Küstenlinien und Gitterlinien hinzu ax.coastlines() ax.gridlines(draw_labels=True, linewidth=0.5, color='gray', linestyle='--') # Setze den Titel je nach Monat ax.set_title(f'Average Daily Precipitation in {["January", "August"][i]}') # Zeige die Plots plt.tight_layout() plt.show()

      Looks good! ;-)

  4. notebooksharing.space notebooksharing.space
    1. avg_daily_tp_mm = ds.tp.groupby('time.month').mean() * 1000 J_avg_daily_tp_mm = avg_daily_tp_mm.sel(month=1) A_avg_daily_tp_mm = avg_daily_tp_mm.sel(month=8) fig, (ax1, ax2) = plt.subplots(ncols=2, subplot_kw={'projection': ccrs.Robinson()}) # January J_avg_daily_tp_mm.plot(ax=ax1, transform=ccrs.PlateCarree(), cmap='YlGnBu', levels=[0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40], cbar_kwargs={'label': 'mm per day'}) # August A_avg_daily_tp_mm.plot(ax=ax2, transform=ccrs.PlateCarree(), cmap='YlGnBu', levels=[0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40], cbar_kwargs={'label': 'mm per day'}) ax1.set_title('Average Daily Precipitation in January, ERA5 1979-2018');ax1.coastlines();ax1.gridlines() ax2.set_title('Average Daily Precipitation in August, ERA5 1979-2018');ax2.coastlines();ax2.gridlines() plt.tight_layout() plt.show()

      Great labels and titles. Nice way to show the subplots side by side. If you adapt the figure size, you could make the colorbar legend look less big (though this is a detail).

    1. In [9]: # Plot fig, axes = plt.subplots(2, 1, figsize=(12, 10), subplot_kw={'projection': ccrs.PlateCarree()}) # January ax1 = axes[0] monthly_avg_precip.sel(month=1).plot.contourf(ax=ax1, levels=[0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40], cmap='YlGnBu') # August ax2 = axes[1] monthly_avg_precip.sel(month=8).plot.contourf(ax=ax2, levels=[0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40], cmap='YlGnBu') #set title ax1.set_title('2.1: Mean average precipitation per day in January (mm/day)') ax1.coastlines() ax2.set_title('2.2: Mean average precipitation per day in August (mm/day)') ax2.coastlines() plt.show()

      Great label units and titles! Levels are also correctly shown. Though I would prefer "precipitation" over "tp" ;-)

      gridlines and the Robinson projection are missing (same as in the figures above). Here, specifically the gridlines would be helpful to see how far north or south the equator the ITCZ lies...

      Potential solution for the code: prcp_cycle = ds.tp.groupby('time.month').mean() * 1000 pm = prcp_cycle.sel(month=1) ax = plt.axes(projection=ccrs.Robinson()) pm.plot(ax=ax, transform=ccrs.PlateCarree(), cbar_kwargs={'label':'precipitation (mm day$^{-1}$)'}, levels=[0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40], cmap='YlGnBu') ax.set_title('$\overline{P_{Jan}}$') ax.coastlines(); ax.gridlines();

    1. ### plotting for January ax = plt.axes(projection=ccrs.Robinson()) p_m.sel(month=1).plot(ax=ax, transform=ccrs.PlateCarree(), cmap='YlGnBu', levels=[0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40], cbar_kwargs={'label': 'mm per day'}) ax.coastlines(); ax.gridlines(); ax.set_title('Average daily precipitation in January');

      Great ;-)

    1. levels= [0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40] fig, axes = plt.subplots(2, 1, figsize=(15, 10), subplot_kw={'projection': ccrs.Robinson()}) fig.suptitle('Average Daily Precipitation \n',fontsize=15, fontweight='bold') # January jan = pre_mthly_mm.sel(month=1) jan.plot(ax=axes[0], cmap='YlGnBu', transform=ccrs.PlateCarree(),cbar_kwargs={'label': 'Precipitation(mm)'}) axes[0].coastlines(); axes[0].gridlines() axes[0].set_title('January') #August aug= pre_mthly_mm.sel(month=8) aug.plot(ax=axes[1],cmap='YlGnBu', transform=ccrs.PlateCarree(), cbar_kwargs={'label':'Precipitation(mm)'}) axes[1].coastlines(); axes[1].gridlines() axes[1].set_title('August');

      you define the levels as requested, but you do not use them to plot the figure. The diferences are better visible when actually showing distinct levels as requested.

      Example code: prcp_cycle = ds.tp.groupby('time.month').mean() * 1000 pm = prcp_cycle.sel(month=1) ax = plt.axes(projection=ccrs.Robinson()) pm.plot(ax=ax, transform=ccrs.PlateCarree(), cbar_kwargs={'label':'precipitation (mm day$^{-1}$)'}, levels=[0.5, 1, 2, 3, 4, 5, 7, 10, 15, 20, 40], cmap='YlGnBu') ax.set_title('$\overline{P_{Jan}}$') ax.coastlines(); ax.gridlines();

      In addition, precipitation unit is "mm per day" ( not just mm as you labelled it)

    1. The fact that these visual cues are missing in e-mail, text, and phone interactions presents some difficulties for reading contextual clues into meaning received through only auditory channels.

      Activity idea: 1) Have students get into pairs. One student should face the front of the room, the other should face the back. 2) Put an image on the screen at the front of the room. 3) Instruct the person facing the screen to describe what they see to the person facing away. The person facing away should draw what they hear. 4) Instruct the person drawing not to look at the screen, ask questions, or offer any verbal or nonverbal feedback. 5) At the end, the person drawing may reveal what they drew and see how closely it matches with the image on the screen.

      This activity demonstrates the impact that visual, verbal, and non-verbal cues have on the communication process.

      Follow-Up Questions: 1) What elements of the communication process were missing? How did this affect understanding? 2) How can miscommunication occur, even when we are doing our best to actively listen?

    1. Author response:

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

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      The use of antalarmin, a selective CRF1 receptor antagonist, prevents the deficits in sociability in (acutely) morphine-treated males, but not in females. In addition, cell-attached experiments show a rescue to control levels of the morphine-induced increased firing in PVN neurons from morphine-treated males. Similar results are obtained in CRF receptor 1-/- male mice, confirming the involvement of CRF receptor 1-mediated signaling in both sociability deficits and neuronal firing changes in morphine-treated male mice.

      Strengths:

      The experiments and analyses appear to be performed to a high standard, and the manuscript is well written and the data clearly presented. The main finding, that CRF-receptor plays a role in sociability deficits occurring after acute morphine administration, is an important contribution to the field.

      Weaknesses:

      The link between the effect of pharmacological and genetic modulation of CRF 1 receptor on sociability and on PVN neuronal firing, is less well supported by the data presented. No evidence of causality is provided.

      Major points:

      (1) The results of behavioral tests and the neural substrate are purely correlative. To find causality would be important to selectively delete or re-express CRF1 receptor sequence in the VPN. Re-expressing the CRF1 receptor in the VPN of male mice and testing them for social behavior and for neuronal firing would be the easier step in this direction.

      We agree with this comment and have acknowledged that further studies, such as genetic or pharmacological inactivation of CRF<sub>1</sub> receptors selectively in the paraventricular nucleus of the hypothalamus (PVN), are warranted to address this issue (page 17, line 25 to page 18, line 1).

      We would also like to mention that our manuscript title intentionally presented our findings separately without implying causality. Our idea was simply to pair the behavioral data to neural activity within a network of interest, i.e., the PVN CRF-oxytocin (OXY)/arginine-vasopressin (AVP) network, which is thought to play a critical role at the interface of substance use disorders and social behavior. Accordingly, we previously reported that genetic CRF<sub>2</sub> receptor deficiency reliably eliminated sociability deficits and hypothalamic OXY and AVP expression induced by cocaine withdrawal (Morisot et al., 2018). Thus, the present manuscript reliably shows that CRF<sub>1</sub> receptor-mediated effects of acute morphine administration upon social behavior are consistently mirrored by neural activity changes within the PVN, and particularly within its OXY<sup>+</sup>/AVP<sup>+</sup> neuronal populations. In addition, we demonstrate that the latter effects are sex-linked, which is in line with previous reports of sex-biased CRF<sub>1</sub> receptor roles in rodents (Rosinger et al., 2019; Valentino et al., 2013) and humans (Roy et al., 2018; Weber et al., 2016).

      (2) It would be interesting to discuss the relationship between morphine dose and CRF1 receptor expression.

      We are not aware of studies reporting CRF<sub>1</sub> receptor expression following acute morphine administration. However, repeated heroin self-administration was shown to increase CRF<sub>1</sub> receptor expression in the ventral tegmental area (VTA). We have mentioned the latter study in the present revised version of our manuscript at page 18, lines 1-2.

      (3) It would be important to show the expression levels of CRF1 receptors in PVN neurons in controls and morphine-treated mice, both males and females.

      We agree with this reviewer comment and, in the present version of the manuscript, have mentioned that examination of CRF<sub>1</sub> receptor expression in the PVN might help to understand the brain mechanisms underlying morphine effects upon social behavior (page 18, lines 2-6). Moreover, at page 15, lines 11-19 we have mentioned studies showing higher levels of the CRF<sub>1</sub> receptor in the PVN of adult (2 months) and old (20-24 months) male mice, as compared to adult and old female mice (Rosinger et al., 2019). Thus, differences in PVN CRF<sub>1</sub> receptor expression between male and female mice might underlie the sex-linked effects of CRF<sub>1</sub> receptor antagonism by antalarmin reported in our manuscript.

      (4) It would be important to discuss the mechanisms by which CRF1 receptor controls the firing frequency of APV+/OXY+ neurons in the VPN of male mice.

      Using the in situ hybridization technique, studies reported relatively low expression of the CRF<sub>1</sub> receptor in the PVN (Van Pett et al., 2000). However, more recent studies using genetic approaches identified a substantial population of CRF<sub>1</sub> receptor-expressing neurons within the PVN (Jiang et al., 2019, 2018). These CRF<sub>1</sub> receptor-expressing neurons are believed to respond to local CRF release and likely form bidirectional connections with both CRF and OXY+/AVP+ neurons (Jiang et al., 2019, 2018). Thus, one proposed mechanism of action is that morphine increases intra-PVN release of CRF, which may act on intra-PVN CRF<sub>1</sub> receptor-expressing neurons. The latter neurons might in turn influence the activity of PVN OXY+/AVP+ neurons, which largely project to the VTA and the bed nucleus of the stria terminalis (BNST) to modulate social behavior. Within this framework, pharmacological or genetic inactivation of CRF<sub>1</sub> receptors might deregulate the activity of intra-PVN CRF-OXY/AVP interactions and thus interfere with opiate-induced social behavior deficits. In particular, the latter phenomenon might be more pronounced in male mice since they express more CRF<sub>1</sub> receptor-positive neurons in the PVN, as compared to female mice (Rosinger et al., 2019). The putative mechanisms of action described herein are also mentioned at page 16, lines 12 to page 17, line 7 of the present revised version of the manuscript.

      Minor points:

      (1) The phase of the estrous cycles in which females are analyzed for both behavior and electrophysiology should be stated.

      The normal estrous cycle of laboratory mice is 4-5 days in length, and it is divided into four phases (proestrus, estrus, metestrus and diestrus). The three-chamber experiments were generally carried out over a 5-day period, thus spanning across the entire estrous cycle. In particular, on each test day approximately the same number of mice was assigned to each experimental group. Thus, within each group the number of female mice tested on each phase of the estrous cycle was likely similar. Moreover, except for firing frequency displayed by vehicle/morphine-treated mice, female and male mice showed similar results variability, indicating a marginal role for the estrous cycle in the spread of data. We would also like to mention relatively recent studies indicating no significant difference over different phases of the estrous cycle in the social interaction test as well as in anxiety-like and anhedonia-like behavioral tests in C57BL/6J female mice (Zhao et al., 2021). Accordingly, similar findings were also reported by other authors who found no difference across the diestrus and estrus phases of the estrous cycle in C57BL/6J female mice tested in behavioral assays of anxiety-like, depression-like and social interaction (Zeng et al., 2023).

      A paragraph has been added to page 20, lines 1-9 of the present version of the manuscript to explain why we did not monitor the estrous cycle in female mice.

      (2) It would be important to show the statistical analysis between sexes.

      Following this reviewer comment, we examined the sociability ratio results by a three-way ANOVA with sex (males vs. females), pretreatment (vehicle vs. antalarmin) and treatment (saline vs. morphine) as between-subjects factors. The latter analysis revealed an almost significant sex X pretreatment X treatment interaction effect (F<sub>1,53</sub>=3.287, P=0.075), which could not allow for post-hoc individual group comparisons. Nevertheless, Newman-Keuls post-hoc comparisons revealed that male mice treated with antalarmin/morphine showed higher sociability ratio than female mice treated with antalarmin/morphine (P<0.05). The latter statistical results have been added to the present revised version of the manuscript at page 7, lines 2-8.

      We also examined neuronal firing frequency by a three-way ANOVA with sex (males vs. females), pretreatment (vehicle vs. antalarmin) and treatment (saline vs. morphine) as between-subjects factors. Analysis of firing frequency of all of the recorded cells in C57BL/6J mice revealed a sex X pretreatment X treatment interaction effect (F<sub>1,195</sub>=4.765, P<0.05). Newman-Keuls post-hoc individual group comparisons revealed that male mice treated with vehicle/morphine showed higher firing frequency than all other male and female groups (P<0.0005). Moreover, male mice treated with antalarmin/morphine showed lower firing frequency than male mice treated with vehicle/morphine (P<0.0005). In net contrast, female mice treated with antalarmin/morphine did not differ from female mice treated with vehicle/morphine (P=0.914). The latter statistical results have been added to the present revised version of the manuscript at page 8, lines 4-12. Finally, similar results were obtained following the three-way ANOVA (sex X pretreatment X treatment) of firing frequency recorded in the subset of neurons co-expressing OXY and AVP (data not shown).

      Thus, sex-linked responses to morphine were detected also by three-way ANOVAs including sex as a variable. However, in the revised version of the manuscript we did not include novel figures combining the two sexes because it would have been largely redundant with the figures already reported, especially with Fig. 1D, Fig. 1G, Fig. 2B and Fig. 2D.

      Reviewer #2 (Public review):

      This manuscript reports a series of studies that sought to identify a biological basis for morphine-induced social deficits. This goal has important translational implications and is, at present, incompletely understood in the field. The extant literature points to changes in periventricular CRF and oxytocin neurons as critical substrates for morphine to alter social behavior. The experiments utilize mice, administered morphine prior to a sociability assay. Both male and female mice show reduced sociability in this procedure. Pretreatment with the CRF1 receptor antagonist, antalarmin, clearly abolished the morphine effect in males, and the data are compelling. Consistently, CRF1-/- male mice appeared to be spared of the effect of morphine (while wild-type and het mice had reduced sociability). The same experiment was reported as non-feasible in females due to the effect of dose on exploratory behavior per se. Seeking a neural correlate of the behavioral pharmacology, acute cell-attached recordings of PVN neurons were made in acute slices from mice pretreated with morphine or anatalarmin. Morphine increased firing frequencies, and both antalarmin and CRF1-/- mice were spared of this effect. Increasing confidence that this is a CRF1 mediated effect, there is a gene deletion dose effect where het's had an intermediate response to morphine. In general, these experiments are well-designed and sufficiently powered to support the authors' inferences. A final experiment repeated the cell-attached recordings with later immunohistochemical verification of the recorded cells as oxytocin or vasopressin positive. Here the data are more nuanced. The majority of sampled cells were positive for both oxytocin and vasopressin, in cells obtained from males, morphine pretreatment increased firing in this population and was CRF1 dependent, however in females the effect of morphine was more modest without sensitivity to CRF1. Given that only ~8 cells were only immunoreactive for oxytocin, it may be premature to attribute the changes in behavior and physiology strictly to oxytocinergic neurons.

      In sum, the data provide convincing behavioral pharmacological evidence and a regional (and possibly cellular) correlation of these effects suggesting that morphine leads to sociality deficits via CRF interacting with oxytocin in the hypothalamus. While this hypothesis remains plausible, the current data do not go so far as directly testing this mechanism in a site or cell-specific way.

      We agree with this reviewer’s comment and acknowledge that further studies are needed to better understand the neural substrates of CRF<sub>1</sub> receptor-mediated sociability deficits induced by morphine. This has been mentioned at page 17, line 25 to page 18, line 6 of the present revised version of the manuscript.

      With regard to the presentation of these data and their interpretation, the manuscript does not sufficiently draw a clear link between mu-opioid receptors, their action on CRF neurons of the PVN, and the synaptic connectivity to oxytocin neurons. Importantly, sex, cell, and site-specific variations in the CRF are well established (see Valentino & Bangasser) yet these are not reviewed nor are hypotheses regarding sex differences articulated at the outset. The manuscript would have more impact on the field if the implications of the sex-specific effects evident here were incorporated into a larger literature.

      At page 15, line 19 to page 16, line 2 of the present version of the manuscript, we have mentioned prior studies reporting differences in CRF<sub>1</sub> receptor signaling or cellular compartmentalization between male and female rodents (Bangasser et al., 2013, 2010). However, the latter studies were conducted in cortical or locus coeruleus brain tissues. Thus, more studies are needed to examine CRF<sub>1</sub> receptor signaling or cellular compartmentalization in the PVN and their relationship to the sex-linked results reported in our manuscript.

      With regards to the model proposed in the discussion, it seems that there is an assumption that ip morphine or antalarmin have specific effects on the PVN and that these mediate behavior - but this is impossible to assume and there are many meaningful alternatives (for example, both MOR and CRF modulation of the raphe or accumbens are worth exploration).

      We focused our discussion on PVN OXY/AVP systems because ourelectrophysiology studies examined neurons expressing OXY and/or AVP in this brain area. However, we understand that other brain areas/systems might mediate the effect of systemic administration of the CRF<sub>1</sub> receptor antagonist antalarmin or whole-body genetic disruption of the CRF<sub>1</sub> receptor upon morphine-induced social behavior deficits. For this reason, at page 16, line 12 to page 17, line 7 of the present version of the manuscript we have mentioned the possible involvement of BNST OXY or VTA dopamine systems in the CRF<sub>1</sub> receptor-mediated social behavior effects of morphine reported herein. Indeed, literature suggests important CRF-OXY and CRF-dopamine interactions in the BNST and the VTA, which might be relevant to the expression of social behavior. Nevertheless, to date the implication of the latter brain systems interactions in social behavior alterations induced by substances of abuse remains to be elucidated.

      While it is up to the authors to conduct additional studies, a demonstration that the physiology findings are in fact specific to the PVN would greatly increase confidence that the pharmacology is localized here. Similarly, direct infusion of antalarmin to the PVN, or cell-specific manipulation of OT neurons (OT-cre mice with inhibitory dreadds) combined with morphine pre-exposure would really tie the correlative data together for a strong mechanistic interpretation.

      We agree with this reviewer’s comment that the suggested experiments would greatly increase the understanding of the brain mechanisms underlying the social behavior deficits induced by opiate substances. We have acknowledged this at page 17, line 25 to page 18, line 6.

      Because the work is framed as informing a clinical problem, the discussion might have increased impact if the authors describe how the acute effects of CRF1 antagonists and morphine might change as a result of repeated use or withdrawal.

      Prior studies reported behavioral and neuroendocrine (hypothalamus-pituitary-adrenal axis) effects of chronic systemic administration of CRF<sub>1</sub> receptor antagonists, such as R121919 and antalarmin (Ayala et al., 2004; Dong et al., 2018). However, to our knowledge, no studies have directly compared the behavioral effects of acute vs. repeated administration of CRF<sub>1</sub> receptor antagonists. We previously reported that acute administration of antalarmin increased the expression of somatic opiate withdrawal in mice, indicating that this compound is effective following withdrawal from repeated morphine administration (Papaleo et al., 2007). Nevertheless, further studies are needed to specifically address this reviewer’s comment.

      Reviewer #3 (Public review):

      Summary:

      In the current manuscript, Piccin et al. identify a role for CRF type 1 receptors in morphine-induced social deficits using a 3-chamber social interaction task in mice. They demonstrate that pre-treatment with a CRFR1 antagonist blocks morphine-induced social deficits in male, but not female, mice, and this is associated with the CRF R1 antagonist blocking morphine-induced increases in PVN neuronal excitability in male but not female mice. They followed up by using a transgenic mouse CRFR1 knockout mouse line. CRFR1 genetic deletion also blocked morphine-induced social deficits, similar to the pharmacological approach, in male mice. This was also associated with morphine-induced increases in PVN neuronal excitability being blocked in CRFR1 knockout mice. Interestingly they found that the pharmacological antagonism of the CRFR1 specifically blocked morphine-induced increases in oxytocin/AVP neurons in the PVN in male mice.

      Strengths:

      The authors used both male and female mice where possible and the studies were fairly well controlled. The authors provided sufficient methodological detail and detailed statistical information. They also examined measures of locomotion in all of the behavioral tasks to separate changes in sociability from overall changes in locomotion. The experiments were well thought out and well controlled. The use of both the pharmacological and genetic approaches provides converging lines of evidence for the role of CRFR1 in morphine-induced social deficits. Additionally, they have identified the PVN as a potential site of action for these CRFR1 effects.

      Weaknesses:

      While the authors included both sexes they analyzed them independently. This was done for simplicity's sake as they have multiple measures but there are several measures where the number of factors is reduced and the inclusion of sex as a factor would be possible.

      Please, see above our response to the same comment made by Reviewer 1.

      Additionally, single doses of both the CRFR1 antagonist and morphine are used within an experiment without justification for the doses. In fact, a lower dose of morphine was needed for the genetic CRFR1 mouse line. This would suggest that the dose of morphine being used is likely causing some aversion that may be more present in the females, as they have lower overall time in the ROI areas of both the object and the mouse following morphine exposure.

      The morphine dose was chosen based on our prior study showing that morphine (2.5 mg/kg) impaired sociability in male and female C57BL/6J mice, without affecting locomotor activity (Piccin et al., 2022). Also, the antalarmin dose (20 mg/kg) and the route of administration (per os) was chosen based on our prior studies demonstrating behavioral effects of this CRF<sub>1</sub> receptor antagonist administered per os (Contarino et al., 2017; Ingallinesi et al., 2012; Piccin and Contarino, 2020). This is now mentioned in the “materials and methods” section of the present revised version of the manuscript at page 23, lines 6-13. We also agree with this reviewer that female mice seemed more sensitive to morphine than male mice. Indeed, during the habituation phase of the three-chamber test female mice treated with morphine (2.5 mg/kg) spent less time in the ROIs containing the empty wire cages, as compared to saline-treated female mice (Fig. 1E). However, morphine did not affect locomotor activity in female mice (Fig. S1B), suggesting independency between social approach and ambulation.

      As for the discussion, the authors do not sufficiently address why CRFR1 has an effect in males but not females and what might be driving that difference, or why male and female mice have different distribution of PVN cell types during the recordings.

      At page 15, line 11 to page 16, line 2, we have mentioned possible mechanisms that might underlie the sex-linked results reported in our manuscript. Moreover, at page 16, lines 6-9 we have mentioned a seminal review reporting sex-linked expression of PVN OXY and AVP in a variety of animal species that is similar to the present results. Nevertheless, as mentioned in the “discussion” section, further studies are needed to elucidate the neural substrates underlying sex-linked effects of opiate substances upon social behavior.

      Additionally, the authors attribute their effect to CRF and CRFR1 within the PVN but do not consider the role of extrahypothalamic CRF and CRFR1. While the PVN does contain the largest density of CRF neurons there are other CRF neurons, notably in the central amygdala and BNST, that have been shown to play important roles in the impact of stress on drug-related behavior. This also holds true for the expression of CRFR1 in other regions of the brain, including the VTA, which is important for drug-related behavior and social behavior. The treatments used in the current manuscript were systemic or brain-wide deletion of CRFR1. Therefore, the authors should consider that the effects could be outside the PVN.

      Even if they suggest a role for PVN CRF<sub>1</sub>-OXY circuits, we are aware that the present data do not support a direct link between behavior and PVN CRF<sub>1</sub> receptors. Thus, at page 16, line 12 to page 17, line 7 of the present version of the manuscript we have mentioned some studies showing a role for PVN OXY, BNST OXY or VTA dopamine systems in social behavior. Interestingly, the latter brain systems are thought to interact with the CRF system. However, more studies are warranted to understand the implication of CRF-OXY or CRF-dopamine interactions in social behavior deficits induced by substances of abuse.

      Recommendations for the authors:

      Reviewer #2 (Recommendations for the authors):

      I commend the authors on crafting a well-written and clear manuscript with excellent figures. Furthermore, the data analysis and rigor are quite high. I have a few suggestions in the order they appear in the manuscript:

      The introduction has a number of abrupt transitions. For example, the sentence beginning with "Besides," in paragraph 2 jumps from CRF to oxytocin and vasopressin without a transition or justification. In all, vasopressin may be better removed from the introduction. There is sufficient evidence in the literature to support the CRF-OT circuit that might mediate behavioral pharmacology and this should be clearly described in the introduction.

      We have added a sentence at page 3, lines 22-23 to introduce possible interactions of the CRF system with other brain systems implicated in social behavior. Also, in the “introduction” section both OXY and AVP systems are mentioned because our electrophysiology studies examined the effect of morphine upon the activity of OXY- and AVP-positive neurons.

      Our interest in the PVN CRF-OXY/AVP network also stems from previous findings from our laboratory showing that genetic inactivation of the CRF<sub>2</sub> receptor eliminated both sociability deficits and increased hypothalamic OXY and AVP expression associated with long-term cocaine withdrawal in male mice (Morisot et al., 2018). Moreover, evidence suggests the implication of AVP systems in opiate effects. In particular, pharmacological antagonism of AVP-V1b receptors decreased the acquisition of morphine-induced conditioned place preference in male C57BL/6N mice housed with morphine-treated mice (Bates et al., 2018).

      Throughout the manuscript, it seems that there is an assumption that ip morphine or antalarmin have specific effects on the PVN and that these mediate behavior - this is impossible to assume and there are many meaningful alternatives (for example, both MOR and CRF modulation of the raphe or accumbens are worth exploration). While it is up to the authors to conduct additional studies, a demonstration that the physiology findings are in fact specific to the PVN would greatly increase confidence that the pharmacology is localized here. Similarly, direct infusion of antalarmin to the PVN, or cell-specific manipulation of OT neurons (OT-cre mice with inhibitory dreadds) combined with morphine pre-exposure would really tie the correlative data together for a strong mechanistic interpretation.

      We agree that the suggested experiments would greatly increase the understanding of the brain mechanisms underlying the social behavior deficits induced by opiate substances. This has been acknowledged at page 17, line 25 to page 18, line 6 of the present version of the manuscript.

      Also in the introduction, the reference to shank3b mice is not the most direct evidence of oxytocin involvement in sociability. It may be helpful to point reviewers to studies with direct manipulation of these populations (Grinevich group, for example).

      At page 4, lines 4-6 of the “introduction” section, we have added a sentence to mention a seminal paper by the Grinevich group demonstrating an important role for OXY-expressing PVN parvocellular neurons in social behavior (Tang et al., 2020). Moreover, at page 4, lines 8-10 we have mentioned a recent study showing that targeted chemogenetic silencing of PVN OXY neurons in male rats impaired short- and long-term social recognition memory (Thirtamara Rajamani et al., 2024).

      It would be helpful in the figures to indicate which panels contain male or female data.

      The sex of the mice is mentioned above each panel of the main and supplemental figures, except for the studies with CRF<sub>1</sub> receptor-deficient mice wherein only experiments carried out with male mice were illustrated. In the latter case, the sex (male) of the mice is mentioned in the related legend.

      The discussion itself departs from the central data in a few ways - the passages suggesting that morphine produces a stress response and that CRF1 antagonists would block the stress state are highly speculative (although testable). The manuscript would have more impact if the sex-specific effects and alternative hypotheses were enhanced in the discussion.

      At page 16, line 12 to page 17, line 7 of the “discussion” section, we have suggested that interaction of the CRF system with other brain systems implicated in social behavior (i.e., OXY, dopamine) might underlie the sex-linked CR<sub>1</sub> receptor-mediated effects of morphine reported in our manuscript. Also, at page 15, line 19 to page 16, line 2 we have mentioned studies showing sex-linked CRF<sub>1</sub> receptor signaling and cellular compartmentalization that might be relevant to the present findings. Finally, to further support the notion of morphine-induced PVN CRF activity, at page 15, lines 4-6 we have mentioned a study suggesting that activation of presynaptic mu-opioid receptors located on PVN GABA terminals might reduce GABA release (and related inhibitory effects) onto PVN CRF neurons (Wamsteeker Cusulin et al., 2013). Nevertheless, we believe that more work is needed to better understand the role for the CRF<sub>1</sub> receptor in opiate-induced stress responses and activity of OXY and dopamine systems implicated in social behavior.

      Reviewer #3 (Recommendations for the authors):

      (1) You should provide justification for the doses selected for treatments and the route of administration for the CRFR1 antagonist, especially for females.

      This has been added at page 23, lines 6-13 of the present version of the manuscript. In particular, the doses and routes of administration for morphine and antalarmin used in the present study were chosen based on previous work from our laboratory. Indeed, the intraperitoneal administration of morphine (2.5 mg/kg) impaired social behavior in male and female mice, without affecting locomotor activity (Piccin et al., 2022). Moreover, the oral route of administration for antalarmin was chosen for its translational relevance, as it could be easily employed in clinical trials assessing the therapeutic value of pharmacological CRF<sub>1</sub> receptor antagonists.

      (2) For the electrophysiology data you should include the number of cells per animal that were obtained. It appears that fewer cells from more females were obtained than in males and so the distribution of individual animals to the overall variance may be different between males and females.

      The number of cells examined and animals used in the electrophysiology experiments are reported above each panel of the related Figures 2, 3 and 4 as well as in the supplementary tables S1B and S1C. Overall, the number of cells examined in male and female mice was quite similar. Also, the number of male and female mice used was comparable. Standard errors of the mean (SEM) were quite similar across the different male and female groups (Fig. 2B and 2D), except for vehicle/morphine-treated male mice. Indeed, in the latter group a considerable number of cells displayed elevated firing responses to morphine, which accounted for the higher spread of the data. Accordingly, as mentioned above, the three-way ANOVA with sex (males vs. females), pretreatment (vehicle vs. antalarmin) and treatment (saline vs. morphine) as between-subjects factors revealed that male mice treated with vehicle/morphine showed higher firing frequency than all other male and female groups (P<0.0005). Finally, a similar pattern of firing frequency was observed also in neurons co-expressing OXY and AVP, wherein vehicle/morphine-treated male mice displayed higher SEM, as compared to all other male and female groups (Fig. 4C and 4F). Thus, except for vehicle/morphine-treated mice, distribution of the firing frequency data did not seem to be linked to the sex of the animal.

      (3) You should consider using a nested analysis for the slice electrophysiology data as that is more appropriate.

      We thank the reviewer for this suggestion. However, after careful consideration, we have decided to keep the current statistical analyses. In particular, given the relatively low variability of our data, we believe that the use of parametric ANOVA tests is appropriate. Moreover, additional details supporting our choice are provided just above in our response to the comment #2.

      (4) While it makes sense to not want to directly compare male and female data that results in needing to run a 4-way ANOVA, there are many measures, such as sociability, firing rate, etc., that if including sex as a factor would result in running a 3-way ANOVA and would allow for direct comparison of male and female mice.

      Please, see above our response to the same comment made by Reviewer 1. Notably, the results of our new statistical analyses including sex as a variable further support sex-linked effects of the CRF<sub>1</sub> receptor antagonist antalarmin upon morphine-induced sociability deficits and PVN neuronal firing. Nevertheless, we would like to keep the figures illustrating our findings as they are since it easily allows detecting the observed sex-linked results. Finally, we hope that this reviewer agrees with our choice, which is consistent with the wording of the title (i.e., “in male mice”).

      (5) There are grammatical and phrasing issues throughout the manuscript and the manuscript would benefit from additional thorough editing.

      We appreciate this reviewer’s feedback. Thus, upon revising, we have carefully edited the manuscript with regard to possible grammatical and phrasing errors. We hope that our changes have made the manuscript clearer in order to facilitate readability by the audience.

      (6) The discussion should be edited to include consideration of an explanation for the presence of the effect in male, but not female, mice more clearly. The discussion should also include some discussion as to why the distribution of cell types used in the electrophysiology recordings was different between males and females and whether the distribution of CRFR1 is different between males and females. Lastly, the authors need to include consideration of extrahypothalamic CRF and CRFR1 as a possible explanation for their effects. While they have PVN neuron recordings, the treatments that they used are brain-wide and therefore the possibility that the critical actions of CRFR1 could be outside the PVN.

      At page 15, line 11 to page 16, line 2 of the “discussion” section, we have suggested several mechanisms that might underlie the sex-linked behavioral and brain effects of CR<sub>1</sub> receptor antagonism reported in our manuscript. With regard to the distribution of cell types examined in the electrophysiology studies, at page 16, lines 6-9 we have mentioned a seminal review reporting sex-linked expression of PVN OXY and AVP in a variety of animal species that is similar to our results. Moreover, at page 18, lines 2-6 we mentioned that more studies are needed to examine PVN CRF<sub>1</sub> receptor expression in male and female animals, an issue that is still poorly understood. Finally, at page 16, line 12 to page 17, line 7 of the “discussion” section we also suggest that CRF<sub>1</sub> receptor-expressing brain areas other than the PVN, such as the BNST or the VTA, might contribute to the sex-linked effects of morphine reported in our manuscript. Thus, in agreement with this reviewer’s suggestion, in the present version of the manuscript we have further emphasized the possible implication of CRF<sub>1</sub> receptor-expressing extrahypothalamic brain areas in social behavior deficits induced by opiate substances.

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    1. Author response:

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

      Reviewer #1 (Public review):

      Comment 1: This manuscript from Clayton and co-authors, entitled ”Mechanism of dimer selectivity and binding cooperativity of BRAF inhibitors”, aims to clarify the molecular mechanism of BRAF dimer selectivity. Indeed, first-generation BRAF inhibitors, targeting monomeric BRAFV600E, are ineffective in treating resistant dimeric BRAF isoforms. Here, the authors employed molecular dynamics simulations to study the conformational dynamics of monomeric and dimeric BRAF, in the presence and absence of inhibitors. Multi-microsecond MD simulations showed an inward shift of the αC helix in the BRAFV600E mutant dimer. This helped in identifying a hydrogen bond between the inhibitors and the BRAF residue Glu501 as critical for dimer compatibility. The stability of the aforementioned interaction seems to be important to distinguish between dimer-selective and equipotent inhibitors.

      The study is overall valuable and robust. The authors used the recently developed particle mesh Ewald constant pH molecular dynamics, a state-of-the-art method, to investigate the correct histidine protonation considering the dynamics of the protein. Then, multi-microsecond simulations showed differences in the flexibility of the αC helix and DFG motif. The dimerization restricts the αC position in the inward conformation, in agreement with the result that dimer-compatible inhibitors can stabilize the αC-in state. Noteworthy, the MD simulations were used to study the interactions between the inhibitors and the protein, suggesting a critical role for a hydrogen bond with Glu501. Finally, simulations of a mixed state of BRAF (one protomer bound to the inhibitor and the other apo) indicate that the ability to stabilize the inward αC state of the apo protomer could be at the basis of the positive cooperativity of PHI1.

      We thank the reviewer for the positive evaluation of our work.

      Comment 2a: Regarding the analyses of the mixed state simulations, the DFG dihedral probability densities for the apo protomer (Fig. 5a right) are highly overlapping. It is not convincing that a slight shift can support the conclusion that the binding in one protomer is enough to shift the DFG motif outward allosterically. Moreover, the DFG dihedral time-series for the apo protomer (Supplementary Figure 9) clearly shows that the measured quantities are affected by significant fluctuations and poor consistency between the three replicates. The apo protomer of the mixed state simulations could be affected by the same problem that the authors pointed out in the case of the apo dimer simulations, where the amount of sampling is insufficient to model the DFG-out/-in transition properly.

      While the reviewer is correct there are large fluctuations in the DFG pseudo dihedral over the course of the apo simulations, these fluctuations occur primarily in the first 2 µs of the simulations, which were removed from our analysis. The reviewer is also correct that these simulations do not sufficiently model the DFG-out/-in transition; however, a full transition is not necessary for our analysis, as we are only interested in the shift of the DFG pseudo dihedral. As to the reviewer’s comment on the overlapping DFG distributions, we agree that the difference is very subtle. We revised the text.

      On page 9, second paragraph from the bottom:

      “While PHI1 or LY binding clearly perturbs the αC helix of the opposite apo protomer, the effect on the DFG conformation is less clear when comparing the DFG dihedral distribution of the the apo protomer in the PHI1 or LY-mixed dimer with that of the apo dimer (blue, orange, and grey, Figure 5a right). All three distributions are broad, covering a range of 160-330°. It appears that, relative to the apo dimer, the DFG of the apo protomer in the PHI1-mixed dimer is slightly shifted to the right, whereas that of the LY-mixed dimer is slightly shifted to the left; however, these differences are very subtle and warrant further investigation in future studies.”

      Comment 2b: There is similar concern with the Lys483-Glu501 salt bridge measured for the apo protomers of the mixed simulations. As it can be observed from the probabilities bar plot (Fig. 5a middle), the standard deviation is too high to support a significant role for this interaction in the allosteric modulation of the apo protomer.

      As for the salt bridge, the fluctuation in the apo dimer and LY-mixed dimer is indeed large, and together with the lower average probability suggests that the salt bridge is weaker, which is consistent with the αC helix moving outward. To clarify this, we revised the text.

      On page 9, second paragraph from the bottom:

      “Consistent with the inward shift of the αC helix, the Glu501–Lys483 salt bridge has a lower average probability and a larger fluctuation in the apo dimer and the apo protomer of the LY-mixed dimer, as compared to the apo protomer of the PHI1-mixed dimer.”

      Reviewer #2 (Public review):

      Comment 1: The authors employ molecular dynamics simulations to understand the selectivity of FDA approved inhibitors within dimeric and monomeric BRAF species. Through these comprehensive simulations, they shed light on the selectivity of BRAF inhibitors by delineating the main structural changes occurring during dimerization and inhibitor action. Notably, they identify the two pivotal elements in this process: the movement and conformational changes involving the alpha-C helix and the formation of a hydrogen bond involving the Glu-501 residue. These findings find support in the analyses of various structures crystallized from dimers and co-crystallized monomers in the presence of inhibitors. The elucidation of this mechanism holds significant potential for advancing our understanding of kinase signalling and the development of future BRAF inhibitor drugs.

      The authors employ a diverse array of computational techniques to characterize the binding sites and interactions between inhibitors and the active site of BRAF in both dimeric and monomeric forms. They combine traditional and advanced molecular dynamics simulation techniques such as CpHMD (all-atom continuous constant pH molecular dynamics) to provide mechanistic explanations. Additionally, the paper introduces methods for identifying and characterizing the formation of the hydrogen bond involving the Glu501 residue without the need for extensive molecular dynamics simulations. This approach facilitates the rapid identification of future BRAF inhibitor candidates.

      We thank the reviewer for the positive evaluation of our work.

      Comment 2: Despite the use of molecular dynamics yields crucial structural insights and outlines a mechanism to elucidate dimer selectivity and cooperativity in these systems, the authors could consider adoption of free energy methods to estimate the values of hydrogen bond energies and hydrophobic interactions, thereby enhancing the depth of their analysis.

      As mentioned in our previous response, current free energy methods are capable of giving accurate estimates of the relative binding free energies of similar ligands; however, accurate calculations of the absolute free energies of hydrogen bond and hydrophobic interactions are not feasible yet. Thus, we decided not to pursue the calculations.

      Reviewer #1 (Recommendations to author):

      Comment 1: It would be useful to cite all supplementary figures in the main text (where relevant). In the present version, only Supplementary Figures 2,3, and 4 are cited in the main text.

      This was an oversight; supplementary figures 5 through 9 are now cited in the text, to point to the time-series of the quantity discussed. We note that supplementary figures 10 and 11 show the time-series of the root mean squared deviation (RMSD) of each protomer in both all monomeric and dimeric simulations; these quantities are not discussed in the manuscript but are provided for further insight.

      Comment 2: It is unclear whether the present data could support a direct involvement of the DFG movement in the allosteric mechanism proposed. The same argument applies to the Lys483Glu501 interaction in the apo protomer of the mixed state simulations. The current simulation data could only support a different stabilization of the αC-helix position. The authors should either remove/tone down the claim or extend the simulations to sample a ”converged” distribution of the DFG dihedral and the Lys483-Glu501 salt bridge of the apo protomers.

      We agree that the DFG change in the apo protomer of the PH1-mixed dimer is very subtle (see our response and revision to comment 2); however, the allosteric involvement of DFG is clearly demonstrated in Figure 5 (right panel in 5a and 5b). We compare three states: apo protomer in the mixed dimer, PHI1-bound protomer in the mixed dimer, and holo dimer (i.e., with two PHI1) Binding of the first PHI1 restricts the DFG conformation to the larger DFG dihedrals (blue curves in the top and bottom right panels). This effect (DFG outward and more restricted) is even strong when the second PHI1 binds, locking the DFG in both protomers to a narrow dihedral range 270–330 degree (green and blue curves in Figure 5b, right panel). These are allosteric effects, demonstrating that the second PH1 binding induces conformational change of the DFG in the first protomer. This is why in Figure 6, the DFG of the PHI1-bound protomer in the mixed dimer is labeled as “almost out”, while the DFG in the holo dimer is labeled as “fully out”.

      The effect of second PHI1 on the DFG of the first protomer is consistent with that the αC helix position, in which case, the second PH1 induces an inward movement of the αC of the first protomer (illustrated as “fully in” in the schematic Figure 6). Through the aC movement, the salt-bridge strength is affected, as we discussed in our response and revision to Reviewer’s comment 2a. To clarify these points, we revised the discussion of Figure 5. We made the x axis range of the DFG dihedral distributions the same between the top and bottom panels in Figure 5. To remove the claim of priming effect on DFG, we revised Figure 6.

      Page 10, Figure 5:

      we made the x axis range of the DFG dihedral distributions on the top and bottom panels the same to facilitate comparison.

      Page 11, second and third paragraphs:

      “Consistent with the change in the DFG conformation between the holo (two inhibitor) and apo dimers (Figure 3c,3f), DFG is rigidified upon binding of the first inhibitor, as evident from the narrower DFG dihedral distribution of the PHI1 or LY-bound protomer in the mixed protomer (Figure 5b right) compared to the apo protomer in the mixed dimer (Figure 5a right). Importantly, the DFG dihedral is right shifted in the occupied vs. apo protomer, demonstrating that the inhibitor pushes the DFG outward.”

      “Consistent with the effect of the second PHI1 on the αC position of the first PHI1-bound protomer, binding of the second PHI1 shifts the peak of the DFG distribution for both protomers further outward, as shown by the 30° larger DFG pseudo dihedral in the holo dimer relative to the mixed dimer (green and blue in Figure 5b right; Supplementary Figures 6,9). In contrast, there is no significant difference in the DFG pseudo dihedral between the LY-mixed and holo dimers. These data suggest that while the binding of the first PHI1 pushes the DFG outward, binding of the second PHI1 has an allosteric effect, shifting the DFG of the opposite protomer further outward.”

      On page 12, the last paragraph of Conclusion, we remove the claim of the priming effect for DFG:

      “The first PHI1 binding in the BRAF<sup>V600E</sup> dimer restricts the motion of the αC helix and DFG, shifting them slightly inward and outward, respectively (Figure 6, bottom right panel). Intriguingly, the first PHI1 binding primes the apo protomer by making the αC more favorable for binding, i.e., shifting the αC inward (Figure 6, bottom right panel). Importantly, upon binding the second PHI1, the αC helix is shifted further inward and the DFG is shifted further outward in both protomers.”

      On page 13, Figure 6:

      we removed the label “slightly outward” for DFG.

      Comment 3: An alternative approach could be using enhanced sampling methods to enhance the diffusion along these coordinates.

      We thank the reviewer for bringing up this point. While that the allostery and cooperativity effects are apparent from our simulation data, we agree that enhanced sampling methods in principle could be used to further converge the conformational sampling; however, these approaches face significant challenges. First, BRAF dimer is weakly associated, with αC helix forming a part of the dimer interface. Enhanced sampling of αC helix would likely result in dimer dissociation. On the other hand, simply using RMSD as a reaction coordinate or progress variable would not necessarily enhance the motion of αC helix or DFG or activation loop, which are all coupled. Second, our extensive simulations of a monomer kinase with metadynamics demonstrated that the kinase conformation becomes distorted when a biasing potential is placed to enhance the motion of DFG. This is likely because the other parts of the protein do not have enough time to relax to accommodate the conformational change. To our knowledge, this aspect has not been discussed in the current metadynamics literature, which focuses on the free energy differences and (local) conformational changes along the reaction coordinate. To clarify these points, we added a discussion.

      Page 6, end of the first paragraph:

      “We note that enhanced sampling methods were not used due to several challenges. First, the BRAF dimer is weakly associated, with αC helix forming a part of the dimer interface (Figure 1a). Enhanced sampling (particularly of αC helix) would likely lead to dimer dissociation. Second, biased sampling methods such as metadynamics may lead to unrealistic conformational states due to the slow relaxation of some parts of the protein to accommodate the conformational change directed by the reaction coordinate. For example, our unpublished metadynamics simulations of a monomer kinase showed that enhancing the DFG conformational change resulted in distortion of the kinase structure.”

      We thank the reviewers again for their valuable comments. We believe our revision has further elevated the quality of the manuscript.

    1. Reviewer #2 (Public review):

      Summary:

      The authors aim to provide a comprehensive understanding of the evolutionary history of the Major Histocompatibility Complex (MHC) gene family across primate species. Specifically, they sought to:

      (1) Analyze the evolutionary patterns of MHC genes and pseudogenes across the entire primate order, spanning 60 million years of evolution.

      (2) Build gene and allele trees to compare the evolutionary rates of MHC Class I and Class II genes, with a focus on identifying which genes have evolved rapidly and which have remained stable.

      (3) Investigate the role of often-overlooked pseudogenes in reconstructing evolutionary events, especially within the Class I region.

      (4) Highlight how different primate species use varied MHC genes, haplotypes, and genetic variation to mount successful immune responses, despite the shared function of the MHC across species.

      (5) Fill gaps in the current understanding of MHC evolution by taking a broader, multi-species perspective using (a) phylogenomic analytical computing methods such as Beast2, Geneconv, BLAST, and the much larger computing capacities that have been developed and made available to researchers over the past few decades, (b) literature review for gene content and arrangement, and genomic rearrangements via haplotype comparisons.

      (6) The authors overall conclusions based on their analyses and results are that 'different species employ different genes, haplotypes, and patterns of variation to achieve a successful immune response'.

      Strengths:

      Essentially, much of the information presented in this paper is already well-known in the MHC field of genomic and genetic research, with few new conclusions and with insufficient respect to past studies. Nevertheless, while MHC evolution is a well-studied area, this paper potentially adds some originality through its comprehensive, cross-species evolutionary analysis of primates, focus on pseudogenes and the modern, large-scale methods employed. Its originality lies in its broad evolutionary scope of the primate order among mammals with solid methodological and phylogenetic analyses.

      The main strengths of this study are the use of large publicly available databases for primate MHC sequences, the intensive computing involved, the phylogenetic tool Beast2 to create multigene Bayesian phylogenetic trees using sequences from all genes and species, separated into Class I and Class II groups to provide a backbone of broad relationships to investigate subtrees, and the presentation of various subtrees as species and gene trees in an attempt to elucidate the unique gene duplications within the different species. The study provides some additional insights with summaries of MHC reference genomes and haplotypes in the context of a literature review to identify the gene content and haplotypes known to be present in different primate species. The phylogenetic overlays or ideograms (Figures 6 and 7) in part show the complexity of the evolution and organisation of the primate MHC genes via the orthologous and paralogous gene and species pathways progressively from the poorly-studied NWM, across a few moderately studied ape species, to the better-studied human MHC genes and haplotypes.

      Weaknesses:

      The title 'The Primate Major Histocompatibility Complex: An Illustrative Example of Gene Family Evolution' suggests that the paper will explore how the Major Histocompatibility Complex (MHC) in primates serves as a model for understanding gene family evolution. The term 'Illustrative Example' in the title would be appropriate if the paper aimed to use the primate Major Histocompatibility Complex (MHC) as a clear and representative case to demonstrate broader principles of gene family evolution. That is, the MHC gene family is not just one instance of gene family evolution but serves as a well-studied, insightful example that can highlight key mechanisms and concepts applicable to other gene families. However, this is not the case, this paper only covers specific details of primate MHC evolution without drawing broader lessons to any other gene families. So, the term 'Illustrative Example' is too broad or generalizing. In this case, a term like 'Case Study' or simply 'Example' would be more suitable. Perhaps, 'An Example of Gene Family Diversity' would be more precise. Also, an explanation or 'reminder' is suggested that this study is not about the origins of the MHC genes from the earliest jawed vertebrates per se (~600 mya), but it is an extension within a subspecies set that has emerged relatively late (~60 mya) in the evolutionary divergent pathways of the MHC genes, systems, and various vertebrate species.

      Phylogenomics. Particular weaknesses in this study are the limitations and problems associated with providing phylogenetic gene and species trees to try and solve the complex issue of the molecular mechanisms involved with imperfect gene duplications, losses, and rearrangements in a complex genomic region such as the MHC that is involved in various effects on the response and regulation of the immune system. A particular deficiency is drawing conclusions based on a single exon of the genes. Different exons present different trees. Which are the more reliable? Why were introns not included in the analyses? The authors attempt to overcome these limitations by including genomic haplotype analysis, duplication models, and the supporting or contradictory information available in previous publications. They succeed in part with this multidiscipline approach, but much is missed because of biased literature selection. The authors should include a paragraph about the benefits and limitations of the software that they have chosen for their analysis, and perhaps suggest some alternative tools that they might have tried comparatively. How were problems with Bayesian phylogeny such as computational intensity, choosing probabilities, choosing particular exons for analysis, assumptions of evolutionary models, rates of evolution, systemic bias, and absence of structural and functional information addressed and controlled for in this study?

      Gene families as haplotypes. In the Introduction, the MHC is referred to as a 'gene family', and in paragraph 2, it is described as being united by the 'MHC fold', despite exhibiting 'very diverse functions'. However, the MHC region is more accurately described as a multigene region containing diverse, haplotype-specific Conserved Polymorphic Sequences, many of which are likely to be regulatory rather than protein-coding. These regulatory elements are essential for controlling the expression of multiple MHC-related products, such as TNF and complement proteins, a relationship demonstrated over 30 years ago. Non-MHC fold loci such as TNF, complement, POU5F1, lncRNA, TRIM genes, LTA, LTB, NFkBIL1, etc, are present across all MHC haplotypes and play significant roles in regulation. Evolutionary selection must act on genotypes, considering both paternal and maternal haplotypes, rather than on individual genes alone. While it is valuable to compile databases for public use, their utility is diminished if they perpetuate outdated theories like the 'birth-and-death model'. The inclusion of prior information or assumptions used in a statistical or computational model, typically in Bayesian analysis, is commendable, but they should be based on genotypic data rather than older models. A more robust approach would consider the imperfect duplication of segments, the history of their conservation, and the functional differences in inheritance patterns. Additionally, the MHC should be examined as a genomic region, with ancestral haplotypes and sequence changes or rearrangements serving as key indicators of human evolution after the 'Out of Africa' migration, and with disease susceptibility providing a measurable outcome. There are more than 7000 different HLA-B and -C alleles at each locus, which suggests that there are many thousands of human HLA haplotypes to study. In this regard, the studies by Dawkins et al (1999 Immunol Rev 167,275), Shiina et al. (2006 Genetics 173,1555) on human MHC gene diversity and disease hitchhiking (haplotypes), and Sznarkowska et al. (2020 Cancers 12,1155) on the complex regulatory networks governing MHC expression, both in terms of immune transcription factor binding sites and regulatory non-coding RNAs, should be examined in greater detail, particularly in the context of MHC gene allelic diversity and locus organization in humans and other primates.

      Diversifying and/or concerted evolution. Both this and past studies highlight diversifying selection or balancing selection model is the dominant force in MHC evolution. This is primarily because the extreme polymorphism observed in MHC genes is advantageous for populations in terms of pathogen defence. Diversification increases the range of peptides that can be presented to T cells, enhancing the immune response. The peptide-binding regions of MHC genes are highly variable, and this variability is maintained through selection for immune function, especially in the face of rapidly evolving pathogens. In contrast, concerted evolution, which typically involves the homogenization of gene duplicates through processes like gene conversion or unequal crossing-over, seems to play a minimal role in MHC evolution. Although gene duplication events have occurred in the MHC region leading to the expansion of gene families, the resulting paralogs often undergo divergent evolution rather than being kept similar or homozygous by concerted evolution. Therefore, unlike gene families such as ribosomal RNA genes or histone genes, where concerted evolution leads to highly similar copies, MHC genes display much higher levels of allelic and functional diversification. Each MHC gene copy tends to evolve independently after duplication, acquiring unique polymorphisms that enhance the repertoire of antigen presentation, rather than undergoing homogenization through gene conversion. Also, in some populations with high polymorphism or genetic drift, allele frequencies may become similar over time without the influence of gene conversion. This similarity can be mistaken for gene conversion when it is simply due to neutral evolution or drift, particularly in small populations or bottlenecked species. Moreover, gene conversion might contribute to greater diversity by creating hybrids or mosaics between different MHC genes. In this regard, can the authors indicate what percentage of the gene numbers in their study have been homogenised by gene conversion compared to those that have been diversified by gene conversion?

      Duplication models. The phylogenetic overlays or ideograms (Figures 6 and 7) show considerable imperfect multigene duplications, losses, and rearrangements, but the paper's Discussion provides no in-depth consideration of the various multigenic models or mechanisms that can be used to explain the occurrence of such events. How do their duplication models compare to those proposed by others? For example, their text simply says on line 292, 'the proposed series of events is not always consistent with phylogenetic data'. How, why, when? Duplication models for the generation and extension of the human MHC class I genes as duplicons (extended gene or segmental genomic structures) by parsimonious imperfect tandem duplications with deletions and rearrangements in the alpha, beta, and kappa blocks were already formulated in the late 1990s and extended to the rhesus macaque in 2004 based on genomic haplotypic sequences. These studies were based on genomic sequences (genes, pseudogenes, retroelements), dot plot matrix comparisons, and phylogenetic analyses of gene and retroelement sequences using computer programs. It already was noted or proposed in these earlier 1999 studies that (1) the ancestor of HLA-P(90)/-T(16)/W(80) represented an old lineage separate from the other HLA class I genes in the alpha block, (2) HLA-U(21) is a duplicated fragment of HLA-A, (3) HLA-F and HLA-V(75) are among the earliest (progenitor) genes or outgroups within the alpha block, (4) distinct Alu and L1 retroelement sequences adjoining HLA-L(30), and HLA-N genomic segments (duplicons) in the kappa block are closely related to those in the HLA-B and HLA-C in the beta block; suggesting an inverted duplication and transposition of the HLA genes and retroelements between the beta and kappa regions. None of these prior human studies were referenced by Fortier and Pritchard in their paper. How does their human MHC class I gene duplication model (Fig. 6) such as gene duplication numbers and turnovers differ from those previously proposed and described by Kulski et al (1997 JME 45,599), (1999 JME 49,84), (2000 JME 50,510), Dawkins et al (1999 Immunol Rev 167,275), and Gaudieri et al (1999 GR 9,541)? Is this a case of reinventing the wheel?

      Results. The results are presented as new findings, whereas most if not all of the results' significance and importance already have been discussed in various other publications. Therefore, the authors might do better to combine the results and discussion into a single section with appropriate citations to previously published findings presented among their results for comparison. Do the trees and subsets differ from previous publications, albeit that they might have fewer comparative examples and samples than the present preprint? Alternatively, the results and discussion could be combined and presented as a review of the field, which would make more sense and be more honest than the current format of essentially rehashing old data.

      Minor corrections:

      (1) Abstract, line 19: 'modern methods'. Too general. What modern methods?

      (2) Abstract, line 25: 'look into [primate] MHC evolution.' The analysis is on the primate MHC genes, not on the entire vertebrate MHC evolution with a gene collection from sharks to humans. The non-primate MHC genes are often differently organised and structurally evolved in comparison to primate MHC.

      (3) Introduction, line 113. 'In a companion paper (Fortier and Pritchard, 2024)' This paper appears to be unpublished. If it's unpublished, it should not be referenced.

      (4) Figures 1 and 2. Use the term 'gene symbols' (circle, square, triangle, inverted triangle, diamond) or 'gene markers' instead of 'points'. 'Asterisks "within symbols" indicate new information.

      (5) Figures. A variety of colours have been applied for visualisation. However, some coloured texts are so light in colour that they are difficult to read against a white background. Could darker colours or black be used for all or most texts?

      (6) Results, line 135. '(Fortier and Pritchard, 2024)' This paper appears to be unpublished. If it's unpublished, it should not be referenced.

      (7) Results, lines 152 to 153, 164, 165, etc. 'Points with an asterisk'. Use the term 'gene symbols' (circle, square, triangle, inverted triangle, diamond) or 'gene markers' instead of 'points'. A point is a small dot such as those used in data points for plotting graphs .... The figures are so small that the asterisks in the circles, squares, triangles, etc, look like points (dots) and the points/asterisks terminology that is used is very confusing visually.

      (8) Line 178 (BEA, 2024) is not listed alphabetically in the References.

      (9) Lines 188-190. 'NWM MHC-G does not group with ape/OWM MHC-G, instead falling outside of the clade containing ape/OWM MHC-A, -G, -J and -K.' This is not surprising given that MHC-A, -G, -J, and -K are paralogs of each other and that some of them, especially in NWM have diverged over time from the paralogs and/or orthologs and might be closer to one paralog than another and not be an actual ortholog of OWM, apes or humans.

      (10) Line 249. Gene conversion: This is recombination between two different genes where a portion of the genes are exchanged with one another so that different portions of the gene can group within one or other of the two gene clades. Alternatively, the gene has been annotated incorrectly if the gene does not group within either of the two alternative clades. Another possibility is that one or two nucleotide mutations have occurred without a recombination resulting in a mistaken interpretation or conclusion of a recombination event. What measures are taken to avoid false-positive conclusions? How many MHC gene conversion (recombination) events have occurred according to the authors' estimates? What measures are taken to avoid false-positive conclusions?

      (11) Lines 284-286. 'The Class I MHC region is further divided into three polymorphic blocks-alpha, beta, and kappa blocks-that each contains MHC genes but are separated by well-conserved non-MHC genes.' The MHC class I region was first designated into conserved polymorphic duplication blocks, alpha and beta by Dawkins et al (1999 Immunol Rev 167,275), and kappa by Kulski et al (2002 Immunol Rev 190,95), and should be acknowledged (cited) accordingly.

      (12) Lines 285-286. 'The majority of the Class I genes are located in the alpha-block, which in humans includes 12 MHC genes and pseudogenes.' This is not strictly correct for many other species, because the majority of class I genes might be in the beta block of new and old-world monkeys, and the authors haven't provided respective counts of duplication numbers to show otherwise. The alpha block in some non-primate mammalian species such as pigs, rats, and mice has no MHC class I genes or only a few. Most MHC class I genes in non-primate mammalian species are found in other regions. For example, see Ando et al (2005 Immunogenetics 57,864) for the pig alpha, beta, and kappa regions in the MHC class I region. There are no pig MHC genes in the alpha block.

      (13) Line 297 to 299. 'The alpha-block also contains a large number of repetitive elements and gene fragments belonging to other gene families, and their specific repeating pattern in humans led to the conclusion that the region was formed by successive block duplications (Shiina et al., 1999).' There are different models for successive block duplications in the alpha block and some are more parsimonious based on imperfect multigenic segmental duplications (Kulski et al 1999, 2000) than others (Shiina et al., 1999). In this regard, Kulski et al (1999, 2000) also used duplicated repetitive elements neighbouring MHC genes to support their phylogenetic analyses and multigenic segmental duplication models. For comparison, can the authors indicate how many duplications and deletions they have in their models for each species?

      (14) Lines 315-315. 'Ours is the first work to show that MHC-U is actually an MHC-A-related gene fragment.' This sentence should be deleted. Other researchers had already inferred that MHC-U is actually an MHC-A-related gene fragment more than 25 years ago (Kulski et al 1999, 2000) when the MHC-U was originally named MHC-21.

      (15) Lines 361-362. 'Notably, our work has revealed that MHC-V is an old fragment.' This is not a new finding or hypothesis. Previous phylogenetic analysis and gene duplication modelling had already inferred HLA-V (formerly HLA-75) to be an old fragment (Kulski et al 1999, 2000).

      (16) Line 431-433. 'the Class II genes have been largely stable across the mammals, although we do see some lineage-specific expansions and contractions (Figure 2 and Figure 2-gure Supplement 2).' Please provide one or two references to support this statement. Is 'gure' a typo?

      (17) Line 437. 'We discovered far more "specific" events in Class I, while "broad-scale" events were predominant in Class II.' Please define the difference between 'specific' and 'broad-scale'.<br /> 450-451. 'This shows that classical genes experience more turnover and are more often affected by long-term balancing selection or convergent evolution.' Is balancing selection a form of divergent evolution that is different from convergent evolution? Please explain in more detail how and why balancing selection or convergent evolution affects classical and nonclassical genes differently.

      References. Some references in the supplementary materials such as Alvarez (1997), Daza-Vamenta (2004), Rojo (2005), Aarnink (2014), Kulski (2022), and others are missing from the Reference list. Please check that all the references in the text and the supplementary materials are listed correctly and alphabetically.

    1. (1) We create andrelease FeedSum, the first large-scale summariza-tion dataset for preference learning, featuring highdiversity in inputs, summaries, and feedback; (2)We examine how different configurations of LLM-generated feedback impact preference learning, andthe importance of feedback quality, dimensional-ity, and granularity. (3) We examine the alignmenttrade-off associated with relying on a single dimen-sion for preference learning. (4) We compare theeffectiveness of DPO and SFT variants. (5) Werelease SummLlama3-8b, which outperforms thenearly 10x larger Llama3-70b-instruct in the threehuman-preferred dimensions.

      Đóng góp chính - Tạo ra bộ FeedSum, có tính đa dạng cao. - Kiểm tra xem với mỗi cấu hình feedback của LLM sẽ tác động đến việc học như thế nào và tầm quan trọng của chất lượng feedback, tính đa chiều và tính mịn. - Kiểm tra tính trade-off liên quan đến việc dựa vào 1 chiều để học - So sánh hiệu quả của các phiên bản DPO và SFT. - Công bố LLM

    1. 人物程式化

      你提到的“程式化的人物形象”是拜占庭艺术,特别是绘画和镶嵌画中非常重要的一个特征。它指的是艺术家在描绘人物时,并非追求完全的写实和自然,而是采用一套固定的模式和规范,使人物形象显得庄重、肃穆,并带有一定的象征意义。

      下面我将详细解释“程式化的人物形象”在拜占庭艺术中的具体表现:

      1. 非写实的人体比例:

      • 修长的人物: 拜占庭艺术中的人物通常被描绘得比较修长,身材比例与现实生活中的人体有所不同。这种拉长的人物形象旨在强调人物的精神性和超越性,而非世俗的肉体存在。
      • 缺乏立体感: 人物的身体往往显得较为扁平,缺乏体积感和肌肉的起伏。艺术家不太注重光影和透视的表现,使得人物形象显得较为平面化。

      2. 脸部特征的固定模式:

      • 大眼睛: 拜占庭人物的眼睛通常被描绘得很大,而且眼神凝视前方,显得庄重而神秘。大眼睛象征着人物的灵性和洞察力。
      • 细长的脸型: 人物的脸型通常比较细长,椭圆形或杏仁形。
      • 表情肃穆: 人物的表情通常比较严肃、庄重,甚至略带忧郁或悲伤。他们很少表现出喜悦、愤怒等明显的情绪,旨在营造一种神圣和超越尘世的氛围。
      • 程式化的胡须和头发: 男性人物的胡须和头发通常以规则的线条和卷曲来表现,显得整齐而对称。

      3. 服饰和姿态的规范:

      • 繁复的服饰: 人物通常穿着华丽的服饰,上面装饰着丰富的图案和宝石。这些服饰旨在彰显人物的地位和神圣性。
      • 固定的姿态: 人物的姿态通常比较固定,例如正面站立、侧面站立或坐姿。他们很少做出大幅度的动作,显得庄重而肃穆。
      • 手势的象征意义: 人物的手势也具有一定的象征意义,例如祝福的手势、祈祷的手势等。

      4. 缺乏个性化:

      • 相似的面容: 由于采用固定的模式来描绘人物,因此不同人物的面容往往比较相似,缺乏个性化的特征。这使得人物更像是某种类型或角色的代表,而非具体的个人。

      程式化的目的:

      拜占庭艺术采用程式化的人物形象,并非因为艺术家缺乏写实能力,而是出于宗教和文化上的考虑:

      • 强调精神性和宗教性: 程式化的人物形象旨在强调人物的精神性和超越性,而非世俗的肉体存在。通过这种方式,艺术家试图将观众的注意力从世俗世界引向神圣世界。
      • 表达神圣的永恒性: 程式化的形象具有一定的永恒性和普遍性,它们超越了时间和空间的限制,代表着某种永恒的真理和价值。
      • 符合宗教仪式的需要: 拜占庭艺术主要服务于宗教仪式,程式化的形象更易于被信徒辨认和理解,并有助于营造庄重肃穆的宗教氛围。

      与其他艺术风格的比较:

      • 与古希腊罗马艺术的比较: 古希腊罗马艺术追求对人体完美的写实描绘,强调人体比例的准确性和肌肉的健美。而拜占庭艺术则相对忽视这些方面,更注重人物的精神性和象征意义。
      • 与文艺复兴艺术的比较: 文艺复兴艺术重新强调对自然的观察和写实描绘,追求人物形象的逼真和个性化。而拜占庭艺术则相对保守,仍然坚持程式化的传统。

      总而言之,“程式化的人物形象”是拜占庭艺术的重要特征,它通过一套固定的模式和规范来描绘人物,旨在强调人物的精神性和宗教性,并表达神圣的永恒性。理解这一特征有助于我们更好地欣赏和理解拜占庭艺术。

    1. 程式化的人物形象

      你提到的“程式化的人物形象”是拜占庭艺术,特别是绘画和镶嵌画中非常重要的一个特征。它指的是艺术家在描绘人物时,并非追求完全的写实和自然,而是采用一套固定的模式和规范,使人物形象显得庄重、肃穆,并带有一定的象征意义。

      下面我将详细解释“程式化的人物形象”在拜占庭艺术中的具体表现:

      1. 非写实的人体比例:

      • 修长的人物: 拜占庭艺术中的人物通常被描绘得比较修长,身材比例与现实生活中的人体有所不同。这种拉长的人物形象旨在强调人物的精神性和超越性,而非世俗的肉体存在。
      • 缺乏立体感: 人物的身体往往显得较为扁平,缺乏体积感和肌肉的起伏。艺术家不太注重光影和透视的表现,使得人物形象显得较为平面化。

      2. 脸部特征的固定模式:

      • 大眼睛: 拜占庭人物的眼睛通常被描绘得很大,而且眼神凝视前方,显得庄重而神秘。大眼睛象征着人物的灵性和洞察力。
      • 细长的脸型: 人物的脸型通常比较细长,椭圆形或杏仁形。
      • 表情肃穆: 人物的表情通常比较严肃、庄重,甚至略带忧郁或悲伤。他们很少表现出喜悦、愤怒等明显的情绪,旨在营造一种神圣和超越尘世的氛围。
      • 程式化的胡须和头发: 男性人物的胡须和头发通常以规则的线条和卷曲来表现,显得整齐而对称。

      3. 服饰和姿态的规范:

      • 繁复的服饰: 人物通常穿着华丽的服饰,上面装饰着丰富的图案和宝石。这些服饰旨在彰显人物的地位和神圣性。
      • 固定的姿态: 人物的姿态通常比较固定,例如正面站立、侧面站立或坐姿。他们很少做出大幅度的动作,显得庄重而肃穆。
      • 手势的象征意义: 人物的手势也具有一定的象征意义,例如祝福的手势、祈祷的手势等。

      4. 缺乏个性化:

      • 相似的面容: 由于采用固定的模式来描绘人物,因此不同人物的面容往往比较相似,缺乏个性化的特征。这使得人物更像是某种类型或角色的代表,而非具体的个人。

      程式化的目的:

      拜占庭艺术采用程式化的人物形象,并非因为艺术家缺乏写实能力,而是出于宗教和文化上的考虑:

      • 强调精神性和宗教性: 程式化的人物形象旨在强调人物的精神性和超越性,而非世俗的肉体存在。通过这种方式,艺术家试图将观众的注意力从世俗世界引向神圣世界。
      • 表达神圣的永恒性: 程式化的形象具有一定的永恒性和普遍性,它们超越了时间和空间的限制,代表着某种永恒的真理和价值。
      • 符合宗教仪式的需要: 拜占庭艺术主要服务于宗教仪式,程式化的形象更易于被信徒辨认和理解,并有助于营造庄重肃穆的宗教氛围。

      与其他艺术风格的比较:

      • 与古希腊罗马艺术的比较: 古希腊罗马艺术追求对人体完美的写实描绘,强调人体比例的准确性和肌肉的健美。而拜占庭艺术则相对忽视这些方面,更注重人物的精神性和象征意义。
      • 与文艺复兴艺术的比较: 文艺复兴艺术重新强调对自然的观察和写实描绘,追求人物形象的逼真和个性化。而拜占庭艺术则相对保守,仍然坚持程式化的传统。

      总而言之,“程式化的人物形象”是拜占庭艺术的重要特征,它通过一套固定的模式和规范来描绘人物,旨在强调人物的精神性和宗教性,并表达神圣的永恒性。理解这一特征有助于我们更好地欣赏和理解拜占庭艺术。

    1. 这篇文章由《大西洋月刊》科学台的记者们撰写,列举了2024年让他们震惊的77个事实,涵盖了历史、科技、自然、健康等多个领域,展现了世界的奇妙和多样性。以下是这些事实的详细总结:

      历史与文化

      1. 在法国印第安人战争期间,洋葱被用来治疗伤口。
      2. 1998年,艾伦·索金坚持不为他的首部电视剧《体育之夜》添加笑声轨,但该剧仍以笑声轨首播。
      3. 漫展无衬线体(Comic Sans)最初是为一个教人如何使用个人电脑的动画狗程序设计的。
      4. 古代,人们会带着装饰华丽的宠物松鼠散步。
      5. 西格蒙德·弗洛伊德让病人躺在沙发上,因为他无法忍受“整天被别人盯着看”。
      6. 1993年,科学家向太平洋倾倒了近1000磅的铁晶体,以从空气中吸收二氧化碳。
      7. 2008年,中国使用人工降雨技术在奥运会前清理北京上空。
      8. 在亚利桑那州的古德伊尔,一个用于生成式人工智能的数据中心每年可能消耗多达5600万加仑的饮用水。

      科技与创新

      1. 生成式人工智能的繁荣成本可能超过阿波罗太空任务。
      2. 超过5.3万部电影和8.5万集电视剧的字幕被用于训练生成式人工智能。
      3. 电动汽 车可能成为最佳警用车辆,因为它们加速快且没有燃料成本。
      4. 美国的面包车销售量从2000年的最高点下降了约80%。
      5. 人类可能通过检测其他行星上的荧光珊瑚来发现外星生命。
      6. 2024年7月,一家网络安全公司意外引入了一个软件错误,导致数万次航班和火车取消或延误,手术暂停,全球电视广播中断。
      7. 2024年4月,一辆红色特斯拉Model S成为首辆行驶200万公里的电动汽车,相当于从地球到月球往返两次,再绕赤道11圈。
      8. 男性避孕可能只需每天在肩膀和上臂涂抹凝胶。
      9. 42%的麻省理工学院学生主修计算机科学。
      10. 空调的节能模式并不节能。
      11. 到2040年,可能只有不到10个国家有足够的雪来举办冬季奥运会。

      自然与环境

      1. 一群蝴蝶不间断地飞越大西洋,仅用了大约8天。
      2. 加利福尼亚灰熊曾经主要是素食,但随着时间的推移,人类使它们变得更肉食。
      3. 蜱虫叮咬可能会让你对哺乳动物的肉过敏,以至于一些牧场主对自己的牛过敏。
      4. 白蚁会埋葬已经死亡一段时间的同伴,而新鲜的尸体则会被它们吃掉。
      5. 20世纪,地球上每天的时间增加了0.3到1.0毫秒,自2000年以来这一速率一直在增加,到2100年可能会翻倍。
      6. 5级飓风的风速比世界上最快的过山车还要快。
      7. 一些科学家认为,多细胞生命可能起源于巨大的山脉。
      8. 随着全球变暖,一些狗雪橇手在夜间驾驶他们的队伍,以防止动物过热。
      9. 极端高温导致学校在8月和9月将数百万人的课间休息移到室内。

      健康与医学

      1. 囊性纤维化儿童不再自动符合许愿基金会的资格,因为一种新药效果极好,这些孩子现在预计有基本正常的寿命。
      2. 你的身体里有你妈妈的——也许还有祖母、兄弟姐妹、阿姨和叔叔的——字面意义上的身体部分。
      3. 当一些人服用最初用于治疗哮喘的药物时,他们的食物过敏也开始消失。
      4. 大脑的质地与木薯布丁差不多。
      5. 巨型南瓜的重量在过去半个世纪里增加了20倍。
      6. 孩子们并不真的需要吃蔬菜。
      7. 你可以通过在米粒内部培养牛细胞来给米饭增添坚果风味。
      8. 蘑菇基因可以使矮牵牛花发光。
      9. 一种由干细胞制成的人类胚胎模型分泌的激素可以使妊娠试验呈阳性。
      10. 美国已婚男性采用妻子姓氏的可能性是没有连字符附加自己姓氏的五倍。
      11. 床虱的交配仪式可能增强了它们的免疫系统。
      12. 东非稀树草原上的狮子因为一种蚂蚁物种而难以猎杀斑马。
      13. 想要与喜欢是不同的。
      14. 自然水中锂含量较高与一些国家较低的自杀率有关。
      15. 人类的汗腺是黑猩猩的10倍。
      16. 如果你想控制汗水,你应该在晚上使用止汗剂。

      食品与农业

      1. 麦当劳直到1990年都用牛油炸薯条。
      2. 这家快餐巨头还精确地烤牛肉饼42秒。
      3. 一棵面包果 树可以养活一个四口之家至少50年。
      4. 蛋白质可以成为相当好的糖替代品。
      5. 格雷厄姆饼干的发明者西勒斯特·格雷厄姆认为他的饼干可以遏制手淫。

      社会与行为

      1. 全球每秒钟扫描超过10000个条形码。
      2. 加州灰熊曾经主要是素食,但随着时间的推移,人类使它们变得更肉食。
      3. 学生交流口音可能是真的。
      4. 每个精子鲸族群使用自己的一套点击声来交流,其中一些声音可能比梵文还要古老。
      5. 美国人在2018年扔掉的小家电是1990年的四倍。
      6. 狗可能正在进入驯化的新浪潮,它们已经经历的驯化可能使它们吠叫得更多。
      7. 大象和鹦鹉使用类似名字的叫声来识别个体,鲸鱼和蝙蝠也可能如此。
      8. 想要与喜欢是不同的。
      9. 一个“基督教保守派”的移动电话服务提供商在美国运营了十多年,它为使用T-Mobile的蜂窝网络付费。
      10. 在乔·拜登退出总统竞选之前,他的竞选团队在唐纳德·特朗普的Truth Social网站上维护了一个账户,他们用它来试图引诱特朗普竞选团队选择一个更极端的副总统候选人。
      11. 超过半数的共和党选民现在支持娱乐性大麻合法化。
      12. 最新的迷幻药可能根本不会引起幻觉。
      13. 一些科学家认为,多细胞生命可能起源于巨大的山脉。

      商业与经济

      1. 政府免费税务准备软件Direct File的员工总数少于为Intuit工作的游说者。
      2. 你可以为你的宠物购买健身追踪器。
      3. 人类基本上已经达到了飞机行李架空间的极限。
      4. 你可以购买一个99美元的量子水瓶,它被“充满”了特殊的治愈频率。

      动物行为

      1. 早期太空舱外部缺乏把手和脚踏板,一些太空行走的宇航员真的很难重新上船。
      2. 狗可能正在进入驯化的新浪潮,它们已经经历的驯化可能使它们吠叫得更多。
      3. 大象和鹦鹉使用类似名字的叫声来识别个体,鲸鱼和蝙蝠也可能如此。

      其他

      1. 人类的大脑会对最简单的动画产生多巴胺反应。
      2. 一位牙医在他父母新装修的房屋的地板砖中发现了一个原始人类的下颌骨。
      3. 口香糖成为棒球的必备品,部分原因是箭牌公司继承人菲利普·箭牌在1932年接管芝加哥小熊队后,将其分发给球员。
      4. 社会学家对长期的街头篮球比赛进行了几次民族志研究。
      5. 每天走10000步的目标并非来自临床科学,而是来自1965年一家日本公司销售计步器的营销活动。
    1. 以下是文件中提到的52件事的总结:

      1. 使用Firefox或Chrome的员工比使用IE或Safari的员工留存率高15%,工作满意度更高。
      2. 10月31日,医生诊断儿童患ADHD的概率比平时高14%,并非因为患ADHD的儿童增多,而是孩子们对万圣节的兴奋影响了诊断。
      3. 美国需要九成民众同意一项政策,该政策才有50%的机会获批。
      4. 男性在感到男性气概受威胁时,购买SUV的意愿比平时高出24个百分点,且愿意为此支付比未受威胁男性多7320美元的价格。
      5. 骂 swear能提升握力9%、靠墙坐时间22%、平板支撑时间12%。
      6. 所有文化都有表示黑白的词汇,若有第三种颜色词汇,一定是红色;若有第四种,则是黄色或绿色。
      7. 自1979年以来,纽约、波士顿和费城街头的步行速度提高了15%。
      8. 印裔美国人拥有美国约一半的汽车旅馆,其中70%姓Patel。
      9. 自2007年以来,年轻男性随意性行为的减少,有25%可归因于电子游戏。
      10. ChatGPT导致Upwork上发布的自由职业工作数量下降了2%。
      11. AI产生的温室气体排放量比人类少。人类写三百字排放27克二氧化碳,而ChatGPT完成同样任务仅需4.4秒,排放2.2克二氧化碳。
      12. 俄罗斯因谷歌在YouTube上屏蔽亲俄媒体频道,对谷歌处以巨额罚款,罚款金额每周翻倍,219周后谷歌将欠俄罗斯一个古戈尔(googol)。
      13. 美国缅因州的卡车司机因州法律中牛津逗号的歧义,额外获得了500万美元的加班费。
      14. 一个城市在饮用水中添加氟化物后,牙医诊所数量会减少9%。
      15. 在线体育博彩合法化导致体育博彩者信用卡债务增加8%,低收入家庭比高收入家庭在博彩上的支出多32%。
      16. 抖腿神器(Fidget spinners)并不起作用,使用它会损害对视频讲座的记忆。
      17. 与100年前相比,如今煮鸡的时间翻倍,因为21世纪的鸡运动量减少。
      18. 美国婴儿名字趋势从一个世纪前的家族姓氏,到一代人前的流行名字,再到如今的流行后缀。如今,500个最流行的名字中有48%共享仅十个后缀。
      19. 爱尔兰维和人员在黎巴嫩驻扎时间太长,导致一些黎巴嫩人开始带有爱尔兰口音。
      20. 1985年,佐治亚州北部一只黑熊因可卡因过量死亡,被制成标本,现位于肯塔基州列克星敦的肯塔基乐趣商城,因肯塔基婚姻法的漏洞,它被允许主持具有法律约束力的婚礼。
      21. 根据1917年的教会法典,月球属于奥兰多教区,因为发现月球的探险队是从奥兰多出发的。
      22. 登月计划从未受到广泛欢迎。唯一一次大多数美国人支持阿波罗计划是在阿波罗11号登月后,当时有53%的人支持。
      23. 女性更有可能建议她们认为与自己一样或更有吸引力的客户剪短发。
      24. 重金属吉他手弹奏快速音乐往往具有较高的同性竞争性。成为重金属吉他手的主要动机不是为了吸引女性,而是为了吸引其他男性。
      25. 怀孕消耗50000卡路里。
      26. 由于随着年龄增长听力下降,25岁以上的男性无法听到高于17.4千赫的声音。英国的店主发明了一种播放17.4千赫声音的警报器,音量为100分贝,用来驱赶闲逛者,主要是年轻男性。
      27. 到公元750年,由于抄写错误和遗忘,英格兰硬币上罗马皇帝的形象演变成了一只豪猪。
      28. 人们高估了他人的不诚实程度约13.6%。
      29. 印度和巴基斯坦的秃鹫因摄入微量的双氯芬酸(一种在印度和巴基斯坦广泛用于牛的抗炎药)而死亡。因此,需要秃鹫的琐罗亚斯德教葬礼受到威胁。
      30. C语言的能效是Python的75.88倍,速度是Python的71.9倍。
      31. 平均而言,美国夫妻之间的基因相似性相当于四至五代堂亲之间的相似性。
      32. 全男性团体更容易说谎。当第一个女性加入全男性团体时,说谎率急剧下降。
      33. 英国部分地区要求房屋至少相隔21米的规定可以追溯到1902年的一项规定,当时两名男子确定这是他们彼此之间能看到对方衬衫下乳头的最近距离。
      34. 男性在使用屏幕点餐时更有可能在麦当劳点两个汉堡,而向真人点餐时通常只点一个。
      35. 马萨诸塞州法律规定算命师必须获得许可,并禁止“假装算命”。
      36. 婴儿模拟器原本旨在阻止青少年怀孕,但实际上却使女孩怀孕的可能性增加。使用过婴儿模拟器的女孩怀孕率为8%,而未使用过的女孩为4%。
      37. 20世纪90年代,朝鲜领导人金正日和现任领导人金正恩使用假巴西护照去了东京的迪士尼乐园(大概)。
      38. 当汽油价格达到每加仑3.50美元时,会出现负面的电视报道。汽油价格每上涨50美分,报道就会增加7.5个百分点。福克斯新闻报道汽油价格最为频繁。
      39. 飞机上不要求使用汽车座椅,因为这会减少座位供应,提高票价,导致更多家庭选择开车。由于开车比飞行更危险,每在飞机上使用一个汽车座椅拯救的孩子,就会有60个孩子在车祸中丧生。
      40. 新闻标题中每增加一个负面词汇,就会增加2.3%的点击率。
      41. 人们在27分钟内就能知道自己是否想买房子,但决定买沙发需要88分钟。
      42. 2019年,美国将其联邦预算的1%用于肾脏透析。
      43. 在雄性投资武器(鹿角、牛角、长牙等)的物种中,雌性的大脑更大。
      44. 第一个被送入太空的人造物体不是斯普特尼克1号,而是一个在内华达州核试验中意外被吹飞的井盖。它达到了地球逃逸速度的六倍,并且再也没有被找到。
      45. 县级学校发生枪击事件后,全国步枪协会(NRA)的捐款在次年增加30%。
      46. 《摩克和明迪》的制作团队需要会说四种语言的审查员来捕捉罗宾·威廉姆斯试图偷偷加入的所有脏话。
      47. 越南战争的征兵抽签实际上并不随机。抽取的数字来自一个没有充分混合的桶,而且抽取人几乎总是从顶部抽取。蒙特卡洛模拟估计数字是随机抽取的概率为0.09%。
      48. 入住白宫的外国领导人和外交官有权享受免费洗衣服务。大多数客人只需要清洗一两件物品,除了本杰明·内塔尼亚胡,他每次访问都会带来装满脏衣服的行李箱。(他否认了这一点。)
      49. Waymo自动驾驶出租车的财产损失索赔比人类司机少88%,人身伤害索赔少92%。在行驶了2530万英里后,Waymo Driver有9起财产损失索赔和2起伤害索赔,而人类司机在行驶同等里程的情况下有78起财产损失索赔和26起伤害索赔。
      50. 在奢侈品牌中,品牌标志大小在七点量表上增加一点,会导致古驰的价格下降122.26美元,路易威登的价格下降26.27美元。
      51. 公牛看不到红色。让它们发怒的不是红色,而是“被糟糕对待”。
      52. 未提及。
    1. voting systems, which are essentially anti-oligarchic, like quadratic voting. Basically, one share, one vote. That's your first vote, but then to have a second vote, you need the-- How do you call it? The square root? Anyway, so the next, I think, is 4 and then 16. You basically cream off the power of money and give it to the contributors, to the people collaborating on the project.

      for - investigate - quadratic voting - SOURCE - Youtube Ma Earth channel interview - Devcon 2024 - Cosmo Local Commoning with Web 3 - Michel Bauwens - 2025, Jan 2

    1. 收藏有与耶稣受难相关的圣物。

      圣十字圣殿(Basilica di Santa Croce)的含义主要围绕着“圣十字架”这一基督教最重要的圣物展开。要理解其含义,需要从几个方面来看:

      1. “圣十字架”的由来:

      根据基督教传统,耶稣基督被钉死在十字架上,因此十字架成为了基督教最重要的象征,代表着耶稣的牺牲和救赎。传说中,耶稣受难的十字架在几个世纪后被圣海伦娜(君士坦丁大帝的母亲)于耶路撒冷寻获,并将其部分带回了罗马。

      2. “圣十字圣殿”的命名和建立:

      • 罗马的圣十字圣殿(Basilica di Santa Croce in Gerusalemme): 这座位于罗马的圣十字圣殿,其名称中的“in Gerusalemme”(在耶路撒冷)就表明了它与耶稣受难地耶路撒冷的联系。传说这座教堂的地基下埋有从加尔瓦略山(耶稣受难地)运来的圣土,并且保存有部分“真十字架”的遗物,例如钉住耶稣的铁钉、十字架的碎片等。因此,这座教堂从一开始就被视为一个重要的圣髑保存地,供信徒朝圣和敬拜。
      • 佛罗伦萨的圣十字圣殿(Basilica di Santa Croce in Firenze): 佛罗伦萨的圣十字圣殿则是因为法王路易九世赠送给圣方济各会的几块“真十字架”碎片而得名。这座教堂也因此成为了重要的宗教场所,并逐渐发展成为佛罗伦萨重要的文化中心,许多杰出人物都安葬于此,因此也被称为“意大利光荣的殿堂”。

      3. “圣十字”的象征意义:

      “圣十字”本身在基督教中就具有极其重要的象征意义:

      • 救赎和牺牲: 十字架是耶稣为救赎人类而牺牲的象征,代表着上帝对人类的大爱。
      • 信仰的标志: 十字架是基督教最显著的标志,代表着基督徒的信仰。
      • 希望和永生: 通过耶稣在十字架上的牺牲,信徒们获得了永生的希望。

      4. 圣十字圣殿的意义:

      结合以上几点,“圣十字圣殿”的含义可以概括为:

      • 保存圣物: 圣十字圣殿是保存“真十字架”相关遗物的重要场所,是基督教重要的圣地之一。
      • 纪念耶稣的牺牲: 教堂通过供奉圣十字架来纪念耶稣为救赎人类而做出的牺牲。
      • 重要的宗教场所: 圣十字圣殿是重要的宗教活动场所,供信徒朝圣、敬拜和祈祷。
      • 文化和历史的象征: 尤其是在佛罗伦萨,圣十字圣殿不仅仅是一座教堂,它还见证了佛罗伦萨的历史和文化发展,成为了重要的文化地标。

      总结:

      无论是罗马的圣十字圣殿还是佛罗伦萨的圣十字圣殿,其名称都直接指向了基督教最重要的圣物——“圣十字架”,并因此承载了丰富的宗教和文化内涵。它们不仅是重要的宗教场所,也是历史和艺术的宝库。

      希望以上解释能够帮助你更好地理解“圣十字圣殿”的含义。

    1. Les extraits présentés concernent une table ronde commémorant les 60 ans de BUC Ressources, un centre de formation en travail social rattaché à la Sauvegarde des Yvelines.

      La discussion explore l'histoire de BUC Ressources, son évolution depuis sa création en 1964, son rôle dans le développement de la formation en travail social, et l'importance croissante de la co-formation intégrant la perspective des personnes accompagnées. L'accent est mis sur l'influence de facteurs historiques, politiques, et philosophiques sur la formation et la pratique du travail social.

      Des intervenants clés, impliqués dans l'histoire de BUC Ressources et experts en travail social, partagent leurs réflexions et expériences.

      Sommaire minuté de la vidéo "BUC Ressources - 60 ans de formation en travail social - Sauvegarde des Yvelines"

      0:34 - 1:00 : Introduction et informations pratiques

      • Table ronde sur le thème "60 ans de formation en travail social".
      • Remerciements aux participants, y compris une collègue du Québec.
      • Invitation à un verre et à une visite guidée des nouvelles installations après la table ronde.

      3:29 - 4:21 : Discours d'Anne Petiau, directrice du CERA

      • Remerciements à BUC Ressources pour son engagement dans la recherche.
      • Soulignement de l'originalité d'avoir un campus, un centre de formation et un centre de recherche au sein d'une association médico-sociale.
      • Importance de poursuivre et de partager ces richesses.
      • Souhaits de continuation et d'excellence pour l'avenir de BUC Ressources.

      4:32 - 5:27 : Historique de BUC Ressources

      • Début de l'activité en 1964.
      • 11 formations diplômantes et certifiantes dispensées.
      • Effectif moyen de 1100 à 1200 étudiants en formation initiale et 650 à 700 en formation continue.
      • Description de BUC Ressources comme un lieu vivant et un bouillon de culture avec des formateurs aux profils variés.
      • Distinction entre l'éducation spécialisée et le travail social à BUC Ressources.

      5:27 - 9:58 : Témoignages d'anciens étudiants et formateurs

      • Parcours et motivations de plusieurs anciens étudiants et formateurs.
      • Description de la formation, notamment la double diplomation en partenariat avec l'Université de Lille.
      • Soutien du Ministère dans la création de l'école et la construction des bâtiments.
      • Importance de l'unité de pensée autour de l'éducation spécialisée et de la liberté dans les approches pédagogiques.
      • Diversité des intervenants invités par les formateurs.
      • Descriptions d'activités et de sessions spécifiques, comme la sculpture sur pierre et le "forestage froissartage".

      11:06 - 14:26 : Spécificités de la pédagogie de BUC Ressources

      • Importance de l'articulation entre théorie et pratique.
      • Possibilité de structurer son parcours en fonction de son profil et des besoins du terrain.
      • Richesse de la co-construction des savoirs et de l'interaction entre étudiants et formateurs.
      • Semaines de regroupement avec des cours sur des thématiques variées et des semaines d'approfondissement au choix.
      • Importance de l'enseignement juridique et de la co-construction de projets avec les personnes accompagnées.
      • Description de l'ambiance conviviale et chaleureuse de l'école, notamment grâce à la cantine et à l'épicerie solidaire.

      17:10 - 18:47 : Impact et perspectives d'avenir

      • Formation de nombreux cadres du secteur.
      • Impact sur l'encadrement et la formation des directeurs et chefs de services.
      • Projet de modernisation des bâtiments et des installations à l'horizon 2030 intégrant le développement durable.
      • Témoignages sur l'apport de la formation sur les plans académique et personnel.
      • Importance de la liberté de penser et de l'ambiance festive à BUC Ressources.

      18:47 - 21:47 : Introduction de la table ronde

      • Remerciements aux participants et introduction du thème "60 ans de formation en travail social".
      • Contexte de la création de BUC Ressources en 1964, peu avant la création du diplôme d'éducateur spécialisé en 1967.
      • BUC Ressources comme partie intégrante de la Sauvegarde des Yvelines, créée en 1876.
      • Objectif de la table ronde : situer BUC Ressources dans l'histoire des établissements de formation en travail social et dans l'histoire plus large du travail social et des évolutions sociales.
      • Présentation des intervenants de la table ronde.

      21:47 - 37:32 : Intervention de Guy Dreano, co-fondateur de BUC Ressources

      • Témoignage en tant que dernier survivant des fondateurs de l'école.
      • Remerciements aux personnes et aux institutions ayant permis la création et le développement de l'école.
      • Importance de l' "ouverture" comme état d'esprit et fil conducteur de BUC Ressources.
      • Contexte professionnel et associatif de la création de l'école.
      • Rôle des conseillers pédagogiques et des moniteurs de stage.
      • Engagement des professionnels dans les instances régionales et nationales pour faire évoluer l'inadaptation sociale des enfants et adolescents.
      • Spécificité de BUC Ressources comme première école dirigée par des éducateurs ayant une expérience de terrain.
      • Chronologie de dates clés marquant l'évolution du secteur et la professionnalisation du métier d'éducateur.

      37:32 - 57:46 : Intervention de Marcel Jaeger, ancien directeur de BUC Ressources et président de l'UNAFORIS

      • Diversification de la structure et de l'activité de BUC Ressources au cours de son développement.
      • Passage d'une petite école à un établissement plus grand, rejoignant le monde des IRTS.
      • Importance des liens avec le secteur professionnel et l'appartenance à la Sauvegarde des Yvelines.
      • Coopérations internationales, notamment sur la question du décloisonnement entre le sanitaire et le social.
      • Distinction de BUC Ressources par son positionnement précoce sur la recherche et la formation à la recherche pour les étudiants.
      • Prise en compte progressive de la question du handicap et organisation d'un colloque sur la loi de 1975 en faveur des personnes handicapées.
      • Importance de l'éthique et de la réflexion sur le positionnement en situation difficile, notamment grâce à l'influence de Guy Dreano.
      • Impact des contraintes extérieures, comme la baisse des subventions de l'État, sur le développement de l'école et l'obligation de se positionner sur la formation continue.
      • Sensibilité de BUC Ressources aux évolutions des politiques publiques et réactivité face aux nouvelles lois.
      • Obligation de formalisation des compétences avec la mise en place de la VAE.
      • Tension entre la formalisation techniciste des compétences et la tradition axée sur les valeurs et la pratique.

      57:46 - 1:12:21 : Intervention d'Amélie Maugère, professeure à l'École de travail social de Montréal

      • Comparaison entre l'histoire de BUC Ressources et celle de l'École de travail social de Montréal, fondée en 1940.
      • Influence de la tradition catholique sur l'École de Montréal et laïcisation progressive de la société québécoise à partir des années 1960.
      • Importance des femmes dans l'avènement du travail social.
      • Tension entre technicisme et valeurs dans la formation.
      • Création d'un système de protection sociale moderne au Québec dans les années 1960 et son impact sur la formation en travail social.
      • Professionnalisation accrue et émergence d'une expertise techniciste.

      1:12:21 - 1:29:22 : Intervention de Carole Lefloc, autrice de "De la grande exclusion au pouvoir d'agir"

      • Parcours personnel d'experte d'expérience et ses différentes formes d'expertise et d'activités dans le travail social.
      • Difficulté à définir l'expertise expérientielle.
      • Importance de l'analyse et de l'extraction des compétences du parcours de vie pour une intégration effective des personnes accompagnées en école de formation.
      • Importance de la participation des personnes concernées dans les décisions et les instances de consultation.
      • Rôle crucial du travail social dans le soutien et la reconstruction des personnes en difficulté.
      • Importance de la formation et de la conscientisation des étudiants sur les réalités vécues par les personnes concernées.
      • Nécessité de reconnaître la participation citoyenne comme une fonction et une activité à part entière.
      • Plaidoyer pour un Tronc commun dans les formations de l'humain, intégrant le savoir expérientiel.
      • Identification et valorisation des compétences issues de l'expérience de vie.

      1:29:22 - 2:12:11 : Intervention d'Elsa Lagier, responsable pédagogique et chargée de recherche au CERA

      • La participation des personnes concernées dans la formation n'est pas nouvelle, mais elle évolue vers une plus grande reconnaissance de leur expertise.
      • Importance de donner du temps et d'adopter une posture d'écoute et de non-jugement envers les personnes concernées.
      • Les témoignages des personnes concernées permettent aux étudiants de comprendre les réalités du terrain et de développer une posture professionnelle plus juste et respectueuse.
      • La formation en travail social doit s'appuyer sur des savoirs pluriels, y compris ceux des personnes concernées.
      • La coformation, associant différentes catégories de personnes dans un même lieu et un même temps, est une modalité prometteuse pour intégrer le savoir expérientiel.
      • L'échange en dehors de la relation d'accompagnement est une modalité spécifique de la coformation.
      • Les émotions occupent une place importante dans la dynamique de la coformation.
      • Les modules de coformation sont perçus comme des moments marquants par les étudiants, qui en retirent des apprentissages durables.
      • Enjeux éthiques et méthodologiques de la coformation, notamment la formation des personnes concernées à l'intervention, leur statut et leur rémunération.
      • Importance de mobiliser un collectif de personnes concernées pour garantir une pluralité d'expériences et de points de vue.
      • La professionnalisation des personnes concernées peut poser question quant à la représentativité de leur discours.
      • BUC Ressources développe des outils et des modules de coformation pour encourager la participation des personnes concernées de manière éthique et pertinente.

      2:12:11 - 2:12:43 : Conclusion de la table ronde

      • Remerciements aux intervenants et aux participants.
      • Invitation à consulter les travaux des intervenants pour approfondir la réflexion.
      • Annonce des prochaines rencontres de BUC Ressources et des conférences disponibles en replay.
      • Invitation à poursuivre les échanges lors du cocktail de clôture.

      2:12:43 - 2:12:59 : Remerciements et invitation au cocktail

      • Remerciements aux participants.
      • Invitation au cocktail de clôture pour poursuivre les échanges de manière informelle.
    1. 没有单一风格,而是多个艺术流派并存(如印象派、立体派、超现实主义等),每个流派都试图重新定义艺术的本质和边界。

      你提出的“多样性与创新性:没有单一风格,而是多个艺术流派并存(如印象派、立体派、超现实主义等),每个流派都试图重新定义艺术的本质和边界”这个观点,准确地阐述了艺术领域中多样性如何驱动创新。我来详细解释一下:

      1. 多样性是创新的沃土:

      多样性在艺术领域体现在多个方面:

      • 风格的多样性: 就像你提到的印象派、立体派、超现实主义等,不同的艺术流派拥有截然不同的表现形式、技巧和理念。
      • 艺术家背景的多样性: 不同的艺术家拥有不同的文化背景、生活经历、教育背景和社会地位,这使得他们对艺术的理解和表达方式各不相同。
      • 创作媒介的多样性: 绘画、雕塑、建筑、音乐、文学、戏剧、电影等不同的艺术媒介,为艺术家提供了丰富的创作空间和可能性。

      这种多样性打破了单一的艺术标准和范式,为创新提供了无限的可能。不同的流派和艺术家相互碰撞、相互影响,从而产生新的思想、新的技巧和新的艺术形式。

      2. 艺术流派的并存与竞争:

      在艺术史上,很少有一个时期只有一种艺术流派占据主导地位。更多的情况是,多个艺术流派并存,它们之间既有竞争,也有相互影响。

      • 竞争: 不同的流派都试图证明自己的艺术理念和表现方式是更优越的,这种竞争推动了艺术的不断发展和创新。
      • 相互影响: 不同的流派之间也会相互借鉴、相互吸收,从而产生新的艺术形式。例如,立体派就受到了后印象派画家塞尚的影响。

      3. 重新定义艺术的本质和边界:

      每个新的艺术流派的出现,都伴随着对艺术本质和边界的重新思考和定义。

      • 印象派: 印象派画家放弃了传统的绘画技巧,转而关注光线和色彩的变化,试图捕捉瞬间的视觉印象,这颠覆了传统的绘画观念。
      • 立体派: 立体派画家将物体分解成不同的几何图形,并将其重新组合在画面上,打破了传统的透视法则,挑战了人们对物体形态的认知。
      • 超现实主义: 超现实主义画家受到弗洛伊德精神分析学的影响,试图表现潜意识和梦境的世界,探索人类内心深处的欲望和情感,这拓展了艺术的表现范围。

      这些流派的出现,都极大地拓展了艺术的边界,使艺术的表现形式和内涵更加丰富多样。

      4. 多样性与创新的关系:

      多样性是创新的必要条件。没有多样性,就没有新的思想、新的视角和新的方法,也就难以产生真正的创新。艺术领域的多样性驱动了艺术的不断发展和变革,使艺术始终保持着活力和创造力。

      总结:

      “没有单一风格,而是多个艺术流派并存,每个流派都试图重新定义艺术的本质和边界”这句话,很好地概括了艺术领域中多样性与创新性的关系。多样性为创新提供了沃土,不同的艺术流派在竞争和相互影响中不断推动艺术的发展,并不断重新定义艺术的本质和边界。

      可以将这个概念推广到其他领域,例如科学、技术、商业等。在这些领域,多样性同样是创新的重要驱动力。拥有不同背景、不同经验和不同观点的人们聚集在一起,才能产生更多新的想法和解决方案,从而推动社会的发展和进步。

    1. Opportunities1) Sleep plays a fundamental role in humanphysiology. Knowledge about sleep can poten-tially improve pain management, chronic dis-ease treatment, and cognitive outcomes inneurodegenerative disorders, along with co-ordinating drug bioavailability. For these in-dications and others, a new technology modelcan be envisioned for the bedroom as a treat-ment site within the home that becomes op-erational as we fall asleep. Applied sleepneuroscience should explore how sleep-wakerhythms can empower individuals to betterrespond to clinical interventions, as well ashelp individuals recover from each day’s pres-sures, thereby preparing them for tomorrow’sdisease risk.2) Sleep is associated with many aspects ofmental and physical well-being. Althoughsleep is acknowledged as a major contribu-tor to mental and physical health outcomes,this growing understanding has yet to becodified into NIH and other federal guidelinesthat would encourage clinical trial designersto incorporate sleep as a common variable ofinterest and to formalize the scheduling, col-lection, and reporting of biosample collectionwith respect to time of day and an individual’ssleep phase. With such mandates in placealong with open science practices, biomedicalresearch could synthesize information frommultiple levels of analysis to provide insightsinto the fundamental contributions of sleepto individual organ systems and emergentphysiology, as well as how sleep modifies thecourse of disease and response to experimen-tal treatments.3) Sleep health itself is multidimensional.Many investigations concerning human sleepare limited by an overly narrow focus on sleepdeprivation and primary sleep disorders, thuscreating a false dichotomy between typicaland atypical sleep. The very concept of sleephealth, which moves beyond clinical disor-ders to emphasize the positive contributionsof sleep to mental and physical well-being,suggests that all sleep gradations are rele-vant to health outcomes. To the extent that thisis the case, each aspect of sleep can become a“lever arm” in neuroscience to perpetuate goodhealth or improve disease-related outcomes.4) Sleep health may represent a pathway forreducing health disparities. Structural bar-riers, working independently or collectively, areknown to have adverse effects on sleep, withlikely effects on mental and physical health out-comes that enhance racial and ethnic dis-parities in health care. Reductions in healthdisparities may be aided with community-level engagement, investments in social ser-vices, and data-driven policies that (i) increaseawareness of the importance of sleep, (ii) creategreater vigilance for primary sleep disorders,and (iii) encourage discussion of sleep prob-lems with medical professionals. Public cam-paigns such as these offer the opportunity forsleep neuroscience to make a tangible differ-ence in the day-to-day lives of people in greatestneed of help.5) Sleep is becoming easier and less expen-sive to assess in the real world. The evolutionof sleep measurement outside the confines ofthe laboratory presents many opportunities toharness an individual’s own data in the serviceof personalized medical approaches that canimprove the ease with which a person’s sleepis conceptualized in relation to their health.Artificial intelligence and other big-data ana-lytics can also examine sleep at the cohort orpopulation scale, thus improving the availa-bility and utility of data gathered across multi-ple naturalistic contexts (104).

      This section mentions about how might sleep research transform health care in the future, The idea of bedroom as a treatment site is really fascinating, which suggest that improving sleep could increase the effect of intervention for chronic diseases and neurodegenerative disorders. To integrate sleep in NIH guideline is essential, we need to work on promoting sleep as a health care metric along with blood pressure and heartbeat rate. Additionally, AI might help a lot on health disparities and personalizing care.

    2. Many studies have describedthe neurophysiology that contributes to sleepregulation, including the neuroanatomy of sleepand arousal-promoting circuitry (1); the dif-fuse, interconnected neurotransmitter systemsthat transition between non–rapid eye move-ment sleep (NREM), REM sleep, and wakefulness(2); and the core molecular clock mechanismand circadian pacemaker activity within thebrain (3). Additional work has delineated howsleep serves as a prerequisite for optimizingthe performance of critical biological func-tions, including those related to memory (4),waste clearance from the brain (5), and nu-trient metabolism (6).

      This first passage introduces us the neurophysiology and neuroanatomy, and it describes the difficult systems that in charge of sleep, and it is linked to our memory, clearing waste from brain and nutrient metabolism, so I was just wondering could improving sleep habitat helps us with better memory and brain function?

    1. Emouvante critique de Brague.

      1) un gros paquet d'insultes: islamophobes (considés comme) les Urvoy et Brague lui même. "ses fantasmes, de ses erreurs parfois et de sa mauvaise foi souvent." "Rémi Brague enrobe les poncifs les plus éculés sur l’islam, qu’il ressert sans la moindre originalité, avec une apparence savante."

      La déqualification des époux Urvoy universitaires spécialistes de l'islam reconnus, ayant démythologisé Al Andalous et son "multiculturalisme" et bien leur qualification d'"islamophobe" signe son fréro. Voilà c'est fait. On se contentera donc de répondre de même: défenseur raciste, hypocrite et prétentieux de l'insupportable.

      2) Les détails. a) les "sciences" islamiques ilm el-khawâtîr la sciences de pensées, traditionnellement associées aux élaborations spirituelles, à la mystique et certainement pas à ce qu'on appelle la psychologie ou alors de manière indirecte. Toutes ces "sciences" datent de l'an mille, et les sciences "objectives" sont antérieures à la grande fermeture du XIIIème siècle, science dont le rapport à l'islam est rien moins que lointain. L'astronomie arabe (disons plutôt persane du moyen âge) n'est pas musulmane et ne doit rien au coran, pas plus que l'algèbre...<br /> L'appropriation tardive de ces savoirs moyen âgeux par des berbères se fantasmant arabes pour éviter un déclassement problématique reste ce qu'il est: pitoyable.

      b) Ibn Hazm. L'auteur du traité poétique "le collier de la colombe" bien qu'accusé de mutazilisme, la doctrine qui voulait imposer la raison partout et qui fut réfutée pour cela, est cité à ce sujet et établit précisément l'asservissement de la raison en théologie à la révélation coranique. La citation est pertinente. Le zahirisme n'accorde pas une moindre place à la raison mais réfute l'analogie et Ibn Hazm reste un docteur important de l'islam.

      De manière générale, la statégie qui consiste à réfuter toute citation islamique gênante par son attribution à un partisan d'une école nécessairement non représentative de l'"islam global" est bien connue du frère musulman moyen. Pas vu pas pris.

      c) Shah Kazemi, islamologue, est chiite et écrit des ouvrages sur l'imam Ali et sa spirituaité. Ne pas le référencer est coupable, certes... Seyyed Hussein Nasr iranien réfugié aux Usa, et pourquoi pas Gilbert Bourdin dont l'oubli est au moins autant coupable ?

      Le name dropping de tout obscur nom oriental , tel celui de abdul al azherd fait rire le mécréant...

      d) Nawawi ne contredit en rien Brague, n'évoquant pas spécifiquement les dhimmis dans ses 40 hadiths. L'indulgence générale envers les dhimmis est une vaste blague raciste et méprisante. La dhimma comme "sauvegarde" est tout simplement risible quand elle cherche à ne pas passer pour ce qu'elle est: une discrimination.

      Les laboureurs ne sont PAS exemptés de la zakat. C'est simple. Il l'étaient d'une forme spéciale c'est tout.

      e) les 4 écoles reconnaissent la polygamie et la monogamie est recommandée par le Coran lui même ! Quand à l'autorisation de troncher ses esclaves, elle est claire...

      f) Le verset de la tolérance, pont aux ânes hypocrite, : Plus de contrainte dans la religion maintenant que le vrai se distingue de l’erreur. capito pepito ? La citation de Qutb illustre parfaitement l'ambiguité constitutive de la chose...

      g) le califat et son interprétation est historiquement fondée, et qualifier de manière insultante la thèse relève du (1).

      h) Brague est trop humble et son humilité a trompé le fréro: l'orthodoxie continue de l'islam est bien celle qu'il décrit, hélas et ne pas le voir, c'est l'accuser ... d'islamophobie.

      i) le soufisme est parfaitement caractérisé: 80 % de l'islam le rejette et avec force. Le "cinquième" c'est 20%... Le soufisme est bien profondément réactionnaire de manière générale, et adossé sur une stricte orthodoxie, pour mieux se faire excuser son mysticisme, profondément rejeté par l'islam juridique.

      j) se contenter de rejeter le wahhabisme comme le fait Al Azhar de Daech (en recommandant de crucifier les djihadistes, suprême forme de foutage de gueule, qui plus est citée par le monsieur , pas dégouté) est parfaitement ridicule.

      k) kazemi est donc la référence absolue... voir https://philitt.fr/2018/10/20/daoud-riffi-en-islam-lintolerance-est-lexception-face-a-une-tolerance-fondamentale-1-2/

      Un disciple de Martin Lings, britannique des années 30, converti à l'islam soufi et sectateur de Guénon...

      l) suspecter Brague d'ignorer la différence entre fiqh et Sharia, sachant que le coran et donc dieu est bien le législateur suprême est un foutage de gueule cynique absurde. Le fréro se mord les couilles, cela impressionne. Rappelons aussi que la sharia INCLUT le fiqh qui n'est absolument pas une "interprétation" de la shariah !

      La citation de Linant de Bellefonds , qui creusa le canal de Suez, est décisive pour apprécier la vraie nature du fiqh ! A hurler de rire ! C'est donc lui qui "prouve" que la raison en islam a tout réglé...

      Le fiqh (la doctrine des fuqaha) est une jurisprudence qui déduit un droit (heureusement non positif, sinon cela serait terrible) des source islamiques. Ca va, vous suivez?

      "libre réflexion sur les fondements" ? Ah bon ?

      m) le droit "naturel" que serait la shariah. Strauss et Villey font partie de ceux qui critiquent l'abandon moderniste de loi naturelle transcendant la loi positive et AUSSI l'interprétation du droit naturel comme seul droit de l'individu hors du contexte de l'Etat. Les citer comme des acquis est symptomatique d'une culture superficielle, celle d'un formé aux écoles multiculturelles fréristes.

      De manière générale, la manière sentencieuse méprisante, et pour tout dire raciste dont un arabo mes couilles fait la leçon à des mécréants en les insultant est tout bonnement insupportable.

      Ibn Arabi ne distingue pas des "voies" mais des aspects, l'ésotérique et l'exotérique, zahir et batir. La conception personnelle du monsieur, d'inspiration vaguement soufie et sans doute à moitié chiite n'est en rien une analyse globale de l'infection globale qu'est l'islam, la suffisance fidéique avec laquelle il cherche à l'imposer de manière méprisante et prétentieuse est merdique et insupportable.

    1. Reviewer #2 (Public review):

      This is an interesting paper from Alonso-Caraballo and colleagues that examines the influence of opioid use, abstinence, and sex on paraventricular thalamus (PVT) to nucleus accumbens shell (NAcSh) medium spiny neurons circuit physiology. The authors first find that prolonged abstinence from extended access to oxycodone self-administration leads to profoundly increased cue-induced reinstatement in females. Next, they found that prolonged abstinence increased PVT-NAcSh MSN synaptic strength, an effect that was likely due to presynaptic adaptation (paired-pulse ratio was decreased in both sexes).

      While this paper is certainly interesting, and well-written, and the experiments seem to be well performed, the behavioral and physiological effects observed are somewhat divorced. Specifically, what accounts for the heightened relapse in females? Since no opioid-related sex differences were observed in PVT-NAcSh neurophysiology, it is unclear how the behavioral and neurophysiological data fit together. Furthermore, the lack of functional manipulation of PVT-NAcSh circuitry leaves one to wonder if this circuit is even important for the behavior that the authors are measuring. I would be more positive about this study if the authors were able to resolve either of the two issues noted above.

      I also noted more moderate weaknesses that the authors should consider:

      (1) There are insufficient animals in some cases. For example, in Figure 4, the Male Saline 14-day abstinence group (n = 3 rats) has less than half of the excitability as compared to the Male Saline 1-day abstinence group (n = 7 rats). This is likely due to variance between animals and, possibly, oversampling. Thus, more rats need to be added to the 14-day abstinence group. Additionally, the range of n neurons/rat should be reported for each experiment to ensure readers that oversampling from single animals is not occurring.

      (2) The IPSC data, for example in Figure 4, is one of the more novel experiments in the manuscript. However, it is quite challenging to see the difference between males and females, saline and oxycodone, at low stimulation intensities within the graph. Authors should expand this so that reviewers/readers can see those data, especially considering other work suggesting that PVT synaptic input onto select NAc interneurons is disrupted following opioid self-administration. Additional comment: It's also interesting that the IPSC amplitude seems to be maximal at ~2mW of light, whereas ~11 mW is required to evoke maximal EPSC amplitude. It would be interesting to know the authors' thoughts on why this may be.

      (3) There is an inadequate description of what has been done to date on the PVT-NAc projection regarding opioid withdrawal, seeking, disinhibition, and the effects on synaptic physiology therein. For example, a critical paper, Keyes et al., 2020 Neuron, is not cited. Additionally, Paniccia et al., 2024 Neuron is inaccurately cited and insufficiently described. Both manuscripts should be described in some detail within the introduction, and the findings should be accurately contextualized within the broader circuit within the discussion.

      (4) Related to the above, the authors should provide a more comprehensive description of how PVT synapses onto cell-type specific neurons in the NAc which expands beyond MSNs, especially considering that PVT has been shown to influence drug/opioid seeking through the innervation of NAc neurons that are not MSNs. For example, see PMIDs 33947849, 36369508, 28973852, 38141605.

    1. Author response:

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

      Public Reviews:

      Reviewer #1 (Public review): 

      In this manuscript, the role of orexin receptors in dopamine transmission is studied. It extends previous findings suggesting an interplay of these two systems in regulating behaviour by first characterising the expression of orexin receptors in the midbrain and then disrupting orexin transmission in dopaminergic neurons by deleting its predominant receptor, OX1R (Ox1R fl/fl, DatCre tg/wt mice). Electrophysiological and calcium imaging data suggest that orexin A acutely and directly stimulates SN and VTA dopaminergic neurons, but does not seem to induce c-Fos expression. Behavioural effects of depleting OX1R from dopaminergic neurons includes enhanced noveltyinduced locomotion and exploration, relative to littermate controls (Ox1R fl/fl, Dat-Cre wt/wt). However, no difference between groups is observed in tests that measure reward processing, anxiety, and energy homeostasis. To test whether depletion of OX1R alters overall orexin-triggered activation across the brain, PET imaging is used in OX1R∆DAT knockout and control mice. This analysis reveals that several regions show a higher neuronal activation after orexin injection in OX1R∆DAT mice, but the authors focus their follow up study on the dorsal bed nucleus of the stria terminalis (BNST) and lateral paragigantocellular nucleus (LPGi). Dopaminergic inputs and expression of dopamine receptors type-1 and -2 (DRD1 & DRD2) is assessed and compared to control demonstrating moderate decrease of DRD1 and DRD2 expression in BNST of OX1R∆DAT mice and unaltered expression of DRD2, with absence of DRD1 expression in LPGi of both groups. Overall, this study is valuable for the information it provides on orexin receptor expression and function on behaviour and for the new tools it generated for the specific study of this receptor in dopaminergic circuits. 

      Strengths: 

      The use of a transgenic line that lacks OX1R in dopamine-transporter expressing neurons is a strong approach to dissect the direct role of orexin in modulating dopamine signalling in the brain. The battery of behavioural assays to study this line provides a valuable source of information for researchers interested in the role of orexin in animal physiology. 

      We thank the reviewer for summarizing the importance and significance of our study. 

      Weaknesses: 

      This study falls short in providing evidence for an anatomical substrate of the altered behaviour observed in mice lacking orexin receptor subtype 1 in dopaminergic neurons. How orexin transmission in dopaminergic neurons regulates the expression of postsynaptic dopamine receptors (as observed in BNST of OX1R<sup>∆DAT</sup> mice) is an intriguing question poorly discussed. Whether disruption of orexin activity alters dopamine release in target areas is an important point not addressed. 

      We identified dopaminergic fibers and dopamine receptors in the dBNST and LPGi, suggesting anatomical basis for dopamine neurons to regulate neural activity and receptor expression levels in these areas. PET imaging scan and c-Fos staining revealed that Ox1R signaling in dopaminergic cells regulates neuronal activity in dBNST and LPGi. The expression levels of Th were unchanged in both regions. Dopamine receptor 2 (DRD2), but not DRD1, is expressed in LPGi. The deletion of Ox1R in DAT-expressing cells did not affect DRD2 expression in LPGi. The expression levels of DRD1 and DRD2 were decreased or showed a tendency to decrease in dBNST. 

      We included the comments in the discussion in this revised manuscript (lines 308-312): ‘The expression levels of Th were not altered in dBNST or LPGi by Ox1R deletion in dopaminergic neurons. It remains unclear whether dopamine release is affected in these regions. It is possible that either the dopaminergic regulation of neuronal activity or the changes in dopamine release could lead to the decreased expression of dopamine receptors in dBNST.’

      Reviewer #2 (Public review): 

      Summary: 

      This manuscript examines expression of orexin receptors in midbrain - with a focus on dopamine neurons - and uses several fairly sophisticated manipulation techniques to explore the role of this peptide neurotransmitter in reward-related behaviors. Specifically, in situ hybridization is used to show that dopamine neurons predominantly express orexin receptor 1 subtype and then go on to delete this receptor in dopamine transporter-expressing using a transgenic strategy. Ex vivo calcium imaging of midbrain neurons is used to show that, in the absence of this receptor, orexin is no longer able to excite dopamine neurons of the substantia nigra. 

      The authors proceed to use this same model to study the effect of orexin receptor 1 deletion on a series of behavioral tests, namely, novelty-induced locomotion and exploration, anxiety-related behavior, preference for sweet solutions, cocaine-induced conditioned place preference, and energy metabolism. Of these, the most consistent effects are seen in the tests of novelty-induced locomotion and exploration in which the mice with orexin 1 receptor deletion are observed to show greater levels of exploration, relative to wild-type, when placed in a novel environment, an effect that is augmented after icv administration of orexin. 

      In the final part of the paper, the authors use PET imaging to compare brain-wide activity patterns in the mutant mice compared to wildtype. They find differences in several areas both under control conditions (i.e., after injection of saline) as well as after injection of orexin. They focus in on changes in dorsal bed nucleus of stria terminalis (dBNST) and the lateral paragigantocellular nucleus (LPGi) and perform analysis of the dopaminergic projections to these areas. They provide anatomical evidence that these regions are innervated by dopamine fibers from midbrain, are activated by orexin in control, but not mutant mice, and that dopamine receptors are present. Thus, they argue these anatomical data support the hypothesis that behavioral effects of orexin receptor 1 deletion in dopamine neurons are due to changes in dopamine signaling in these areas.

      Strengths: 

      Understanding how orexin interacts with the dopamine system is an important question and this paper contains several novel findings along these lines. Specifically:

      (1) Distribution of orexin receptor subtypes in VTA and SN is explored thoroughly.

      (2) Use of the genetic model that knocks out a specific orexin receptor subtype from dopaminetransporter-expressing neurons is a useful model and helps to narrow down the behavioral significance of this interaction.  

      (3) PET studies showing how central administration of orexin evokes dopamine release across the brain is intriguing, especially that two key areas are pursued - BNST and LPGi - where the dopamine projection is not as well described/understood. 

      We thank the reviewer for summarizing the importance and significance of our study. 

      Weaknesses: 

      The role of the orexin-dopamine interaction is not explored in enough detail. The manuscript presents several related findings, but the combination of anatomy and manipulation studies do not quite tell a cogent story. Ideally, one would like to see the authors focus on a specific behavioral parameter and show that one of their final target areas (dBNST or LPGi) was responsible or at least correlated with this behavioral readout. 

      We agree that exploring the orexin-dopamine interactions in more detail and focusing on the behavioral impact of their final target areas (e.g., dBNST or LPGi), would provide valuable data. While we are very interested in pursuing these studies, the aim of the present manuscript is to provide an overview of the behavioral roles of orexin-dopamine interaction and to propose some promising downstream pathways in a relatively broad and systematic manner. 

      In many places in the Results, insufficient explanation and statistical reporting is provided. Throughout the Results - especially in the section on behavior although not restricted to this part - statements are made without statistical tests presented to back up the claims, e.g., "Compared to controls, Ox1R<sup>ΔDAT</sup> 143 mice did not show significant changes in spontaneous locomotor activity in home cages" (L143) and "In a hole-board test, female Ox1RΔDAT mice showed increased nose pokes into the holes in early (1st and 2nd) sessions compared to control mice" (L151). In other places, ANOVAs are mentioned but full results including main effects and interactions are not described in detail, e.g., in F3-S3, only a single p-value is presented and it is difficult to know if this is the interaction term or a post hoc test (L205). These and all other statements need statistics included in the text as support. Addition of these statistical details was also requested by the editor. 

      We submitted all our source data as Excel spreadsheets to eLife during our first-round revision, and the full statistics, such as main effects and interactions, are presented alongside the source data in the respective spreadsheets. We thank the reviewer for pointing out our lack of clarity in the manuscript. In this revised manuscript, we included the statistical details of ANOVAs mentioned above in the figure legends. In the figure legends, we also explained that the full statistics were provided alongside the source data in the supplementary materials.

      In the presentation of reward processing this is particularly important as no statistical tests are shown to demonstrate that controls show a cocaine-induced preference or a sucrose preference. Here, one option would be to perform one-sample t-tests showing that the data were different to zero (no preference). As it is, the claim that "Both of the control and Ox1RΔDAT groups showed a preference for cocaine injection" is not yet statistically supported. 

      We thank the reviewer for the suggestions. We have added the one-sample t-test results in this revised manuscript (Figure 2–figure supplement 4, lines 171 - 183). 

      Recommendations for the authors:

      Reviewer #2 (Recommendations for the authors): 

      Can the authors comment on overlap between DAT and Ox1R in brain areas outside VTA/SN? Is there any? 

      We only focused on the expression patterns of orexin receptors in VTA/SN, and we did not examine other brain regions. Additionally, little is known from the literature about the expression of Ox1R in DAT-expressing cells in brain areas outside VTA/SN. Further analysis is necessary to answer this question. We have added the comment in our discussion (lines 243 - 344).

      For the Ca2+ imaging experiment, it is unclear to me why the authors do not show all the neurons (almost 160 in total) and just select 5 neurons to show for each condition. 

      Heat maps of all recorded neurons are now shown in Figure 1—figure supplement 4.

      There are other claims that still require a statistical justification to be included in addition to the passages on behavior mentioned above, e.g., "Increasing the orexin A concentration to 300 nM further increased [Ca2+]i" (L118). 

      Authors should ensure that all such claims are either presented with a statistical test or are phrased differently, e.g. "Visual inspection of data suggested that there was a further increase...". In addition, when an ANOVA is conducted, full results including main effects and interactions should be described. 

      We emphasize now our statement that ALREADY 100 nM orexin A significantly increased [Ca<sup>2+</sup>]i levels (lines 117 - 118).

      We submitted all our source data as Excel spreadsheets to eLife during our first-round revision, and the full statistics, such as main effects and interactions, are presented alongside the source data in the respective spreadsheets. For clarity, we chose to include only the key statistical information in the main text and figures. We thank the reviewer for pointing this out. In this revised manuscript, we have emphasized in each figure legend: ‘Source data and full statistics are provided in the supplementary materials’.

      Typos in figure captions  

      F2-S1 - spontanous 

      F3-S2 - intrest 

      We apologize for the typos. We have corrected them in this revised manuscript.

      Editor's note: 

      Should you choose to revise your manuscript, please include full statistical reporting including exact p-values wherever possible alongside the summary statistics (test statistic and df) and 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05. 

      We submitted all our source data as Excel spreadsheets to eLife during our first-round revision, and the full statistics, such as test statistics, df and 95% confidence intervals, are presented alongside the source data in the respective spreadsheets. We thank the editor’s note. In this revised manuscript, we have included more statistical information in the main text and figure legends (see our response to reviewer #2). In the figure legends, we also explained that the full statistics were provided alongside the source data in the supplementary materials. In addition, we also uploaded the source data and full statistics in the bioRxiv before we upload this revised manuscript to eLife.

  5. notebooksharing.space notebooksharing.space
    1. This approach refits each model, leaving out one hectare of field plot data at a time (four subplots).

      I know there are limitations of what is doable with field plot data, and I think this is a good start. However, I would probably either increase the spatial fold size to 4 ha, or do a buffered leave one out cross validation, i.e. remove one 0.25 ha pixel each and its entire neighbourhood of 8 cells (9 * 0.25 ha = 2.25 ha). Realistically, AGB will be correlated over distances larger than this, so testing a 5 x 5 window (25 * 0.25 ha = 6.25 ha) or 7 x 7 window would be even better.

      Alternatively, at plots as large as the 50 ha BCI plot, it would also make sense to subdivide into 10 5ha or even 5 10 ha folds, and see how well the models do there.

    1. 强调简洁和功能性: 相比其他历史主义风格,如新哥特式或新文艺复兴式,“圆形拱券风格”更注重建筑的简洁和功能性,避免过度的装饰。

      你提出的这句话准确地概括了“圆形拱券风格”(Rundbogenstil)相对于其他历史主义风格(如新哥特式或新文艺复兴式)的一个重要特点:强调简洁和功能性,避免过度装饰。为了更详细地解释这一点,我们可以从以下几个方面进行阐述:

      1. 历史主义建筑的背景:

      19世纪是历史主义建筑盛行的时期。历史主义建筑师们从不同的历史风格中汲取灵感,创造出各种复兴风格,例如:

      • 新哥特式: 复兴中世纪哥特式建筑的风格,强调尖拱、飞扶壁、高耸的立面和繁复的装饰。
      • 新文艺复兴式: 复兴文艺复兴时期建筑的风格,强调古典柱式、对称的布局和精美的细节。
      • 新巴洛克式: 复兴巴洛克时期建筑的风格,强调曲线、动态感和华丽的装饰。

      这些复兴风格通常非常注重装饰,力求在建筑中重现历史风格的繁复和华丽。

      2. “圆形拱券风格”的特点:

      与上述复兴风格不同,“圆形拱券风格”更加注重简洁和功能性,这主要体现在以下几个方面:

      • 简洁的造型: “圆形拱券风格”的建筑通常采用简单的几何形体,例如方形、矩形和圆形。建筑的立面也相对简洁,没有过多的曲线和装饰。
      • 强调结构和功能: 建筑师们更加关注建筑的结构合理性和功能实用性。例如,火车站等交通建筑采用“圆形拱券风格”时,会充分考虑人流的疏散、空间的利用和交通的效率。
      • 避免过度装饰: 虽然“圆形拱券风格”也借鉴了一些历史风格的元素,例如圆形拱券、柱子和壁柱等,但它避免了过度装饰,例如繁复的雕塑、精细的线脚和华丽的色彩。装饰通常比较简洁,例如简单的几何图案、盲拱和砖砌纹样等。
      • 材料的诚实运用: “圆形拱券风格”的建筑师们倾向于诚实地运用建筑材料,例如砖、石和木材,并尽可能地展现材料的自然质感。

      3. “圆形拱券风格”与其他历史主义风格的比较:

      • 与新哥特式的比较: 新哥特式建筑追求高耸、轻盈和繁复的装饰,而“圆形拱券风格”则追求稳重、简洁和功能性。
      • 与新文艺复兴式的比较: 新文艺复兴式建筑强调古典柱式、对称的布局和精美的细节,而“圆形拱券风格”则更加注重简洁的造型和功能的实用性。
      • 与新巴洛克式的比较: 新巴洛克式建筑追求曲线、动态感和华丽的装饰,而“圆形拱券风格”则更加注重简洁的几何形体和朴素的风格。

      4. “圆形拱券风格”的代表作品:

      卡尔斯鲁厄火车总站是“圆形拱券风格”的典型代表。这座建筑采用了大量的圆形拱券,但整体造型简洁,没有过多的装饰。建筑的内部空间也充分考虑了交通的功能需求,例如宽敞的候车大厅和便捷的通道。

      总结:

      “圆形拱券风格”在19世纪的历史主义建筑中独树一帜,它更加注重简洁和功能性,避免了其他复兴风格的过度装饰。这种风格的出现,反映了当时建筑界对功能和实用性的重视,也为后来的现代建筑的发展奠定了一定的基础。

      通过以上解释,相信你对“圆形拱券风格”强调简洁和功能性的特点有了更深入的理解。

    1. 13世纪是德国哥特式建筑发展的重要时期,建筑师们受法国哥特式建筑的影响,同时也发展出了具有本土特色的风格。13世纪是德国哥特式建筑发展的重要时期,从罗曼式风格逐渐过渡到成熟的哥特式风格。这个时期的建筑师们受到法国哥特式建筑的影响,但也发展出了自己的特色。

      你提供的这段文字准确地指出了13世纪是德国哥特式建筑发展的重要时期,并且强调了德国哥特式建筑在受到法国影响的同时,也发展出了本土特色。要详细解释德国本土的哥特式建筑特色,我们需要从以下几个方面进行阐述:

      1. 法国哥特式建筑的影响:

      首先,我们需要承认法国是哥特式建筑的发源地,其早期和盛期哥特式建筑对欧洲其他地区产生了深远影响,德国也不例外。法国哥特式建筑的主要特点包括:

      • 尖拱券和肋拱顶的广泛应用: 这使得建筑可以建造得更高更轻盈。
      • 飞扶壁系统的成熟: 有效地平衡了拱顶的推力,使得墙面可以开设更大的窗户。
      • 高耸的立面和尖塔: 营造出向上升腾的视觉效果。
      • 精美的雕塑和彩色玻璃窗: 增强了建筑的装饰性和艺术性。

      德国的早期哥特式建筑在很大程度上借鉴了法国的这些特点。

      2. 德国本土哥特式建筑的特色:

      虽然受到法国的影响,但德国建筑师并没有完全照搬法国的风格,而是在此基础上结合了本土的传统和审美,发展出了具有自身特色的哥特式建筑,主要体现在以下几个方面:

      • 西侧双塔的流行: 德国的许多哥特式教堂在西立面都建有两座高塔,这与法国一些只有单塔或没有高塔的教堂有所不同,例如科隆大教堂就是典型的例子。这种双塔设计增强了建筑的庄严感和视觉冲击力。
      • 厅式教堂的流行(Hallenkirche): 与法国常见的高耸的中殿和较低的侧廊不同,德国的厅式教堂中殿和侧廊的高度接近或相等,形成一个宽敞的内部空间。这种布局使得教堂内部更加开阔明亮,也更适合大型集会。
      • 砖砌建筑的广泛应用: 德国北部和波罗的海沿岸地区盛产砖块,因此在这些地区的哥特式建筑中,砖砌结构得到了广泛应用,形成了独特的“砖砌哥特式”(Backsteingotik)风格。这种风格的建筑通常使用红砖砌筑,并运用各种砖砌技巧来创造装饰效果,例如几何图案、盲拱等。
      • 相对保守的比例和装饰: 与法国哥特式建筑的纤细和繁复相比,德国哥特式建筑的比例通常更加稳重,装饰也相对简洁。
      • 强调内部空间的连续性: 德国哥特式建筑更注重内部空间的连续性和整体感,而不是像法国哥特式那样强调各个部分的独立性。

      3. 13世纪德国哥特式建筑的过渡性:

      你提到的“从罗曼式风格逐渐过渡到成熟的哥特式风格”非常重要。13世纪的德国哥特式建筑正处于一个过渡时期,因此我们可以看到一些建筑既保留了罗曼式建筑的特征,又开始采用哥特式建筑的新元素。例如,一些教堂的拱顶虽然采用了尖拱,但仍然保留了较为厚重的墙体和较小的窗户。

      4. 重要实例:

      • 科隆大教堂(Kölner Dom): 德国最著名的哥特式教堂,也是世界上最高的教堂之一。它采用了典型的法国哥特式风格,但也融入了一些德国本土的元素,例如西侧的双塔。
      • 弗莱堡大教堂(Freiburger Münster): 另一座重要的德国哥特式教堂,以其精美的尖塔和彩色玻璃窗而闻名。
      • 吕贝克圣玛丽教堂(Marienkirche in Lübeck): 砖砌哥特式的杰出代表,展示了砖砌建筑的独特魅力。

      总结:

      13世纪是德国哥特式建筑发展的重要时期,建筑师们在受到法国哥特式建筑影响的同时,也发展出了具有本土特色的风格,主要体现在西侧双塔的流行、厅式教堂的流行、砖砌建筑的广泛应用、相对保守的比例和装饰以及强调内部空间的连续性等方面。这些特色使得德国哥特式建筑在欧洲哥特式建筑中独树一帜。

      为了更深入地了解德国哥特式建筑,建议搜索以下关键词:

      • Deutsche Gotik (德国哥特式)
      • Backsteingotik (砖砌哥特式)
      • Hallenkirche (厅式教堂)
      • Kölner Dom (科隆大教堂)
      • Marienkirche Lübeck (吕贝克圣玛丽教堂)

      通过这些关键词,可以找到更多相关的图片、文献和资料。

    1. Allowances....● The three lowest scores will be excluded from your classroom preparation quizzes (Bundle 1).● The two lowest scores will be excluded from your classroom participation activities (Bundle 2).● You have the opportunity to revise and resubmit one question from Mini-project 1 within oneweek after your initial submission is returned to you (Bundle 4).6

      This is very helpful. Thank you!

    1. 7、中厅的朴素与圣坛的华丽反差极大,中厅与侧廊的架构打破了传统古典建筑的平

      你提供的这段文字描述了罗马式建筑的一些特征,其中最后一点“中厅的朴素与圣坛的华丽反差极大,中厅与侧廊的架构打破了传统古典建筑的平衡感”需要更详细的解释。我们先整体回顾一下罗马式建筑的特征,然后再重点解释你提出的这一点。

      罗马式建筑的特征:

      1. 厚重的墙体和连续的小券: 罗马式建筑继承了古罗马建筑的厚重感,墙体非常厚实,以支撑沉重的拱顶。墙面上常使用连续的小券(连续的小型拱券),洞口则采用同心的多层小圆券,这既减轻了视觉上的沉重感,也增强了结构的稳定性。
      2. 半圆形拱券的广泛应用: 半圆形拱券是罗马式建筑最显著的特征之一,几乎所有的门、窗、拱廊和拱顶都使用半圆形拱券结构。
      3. 扶壁和肋骨拱: 为了平衡拱顶产生的巨大横向推力,罗马式建筑采用了扶壁(支撑墙体的外部结构)和肋骨拱(加强拱顶的骨架结构)。早期的罗马式建筑扶壁较为简单,突出墙体不多,后期的扶壁则逐渐发展成更复杂的结构。
      4. 西侧的钟楼: 罗马式教堂通常在西侧设有一到两座钟楼,有时在拉丁十字的交叉点和横厅上方也会设置钟楼。
      5. 中厅柱子的韵律排列: 中厅的柱子通常以大小交替的方式排列,形成一种韵律感。
      6. 较小的窗户和阴暗的内部: 由于厚重的墙体和拱顶结构,罗马式建筑的窗户相对较小,导致内部光线较暗,营造出一种神秘肃穆的氛围。
      7. 中厅的朴素与圣坛的华丽反差,以及中厅与侧廊架构打破古典平衡: 这是本段解释的重点。

      详细解释“中厅的朴素与圣坛的华丽反差极大,中厅与侧廊的架构打破了传统古典建筑的平衡感”:

      • 中厅的朴素与圣坛的华丽反差极大:
        • 中厅: 罗马式教堂的中厅通常设计得相对朴素简洁,墙面和柱子装饰较少,主要强调空间的体量感和纵深感。目的是引导信徒的视线向前,集中于圣坛。
        • 圣坛: 圣坛是教堂中最神圣的地方,是举行宗教仪式和放置祭品的地方。罗马式教堂的圣坛区域通常装饰得非常华丽,使用精美的雕刻、绘画、镶嵌工艺和贵重材料(如黄金、宝石等),以突出其重要性和神圣性。这种朴素与华丽的对比,旨在强调宗教仪式的神圣性和庄严感。
      • 中厅与侧廊的架构打破古典平衡:
        • 古典建筑的平衡: 古典建筑,如古希腊和古罗马建筑,强调对称、平衡和和谐。建筑的各个部分之间存在清晰的比例关系,例如柱子的高度和间距、建筑的宽度和长度等。
        • 罗马式建筑的结构特点: 罗马式教堂的中厅通常比侧廊高很多,形成明显的高差。中厅的拱顶也比侧廊的拱顶高大。这种高差和拱顶的变化打破了古典建筑强调的水平平衡感,创造出一种向上升腾的动势,引导人们的视线向上,象征着对天堂的向往。此外,中厅和侧廊的柱子大小和间距也可能存在差异,进一步打破了古典建筑的规整性。

      总结:

      罗马式建筑在中厅和圣坛的处理上,以及中厅与侧廊的架构上,都体现出与古典建筑不同的特点。中厅的朴素与圣坛的华丽形成鲜明对比,突出了宗教仪式的神圣性;中厅与侧廊的高差和拱顶的变化打破了古典建筑的平衡感,创造出一种向上升腾的动势,这些都是罗马式建筑的重要特征,也使其与之前的建筑风格区分开来。

      理解这些特征有助于我们更好地辨别罗马式建筑,并欣赏其独特的艺术魅力。

    1. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This study sought to reveal the potential roles of m6A RNA methylation in gene dosage regulatory mechanisms, particularly in the context of aneuploid genomes in Drosophila. Specifically, this work looked at the relationships between the expression of m6A regulatory factors, RNA methylation status, classical and inverse dosage effects, and dosage compensation. Using RNA sequencing and m6A mapping experiments, an in-depth analysis was performed to reveal changes in m6A status and expression changes across multiple aneuploid Drosophila models. The authors propose that m6A methylation regulates MOF and, in turn, deposition of H4K16Ac, critical regulators of gene dosage in the context of genomic imbalance.

      Strengths:

      This study seeks to address an interesting question with respect to gene dosage regulation and the possible roles of m6A in that process. Previous work has linked m6A to X-inactivation in humans through the Xist lncRNA, and to the regulation of the Sxl in flies. This study seeks to broaden that understanding beyond these specific contexts to more broadly understand how m6A impacts imbalanced genomes in other contexts.

      Weaknesses:

      The methods being used particularly for analysis of m6A at both the bulk and transcript-specific level are not sufficiently specific or quantitative to be able to confidently draw the conclusions the authors seek to make. MeRIP m6A mapping experiments can be very valuable, but differential methylation is difficult to assess when changes are small (as they often are, in this study but also m6A studies more broadly). For instance, based on the data presented and the methods described, it is not clear that the statement that "expression levels at m6A sites in aneuploidies are significantly higher than that in wildtype" is supported. MeRIP experiments are not quantitative, and since there are far fewer peaks in aneuploidies, it stands to reason that more antibody binding sites may be available to enrich those fewer peaks to a larger extent. But based on the data as presented (figure 2D) this conclusion was drawn from RPKM in IP samples, which may not fully account for changing transcript abundances in absolute (expression level changes) and relative (proportion of transcripts in input RNA sample) terms.

      Methylated RNA immunoprecipitation followed by sequencing (MeRIP-seq) is a commonly used strategy of genome-wide mapping of m6A modification. This method uses anti-m6A antibody to immunoprecipitate RNA fragments, which results in selective enrichment of methylated RNA. Then the RNA fragments were subjected to deep sequencing, and the regions enriched in the immunoprecipitate relative to input samples are identified as m6A peaks using the peak calling algorithm. We identified m6A peaks in different samples by the exomePeak2 program and determined common m6A peaks for each genotype based on the intersection of biological replicates. Figure 2D shows the RPM values of m6A peaks in MeRIP samples for each genotype, indicating that the levels of reads in the m6A peak regions were significantly higher in the aneuploid IP samples than in wildtypes. When the enrichment of IP samples relative to Input samples (RPM.IP/RPM.Input) was taken into account, the statistics for all three aneuploidies were still significantly higher than those of the wildtypes (Mann Whitney U test p-values < 0.001). This analysis is not about changes in the abundance of transcripts, but from the MeRIP perspective, showing that there are relatively more m6A-modified reads mapped to the m6A peaks in aneuploidies than that in wildtypes. We hope to provide a possible explanation for the phenomenon that the quantitative changes of m6A peaks are not consistent with the overall m6A abundance trend. We have added the results of IP/Input in the main text, and revised the description in the manuscript to make it more precise to reduce possible misunderstandings.

      The bulk-level m6A measurements as performed here also cannot effectively support these conclusions, as they are measured in total RNA. The focus of the work is mRNA m6A regulators, but m6A levels measured from total RNA samples will not reflect mRNA m6A levels as there are other abundance RNAs that contain m6A (including rRNA). As a result, conclusions about mRNA m6A levels from these measurements are not supported.

      According to published articles, m6A levels of mRNA or total RNA can be detected by different methods (such as mass spectrometry, 2D thin-layer chromatography, etc.) in Drosophila cells or tissues [1-3]. We used the EpiQuik m6A RNA Methylation Quantification Kit, which is suitable for detecting m6A methylation status directly using total RNA isolated from any species such as mammals, plants, fungi, bacteria, and viruses. This kit has previously been used by researchers to detect the m6A/A ratio in total RNA [4, 5] or purified mRNA [6] from different species. Our pre-experiments showed that the enrichment of mRNA from total RNA did not appear to significantly affect the results of the detection of m6A levels.

      We extracted and purified mRNA from the heads of the control and MSL2 transgenic Drosophila to verify our conclusion. mRNA was isolated from total RNA using the Dynabeads mRNA purification kit (Invitrogen, Carlsbad, CA, USA, 61006). It was showing a heightened abundance of m6A modification on mRNA as opposed to total RNA (Figure 7E,F; Figure 7—figure supplement 1G,H). Compared with control Drosophila, the abundance changes of m6A in mRNA and total RNA in MSL2 transgenic Drosophila are basically the same. These results supported the conclusions in our manuscript. In the MSL2 knockdown Drosophila, the m6A modification levels on mRNA mirrored those observed on total RNA, exhibiting a significant downregulation (Figure 7E; Figure 7—figure supplement 1G). The only difference is that no substantial difference in the m6A abundance on mRNA was detected between MSL2 overexpressed female and the control Drosophila (Figure 7F; Figure 7—figure supplement 1H). It is suggested that m6A modification in other types of RNA other than mRNA (e.g., lncRNA, rRNA) is not necessarily meaningless, which is the future research direction. We will also add discussions of this issue in the manuscript.

      (1) Lence T, et al. (2016) m6A modulates neuronal functions and sex determination in Drosophila. Nature 540(7632):242-247.

      (2) Haussmann IU, et al. (2016) m(6)A potentiates Sxl alternative pre-mRNA splicing for robust Drosophila sex determination. Nature 540(7632):301-304.

      (3) Kan L, et al. (2017) The m(6)A pathway facilitates sex determination in Drosophila. Nat Commun 8:15737.

      (4) Zhu C, et al. (2023) RNA Methylome Reveals the m(6)A-mediated Regulation of Flavor Metabolites in Tea Leaves under Solar-withering. Genomics Proteomics Bioinformatics 21(4):769-787.

      (5) Song H, et al. (2021) METTL3-mediated m(6)A RNA methylation promotes the anti-tumour immunity of natural killer cells. Nat Commun 12(1):5522.

      (6) Yin H, et al. (2021) RNA m6A methylation orchestrates cancer growth and metastasis via macrophage reprogramming. Nat Commun 12(1):1394.

      Reviewer #2 (Public Review):

      Summary:

      The authors have tested the effects of partial- or whole-chromosome aneuploidy on the m6A RNA modification in Drosophila. The data reveal that overall m6A levels trend up but that the number of sites found by meRIP-seq trend down, which seems to suggest that aneuploidy causes a subset of sites to become hyper-methylated. Subsequent bioinformatic analysis of other published datasets establish correlations between the activity of the H4K16 acetyltransferase dosage compensation complex (DCC) and the expression of m6A components and m6A abundance, suggesting that DCC and m6A can act in a feedback loop on each other. Overall, this paper uses bioinformatic trends to generate a candidate model of feedback between DCC and m6A. It would be improved by functional studies that validate the effect in vivo.

      Strengths:

      • Thorough bioinformatic analysis of their data.

      • Incorporation of other published datasets that enhance scope and rigor.

      • Finds trends that suggest that a chromosome counting mechanism can control m6A, as fits with pub data that the Sxl mRNA is m6A modified in XX females and not XY males.

      • Suggests this counting mechanism may be due to the effect of chromatin-dependent effects on the expression of m6A components.

      Weaknesses:

      • The linkage between H4K16 machinery and m6A is indirect and based on bioinformatic trends with little follow-up to test the mechanistic bases of these trends.

      Western blots were performed to detect H4K16Ac in Ythdc1 knockdown Drosophila and control Drosophila. Through quantitative analysis, it is demonstrated that H4K16Ac levels changed significantly in Ythdc1 knockdown Drosophila. Combined with the results of polytene chromosome immunostaining in third instar larvae, we found that Ythdc1 affects the expression of H4K16Ac in tissue- and developmental stage-specific manners. This specificity may be associated with the onuniformity and heterogeneity of RNA m6A modification characteristics, encompassing the tissue specificity, the developmental specificity, the different numbers of m6A sites in one transcript, the different proportions of methylated transcripts, et cetera [1-3].

      In addition, we found a set of ChIP-seq data (GSE109901) of H4K16ac in female and male Drosophila larvae from the public database, and analyzed whether H4K16ac is directly associated with m6A regulator genes. ChIP-seq is a standard method to study transcription factor binding and histone modification by using efficient and specific antibodies for immunoprecipitation. The results showed that there were H4K16ac peaks at the 5' region in gene of m6A reader Ythdc1 in both males and females. In addition, most of the genome sites where the other m6A regulator genes located are acetylated at H4K16 in both sexes, except that Ime4 shows sexual dimorphism and only contains H4K16ac peak in females. These results indicate that the m6A regulator gene itself is acetylated at H4K16, so there is a direct relationship between H4K16ac and m6A regulators. We have added these contents to the text.

      Our analysis of experimental outcomes and public sequencing data has shed light on the interaction of the m6A reader protein Ythdc1 with H4K16Ac. We appreciate your interest in the complex interplay between H4K16Ac and m6A modifications. We acknowledge the intricacy of this interaction and concur that it merits further investigation, potentially supported by additional experiments.

      In current submitted manuscript, it is mainly focused on the role of RNA m6A modification in genomes experiencing imbalance, and we are going to explore this complex interplay in subsequent work for sure.

      (1) Meyer, K. D., et al. (2012). Comprehensive analysis of mRNA methylation reveals enrichment in 3' UTRs and near stop codons. Cell, 149(7), 1635-1646.

      (2) Meyer, K. D., & Jaffrey, S. R. (2014). The dynamic epitranscriptome: N6-methyladenosine and gene expression control. Nature Reviews: Molecular Cell Biology, 15(5), 313-326.

      (3) Zaccara, S., Ries, R. J., & Jaffrey, S. R. (2019). Reading, writing and erasing mRNA methylation. Nature Reviews: Molecular Cell Biology, 20(10), 608-624.

      • The paper lacks sufficient in vivo validation of the effects of DCC alleles on m6A and vice versa. For example, Is the Ythdc1 genomic locus a direct target of the DCC component Msl-2 ? (see Figure 7).

      In order to study whether Ythdc1 genomic locus is a direct target of DCC component, we first analyzed a published MSL2 ChIP-seq data of Drosophila (GSE58768). Since MSL2 is only expressed in males under normal conditions, this set of data is from male Drosophila. According to the results, the majority (99.1%) of MSL2 peaks are located on the X chromosome, while the MSL2 peaks on other chromosomes are few. This is consistent with the fact that MSL2 is enriched on the X chromosome in male Drosophila [1, 2]. Ythdc1 gene is located on chromosome 3L, and there is no MSL2 peak near it. Similarly, other m6A regulator genes are not X-linked, and there is no MSL2 peak. Then we analyzed the MOF ChIP-seq data (GSE58768) of male Drosophila. It was found that 61.6% of MOF peaks were located on the X chromosome, which was also expected [3, 4]. Although there are more MOF peaks on autosomes than MSL2 peaks, MOF peaks are absent on m6A regulator genes on autosomes. Therefore, at present, there is no evidence that the gene locus of m6A regulators are the direct targets of DCC component MSL2 and MOF, which may be due to the fact that most MSL2 and MOF are tethered to the X chromosome by MSL complex under physiological conditions. Whether there are other direct or indirect interactions between Ythdc1 and MSL2 is an issue worthy of further study in the future.

      (1) Bashaw GJ & Baker BS (1995) The msl-2 dosage compensation gene of Drosophila encodes a putative DNA-binding protein whose expression is sex specifically regulated by Sex-lethal. Development 121(10):3245-3258.

      (2) Kelley RL, et al. (1995) Expression of msl-2 causes assembly of dosage compensation regulators on the X chromosomes and female lethality in Drosophila. Cell 81(6):867-877.

      (3) Kind J, et al. (2008) Genome-wide analysis reveals MOF as a key regulator of dosage compensation and gene expression in Drosophila. Cell 133(5):813-828.

      (4) Conrad T, et al. (2012) The MOF chromobarrel domain controls genome-wide H4K16 acetylation and spreading of the MSL complex. Dev Cell 22(3):610-624.

      Quite a bit of technical detail is omitted from the main text, making it difficult for the reader to interpret outcomes.

      (1) Please add the tissues to the labels in Figure 1D.

      Figure 1D shows the subcellular localization of FISH probe signals in Drosophila embryos. Arrowheads indicate the foci of probe signals. The corresponding tissue types are (1) blastoderm nuclei; (2) yolk plasm and pole cells; (3) brain and midgut; (4) salivary gland and midgut; (5) blastoderm nuclei and yolk cortex; (6) blastoderm nuclei and pole cells; (7) blastoderm nuclei and yolk cortex; (8) germ band. We have added these to the manuscript.

      (2) In the main text, please provide detail on the source tissues used for meRIP; was it whole larvae? adult heads? Most published datasets are from S2 cells or adult heads and comparing m6A across tissues and developmental stages could introduce quite a bit of variability, even in wt samples. This issue seems to be what the authors discuss in lines 197-199.

      In this article, the material used to perform MeRIP-seq was the whole third instar larvae. Because trisomy 2L and metafemale Drosophila died before developing into adults, it was not possible to use the heads of adults for MeRIP-seq detection of aneuploidy. For other experiments described here, the m6A abundance was measured using whole larvae or adult heads; material used for RT-qPCR analysis was whole larvae, larval brains, or adult heads; Drosophila embryos at different developmental stages were used for fluorescence in situ hybridization (FISH) experiments. We provide a detailed description of the experimental material for each assay in the manuscript.

      (3) In the main text, please identify the technique used to measure "total m6A/A" in Fig 2A. I assume it is mass spec.

      We used the EpiQuik m6A RNA Methylation Quantification Kit (Colorimetric) (Epigentek, NY, USA, Cat # P-9005) to measure the m6A/A ratio in RNA samples. This kit is commercially available for quantification of m6A RNA methylation, which used colorimetric assay with easy-to-follow steps for convenience and speed, and is suitable for detecting m6A methylation status directly using total RNA isolated from any species such as mammals, plants, fungi, bacteria, and viruses.

      (4) Line 190-191: the text describes annotating m6A sites by "nearest gene" which is confusing. The sites are mapped in RNAs, so the authors must unambiguously know the identity of the gene/transcript, right?

      When the m6A peaks were annotated using the R package ChIPseeker, it will include two items: "genomic annotation" and "nearest gene annotation". "Genomic annotation" tells us which genomic features the peak is annotated to, such as 5’UTR, 3’UTR, exon, etc. "Nearest gene annotation" indicates which specific gene/transcript the peak is matched to. We modified the description in the main text to make it easier to understand.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      While I believe this study aims to address a very interesting question and demonstrates intriguing evidence suggesting a role for m6A in unbalanced genomes, technical limitations in the methods being used limited my confidence in the overall conclusions. In addition, some of the analyses seemed to distract a bit from the main question of the work, which made thoroughly reading and reviewing the work challenging at times due to the length and lack of cohesion. Some specific points and suggestions are detailed below.

      (1) Some specific points/recommendations for the bulk m6A measurements: for Figure 2A, the authors refer to m6A/A ratio in the text, but based on the methods section and axis labels in Figure 2A (as well as other figures), it may represent m6A% in total RNA. The authors should just clarify which one it is and make the text and figures consistent. The methods description also seems to specify that m6A is quantified in total RNA, and yet the factors being discussed (Ime4, Ythdc1, etc) are associated with m6A in mRNA. Since m6A is present in non-mRNAs (including highly abundant rRNAs), m6A analysis of total RNA may be masking some of the effects due to the relatively low abundance of mRNA relative to rRNA. It is possible that the above point contributes to the discrepancy between the overall m6A abundance in aneuploidies and the changing methylase expression levels (which does seem to correlate better with m6A sequencing data). On a related note, though the authors suggest in Figures 7E and F that m6A level changes are different in males and females, the levels and trends of m6A% in these panels seem quite similar, and the absence of the presence of statistical significance seems driven by higher variation (larger error bars) in the measurements in 7F (and again effects may be masked if total RNA is being quantified). This may be a very addressable issue, as m6A analysis of mRNA-enriched samples should be feasible, and in fact, may show clearer changes to better support the authors' conclusions.

      Thank you for your helpful comments.

      As suggested, the abundance of m6A on mRNA were detected (Figure 7E, F). Total RNA was extracted from the heads of the control and MSL2 transgenic Drosophila and mRNA was isolated using the Dynabeads mRNA purification kit (Invitrogen, Carlsbad, CA, USA, 61006). 300-600 ng mRNA can be purified from 40 μg total RNA (200-300 heads per sample). We used the EpiQuik m6A RNA Methylation Quantification Kit (Colorimetric) (Epigentek, NY, USA, Cat # P-9005) to measure the abundance of m6A in mRNA samples (200ng). The results obtained by this method represent the m6A/A ratio (%), which is also written as m6A% on the user guide of the kit. We made corresponding revisions in the main text and figures to made them consistent.

      It is showing a heightened abundance of m6A modification on mRNA as opposed to total RNA including some other types of RNA such as mRNA, lncRNA, and rRNA (Figure 7E,F; Figure 7—figure supplement 1G,H). Consistently, in the MSL2 knockdown Drosophila, the m6A modification levels on mRNA mirrored those observed on total RNA, exhibiting a significant downregulation (Figure 7E; Figure 7—figure supplement 1G). In contrast, no substantial difference in the m6A abundance on mRNA was detected between MSL2 overexpressed Drosophila and the control Drosophila (Figure 7F; Figure 7—figure supplement 1H). The differences of m6A abundance between males and females were not statistically significant (Figure 7E,F), prompting us to make revisions to the manuscript.

      (2) The analyses in Figures 5 and 6 describe a lot of different comparisons derived from these datasets, and while there seem to be many interesting new hypotheses to be tested, the authors do not make any definitive conclusions from these analyses. These figures also seem to diverge a bit from the main conclusion of the work, and from this reviewer's perspective made it more difficult to read and review the work. Overall streamlining the narrative may help readers appreciate the main conclusions of the work (though this is of course up to the author's discretion).

      As indicated in Figure 5, the results demonstrated a sexually dimorphic role of m6A modification in the regulation of gene expression in aneuploid Drosophila, suggesting its potential involvement in the gene regulatory network through interactions with dosage-sensitive regulators. Furthermore, Figure 6 illustrated the intricate interplay between RNA m6A modification, gene expression, and alternative splicing under genomic imbalance, with RNA splicing being more intimately associated with m6A methylation than gene transcription itself.

      This manuscript also discussed the correlation between methylation status and classical dosage effects, dosage compensation effects, and inverse dosage effects. We have initially demonstrated that RNA m6A methylation could influence dosage-dependent gene regulation via multiple avenues, such as interactions with dosage-sensitive modifiers, alternative splicing mechanisms, the MSL complex, and other related processes. Indeed, our study primarily utilizes m6A methylated RNA immunoprecipitation sequencing (MeRIP-Seq) to comprehensively investigate the role of RNA m6A modification in genomes experiencing imbalance. We agree that more specific and in-depth research on these factors will be instrumental in elucidating the precise mechanisms by which m6A modification regulates expression in unbalanced genomes, which we acknowledge as a significant avenue for our future research.

      We are grateful for your suggestions and, should it be necessary, we might to simplify the volume of the whole manuscript by removing or condensing the data analyse and description to enhance the prominence of the central theme.

      Reviewer #2 (Recommendations For The Authors):

      Overall, please provide enough technical detail in the main text so that the reader understands what was done, and does not have to repeatedly dig into figure legends and materials and methods to understand each data statement.

      Thank you for your suggestions. We have added some technical details to the manuscript and made some modifications as suggested.

    1. for - meaning crisis - 50 episodes - John Vervaeke - meaning crisis - summary table of 50 episodes

      meaning crisis - summary table of the title of 50 episodes - 1: Introduction - 2: Flow, Metaphor, and the Axial Revolution - 3: Continuous Cosmos and Modern World Grammar - 4: Socrates and the Quest for Wisdom - 5: Plato and the Cave - 6:Aristotle, Kant, and Evolution - 7: Aristotle's World View and Erich Fromm - 8: The Buddha and "Mindfulness" - 9: Insight - 10: Consciousness - 11: Higher States of Consciousness, Part 1 - 12: Higher States of Consciousness, Part 2 - 13: Buddhism and Parasitic Processing - 14: Epicurians, Cynics, and Stoics - 15: Marcel Aurelius and Jesus - 16:Christianity and Agape - 17:Gnosis and Existential Inertia - 18: Plotinus and Neoplatonism - 19: Augustine and Aquinas - 20: Death of the Universe - 21: Martin Luther and Descartes - 22: Descartes vs. Hobbes - 23: Romanticism - 24: Hegel - 25: The Clash - 26: Cognitive Science - 27:Problem Formulation - 28: Convergence to Relevance Realization - 29: Getting to the Depths of Relevance Realization - 30: Relevance Realization Meets Dynamical Systems Theory - 31: Embodied-Embedded RR as Dynamical-Developmental GI - 32: in the Brain, Insight, and Consciousness - 33: The Spirituality of RR: Wonder/Awe/Mystery/Sacredness - 34: Sacredness: Horror, Music, and the Symbol - 35: The Symbol, Sacredness, and the Sacred - 36: Religio/Perennial Problems/Reverse Eng. Enlightenment - 37: Reverse Engineering Enlightenment: Part 2 - 38: Agape and 4E Cognitive Science - 39: The Religion of No Religion - 40: Wisdom and Rationality? - 41: What is Rationality? - 42: Intelligence, Rationality, and Wisdom - 43: Wisdom and Virtue - 44: Theories of Wisdom - 45: The Nature of Wisdom - 46: Conclusion and the Prophets of the Meaning Crisis - 47: Heidegger - 48: Corbin and the Divine Double - 49: Corbin and Jung - 50: Tillich and Barfield

    1. Author response:

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

      Reviewer #1 (Public review):

      Summary:

      How reconsolidation works - particularly in humans - remains largely unknown. With an elegant, 3-day design, combining fMRI and psychopharmacology, the authors provide evidence for a certain role for noradrenaline in the reconsolidation of memory for neutral stimuli. All memory tasks were performed in the context of fMRI scanning, with additional resting-state acquisitions performed before and after recall testing on Day 2. On Day 1, 3 groups of healthy participants encoded word-picture associates (with pictures being either scenes or objects) and then performed an immediate cued recall task to presentation of the word (answering is the word old or new, and whether it was paired with a scene or an object). On Day 2, the cued recall task was repeated using half of the stimulus set words encoded on Day 1 (only old words were presented, with subjects required to indicate prior scene vs object pairing). This test was immediately preceded by the oral administration of placebo, cortisol, or yohimbine (to raise noradrenaline levels) depending on group assignment. On Day 3, all words presented on Day 1 were presented. As expected, on Day 3, memory was significantly enhanced for associations that were cued and successfully retrieved on Day 2 compared to uncued associations. However, for associative d', there was no Cued × Group interaction nor a main effect of Group, i.e., on the standard measure of memory performance, post-retrieval drug presence on Day 2 did not affect memory reconsolidation. As further evidence for a null result, fMRI univariate analyses showed no Cued × Group interactions in whole-brain or ROI activity.

      Strengths:

      There are some aspects of this study that I find impressive. The study is well-designed and the fMRI analysis methodology is innovative and sound. The authors have made meticulous and thorough physiological measurements, and assays of mood, throughout the experiment. By doing so, they have overcome, to a considerable extent, the difficulties inherent in the timing of human oral drug delivery in reconsolidation tasks, where it is difficult to have the drug present in the immediate recall period without affecting recall itself. This is beautifully shown in Figure 3. I also think that having some neurobiological assay of memory reactivation when studying reconsolidation in humans is critical, and the authors provide this. While multi-voxel patterns of hemodynamic responses are, in my view, very difficult to equate with an "engram", these patterns do have something to do with memory.

      We thank the reviewer for considering aspects of our work impressive, the study to be well-designed, and the methodology to be innovative and sound.

      Weaknesses:

      I have major issues regarding the behavioral results and the framing of the manuscript.

      (1) To arrive at group differences in memory performance, the authors performed median splitting of Day 3 trials by short and long reaction times during memory cueing on Day 2, as they took this as a putative measure of high/low levels of memory reactivation. Associative category hits on Day 3 showed a Group by Day 2 Reaction time (short, long) interaction, with post-hocs showing (according to the text) worse memory for short Day 2 RTs in the Yohimbine group. These post-hocs should be corrected for multiple comparisons, as the result is not what would be predicted (see point 2). My primary issue here is that we are not given RT data for each group, nor is the median splitting procedure described in the methods. Was this across all groups, or within groups? Are short RTs in the yohimbine group any different from short RTs in the other two groups? Unfortunately, we are not given Day 2 picture category memory levels or reaction times for each group. This is relevant because (as given in Supplemental Table S1) memory performance (d´) for the Yohimbine group on Day 1 immediate testing is (roughly speaking) 20% lower than the other 2 groups (independently of whether the pairs will be presented again the following day). I appreciate that this is not significant in a group x performance ANOVA but how does this relate to later memory performance? What were the group-specific RTs on Day 1? So, before the reader goes into the fMRI results, there are questions regarding the supposed drug-induced changes in behavior. Indeed, in the discussion, there is repeated mention of subsequent memory impairment produced by yohimbine but the nature of the impairment is not clear.

      Thank you for the opportunity to clarify these important issues.

      Reaction times are well established proxies (correlates) of memory strength and memory confidence in previous research, as they reflect cognitive processes involved in retrieving information. Faster reaction times indicate stronger mnemonic evidence and higher confidence in the accuracy of a memory decision, while slower responses suggest weaker evidence and decision uncertainty or doubt. This relationship is supported by an extensive literature (e.g., Starns 2021; Robinson et al., 1997; Ratcliff & Murdock, 1976; amongst others). Importantly, distinguishing between high and low confidence choices in a memory task serves the purpose of differentiating between particularly strong memory evidence (e.g., in associative cued recall, when remembering is particularly vivid) and weaker memory evidence. Separating low from high confidence responses based on participants’ reaction times was especially important in the current analyses, because previous research demonstrates that reaction times during cued recall tasks inversely correlate with hippocampal involvement (Heinbockel et al., 2024; Gagnon et al. 2019) and that stress-effects on human memory may be particularly pronounced for high-confidence memories (Gagnon et al., 2019).

      In response to the Reviewer 1’s comments, we have elaborated on our rationale for the distinction between short and long reaction times in the introduction, results, and methods. Please see page 4, lines 144 to 148:

      “We distinguished between responses with short and long reaction times indicative of high and low confidence responses because previous research showed that reaction times are inversely correlated with hippocampal memory involvement(58-60) and memory strength(61,62), and that high confidence memories associated with short reaction times may be particularly sensitive to stress effects(63).”

      On page 13, lines 520 to 523:

      “Reaction times in the Day 2 Memory cueing task revealed a trial-specific gradient in reactivation strength. Thus, we turned to single-trial analyses, differentiating Day 3 trials by short and long reaction times during memory cueing on Day 2 (median split), indicative of high vs. low memory confidence(58–60) and hippocampal reactivation(26,63).”

      And on page 26, lines 1046 to 1053:

      “Reaction times serve as a proxy for memory confidence and memory strength, with faster responses reflecting higher confidence/strength and slower responses suggesting greater uncertainty/weaker memory. The association between reaction times and memory confidence has been established by previous research(58–60), suggesting that the distinction between high from low confidence responses differentiates vividly recalled associations from decisions based on weaker memory evidence. Reaction times are further linked to hippocampal activity during recall tasks(26,53), and stress effects on memory are particularly pronounced for high-confidence memories(53).”

      With respect to behavioral data reporting, we agree that the critical median-split procedure was not sufficiently clear in the original manuscript. We elaborate on this important aspect of the analysis now on page 26, lines 1053 to 1057:

      “We conducted a median-split within each participant to categorize trials as fast vs. slow reaction time trials during Day 2 memory cueing. We conducted this split on the participant- and not group-level because there is substantial inter-individual variability in overall reaction times. This approach also results in an equal number of trials in the low and high confidence conditions.”

      We completely agree that the relevant post-hoc test should be corrected for multiple comparisons. Please note that all reported post-hoc tests had been Bonferroni-corrected already. We clarify this now by explicitly referring to corrected p-values (P<sub>corr</sub>) and indicate in the methods that P<sub>corr</sub> refers to Bonferroni-corrected p-values. (please see page 25, lines 1036 to 1038).

      We further agree that for a comprehensive overview of the behaviour in terms of memory performance and RTs, these data need to be provided for each group and experimental day. Therefore, we now extended Supplementary Table S1 to include descriptive indices of memory performance (hits, dprime) and RTs for each group for each day. Moreover, we now report ANOVAs for reaction times for each of the experimental days in the main text.

      The ANOVA for Day 1 is now reported on page 6, lines 200 to 204: “To test for potential group differences in reaction times for correctly remembered associations on Day 1, we fit a linear model including the factors Group and Cueing. Critically, we did not observe a significant Group x Cueing interaction, suggesting no RT difference between groups for later cued and not cued items (F(2,58) = 1.41, P = .258, η<sup>2</sup> = 0.01; Supplemental Table S1).”

      The ANOVA for Day 2 is now reported on page 7, lines 243 to 248: “To test for potential group differences in reaction times for correctly remembered associations on Day 2, we fit a linear model including the factors Group and Reaction time (slow/fast) following the subject specific median split. The model did not reveal any main effect or interaction including the factor Group (all Ps > .535; Supplemental Table S1), indicating that there was no RT difference between groups, nor between low and high RT trials in the groups.”

      The ANOVA for Day 3 is reported on page 13 lines 487 to 494: “To test for potential group differences in reaction times for correctly remembered associations on Day 3 we fit a linear model including the factors Group and Cueing. This model did not reveal any main effect or interaction including the factor Group (all Ps > .267), indicating that there was no average RT difference between groups. As expected we observed a main effect of the factor Cueing, indicating a significant difference of reaction times across groups between trials that were successfully cued and those not cued on Day 2 (F(2,58) = 153.07, P < .001, η<sup>2</sup> = 0.22; Supplemental Table S1).”

      (2) The authors should be clearer as to what their original hypotheses were, and why they did the experiment. Despite being a complex literature, I would have thought the hypotheses would be reconsolidation impairment by cortisol and enhancement by yohimbine. Here it is relevant to point out that - only when the reader gets to the Methods section - there is mention of a paper published by this group in 2024. In this publication, the authors used the same study design but administered a stress manipulation after Day 2 cued recall, instead of a pharmacological one. They did not find a difference in associative hit rate between stress and control groups, but - similar to the current manuscript - reported that post-retrieval stress disrupts subsequent remembering (Day 3 performance) depending on neural memory reinstatement during reactivation (specifically driven by the hippocampus and its correlation with neocortical areas).

      Instead of using these results, and other human studies, to motivate the current work, reference is made to a recent animal study: Line 169 "Building on recent findings in rodents (Khalaf et al. 2018), we hypothesized that the effects of post-retrieval noradrenergic and glucocorticoid activation would critically depend on the reinstatement of the neural event representation during retrieval". It is difficult to follow that a rodent study using contextual fear conditioning and examining single neuron activity to remote fear recall and extinction would be relevant enough to motivate a hypothesis for a human psychopharmacological study on emotionally neutral paired associates.

      We agree that our recent publication utilizing a very similar experimental design including three days is highly relevant in the context of the current study and we now refer to this recent study earlier in our manuscript. Please see page 3, lines 89 to 94:  

      “Recently, we showed a detrimental impact of post-retrieval stress on subsequent memory that was contingent upon reinstatement dynamics in the Hippocampus, VTC and PCC during memory reactivation26. While this study provided initial insights into the potential brain mechanisms involved in the effects of post-retrieval stress on subsequent memory, the underlying neuroendocrine mechanisms remained elusive.”

      Moreover, we explicitly state our hypothesis regarding the neural mechanism, with reference to our recent work, on page 5, lines 166 to 169:

      “Building on our recent findings in humans(26) as well as current insights from rodents(47), we hypothesized that the effects of post-retrieval noradrenergic and glucocorticoid activation would critically depend on the reinstatement of the neural event representation during retrieval.”

      Concerning the potential direction of the effects of post-retrieval cortisol and noradrenaline, the literature is indeed mixed with partially contradicting results, which made it, in our view, difficult to derive a clear hypothesis of potentially opposite effects of cortisol and yohimbine. We summarize the relevant evidence in the introduction on pages 3 to 4, lines 100 to 113:

      “Some studies, using emotional recognition memory or fear conditioning in healthy humans, suggest enhancing effects of post-retrieval glucocorticoids on subsequent memory(30,31). However, rodent studies on neutral recognition memory(21), fear conditioning(32), as well as evidence from humans on episodic recognition memory(33) report impairing effects of glucocorticoid receptor activation on post-retrieval memory dynamics. For noradrenaline, post-retrieval blockade of noradrenergic activity impairs putative reconsolidation or future memory accessibility in human fear conditioning(34), as well as drug (alcohol) memory(35) and spatial memory in rodents(36). However, this effect is not consistently observed in human studies on fear conditioning(40), speaking anxiety(37), inhibitory avoidance(39), traumatic mental imagination (PTSD patients)(38), and might depend on the arousal state of the individual(21) or the exact timing of drug administration as suggested by studies in humans(41) and rodents(42). Thus, while there is evidence that glucocorticoid and noradrenergic activation after retrieval can affect subsequent memory, the direction of these effects remains elusive.”

      In addition to these reviewer comments and in response to the eLife assessment, we would like to emphasize that the present findings are in our view not only relevant for a subfield but may be of considerable interest for researchers from various fields, beyond experimental memory research, including Neurobiology, Psychiatry, Clinical Psychology, Educational Psychology, or Law Psychology. We highlight the relevance of the topic and our findings now more explicitly in the introduction and discussion. Please see page 3:

      “The dynamics of memory after retrieval, whether through reconsolidation of the original trace or interference with retrieval-related traces, have fundamental implications for educational settings, eyewitness testimony, or mental disorders(5,11,12). In clinical contexts, post-retrieval changes of memory might offer a unique opportunity to retrospectively modify or render less accessible unwanted memories, such as those associated with posttraumatic stress disorder (PTSD) or anxiety disorders(13–15). Given these potential far reaching implications, understanding the mechanisms underlying post-retrieval dynamics of memory is essential.”

      On page 17:

      “Upon their retrieval, memories can become sensitive to modification(1,2). Such post-retrieval changes in memory may be fundamental for adaptation to volatile environments and have critical implications for eyewitness testimony, clinical or educational contexts(5,11–15). Yet, the brain mechanisms involved in the dynamics of memory after retrieval are largely unknown, especially in humans.”

      And on page 19:

      “Beyond their theoretical relevance, these findings may have relevant implications for attempts to employ post-retrieval manipulations to modify unwanted memories in anxiety disorders or PTSD(97,98). Specifically, the present findings suggest that such interventions may be particularly promising if combined with cognitive or brain stimulation techniques ensuring a sufficient memory reactivation.“

      Reviewer #1 (Recommendations for the authors):

      (1) Related to major issue 2 in the Public Review. In the introduction, it would be helpful to be specific about the type of memory being probed in the different studies referenced (episodic vs conditioning). For the former, please make it clear whether stimuli to be remembered were emotional or neutral, and for which stimulus class drug effects were observed. This is particularly important given that in the first paragraph, you describe memory reactivation in the context of traumatic memories via mention of PTSD. It would also be helpful to know to which species you refer. For example, in line 115, "timing of drug administration..." a rodent and a human study are cited.

      We completely agree that these aspects are important. We have therefore rewritten the corresponding paragraph in the introduction to clarify the type of memory probed, the emotionality of the stimuli and the species tested. Please see pages 3 to 4, lines 100 to 113:

      “Some studies, using emotional recognition memory or fear conditioning in healthy humans, suggest enhancing effects of post-retrieval glucocorticoids on subsequent memory(30,31). However, rodent studies on neutral recognition memory(21), fear conditioning(32), as well as evidence from humans on episodic recognition memory(33) report impairing effects of glucocorticoid receptor activation on post-retrieval memory dynamics. For noradrenaline, post-retrieval blockade of noradrenergic activity impairs putative reconsolidation or future memory accessibility in human fear conditioning(34), as well as drug (alcohol) memory(35) and spatial memory in rodents(36). However, this effect is not consistently observed in human studies on fear conditioning(40), speaking anxiety(37), inhibitory avoidance(39), traumatic mental imagination (PTSD patients)(38), and might depend on the arousal state of the individual(21) or the exact timing of drug administration as suggested by studies in humans(41) and rodents(42). Thus, while there is evidence that glucocorticoid and noradrenergic activation after retrieval can affect subsequent memory, the direction of these effects remains elusive.”

      (2) The Bos 2014 reference appears incorrect. I think you mean the Frontiers paper of the same year.

      Thank you for noticing this mistake, which has been corrected.

      (3) Line 734 "The study employed a fully crossed, placebo-controlled, double-blind, between-subjects design". What is a fully crossed design?

      A fully-crossed design refers to studies in which all possible combinations of multiple between-subjects factors are implemented. However, because the factor reactivation/cueing was manipulated within-subject in the present study and there is only one between-subjects factor (group/drug), “fully-crossed” may be misleading here. We removed it from the manuscript.

      (4) Supplemental Table S3. Are these ordered in terms of significance? A t- or Z-value for each cluster (either of the peak or a summed value) would be helpful.

      We agree that the ordering of the clusters was not clearly described. In the revised Supplemental Table S3, we have now added a column with the cluster-peak specific T-values and added an explanation in the table caption: “Depicted clusters are ordered by cluster-peak T-values.”

      (5) Please provide the requested memory performance and reaction time data, and relevant group comparisons.

      In response to general comment #1 above, we now provide all relevant accuracy and reaction time data for all groups and experimental days in the revised Supplemental Table S1. Moreover, we now report the relevant group comparisons in the main text on page 6, lines 200 to 204, on page 7, lines 243 to 248, and on page 13, lines 487 to 494.

      (6) Please rewrite the introduction with specific hypotheses, mention your recent results published in Science Advances, and attend to suggestions made in the first comment above.

      We have rewritten parts of the introduction to make the link to our recent publication clearer and to clarify the types of memories and species tested, as suggested by the reviewer (please see pages 3 to 4, lines 100 to 113). Moreover, we explicitly state our hypothesis regarding the neural mechanism on page 5, lines 166 to 169:

      “Building on our recent findings in humans(26) as well as current insights from rodents(47), we hypothesized that the effects of post-retrieval noradrenergic and glucocorticoid activation would critically depend on the reinstatement of the neural event representation during retrieval.”

      In terms of the direction of the potential cortisol and yohimbine effects, we have elaborated on the relevant literature, which in our view does not allow a clear prediction regarding the nature of the drug effects. We have made this explicit by stating that “… while there is evidence that glucocorticoid and noradrenergic activation after retrieval can affect subsequent memory, the direction of these effects remains elusive.” (please see page 4, lines 111 to 113). It would be, in our view, inappropriate to retrospectively add another, more specific “hypothesis”.

      Reviewer #2 (Public review):

      Summary:

      The authors aimed to investigate how noradrenergic and glucocorticoid activity after retrieval influence subsequent memory recall with a 24-hour interval, by using a controlled three-day fMRI study involving pharmacological manipulation. They found that noradrenergic activity after retrieval selectively impairs subsequent memory recall, depending on hippocampal and cortical reactivation during retrieval.

      Overall, there are several significant strengths of this well-written manuscript.

      Strengths:

      (1) The study is methodologically rigorous, employing a well-structured three-day experimental design that includes fMRI imaging, pharmacological interventions, and controlled memory tests.

      (2) The use of pharmacological agents (i.e., hydrocortisone and yohimbine) to manipulate glucocorticoid and noradrenergic activity is a significant strength.

      (3) The clear distinction between online and offline neural reactivation using MVPA and RSA approaches provides valuable insights into how memory dynamics are influenced by noradrenergic and glucocorticoid activity distinctly.

      We thank the reviewer for these very positive and encouraging remarks.

      Weaknesses:

      (1) One potential limitation is the reliance on distinct pharmacodynamics of hydrocortisone and yohimbine, which may complicate the interpretation of the results.

      We agree that the pharmacodynamics of hydrocortisone and yohimbine are different. However, we took these pharmacodynamics into account when designing the experiment and have made an effort to accurately track the indicators for noradrenergic arousal and glucocorticoids across the experiment. As shown in Figure 2, these indicators confirm that both drugs are active within the time window of approximately 40-90 minutes after reactivation. This time window corresponds to the proposed reconsolidation window, which is assumed to open around 10 minutes post-reactivation and to remain open for a few hours (approximately 90 minutes; Monfils & Holmes, 2018; Lee et al., 2017; Monfils et al., 2009).

      We have now acknowledged the distinct pharmacodynamics of hydrocortisone and yohimbine on page 21, lines 845 to 847: “We note that yohimbine and hydrocortisone follow distinct pharmacodynamics(104,105), yet selected the administration timing to ensure that both substances are active within the relevant post-retrieval time window.”

      In the results section, on page 11, lines 437 to 439, we further emphasize this differential dynamic: “Our data demonstrate that, despite the distinct pharmacodynamics of CORT and YOH, both substances are active within the time window that is critical for potential reconsolidation effects(3,4,43).”

      (2) Another point related above, individual differences in pharmacological responses, physiological and cortisol measures may contribute to memory recall on Day 3.

      The administered drugs elicit a pronounced adrenergic and glucocorticoid response, respectively. Specifically, the cortisol levels reached by 20mg of hydrocortisone correspond to those observed after a significant stressor exposure. Moreover, individual variation in stress system activation following drug intake tends to be less pronounced than in response to a natural stressor. Nevertheless, we fully agree that individual factors, such as metabolism or body weight, can influence the drug's action.

      We therefore re-analysed the reported Day 3 models, now including individual measures of baseline-to-peak changes in cortisol and systolic blood pressure, respectively. We report these additional analyses in the supplement and refer the interested reader to these analyses on page 15, lines 580 to 586:

      “As individual factors, such as metabolism or body weight, can influence the drug's action, we ran an additional analysis in which we included individual (baseline-to-peak) differences in salivary cortisol and (systolic) blood pressure, respectively. This analysis did not show any group by baseline-to-peak difference interaction suggesting that the observed memory effects were mainly driven by the pharmacological intervention group per se and less by individual variation in responses to the drug (see Supplemental Results).”

      And in the Supplemental Results:

      “To account for individual differences in cortisol responses after pill intake, we fit additional GLMMs predicting Day 3 subsequent memory of cued and correct trials including the factors Individual baseline-to-peak cortisol and Group. Doing so allowed us to account for variation in Day 3 performance, which might have resulted from within-group variation in cortisol responses, in particular in the CORT group. Importantly, none of the models predicting Day 3 memory performance by Day 2 cortisol-increase and Group, median-split RTs (high/low), hippocampal activity and RTs, or hippocampal activity and VTC category reinstatement revealed a significant group x baseline-to-peak cortisol interaction (all Ps > .122). These results suggest that inter-individual differences in cortisol responses did not have a significant impact on subsequent memory, beyond the influence of group per se. The same analyses were repeated for systolic blood pressure employing GLMMs predicting Day 3 subsequent memory of cued and correct trials including the factors Individual baseline-to-peak systolic blood pressure and Group to account for variation in Day 3 performance, which might have resulted from within-group variation in blood pressure response, in particular in the YOH group. While the model predicting Day 3 memory performance revealed a significant Individual baseline-to-peak systolic blood pressure × Group × median-split RTs (high/low) interaction (β = -0.05 ± 0.02, z = -2.04, P = .041, R<sup>2</sup><sub>conditional</sub> = 0.01), post-hoc slope tests, however, did not show any significant difference between groups (all P<sub>Corr</sub> > .329). The remaining models including hippocampal activity and RTs, or hippocampal activity and VTC category reinstatement did not reveal a significant Group × Individual baseline-to-peak systolic blood pressure interaction (all Ps > .101). These results suggest that inter-individual differences in systolic blood pressure responses did not have a significant impact on subsequent memory, beyond the influence of group per se.”

      Although we acknowledge that our study may not have been sufficiently powered for an analysis of individual differences, these data suggest that our memory effects were mainly driven by the pharmacological intervention group per se and less by individual variation in responses. It is to be noted, however, that all participants of the respective groups showed a pronounced increase in cortisol concentrations (on average > 1000% in the CORT group) and autonomic arousal (on average > 10% in the YOH group), respectively. These increases appeared to be sufficient to drive the observed memory effects, irrespective of some individual variation in the magnitude of the response.

      (3) Median-splitting approach for reaction times and hippocampal activity should better be justified.

      Reaction times are well established proxies (correlates) of memory strength and memory confidence in previous research, as they reflect cognitive processes involved in retrieving information. Faster reaction times indicate stronger mnemonic evidence and higher confidence in the accuracy of a memory decision, while slower responses suggest weaker evidence and decision uncertainty or doubt. This relationship is supported by an extensive literature (e.g., Starns 2021; Robinson et al., 1997; Ratcliff & Murdock, 1976; amongst others). Importantly, distinguishing between high and low confidence choices in a memory task serves the purpose to differentiating between particularly strong memory evidence (e.g., is associative cued recall, when remembering is particularly vivid) and weaker memory evidence. Separating low from high confidence responses based on participants’ reaction times was especially important in the current analyses, because previous research demonstrates that reaction times during cued recall tasks inversely correlate with hippocampal involvement  Heinbockel et al., 2024; Gagnon et al. 2019) and that stress-effects on human memory may be particularly pronounced for high-confidence memories (Gagnon et al., 2019).

      In response to the Reviewer comments, we have elaborated on our rationale for the distinction between short and long reaction times in the introduction, results, and methods. Please see page 4, lines 144 to 148:

      “We distinguished between responses with short and long reaction times indicative of high and low confidence responses because previous research showed that reaction times are inversely correlated with hippocampal memory involvement(58–60) and memory strength(61,62), and that high confidence memories associated with short reaction times may be particularly sensitive to stress effects(63).”

      On page 13, lines 520 to 523:

      “Reaction times in the Day 2 Memory cueing task revealed a trial-specific gradient in reactivation strength. Thus, we turned to single-trial analyses, differentiating Day 3 trials by short and long reaction times during memory cueing on Day 2 (median split), indicative of high vs. low memory confidence(58–60) and hippocampal reactivation(26,63).”

      And on page 26, lines 1046 to 1053:

      “Reaction times serve as a proxy for memory confidence and memory strength, with faster responses reflecting higher confidence/strength and slower responses suggesting greater uncertainty/weaker memory. The association between reaction times and memory confidence has been established by previous research(58–60), suggesting that the distinction between high from low confidence responses differentiates vividly recalled associations from decisions based on weaker memory evidence. Reaction times are further linked to hippocampal activity during recall tasks(26,53), and stress effects on memory are particularly pronounced for high-confidence memories(53).”

      We agree that the critical median-split procedure was not sufficiently clear in the original manuscript. We elaborate on this important aspect of the analysis now on page 26, lines 1053 to 1057:

      “We conducted a median-split within each participant to categorize trials as slow vs. fast reaction time trials during Day 2 memory cueing. We chose to conduct this split on the participant- and not group-level because there is substantial inter-individual variability in overall reaction times and to retain an equal number of trials in the low and high confidence conditions.”

      In addition to these reviewer comments and in response to the eLife assessment, we would like to emphasize that the present findings are in our view not only relevant for a subfield but may be of considerable interest for researchers from various fields, beyond experimental memory research, including Neurobiology, Psychiatry, Clinical Psychology, Educational Psychology, or Law Psychology. We highlight the relevance of the topic and our findings now more explicitly in the introduction and discussion. Please see page 3:

      “The dynamics of memory after retrieval, whether through reconsolidation of the original trace or interference with retrieval-related traces, have fundamental implications for educational settings, eyewitness testimony, or mental disorders5,11,12. In clinical contexts, post-retrieval changes of memory might offer a unique opportunity to retrospectively modify or render less accessible unwanted memories, such as those associated with posttraumatic stress disorder (PTSD) or anxiety disorders(13–15). Given these potential far reaching implications, understanding the mechanisms underlying post-retrieval dynamics of memory is essential.”

      On page 17:

      “Upon their retrieval, memories can become sensitive to modification(1,2). Such post-retrieval changes in memory may be fundamental for adaptation to volatile environments and have critical implications for eyewitness testimony, clinical or educational contexts(5,11–15), Yet, the brain mechanisms involved in the dynamics of memory after retrieval are largely unknown, especially in humans.”

      And on page 19:

      “Beyond their theoretical relevance, these findings may have relevant implications for attempts to employ post-retrieval manipulations to modify unwanted memories in anxiety disorders or PTSD(97,98). Specifically, the present findings suggest that such interventions may be particularly promising if combined with cognitive or brain stimulation techniques ensuring a sufficient memory reactivation.“

      Reviewer #2 (Recommendations for the authors):

      My comments and/or questions for the authors to improve this well-written manuscript.

      (1) This study identifies the modulatory role of the hippocampus and VTC in the effects of norepinephrine on subsequent memory. Are there functional interactions between these ROIs and other brain regions that could be wise to consider for a more comprehensive understanding of the underlying neural mechanisms?

      We agree that functional interactions of hippocampus and VTC and other regions that were active during Day 2 memory cueing are relevant for our understanding of the underlying mechanisms. We therefore now performed connectivity analyses using general psycho-physiological interaction analysis (gPPI; as implemented in SPM) and report the results of this analysis on page 16, lines 635 to 644, and added Supplemental Table S4 including gPPI statistics.

      “We conducted general psycho-physiological interaction analysis (gPPI) analyses on the Day 2 memory cueing task (remembered – forgotten), which revealed that successful cueing was accompanied by significant functional connectivity between the left hippocampus, VTC, PCC and MPFC (see Supplemental Table S4). However, using these connectivity estimates to predict Day 3 subsequent memory performance (dprime) via regression did not reveal any significant Group × Connectivity interactions, indicating that the pharmacological manipulation (i.e. noradrenergic stimulation) did not modulate subsequent memory based on functional connectivity during memory cueing (all P<sub>Corr</sub> > .228). The same pattern of results was observed when including single trial beta estimates from multiple ROIs during memory cueing to predict Day 3 memory (all interaction effects P<sub>Corr</sub> > .288).”

      (2) In theory, noradrenergic activity would have a profound impact on activity in widespread brain regions that are closely related to memory function. It would be interesting to know other possible effects beyond the hippocampus and VTC.

      We agree and included in our analysis additional ROIs beyond the HC and VTC; we now report these explorative results on page 16, lines 616 to 633:

      “Beyond hippocampal and VTC activity during memory cueing (Day 2), we exploratively reanalysed the GLMMs predicting Day 3 memory performance including the PCC, which was relevant during memory cueing in the current study and in our previous work(26).  Predicting Day 3 memory performance by the factors Group and Single trial beta activity during memory cueing in the PCC did not reveal a significant interaction (P<sub>Corr</sub>  = 1); adding the factor Reaction time to the model also did not result in a significant interaction (P<sub>Corr</sub> = 1). We also included the Medial Prefrontal Cortex (MPFC) to predict Day 3 memory performance, as the MPFC has been shown to be sensitive to noradrenergic modulation in previous work(75). Predicting Day 3 memory performance by the factors Group and Single trial beta activity during memory cueing in the MPFC did not reveal a significant interaction (P<sub>Corr</sub>  = 1); adding the factor Reaction time to the model also did not result in a significant interaction (P<sub>Corr</sub> = 1), which indicates that the MPFC was not modulated by either pharmacological intervention. Finally, we investigated memory cueing from all remaining ROIs that were significantly activated during the Day 2 memory cueing task (Day 2 whole-brain analysis; correct-incorrect; Supplemental Table S3). We again fit GLMMs predicting Day 3 memory performance by the factors Group and Single trial beta activity during memory cueing. Again, we did not observe any significant interaction effect any of the ROIs (all interaction P<sub>Corr</sub> > .060) and these results did not change when adding the factor Reaction time to the respective models (all  P<sub>Corr</sub> > .075).”

      (3) There are substantial individual differences in pharmacological responses, physiological and cortisol measures, as shown in Figure 3A&B. If such individual differences are taken into account, are there any potential effects on subsequent recall on Day 3 pertaining to the hydrocortisone group?

      In response to this comment (and the General comment #1 of this reviewer), we now re-analyzed the respective models including individual measures of baseline-to-peak cortisol and systolic blood pressure.

      We re-analysed the reported Day 3 models, now including individual measures of baseline-to-peak changes in cortisol and systolic blood pressure, respectively. We report these additional analyses in the supplement and refer the interested reader to these analyses on page 15, lines 580 to 586:

      “As individual factors, such as metabolism or body weight, can influence the drug's action, we ran an additional analysis in which we included individual (baseline-to-peak) differences in salivary cortisol and (systolic) blood pressure, respectively. This analysis did not show any group by baseline-to-peak difference interaction suggesting that the observed memory effects were mainly driven by the pharmacological intervention group per se and less by individual variation in responses to the drug (see Supplemental Results).”

      And in the Supplemental Results:

      “To account for individual differences in cortisol responses after pill intake, we fit additional GLMMs predicting Day 3 subsequent memory of cued and correct trials including the factors Individual baseline-to-peak cortisol and Group. Doing so allowed us to account for variation in Day 3 performance, which might have resulted from within-group variation in cortisol responses, in particular in the CORT group. Importantly, none of the models predicting Day 3 memory performance by Day 2 cortisol-increase and Group, median-split RTs (high/low), hippocampal activity and RTs, or hippocampal activity and VTC category reinstatement revealed a significant group x baseline-to-peak cortisol interaction (all Ps > .122). These results suggest that inter-individual differences in cortisol responses did not have a significant impact on subsequent memory, beyond the influence of group per se. The same analyses were repeated for systolic blood pressure employing GLMMs predicting Day 3 subsequent memory of cued and correct trials including the factors Individual baseline-to-peak systolic blood pressure and Group to account for variation in Day 3 performance, which might have resulted from within-group variation in blood pressure response, in particular in the YOH group. While the model predicting Day 3 memory performance revealed a significant Individual baseline-to-peak systolic blood pressure × Group × median-split RTs (high/low) interaction (β = -0.05 ± 0.02, z = -2.04, P = .041, R<sup>2</sup><sub>conditional</sub> = 0.01), post-hoc slope tests, however, did not show any significant difference between groups (all P<sub>Corr</sub> > .329). The remaining models including hippocampal activity and RTs, or hippocampal activity and VTC category reinstatement did not reveal a significant Group × Individual baseline-to-peak systolic blood pressure interaction (all Ps > .101). These results suggest that inter-individual differences in systolic blood pressure responses did not have a significant impact on subsequent memory, beyond the influence of group per se.”

      (4) Median-splitting approach for reaction times and hippocampal activity should better be justified.

      Reaction times are well established proxies (correlates) of memory strength and memory confidence in previous research, as they reflect cognitive processes involved in retrieving information. Faster reaction times indicate stronger mnemonic evidence and higher confidence in the accuracy of a memory decision, while slower responses suggest weaker evidence and decision uncertainty or doubt. This relationship is supported by an extensive literature (e.g., Starns 2021; Robinson et al., 1997; Ratcliff & Murdock, 1976; amongst others). Importantly, distinguishing between high and low confidence choices in a memory task serves the purpose to differentiating between particularly strong memory evidence (e.g., is associative cued recall, when remembering is particularly vivid) and weaker memory evidence. Separating low from high confidence responses based on participants’ reaction times was especially important in the current analyses, because previous research demonstrates that reaction times during cued recall tasks inversely correlate with hippocampal involvement ( Heinbockel et al., 2024; Gagnon et al. 2019) and that stress-effects on human memory may be particularly pronounced for high-confidence memories (Gagnon et al., 2019).

      In response to the Reviewer comments, we have elaborated on our rationale for the distinction between short and long reaction times in the introduction, results, and methods. Please see page 4, lines 144 to 148:

      “We distinguished between responses with short and long reaction times indicative of high and low confidence responses because previous research showed that reaction times are inversely correlated with hippocampal memory involvement(58–60) and memory strength(61,62), and that high confidence memories associated with short reaction times may be particularly sensitive to stress effects(63).”

      On page 13, lines 520 to 523:

      “Reaction times in the Day 2 Memory cueing task revealed a trial-specific gradient in reactivation strength. Thus, we turned to single-trial analyses, differentiating Day 3 trials by short and long reaction times during memory cueing on Day 2 (median split), indicative of high vs. low memory confidence(58–60) and hippocampal reactivation(26,63).”

      And on page 26, lines 1046 to 1053:

      “Reaction times serve as a proxy for memory confidence and memory strength, with faster responses reflecting higher confidence/strength and slower responses suggesting greater uncertainty/weaker memory. The association between reaction times and memory confidence has been established by previous research(58–60), suggesting that the distinction between high from low confidence responses differentiates vividly recalled associations from decisions based on weaker memory evidence. Reaction times are further linked to hippocampal activity during recall tasks(26,53), and stress effects on memory are particularly pronounced for high-confidence memories(53).”

      Minor comments:

      (5) Please include the full names of key abbreviations in the figure legends, such as "ass.cat.hit" and among others.

      We now include the full names of key abbreviations in all figure legends (e.g., ass.cat.hit = associative category hit).

      (6) Please introduce various metrics used in the study to aid readers in better understanding the measurements they utilized.

      We agree that various measures that were included in our analyses had not been described clearly enough before, especially concerning the multivariate analyses. We therefore added short explanations across the results section.

      Page 8, lines 279 to 280: “Classifier accuracy is derived from the sum of correct predictions the trained classifier made in the test-set, relative to the total amount of predictions.”

      Page 8, lines 290 to 292:  “Neural reinstatement reflects the extent to which a neural activity pattern (i.e., for objects) that was present during encoding is reactivated during retrieval (e.g., memory cueing).”

      Page 8, lines 299 to 301:  “The logits here reflect the log-transformed trial-wise probability of a pattern either representing a scene or an object.”

      Page 10, lines 378 to 380:  “Beyond category-level reinstatement, we assessed event-level memory trace reinstatement from initial encoding (Day 1) to memory cueing (Day 2), via RSA, correlating neural patterns in each region (hippocampus, VTC, and PCC) across days.”

      (7) Please explain what the different colors represent in Figures 5B and 5C to avoid confusion. It would be good to indicate significant differences in the figures if applicable.

      We now added line legends to the figure and also the caption to clarify what exactly is depicted. We added asterisks to mark significant differences.

      References:

      Monfils, M. H., Cowansage, K. K., Klann, E., & LeDoux, J. E. (2009). Extinction-reconsolidation boundaries: key to persistent attenuation of fear memories. science324(5929), 951-955.

      Monfils, M. H., & Holmes, E. A. (2018). Memory boundaries: opening a window inspired by reconsolidation to treat anxiety, trauma-related, and addiction disorders. The Lancet Psychiatry5(12), 1032-1042.

      Lee, J. L. C., Nader, K. & Schiller, D. An Update on Memory Reconsolidation Updating. Trends Cogn. Sci. 21, 531–545 (2017).

      Radley, J. J., Williams, B., & Sawchenko, P. E. (2008). Noradrenergic innervation of the dorsal medial prefrontal cortex modulates hypothalamo-pituitary-adrenal responses to acute emotional stress. Journal of Neuroscience28(22), 5806-5816.

      Heinbockel, H., Wagner, A. D., & Schwabe, L. (2024). Post-retrieval stress impairs subsequent memory depending on hippocampal memory trace reinstatement during reactivation. Science Advances10(18), eadm7504.

    1. Reviewer #3 (Public review):

      Summary:

      Jin, Briggs et al. made use of light-sheet 3D imaging and data analysis to assess the collective network activity in isolated mouse islets. The major advantage of using whole islet imaging, despite compromising on a speed of acquisition, is that it provides a complete description of the network, while 2D networks are only an approximation of the islet network. In static-incubation conditions, excluding the effects of perfusion, they assessed two subpopulations of beta cells and their spatial consistency and metabolic dependence.

      Strengths:

      The authors confirmed that coordinated Ca2+ oscillations are important for glycemic control. In addition, they definitively disproved the role of individual privileged cells, which were suggested to lead or coordinate Ca²⁺ oscillations. They provided evidence for differential regional stability, confirming the previously described stochastic nature of the beta cells that act as strongly connected hubs as well as beta cells in initiating regions (doi.org/10.1103/PhysRevLett.127.168101). This has not been a surprise to the reviewer.

      The fact that islet cores contain beta cells that are more active and more coordinated has also been readily observed in high-frequency 2D recordings (e.g. DOI: 10.2337/db22-0952), suggesting that the high-speed capture of fast activity can partially compensate for incomplete topological information.

      They also found an increased metabolic sensitivity of mantle regions of an islet with subpopulation of beta cells with a high probability of leading the islet activity and which can be entrained by fuel input. They discuss a potential role of alpha/delta cell interaction, however relative lack of beta cells in the islet border region could also be a factor contributing to less connectivity and higher excitability.

      The Methods section contains a useful series of direct instructions on how to approach fast 3D imaging with currently available hardware and software.

      The Discussion is clear and includes most of the issues regarding the interpretation of the presented results.

      Taken together it is a strong technical paper to demonstrate the stochasticity regarding the functions subpopulations of beta cells in the islets may have and how less well-resolved approaches (both missing spatial resolution as well as missing temporal resolution) led us to jump to unjustified conclusions regarding the fixed roles of individual beta cells within an islet.

      Weaknesses:

      There are a few relevant issues that need to be addressed.

      (1) The study is not internally consistent regarding the Results section. In the text the authors discuss changes in membrane potential (not been measured in this study), while in the figures they exclusively describe Ca2+ oscillations (which were measured). Examples are on lines 149, 150, 153, 154, 263... It is recommended that the silent and active phase in the Results section describe processes actually measured in this study as shown 6A.

      (2) There are in fact no radially oriented networks in the core of an islet (l. 130, Fig. 4) apart from the fact that every hub has somewhat radially oriented edges. For radiality to have some general meaning, the normalized distance from the geometric center would need to be lower than 0.4. The networks are centrally located, which does not change the major conclusions of the study.

      (3) The study would profit from acknowledging that Ca2+ influx is not a sole mechanism to drive insulin secretion and that KATP channels are not the sole target sensitive to changes in the cytosolic (global or local) ADP and ATP concentration or that there is an absolute concentration-dependence of these ligands on KATP channels. The relatively small conductance changes that have been found associated to active and silent phases (closing and opening of the KATP channels as interpreted by the authors, respectively, doi: 10.1152/ajpendo.00046.2013) and should be due to metabolic factors, could be also associated to desensitization of KATP channels to ATP due to the increase in cytosolic Ca2+ changes after intracellular Ca2+ flux (DOI: 10.1210/endo.143.2.8625) as they have been found to operate also at time scales, significantly faster (DOI: 10.2337/db22-0952) than reported before (refs. 21,22). Metabolic changes influence intracellular Ca2+ flux as well.

      (4) There is no explanation for why KL divergence is so different between the pre-test regional consistency of the islets used to test the vehicle compared to those where GKa and PKa have been tested.

    1. Reviewer #1 (Public review):

      Summary:

      In this paper, the authors develop a biologically plausible recurrent neural network model to explain how the hippocampus generates and uses barcode-like activity to support episodic memory. They address key questions raised by recent experimental findings: how barcodes are generated, how they interact with memory content (such as place and seed-related activity), and how the hippocampus balances memory specificity with flexible recall. The authors demonstrate that chaotic dynamics in a recurrent neural network can produce barcodes that reduce memory interference, complement place tuning, and enable context-dependent memory retrieval, while aligning their model with observed hippocampal activity during caching and retrieval in chickadees.

      Strengths:

      (1) The manuscript is well-written and structured.<br /> (2) The paper provides a detailed and biologically plausible mechanism for generating and utilizing barcode activity through chaotic dynamics in a recurrent neural network. This mechanism effectively explains how barcodes reduce memory interference, complement place tuning, and enable flexible, context-dependent recall.<br /> (3) The authors successfully reproduce key experimental findings on hippocampal barcode activity from chickadee studies, including the distinct correlations observed during caching, retrieval, and visits.<br /> (4) Overall, the study addresses a somewhat puzzling question about how memory indices and content signals coexist and interact in the same hippocampal population. By proposing a unified model, it provides significant conceptual clarity.

      Weaknesses:

      The recurrent neural network model incorporates assumptions and mechanisms, such as the modulation of recurrent input strength, whose biological underpinnings remain unclear. The authors acknowledge some of these limitations thoughtfully, offering plausible mechanisms and discussing their implications in depth.

      One thread of questions that authors may want to further explore is related to the chaotic nature of activity that generates barcodes when recurrence is strong. Chaos inherently implies sensitivity to initial conditions and noise, which raises questions about its reliability as a mechanism for producing robust and repeatable barcode signals. How sensitive are the results to noise in both the dynamics and the input signals? Does this sensitivity affect the stability of the generated barcodes and place fields, potentially disrupting their functional roles? Moreover, does the implemented plasticity mitigate some of this chaos, or might it amplify it under certain conditions? Clarifying these aspects could strengthen the argument for the robustness of the proposed mechanism.

      It may also be worth exploring the robustness of the results to certain modeling assumptions. For instance, the choice to run the network for a fixed amount of time and then use the activity at the end for plasticity could be relaxed.

    1. autêntico
      1. Cuja autoria é ratificada.
      2. De origem comprovada.
      3. Diz-se de qualquer documento digno de fé ou confiança; fidedigno, legítimo.
      4. Jur Revestido de formalidades legais; certificado por testemunho público e solene.
      5. Que tem validade, autoridade.
      6. Que não é falso ou imitativo; original.
      7. Que é incontestável: Narração autêntica.
      8. Diz-se do indivíduo que se assume tal qual é, que se apresenta socialmente sem falsidade ou de forma a dissimular sua verdadeira identidade.
      9. Do próprio punho da pessoa: Assinatura autêntica.
      10. Que imita ou copia fielmente; que se produziu em fiel conformidade com o original: A aparência de sua nova casa era a de um autêntico castelo alemão.
    1. Design justice argues, then, that some designs, when they cannot be universal, should simply not be made. And if they can be universal, then they should be made in ways that 1) center power inequalities, 2) center the voices of all directly impacted by the design outcomes, 3) prioritize impact on communities over designers’ intents, 4) view designers as facilitators rather than designers, 5) ensure designs are sustainable and community led, and 6) build upon and amplify the solutions that communities have already found.

      I disagree with the idea that if a design is not universal it should not be made, improvising designs is something that should be worked towards. The problems should be emphasized and centered for adequate solutions. Communities affected should be able to comfortably voice their concerns and properly have them addressed. Making sure that designers are community led is something that would make sure the outcomes benefit everyone. I do agree with the rest of points addressed specifically the idea of viewing designers as facilitators and working with communities to ensure the designs don't perpetuate any more harm.

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

      Learn more at Review Commons


      Reply to the reviewers

      We thank the reviewers for their general comment and for the critical evaluation of our analyses and results interpretation. Their comments greatly helped us to improve the manuscript.

      • *

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

      Summary: An analysis of an Arabidopsis VSP13 presumed lipid transport is provided. The analysis pretty much follows similar studies done on yeast and human homologs. Key findings are the identification of multiple products from the locus due to differential splicing, analysis of lipid binding and transport properties, subcellular location, tissue specific promoter activity, mutant analysis suggesting a role in lipid remodeling following phosphate deprivation, but no physiological or growth defects of the mutants. Major points: The paper is generally written and documented, the experiments are well conducted and follow established protocols. The following major points should be considered:

      1. There are complementary lipid binding assays that should be considered such as liposome binding assays, or lipid/western dot blots. All of these might give slightly different results and may inform a consensus. Of course, non-membrane lipids such as TAG cannot be tested in a liposome assay.

      Concerning lipid transfer proteins (LTPs), it is important to differentiate the lipid binding capacity related to the transport specificity (which lipids are transported by a LTP?) from the lipid binding capacity linked to the targeting of a LTP to a specific membrane (a LTP can bind a specific lipid via a domain distinct from the lipid transfer domain to be targeted in cells, but will not transport this lipid). Both aspects are of high interest to be determined. Our goal here was to focus on the identification of the lipids bound to AtVPS13M1 and to be likely transported, which is why we used a truncation (1-335) corresponding to the N-term part of the hydrophobic tunnel. Liposome binding assays and lipid dot blots are necessary to answer the question of the membrane binding capacity of the protein. We think that this aspect is out of the scope of the current article as it will require to express and purify other AtVPS13M1 domains that are known to bind lipids such as the two PH domains and the C2. This will be the scope of future investigations in our lab.

      Similarly, lipid transfer based only on fluorophore-labeled lipids may be misleading because the fluorophore could affect binding. It is mentioned that the protein in this assay is tethered by 3xHis to the liposomes. Un less I ma missing something, I do not understand how that should work. This needs to be better explained.

      We truly agree with Reviewer 1 that the presence of a fluorophore could affect lipid binding to the protein. In this assay, lipids are labeled on their polar head and it is therefore difficult to conclude about the specificity of our protein in term of transport. This assay is used as a qualitative assay to show that AtVPS13M1(1-335) is able to transfer lipids in vitro, and in the manuscript, we did not make any conclusion about its transport specificity based on this assay, but rather used the binding assay to assess the binding, and likely transport, specificity of AtVPS13M1. FRET-based assay is a well-accepted assay in the lipid transfer community to easily probe lipid transport in vitro and has been used in the past to assess transfer capacity of different proteins, including for VPS13 proteins (for examples, see (Kumar et al., 2018; Hanna et al., 2022; Valverde et al., 2019)).

      To be able to transfer lipids from one liposome to another, both liposomes have to be in close proximity. Therefore, we attached our protein on donor acceptors, to favor the transport of the fluorescent lipids from the donor to the acceptor liposomes. Then, we progressively increased acceptor liposomes concentration to favor liposome proximity and the chance to have lipid transfer. We added a scheme on Figure 3B of the revised version of the manuscript to clarify the principle of the assay. In addition, we provided further control experiments suggested by Reviewers 2 and 3 showing that the fluorescence signal intensity depend on AtVPS13M1(1-335) protein concentration and that no fluorescence increase is measured with a control protein (Tom20.3) (see Figure 3C-D of the revised manuscript).

      The in vivo lipid binding assay could be obscured by the fact that the protein was produced in insect cells and lipid binding occurs during the producing. What is the evidence that added plants calli lipids can replace lipids already present during isolation.

      Actually we don’t really know whether the insect cells lipids initially bound to AtVPS13M1(1-335) are replaced by calli lipids or whether they bound to still available lipid binding sites on the protein. But we have two main lines of evidence showing that our purified protein can bind plant lipids even in the presence of insect cells lipids: 1) our protein can bind SQDG and MGDG, two plants specific lipids, and 2) as explained p.8 (lines 243-254), lipids coming from both organisms have a specific acyl-chain composition, with insect cells fatty acids mainly composed of C16 and C18 with 0 or 1 unsaturation whereas plant lipids can have up to 3 unsaturations. By analyzing and presenting on the histograms lipid species from insect cells, calli and those bound to AtVPS13M1(1-335), we were able to conclude that for all the lipid classes besides PS, a wide range of lipid species deriving from both organisms was bound to our protein. The data about the lipid species bound to AtVPS13M1(1-335) are presented in Figure 2E and S2.

      The effects on lipid composition of the mutants are not very drastic from what I can tell. Furthermore, how does this fit with the lipid composition of mitochondria where the protein appears to be mostly located?

      It is true that lipid composition variations in the mutants are not drastic but still statistically significant. As a general point in the field of lipid transfer, it is not very common to have major changes in total lipidome on single mutants of lipid transfer proteins because of a high redundancy of lipid transport pathway in cells. This is particularly true for VPS13 proteins, as exemplified by multiple studies. Major lipid phenotypes can be revealed in specific conditions, such as phosphate starvation in our case, or when looking at specific organelles or specific tissues and/or developmental stages. This is explained and illustrated by examples in the discussion part p. 16 (line 526-532). In addition, as suggested by Reviewer 3, we performed further lipid analysis on calli and also on rosettes under Pi starvation and found a similar trend (Figure 4 and S4 of the revised version of the manuscript). Thus, we believe that, even if not drastic, these variations during Pi starvation are a real phenotype of our mutants.

      As we found that our protein is located at the mitochondrial surface, we agree that Reviewer 1’s suggestion to perform lipidomic analyses on isolated mitochondria will be of high interest but this will be the scope of future studies that we will performed in our lab. First, we would like to identify all the organelles at which AtVPS13M1 is localized before performing subfractionations of these different organelles from the same pool of cell cultures grown in presence or absence of phosphate.

      For the localization of the fusion protein, has it been tested whether the furoin is functional? This should be tested (e.g. by reversion of lipid composition).

      As we did not observe major developmental phenotypes in our mutants, complementation should be indeed tested by performing lipidomic analyses in calli or plants grown in presence or absence of Pi, which is a time-consuming and expensive experiment. Because we used the fusions mainly for tissue expression study and subcellular localization and not for functional analyses, we believe that this is not an essential control to be performed for this work.

      It is speculated that different splice forms are located to different compartments. Can that be tested and used to explain the observed subcellular location patterns?

      Indeed some splice forms can modify the sequence of domains putatively involved in protein localization. This could be tested by producing synthetic constructs with one specific exon organization, which is challenging according to the size of AtVPS13M1 cDNA (around 12kb). In addition, our long-read sequencing experiment and PCR analyses revealed the existence of six transcripts, a major one representing around 92% and the five others representing less than 2.5% (Figure 1D). Among the five less abundant transcripts, four produce proteins with a premature stop codon and are likely to arise from splicing defects as explained in the discussion part p. 15 (lines 488-496). One produces a full-length protein with an additional loop in the VAB domain but because of the low abundance of this alternative transcript (1.4%), we believe it does not contribute significantly to the major localization we observed in plants and did not attend to analyze its localization.

      GUS fusion data only probe promoter activity but not all levels of gene expression. That caveat should be discussed.

      We are aware of this drawback and that is the reason why we fused the GUS enzyme directly to our protein expressed under its native locus (i.e. with endogenous promoter and exons/introns) as depicted in Figure 5A. Therefore, our construction allows to assess directly AtVPS13M1 protein level in plant tissues.

      Minor points: 1. Extraplastidic DGDG and export from chloroplasts following phosphate derivation was first reported in PMID: 10973486.

      We added this reference in the text.

      Check throughout the correct usage of gene expression as genes are expressed and proteins produced.

      Many thanks for this remark, we modified the text accordingly

      In general, the paper is too long. Redundancies between introduction, results and discussion should be removed to streamline.

      We reduced the text to avoid redundancy.

      I suggest to redraw the excel graphs to increase line thickness and enlarge font size to increase presentation and readability.

      We tried as much as we can to enlarge graphs and font size increasing readability.

      Reviewer #1 (Significance (Required)):

      Significance: Interorganellar lipid trafficking is an important topic and especially under studied in plants. Identifying components involved represents significant progress in the field. Similarly, lipid remodeling following phosphate derivation is an important phenomenon and the current advances our understanding.

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

      Summary: The manuscript "AtVPS13M1 is involved in lipid remodelling in low phosphate and is located at the mitochondria surface in plants" by Leterme et al. identifies the protein VPS13M1 as a lipid transporter in Arabidopsis thaliana with important functions during phosphate starvation. The researchers were able to localise this protein to mitochondria via GFP-targeting in Arabidopsis. Although VPS13 proteins are well described in yeast and mammals, highlighting their importance in many vital cellular processes, there is very little information on them in plants. This manuscript provides new insights into plant VPS13 proteins and contributes to a better understanding of these proteins and their role in abiotic stress responses, such as phosphate starvation.

      Major points: - Please describe and define the domains of the VPS13M1 protein in detail, providing also a figure for that. Figure 1 is mainly describing possible splice variants, whereas the characteristics of the protein are missing.

      We have added information on AtVPS13M1 domain organization in the introduction (p.4, lines 103-109) and referred to Figure 1A that described protein domain organization. We did not added too much details as plant VPS13 protein domains organization was extensively described in two previous studies cited several times in the manuscript (Leterme et al., 2023; Levine, 2022).

      • Please compare the expression level of VPS13M1 in the presence and in the absence of phosphate.

      Many thanks for this suggestion. We performed qRT-PCR analyses of AtVPS13M1 from mRNA extracted from calli grown six days in presence and absence of phosphate. The results obtained did not reveal variations in mRNA level. The results were added in Figure S1A of the revised version of the manuscript and discussed in p.5 (lines 154-156).

      • Page 9, second paragraph: Here, the lipid transport capability of AtVPS13M1 is described. Varying concentrations of this recombinant protein should be used in this test. Further, it is not highlighted, that a truncated version of VSP13M1 is able to transport lipids. This is surprising, since this truncated version is less than 10% of the total protein (only aa 1-335).

      We agree with reviewer 2 that increasing protein concentration is an important control to perform. We included an experiment with an increasing quantity of protein (2X and 4X) in the revised version of the manuscript and showed that the signal intensity increased faster when protein concentration is higher (Figure 3D of the revised manuscript). As requested by Reviewer 3, we also included a negative control with Tom20.3 to show that the signal increase after the addition of AtVPS13M1(1-335) is specific to this protein (Figure 3C of the revised manuscript).

      The transport ability of the N-terminal part of VPS13 was demonstrated in yeast and mammals VPS13D (Kumar et al., 2018; Wang et al., 2021). We highlighted this p. 7 (lines 213-218) of the revised version of the manuscript. This is explained by the inherent structure of VPS13 proteins that are composed of several repeats of the same domain type called RBG (for repeating β-groove), each forming a β-sheet with a hydrophobic surface. The higher the number of RBG repeats, the longer the hydrophobic tunnel is. The (1-335) N-terminal region corresponds to two RBG unit repeats forming a “small” tunnel able to bind and transfer lipids. The number of RBG repeats has influence on the quantity of lipids bound per protein in vitro, the longest the protein is, the highest the number of lipid molecules bound is (Kumar et al., 2018), but the effect on protein length on in vitro lipid transfer capacity has not been investigated yet to the best of our knowledge.

      • Also, for phenotype analysis, T-DNA insertion mutants are used that still contain VPS13M1 transcripts. Although protein fragments where not detected by proteomic analysis, this might be due to low sensitivity of the proteomic assay. Further the lipid transport domain of VPS13M1 (aa 1-335) might not be affected by the T-DNA insertions at all. Here more detailed analysis needs to be done to prove that indeed loss-of protein function occurs in the mutants.

      We do not have other methods than proteomic to test whether our mutants are KO or not. We tried unsuccessfully to produce antibodies. Mass spectrometry is the most sensitive method but the absence of detection indeed does not mean the absence of the protein. From proteomic data, we can conclude that at least, our mutants present a decrease in AtVPS13M1 protein level, thus we called them “knock down” in the revised version of the manuscript and added the following sentence p. 9 (lines 297-300): “As the absence of detection of a protein by mass spectrometry-based proteomics does not allow us to strictly claim the absence of this protein in the sample, we concluded that AtVPS13M1 expression in both atvps13m1-1 and atvps13m1-4 was below the detection limit and consider them as knock down (KD) for AtVPS13M1.”

      • Localisation in mitochondria: As the Yepet signal is very weak, a control image of not transfected plant tissue needs to be included. Otherwise, it might be hard to distinguish the Yepet signal from background signal. The localisation data presented in Figure 5 does not allow the conclusion that VPS13M1 is localized at the surface of mitochondria as stated in the title. It only indicates (provided respective controls see above) that VPS13M1 is in mitochondria. Please provide more detailed analysis such as targeting to tobacco protoplasts, immunoblots or in vitro protein import assays. Also test +Pi vs. -Pi to see if VPS13M1 localisation is altered in dependence of Pi.

      Indeed our Yepet signal is not very strong but on the experiments we performed on Col0 non-transformed plants, we did not very often see fluorescence background in the leaves’ vascular tissue, that is why we focused our study on this tissue. We sometimes observed some background signals in some cells that are clearly different from AtVPS13M1-3xYepet signals and never co-localized with mitochondria. Examples of these aspecific signals are presented in Figure S6E of the revised version of the manuscript.

      We agree with reviewer 2 that our confocal images suggested, but not demonstrated, a localization at the surface of mitochondria. To confirm the localization, we generated calli cell cultures from AtVPS13M1-3xYepet lines and performed subcellular fractionations and western blot analyses confirming that AtVPS13M1 was indeed enriched in mitochondria and also in microsomal fractions (Figure 6G of the revised version). Then we performed mild proteolytic digestion of the isolated mitochondria with thermolysin and show that AtVPS13M1 was degraded, as the outer membrane protein Tom20.3, but not the inner membrane protein AtMic60, showing that AtVPS13M1 is indeed at the surface of mitochondria (Figure 5H of the revised manuscript). We believe that this experiment, in addition to the confocal images showing a signal around mitochondria, convincingly demonstrates that AtVPS13M1 is located at the surface of mitochondria.

      The localization of AtVPS13M1 under Pi starvation is a very important question that we tried to investigate without success. Indeed, we intended to perform confocal imaging on seedlings grown in liquid media to easily perform Pi starvation as described for the analysis of AtVPS13M1 tissue expression with β-glucuronidase constructs. However, the level of fluorescence background was very high in seedlings and no clear differences between non-transformed and AtVPS13M1-3xYepet lines were observed, even in root tips where the protein is supposed to be the most highly expressed according to β-glucuronidase assays. Example of images obtained are presented in Figure R1. We concluded that the level of expression of our construct was too low in seedlings. The constructions of lines with a higher AtVPS13M1 expression level, by changing the promotor, to better analyze AtVPS13M1 in different tissues or in response to Pi starvation will be the scope of future work in our laboratory in order to investigate AtVPS13M1 localization under low Pi.

      Phenotype analysis needs to be done under Pi stress and not under cold stress! Further, root architecture and root growth should also be done under Pi depletion. Here the title is also misleading, it is not at all clear why the authors switch from phosphate starvation to cold stress.

      In the revised version of the manuscript, we analyzed the seedlings root growth of two mutants (atvps13m1-3 and m1-4) under low Pi and did not notice significant differences (Figure 7E, S7D of the revised version). We analyzed growth under cold stress because this stress also promotes remodeling of lipids, but we agree that it goes beyond the scope of this article that is focused on Pi starvation and we removed this part from the revised manuscript.

      Minor points: Page 3, line 1: what does the abbreviation VPS stand for?

      The definition of VPS (Vacuolar Protein Sorting) was added.

      Page 3, line 1: change "amino acids residues" to "amino acid residues"

      This was done.

      Page 3, line 8 - 12: please rewrite this sentence. You write, that because of their distribution VPS13 proteins do exhibit many important physiological roles. The opposite is true: They are widely distributed in the cell because of their involvement in many physiological processes.

      We changed the sentence to “ VPS13 proteins localize to a wide variety of membranes and membrane contact sites (MCSs) in yeast and human (Dziurdzik and Conibear, 2021). This broad distribution on different organelles and MCSs is important to sustain their important roles in numerous cellular and organellar processes such as meiosis and sporulation, maintenance of actin skeleton and cell morphology, mitochondrial function, regulation of cellular phosphatidylinositol phosphates level and biogenesis of autophagosome and acrosome (Dziurdzik and Conibear, 2021; Hanna et al., 2023; Leonzino et al., 2021).”

      Page 6, line6: change "cDNA obtained from A. thaliana" to "cDNA generated from A. thaliana.

      This was done.

      Page 6, line 10: change" 7.6kb" to "7.6 kb"

      This was done.

      Page 7: address this question: can the isoforms form functional VPS13 proteins? This might help to postulate whether these isoforms are a result of defective splicing events.

      We addressed this aspect in the discussion p.15 at lines 486-502.

      Figure 2 B: Change "AtVPS13M1"to "AtVPS13M1(1-335)"

      This was done.

      Figure 2, legend: -put a blank before µM in each case.

      This was done.

      -Change 0,125µM to 0.125 µM

      This was done.

      -what does "in absence (A-0µM)" mean?

      This means that the Acceptor liposomes are at 0 µM. To clarify, we changed it to “Acceptor 0 µM” in the revised version of the manuscript (Figure 3C).

      -Which statistical analysis was employed?

      We performed a non-parametric Mann-Whitney test in the revised version of the manuscript. This was indicated in the legend.

      -Further, rewrite the sentence "Mass spectrometry (MS) analysis of lipids bound to AtVPS13M1(1-335) or Tom20 (negative control) after incubation with calli total lipids. Results are expresses in nmol of lipids per nmol of proteins (C) or in mol% (D)". -"C" and "D" are not directly comparable, as in "C" no Tom20 was used and in "C" no insect cells were used.

      -Further, in "D" the experimental setup is not clear. AtVPS13(1-335) is supposed to be purified protein after incubation with calli lipids (figure 2, A). Further, in the same figure, lipid composition of "insect cells" and "calli-Pi" are compared àwhy? Please clarify this.

      C and D are two different representations of the same results providing different types of information. In C., the results are expressed in nmol of lipids / nmol of proteins to assess 1) that the level of lipids found in AtVPS13M1(1-335) purifications is significantly higher than what we can expect from the background (assessed using Tom20) and 2) what are the classes of lipids that associate or not to AtVPS13M1(1-335). In D. the lipid distribution in mol% is presented for AtVPS13M1(1-335) as well as for total extracts from calli and insect cells to be able to compare if one lipid class is particularly enriched or not in AtVPS13M1(1-335) purifications compared to the initial extracts with which the protein was incubated. As an example, it allows to deduce that the absence of DGDG detected in the AtVPS13M1(1-335) purifications is not linked to a low level of DGDG in the calli extract, because it represented around 15 mol%, but likely to a weak affinity of the protein for this lipid. We did not represent the Tom20 lipid distribution on this graph because it represents background of lipid binding to the purification column and might suggest that Tom20 binds lipids. We changed the legend in this way and hope that it is clearer now: “C-D. Mass spectrometry (MS) analysis of lipids bound to AtVPS13M1(1-335) or Tom20 (negative control) after incubation with calli total lipids and repurification. Results are expresses in nmol of lipids per nmol of proteins in order to analyze the absolute quantity of the different lipid classes bound to AtVPS13M1(1-335) compared to Tom20 negative control (C), and in mol% to assess the global distribution of lipid classes in AtVPS13M1(1-335) purifications compared to the total lipid extract of insect cells and calli (D).”

      Figure 3: -t-test requires a normal distribution of the data. This is not possible for an n=3. Please use an adequate analysis.

      We performed more replicates and used non-parametric Mann-Whitney analyses in the revised version of the manuscript.

      -Please clarify the meaning of the letters on the top of the bars in the legend.

      This corresponded to the significance of t-tests performed in the first version of the manuscript that were reported in Table S3. As in the new version we performed Mann-Whitney tests, we highlighted the significance by stars and in the figure legends.

      Please, make it clear that two figures belong to C.

      This was clarified in the legend.

      -Reorganise the order of figure 3 (AàBàCàD)

      Because of the configuration of the different histograms presented in the figure, we were not able to change the order but we believed that the graphs can be easily red this way.

      Page 10, 3. Paragraph: since the finding, that no peptides were found in the VSP13M1 ko lines, although transcription was not altered, is surprising, please include the proteomic data in the supplement

      Proteomic data were deposited on PRIDE with the identifier PXD052019. They will remain not publicly accessible until the acceptance of the manuscript.

      Page 11, line 17: The in vitro experiments showed a low affinity of VSP13M1 towards galactolipids. It is further claimed that this is consistent with the finding of the AtVSP13M1 Ko line in vivo, that in absence of PI, no change in DGDG content could be observed. However, the "absence" of VSP13M1 in vivo might still result in a bigger VSP13M1 protein, than the truncated form (1-335) used for the in vitro experiments

      It is true that our in vitro experiments were performed only with a portion of AtVPS13M1 and that the length of the protein could influence protein binding specificity. We removed this assessment from the manuscript.

      Page 13, lane 8: you should reconsider the use of a triple Yepet tag: If two or more identical fluorescent molecules are in close proximity, their fluorescence emission is quenched, which results in a weak signal (as the one that you obtained). See: Zhuang et al. 2000 (PNAS) Fluorescence quenching: A tool for single-molecule protein-folding study

      Many thanks to point this paper. We use a triple Yepet because AtVPS13M1 has a very low level of expression and because this strategy was used successfully to visualize proteins for which the signal was below the detection level with a single GFP (Zhou et al., 2011). The quenching of the 3xYepet might also depend on the conformation they adopt on the targeting protein.

      Page 13, line 14: change 1µm to 1 µm

      This was done.

      Page 13, line 29: please reduce the sentence to the first part: if A does not colocalize with B, it is not necessary to mention that B does not colocalise with A.

      The sentence was modified accordingly.

      Page 14, 2. Paragraph: it is not conclusive that phenotype analysis is suddenly conducted with plants under cold stress, since everything was about Pi-starvation and the role of VSP13M1. Lipid remodelling under Pi stress completely differs from the lipid remodelling under cold stress.

      We eliminated this part in the revised version of the manuscript.

      Page 14, line 20: change figure to Figure

      This was done.

      Page 07, line 17: change artifact to artefact

      This was done.

      Reviewer #2 (Significance (Required)):

      General assessment: The paper is well written and technically sound. However, some points could be identified, that definitely need a revision. Overall, we got the impression that so far, the data gathered are still quite preliminary and need some more detailed investigations prior to publication (see major points).

      Advance: The study definitely fills a gap of knowledge since not much is known on the function of plant VPS13 proteins so far.

      Audience: The study is of very high interest to the plant lipid community but as well of general interest for Plant Molecular Biology and intracellular transport.

      Our expertise: Plant membrane transport and lipid homeostasis.

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

      The manuscript by Leterme et al. (2024) describes the characterization of VPS13M1 from Arabidopsis. VPS13 proteins have been analyzed in yeast and animals, where they establish lipid transfer connections between organelles, but not much is known about VPS13 proteins in plants. First, different splicing forms were characterized, and the form A was identified as the most relevant one with 92% of the transcripts. The protein (just N-terminal 335 amino acids out of ca. 3000 amino acids) was expressed in insect cells and purified. Next, the protein was used for lipid binding assays with NBD-labeled lipids followed by analysis in polyacrylamide gel electrophoresis. VPS13M1 bound to PC, PE, PS and PA. Then, the protein from insect cells was incubated with Arabidopsis callus lipids, and lipids bound to VPS13M1 analyzed by LC-MS/MS. Lipid transfer between liposomes was measured by the change in fluorescence in donor liposomes derived from two labeled lipids after addition of the protein caused by lipid transfer and dilution to acceptor liposomes. T-DNA insertion mutants were isolated and the lipids measured in callus derived from these mutants. Protein localization in different plant organs was recorded with a GUS fusion construct transferred into transgenic plants. The protein was localized to mitochondria using a VPS13M1-Yepet fusion construct transferred into mutant plants. The mutant plants show no visible difference to wild type, even when the plants were grown under stress conditions like low temperature. The main message of the title is that VPS13M1 localizes to the mitochondria which is well documented, and it is involved in lipid remodeling under low phosphate conditions.

      The lipid transfer assay shown in Figure 2F lacks a negative control. This would be the experiment with donor and acceptor liposomes in the presence of another protein like Tom20.

      Many thanks for this suggestion. In the revised version of the manuscript, we performed a fluorescent lipid transport assay with Tom20.3 in the presence of 25 µM of donor liposomes and 1.5 mM of acceptor liposomes, the condition for which we observed a maximum of transport for AtVPS13M1(1-335). As expected, no fluorescence increase was observed. The results are presented in the Figure 3C of the revised manuscript.

      The lipid data (Fig. 3 and Fig. S4) do not sufficiently support the second claim, i.e. that the protein is involved in lipid remodeling under low P. Data in Fig. 3C are derived from only 3 replicates and in Fig. S4 from only 2 replicas with considerable error bars. Having only 2 replicates is definitely not sufficient. Fig. 3C shows a suppression in the decrease in PE and PC at 4 d of P deprivation (significant for two mutants for PE, for only one for PC). Fig. S4A shows suppression of the decrease in PC at 6 d after P deprivation (significant for both mutants), but no significant effect on PE. Fig. 4SB shows no significant change in PE or PC at -P after 8 d of P deprivation. The data are not consistent. There are also problems with the statistics in Fig. 3 and Fig. S4. The authors used T-test, but place letters a, b, c on top of the bars. Usually, asterisks should be used to indicate significant differences. Data indicate medians and ranges, not mean and SD. In Fig. S4, how can you indicate median and range if you have only 2 replicates? Why did the authors use callus for lipid measurements? Why not use leaves and root tissues? What does adjusted nmol mean? What does the dashed line at 1.05 on the y axis mean? Taken together, I suggest to repeat lipid measurements with leaves and roots from plantets grown under +P and -P conditions in tissue culture with 5 replcates. Significant differences can be analyzed on the level of absolute (nmol per mg FW/DW) or relative (%) amounts.

      Here are our answers to concerns about the design of our lipidomics experiments:

      We used calli for lipid measurement because it is very easy to control growth conditions and to performed phosphate starvation from this cell cultures. The second reason is that it is a non-photosynthetic tissue with a high level of phospholipids and a low level of galactoglycerolipids and it is easier to monitor the modification of the balance phospholipids/galactoglycerolipids in this system. The lipid analysis on calli at 4 days of growth in presence or absence of Pi were performed on 3 biological replicates but on two different mutants (atvps13m-1 and m1-3) and we drew our conclusions based on variations that were significant for both mutants. In the revised version of the manuscript, we performed further lipidomic analyses on calli from Col0 and another mutant (atvps13m1-2) after 6 days of growth in presence or absence of Pi (Figure 4E, S4A-C, n=4-5) and added new data on a photosynthetic tissue (rosettes) from Col0 and atvps13m1-3 mutant. For rosettes analysis, seeds were germinated 4 days in plates with 1 mM Pi and then transferred on plates with 1 mM or 5 µM of Pi. Rosettes were harvested and lipids analyzed after 6 days (Figure 4F-G, S4D, n=4-5). All the data were represented with medians and ranges because we believe that median is less sensitive to extreme values than mean and might better represent what is occurring. Ranges highlight the minimal and maximal value of the data analyzed and we believe it is a representative view of the variability we obtained between biological samples.

      Lipid measurement are done by mass spectrometry. As it was already reported, mass spectrometry quantification is not trivial as the intensity of the response depends on the nature of the molecule (for a review, see (Jouhet et al., 2024)). To counteract this ionisation problem, we developed a method with an external standard that we called Quantified Control (QC) corresponding to an A. thaliana callus lipid extract for which the precised lipid composition was determined by TLC and GC-FID. All our MS signals were “adjusted” to the signal of this QC as described in (Jouhet et al., 2017). Therefore our lipid measurement are in adjusted nmol. In material and method we modified the sentence accordingly p22 lines 720-723: “Lipid amounts (pmol) were adjusted for response differences between internal standards and endogenous lipids and by comparison with a quality control (QC).” This allows to represent all the lipid classes on a same graph and to have an estimation of the lipid classes distribution. To assess the significance of our results, we used in the revised version of the manuscript non-parametric Mann-Whitney tests and added stars representing the p-value on charts. This was indicated in the figure legends.

      Here are our answers to concerns about the interpretation of our lipidomics experiments:

      To summarize, in the revised version of the manuscript, lipid analyses were performed in calli from 3 different mutants (two at day 4, one at day 6) and in the rosettes from one of these mutants. All the results are presented in Figure 4 and S4. In all the experiments, we found that in +Pi, there is no major modifications in the lipid content or composition. In –Pi, we found that the total glycerolipid content is always higher in the mutant compared to the Col0, whatever the tissue or mutant considered (Figure 4A and S4A, D). In calli, this higher increase in lipid content is mainly due to an accumulation of phospholipids and in rosettes, of galactolipids. Because of high variability between our biological replicates, we did not always found significant differences in the absolute amount of lipids in –Pi. However, the analysis of the fold change in lipid content in –Pi vs +Pi always pointed toward a reduced extent of phospholipid degradation. We also added in these graphs the fold change for the total phospholipids and total galactolipids contents in the revised version of the manuscript. We believe that the new analyses we performed strengthen our conclusion about the role of AtVPS13M1 in phospholipid degradation and not on the recycling of precursors backbone to feed galactoglycerolipids synthesis at the chloroplast envelope.

      Page 9, line 15: Please use the standard form of abbreviations of lipid molecular species with colon, e.g. PC32:0, not PC32-0

      The lipid species nomenclature has been changed accordingly.

      Page 11, line 4, (atvps13m1.1 and m1.3: please indicate the existence of mutant alleles with dashes, i.e. (atvps13m1-1 and atvps13m1-3

      Names of the mutants have been changed accordingly.

      Page 14, line 21: which line is indicated by atvps13m1.2-4? What does -4 indicate here?

      This indicates that mutants m1-2 to m1-4 were analyzed.

      Page 16, line 25: many abbreviations used here are very specific and not well known to the general audience e.g. ONT, IR, PTC, NMD etc. I think it is OK to mention them here, but still use the full terms, given that they are not used very frequently in the manuscript.

      We kept ONT abbreviation because it was cited many times in both the results and discussion part. IR, PTC and NMD were cited only in the discussion and were eliminated.

      Page 19, line 11. The authors cite Hsueh et al and Yang et al for LPTD1 playing a role in lipid homeostasis during P deficiency. But Yang et al. described the function of a SEC14 protein in Arabidopsis and rice during P deficiency. Is SEC14 related to LPTD1?

      Many thanks for noticing this mistake. We removed the citation Yang et al. in the revised version of the manuscript.

      Reference Tangpranomkorn et al. 2022: In the text, it says that this is a preprint, but in the Reference list, this is indicated with "Plant Biology" as Journal. In the internet, I could only find this manuscript in bioRxiv.

      This manuscript was accepted in “New Phytologist” in December 2024 and is now cited accordingly in the new version of the manuscript.

      Reviewer #3 (Significance (Required)):

      The manuscript by Leterme et al describes the characterization of the lipid binding and transport protein VTPS13M1 from Arabidopsis. I think that the liposome assay needs to be done with a negative control. Furthermore, I have major concerns with the lipid data in Fig. 3C and Fig. S4. These lipid data of the current manuscript need to be redone. I do not agree that the lipid data allow the conclusion that "AtVPS13M1 is involved in lipid remodeling in low phosphate" as stated in the title.

      References cited in this document:

      Dziurdzik, S.K., and E. Conibear. 2021. The Vps13 Family of Lipid Transporters and Its Role at Membrane Contact Sites. Int J Mol Sci. 22:2905. doi:10.3390/ijms22062905.

      Hanna, M., A. Guillén-Samander, and P. De Camilli. 2023. RBG Motif Bridge-Like Lipid Transport Proteins: Structure, Functions, and Open Questions. Annu Rev Cell Dev Biol. 39:409–434. doi:10.1146/annurev-cellbio-120420-014634.

      Hanna, M.G., P.H. Suen, Y. Wu, K.M. Reinisch, and P. De Camilli. 2022. SHIP164 is a chorein motif lipid transfer protein that controls endosome–Golgi membrane traffic. Journal of Cell Biology. 221:e202111018. doi:10.1083/jcb.202111018.

      Jouhet, J., E. Alves, Y. Boutté, S. Darnet, F. Domergue, T. Durand, P. Fischer, L. Fouillen, M. Grube, J. Joubès, U. Kalnenieks, J.M. Kargul, I. Khozin-Goldberg, C. Leblanc, S. Letsiou, J. Lupette, G.V. Markov, I. Medina, T. Melo, P. Mojzeš, S. Momchilova, S. Mongrand, A.S.P. Moreira, B.B. Neves, C. Oger, F. Rey, S. Santaeufemia, H. Schaller, G. Schleyer, Z. Tietel, G. Zammit, C. Ziv, and R. Domingues. 2024. Plant and algal lipidomes: Analysis, composition, and their societal significance. Progress in Lipid Research. 96:101290. doi:10.1016/j.plipres.2024.101290.

      Jouhet, J., J. Lupette, O. Clerc, L. Magneschi, M. Bedhomme, S. Collin, S. Roy, E. Maréchal, and F. Rébeillé. 2017. LC-MS/MS versus TLC plus GC methods: Consistency of glycerolipid and fatty acid profiles in microalgae and higher plant cells and effect of a nitrogen starvation. PLoS ONE. 12:e0182423. doi:10.1371/journal.pone.0182423.

      Kumar, N., M. Leonzino, W. Hancock-Cerutti, F.A. Horenkamp, P. Li, J.A. Lees, H. Wheeler, K.M. Reinisch, and P. De Camilli. 2018. VPS13A and VPS13C are lipid transport proteins differentially localized at ER contact sites. J Cell Biol. 217:3625–3639. doi:10.1083/jcb.201807019.

      Leonzino, M., K.M. Reinisch, and P. De Camilli. 2021. Insights into VPS13 properties and function reveal a new mechanism of eukaryotic lipid transport. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1866:159003. doi:10.1016/j.bbalip.2021.159003.

      Leterme, S., O. Bastien, R.A. Cigliano, A. Amato, and M. Michaud. 2023. Phylogenetic and Structural Analyses of VPS13 Proteins in Archaeplastida Reveal Their Complex Evolutionary History in Viridiplantae. Contact (Thousand Oaks). 6:1–23. doi:10.1177/25152564231211976.

      Levine, T.P. 2022. Sequence Analysis and Structural Predictions of Lipid Transfer Bridges in the Repeating Beta Groove (RBG) Superfamily Reveal Past and Present Domain Variations Affecting Form, Function and Interactions of VPS13, ATG2, SHIP164, Hobbit and Tweek. Contact. 5:251525642211343. doi:10.1177/25152564221134328.

      Valverde, D.P., S. Yu, V. Boggavarapu, N. Kumar, J.A. Lees, T. Walz, K.M. Reinisch, and T.J. Melia. 2019. ATG2 transports lipids to promote autophagosome biogenesis. J Cell Biol. 218:1787–1798. doi:10.1083/jcb.201811139.

      Wang, J., N. Fang, J. Xiong, Y. Du, Y. Cao, and W.-K. Ji. 2021. An ESCRT-dependent step in fatty acid transfer from lipid droplets to mitochondria through VPS13D−TSG101 interactions. Nat Commun. 12:1252. doi:10.1038/s41467-021-21525-5.

      Zhou, R., L.M. Benavente, A.N. Stepanova, and J.M. Alonso. 2011. A recombineering-based gene tagging system for Arabidopsis. Plant J. 66:712–723. doi:10.1111/j.1365-313X.2011.04524.x.

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      Referee #3

      Evidence, reproducibility and clarity

      The manuscript by Leterme et al. (2024) describes the characterization of VPS13M1 from Arabidopsis. VPS13 proteins have been analyzed in yeast and animals, where they establish lipid transfer connections between organelles, but not much is known about VPS13 proteins in plants. First, different splicing forms were characterized, and the form A was identified as the most relevant one with 92% of the transcripts. The protein (just N-terminal 335 amino acids out of ca. 3000 amino acids) was expressed in insect cells and purified. Next, the protein was used for lipid binding assays with NBD-labeled lipids followed by analysis in polyacrylamide gel electrophoresis. VPS13M1 bound to PC, PE, PS and PA. Then, the protein from insect cells was incubated with Arabidopsis callus lipids, and lipids bound to VPS13M1 analyzed by LC-MS/MS. Lipid transfer between liposomes was measured by the change in fluorescence in donor liposomes derived from two labeled lipids after addition of the protein caused by lipid transfer and dilution to acceptor liposomes. T-DNA insertion mutants were isolated and the lipids measured in callus derived from these mutants. Protein localization in different plant organs was recorded with a GUS fusion construct transferred into transgenic plants. The protein was localized to mitochondria using a VPS13M1-Yepet fusion construct transferred into mutant plants. The mutant plants show no visible difference to wild type, even when the plants were grown under stress conditions like low temperature. The main message of the title is that VPS13M1 localizes to the mitochondria which is well documented, and it is involved in lipid remodeling under low phosphate conditions. The lipid transfer assay shown in Figure 2F lacks a negative control. This would be the experiment with donor and acceptor liposomes in the presence of another protein like Tom20. The lipid data (Fig. 3 and Fig. S4) do not sufficiently support the second claim, i.e. that the protein is involved in lipid remodeling under low P. Data in Fig. 3C are derived from only 3 replicates and in Fig. S4 from only 2 replicas with considerable error bars. Having only 2 replicates is definitely not sufficient. Fig. 3C shows a suppression in the decrease in PE and PC at 4 d of P deprivation (significant for two mutants for PE, for only one for PC). Fig. S4A shows suppression of the decrease in PC at 6 d after P deprivation (significant for both mutants), but no significant effect on PE. Fig. 4SB shows no significant change in PE or PC at -P after 8 d of P deprivation. The data are not consistent. There are also problems with the statistics in Fig. 3 and Fig. S4. The authors used T-test, but place letters a, b, c on top of the bars. Usually, asterisks should be used to indicate significant differences. Data indicate medians and ranges, not mean and SD. In Fig. S4, how can you indicate median and range if you have only 2 replicates? Why did the authors use callus for lipid measurements? Why not use leaves and root tissues? What does adjusted nmol mean? What does the dashed line at 1.05 on the y axis mean? Taken together, I suggest to repeat lipid measurements with leaves and roots from plantets grown under +P and -P conditions in tissue culture with 5 replcates. Significant differences can be analyzed on the level of absolute (nmol per mg FW/DW) or relative (%) amounts. Page 9, line 15: Please use the standard form of abbreviations of lipid molecular species with colon, e.g. PC32:0, not PC32-0 Page 11, line 4, (atvps13m1.1 and m1.3: please indicate the existence of mutant alleles with dashes, i.e. (atvps13m1-1 and atvps13m1-3

      Page 14, line 21: which line is indicated by atvps13m1.2-4? What does -4 indicate here? Page 16, line 25: many abbreviations used here are very specific and not well known to the general audience e.g. ONT, IR, PTC, NMD etc. I think it is OK to mention them here, but still use the full terms, given that they are not used very frequently in the manuscript. Page 19, line 11. The authors cite Hsueh et al and Yang et al for LPTD1 playing a role in lipid homeostasis during P deficiency. But Yang et al. described the function of a SEC14 protein in Arabidopsis and rice during P deficiency. Is SEC14 related to LPTD1? Reference Tangpranomkorn et al. 2022: In the text, it says that this is a preprint, but in the Reference list, this is indicated with "Plant Biology" as Journal. In the internet, I could only find this manuscript in bioRxiv.

      Significance

      The manuscript by Leterme et al describes the characterization of the lipid binding and transport protein VTPS13M1 from Arabidopsis. I think that the liposome assay needs to be done with a negative control. Furthermore, I have major concerns with the lipid data in Fig. 3C and Fig. S4. These lipid data of the current manuscript need to be redone. I do not agree that the lipid data allow the conclusion that "AtVPS13M1 is involved in lipid remodeling in low phosphate" as stated in the title.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary: An analysis of an Arabidopsis VSP13 presumed lipid transport is provided. The analysis pretty much follows similar studies done on yeast and human homologs. Key findings are the identification of multiple products from the locus due to differential splicing, analysis of lipid binding and transport properties, subcellular location, tissue specific promoter activity, mutant analysis suggesting a role in lipid remodeling following phosphate deprivation, but no physiological or growth defects of the mutants.

      Major points: The paper is generally written and documented, the experiments are well conducted and follow established protocols. The following major points should be considered:

      1. There are complementary lipid binding assays that should be considered such as liposome binding assays, or lipid/western dot blots. All of these might give slightly different results and may inform a consensus. Of course, non-membrane lipids such as TAG cannot be tested in a liposome assay.
      2. Similarly, lipid transfer based only on fluorophore-labeled lipids may be misleading because the fluorophore could affect binding. It is mentioned that the protein in this assay is tethered by 3xHiis to the liposomes. Un less I ma missing something, I do not understand how that should work. This needs to be better explained.
      3. The in vivo lipid binding assay could be obscured by the fact that the protein was produced in insect cells and lipid binding occurs during the producing. What is the evidence that added plants calli lipids can replace lipids already present during isolation.
      4. The effects on lipid composition of the mutants are not very drastic from what I can tell. Furthermore, how does this fit with the lipid composition of mitochondria where the protein appears to be mostly located?
      5. For the localization of the fusion protein, has it been tested whether the furoin is functional? This should be tested (e.g. by reversion of lipid composition).
      6. It is speculated that different splice forms are located to different compartments. Can that be tested and used to explain the observed subcellular location patterns?
      7. GUS fusion data only probe promoter activity but not all levels of gene expression. That caveat should be discussed.

      Minor points:

      1. Extraplastidic DGDG and export from chloroplasts following phosphate derivation was first reported in PMID: 10973486.
      2. Check throughout the correct usage of gene expression as genes are expressed and proteins produced.
      3. In general, the paper is too long. Redundancies between introduction, results and discussion should be removed to streamline.
      4. I suggest to redraw the excel graphs to increase line thickness and enlarge font size to increase presentation and readability.

      Significance

      Interorganellar lipid trafficking is an important topic and especially under studied in plants. Identifying components involved represents significant progress in the field. Similarly, lipid remodeling following phosphate derivation is an important phenomenon and the current advances our understanding.

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      Reply to the reviewers

      Reviewer #1

      Evidence, reproducibility and clarity

      The authors study early events initiated in T cells upon chemokine activation leading to cell polarization preceding cell migration. The show that actin dynamics at the centrosome are regulated in a cAMP/PKA dependent manner using different reporter systems and imaging approaches

      Significance

      This work will be of interest to immunologists with a strong cell biology background. The strength of the study is the detailed cell biological / near biophysical analysis of early changes in acting dynamics in relation to centrosome positioning. THe data is well controlled and convincing. Conclusions adequate based on available data.

      The limitation I see is the use of a single cell line system of cancerous origin and the fact that only changes in cellular morphology are quantified, but not cellular behavior itself - e.g migration, T cell intrinsic signalling. If some key observations can be validated in primary T cells this would be perfect, or at least in a second model system. If signalling related to changed morphology is affect by regional inhibition of PKA/actin remodelling, remains uncertain, too - maybe there is a way to monitor additional parameters, other than roundness/PKA activity.

      • In order to complete our results, key experiments have been performed in primary human blood T lymphocytes (PBT). 4 experiments have been realized with 4 different donors. In this model, as in CEM T cell line, we have observed that:
      • chemokine-induced PBT deformation is inhibited by the PKA inhibitor H89. Unstimulated PBT are poorly deformed so that H89 by itself only slightly (but not significantly) increases resting roundness.

      • chemokine stimulation induces a decrease of centrosomal actin which is partly prevented by H89 treatment. In these conditions, centrosomal actin remains at a level superior to the resting one. H89 by itself is sufficient to promote an increase in centrosomal actin.

      Altogether, these results demonstrate that in PBT as in CEM, in resting conditions as well as after chemokine stimulation, the level of centrosomal actin is controlled by PKA activity and is associated with cell deformation.

      These new results are presented in Fig Supp 4 and described in the manuscript (lines 158-164 and 199-202).

      • In order to investigate the consequences of the PKA inhibition on chemokine-induced cell behavior, Transwell migratory assays have been performed. As presented in Fig Supp 3b, the chemokine-triggered T cell migration through 5µm pores is reduced by H89 This suggests that the reduction of T cell deformation after PKA inhibition has a direct consequence on the physiological behavior of T lymphocyte. This result is described in the manuscript (lines 165-169).

        __Reviewer #2 __

      Evidence, reproducibility and clarity

      The ability of T cells to migrate along chemotactic cues is critical for the initiation and regulation of adaptive immune responses. To migrate directionally, cells require a polarised shape and intracellular organisation, allowing intracellular force generation towards the intended direction of migration.

      The manuscript by Simao et al investigates the role of the centrosome and its co-localised pool of the actin cytoskeleton in defining the direction of an initial polarisation while being surrounded by homogenous chemokine concentration. The authors (i) describe a correlation of the intracellular position of the centrosome with the site of polarisation, (ii) identify that a reduced amount of actin at the centrosome is beneficial for cell polarisation and that (iii) the protein kinase PKA regulates this actin pool at the centrosome.

      Overall, the data presented appear convincing but would benefit from a more detailed presentation of representative image examples and additional experimental data.

      Major points:

      (i) Many experimental microscopy datasets are quantified but lack representative images. These representative images are important to be able to judge the underlying data and should be included for the datasets shown in Figure 2, Fig. 3c, Fig. 4d (Lifeact examples), and Fig. 6 (Centrin VCA). In addition, the differences in the signal intensity of the actin cytoskeleton are sometimes hardly visible in the provided representative images (e.g., Fig. 4b, control vs CXCL12). Could the authors come up with solutions to show this in a better way (e.g., zooms and/or fire-colour coding)?

      As suggested by the reviewer, some representative images have been added for all experiments (Figures 3, Supp 3a, Supp 4 a & c, Supp 7a, Supp 8). Furthermore, a zoom of actin network around the centrosome in different conditions is now presented in Fig 3b (previous Fig 4b)).

      (ii) The authors use an experimental setup in which the cells 'see' a homogenous chemokine concentration around them. Further, they discuss different models in the introduction of how the local cellular polarisation in such a uniform chemokine sounding is defined, including a model of polarised localisation of chemokine receptors on the plasma membrane. However, in a tissue, chemokines are typically not homogeneously distributed but are present in the form of a gradient, e.g. due to local chemokine sources or the self-generation of chemotactic gradients by neighbouring migrating cells. Therefore, it would be interesting to know whether the described repositioning of the centrosome and the changes in the actin pool are also important if cells are in a chemokine gradient. Experimentally, this could be addressed by providing a local chemokine source (e.g. from a micropipette). If this goes beyond the scope of the manuscript, then at least this aspect of chemokine gradients should be clearly mentioned and discussed in the introduction and the discussion sections.

      We thank the reviewer for this remark. We had not actually addressed this point.

      • We have tried to create chemokine gradients. But, we have never been able to observe all cells polarizing in the same direction (along this gradient). This negative result might however be due to our experimental setup so that this result is not mentioned in the manuscript. However, to our knowledge, no real chemotaxis has been described in T lymphocytes.

      • We have performed some Transwell assays that mimic trans-endothelial migration and have shown the involvement of PKA (Figure Supp 3b, lines 165-169). But the involvement of centrosomal actin could not be investigated in this experiment.

      • This question is now addressed in introduction (lines 44-47) and in discussion (lines 400-405).

      (iii) Given that the centrosome acts as a microtubule-organising center (MTOC), it would be interesting to see the microtubules during polarisation. Did the author try the visualisation of microtubules in live or by immunofluorescence stainings? Would it be a plausible model that reduced actin polarisation allows microtubule polarisation towards the cell periphery and thereby induces a protrusion by delivering signalling and cytoskeleton components towards the newly forming protrusion? May this be only targeted towards one side of the centrosome, as the nucleus may sterically hinder the efficient growth of microtubules to the other cellular side? What would happen in cells without a nucleus? And what would happen in cells without a centrosome (e.g., by PLK4 inhibition via centrinone) - are cells still able to form protrusions efficiently? These experimental suggestion are optional but could significantly improve the study.

      • As suggested by the reviewer, we performed new experiments to quantify microtubules together with actin in the centrosomal area. As previously mentioned in discussion, we were expecting that microtubule evolution mirrors that of actin. This is indeed the case after chemokine stimulation, where the quantity of microtubules present in the centrosomal area increases as actin decreases. However, after H89 treatment, an enrichment of both cytoskeleton networks is observed. It suggests that PKA could affect directly microtubule polymerization/depolymerization equilibrium independently of actin level possibly through Microtubules Associated proteins phosphorylation. Nevertheless, the effect of centrosomal actin level on cell polarization we emphasize, might partly be due to its consequence on microtubule growth. These results are now presented in Figure 4c and representative images shown in Figure Supp 9. Furthermore, this observation is mentioned in the results part (line 256-263) and in discussion (line 428-442).

      • The sterical role of the nucleus on the polarization is an interesting hypothesis that we have been however unable to test it. T lymphocytes are small cells (around 15µm diameter for CEM cell line) that seems to be difficult to enucleate.

      • We have tried to obtain cells without centrosomes in order to test their ability to polarize. To this purpose, we have treated cells with the PLK4 inhibitor, centrinone (500nM) for 24 to 48h hours. Although we could observe after 33 hours, that the large majority of cells present only one centriole, we never got cells without centrioles. After this one-centriole stage, the cells started dying.

        (iv) Bringing actin artificially to the centrosome via the centrin-VCA construct is a very nice approach. However, the dataset would strongly benefit from samples, in which the chemokine CXCL12 is included.

      The effect of chemokine on centrin-VCA expressing cells has been investigated. This result is displayed in Fig 4e. In cells expressing the centrin-VCA construct, the level of actin at the centrosome is higher than in control cells. However, upon chemokine stimulation, the signaling pathways leading to actin reduction are still active so that the level of centrosomal actin decreases (insignificantly different to the control) and the cells do not deform (insignificantly different to the control). These results are now discussed in the manuscript (lines 283-287).

      Minor points:

      (i) The study is based on a lymphoblastic cell line called CEM T cells. This should be clearly stated at the beginning of the results section and in all figure legends, as it remains unknown whether primary T lymphocytes would show the same behavior. Additionally, the methods section should contain more details about this cell line, e.g. whether it is from mouse or human origin.

      The cells used for the experiments are now clearly indicated in the figure legends and specified in the manuscript (results and methods).

      Furthermore, as mentioned in the response to reviewer #1, new experiments have been performed with primary human blood T cells. Similar effect of PKA on cell deformation and centrosomal actin regulation have been observed. These new experiments are presented in Fig Supp 4 and described in the manuscript (lines 158-164 and 199-202).

      (ii) The authors mention 'suboptimal' conditions of stimulation. However, it remains unclear in the results sections what this means. Some of the experimental modulations (e.g. the cAMP analog Rp-8-CT-cAMPS) seem to only show an effect in these suboptimal conditions but not in the optimal conditions. This should be clearly stated and discussed.

      In resting cells, Rp-8-CT-cAMPS has a similar effect as H89: it induces an increase in cell roundness as well as in centrosomal actin. However, after chemokine simulation, the inhibition of cell deformation and of centrosomal actin reduction is only observed with low intensity stimulation (Figures 2g & 3d vs Supp 5a). Our interpretation is that this chemical is not potent enough to counteract strong activation of PKA. Indeed, in resting conditions or after mild PKA activation, it blocks the effect of chemokine. This might be due to the fact that the inhibitor concentration reached within the cells is not enough. The text concerning this part has been modified for more clarity (lines 171-178 and 203-206) and the figure legends mention explicitly the chemokine concentrations used for stimulation.

      (iii) 23 out of the 38 references are older than 5 years, and most of them are older than 10 years. While it is surely very important to refer to these older findings, the authors may include more knowledge from recent years. This may include references about centrosome positioning in immune cells and motile cells (e.g., PMID32379884, PMID29934494, PMID30944468, PMID37987147, PMID36398880, PMID38627564, PMID33634136) and the actin cytoskeleton at the centrosome (PMID33609453), PMID33184056, PMID36111670.

      The references have been updated and more recent publications added.

      (iv) The first paragraph of the discussion (lines 253 - 262) needs references.

      Some references have been added to this paragraph.

      (v) Some Figures maybe combined as the findings are closely related (e.g., Figures 2 and 3; and Figures 5 and 6).

      The figures have been modified according to this suggestion.

      (vi) Line 94, Supply. Fig. 1: the authors that the chemokine receptor CXCR4 has a uniform distribution in non-stimulated cells. This is not directly evident in the images as there are areas of more and less signal. It would be important to clearly describe this in the text. Further, the labelling of the figure would benefit from labelings such as 'cell 1', 'cell 2', etc to directly make clear that these are images from 3 representative cells.

      We thank the reviewer for this remark. The CXCR4 distribution is indeed not strictly uniform. We now use the fire-colour coding which makes this point more obvious in images (Fig Supp 1).

      However, although some high spots of CXCR4 accumulation can be observed, they are not associated to the location of centrosome and, can thus not explain the preferential position of the polarization axis we observe. This point is discussed in the new version of the manuscript (lines 113-120).

      Furthermore, in the new figure concerning CXCR4 distribution (Fig Supp 1), we labelled each image with " cell x" in order to explicit that this figure displays different representative cells.

      (vii) Different centrin isoforms exist (centrin 1, 2, 3). It should be mentioned in the results and methods section, which isoform was used for their genetic constructs (e.g., centrin-GFP, centrin-VCA).

      We have corrected this omission. The fact that centrin1 isoform was used is now mentioned in the text, the legends and in the methods part.

      Significance

      This manuscript employs a lymphoblastic cell line called CEM T cells as a model for T lymphocytes. Using imaging of these cells on 2D substrates with and without chemokine, the authors identify a PKA-controlled actin pool at the centrosome that appears to regulate the local site of protrusion formation during cell polarisation. This is an interesting finding that adds to the knowledge of (i) the functions of centrosome positioning and (ii) the functions of the actin cytoskeleton at the centrosome. Thus, the study will be interesting to readers in the centrosome and migration fields. To broaden the scope of the manuscript, the findings could be tested in primary T lymphocytes and mechanistically address the role of microtubules within the described process.

      Reviewer #3

      __SUMMARY __Using a variety of live- and fixed-cell imaging techniques, the authors make correlative and causative connections between chemokine-stimulated increases in cAMP and localized PKA activity, positioning and F-actin content of the centrosome, and cell polarity in T-cells.

      MAJOR COMMENTS

      1. The authors state that "uniform CXCR4 labelling is observed in unstimulated cells" (ln94-95). While the panels in Supp Fig1a show a pattern in unstimulated cells that is obviously less dramatically asymmetrical than seen for stimulated (and, importantly, already polarized) cells in Supp Fig1b, the labelling in unstimulated cells is still far from uniform, as there is considerable heterogeneity of signal intensity along the perimeter. This is important, given that they are looking at a membrane receptor, even small fluctuations in which may be greatly amplified and thus have considerable effects on symmetry downstream. The authors should either quantify the intensity (e.g. signal as a function of polar coordinate value) or soften their language to more accurately reflect the data.

      We thank the reviewer for this remark. The distribution of CXCR4 receptors is indeed not strictly uniform even in unstimulated cells. In order to make this point more obvious, we have used the fire-colour coding for CXCR4 distribution in Fig Supp1. As mentioned in the response to the reviewer #2, high spots of CXCR4 accumulation exist but they are not associated to the location of centrosome and thus, cannot explain the preferential position of the polarization axis we observe. This point is discussed in the new version of the manuscript (lines 113-120).

      Regarding the analysis of polarization events in Fig. 1c and 1d, it is not clear how, exactly, the time point for the cortex opening is determined. For example, in the sample images in 1c, would the +110s or the +340s time point be used? The reason this is important is that the angle seems to change with time (at least in the example given) and there are also heterogeneities (specifically, decreases) in SiR-actin intensity along the cortex that precede cortex opening. Thus, it is not clear whether the cortex begins to open in closer proximity to the centrosome or whether the centrosome is further aligned after the cortex opens.

      First of all, we would like to apologize that there is an error in the time labeling in Fig 1c. The third image corresponds to + 210s and not +110s. This has been corrected in the new Fig 1c. In this example, +210 s and not +340 s has been considered as the opening of the actin cortex.

      More generally, the time for angle determination was performed by watching movies. Images were analyzed only relatively to previous and the next ones. Indeed, we first determined the period when 1/ SiRActin labeling stably decreases at one pole of the cell and 2/ the cell simultaneously deforms (transmitted light pictures). Playing the sequence backward, allowed us to determine the beginning of cortex opening. This time was then the reference for measuring the polarization angles. Thus, transient SiRActin heterogeneities we could indeed observe sometimes, were not considered. These precisions have been added to the Methods section (lines 559-564)

      Also regarding Figure 1d, it is not clear how many cells and experimental replicates are represented in the data - the Results text reports 60 cells from 11 experiments (ln106) but the legend reports 58 cells (ln564) without mention of experimental replicate number.

      We thank the reviewer for pointing out this error which we have corrected. The correct number of cells is 60. These cells are from 11 different experiments. We pooled all individual values of the 60 cells to establish angle distribution.

      Also, while the rose plot is useful, it is important to have statistical analysis on the skewness of the response and/or to report something other than the average angle - for example, the percentage of cells with a cortex opening in the same 90-degree quadrant as the centrosome.

      For more clarity, the position of the median has been added to the rose plot. Furthermore, a pie plot reports now the distribution of the angles (Fig 1d).

      Finally, it might be clearer to the reader to have the rose plot and the model cell oriented in the same direction.

      We agree to this suggestion and the cell (Fig 1c), the schematic drawing and the rose plot (Fig 1d) are all three oriented in the same direction.

      For their PKA inhibition experiments, the authors introduce H89 as "a competitive inhibitor of ATP on the PKA catalytic subunit" (ln138-139). H89 is a very non-specific inhibitor, as demonstrated by Davies et al (PMID 10998351) and reviewed by Lochner & Moolman (PMID 17214602) and should be introduced more accurately.

      H89, as a competitive inhibitor of ATP, is indeed not specific to PKA. At the low concentration we used, few other kinases can be inhibited. We now introduce more precisely the inhibitor and add references (lines 152-155 and 172-173).

      To their credit, the authors use an orthogonal approach of PKA inhibition with a cAMP analog and see comparable effects. Those data, currently in Supp Fig. 3, should be included as primary data, given that the H89 data can only be correctly interpreted in the context of the Rp-cAMPS data (this applies to both Fig3 and Fig4).

      As suggested, the data concerning Rp-8CPT-cAMPS are now included in the main figures (Fig 2g & Fig 3d) and the text has also been modified (lines 172-178 and 203-206).

      As part of Fig.5, the authors state "AKAP450 is a type II AKAP i.e. it is able to bind RII subunits of PKA. In order to determine whether this AKAP allows a [sic] compartmentalization of the PKA activity responsible for centrosomal F-actin regulation, we used the specific peptide (Ht31)". Ht31 broadly inhibits PKA anchoring; its effect is not specific for any individual AKAP, including AKAP9/AKAP450.

      We completely agree with this point and did not want to mean that Ht31 was specific to AKAP450. Therefore, the sentence has been modified to be more explicit (lines 234-236).

      Moreover, the authors neither show/confirm PKA localization to the centrosome nor its displacement with the indicated concentration of Ht31, and they do not include data that PKA is displaced from the centrosome with any greater specificity or sensitivity than its displacement from any other subcellular location. Therefore, this statement (as well as the claim in the Abstract that "a specific pool of protein kinase A) (ln15) by the authors is not accurate. The authors should, at the very least, re-word the statement and, for the sake of rigor and support of their hypotheses, confirm that PKA (subunits and/or activity) is displaced from the centrosome.

      We thank the reviewer for raising this fair point. We have performed experiments to determine the distribution of PKA (immunofluorescence, using an antibody against PKA Ca). Although the labeling is not very good, we can evidence a slight accumulation of the protein around the centrosome. This enrichment is statistically reduced in the presence of the inhibitory peptide Ht31. This suggest that 1) a pool of PKA accumulates around the centrosome and 2) it is displaced by Ht31.

      These results as well as the corresponding images are presented in Figure Supp 7 and described in the new version of the manuscript (lines 236-245).

      The experiments & results using VCA-centrin-GFP are very intriguing. However, it is crucial that primary data (i.e. photomicrographs/panels of fluorescent images of centrin/VCA-centrin localization, centrosomal F-actin, and roundness) be included for the readers' inspection. Also, it is not clear whether the graphically summarized data on centrosomal F-actin and roundness (Fig. 6b) represent analysis of cells before and after CXCL12 stimulation, or only before or only after. If either of the latter, analysis of these parameters both before and after stimulation should be included.

      Representative images of cells expressing centrin/centrin-VCA are now provided and shown in Fig Supp 8. They show that centrin-VCA expressing cells are less deformed (a, b) but also display a higher quantity of F-actin around the centrosome (a).

      The effect of stimulation in centrin-VCA expressing cells is now shown in Figure 4e. As mentioned in response to the reviewer #2 (iv), in cells expressing the centrin-VCA construct, the level of actin at the centrosome is higher than in control cells. However, upon chemokine stimulation, the signaling pathways leading to actin reduction are still active so that the level of centrosomal actin decreases (insignificantly different to the control) and the cells do not deform (insignificantly different to the control). These results are now discussed in the manuscript (lines 283-287).

      MINOR COMMENTS

      1. The writing is generally clear and accurate, but often somewhat 'choppy'. As one of many examples: "As depicted in Figure 1b, in this configuration, we observed that cell deformation starts rapidly after stimulation. The mean delay between cell stimulation and the time when cells start to deform is 112 {plus minus} 10 s (n=48 cells)" could be re-written as "As depicted in Figure 1b, in this configuration, we observed that cell deformation starts rapidly after stimulation, with a mean delay between cell stimulation and initiation of cell deformation of 112 {plus minus} 10 s (n=48 cells)." This is completely stylistic, of course, and would simply (albeit slightly) improve the readability of the work.

      We have tried to improve the writing.

      The authors comment that the contribution of calcium, PI3K, and cAMP signaling "in the early processes allowing the establishment of the asymmetric distribution of cellular components and of the polarity regulators is still elusive" (ln33-35) seems a bit overstated, as there have been numerous, impactful contributions investigating each of those pathways.

      We agree that these actors have been already clearly shown to be involved in polarization and/or migration as reported in the review by V. Niggli. However, the precise role they play in the initiation of T cell polarization is not clear. The sentence concerning this point has been modified in the introduction (lines 36-40).

      The work seems to starts off as being focused on symmetry breaking rather than polarization, but this can be mitigated through rewriting the Introduction.

      Symmetry breaking is for us the initial step (prerequisite) for cell polarization. Two sentences have been modified to clarify this point (lines 46-47 and 74-75).

      The phrase "the major one" (ln47), presumably referring to one of "several local signaling poles" (earlier in ln47) is ambiguous and should be reworded (e.g. "the pole with the highest density of receptors").

      The sentence has been modified (lines 53-54).

      The phrase "variations of cAMP after CXCL12 addition upon dynamic cell imaging" (ln112) is not clear.

      The sentence has been modified (lines 124-125).

      The authors may want to reconsider the use of an ellipsis (ln25), which stands out as somewhat informal for a scientific manuscript.

      The sentence has been reworded (lines 27-29).

      There are several typographical errors throughout that should be addressed (e.g. "AMPc" rather than "cAMP" in the header of Fig7b.; "we were able establish" (ln 130); "while PKA are rapidly activated" (ln133)).

      We have corrected typographical errors.

      The figure legends most often read more like miniature, repeated results sections than detailed descriptions of experimental details and data processing, analysis and depiction.

      Figure legends have been rewritten.

      __SIGNIFICANCE __Directional cell migration is a fundamentally important aspect of cell biology. Understanding the molecular mechanisms that govern cellular symmetry breaking, polarization, and migration are - in turn - important for a fuller understanding of how cells efficiently move from location to location. T cells, which are highly dependent on efficient and dynamically, cytokine-directed migration for their physiologic function, are an excellent model system in which to unravel such molecular mechanisms. The authors efforts to connect localized cytokine-initiated signaling events with changes in centrosomal actin decoration and thence into cell polarity are, therefore, of considerable potential significance.

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

      Learn more at Review Commons


      Referee #3

      Evidence, reproducibility and clarity

      Summary

      Using a variety of live- and fixed-cell imaging techniques, the authors make correlative and causative connections between chemokine-stimulated increases in cAMP and localized PKA activity, positioning and F-actin content of the centrosome, and cell polarity in T-cells.

      Major Comments

      1. The authors state that "uniform CXCR4 labelling is observed in unstimulated cells" (ln94-95). While the panels in Supp Fig1a show a pattern in unstimulated cells that is obviously less dramatically asymmetrical than seen for stimulated (and, importantly, already polarized) cells in Supp Fig1b, the labelling in unstimulated cells is still far from uniform, as there is considerable heterogeneity of signal intensity along the perimeter. This is important, given that they are looking at a membrane receptor, even small fluctuations in which may be greatly amplified and thus have considerable effects on symmetry downstream. The authors should either quantify the intensity (e.g. signal as a function of polar coordinate value) or soften their language to more accurately reflect the data.
      2. Regarding the analysis of polarization events in Fig. 1c and 1d, it is not clear how, exactly, the time point for the cortex opening is determined. For example, in the sample images in 1c, would the +110s or the +340s time point be used? The reason this is important is that the angle seems to change with time (at least in the example given) and there are also heterogeneities (specifically, decreases) in SiR-actin intensity along the cortex that precede cortex opening. Thus, it is not clear whether the cortex begins to open in closer proximity to the centrosome or whether the centrosome is further aligned after the cortex opens.
      3. Also regarding Figure 1d, it is not clear how many cells and experimental replicates are represented in the data - the Results text reports 60 cells from 11 experiments (ln106) but the legend reports 58 cells (ln564) without mention of experimental replicate number. Also, while the rose plot is useful, it is important to have statistical analysis on the skewness of the response and/or to report something other than the average angle - for example, the percentage of cells with a cortex opening in the same 90-degree quadrant as the centrosome. Finally, it might be clearer to the reader to have the rose plot and the model cell oriented in the same direction.
      4. For their PKA inhibition experiments, the authors introduce H89 as "a competitive inhibitor of ATP on the PKA catalytic subunit" (ln138-139). H89 is a very non-specific inhibitor, as demonstrated by Davies et al (PMID 10998351) and reviewed by Lochner & Moolman (PMID 17214602) and should be introduced more accurately. To their credit, the authors use an orthogonal approach of PKA inhibition with a cAMP analog and see comparable effects. Those data, currently in Supp Fig. 3, should be included as primary data, given that the H89 data can only be correctly interpreted in the context of the Rp-cAMPS data (this applies to both Fig3 and Fig4).
      5. As part of Fig.5, the authors state "AKAP450 is a type II AKAP i.e. it is able to bind RII subunits of PKA. In order to determine whether this AKAP allows a [sic] compartmentalization of the PKA activity responsible for centrosomal F-actin regulation, we used the specific peptide (Ht31)". Ht31 broadly inhibits PKA anchoring; its effect is not specific for any individual AKAP, including AKAP9/AKAP450. Moreover, the authors neither show/confirm PKA localization to the centrosome nor its displacement with the indicated concentration of Ht31, and they do not include data that PKA is displaced from the centrosome with any greater specificity or sensitivity than its displacement from any other subcellular location. Therefore, this statement (as well as the claim in the Abstract that "a specific pool of protein kinase A) (ln15) by the authors is not accurate. The authors should, at the very least, re-word the statement and, for the sake of rigor and support of their hypotheses, confirm that PKA (subunits and/or activity) is displaced from the centrosome.
      6. The experiments & results using VCA-centrin-GFP are very intriguing. However, it is crucial that primary data (i.e. photomicrographs/panels of fluorescent images of centrin/VCA-centrin localization, centrosomal F-actin, and roundness) be included for the readers' inspection. Also, it is not clear whether the graphically summarized data on centrosomal F-actin and roundness (Fig. 6b) represent analysis of cells before and after CXCL12 stimulation, or only before or only after. If either of the latter, analysis of these parameters both before and after stimulation should be included.

      Minor Comments

      1. The writing is generally clear and accurate, but often somewhat 'choppy'. As one of many examples: "As depicted in Figure 1b, in this configuration, we observed that cell deformation starts rapidly after stimulation. The mean delay between cell stimulation and the time when cells start to deform is 112 {plus minus} 10 s (n=48 cells)" could be re-written as "As depicted in Figure 1b, in this configuration, we observed that cell deformation starts rapidly after stimulation, with a mean delay between cell stimulation and initiation of cell deformation of 112 {plus minus} 10 s (n=48 cells)." This is completely stylistic, of course, and would simply (albeit slightly) improve the readability of the work.
      2. The authors comment that the contribution of calcium, PI3K, and cAMP signaling "in the early processes allowing the establishment of the asymmetric distribution of cellular components and of the polarity regulators is still elusive" (ln33-35) seems a bit overstated, as there have been numerous, impactful contributions investigating each of those pathways.
      3. The work seems to starts off as being focused on symmetry breaking rather than polarization, but this can be mitigated through rewriting the Introduction.
      4. The phrase "the major one" (ln47), presumably referring to one of "several local signaling poles" (earlier in ln47) is ambiguous and should be reworded (e.g. "the pole with the highest density of receptors").
      5. The phrase "variations of cAMP after CXCL12 addition upon dynamic cell imaging" (ln112) is not clear.
      6. The authors may want to reconsider the use of an ellipsis (ln25), which stands out as somewhat informal for a scientific manuscript.
      7. There are several typographical errors throughout that should be addressed (e.g. "AMPc" rather than "cAMP" in the header of Fig7b.; "we were able establish" (ln 130); "while PKA are rapidly activated" (ln133)).
      8. The figure legends most often read more like miniature, repeated results sections than detailed descriptions of experimental details and data processing, analysis and depiction.

      Significance

      Directional cell migration is a fundamentally important aspect of cell biology. Understanding the molecular mechanisms that govern cellular symmetry breaking, polarization, and migration are - in turn - important for a fuller understanding of how cells efficiently move from location to location. T cells, which are highly dependent on efficient and dynamically, cytokine-directed migration for their physiologic function, are an excellent model system in which to unravel such molecular mechanisms. The authors efforts to connect localized cytokine-initiated signaling events with changes in centrosomal actin decoration and thence into cell polarity are, therefore, of considerable potential significance.

    1. 安茹帝国的建立和衰落直接导致了百年战争(1337–1453),这是英法之间持续对抗的标志。

      你提出的观点非常重要,安茹帝国的建立和衰落确实是百年战争(1337–1453)的重要背景因素。它们之间的关系是复杂的,我将详细解释如下:

      1. 安茹帝国的建立(12世纪):

      • 联姻与继承: 安茹帝国并非一个正式的“帝国”,而是通过一系列的联姻和继承,由安茹伯爵(后来也成为英格兰国王)统治的一系列领土的集合。这些领土包括安茹、诺曼底、阿基坦和英格兰等。
      • 亨利二世: 安茹帝国的鼎盛时期是在亨利二世(1133-1189)统治时期。他通过继承、婚姻和军事征服,控制了从苏格兰边境到比利牛斯山脉的广袤领土,横跨英吉利海峡两岸。
      • 法兰西王国的制约: 虽然亨利二世控制了法国西部的大片领土,但他仍然是法兰西国王的封臣。这种复杂的封建关系为日后的冲突埋下了伏笔。

      2. 安茹帝国的衰落(13世纪初):

      • 约翰失地: 在约翰王(1166-1216)统治时期,由于他与法兰西国王腓力二世的战争失利,以及他与教皇和英格兰贵族的冲突,安茹帝国在法国的大部分领土(包括诺曼底、安茹、曼恩和图赖讷)被法兰西王国吞并。这一事件发生在1202年至1214年之间,以1214年的布汶战役为重要转折点。
      • 阿基坦的残余: 虽然失去了大部分领土,但英格兰国王仍然控制着阿基坦(主要位于法国西南部)的部分地区。这块领地成为日后英法冲突的重要导火索。

      3. 百年战争的爆发(1337-1453):

      • 王位继承权之争: 百年战争的直接原因是法兰西卡佩王朝的绝嗣。1328年,法兰西国王查理四世去世,没有男性后裔继承王位。英格兰国王爱德华三世是查理四世的外甥,他根据母系血统主张自己有权继承法兰西王位。然而,法兰西贵族选择了腓力六世作为新国王,开启了瓦卢瓦王朝。
      • 阿基坦的地位: 除了王位继承权之争,阿基坦的地位也是战争的重要原因。英格兰国王仍然控制着阿基坦的部分地区,法兰西国王一直希望将其收回。这使得阿基坦成为两国冲突的前线。
      • 安茹帝国的遗产: 安茹帝国的存在及其衰落,为百年战争埋下了深远的种子:
        • 领土纠纷: 曾经庞大的安茹帝国在法国的领土,成为英法两国长期争夺的目标。
        • 封建关系: 英格兰国王作为曾经的安茹伯爵,在法兰西的领地上拥有封地,这种复杂的封建关系导致了双方的权力冲突。
        • 历史记忆: 安茹帝国曾经的辉煌和后来的丧失,都加剧了英法两国之间的敌对情绪。

      4. 百年战争的影响:

      • 民族认同的形成: 百年战争促进了英法两国民族认同的形成。战争期间,双方都逐渐形成了强烈的民族意识。
      • 政治格局的改变: 战争结束后,英格兰失去了在法国的所有领地(除了加莱短暂的时期),彻底退出了欧洲大陆的争霸。法兰西则巩固了其在西欧的霸主地位。

      总结:

      安茹帝国的建立和衰落,为百年战争的爆发创造了重要的背景条件。领土纠纷、封建关系和历史记忆,都加剧了英法两国之间的矛盾,最终导致了这场旷日持久的战争。百年战争不仅是英法两国历史上重要的分水岭,也对欧洲历史产生了深远的影响。

      因此,你提出的“安茹帝国的建立和衰落直接导致了百年战争”的说法是基本正确的,虽然“直接导致”可能稍显绝对,但它们之间的因果关系和相互影响是毋庸置疑的。安茹帝国的存在和衰落,为百年战争的爆发提供了重要的历史背景和深层原因。

    1. For a few crumbs off their table, that they ploughed into the Trump campaign, the Big Tech brotherhood are in the process of receiving three amazing gifts

      for - Trumps three gifts to lobbyists - article - Le Monde - Musk, Trump and the Broligarch's novel hyper-weapon - Yanis Varoufakis - 2025, Jan 4 - 1. Huge government contracts - 2. Deregulation will enable a free-for-all - 3. State-sanctioned power over labor

    1. Author response:

      We thank the reviewers for the constructive suggestions made in the Public Reviews and the Recommendations to Authors. We intend to address these comments in a revised manuscript as follows:

      (1) We will revise the text according to the reviewer suggestions with regards to specific RBM20-dependent mRNAs and providing more detailed explanations in results and discussion.

      (2) We will upload higher resolution images of several figures (resolution had been reduced to achieve lower file sizes) to address the comment regarding “data quality”.

      (3) We will include data on eCLIP control experiments.

      (4) We will add information on replication and new data for the western blot analysis.

    1. Reviewer #1 (Public review):

      This work regards the role of Aurora Kinase A (AurA) in trained immunity. The authors claim that AurA is essential to the induction of trained immunity. The paper starts with a series of experiments showing the effects of suppressing AurA on beta-glucan-trained immunity. This is followed by an account of how AurA inhibition changes the epigenetic and metabolic reprogramming that are characteristic of trained immunity. The authors then zoom in on specific metabolic and epigenetic processes (regulation of S-adenocylmethionine metabolism & histone methylation). Finally, an inhibitor of AurA is used to reduce beta-glucan's anti-tumour effects in a subcutaneous MC-38 model.

      Strengths:

      With the exception of my confusion around the methods used for relative gene expression measurements, the experimental methods are generally well-described. I appreciate the authors' broad approach to studying different key aspects of trained immunity (from comprehensive transcriptome/chromatin accessibility measurements to detailed mechanistic experiments). Approaching the hypothesis from many different angles inspires confidence in the results (although not completely - see weaknesses section). Furthermore, the large drug-screening panel is a valuable tool as these drugs are readily available for translational drug-repurposing research.

      Weaknesses

      (1) The manuscript contains factual inaccuracies such as:<br /> (a) Intro: the claim that trained cells display a shift from OXPHOS to glycolysis based on the paper by Cheng et al. in 2014; this was later shown to be dependent on the dose of stimulation and actually both glycolysis and OXPHOS are generally upregulated in trained cells (pmid 32320649)<br /> (b) Discussion: Trained immunity was first described as such in 2011, not decades ago.

      (2) The authors approach their hypothesis from different angles, which inspires a degree of confidence in the results. However, the statistical methods and reporting are underwhelming.<br /> (a) Graphs depict mean +/- SEM, whereas mean +/- SD is almost always more informative.<br /> (b) The use of 1-tailed tests is dubious in this scenario. Furthermore, in many experiments/figures the case could be made that the comparisons should be considered paired (the responses of cells from the same animal are inherently not independent due to their shared genetic background and, up until cell isolation, the same host factors like serum composition/microbiome/systemic inflammation etc).<br /> (c) It could be explained a little more clearly how multiple testing correction was done and why specific tests were chosen in each instance.<br /> (d) Most experiments are done with n = 3, some experiments are done with n = 5. This is not a lot. While I don't think power analyses should be required for simple in vitro experiments, I would be wary of drawing conclusions based on n = 3. It is also not indicated if the data points were acquired in independent experiments. ATAC-seq/RNA-seq was, judging by the figures, done on only 2 mice per group. No power calculations were done for the in vivo tumor model.<br /> (e) Furthermore, the data spread in many experiments (particularly BMDM experiments) is extremely small. I wonder if these are true biological replicates, meaning each point represents BMDMs from a different animal? (disclaimer: I work with human materials where the spread is of course always much larger than in animal experiments, so I might be misjudging this.).

      (3) Maybe the authors are reserving this for a separate paper, but it would be fantastic if the authors would report the outcomes of the entire drug screening instead of only a selected few. The field would benefit from this as it would save needless repeat experiments. The list of drugs contains several known inhibitors of training (e.g. mTOR inhibitors) so there must have been more 'hits' than the reported 8 Aurora inhibitors.

      (4) Relating to the drug screen and subsequent experiments: it is unclear to me in supplementary figure 1B which concentrations belong to secondary screens #1/#2 - the methods mention 5 µM for the primary screen and "0.2 and 1 µM" for secondary screens, is it in this order or in order of descending concentration?<br /> (a) It is unclear if the drug screen was performed with technical replicates or not - the supplementary figure 1B suggests no replicates and quite a large spread (in some cases lower concentration works better?)

      (5) The methods for (presumably) qPCR for measuring gene expression in Figure 1C are missing. Which reference gene was used and is this a suitably stable gene?

      (6) From the complete unedited blot image of Figure 1D it appears that the p-Aurora and total Aurora are not from the same gel (discordant number of lanes and positioning). This could be alright if there are no/only slight technical errors, but I find it misleading as it is presented as if the actin (loading control to account for aforementioned technical errors!) counts for the entire figure.

      (7) Figure 2: This figure highlights results that are by far not the strongest ones - I think the 'top hits' deserve some more glory. A small explanation on why the highlighted results were selected would have been fitting.

      (8) Figure 3 incl supplement: the carbon tracing experiments show more glucose-carbon going into TCA cycle (suggesting upregulated oxidative metabolism), but no mito stress test was performed on the seahorse.

      (9) Inconsistent use of an 'alisertib-alone' control in addition to 'medium', 'b-glucan', 'b-glucan + alisertib'. This control would be of great added value in many cases, in my opinion.

      (10) Figure 4A: looking at the unedited blot images, the blot for H3K36me3 appears in its original orientation, whereas other images appear horizontally mirrored. Please note, I don't think there is any malicious intent but this is quite sloppy and the authors should explain why/how this happened (are they different gels and the loading sequence was reversed?)

      (11) For many figures, for example prominently figure 5, the text describes 'beta-glucan training' whereas the figures actually depict acute stimulation with beta-glucan. While this is partially a semantic issue (technically, the stimulation is 'the training-phase' of the experiment), this could confuse the reader.

      (12) Figure 6: Cytokines, especially IL-6 and IL-1β, can be excreted by tumour cells and have pro-tumoral functions. This is not likely in the context of the other results in this case, but since there is flow cytometry data from the tumour material it would have been nice to see also intracellular cytokine staining to pinpoint the source of these cytokines.

    1. 详细说明

      这幅地图展示了公元714年查理·马特(Charles Martel)掌权时的法兰克王国(Francia)疆域及其各主要区域。法兰克王国是中世纪初期西欧最重要的政权之一,其疆域在查理·马特时期为后来的加洛林王朝(Charlemagne的帝国)奠定了基础。

      以下是对地图的详细解释:


      1. 法兰克王国的主要区域划分

      在查理·马特执政时期,法兰克王国并不是一个完全统一的国家,而是由多个公国和地区组成,各区域具有相对的自治权。这些区域包括:

      (1) Neustria(纽斯特里亚)

      • 位置: 位于法兰克王国的西部。
      • 特点:
      • 纽斯特里亚是法兰克王国西部的主要地区之一,通常被认为是后来的西法兰克王国(即今天的法国)的前身。
      • 与奥斯特拉西亚经常存在竞争关系。

      (2) Austrasia(奥斯特拉西亚)

      • 位置: 位于王国的东部。
      • 特点:
      • 奥斯特拉西亚是法兰克王国东部的重要区域,是查理·马特家族(加洛林王朝)的权力核心。
      • 包括今日法国的东北部、比利时、卢森堡及德国的部分地区。

      (3) Burgundy(勃艮第)

      • 位置: 位于王国的中部和东南部。
      • 特点:
      • 勃艮第是一个历史悠久的区域,具有相对的独立性。
      • 后来成为法国王国和神圣罗马帝国的重要组成部分。

      (4) Duchy of Aquitaine(阿基坦公国)

      • 位置: 位于法兰克王国的西南部。
      • 特点:
      • 阿基坦公国在714年时是一个半独立的区域,其统治者拥有很大的自主权。

      (5) Provence(普罗旺斯)

      • 位置: 位于法兰克王国的东南角,接近地中海。
      • 特点:
      • 普罗旺斯地处地中海沿岸,是一个重要的贸易和文化区域。

      (6) Duchy of Gascony(加斯科涅公国)

      • 位置: 位于王国的南部。
      • 特点:
      • 与阿基坦相邻,也是一个具有一定独立性的地区。

      2. 周边的邻国与势力

      法兰克王国在714年面临着来自多个方向的威胁:

      (1) 萨克森人(Saxons)

      • 位置: 位于法兰克王国的东北部。
      • 威胁:
      • 萨克森人是日耳曼部落之一,与法兰克人长期交战。

      (2) 阿勒曼尼人(Alamanni)

      • 位置: 位于奥斯特拉西亚的东南部。
      • 威胁:
      • 阿勒曼尼人是另一个日耳曼部落,与法兰克王国的边境接壤。

      (3) 倭马亚王朝(Umayyad Caliphate)

      • 位置: 法兰克王国的南部。
      • 威胁:
      • 这一时期,倭马亚王朝控制了伊比利亚半岛,并试图向北扩张,最终在732年的普瓦捷战役(Battle of Tours)中被查理·马特击败。

      (4) 布列塔尼人(Bretons)

      • 位置: 法兰克王国西北部。
      • 特点:
      • 布列塔尼地区保持了相对的独立性,法兰克王国对其影响力有限。

      3. 查理·马特(Charles Martel)的崛起

      • 查理·马特在714年接替父亲丕平二世成为法兰克王国的事实统治者。
      • 他以“宫相”(Mayor of the Palace)的身份掌握权力,虽然当时的国王名义上是墨洛温王朝的统治者,但实权实际上掌握在查理·马特手中。
      • 查理·马特的两大成就:
      • 内部统一: 查理成功平定了法兰克王国内部各地区(如纽斯特里亚和奥斯特拉西亚)的叛乱,进一步巩固了王权。
      • 外部防御: 他最著名的功绩是732年击败了入侵的倭马亚王朝军队,阻止了伊斯兰势力向西欧的进一步扩张。

      4. 地图中的重要地点

      (1) Tours(普瓦捷)

      • 位置: 在法兰克王国的西南部。
      • 事件:
      • 732年,查理·马特在普瓦捷战役中击败了倭马亚王朝的军队,被视为捍卫基督教欧洲的重要胜利。

      (2) Tournai(图尔奈)

      • 位置: 法兰克王国北部,靠近奥斯特拉西亚。
      • 意义:
      • 是法兰克王国早期的重要城市之一。

      5. 法兰克王国的地缘政治重要性

      • 法兰克王国位于西欧的中心,东接日耳曼部落,西接大西洋,南接地中海和伊比利亚半岛。
      • 它的地理位置使其成为欧洲的重要政治、文化和军事力量。

      总结

      这张地图展示了714年查理·马特接管法兰克王国时的政治版图。法兰克王国虽然名义上统一,但实际上由多个相对独立的地区组成。在查理·马特的领导下,法兰克王国不仅成功击退了外敌(如倭马亚王朝),还为加洛林王朝的建立和欧洲中世纪的基督教统治奠定了基础。这段时期的法兰克王国是西欧历史的重要转折点,也是现代法国、德国和其他欧洲国家的雏形。

    1. AbstractBackground Cardamine chenopodiifolia is an amphicarpic plant that develops two fruit morphs, one above and the other below ground. Above-ground fruit disperse their seeds by explosive coiling of the fruit valves, while below-ground fruit are non-explosive. Amphicarpy is a rare trait that is associated with polyploidy in C. chenopodiifolia. Studies into the development and evolution of this trait are currently limited by the absence of genomic data for C. chenopodiifolia.Results We produced a chromosome-scale assembly of the octoploid C. chenopodiifolia genome using high-fidelity long read sequencing with the Pacific Biosciences platform. We successfully assembled 32 chromosomes and two organelle genomes with a total length of 597.2 Mbp and an N50 of 18.8 kbp (estimated genome size from flow cytometry: 626 Mbp). We assessed the quality of this assembly using genome-wide chromosome conformation capture (Omni-C) and BUSCO analysis (97.1% genome completeness). Additionally, we conducted synteny analysis to infer that C. chenopodiifolia likely originated via allo-rather than auto-polyploidy and phased one of the four sub-genomes.Conclusions This study provides a draft genome assembly for C. chenopodiifolia, which is a polyploid, amphicarpic species within the Brassicaceae family. This genome offers a valuable resource to investigate the under-studied trait of amphicarpy and the origin of new traits by allopolyploidy.

      Reviewer 1. Rie Shimizu

      This manuscript deciphers the complicated genome of an octoploid species, Cardamine chenopodiifolia. They successfully assembled a chromosome-level genome with 32 chromosomes, consistent with the chromosome counting. They evaluated the quality of the genome by several methods (mapping Omni-C reads, BUSCO, variant calling etc.). All benchmarks ensured the high quality of their assembly. They even tried to phase the chromosomes into four subgenomes, and one subgenome was successfully phased thanks to its higher divergence compared to the other three sets. Despite their intensive effort, the other three subgenomes could not be phased, suggesting the relationship originated from the same or closely related species. As a whole, the manuscript is very well written and describes enough details, and the genome data looks like it is already available in a public database. They even added a description of the biological application of this assembly about the amphicarpy.

      I only found a few minor points for which I kindly suggest reconsideration/rephrasing before publication, as listed below. *As the review PDF does not contain the line numbers, I suggest the original description at the first line and then write my comments.

      –C. chenopodiifolia genome is octoploid …, suggesting that its genome is octoploid. They compare the 8C peak of C. hirsuta and 2C peak of the target, but considering the genome size variation among Cardamine species, I do not think this is an appropriate expression. The pattern may mean ‘consistent’ with the expectation from C. hirsuta peaks but does not ‘suggest’ octoploidy. -C. chenopodiifolia chromosome-level genome assembly PacBio Sequel II platform. Here and nowhere, they do not mention the mode of sequencing (only found in method and the title of a table). Maybe ‘HiFi’ could be added here to make the method clearer. -Table 2. It would make more sense to overview the genome quality if the N90 and L90 (or similar, if it is already fragmented at L90) values are added. (maybe the same for Table 1). Otherwise Nx curves would be also fine for the same purpose. -We obtained only 20800 variants,…as expected for a selfing species. It might be partially due to selfing in wild habitat, but also by selfing (5 times) in the lab. This should be mentioned here to avoid misleading. -Table 4 The unit of each item (bp, number, frequency…?) should be suggested. In addition to the points listed above, I appreciate more Information about the phased chromosomes set: Total subgenome sizes of this set and the other three sets?(1:3 or imbalanced?) It would be even better with a synteny plot in addition to the colinear plot as Fig 3C. (e.g. by GENESPACE or something similar, including phased and unphased chenopodiifolia chromosome sets and C. hirsuta)

      Reviewer 2. .Qing Liu

      This manuscript “Polyploid genome assembly of Cardamine chenopodiifolia” produced a chromosome-scale assembly of the octoploid C. chenopodiifolia genome using highfidelity long read sequencing with the Pacific Biosciences platform with two organelle genomes with a total length of 597.2 Mb and an N50 of 18.8 Mb together with BUSCO analysis (99.8% genome completeness), and phased one of the four sub-genomes. This study provides a valuable resource to investigate the understudied trait of amphicarpy and the origin of new traits by allopolyploidy. The manuscript is suitably edited and significant data for amphicarpy breeding of C. chenopodiifolia except for the below revision points. The major revision is suggested for the current version of the manuscript.

      1 Please elucidate “an N50 of 18.8 Mb”, which is Contig or Scaffold N50 length. 2 Please elucidate “originated via allo- rather than auto-polyploidy”, which is “originated via allopolyploidy rather than autopolyploidy”. 3 Please substitute the word “understudied trait” using alternative sensible word. 4 “to phase this set of chromosomes by gene tree topology analysis”, it is suggested to be “to phase this set of chromosomes by gene phylogeney analysis”. 5 In the first section of Resuts, Cardamine chenopodiifolia genome is octoploid is suggested. 6 Could Table 1 and Table2 be combined as one table to present the sequencing and assembly characterization of C. chenopodiifolia genome. 7 Could the entromere locations be predicted in Table 5, which is the 32 chromosome summary of C. chenopodiifolia genome. 8 In Table 2, assembly 32 chromosomes including two organelles, which is not close related with the C. chenopodiifolia genome, from my point of view, two organelle genome assembly do not critical section of manuscript. 9 Could all figure numbers are ordered below each group figures, for example the below figure should be numbered before the Figure 2A (according group figure presence order). I wonder it is Figure 2, authors want to elucidate the chromosome number 2n=42, while I can’t count out 42 chromosomes from present format.Could authors using alternative clear figure to show the cytological evidence of C. chenopodiifolia chromosome number. 10 In Figure 5A, it is difficult to point out the clear meaning for first-diverged chromosome from gene tree, which is a phylogenetic meaning tree or just framework, could author redraw this Figure 5A in order to reader got what you mean.

      Reviewer 3. Kang Zhang.

      The paper produced a chromosome-scale assembly of the C. chenopodiifolia genome in the Brassicaceae family, and offers a valuable resource to investigate the understudied trait of amphicarpy and the origin of new traits by allopolyploidy. I have the following comments which can be considered to improve the ms.

      Major points. 1.The introduction states that Cardamine is among the largest genera within the Brassicaceae family. The octaploid model species C. occulta and the diploid C. hirsuta have been sequenced. Therefore, I propose that a description of the evolutionary relationships among various species be included here. Additionally, the significance of the amphicarpic trait in the study of plant evolution and adaptation could be highlighted when discussing their octoploid characteristics. 2.The paper omits a detailed description of genome annotation and significant genomic features, which are essential for clearly illustrating the characteristics of the genome. To enhance this aspect, it would be beneficial to include a circular chart that displays fundamental components such as gene density, CG content, TE density, and collinearity links, among others. 3.The authors employed various techniques to differentiate the four subgenomic sets within the C. chenopodiifolia genome and ultimately managed to isolate a single sub-genomic set. The paper references the assembly of the octaploid genome of another model plant, C. occulta, within the same genus. Could it be utilized to compare with C. chenopodiifolia to achieve improvements? In addition, I suggest the authors to examine the gene density differences among these subgenomes, which could be helpful in distinguishing them. 4.Little important information were included in Table 1, 3, and Figure 4. These tables and figures should be moved to Supplementary data. 5.Evidence from Hi-C heatmap should be provided to validate the structural variations among different sets of subgenomes, such as those in Figure 3.

      Minor points. 1.Figure 5B, please change the vertical coordinate ‘# gene pairs’ to ‘Number of gene pairs’. The fonts in some figures are a little bit small. I suggest to adjust them to make it easy to read.

    1. Reviewer #1 (Public review):

      Summary:

      The manuscript discusses the role of phosphorylated ubiquitin (pUb) by PINK1 kinase in neurodegenerative diseases. It reveals that elevated levels of pUb are observed in aged human brains and those affected by Parkinson's disease (PD), as well as in Alzheimer's disease (AD), aging, and ischemic injury. The study shows that increased pUb impairs proteasomal degradation, leading to protein aggregation and neurodegeneration. The authors also demonstrate that PINK1 knockout can mitigate protein aggregation in aging and ischemic mouse brains, as well as in cells treated with a proteasome inhibitor. While this study provided some interesting data, several important points should be addressed before being further considered.

      Strengths:

      (1) Reveals a novel pathological mechanism of neurodegeneration mediated by pUb, providing a new perspective on understanding neurodegenerative diseases.<br /> (2) The study covers not only a single disease model but also various neurodegenerative diseases such as Alzheimer's disease, aging, and ischemic injury, enhancing the breadth and applicability of the research findings.

      Weaknesses:

      (1) PINK1 has been reported as a kinase capable of phosphorylating Ubiquitin, hence the expected outcome of increased p-Ub levels upon PINK1 overexpression. Figures 5E-F do not demonstrate a significant increase in Ub levels upon overexpression of PINK1 alone, whereas the evident increase in Ub expression upon overexpression of S65A is apparent. Therefore, the notion that increased Ub phosphorylation leads to protein aggregation in mouse hippocampal neurons is not yet convincingly supported.<br /> (2) The specificity of PINK1 and p-Ub antibodies requires further validation, as a series of literature indicate that the expression of the PINK1 protein is relatively low and difficult to detect under physiological conditions.<br /> (3) In Figure 6, relying solely on Western blot staining and golgi staining under high magnification is insufficient to prove the impact of PINK1 overexpression on neuronal integrity and cognitive function. The authors should supplement their findings with immunostaining results for MAP2 or NeuN to demonstrate whether neuronal cells are affected.<br /> (4) The authors should provide more detailed figure captions to facilitate the understanding of the results depicted in the figures.<br /> (5) While the study proposes that pUb promotes neurodegeneration by affecting proteasomal function, the specific molecular mechanisms and signaling pathways remain to be elucidated.

    1. 纳什的作品将浪漫主义和古典建筑风格结合,使得建筑风格中融入更多的情感元素,影响了后来的建筑设计

      这段话描述的是建筑领域中浪漫主义风格的一种表现形式,以及建筑师约翰·纳什(John Nash)在其中的贡献。要理解这段话,需要分解成几个关键点:

      1. 浪漫主义风格的总体特征: 浪漫主义是一种影响广泛的文化思潮,它在艺术、文学、音乐等领域都有体现。在建筑领域,浪漫主义是对之前盛行的理性、规范的古典主义的反叛。它强调:

        • 情感的表达: 相较于古典主义的严谨和理性,浪漫主义更注重情感的抒发,追求建筑作品能够唤起人们的感受。
        • 个性和自由: 反对刻板的规则和模仿,鼓励建筑师发挥创造力,展现独特的风格。
        • 对自然的向往: 常常从自然界中汲取灵感,例如运用曲线、不对称的构图等,营造自然、野性的氛围。
        • 对历史和传统的追溯: 特别是对中世纪的哥特式建筑等历史风格的重新审视和运用。
      2. 古典建筑风格的特征: 作为浪漫主义的反面,古典建筑风格强调:

        • 理性与秩序: 追求建筑的比例、对称和和谐,遵循严格的规则和规范。
        • 几何形式: 常用圆形、方形、三角形等几何图形进行建筑设计。
        • 庄重与肃穆: 营造一种庄严、肃穆的氛围。
      3. 纳什的贡献: 约翰·纳什是一位英国建筑师,他生活在18世纪末至19世纪初,正是浪漫主义思潮兴盛的时期。他的独特之处在于,他并没有完全抛弃古典主义,而是将其与浪漫主义相结合,创造出了一种新的建筑风格。具体来说,他可能:

        • 在古典建筑的基础上融入浪漫主义元素: 例如,在古典建筑的立面上增加一些曲线、不对称的装饰,或者运用一些象征性的符号,以表达情感。
        • 将建筑与周围的自然环境相融合: 例如,在设计园林或城市规划时,考虑到地形、植被等自然因素,使建筑与自然环境和谐统一。
        • 创造出更具戏剧性和情感冲击力的建筑空间: 例如,运用光线、色彩、空间的变化等手法,营造出不同的氛围,以唤起人们的情感共鸣。
      4. 对后世的影响: 纳什的这种融合风格为后来的建筑设计开辟了新的道路,影响了后来的建筑师们在设计中更加注重情感的表达和个性的展现。他的作品也成为了浪漫主义建筑的重要代表作。

      举例说明:

      为了更好地理解,可以举一些纳什的代表作作为例子,例如:

      • 布莱顿皇家穹顶宫(Royal Pavilion, Brighton): 这座建筑融合了印度莫卧儿王朝和中国清朝的建筑元素,展现出浓郁的异域情调,是浪漫主义风格的典型代表。
      • 伦敦摄政街(Regent Street): 这条街道的规划和建筑设计体现了纳什对城市规划的理念,他将建筑与周围的环境相融合,创造出了一条优美的城市景观。

      通过以上分析,我们可以更好地理解“纳什的作品将浪漫主义和古典建筑风格结合,使得建筑风格中融入更多的情感元素,影响了后来的建筑设计”这句话的含义。它强调了浪漫主义在建筑领域的重要性,以及纳什作为一位重要的建筑师,在融合不同风格、表达情感方面所做出的贡献。

      总而言之,这段话描述了建筑领域中浪漫主义风格的兴起和发展,以及约翰·纳什在其中的重要作用。他通过将浪漫主义和古典主义相结合,为建筑设计注入了更多情感和个性,对后世产生了深远的影响。

    1. Author response:

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

      Reviewer #1 (Public review):

      Previous experimental studies demonstrated that membrane association drives avidity for several potent broadly HIV-neutralizing antibodies and its loss dramatically reduces neutralization. In this study, the authors present a tour de force analysis of molecular dynamics (MD) simulations that demonstrate how several HIV-neutralizing membrane-proximal external region (MPER)-targeting antibodies associate with a model lipid bilayer.

      First, the authors compared how three MPER antibodies, 4E10, PGZL1, and 10E8, associated with model membranes, constructed with two lipid compositions similar to native viral membranes. They found that the related antibodies 4E10 and PGZL1 strongly associate with a phospholipid near heavy chain loop 1, consistent with prior crystallographic studies. They also discovered that a previously unappreciated framework region between loops 2-3 in the 4E10/PGZL1 heavy chain contributes to membrane association. Simulations of 10E8, an antibody from a different lineage, revealed several differences from published X-ray structures. Namely, a phosphatidylcholine binding site was offset and includes significant interaction with a nearby framework region. The revised manuscript demonstrates that these lipid interactions are robust to alterations in membrane composition and rigidity. However, it does not address the reverse-that phospholipids known experimentally not to associate with these antibodies (if any such lipids exist) also fail to interact in MD simulations.

      Next, the authors simulate another MPER-targeting antibody, LN01, with a model HIV membrane either containing or missing an MPER antigen fragment within. Of note, LN01 inserts more deeply into the membrane when the MPER antigen is present, supporting an energy balance between the lowest energy conformations of LN01, MPER, and the complex. These simulations recapitulate lipid binding interactions solved in published crystallographic studies but also lead to the discovery of a novel lipid binding site the authors term the "Loading Site", which could guide future experiments with this antibody.

      The authors next established course-grained (CG) MD simulations of the various antibodies with model membranes to study membrane embedding. These simulations facilitated greater sampling of different initial antibody geometries relative to membrane. These CG simulations , which cannot resolve atomistic interactions, are nonetheless compelling because negative controls (ab 13h11, BSA) that should not associate with membrane indeed sample significantly less membrane.

      Distinct geometries derived from CG simulations were then used to initialize all-atom MD simulations to study insertion in finer detail (e.g., phospholipid association), which largely recapitulate their earlier results, albeit with more unbiased sampling. The multiscale model of an initial CG study with broad geometric sampling, followed by all-atom MD, provides a generalized framework for such simulations.

      Finally, the authors construct velocity pulling simulations to estimate the energetics of antibody membrane embedding. Using the multiscale modelling workflow to achieve greater geometric sampling, they demonstrate that their model reliably predicts lower association energetics for known mutations in 4E10 that disrupt lipid binding. However, the model does have limitations: namely, its ability to predict more subtle changes along a lineage-intermediate mutations that reduce lipid binding are indistinguishable from mutations that completely ablate lipid association. Thus, while large/binary differences in lipid affinity might be predictable, the use of this method as a generative model are likely more limited.

      The MD simulations conducted throughout are rigorous and the analysis are extensive, creative, and biologically inspired. Overall, these analyses provide an important mechanistic characterization of how broadly neutralizing antibodies associate with lipids proximal to membrane-associated epitopes to drive neutralization.

      Reviewer #2 (Public review):

      In this study, Maillie et al. have carried out a set of multiscale molecular dynamics simulations to investigate the interactions between the viral membrane and four broadly neutralizing antibodies that target the membrane proximal exposed region (MPER) of the HIV-1 envelope trimer. The simulation recapitulated in several cases the binding sites of lipid head groups that were observed experimentally by X-ray crystallography, as well as some new binding sites. These binding sites were further validated using a structural bioinformatics approach. Finally, steered molecular dynamics was used to measure the binding strength between the membrane and variants of the 4E10 and PGZL1 antibodies.

      The use of multiscale MD simulations allows for a detailed exploration of the system at different time and length scales. The combination of MD simulations and structural bioinformatics provides a comprehensive approach to validate the identified binding sites. Finally, the steered MD simulations offer quantitative insights into the binding strength between the membrane and bnAbs.

      While the simulations and analyses provide qualitative insights into the binding interactions, they do not offer a quantitative assessment of energetics. The coarse-grained simulations exhibit artifacts and thus require careful analysis.

      This study contributes to a deeper understanding of the molecular mechanisms underlying bnAb recognition of the HIV-1 envelope. The insights gained from this work could inform the design of more potent and broadly neutralizing antibodies.

      Recommendations for the authors:

      Reviewing Editor:

      We recommend the authors remove the figure and section related to bnAb LN01, perform additional analysis (e.g., further expanding on the differences in antibody binding in the presence or absence of antigen), and present this as a separate manuscript in a follow-up study.

      We consider the analysis of a bnAb with a transmembrane antigen and of LN01 as essential to the manuscript and novel results.  Study of LN01 provides many insights unique from the other MPER bnAbs in this study.  We agree further characterization of LN01 and bnAbs with transmembrane antigen or full-length Env are intriguing and necessary to complete the full mechanistic understanding of lipid-associated antibodies.  LN01 section in this paper is novel in the field and demonstrates the preliminary evidence motivating further work, which we agree are beyond the scope of this already long detailed study.

      Reviewer #1 (Recommendations for the authors):

      I appreciate the degree to which the authors responded to my previous points raised in the private review, including edits where I might have missed something in the manuscript or relevant literature. I imagine such a point-by-point response was quite onerous. Thank you also for balancing presentation/clarity with content/rigor considering the large information content of this manuscript; in silico results are inherently hard to present given the delicate balance between rigorous validation and novel information content. I apologize if I repeat points raised and addressed previously and commend the authors on their revised study, which is much improved in clarity; any additional revisions are of course entirely at your discretion.

      "...now having more diversity in lipid headgroup chemistries" references the wrong figure-it should be: Figure 2-figure supplement 2A-C. The incorrect figure is also referenced again several sentences down: "...relevant CDR and framework surface loops..."

      Thank you for pointing out this error. We have corrected figure references.

      "One shared conformational difference observed for these bnAbs the higher cholesterol bilayers was slightly more extensive and broader interaction profiles as well as modestly deeper embedding of the relevant CDR and framework surfaces loops" please rephrase

      Thank you for this suggestion.  We rephrased this for improved clarity and flow. 

      "These results bolster the feasibility for using all-atom MD as an in silico platform to explore differential phospholipid affinity at these sites (i.e., specificity studies) and influence on antibody preferred conformation as membrane composition and lipid chemistry are systematically varied" Please tone down these speculations-you have demonstrated that simulations are robust to different headgroup chemistries but have not provided evidence for the exclusion of lipids that are known not to associate with these antibodies.

      We rephrased this speculation to highlight the potential of this application. We also emphasize future studies that would be required to achieve this application in the following sentence.

      “These results motivate use of all-atom MD as an in silico approach for exploring differential phospholipid affinity at these sites…”

      Figure 2A: Specify which PDB entry corresponds to the displayed crystal structures in the main figure or caption.

      We clarified these PDB entries in the figure caption. 

      Check reference formatting in supplemental figures when generating VOR.

      I am not sure how relevant this might be to the claims of Figure 2-figure supplement 3, but AlphaFold3-based phospholigand docking might provide an additional orthogonal approach if relevant ligand(s) are available for such analysis (particularly for the newly proposed 10E8 POPC complex).

      Thank you for this suggestion.  AI/ML based prediction methods like AF3 and RoseTTAFold All-Atom (RFAA) are interesting new methods that have come since our initial submission.   We’ve decided these experiments are beyond the scope of this already long and detailed study. We have added a sentence suggesting use of these methods in future work.

      "We next studied bnAb LN01 to interrogate differences" --> this transition still reads a bit unclear. Why shift gears and change antibodies? Also, while you do go into its interactions both +/- antigen, there's no lead into the simulation initialization with and without antigen to guide the reader into the comparisons you will draw in the figure. Also, the order of information presentation is a bit strange, where the rationale for choosing a single monomeric helix is brought up in the middle of the paragraph instead of at the beginning of the section. In the next paragraph, it goes back to the initialization of the membrane composition again, which feels a bit disorganized-I do appreciate the unique challenge of having to weave through so much quality data! In fact, if you were to conduct simulations of membrane + antigen vs. membrane + LN01 vs. membrane + LN01 + antigen, I am tempted to say that this could be removed from this manuscript and flow better as a paper in and of itself.

      We thank the reviewer for the suggestion to improve the writing style.  We feel this section adds a lot of value to the manuscript, so we will keep it in the paper and improved the transition as well as rationale.  

      We selected to study the additional antibody LN01 and the monomeric MPER-TM antigen conformation because of the existing structural evidence available without additional creative model building.  This rationale has been updated in the new text.  

      We changd the order of information as suggested, moving the rationale for antigen fragment earlier in the paragraph followed by the background of the lipids sites from the crystal that can lead into simulation set-up.  We clarified the simulation initialization was similar for systems with and without antigen in the opening sentence of the paragraph

      "previously observed snorkeling and hydration of TM Arg686" --> Is this R696 (numbering could be different based on the particular Env)?

      Thank you for noting this typo, we have corrected the numbering.

      Potential font color issue with Figure 3-Figure supplement 1 B and part of A text-could be fixed in typesetting.

      The discussion reads very well. Is it possible to direct antibody maturation, even in an engineered context, towards membrane affinity without increasing immunogenic polyreactivity? This is mentioned very briefly and cited with ref 36, but I would be interested in the author's thoughts on this topic.

      We thank the reviewer for the insightful idea to explore in future work.  Our conclusion alludes to possibly artificially evolving membrane affinity studied by MD, as done in vitro by Nieva and co-workers.  Because the hypothetical nature, we’ve chosen not to elaborate on those ideas from this manuscript.

      Reviewer #2 (Recommendations for the authors):

      To ensure reproducibility and facilitate further research, the authors should publicly deposit the code for running the MD simulations and analyses (e.g., on GitHub) along with the underlying data used in the study (e.g., on Zenodo.org).

      We appreciate the consideration for open-source code and analysis. Representative code and simulation trajectories were uploaded to the following repositories:

      https://github.com/cmaillie98/mper_bnAbs.git

      https://zenodo.org/records/13830877

      —-

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Previous experimental studies demonstrated that membrane association drives avidity for several potent broadly HIV-neutralizing antibodies and its loss dramatically reduces neutralization. In this study, the authors present a tour de force analysis of molecular dynamics (MD) simulations that demonstrate how several HIV-neutralizing membrane-proximal external region (MPER)-targeting antibodies associate with a model lipid bilayer.

      First, the authors compared how three MPER antibodies, 4E10, PGZL1, and 10E8, associated with model membranes, constructed with a lipid composition similar to the native virion. They found that the related antibodies 4E10 and PGZL1 strongly associate with a phospholipid near heavy chain loop 1, consistent with prior crystallographic studies. They also discovered that a previously unappreciated framework region between loops 2-3 in the 4E10/PGZL1 heavy chain contributes to membrane association. Simulations of 10E8, an antibody from a different lineage, revealed several differences from published X-ray structures. Namely, a phosphatidylcholine binding site was offset and includes significant interaction with a nearby framework region.

      Next, the authors simulate another MPER-targeting antibody, LN01, with a model HIV membrane either containing or missing an MPER antigen fragment within. Of note, LN01 inserts more deeply into the membrane when the MPER antigen is present, supporting an energy balance between the lowest energy conformations of LN01, MPER, and the complex. Additional contacts and conformational restraints imposed by ectodomain regions of the envelope glycoprotein, however, remain unaddressed-the size of such simulations likely runs into technical limitations including sampling and compute time.

      The authors next established course-grained (CG) MD simulations of the various antibodies with model membranes to study membrane embedding. These simulations facilitated greater sampling of different initial antibody geometries relative to membrane. Distinct geometries derived from CG simulations were then used to initialize all-atom MD simulations to study insertion in finer detail (e.g., phospholipid association), which largely recapitulate their earlier results, albeit with more unbiased sampling. The multiscale model of an initial CG study with broad geometric sampling, followed by all-atom MD, provides a generalized framework for such simulations.

      Finally, the authors construct velocity pulling simulations to estimate the energetics of antibody membrane embedding. Using the multiscale modelling workflow to achieve greater geometric sampling, they demonstrate that their model reliably predicts lower association energetics for known mutations in 4E10 that disrupt lipid binding. However, the model does have limitations: namely, its ability to predict more subtle changes along a lineage-intermediate mutations that reduce lipid binding are indistinguishable from mutations that completely ablate lipid association. Thus, while large/binary differences in lipid affinity might be predictable, the use of this method as a generative model are likely more limited.

      The MD simulations conducted throughout are rigorous and the analysis are extensive. However, given the large amount of data presented within the manuscript, the text would benefit from clearer subsections that delineate discrete mechanistic discoveries, particularly for experimentalists interested in antibody discovery and design. One area the paper does not address involves the polyreactivity associated with membrane binding antibodies-MD simulations and/or pulling velocity experiments with model membranes of different compositions, with and without model antigens, would be needed. Finally, given the challenges in initializing these simulations and their limitations, the text regarding their generalized use for discovery, rather than mechanism, could be toned down.

      Overall, these analyses provide an important mechanistic characterization of how broadly neutralizing antibodies associate with lipids proximal to membrane-associated epitopes to drive neutralization.

      Reviewer #2 (Public Review):

      In this study, Maillie et al. have carried out a set of multiscale molecular dynamics simulations to investigate the interactions between the viral membrane and four broadly neutralizing antibodies that target the membrane proximal exposed region (MPER) of the HIV-1 envelope trimer. The simulation recapitulated in several cases the binding sites of lipid head groups that were observed experimentally by X-ray crystallography, as well as some new binding sites. These binding sites were further validated using a structural bioinformatics approach. Finally, steered molecular dynamics was used to measure the binding strength between the membrane and variants of the 4E10 and PGZL1 antibodies.

      The conclusions from the paper are mostly well supported by the simulations, however, they remain very descriptive and the key findings should be better described and validated. In particular:

      It has been shown that the lipid composition of HIV membrane is rich in cholesterol [1], which accounts for almost 50% molar ratio. The authors use a very different composition and should therefore provide a reference. It has been shown for 4E10 that the change in lipid composition affects dynamics of the binding. The robustness of the results to changes of the lipid composition should also be reported.

      The real advantage of the multiscale approach (coarse grained (CG) simulation followed by a back-mapped all atom simulation) remains unclear. In most cases, the binding mode in the CG simulations seem to be an artifact.

      The results reported in this study should be better compared to available experimental data. For example how does the approach angle compare to cryo-EM structure of the bnAbs engaging with the MPER region, e.g. [2-3]? How do these results from this study compare to previous molecular dynamics studies, e.g.[4-5]?

      References<br /> (1) Brügger, Britta, et al. "The HIV lipidome: a raft with an unusual composition." Proceedings of the National Academy of Sciences 103.8 (2006): 2641-2646.<br /> (2) Rantalainen, Kimmo, et al. "HIV-1 envelope and MPER antibody structures in lipid assemblies." Cell Reports 31.4 (2020).<br /> (3) Yang, Shuang, et al. "Dynamic HIV-1 spike motion creates vulnerability for its membrane-bound tripod to antibody attack." Nature Communications 13.1 (2022): 6393.<br /> (4) Carravilla, Pablo, et al. "The bilayer collective properties govern the interaction of an HIV-1 antibody with the viral membrane." Biophysical Journal 118.1 (2020): 44-56.<br /> (5) Pinto, Dora, et al. "Structural basis for broad HIV-1 neutralization by the MPER-specific human broadly neutralizing antibody LN01." Cell host & microbe 26.5 (2019): 623-637.

      Considering reviewer suggestions, we slightly reorganized the results section into specific sub-sections with headings and changed the order in which key results were presented to allow the subsequent analysis more accessible for readers.  Supplemental materials were redistributed into eLife format, having each supplemental item grouped to a corresponding main figure. Many slightly detail modifications were made to figures (mostly supplemental items) without changing their character, such as clearer axes labels or revised annotations within panels.

      The major additions within the results sections based on the reviews were:

      (1) An expanded the comparison between our simulation analyses to previous simulations and to existing cryo-EM structural evidence for MPER antibodies’ membrane orientation the context of full-length antigen, resulting in new supplemental figure panels.

      (2) New atomistic simulations of 10E8, PGZL1, and 4E10 evaluating the phospholipid binding predictions in a different lipid composition more closely modeling HIV membranes.

      Minor edits to the analyses and interpretations include:

      (1) Outlining the geometric components contributing to variance in substates after clustering the atomistic 10E8, 4E10, and PGZL1 simulations.

      (2) Better defining the variance and durability of membrane interactions within and across systems in the coarse grain methods section.

      (3) Removed interpretations in the original results sections regarding polyreactivity and energetics for MPER bnAbs that were not explicitly supported by data.   

      (4) More context of the prevenance of bnAb loop geometries in structural informatics section

      (5) Rationale for the choice of the continuous helix MPER-TM conformation in LN01-antigen conformations, and citations to previous gp41 TM simulations.

      (6) Removed language on the novelty of the coarse grain and steered pulling simulations as newly developed approaches; tempering the potential discriminating power and applications of those approaches, in light of their limitations.

      The discussion was revised to provide more novel context of the results within the field, including discussing direct relevance of the simulation methods for evaluating immune tolerance mechanisms and into antibody engineering.   We have shared custom scripts used for molecular dynamics analysis on github (https://github.com/cmaillie98/mper_bnAbs.git) and uploaded trajectories to a public repository hosted on Zenodo (https://zenodo.org/records/13830877).

      Recommendations for the authors:

      Below, I provide an extensive list of minor edits associated with the text and figures for the authors to consider. I provide these with the hope of increasing the accessibility of the manuscript to broader audiences but leave changes to the discretion of the authors.

      Text/clarity

      Figure 1 main text

      The main text discussing Figure 1 is disorganized, making the analysis difficult to follow. I would suggest the following: moving the sentence, "4E10 and PG2L1 are structurally homologous" immediately after the paragraph discussing the simulation initiation. Then, add a sentence that directly compares their experimental affinity, neutralization, and polyreactivity of 4E10 and PG2L1 (later, an unintroduced idea pops up, "These patterns may in part explain 4E10's greater polyreactivity"). Next, lead into the discussion of the MD simulation data with something to the effect of: "Given these similarities, we first compared mechanisms of membrane insertion between 4E10 and PG2L1 to bolster confidence in our predictions". Later, the sentence "Across 4E10 and PGZL1 simulations, the bound lipid phosphates"

      We thank the reviewer for the suggestion and we have restructured the beginning of the results to implement this style: to first introduce then discuss the comparative PGZL1 & 4E10 results, i.e. Figure 1 plus associated supplements.

      In the background and the introduction text leading up to Figure 1, CDR-H3 is discussed at length, however, the first figure focuses almost entirely on how CDR-H1 coordinates a lipid phosphate headgroup. Are there experimental mutations in this loop that do not affect affinity (e.g., to a soluble gp41 peptide), but do affect neutralization (like the WAWA mutation for CDR-H3, discussed later)?

      We have altered the Introduction (para 2) and Results (4E10/PGZL1 sub-section) to give more balanced discussion of CDRs H1 & H3.  That includes referencing experimental data addressing the reviewer’s question; a PGZL1 clone H4K3 where mutations to CDRH1 were introduced and shown have minimal impact on affinity to MPER peptide via ELISA and BLI, but those mutant bnAbs had significantly reduced neutralization efficacy (PMC6879610).

      The sentence "These phospholipid binding events were highly stable, typically persisting for hundreds of nanoseconds" should be moved down to immediately precede, "[However], in a PGZL1 simulation, we observed a". This would be a good place for a paragraph break following, "Thus, these bnABs constitutively", since this block of text is very long.

      Similarly, the sentence and parts of the section, "Likewise, the interactions coordinating the lipid phosphate oxygens at CDR-H1" more appropriately belongs immediately before or after the sentence, "Our simulations uncover the CDR-lipid interactions that are the most feasible".

      Thank you for the detailed guidance in reorganizing the Figure 1 results.  We followed the advice to directly compare 4E10 and PGZL1 results separately from 10E8, moving those sections of text appropriately.  New paragraph breaks were added to improve accessibility and flow of concepts throughout the Results.

      In the sentence, "our simulations uncover CDR-lipid interactions that are the most feasible and biologically relevant in the context of a full [HIV] lipid bilayer... validation to which of the many possible ions" à have you confidently determined lipid binding and positioning outside of the site validated in figure 1? Which site(s) are these referencing? The next two sentences then introduce two new ideas on the loop backbone stability then lead into lipid exchange, which is a bit jarring.

      We have adjusted the language concerning the putative ions/lipids electron density across the many PGZL1 and 4E10 crystal structures, and additionally make the explicit point that we confidently determined the lack of lipid binding outside of the site focused on in Figure 1.

      “… both bnAbs showed strong hotspots for a lipid phosphate bound within the CDR-H1 loops, with minimal phospholipid or cholesterol ordering around the proteins elsewhere.  The simulated lipid phosphates bound within CDR-H1 have exceptional overlap with electron densities and atomic details of modelled headgroups from respective lipid-soaked co-crystal structures…”

      Figure 2 main text

      "We similarly investigated bnAb 10E8" - Please make this a separate subheader, the block text is very long up to this point.

      Thank you for the suggestion. We introduced a sub-header to separate work on 10E8 all-atom simulations.

      "we observed a POPC complexed with... modelled as headgroup phosphoglycerol anions..." - please cite the references within the text.

      Thank you for pointing out this missing reference, we added the appropriate reference.

      "One striking and novel observation" - please remove the phrase "striking" throughout, for following best practices in scientific writing (PMC10212555)-this is generally well-done throughout.

      We removed “striking” from our text per your suggestion.

      "This CDR-L1 site highlights... (>500 fold) across HIV strains" - How much do R29 and Y32 also contribute to antigen binding and the conformation of this loop? These mutants also decreased Kd by approximately 20X, and based on the co-crystal structure with the TM antigen (PDB: 4XCC), seem to play a more direct role in antigen contact. Additionally, these residues should be highlighted on a figure, otherwise it's difficult to understand why they are important for membrane association.

      We thank the reviewer for deep engagement to these supporting experimental details.  The R29A+Y32A 10E8 mutant referenced in the text showed only 4-fold Kd increase, a modest change for an SPR binding experiment.  Whereas R29E+Y32E 10E8 mutant resulted in 40x Kd increase, the “20x” the reviewer refers to.  Both 10E8 mutants showed similar drastically reduced breadth and potency of over 2 orders of magnitude on average.

      These mutated CDR-L1 residues are not directly involved in antigen contact and adopt the same loop helix conformation when antigen is bound.  A minor impact on antigen binding affinity could be due altering pre-organization of CDR loops upon losing interactions from the Tyr & Arg sidechains - particularly Tyr31 in contact with CDR-H3.

      As per the suggestion, clearer annotated figure panel denoting these sidechains has been added to Figure 2-Figure Supplement 1 for 10E8 analysis.

      "Structural searches querying... identified between 10^5 and 2*10^6..." - why is this value represented as such a large range? Does this depend on the parameters used for analysis? Please clarify.

      Additionally, how prevalent are any random loop conformations compared to the ones you searched? It's otherwise difficult to attribute number of occurrences within the 2 A cutoff to biological significance, as this number is not put in context.

      We appreciate the reviewers comment to contextualize the range and relative frequency of the bnAb loop conformations.   RMSD and length of loop are the key parameters, which can be controlled by searching reference loops of similar length.  The main point of the backbone-level searching is simply to imply the bnAb loops are not particularly rare when comparing loops of similar length.   

      We did as was suggested and added comparison to random loops of the same length to the main text, including a new Supplementary Table 4.   

      “…identified between 105 to 2∙106 geometrically similar sub-segments within natural proteins (<2 Å RMSD)40, reflecting they are relatively prevalent (not rare) in the protein universe, comparing well with frequency of other surface loops of similar length in antibodies (Supplementary Table 3).”

      "We next examined the geometries" could start after its own new subheading. Moreover, while there's an emphasis on tilt for neutralization, there is not a figure clearly modelling the proposed Env tilt compared to the relatively planar bilayer. It would be helpful to have an additional panel somewhere that shows the orientation of the antibody (e.g., a representative pose) in the simulations relative to an appropriately curved membrane, Env, the binding conformation of the antibody to Env, and apo Env, given the tilting observed in PMID: 32348769 and theorized in PMC5338832. What additional conformational changes or tilting need to occur between the antibodies and Env to accomplish binding to their respective epitopes?

      Thank you for outlining an interesting element to consider in our analysis of a multi-step binding mechanism for MPER antibodies. We added additional figure panels in the supplement to outline the similarities and differences between our simulations and Fabs with the inferred membranes in cryo-EM experiments of full-length HIV Env.  The simulated Fabs’ angles are very similar with only minor tilting to match the cryo-EM antibody-membrane geometries. 

      We added Figure 1-figure supplement 1A & Figure 2-figure supplement 2A, and alter to text to reflect this:

      “The primary difference is Env-bound Fabs in cryo-EM adopt slightly more shallow approach angles (~15_°_) relative to the bilayer normal.  The simulated bnAbs in isolation prefer orientations slightly more upright, but presenting CDRs at approximately the same depth and orientation.  Thus, these bnAbs appear pre-disposed in their membrane surface conformations, needing only a minor tilt to form the membrane-antibody-antigen neutralization complex.”   

      Env tilt dynamics and membrane curvature of natural virions may reconcile some of these differences.  Recent in situ tomography of Full-length Env in pseudo-virions corroborates our approximation of flat bilayers over the short length scales around Env.

      The sentence "we next examined the geometries" mentions "potential energy cost, if any, for reorienting...". However, there's no further discussions of geometry or energy cost within this section. Please rephrase, or move this figure to main and increase discussion associated with the various conformational ensembles, their geometry, and their phospholipid association.

      As the reviewer highlights, the unbiased simulations and our analysis do not explicitly evaluate energetics.  We removed this phrase, and now only allude to the minimal energy barrier between the similar geometric conformations, relative to the tilting & access requirements for antigen binding mechanism.

      “The apparent barrier for re-orientation is likely much less energetically constraining than shielding glycans and accessibility of MPER”

      ".. describing the spectrum of surface-bound conformations" cites the wrong figure.

      Thank you for noticing this error; we correct the figure reference to (Figure 2-figure supplement 4).

      Please comment on the significance of how global clustering (Fig. S5A-C) was similar for 4E10 and PGZL1, but different for 10E8 (e.g., blue, orange, and yellow clusters for 4E10 and PHZL1 versus cyan, red, and green clusters for 10E8). As the cyan cluster seems to be much closer in Euclidian space to the 4E10/PGZL1 clusters, it might warrant additional analysis. What do these clusters represent in terms of structure/conformation? How do these clusters differ in membrane insertion as in (A)?

      We are grateful you identify analysis in the geometric clustering section that may be of interest to other readers. We have added additional supplementary table (Table 2) to detail the CDR loop membrane insertion and global Fab angles which describe each cluster, to demonstrate their similarities and differences.  We also better describe how global clustering was similar for 4E10 and PGZL1, but different for 10E8 in the relevant results section<br /> The cyan cluster is not close in structure to 4E10/PGZL1 clusters.  We note the original figure panel had an error.  The updated Figure 2-supplement 4B shows the correct Euclidian distance hierarchy with an early split between 4e10/pgzl1 and 10e8 clusters.

      Figure 3 main text

      The start of this section, "We next studied bnAb LN01...", is a good place for a new subheader.

      We have added an additional subheader here: Antigen influence on membrane bound conformations and lipid binding sites for LN01

      There should be a sentence in the main text defining the replicate setup and production MD run time. Is the apo and complex based on a published structure? How do you embed the MPER? Is the apo structure docked to membrane like in 4E10? The MD setup could also be better delineated within the methods.

      The first two paragraphs in this section have been updated to clarify the relevant simulations configuration and Fab membrane docking prediction details. 

      The procedure was the same for predicting an initial membrane insertion, albeit now we use the LN01-TM complex and the calculation will account for the membrane burial of the the TM domain and MPER fragment.  As mentioned, LN01 is predicted as inserted with CDR loops insert similarly with or without the TM-MPER fragment.  The geometry differs from PGZL1/4E10 and 10E8, denoted by the text.

      Please comment on the oligomerization state of the antigen used in the MD simulation: how does the simulation differ from a crossed MPER as observed in an MPER antibody-bound Env cryo-EM structure (PMID: 32348769), a three-helix bundle (PMC7210310), or single transmembrane helix (PMC6121722)? How does the model MPER monomer embed in the membrane compared to simulations with a trimeric MPER (PMC6035291, PMID: 33882664)-namely, key arginine residues such as R696?

      We thank the reviewer for pointing out critical underlying rationale for modeling this TM-MPER-LN01 complex which we have corrected in the revised draft. The range of potential conformations and display of MPER based on TM domain organization could easily be its own paper – we in fact have a manuscript in preparation on the topic.  

      The updated text expands the rationale for choosing the monomeric uninterrupted helix form of the MPER-TM model antigen (para 1 of LN01 section). The alternative conformations we did not to explore are called out, with references provided by the reviewer.

      The discussion qualified that the MPER presentation is likely oversimplified here, noting MPER display in the full-length Env trimer will vary in different conformational states or membrane environments. However, the only cryo-EM structures of full-length ENV with TM domains resolved have this continuous helix MPER-TM conformation – seen both within crossing TM dimers or dissociated TM monomers.

      Are there additional analyses that can validate the dynamics of the MPER monomer in the membrane and relative to LN01? Such as key contacts you would expect to maintain over the duration of the MD simulation?

      We also increased description of this TM domain’s behavior, dynamics (tilt, orientation, Arg696 snorkeling, and complex w LN01) to provide a clearer picture of the simulation results – which aligns with past MD of the gp41 TM domain as a monomer (para 2 of LN01 section).  As well, we noted key LN01-MPER contacts that were maintained.

      How does the model MPER modulate membrane properties like lipid density and lipid proximities near LN01?

      We checked and didn’t notice differences for the types of lipids (chol, etc) proximal to the MPER-TM or the CDR loops versus the bulk lipid bilayer distributions.  Due to the already long & detailed nature of this manuscript, we elect not to include discussion on this topic.

      Supplemental figure 1H-I would be better positioned as a figure 3-associated supplemental figure.

      We rearranged to follow the eLife format and have paired supplemental panels with their most relevant main figures.

      Figure 3F/H reference a "loading site" but this site is defined much later in the text, which was confusing.

      Thank you for pointing out this source of confusion, we rearranged our discussion to reflect the order in which we present data in figures.

      What evidence suggests that lipids "quickly exchange from the Loading site into the X-ray site by diffusion"? I do not gather this from Figure S1H/I.

      We have rearranged the loading side and x-ray site RMSD maps in Figure 3-Figure supplement 1 to better illustrate how a lipid exchanges between these sites.

      Figure 4 main text

      The authors assert that in the CG simulations, restraints, "[maintain] Fab tertiary and quaternary structure". However, backbone RMSD does not directly assert this claim-an additional analysis of the key interfacial residues between chains, or geometric analysis between the chains, would better support this claim.

      Thank you for pointing this point.  We rephrased to add that the major sidechain contacts between heavy and light chain persist, in addition to backbone RMSD, to describe how these Fabs maintain the fold stably in CG representation. 

      In several cases, CG models sample and then dissociate from the membrane. In the text, the authors mention, "course-grained models can distinguishing unfavorable and favorable membrane-bound conformations". Is there a particular orientation that causes/favors membrane association and dissociation? This analysis could look at conformations immediately preceding association and dissociation to give clues as to what orientation(s) favor each state.

      Thank you for suggesting this interesting analysis.  Clustering analysis of associated states are presented in Figure 5, Figure 5-Figure Supplement 1, and Figure 6, which show all CDR and framework loop directed insertion.  This feature is currently described in the main text.  

      We did not find strong correlation of specific orientations as “pre-dissociation” states or ineffective non-inserting “scanning” events.  We revised the key sentence to reflect the major take away – that non-CDR alternative conformations did not insert and most of those having CDRs inserted in a different manner than all-atom simulations also were prone to dissociate:

      “Given that non-CDR directed and alternative CDR-embedded orientations readily dissociate, we conclude that course-grained models can distinguish unfavorable and favorable membrane-bound conformations to an extent that provides utility for characterizing antibody-bilayer interaction mechanisms.”

      Figure 6 main text

      "For 4E10, trajectories initiated from all three geometries..." only two geometries are shown for each antibody. Please include all three on the plot.

      The plots include markers for all three geometries for 4E10, highlighted in stars or with letters on the density plots of angles sampled (Figure 6B,C)

      "Aligning a full-length IgG... unlikely that two Fabs simultaneously..." Are there theoretical conformations in which two Fabs could simultaneously associate with membrane? If this was physiological or could be designed rationally, could an antibody benefit further from avidity?

      Our modeling suggests the theoretical conformations having two Fabs on the membrane are infeasible.  It’s even less likely multiple Env antigens could be engaged by one IgG.  We have revised the text to express this more clearly.

      Figure 7 main text

      "An intermediate... showed a modest reduction in affinity..." what affinity does PGZL1 have for this antigen?

      The preceding sentence for this information: “Mature PGZL1 has relatively high affinity to the MPER epitope peptide (Kd = 10 nM) and demonstrates great breadth and potency, neutralizing 84% of a 130 strain panel “

      Figures

      Figure 1

      It would be helpful to have an additional panel at the top of this figure further zoomed out showing the orientation of the antibody (e.g., a representative pose) in the simulations relative to an appropriately curved membrane, Env, the binding conformation of the antibody to Env, and apo Env, given the tilting observed in PMID: 32348769 and theorized in PMC5338832. What additional conformational changes or tilting need to occur between the antibodies and Env to accomplish binding to their respective epitopes?

      Thank you for the suggestion to include this analysis.  We have added to the text reflecting this information, as well as making new supplemental panels for 4E10 and 10E8 that we compare simulated 4E10 and 10E8 Fab conformations to cryoEM density maps with Fabs bound to full-length HIV Env. Figure 1-figure supplement 1A & Figure 2-figure supplement 2A

      In Figure 1, space permitting, it would be helpful to annotate the distances between the phosphates and side chains (similarly, for Figure S1A).

      To avoid the overloading the Main figure panels with text, those relevant distances are listed in the methods sections.  Those distances are used to define the “bound” lipid phosphate state.  Generally, we note the interactions are within hydrogen bonding distance.

      Annotating "Replicate 1" and "Replicate 2" on the left side of Figure 1C/D would make this figure immediately intuitive.

      We have added these labels.

      Figure caption 1C: Please clarify the threshold/definition of a contact used to binarize "bound" versus "unbound" (for example, "mean distance cutoff of 2A between the phosphate oxygen and the COM of CDR-H1") [on further reading of the methods section, this criterion is quite involved and might benefit from: a sentence that includes "see methods"]. Additionally, C could use a sentence explaining the bar such as in E, "Phosphate binding is mapped to above each MD trajectory" Please define FR-H3 in the figure caption for E/F.

      We have added these details to the figure caption.

      Because Figure 1 is aggregated simulation time, it would be helpful to also represent the data as individual replicates or incorporate this information to calculate standard deviations/statistics (e.g., 1 microsecond max using the replicates to compute a standard deviation).

      We believe the current quantification & display of data via sharing all trajectories is sufficient to convey the major point for how often each CDR-phosholipid binding site it occupied.  Further tracking and statistics of inter-atomic distances will likely be too tedious & add minimal value. There is some dynamics of the phosphate oxygens between the polar within the CDR site but our “bound” state definitions sufficiently describe the key participating interactions are made.

      Figure 2

      For A, it would be helpful to annotate the yellow and blue mesh on the figure itself.

      We have defined the orange phosphate and blue choline densities.

      Also, where are R29 and Y32 relative to this site? In the X-ray panels, Y38 is not shown, and the box delineating the zoom-in is almost imperceptible.

      Thank you for this suggestion to include those amino acids which are referenced in the text as critical sites where mutation impacts function. To clarify, Y32 is the pdb numbering for residue Y38 in IMGT numbering. We have added a panel to Figure 2-Figure Supplement 1 having a cartoon graphic of 10E8 loop groove with sidechains & annotating R29 and Y38, staying consistent with out use of IMGT numbering in the manuscript.

      Figure 3

      It might read clearer to have "LN01+MPER-TM" and "LN01-Apo" in the middle of A/B and C/D, respectively, and a dotted line delineating the left and right side of the figure panels.

      We have added these details to the figure for clarity for readers.

      It would be helpful to show some critical interactions that are discussed in the text, such as the salt bridge with K31, by labeling these on the figure (e.g., in E-H).

      We drafted figure panels with dashed lines to indicate those key interactions.  However, they became almost imperceptible and overloaded with annotations that distracted from the overall details.  For K31, the interaction occurs in LN01 crystal structures readers can refer to.

      Why are axes cut off for J?

      We corrected this.

      Please re-define K/L plots as in Figure 1, and explain abbreviations.

      We updated the figure caption to reflect these changes.

      Figure 4

      The caption for panel A states that the Fab begins in solvent 1-2 nm above the bilayer, but the main text states 0.5-2 nm.

      We have reconciled this difference and listed the correct distances: 0.5-2nm.

      Please label the y-axis as "Replicate" for relevant figure panels so that they are more immediately interpretable.

      This label has been added.

      A legend with "membrane-associated" and "non-associated" within the figure would be helpful. Additionally, the average percent membrane associated, with a standard deviation, should be shown (Similar to 1C, albeit with the statistics).

      This legend has been added.  We also added the additional statistical metrics requested to strengthen our analysis.

      The text references "10, 14, and 12 extended insertion events" for the three antibody-based simulations. How do you define "extended insertion events"? Would breaking this into average insertion time and standard deviation better highlight the association differences between MPER antibodies and controls, in addition to the variability due to difference random initialization?

      We thank the reviewer for the insightful suggestion on how to better organize quantitative analysis to support the method. Supplemental Table 3 includes these numbers.

      Figure 5

      The analysis in Fig. S6C could be included here as a main figure.

      The drafted revised figure adding S6C to Figure 5 made for too much information.  Likewise, putting this panel S6C separated it from the parent clustering data of S6B, so we decided to keep these figures separated.  The S6 figure is now Figure 5-figure supplement 1.

      Figure 6

      Please annotate membrane insertion on E as %.

      These are phosphate binding RMSD/occupancy vs time.  The panels are now too small to annotate by %.  The qualitative presentation is sufficient at this stage.  The quantitative % are listed in-line within text when relevant to support assertions made. 

      Please use the figure caption to explain why certain clusters (e.g., 10E8 cluster A, artifact, Fig. S6E) are not included in panel E.

      We have added this information in the figure caption.

      Figure 7

      Please show all points on the box and whisker plots (panels E and F), and perform appropriate statistical tests to see if means are significantly different (these are mentioned in the text, but should be annotated on the graph and mentioned within the figure caption).

      We have changed these plots to show all data points along with relevant statistical comparisons. The figure captions describe unpaired t-test statistical tests used.

      Figure S1

      G, H, and I do not belong here-they should be moved to accompany their relevant text section, which associates with Figure 3. It would be helpful to associate this with Figure 3 in the eLife format, "Figure 3-Supplemental Figure 1" or its equivalent.

      It's very difficult to distinguish the green and blue circles on panel G.

      We darkened the shading and added outline for better visualization

      Subfigure I is missing a caption, could be included with H: "(H,I) Additional replicates for LN01+TM (H) and LN01 (I)".

      We corrected this as suggested.

      Why is H only 3 simulations and not 4? Does it not have a lipid in the x-ray site? Also, the caption states "(top, green)" and "(bottom, cyan)", but the green vs. cyan figures are organized on the left and right. Additional labels within the figure would help make this more intuitive.

      If the point of H and I is to illustrate that POPC exchanges between the X-ray and loading sites, this is unclear from the figure. Consider clarifying these figures.

      Thank you for describing the confusion in this figure, we have added labels to clarify.

      Figure S2 (panels split between revised Figure 4 associated figure supplements)

      The LN01 figures should likely follow later so that they can associate with Figure 3, despite being a similar analysis.

      We corrected supplements to eLife format so supplements are associated with relevant main figures.

      Figure S3 (panels split between revised Figure 1 & 2 associated figure supplements)

      As hydrophobicity is discussed as a driving factor for residue insertion, it would be helpful to have a rolling hydrophobicity chart underneath each plot to make this claim obvious.

      We prefer the current format, due to the worry of having too much information in these already data-rich panels.  As well, residues are not apolar but are deeply inserted.

      Figure S4 (panels split between revised Figure 1 & 2 associated figure supplements)

      It would be helpful to label the relevant loops on these figures.

      We have labeled loops for clarity.

      Do any of these loops have minor contacts with Env in the structure?

      The 4E10 and PGZL1 CDRH-1 loop does not directly contact bound MPER peptides bound in crystal structures. 

      FRL-3 and CDR-H1 in 10E8 do not contact the MPER peptide antigen component based on x-ray crystal structures.

      Do motif contacts with lipid involve minor contacts with additional loops other than those displayed in this figure?

      The phosphate-loop interactions in motifs used as query bait here are mediated solely by the backbone and side chain interactions of the loops displayed. We visually inspected most matches and did not see any “consensus” additional peripheral interactions common across each potential instance in the unrelated proteins.  The supplied Supplemental Table 2 contains the information if a reader wanted to conduct a detailed search. 

      Why is there such a difference between the loop conformation adopted in the X-ray structure and that in the MD simulation, and why does this lead to the large observed differences in ligand-binding structure matches?

      We thank the reviewer for carefully noting our error in labeling of CDR loop and framework region input queries. We revised the labeling to clarify the issue.

      The is minimal structural difference between the loops in x-ray and MD.

      Figure S5 (Figure 2-Figure supplement 4)

      This figure is not colorblind friendly-it would be helpful to change to such a pallet as the data are interesting, but uninterpretable to some.

      We have left this figure the same.

      "Susbstates" - "Substates"

      Corrected, thank you.

      Panel B is uninterpretable-please break the axis so that the Euclidian distances can be represented accurately but the histograms can be interpreted.

      We have adjusted axis for this plot to better illustrate the cluster thresholds.

      The clusters in D-H should be analyzed in greater depth. What is the structural relevance of these clusters other than differences in phospholipid occupancy in (I)? Snapshots of representative poses for each cluster could help clarify these differences.

      We have adjusted the text to describe the geometric differences in each of those clusters that result in the different exceptionally lower propensities for forming the key phospholipid interaction.  

      The figure caption should make it clear that 3 μS of aggregate simulation time is being used here instead of 4 μS to start with unique tilt initializations. E.g., "unique starting membrane-bound conformations (0 degrees, -15 degrees, 15 degrees initialization relative to the docked pose)". Further, why was the particular 0-degree replicate chosen while the other was thrown out? Or was this information averaged? Why is the full 4 μS then used for D-I?

      We thank the reviewer for noting these details.  We didn’t want to bias the differential between 10E8 and 4E10/PGZL1 by including the replicate simulations.  The analysis was mainly intended to achieve more coarse resolution distinction between 10E8 and the similar PGZL1/4E10.  

      In the subsequent clustering of individual bnAb simulation groups, the replicate 0 degree simulations had sufficiently different geometric sampling and unique lipid binding behavior that we though it should be used (4 us total) to achieve finer conformational resolution for each bnAb.

      Figure S6 (now Figure 5-Figure Supplement 1)

      Please label the CDRs in C and provide a color key like in other figures. Also, please label the y-axes. This figure could move to main below 5B with the clusters "A,B,C" labeled on 5B.

      We have added the axes labels and color key legend.  We retained a minimal CDR loop labeling scheme for the more throughput interaction profiles here where colored sections in the residue axes denote CDR loop regions.

      Figure S7 (Figure 7 Figure Supplement 1)

      Panels A and B would likely read better if swapped.

      We have swapped these panels for a better flow.

      For panel C, please display mean and standard deviation, and compare these values with an appropriate statistical test.

      This is already displayed in main figure, we have removed it from supplement.

      For E and F, please clarify from which trajectory(s) you are extracting this conformation from. Are these the global mean/representative poses? How do they compare to other geometrically distinct clusters?

      The requested information was added to supplemental figure caption.  These are frames from 2 distinct time points selected phosphate bound frames from 0-degree tilt replicates for both 4E10 and 10E8, representing at least 2 distinct macroscopic substates differing in global light chain and heavy chain orientation towards the membrane. 

      Table S2 (now Supplementary Table 3)

      Please add details for the 13h11 simulation.

      Additionally, please add average contact time and their standard deviation to the table, rather than just the aggregated total time. This will highlight the variability associated with the random initializations of each simulation.

      We have added the details for 13h11 and the requested analysis (average aggregated time +/- standard deviation and average time per association event +- standard deviation) to supplement our summary statistics for this method.

      Reviewer #2 (Recommendations For The Authors):

      (1) The structure of the manuscript should be improved. For example, almost half of the introduction (three paragraphs) summarize the results. I found it hard to navigate all the data and specific interactions described in the result section. Furthermore, the claims at the end of several sections seem unsupported. Especially for the generalization of the approach. This should be moved to the discussion section. The discussion is pretty general and does not provide much context to the results presented in this study.

      We have significantly reorganized the results section to improve the flow of the manuscript and accessibility for readers, especially the first sections of all-atom simulations. We also removed claims not directly supported by data from our results, and expanded on some of these concepts in the discussion to make some more novel context to the result.

      (2) The author should cite more rigorously previous work and refrain from using the term "develop" to describe the simple use of a well established method. E.g. Several studies have investigated membrane protein interactions e.g. [1], membrane protein-bilayer self-assembly [2], steered molecular dynamics [3], etc.

      Thank you for identifying relevant work for the simulations that set precedent for our novel application to antibody-membrane interactions.  We have removed language about development of simulation methods from the text and now better reference the precedent simulation methods used here.

      (3) Have the authors considered estimating the PMF by combining the steered MD simulation through the application of Jarzynski's equality?

      We performed from preliminary PMFs for Fab-membrane binding, but saw it was taking upward of 40 us to reach convergence.  Steered simulations focus on a key lipid may be easier.

      Although PMFs are beyond the scope of this work, we added proposals & allusion to their utility as the next steps for more rigorous quantification of fab-membrane interactions.

      Minor

      (4) The term "integrative modeling" is usually used for computational pipelines which incorporate experimental data. Multiscale modeling would be more appropriate for this study.

      We altered descriptions throughout the manuscript to reflect this comment.

      (5) Units to report the force in the steered molecular dynamics are incorrect. They should be 98.

      We changed axes and results to correctly report this unit.

      (6) Labels for axes of several graphs are not missing.

      We added labels to all axes of graphs, except for a few where stacked labels can be easily interpreted to save space and reduce complexity in figures.

      (7) Figure 3 K & L is this really < 1% of total? The term "total" should also be clarified.

      Thank you for pointing this out, we changed the % labels to be correct with axes from 0-100%. We clarified total in the figure caption.

      (8) The font size in figures should be uniformized.

      This suggestion has been applied

      (9) Time needed for steered MD should be reported in CPUh and not hours (page 17).

      We removed comments on explicit time measurements for our simulations.

      (10) Version of Martini force field is missing in methods section

      We used Martini 2.6 and added this to the methods.

      References

      (1) Prunotto, Alessio, et al. "Molecular bases of the membrane association mechanism potentiating antibiotic resistance by New Delhi metallo-β-lactamase 1." ACS infectious diseases 6.10 (2020): 2719-2731.

      (2) Scott, Kathryn A., et al. "Coarse-grained MD simulations of membrane protein-bilayer self-assembly." Structure 16.4 (2008): 621-630.

      (3) Izrailev, S., et al. "Computational molecular dynamics: challenges, methods, ideas. Chapter 1. Steered molecular dynamics." (1997).

    1. Reviewer #1 (Public review):

      Summary:

      In this manuscript, Shao et al. investigate the contribution of different cortical areas to working memory maintenance and control processes, an important topic involving different ideas about how the human brain represents and uses information when no longer available to sensory systems. In two fMRI experiments, they demonstrate that human frontal cortex (area sPCS) represents stimulus (orientation) information both during typical maintenance, but even more so when a categorical response demand is present. That is, when participants have to apply an added level of decision control to the WM stimulus, sPCS areas encode stimulus information more than conditions without this added demand. These effects are then expanded upon using multi-area neural network models, recapitulating the empirical gradient of memory vs control effects from visual to parietal and frontal cortices. Multiple experiments and analysis frameworks provide support for the authors' conclusions, and control experiments and analysis are provided to help interpret and isolate the frontal cortex effect of interest. While some alternative explanations/theories may explain the roles of frontal cortex in this study and experiments, important additional analyses have been added that help ensure a strong level of support for these results and interpretations.

      Strengths:

      - The authors use an interesting and clever task design across two fMRI experiments that is able to parse out contributions of WM maintenance alone along with categorical, rule-based decisions. Importantly, the second experiment only uses one fixed rule, providing both an internal replication of Experiment 1's effects and extending them to a different situation when rule switching effects are not involved across mini-blocks.

      - The reported analyses using both inverted encoding models (IEM) and decoders (SVM) demonstrate the stimulus reconstruction effects across different methods, which may be sensitive to different aspects of the relationship between patterns of brain activity and the experimental stimuli.

      - Linking the multivariate activity patterns to memory behavior is critical in thinking about the potential differential roles of cortical areas in sub-serving successful working memory. Figure 3's nicely shows a similar interaction to that of Figure 2 in the role of sPCS in the categorization vs. maintenance tasks. This is an important contribution to the field when we consider how a distributed set of interacting cortical areas supports successful working memory behavior.

      - The cross-decoding analysis in Figure 4 is a clever and interesting way to parse out how stimulus and rule/category information may be intertwined, which would have been one of the foremost potential questions or analyses requested by careful readers.

      - Additional ROI analyses in more anterior regions of the PFC help to contextualize the main effects of interest in the sPCS (and no effect in the inferior frontal areas, which are also retinotopic, adds specificity). And, more explanation for how motor areas or preparation are likely not involved strengthens the takeaways of the study (M1 control analysis).

      Weaknesses:

      - An explicit, quantitative link between the RNN and fMRI data is perhaps a last point that would integrate the RNN conclusion and analyses in line with the human imaging data.

      - As Rev 2 mentions, multiple types of information codes may be present, and the response letter Figure 5 using representational similarity (RSA) gets at this question. It would strengthen the work to, at minimum, include this analysis as an extended or supplemental figure.

      To sum up the results, a possible, brief schematic of each cortical area analyzed and its contribution to information coding in WM and successful subsequent behavior may help readers take away important conclusions of the cortical circuitry involved.

    1. Présentation du projet Open minds https://www.openmindsproject.eu porté par Assodev-Marsnet https://www.marsnet.org , et 3 autres partenaires européens : L'objectif du projet est de Former et outiller au numérique libre les associations / le secteur socio-culturel et de favoriser la transition vers les logiciels libres et les services éthiques de cess acteurs :

      Plateforme de ressources et de solutions numériques libres pour le secteur socio-culturelle : 1000 fiches Solutions : logiciels et services en ligne, Formations, Tutoriels et documentation, Annuaire d'acteurs du libre : prestataires, accompagnement, formation, associations usagères Avis, Recommandations, Témoignages Forum, Agenda, Actualités, Article, FAQ, Glossaire

      6 modules de formation en ligne à distance et en présentiel 1 Outils collaboratifs et de travail à distance 2 Communication (sites web - réseaux sociaux - newsletter) 3 Solutions multimédias 4 Bureautique et Internet 5 transition des associations vers le numérique libre 6 E-Inclusion

      Démonstration : comment trouver des ressources et solutions numériques libres spécifiques aux associations. Invitation à participer au comité de pilotage pour améliorer et diffuser la plateforme Présentation d'autres projets emancip'asso, framalibre, comptoir du libre, ...

    1. ICON解说

      这幅纹章看起来是某个城市、家族或机构的徽章,结合了不同的象征性图案和元素。以下是基于纹章设计规则的详细分析:


      1. 中央盾徽

      • 主体设计:
      • 盾徽由多个元素组合而成,每个部分都有特定的象征意义。

      (1) 蓝底百合花与玫瑰花

      • 百合花(Fleur-de-Lys):通常象征与法国的联系,或表示纯洁与高贵。
      • 中心的白玫瑰:可能与英格兰的约克家族有关,因为白玫瑰是约克家族的象征。

      (2) 红十字

      • 红色十字通常象征圣乔治十字(St. George's Cross),代表英格兰或基督教信仰的守护。

      (3) 黑色鸟与鱼

      • 鸟(盾徽左下角):黑色鸟可能是乌鸦或渡鸦,象征智慧、守护或与特定地方的历史关联。
      • 鱼(盾徽下方中心):鱼可能象征丰饶、信仰或与水域有关的历史,比如河流或港口城市。

      2. 头盔与饰冠

      • 头盔(Helmet):在盾徽上方的头盔是骑士或贵族纹章的常见元素,象征家族或机构的荣耀与战斗精神。
      • 饰冠(Crest)
      • 头盔上饰有一簇羽毛或树枝状图案,可能象征繁荣、和平或勇气。

      3. 两侧的支撑者

      • 纹章两侧有两只鸟,作为盾徽的支撑者(Supporters)。支撑者在纹章学中通常具有特定象征意义,代表历史、地理或文化特性。
      • 左侧的黑鸟:可能是乌鸦或渡鸦,通常象征智慧或死亡,也可能与特定历史事件或地名相关。
      • 右侧的浅色鸟:可能是夜莺(Nightingale),象征诗意、歌声和艺术。

      4. 颜色与象征意义

      • 颜色在纹章中也有特殊的含义:
      • 蓝色:忠诚、真理。
      • 红色:勇气、牺牲。
      • 金色/黄色:高贵、慷慨。
      • 黑色:坚定、悲伤或智慧。

      5. 纹章的用途

      • 这样的纹章可能属于以下类别之一:
      • 家族纹章:代表某个贵族家族,显示其荣耀、血统和历史成就。
      • 城市或机构徽章:如果与城市相关,可能是一个有历史意义的地方,如河流、港口或重要的文化象征。
      • 宗教关联:某些元素(如圣乔治十字)表明它可能与宗教机构或历史上的圣徒有关。

      6. 可能的历史背景

      • 纹章学中,类似的设计常见于欧洲,特别是英国、法国等国,用于家族、城市或教会的象征。
      • 具体含义可能与当地历史或文化相关,例如河流、重要的鸟类或宗教象征。

      总结

      这幅纹章通过多样的图案和元素,结合了百合花、圣乔治十字、鸟类和鱼,展示了某个家族、城市或机构的丰富历史和象征意义。具体背景和象征需要结合所属地区或家族的具体历史才能完全解读。如果您能提供更多信息,比如这幅纹章的来源或所属机构,我可以进一步为您分析和解释其独特意义!

    1. Reviewer #3 (Public review):

      Summary:

      The report by Shin, Lee, Kim, and Lee entitled "Progressive overfilling of readily releasable pool underlies short-term facilitation at recurrent excitatory synapses in layer 2/3 of the rat prefrontal cortex" describes electrophysiological experiments of short-term synaptic plasticity during repetitive presynaptic stimulation at synapses between layer 2/3 pyramidal neurons and nearby target neurons. Manipulations include pharmacological inhibition of PLC and actin polymerization, activation of DAG receptors, and shRNA knockdown of Syt7. The results are interpreted as support for the hypothesis that synaptic vesicle release sites are vacant most of the time at resting synapses (i.e., p_occ is low) and that facilitation (and augmentation) components of short-term enhancement are caused by an increase in occupancy, presumably because of acceleration of the transition from not-occupied to occupied. The report additionally describes behavioural experiments where trace fear conditioning is degraded by knocking down syt7 in the same synapses.

      Strengths:

      The strength of the study is in the new information about short-term plasticity at local synapses in layer 2/3, and the major disruption of a memory task after eliminating short-term enhancement at only 15% of excitatory synapses in a single layer of a small brain region. The local synapses in layer 2/3 were previously difficult to study, but the authors have overcome a number of challenges by combining channel rhodopsins with in vitro electroporation, which is an impressive technical advance.

      Weaknesses:

      The question of whether or not short-term enhancement causes an increase in p_occ (i.e., "readily releasable pool overfilling") is important because it cuts to the heart of the ongoing debate about how to model short term synaptic plasticity in general. However, my opinion is that, in their current form, the results do not constitute strong support for an increase in p_occ, even though this is presented as the main conclusion. Instead, there are at least two alternative explanations for the results that both seem more likely. Neither alternative is acknowledged in the present version of the report.

      The evidence presented to support overfilling is essentially two-fold. The first is strong paired pulse depression of synaptic strength when the interval between action potentials is 20 or 25 ms, but not when the interval is 50 ms. Subsequent stimuli at frequencies between 5 and 40 Hz then drive enhancement. The second is the observation that a slow component of recovery from depression after trains of action potentials is unveiled after eliminating enhancement by knocking down syt7. Of the two, the second is predicted by essentially all models where enhancement mechanisms operate independently of release site depletion - i.e., transient increases in p_occ, p_v, or even N - so isn't the sort of support that would distinguish the hypothesis from alternatives (Garcia-Perez and Wesseling, 2008, https://doi.org/10.1152/jn.01348.2007).

      Regarding the paired pulse depression: The authors ascribe this to depletion of a homogeneous population of release sites, all with similar p_v. However, the details fit better with the alternative hypothesis that the depression is instead caused by quickly reversing inactivation of Ca2+ channels near release sites, as proposed by Dobrunz and Stevens to explain a similar phenomenon at a different type of synapse (1997, PNAS,<br /> https://doi.org/10.1073/pnas.94.26.14843). The details that fit better with Ca2+ channel inactivation include the combination of the sigmoid time course of the recovery from depression (plotted backwards in Fig1G,I) and observations that EGTA (Fig2B) increases the paired-pulse depression seen after 25 ms intervals. That is, the authors ascribe the sigmoid recovery to a delay in the activation of the facilitation mechanism, but the increased paired pulse depression after loading EGTA indicates, instead, that the facilitation mechanism has already caused p_r to double within the first 25 ms (relative to the value if the facilitation mechanism was not active). Meanwhile, Ca2+ channel inactivation would be expected to cause a sigmoidal recovery of synaptic strength because of the sigmoidal relationship between Ca2+-influx and exocytosis (Dodge and Rahamimoff, 1967, https://doi.org/10.1113/jphysiol.1967.sp008367).

      The Ca2+-channel inactivation hypothesis could probably be ruled in or out with experiments analogous to the 1997 Dobrunz study, except after lowering extracellular Ca2+ to the point where synaptic transmission failures are frequent. However, a possible complication might be a large increase in facilitation in low Ca2+ (Fig2B of Stevens and Wesseling, 1999, https://doi.org/10.1016/s0896-6273(00)80685-6).

      On the other hand, even if the paired pulse depression is caused by depletion of release sites rather than Ca2+-channel inactivation, there does not seem to be any support for the critical assumption that all of the release sites have similar p_v. And indeed, there seems to be substantial emerging evidence from other studies for multiple types of release sites with 5 to 20-fold differences in p_v at a wide variety of synapse types (Maschi and Klyachko, eLife, 2020, https://doi.org/10.7554/elife.55210; Rodriguez Gotor et al, eLife, 2024, https://doi.org/10.7554/elife.88212 and refs. therein). If so, the paired pulse depression could be caused by depletion of release sites with high p_v, whereas the facilitation could occur at sites with much lower p_v that are still occupied. It might be possible to address this by eliminating assumptions about the distribution of p_v across release sites from the variance-mean analysis, but this seems difficult; simply showing how a few selected distributions wouldn't work - such as in standard multiple probability fluctuation analyses - wouldn't add much.

      In any case, the large increase - often 10-fold or more - in enhancement seen after lowering Ca2+ below 0.25 mM at a broad range of synapses and neuro-muscular junctions noted above is a potent reason to be cautious about the LS/TS model. There is morphological evidence that the transitions from a loose to tight docking state (LS to TS) occur, and even that the timing is accelerated by activity. However, 10-fold enhancement would imply that at least 90 % of vesicles start off in the LS state, and this has not been reported. In addition, my understanding is that the reverse transition (TS to LS) is thought to occur within 10s of ms of the action potential, which is 10-fold too fast to account for the reversal of facilitation seen at the same synapses (Kusick et al, 2020, https://doi.org/10.1038/s41593-020-00716-1).

      Individual points:

      (1) An additional problem with the overfilling hypothesis is that syt7 knockdown increases the estimate of p_occ extracted from the variance-mean analysis, which would imply a faster transition from unoccupied to occupied, and would consequently predict faster recovery from depression. However, recovery from depression seen in experiments was slower, not faster. Meanwhile, the apparent decrease in the estimate of N extracted from the mean-variance analysis is not anticipated by the authors' model, but fits well with alternatives where p_v varies extensively among release sites because release sites with low p_v would essentially be silent in the absence of facilitation.

      (2) Figure S4A: I like the TTX part of this control, but the 4-AP part needs a positive control to be meaningful (e.g., absence of TTX).

      (3) Line 251: At least some of the previous studies that concluded these drugs affect vesicle dynamics used logic that was based on some of the same assumptions that are problematic for the present study, so the reasoning is a bit circular.

      (4) Line 329 and Line 461: A similar problem with circularity for interpreting earlier syt7 studies.

    1. Author response:

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      In this study, the authors explore a novel mechanism linking aging to chromosome mis-segregation and aneuploidy in yeast cells. They reveal that, in old yeast mother cells, chromosome loss occurs through asymmetric partitioning of chromosomes to daughter cells, a process coupled with the inheritance of an old Spindle Pole Body. Remarkably, the authors identify that remodeling of the nuclear pore complex (NPC), specifically the displacement of its nuclear basket, triggers these asymmetric segregation events. This disruption also leads to the leakage of unspliced pre-mRNAs into the cytoplasm, highlighting a breakdown in RNA quality control. Through genetic manipulation, the study demonstrates that removing introns from key chromosome segregation genes is sufficient to prevent chromosome loss in aged cells. Moreover, promoting pre-mRNA leakage in young cells mimics the chromosome mis-segregation observed in old cells, providing further evidence for the critical role of nuclear envelope integrity and RNA processing in aging-related genome instability.

      Strengths:

      The findings presented are not only intriguing but also well-supported by robust experimental data, highlighting a previously unrecognized connection between nuclear envelope integrity, RNA processing, and genome stability in aging cells, deepening our understanding of the molecular basis of chromosome loss in aging.

      We thank the reviewer for this very positive assessment of our work

      Weaknesses:

      Further analysis of yeast aging data from microfluidic experiments will provide important information about the dynamic features and prevalence of the key aging phenotypes, e.g. pre-mRNA leakage and chromosome loss, reported in this work.

      We thank the reviewer for bringing this point, which we will address indeed in the revised version of the manuscript.  In short, chromosome loss is an abrupt, late event in the lifespan of the cells.  Its prevalence is more complex to assess and will require correlated loss rate of several chromosomes concomitantly. The prevalence of the pre-mRNA leakage phenotype is easier to assess and we will provide data about this in the revised manuscript as well.  Our data show that the prevalence is quite high (well above 50%), even if not every cell is affected.

      In addition, a discussion would be needed to clarify the relationship between "chromosome loss" in this study and "genomic missegregation" reported previously in yeast aging.

      The genomic missegregation mentioned by the reviewer is a process distinct from the chromosome loss that we report.  Genomic missegregation is characterized by the entry of both SPBs and all the chromosomes into the daughter cell compartment (PMID: 31714209).  We do observed these events in our movies as well.  In contrast, the chromosome loss phenotype is takes place under proper elongation of the spindle and proper segregation of the two SPBs between mother and bud, as shown in figure 2 of the manuscript.  In our movies, chromosome loss is at least three fold more frequent (for a single chromosome) than full genome missegregation.  Furthermore, whereas chromosome loss is alleviated by the removal of the introns of MCM21, NBL1 and GLC7, genomic missegregation is not.

      Nevertheless, we thank the reviewer for bringing up the possible confusion between the two phenotypes.  We will explain and illustrate the difference between the two processes in the revised manuscript.

      Reviewer #2 (Public review):

      Summary:

      The authors make the interesting discovery of increased chromosome non-dysjunction in aging yeast mother cells. The phenotype is quite striking and well supported with solid experimental evidence. This is quite significant to a haploid cell (as used here) - loss of an essential chromosome leads to death soon thereafter. The authors then work to tie this phenotype to other age-associated phenotypes that have been previously characterized: accumulation of extrachromosomal rDNA circles that then correlate with compromised nuclear pore export functions, which correlates with "leaky" pores that permit unspliced mRNA messages to be inappropriately exported to the cytoplasm. They then infer that three intron containing mRNAs that encode portions in resolving sister chromatid separation during mitosis, are unspliced in this age-associated defect and thus lead to the non-dysjunction problem.

      Strengths: The discovery of age-associated chromosome non-dysjunction is an interesting discovery, and it is demonstrated in a convincing fashion with "classic" microscopy-based single cell fluorescent chromosome assays that are appropriate and seem robust. The correlation of this phenotype with other age-associated phenotypes - specifically extrachromosomal rDNA circles and nuclear pore dysfunction - is supported by in vivo genetic manipulations that have been well-characterized in the past.

      In addition, the application of the single cell mRNA splicing defect reporter showed very convincingly that general mRNA splicing is compromised in aged cells. Such a pleiotropic event certainly has big implications.

      We thank the reviewer for this assessment of our work.  To avoid confusion, we would like to stress out, however, that our data do not show that splicing per se is defective in old cells.  We only show that unspliced mRNAs tend to leak out of the nucleus of old cells.

      Weaknesses:

      The biggest weakness is "connecting all the dots" of causality and linking the splicing defect to chromosome disjunction. I commend the authors for making a valiant effort in this regard, but there are many caveats to this interpretation. While the "triple intron" removal suppressed the non-dysjunction defect in aged cells, this could simply be a kinetic fix, where a slowdown in the relevant aspects of mitosis, could give the cell time to resolve the syntelic attachment of the chromatids.

      The possibility that intron-removal leads to a kinetic fix is an interesting idea that we will address in the revised manuscript.  So far we have no observed that removing these introns slows down mitosis but we will test the idea by doing precise measurements.

      To this point, I note that the intron-less version of GLC7, which affects the most dramatic suppression of the three genes, is reported by one of the authors to have a slow growth rate (Parenteau et al, 2008 - https://doi.org/10.1091/mbc.e07-12-1254)

      The reviewer is right, removing the intron of GLC7 reduces the expression levels of the gene product (PMID: 16816425) to about 50% of the original value and causes a slow growth phenotype.  However, the cells revert fairly rapidly through duplication of the GLC7 gene.  As a consequence, neither the GLC7-∆i nor the 3x∆i mutant strains show noticeable growth phenotypes by spot assays.  We will document these findings and provide a measurement of the growth rate of the mutant strain in the revised manuscript. 

      In addition, the lifespan curve containing the 3∆i in Figure 5E has a very unusual shape, suggesting a growth problem/"sickness" in this strain.

      To be accurate the strain plotted in Figure 5E is not the 3x∆i triple mutant strain but the 3x∆i mlp1∆  quadruple mutant strain.  The 3x∆i triple mutant strain is plotted in Figure 4D and its shape is similar to that of the wild type cells.  The strain in Figure 5E is indeed sick ,due to the removal of the nuclear basket. However, the 3x∆i mutations partially rescue the replicative lifespan shortening due the mlp1∆ mutation (see text).  Illustrating the fact that the 3x∆i mutant strain is not particularly sick, it shows a prolonged lifespan and a fairly standard aging curve.

      Lastly, the Herculean effort to perform FISH of the introns in the cytoplasm is quite literally at the statistical limit of this assay. The data were not as robust as the other assays employed through this study. The data show either "no" signal for the young cells or a signal of 0, 1,or 2 FISH foci in the aged cells. In a Poisson distribution, which this follows, it is improbable to distinguish between these differences.

      This is correct, this experiment was not the easiest of the manuscript... However, despite the limitations of the assay, the data presented in figure 6B are quite clear.  300 cells aged by MEP were analysed, divided in the cohorts of 100 each, and the distribution of foci (nuclear vs cytoplasmic) in these aged cells were compared to the distribution in three cohorts of young cells.  For all 3 aged cohorts, over 70% of the visible foci were cytoplasmic, while in the young cells, this figure was around 3%.  A t-test was conducted to compare these frequencies between young and old cells (Figure 6B).  The difference is highly significant.  The reviewer refers to the supplementary Figure 4, where we were simply asking i) is the signal lost in cells lacking the intron of GLC7 (the response is unambiguously yes) and ii) what is the general number of dots per cells between young and old wild type cells (without distinguishing between nuclear and cytoplasmic) and the information to be taken from this last quantification is indeed that there is no clearly distinguishable difference between these two population of cells.  In other word, the reason why there are more dots in the cytoplasm of the old cells in the Figure 6B is not because the old cells have much more dots in general.  We hope that these clarifications help understand the data better.  We will make sure that this is clearer in the revised manuscript.

      Reviewer #3 (Public review):

      Summary:

      Mirkovic et al explore the cause underlying development of aneuploidy during aging. This paper provides a compelling insight into the basis of chromosome missegregation in aged cells, tying this phenomenon to the established Nuclear Pore Complex architecture remodeling that occurs with aging across a large span of diverse organisms. The authors first establish that aged mother cells exhibit aberrant error correction during mitosis. As extrachromosomal rDNA circles (ERCs) are known to increase with age and lead to NPC dysfunction that can result in leakage of unspliced pre-mRNAs, Mirkovic et al search for intron-containing genes in yeast that may be underlying chromosome missegregation, identifying three genes in the aurora B-dependent error correction pathway: MCM21, NBL1, and GLC7. Interestingly, intron-less mutants in these genes suppress chromosome loss in aged cells, with a significant impact observed when all three introns were deleted (3x∆i). The 3x∆i mutant also suppresses the increased chromosome loss resulting from nuclear basket destabilization in a mlp1∆ mutant. The authors then directly test if aged cells do exhibit aberrant mRNA export, using RNA FISH to identify that old cells indeed leak intron-containing pre-mRNA into the cytoplasm, as well as a reporter assay to demonstrate translation of leaked pre-mRNA, and that this is suppressed in cells producing less ERCs. Mutants causing increased pre-mRNA leakage are sufficient to induce chromosome missegregation, which is suppressed by the 3x∆i.

      Strengths:

      The finding that deleting the introns of 3 genes in the Aurora B pathway can suppress age-related chromosome missegregation is highly compelling. Additionally, the rationale behind the various experiments in this paper is well-reasoned and clearly explained.

      We thank the reviewer for their very positive assessment of our work

      Weaknesses:

      In some cases, controls for experiments were not presented or were depicted in other figures.

      We are sorry about this confusion.  We will improve our presentation of the controls, make sure that they are brought back again each time they are relevant (we wanted to limit the cases of replotting the same controls several times).  We will also add those that are missing (such as those mentioned by reviewer 2, see above)

      High variability was seen in chromosome loss data, leading to large error bars.

      We thank the reviewer for this comment. The variance in those two figures (3A and 5D) comes from the suboptimal plotting of this data. This will be corrected in the revised version of the manuscript. 

      The text could have been more polished.

      Thank you for this comment.  We will go through the manuscript again in details

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      Reply to the reviewers

      Response to Reviewers

      We thank the reviewers for their fair and thorough review. With regards to the reviewers’ comments, both largely focused on something that is a misunderstanding. For unclear reasons, both reviewers thought that most of the data shown was in pregnant or previously pregnant mice and both requested a significant amount of preliminary data regarding virgin mice (R1 comment #3, #4, R2 comment #1). This may be due to a (now-corrected) typo in the results section despite the methods section being correct, or the very few instances of pregnant mice being used for analyses that led to confusion. As mentioned below, the entire manuscript evaluates virgin mice, with a few specific exceptions, so the preliminary revisions have emphasized the parity status of the mice used in every experiment. We regret this misunderstanding happened and we are concerned this may have led to reviews that were biased towards a negative viewpoint. We hope the completed preliminary revisions (indicated in red text in the manuscript) and the planned revisions will, combined, satisfy the reviewer’s concerns and clarify points of confusion, while leading to a greatly improved manuscript.


      Reviewer 1:

      Major points

      1. Major Comment 1: “Several of the conclusions are made based on a limited number of replicates (often n=3) which is not a robust sample size to make a rigorous conclusion.”

      We have consulted with a biostatistician (Adam Lane, now included in acknowledgements) and plan to add at least 3 more mice per group to bring the total sample size to 6-7. Given our results are already statistically significant with an n=3-4, we do not anticipate any changes in the overall results of our data. We have already collected at least 3 more age-matched and parity-matched mice per group for the molecular analyses and are working on performing the immunohistochemical stains, western blots, etc.


      Major Comment 2: The main text for Figure 1C mentions repression of luciferase expression by doxycycline chow, however the figure does not show any discernable repression in the Dek-OE conditions.

      We believe the reviewer may have mis-interpreted the figure. The mouse on the far left (“control”) with no luciferase signal is the dox chow-repressed condition. We have revised the figure label to specify that “Control” is the “+dox condition” and throughout the manuscript have specified “+dox controls” instead of just “controls.”


      Major Comments 3: To evaluate the impact of prolonged Dek overexpression on mammary epithelium in Figure 1G and 1H, the authors used multiparous females. One confounding factor with this experimental set up is the impact of previous pregnancies on the development of the mammary epithelium and in lowering tumorigenesis. Therefore, the impact of Dek on tumorigenesis cannot be determined in multiparous animals alone. To get a full picture, nulliparous animals should also be examined.

      __We have revised the text on page 6 to explain that we have monitored tumor growth in both aged virgins and in multiparous mice (our female breeders) and neither group develops tumors. __

      Major Comment 4: “To elucidate the molecular underpinning of Dek-OE phenotypes, the authors performed bulk RNA sequencing in Figure 2. Similar to point 2 however, only multiparous animals were used. As it has been previously shown that pregnancy significantly impacts the transcriptome of mammary glands, the effects of Dek overexpression can't be generalized to mammary glands as a whole. To make it generalizable, nulliparous Dek-OE animals must also be characterized.”

      As mentioned in the introduction to the review, the reviewer has misunderstood the experimental design, perhaps through a single typo in the Results section when the Methods were correct, or through poor writing on our behalf. Regardless, the RNA-Seq, whole mounts, and all subsequent molecular validations were conducted on virgin mice. The only exceptions are in Figure 4, where we do explore the expression of endogenous Dek during pregnancy and the impact of pregnancy in the transgenic model. We have revised the typographical error, confirmed the parity status of all mice in the study to date, and have specifically added the parity status to each experiment in Results section and/or Figure Legend.


      Major Comment 5: To validate findings from their transcriptomics work, the authors used IHC and western blots of candidate proteins that were found to be down regulated. In Figure 3A and 3C, the decrease in p21 protein levels through western blot seem much more modest than what the decrease seen in 3A would suggest.

      We thank the reviewer for pointing this out. With increased sample sizes, as requested, we hope this will resolve. We plan to increase sample size and quantify the p21 western blot to potentially resolve the concern. In addition, we would like to note that the p21 IHC is specific for mammary epithelium signal while the western blot is whole mammary gland lysate that includes quiescent stromal cells, which may explain the slight discrepancy between the two methods.

      Major Comment 6: In Figure 3G-3I, the authors test the CDK4/6 inhibitor palbociclib to establish a direct link between the phenotypes seem in Dek-OE and cell cycle progression in organoid culture. Have the authors verified these findings with treatment of Dek-OE mice with palbociclib? In addition, have the authors checked to see if palbociclib corrected any of the transcriptional features associated with the Dek-OE model found in their transcriptomics data? In addition, the authors claim that the effect is specific to Dek-OE organoids as the effects of palbociclib on growth are not seen in control organoids. However, the data on unperturbed growth of control cells are not seen. To determine the specificity of the effects of palbociclib on Dek-OE derived organoids, the authors must show a time course tracking the growth of organoids with and without palbociclib. Rather than conclude the effects of palbociclib being specific to Dek-OE organoids, the authors most likely wanted to conclude that the increased growth of Dek-OE organoids compared to control organoids is dependent on the increase in cell cycle factors. (The validity of this is also weird though because even if division and growth were triggered through other transcriptional changes they found, like increased metabolism, growth in that scenario would be stopped by palbo as well)

      1. Because the hyperplasia phenotype accumulates over the lifetime of the animal, the amount of treatment time required to abrogate the hyperplasia phenotype could be from days to weeks to months. For this reason, we believe it is outside the scope of this revision to test the effects of palbociclib in vivo.
      2. We plan to re-do this experiment with palbociclib treatment to test organoid growth over time as suggested and, time permitting, perform immunofluorescence for some of the transcription targets such as cyclins, CDKs, Ki67, and p27/p21
      3. We have revised the text on page 8 to say “____We observed that the increased growth of Dek over-expressing organoids was dependent on the Dek-induced increase in CDK4/6, since palbociclib treatment resulted in smaller Dek over-expressing organoids that were comparable to organoids from +dox controls.” We also agree that CDK inhibitor treatment may impact multiple downstream signaling pathways. However, the authors do not see this as a negative because cell proliferation, induced by cyclin/CDK complexes, requires metabolic regulation to support physical growth of the cell. The two processes are intricately integrated and have a bidirectional relationship. Thus, it is possible that DEK induces both processes, or it may only promote one process (i.e.: cell cycle) and the other one (i.e.: metabolism) is induced as a secondary result of cell cycle demands. This is one reason why we indicate that metabolic dysregulation should be further studied in the Discussion section. Indeed, a colleague in the DEK field (Susanne Wells) is already working on the relationship between DEK over-expression and metabolic dysfunction, thus this particular aspect of the request is outside the scope of this manuscript.

      Major Comment 7: In the main text of Figure 4, the authors conclude that markers for luminal hormone sensing cells were unchanged in Dek-OE mammary glands, however the data to show this is not shown. This is problematic because the authors are directly drawing the conclusion that Dek-OE specifically upregulates luminal alveolar markers using this data.

      We have revised the manuscript to include a new supplementary figure (now Fig S4) to include a western blot for HER2 and ERa and a summary of RNA expression data from the bulk RNA-Seq experiment. We will also perform additional western blots to increase the sample size to demonstrate this negative data as part of our planned


      Major comment 8: In figure 7, the authors look at a conditional knockout of Dek and conclude that pup death in the knockout was due to insufficient milk production by dams. While the authors establish that H3K27me3 and Ezh2 expression are abrogated, morphological analysis of the ducts is missing and would present convincing data. For instance, in the Dek conditional knockout, are luminal alveolar cells unable to differentiate fully, or are there far fewer? Decreased levels of histone modifications does not tell you much about whether repressive chromatin has changed its landscape in Dek KO mice, which is actually what influences transcription.

      __We plan to add histological and whole mount imaging of Dek knockout mammary glands in the revision. We have preliminary data that supports this from 2 mice and will be collecting more samples for the revision. However, as noted in Fig 7C-D, heterozygous females also have small litter sizes and this will pose a breeding challenge for generating knockout females for this experiment in a timely manner. __

      Minor Points:

      All figures need some sort of reformatting. Several of the conclusions are made based on a limited number of replicates (often n=3) which is not a robust sample size to make a rigorous conclusion. Many figures have text that is stretched. Histology and whole mount images are missing scale bar. IHC quantifications are obscure - what is an optical density? how many animals were analyzed and how many fields of vision were captured? Figure 2F is absolutely impossible to understand. Neither figures nor legends disclose the number of animals or samples analyzed. The statistical test utilized across all figures is not appropriated. Fig5B GSEA plots are missing statistical significance, and without this information one cannot properly access the relevance of the findings. Fig5C - how were co-expressed genes defined? is this just random genes that are expressed in cells that have higher levels of DEK? The term co-expressed suggests a specific type of analysis that would investigate linkage of expression between genes, which i dont think is the case here.

      __As the reviewer already mentioned in major comment #1, there was a concern with sample size, which we addressed above in the planned revisions. We believe this concern about sample size was the rationale for the minor comment about “The statistical test utilized across all figures is not appropriate.” We have consulted with a biostatistician, Adam Lane PhD, who has confirmed that our statistical approaches were correct but were limited by our sample size. Thus, we do not agree with the reviewer’s view of statistical analyses. We have revised the text to include sample size information in figure legends and statistical significance information for GSEA plots in Fig 5, With regards to figure text being stretched, it does not look like that in our version of the document and reviewer 2 did not comment on this, so we would like the reviewer to identify a specific instance of this. We plan to capture images with size bars for IHC while we are performing the additional sample size collection. The reviewer asked about the number of fields of view for IHC quantification and we would like to note that our methods section already had that information in the first submission, “at least 3 fields of view from at least 3 different mice per group.” Our methods section also already had information regarding the identification of co-expressed genes in scRNA-Seq data and quantifying IHC with Image J. However, we have revised the text to add some clarifying sentences that we hope helps the reviewer better understand our methods. Finally, we are not sure what is “absolutely impossible to understand” about Fig 2F, which is a network visualization of functional enrichment analyses for differentially expressed genes in our RNA-Seq data. Is the text too small, or does the reviewer not understand the network? We would appreciate it if the reviewer could clarify this concern in their next review. __


      Minor Point 1: Throughout, it would be better to indicate the genotype of the "Control" animals on each figure so as the rigor the experiment can be evaluated fully.

      It appears that the reviewer was not aware that all controls were the same genotype and were the bitransgenic mice on dox chow. We have revised the manuscript to better clarify that “controls” = “+dox chow” bitransgenics and have added text on page 5 to directly state this. We have also revised Fig 1C to specify that the mouse with no luciferase signal is the “+dox” control.


      Minor Point 2: Standard nomenclature for gene names and protein names should be corrected throughout the text.

      __We have revised the text to confirm gene and protein names are correct. We have followed convention in using italics for gene names, non-italics for protein names, all capital letters for human genes/proteins (i.e.: DEK) and only first letter capitalization for non-human gene names (i.e.: Dek). __


      Minor Point 3: Similar to the point above, the use of Dek-OE to either refer to the mouse model or function as an acronym for "Dek overexpression" is inconsistent throughout the text.

      We thank the reviewer for pointing out this inconsistency and we have revised the text so that the “-OE” notation is only used when discussing the mice and have changed to writing out “over-expression” for function.


      Minor Point 4: In the main text for Figure 4I-J, the authors state that DEK was previously published as an Erα target gene, however there is no citation to support this.

      We have revised the text to include this citation, which is:

      16. Privette Vinnedge, L.M., et al., The DEK Oncogene Is a Target of Steroid Hormone Receptor Signaling in Breast Cancer. PLoS One, 2012. 7(10): p. e46985.

      Minor Point 5: It is unclear what the conclusion drawn from the experiments shown in Figure 4G-H and Figure 4I-J mean with respect to the goal of Figure 4, which was to show that Dek-OE mice have an expanded luminal alveolar compartment.

      We have revised the text to better explain that we were investigating the impact of ovarian hormones and pregnancy on endogenous Dek expression in wild-type mice, since this information has not been previously reported and adds context to our study.


      Minor Point 6: Optical density was used to quantify IHC experiments, which was performed using color deconvolution in ImageJ. Something that is unclear is whether the authors are measuring density in the entire field of view, or if the authors are measuring optical density per cell. This has implications whether there are more cell expressing the protein of interest, or if the existing cells are expressing a higher level of the protein of interest.

      We have revised the text to include more information in the methods. The Methods now states: “____Image J color deconvolution was utilized to measure the staining intensity only within mammary epithelial cells from at least 3 fields of view from at least 3 different mice per group. Specifically, cross-sections of similarly sized ducts were outlined such that only the collective epithelial cells within that cross section were measured, removing background signal from the stromal cells. Only single cross-sections of ducts were analyzed to minimize the impact of epithelial hyperplasia in experimental mice compared to controls fed dox chow.”


      Minor Point 7: In the main text for Figure 6D, the system being used to overexpress DEK protein is not described. It is not the same genetic system as is used in the Dek-OE mice, as doxycycline is inducing Dek expression.

      We have revised the figure 6 legend to specify “____DEK over-expression was accomplished with a dox-inducible pTRIPZ vector while DEK knockdown was accomplished with a pLKO.1 shRNA vector” and we kindly point the reviewer to the Methods section (“human cell lines” subsection) as written in the first submission which included detailed information for the subcloning of DEK cDNA into the pTRIPZ vector.


      Reviewer 2

      _All comments_

      1. Comment 1: This study would be improved by sharing important data including virgin mammary gland development in the DEK-OE and DEK-KO models (ductal growth and branching) and the expression of markers including ESR1, PGR, and ERBB2 (data not shown, page 8). Although there may be no differences, this is important data to share regarding the goal of this study. For example, in the DEK-OE model, data are only evaluated in the aged/multiparous stage and in the DEK-KO model, data are only evaluated during lactation. Furthermore, the DEK-KO model resembles germline DEK loss (under control of the CMV promoter), and there is limited validation of a MEC-intrinsic function.

      We have revised the manuscript to include data on Esr1/ERa and Erbb2/Her2 by western blot in new Fig S4 as well as the bulk RNA-Seq mRNA levels (by FPKM) for select basal and hormone sensing cell populations. The concern regarding parity was also mentioned by Reviewer 1 (major comments 3&4 above). Briefly we have clarified that ____nearly all data in the manuscript is from nulliparous (virgin) females and have revised the text throughout to more clearly state this fact. We have also revised the text to address the limitation of the CMV promoter. The Discussion section now states “____However, it is noted that one weakness of this CMV-Cre knockout model, is that there is a constitutive loss of Dek, which limits the interpretation for mammary epithelial cell-specific Dek functions.”

      Comment 2: Another major concern with this manuscript is the use of immunohistochemistry (IHC) and bulk mammary gland lysate western blots. IHC is non-quantitative, and the images are low resolution. For example, using IHC DEK expression is observed in all MECs (control and DEK-OE mice, Figure 1F), however, in the scRNAseq data DEK expression is confined to basal cells and a subset of stem/progenitor cells (Figure 5A). Furthermore, the hyperplasia in the DEK-OE model will bias bulk analysis (such as western blot and RNAseq) towards increased expression of MEC markers.

      1. __We have revised the text to point out that IHC images for Dek in control tissues show some cells have higher expression than others, which is what would be predicted by scRNA-Seq. The text now states on page 16 “____The scRNA-Seq data suggests that Dek is more highly expressed in specific subpopulations of cells, and the variable intensity of immunohistochemical staining for Dek in epithelial cells within control mouse tissue supports this (see Fig 3I, 4I, 4K, and 7H).” Furthermore, on page 10 in the Result section we have revised the text to state “The mammary gland undergoes substantial hormone-induced remodeling across the murine lifespan. We show that Dek is highest during pregnancy and minimally expressed during lactation and involution (Fig 4K), and that Dek protein expression is not uniform across all epithelial cells in wild-type glands (Fig 3I, 4I-K). This suggests that certain epithelial subpopulations express more Dek than others.” __
      2. __We acknowledge that IHC and western blots are only semi-quantitative, which is why we attempt to perform both as orthogonal approaches or find additional ways to support our findings throughout the manuscript (i.e.: co-expression at the RNA level from other sources, small molecule inhibitor treatment, etc). We also note that these methods are used to validate the quantitative method of RNA-Seq, and (often) validation of differentially expressed genes can be limited by antibody availability and the applications those antibodies are suitable for. __
      3. We also have revised the text to acknowledge that we knew the bulk RNA-Seq would be biased towards the hyperplastic cells. We wanted to take advantage of that bias to identify a gene signature that could be used to determine which cell type was leading to the hyperplasia phenotype. We used the differentially expressed genes to identify biomarkers for specific cell populations. On pages 6-7 the text now reads “____We performed bulk RNA sequencing on whole mammary tissue from two +dox control and two Dek-OE adult virgin females at 15 months of age to discover molecular targets regulated by Dek over-expression and to reveal a gene signature that could help identify the expanded cell population(s) in hyperplastic glands.” And “DEGs were plotted as a heatmap and ontologies for biomarkers of cell populations were defined to help identify the expanded cell population driving Dek-induced hyperplasia.”

      Comment 3: A third major concern is the mechanistic link between DEK and H3K27me3. Most of the data are correlative and rely on bulk analysis or IHC. For example, in the DEK-OE organoid model, is there an increase in H3K27me3. Additionally, in the DEK-OE organoids, can loss of EZH2 block the increased cell proliferation?

      __We plan to revise the manuscript to include an experiment in which we treat primary mammary epithelial cell organoids from Dek-OE mice with EZH2 inhibitor, GSK-126, +/- doxycycline for a mechanistic or functional link between DEK and H3K27me3 levels. We will then determine organoid size and attempt molecular characterization with IF. This will support the biochemical studies in Fig 6 showing DEK interacts with the PRC2 complex. __


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      Referee #1

      Evidence, reproducibility and clarity

      Johnstone & Leck et al. report their findings on the DEK chromatin remodeler and its newly discovered role in the development of the mammary gland through the use of a mammary epithelium-specific Dek overexpression model (Dek-OE). Using immunohistochemistry (IHC) and whole mounts of mammary glands, they show that the Dek-OE model is characterized by epithelial hyperplasia in multiparous, 15-month-old females. Through performing and analyzing bulk RNA sequencing of whole mammary tissue, they find that overexpression of Dek is correlated with cell cycle entry and progression, and the expression of luminal alveolar and mammary progenitor genes. The deregulation of cell cycle inhibitors was confirmed through IHC and western blot. To further support the connection between Dek and the cell cycle, it was also shown that palbociclib treatment of mammary epithelial organoids derived from Dek-OE mice was able to rescue the hyperplastic phenotype. To validate their transcriptomic findings of increased expression of luminal progenitor genes, IHC and western blots for alveolar markers and milk proteins were performed. By performing ovariectomy and looking at DEK expression throughout the development of the mammary gland, it was also found that Dek expression was promoted by ovarian hormones. Analysis of single-cell data from a previously published single cell gene atlas of the mammary gland, the authors found that Dek expression heavily overlapped with mammary stem cells and luminal progenitor populations, and was heavily correlated with expression of PRC2 components. Using western blots and a GFP-trap assay, it was found that Dek overexpression leads to increased H3K27me3, and PRC2 components directly interact with DEK. Using a conditional knockout of Dek, the authors found that Dek loss leads to decreased expression of PRC2 components in mammary epithelial cells by IHC and a failure for dams to lactate efficiently. While the authors findings are novel, there are major points that need to be strengthened and elaborated for clarity.

      Major points:

      1. Several of the conclusions are made based on a limited number of replicates (often n=3) which is not a robust sample size to make a rigorous conclusion.
      2. The main text for Figure 1C mentions repression of luciferase expression by doxycycline chow, however the figure does not show any discernable repression in the Dek-OE conditions.
      3. To evaluate the impact of prolonged Dek overexpression on mammary epithelium in Figure 1G and 1H, the authors used multiparous females. One confounding factor with this experimental set up is the impact of previous pregnancies on the development of the mammary epithelium and in lowering tumorigenesis. Therefore, the impact of Dek on tumorigenesis cannot be determined in multiparous animals alone. To get a full picture, nulliparous animals should also be examined.
      4. To elucidate the molecular underpinning of Dek-OE phenotypes, the authors performed bulk RNA sequencing in Figure 2. Similar to point 2 however, only multiparous animals were used. As it has been previously shown that pregnancy significantly impacts the transcriptome of mammary glands, the effects of Dek overexpression can't be generalized to mammary glands as a whole. To make it generalizable, nulliparous Dek-OE animals must also be characterized.
      5. To validate findings from their transcriptomics work, the authors used IHC and western blots of candidate proteins that were found to be down regulated. In Figure 3A and 3C, the decrease in p21 protein levels through western blot seem much more modest than what the decrease seen in 3A would suggest.
      6. In Figure 3G-3I, the authors test the CDK4/6 inhibitor palbociclib to establish a direct link between the phenotypes seem in Dek-OE and cell cycle progression in organoid culture. Have the authors verified these findings with treatment of Dek-OE mice with palbociclib? In addition, have the authors checked to see if palbociclib corrected any of the transcriptional features associated with the Dek-OE model found in their transcriptomics data? In addition, the authors claim that the effect is specific to Dek-OE organoids as the effects of palbociclib on growth are not seen in control organoids. However, the data on unperturbed growth of control cells are not seen. To determine the specificity of the effects of palbociclib on Dek-OE derived organoids, the authors must show a time course tracking the growth of organoids with and without palbociclib. Rather than conclude the effects of palbociclib being specific to Dek-OE organoids, the authors most likely wanted to conclude that the increased growth of Dek-OE organoids compared to control organoids is dependent on the increase in cell cycle factors. (The validity of this is also weird though because even if division and growth were triggered through other transcriptional changes they found, like increased metabolism, growth in that scenario would be stopped by palbo as well)
      7. In the main text of Figure 4, the authors conclude that markers for luminal hormone sensing cells were unchanged in Dek-OE mammary glands, however the data to show this is not shown. This is problematic because the authors are directly drawing the conclusion that Dek-OE specifically upregulates luminal alveolar markers using this data.
      8. In figure 7, the authors look at a conditional knockout of Dek and conclude that pup death in the knockout was due to insufficient milk production by dams. While the authors establish that H3K27me3 and Ezh2 expression are abrogated, morphological analysis of the ducts is missing and would present convincing data. For instance, in the Dek conditional knockout, are luminal alveolar cells unable to differentiate fully, or are there far fewer? Decreased levels of histone modifications does not tell you much about whether repressive chromatin has changed its landscape in Dek KO mice, which is actually what influences transcription.

      Minor points:

      All figures need some sort of reformatting. Several of the conclusions are made based on a limited number of replicates (often n=3) which is not a robust sample size to make a rigorous conclusion. Many figures have text that is stretched. Histology and whole mount images are missing scale bar. IHC quantifications are obscure - what is an optical density? how many animals were analyzed and how many fields of vision were captured? Figure 2F is absolutely impossible to understand. Neither figures nor legends disclose the number of animals or samples analyzed. The statistical test utilized across all figures is not appropriated. Fig5B GSEA plots are missing statistical significance, and without this information one cannot properly access the relevance of the findings. Fig5C - how were co-expressed genes defined? is this just random genes that are expressed in cells that have higher levels of DEK? The term co-expressed suggests a specific type of analysis that would investigate linkage of expression between genes, which i dont think is the case here.

      1. Throughout, it would be better to indicate the genotype of the "Control" animals on each figure so as the rigor the experiment can be evaluated fully.
      2. Standard nomenclature for gene names and protein names should be corrected throughout the text.
      3. Similar to the point above, the use of Dek-OE to either refer to the mouse model or function as an acronym for "Dek overexpression" is inconsistent throughout the text.
      4. In the main text for Figure 4I-J, the authors state that DEK was previously published as an Erα target gene, however there is no citation to support this.
      5. It is unclear what the conclusion drawn from the experiments shown in Figure 4G-H and Figure 4I-J mean with respect to the goal of Figure 4, which was to show that Dek-OE mice have an expanded luminal alveolar compartment.
      6. Optical density was used to quantify IHC experiments, which was performed using color deconvolution in ImageJ. Something that is unclear is whether the authors are measuring density in the entire field of view, or if the authors are measuring optical density per cell. This has implications whether there are more cell expressing the protein of interest, or if the existing cells are expressing a higher level of the protein of interest.
      7. In the main text for Figure 6D, the system being used to overexpress DEK protein is not described. It is not the same genetic system as is used in the Dek-OE mice, as doxycycline is inducing Dek expression.

      Significance

      The role of Dek in tumorigenesis and in maintaining stem-like qualities in breast cancer cell lines have been previously reported. However, Dek has never been studied in the context of the normal mammary gland. The authors work revealing the role of Dek in normal development of the mammary gland is significant as understanding it has the potential of revealing additional roles Dek may have as an oncogene in breast cancers.

    1. Reviewer #1 (Public review):

      Summary:

      This work made a lot of efforts to explore the multifaceted roles of the inferior colliculus (IC) in auditory processing, extending beyond traditional sensory encoding. The authors recorded neuronal activity from the IC at single unit level when monkeys were passively exposed or actively engaged in behavioral task. They concluded that 1)IC neurons showed sustained firing patterns related to sound duration, indicating their roles in temporal perception, 2) IC neuronal firing rates increased as sound sequences progress, reflecting modulation by behavioral context rather than reward anticipation, 3) IC neurons encode reward prediction error and their capability of adjusting responses based on reward predictability, 4) IC neural activity correlates with decision-making. In summary, this study tried to provide a new perspective on IC functions by exploring its roles in sensory prediction and reward processing, what are not traditionally associated with this structure.

      Strengths:

      The major strength of this work is that the authors performed electrophysiological recordings from the IC of behaving monkeys. Compared with the auditory cortex and thalamus, the IC in monkeys has not been adequately explored.

      Comments on revised version:

      The authors have adequately addressed all my concerns.

    1. five such remedies: (1) Replace leader style measures by measures of reward and punishment. 7 (2) Differentiate between subordinates. (3) Review the circumstances which call for leadership. (4) Examine leaders’ perceptions of subordinates. (5) Reexamine the basis of subordinates’ perceptions of leaders.

      How they want to bring back the contingency approach

    1. Author response:

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

      Public Reviews:

      Reviewer #1 (Public review):

      In this manuscript, the authors recorded cerebellar unipolar brush cells (UBCs) in acute brain slices. They confirmed that mossy fiber (MF) inputs generate a continuum of UBC responses. Using systematic and physiological trains of MF electrical stimulation, they demonstrated that MF inputs either increased or decreased UBC firing rates (UBC ON vs. OFF) or induced complex, long-lasting modulation of their discharges. The MF influence on UBC firing was directly associated with a specific combination of metabotropic glutamate receptors, mGluR2/3 (inhibitory) and mGluR1 (excitatory). Ultimately, the amount and ratio of these two receptors controlled the time course of the effect, yielding specific temporal transformations such as phase shifts.

      Overall, the topic is compelling, as it broadens our understanding of temporal processing in the cerebellar cortex. The experiments are well-executed and properly analyzed.

      Strengths:

      (1) A wide range of MF stimulation patterns was explored, including burst duration and frequency dependency, which could serve as a valuable foundation for explicit modeling of temporal transformations in the granule cell layer.

      (2) The pharmacological blockade of mGluR2/3, mGluR1, AMPA, and NMDA receptors helped identify the specific roles of these glutamate receptors.

      (3) The experiments convincingly demonstrate the key role of mGluR1 receptors in temporal information processing by UBCs.

      Weaknesses:

      (1) This study is largely descriptive and represents only a modest incremental advance from the previous work (Guo et al., Nat. Commun., 2021). 

      We feel that the present study is a major advance.  It builds on (Guo et al., Nat. Commun., 2021) in which we examined the effects of bursts of 20 stimuli at 100 spk/s.  In that study we found that differential expression of mGluR1 and mGluR2 let to a continuum of temporal responses in UBCs, but AMPARs make a minimal contribution for such bursts. It was not known how UBCs transform realistic mossy fiber input patterns. Here we provide a comprehensive evaluation of a wide range of input patterns that include a range of bursts comprised of 1-20 stimuli, sustained stimulation with stimulation of 1 spk/s to 60 spk/s. This more thorough assessment of UBC transformations combined with a pharmacological assessment of the contributions of different glutamate receptor subtypes provided many new insights: 

      • We found that UBC transformations are comprised of two different components: a slow temporally filtered component controlled by an interplay of mGluR1 and mGluR2, and a second component mediated by AMPARs that can convey spike timing information. NMDARs do not make a major contribution to UBC firing. The finding that UBCs simultaneously convey two types of signals, a slow filtered response and responses to single stimuli, has important implications for the computational potential of UBCs and fundamentally changes the way we think about UBCs.  

      • We found that with regard to the slow filtered component mediated by mGluR1 and mGluR2, we could extend the concept of a continuum of responses evoked by 20 stimuli at 100 spk/s (Guo et al., Nat. Commun., 2021) to a wide range of stimuli. It was not a given that this would be the case.   

      • The contributions of AMPARs was surprising. Even though snRNAseq data did not reveal a gradient of AMPAR expression across the population of UBCs (Guo et al., Nat. Commun., 2021), we found that there was a gradient of AMPA-mediated responses, and that the AMPA component was also most prominent in cells with a large mGluR1 component. Our finding that AMPAR accessory proteins exhibit a gradient across the population, which could account for the gradient of AMPAR responses, will prompt additional studies to test their involvement. 

      (2) The MF activity used to mimic natural stimulation was previously collected in primates, while the recordings were conducted in mice.

      Our first task was to determine the firing properties of mossy fibers under physiological conditions in UBC rich cerebellar regions. Previous studies have estimated this in anesthetized mice using whole cell granule cell recordings (Arenz et al., 2008; Witter & De Zeeuw 2015). However, for assessing firing patterns during awake behavior, we felt that the most comprehensive data set available in a UBC rich cerebellar region was for mossy fibers involved in smooth pursuit in monkeys (David J. Herzfeld and Stephen G. Lisberger). This revealed the general features of mossy fiber firing that helped us design stimulus patterns to thoroughly probe the properties of MF to UBC transformations. The firing patterns are designed to investigate the transformations for a wide range of activity patterns and have important general implications for UBC transformations that are likely applicable to UBCs in different species that are activated in different ways.   

      (3) Inhibition was blocked throughout the study, reducing its physiological relevance.

      The reviewer correctly brings up the very important issue of inhibition in shaping UBC responses.  It is well established that UBCs are inhibited by Golgi cells (Rousseau et al., 2012), and we recently showed that some UBCs are also inhibited by PCs (Guo et al., eLife, 2021). This will undoubtedly influence the firing of UBCs in vivo. We considered examining this issue, but felt that brain slice experiments are not well suited to this. In contrast to MF inputs that can be activated with a realistic activity pattern, it is exceedingly difficult to know how Golgi cells and Purkinje cells are activated under physiological conditions. Each UBC is activated by a single mossy fiber, but inhibition is provided by Golgi cells that are activated by many mossy fibers and granule cells, and PCs that are controlled by many granule cells and many other PCs. In addition, we found that many Golgi cells do not survive very well in slices, and the axons of many PCs are severed in brain slice. Although limitations of the slice preparation prevent us from determining the role of inhibition in shaping UBC responses, we have added a section to the discussion in which we address the important issue of inhibition and UBC responses.   

      Reviewer #2 (Public review):

      This study addresses the question of how UBCs transform synaptic input patterns into spiking output patterns and how different glutamate receptors contribute to their transformations. The first figure utilizes recorded patterns of mossy fiber firing during eye movements in the flocculus of rhesus monkeys obtained from another laboratory. In the first figure, these patterns are used to stimulate mossy fibers in the mouse cerebellum during extracellular recordings of UBCs in acute mouse brain slices. The remaining experiments stimulate mossy fiber inputs at different rates or burst durations, which is described as 'mossy-fiber like', although they are quite simpler than those recorded in vivo. As expected from previous work, AMPA mediates the fast responses, and mGluR1 and mGluR2/3 mediate the majority of longer-duration and delayed responses. The manuscript is well organized and the discussion contextualizes the results effectively.

      The authors use extracellular recordings because the washout of intracellular molecules necessary for metabotropic signaling may occur during whole-cell recordings. These cell-attached recordings do not allow one to confirm that electrical stimulation produces a postsynaptic current on every stimulus. Moreover, it is not clear that the synaptic input is monosynaptic, as UBCs synapse on one another. This leaves open the possibility that delays in firing could be due to disynaptic stimulation. Additionally, the result that AMPAmediated responses were surprisingly small in many UBCs, despite apparent mRNA expression, suggests the possibility that spillover from other nearby synapses activated the higher affinity extrasynaptic mGluRs and that that main mossy fiber input to the UBC was not being stimulated. For these reasons, some whole-cell recordings (or perforated patch) would show that when stimulation is confirmed to be monosynaptic and reliable it can produce the same range of spiking responses seen extracellularly and that AMPA receptormediated currents are indeed small or absent in some UBCs.

      We appreciate the reviewer’s concerns regarding the reliability of mossy fiber activation, the possibility of glutamate spillover from other synapses, and the possibility of disynaptic activation involving stimulation of MFàUBCàUBC connections. We examined these issues in a previous study (Guo et al., Nat. Commun., 2021).  We did on-cell recordings and followed that up with whole cell voltage clamp recordings from the same cell (Guo et al., Nat. Commun., 2021, Fig. 5), and there was good agreement with the amplitude and timing of spiking and the time course and amplitudes of the synaptic currents.  We also compared responses evoked by focal glutamate uncaging over the brush and MF stimulation (Guo et al., Nat. Commun., 2021, Fig. 4). We found that the time courses and amplitudes of the responses were remarkably similar. This strongly suggests that the responses we observe do not reflect disynaptic activation (MFàUBCàUBC connections). We also showed that the responses were all-or-none: at low intensities no response was evoked, as the intensity of extracellular stimulation was increased a large response was suddenly evoked at a threshold intensity and further increases in intensity did not increase the amplitude of the response (Guo et al., Nat. Commun., 2021, Extended data Fig. 1).  We can be well above threshold and still excite the same response, and as a result we do not see stereotyped indications of an inability to stimulate during prolonged high frequency activation.  We recognize the importance of these issues, so we have  added a section dealing explicitly with these issues (pp. 15-16).  

      A discussion of whether the tested glutamate receptors affected the spontaneous firing rates of these cells would be informative as standing currents have been reported in UBCs. It is unclear whether the firing rate was normalized for each stimulation, each drug application, or each cell. It would also be informative to report whether UBCs characterized as responding with Fast, Mid-range, Slow, and OFF responses have different spontaneous firing rates or spontaneous firing patterns (regular vs irregular).

      The spontaneous firing of UBCs is indeed an interesting issue that is deserving of further investigation. It is not currently known how spontaneous firing at rest is regulated in UBCs, however, in previous work we have shown that there is great diversity in the rates across the population of UBCs in the dorsal cochlear nucleus (Huson & Regehr, JNeurosci, 2023, Fig. 4). Unfortunately, during the kind of sustained high-frequency stimulation protocols (as used in this study) spontaneous firing rates tend to increase. This is likely an effect of residual receptor activation. As such, our current dataset is not suitable to performing in depth analysis of the effects of the different glutamate receptors on spontaneous firing rates. As this study aims to explore UBC responses to MF inputs we feel that specific experiments to address the issue of spontaneous firing rates are outside of the scope.

      As the reviewers points out there are indeed different ways the firing rates can be normalized for display in the heatmaps, and different normalizations have been used in different figures. We have made sure that the method for normalization is clearly indicated in the figure legends for each of the heatmaps on display, specifying the protocol and drug application used for normalization.

      Figure 1 shows examples of how Fast, Mid-range, Slow, and OFF UBCs respond to in vivo MF firing patterns, but lacks a summary of how the input is transformed across a population of UBCs. In panel d, it looks as if the phase of firing becomes more delayed across the examples from Fast to OFF UBCs. Quantifying this input/output relationship more thoroughly would strengthen these results.

      The UBC responses to in vivo MF firing patterns are intriguing and we agree that there appears to be increasing delays for slower UBCs visible in Figure 1. However, we feel that the true in vivo MF firing patterns are too complex and irregular for rigorous interpretation. Therefore, we only tested simplified burst and smooth pursuit-like input patterns on the full population of UBCs. Here we indeed do see increasingly delayed responses as UBCs get slower (Fig. 4).

      Inhibition was pharmacologically blocked in these studies. Golgi cells and other inhibitory interneurons likely contribute to how UBCs transform input signals. Speculation of how GABAergic and glycinergic synaptic inhibition may contribute additional context to help readers understand how a circuit with intact inhibition may behave. 

      As indicated in our response to reviewer 1, we have added a section discussing the very important issue of inhibition and UBC responses in vivo.   

      Recommendations for the authors:

      Reviewer #1 (Recommendations for the authors):

      (1) Including recordings without inhibition blocked would strengthen the study and provide a more comprehensive view of the transformations made by UBCs at the input stage of the cerebellar cortex.

      See response to public comments.   

      (2) The authors claim that a continuum of temporal responses was observed in UBCs, but they also distinguish between fast, mid-range, slow, and OFF UBCs. While some UBCs fire spontaneously, others are activated by MF inputs. A more thorough classification effort would clarify the various response profiles observed under specific MF stimulation regimes. Have the authors considered using machine learning algorithms to aid in classification? 

      We fundamentally feel that these response properties do not conform to rigid categories. In our previous work we have shown that UBC population constitutes a continuum in terms of gene expression, and in terms of spontaneous and evoked firing patterns. While in order to answer some questions empirically it may still be useful to apply advanced algorithms to enforce separate groups to be compared, in this work we aimed to present the full range of UBC responses without introducing any additional biases that such methods would produce.

      (3) A robust classification could assist in quantifying the temporal shifts observed during smooth pursuit-like MF stimulation, a critical outcome of the study.

      As stated above, we prefer to present an unbiased overview of the continuous nature of the UBC population, as we believe that this is fundamentally the most accurate representation. While it is true that this prevents us from providing a quantification in the different temporal shifts, we believe that the range of shifts across the population is sufficiently large and continuously varying the be convincing (see Figure 4d).  

      (4) In Figure 5, contrary to what is described on page 10, Cells 10 and 11 (OFF UBCs) appear to behave differently, as mGluR1 does not seem to affect their firing rates. A specific case should be made for OFF UBCs. 

      Indeed, cells 10 and 11 do not show clear increases in firing and are not strongly affected by blocking of mGluR1. However, as discussed above and explored in our previous work, we feel that the range of UBC increases in firing is best described as a continuum, including the extreme where increases in firing are no longer clearly observable. As the aim in this work is to describe this continuum of responses for physiologically relevant inputs, we do not feel there is a benefit to creating a specific case for OFF UBCs here. It should be pointed out that the number of “pure” OFF UBCs completely lacking an mGluR1 component is very small.  

      (5) A summary diagram should be added at the end of the manuscript to highlight the key temporal features observed in this study. 

      This is a great suggestion and we have prepared such a summary diagram (Figure 6).

      Reviewer #2 (Recommendations for the authors):

      (1) Page 3- "Assed" should be "assessed"

      (2) Page 19- "by integrating" is repeated twice

      (3) It was not noted whether the data would be made available. It could be useful for those interested in implementing UBCs in models of the cerebellar cortex.

      We agree that this data set is invaluable to those interested in implementing UBCs in models of the cerebellar cortex.  We will make the dataset available as described in the text.

    1. Author response:

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

      Reviewer #1:

      (1) “…Given that the focus in the paper is on tissue-specific immune training, it would be helpful to know whether the ongoing presence of BCG at low levels in the profiled tissue contributes to the trained immunity phenotypes observed.”….“To address point 1, the authors could treat with anti-BCG antibiotics at 2 or 4 weeks post-BCG exposure and profile the impact on trained immunity phenotypes.”

      We thank the reviewer for this important comment. The experiment suggested by the reviewer is to treat with abx to remove BCG from the tissue from the first week post challenge for the duration of four weeks. In previous work, Kaufmann et al (PMID: 29328912) showed that after a month of antibiotics, BCG levels are reduced, but residual BCG levels still remains. Accroding to their results, while antibiotic treatment reduces the training phenotype of LKS<sup>+</sup> HSC expansion in the bone marrow, protection against TB was maintained during ex-vivo challenge of BMDMs.

      In our experiments, we are concerned that antibiotic treatment will only change the dynamics of BCG clearance, but residual BCG will remain and will limit our interpretation. Furthermore, examining the transcriptional changes we observed at early timeponts after BCG may not be relavant at 1 month post antibiotics.

      As an alternative approach, we refer to our results with an antibody to block early IFNg signaling (1-5 days; Figure S4 K-M). Here, although BCG levels are comparable between treatment and control groups, we were unable to detect any TI-related transcriptional signatures upon early aIFNg treatment. This indicates that that residual BCG is not sufficient for the TI phenotype in the spleen. We now emphasize this point in the revised version of the manuscript (see lines 335-339).

      (2) “Related to the point about BCG above, it would be helpful to understand whether this is a specifically time-limited requirement when trained immunity is first induced, or whether ongoing signaling through this axis is required for maintenance of the observed trained immunity phenotypes.”… “To address point 2, authors could treat with the inhibitor at 2 weeks and/or 4 weeks post-BCG and profiling later transcriptional and/or salmonella growth phenotypes.”

      We thank the reviewer for his comment, but respectfully claim that this experiment might not be feasible. As IFNg signaling is directly required for control of Salmonella infection,  we are concerned that late IFNg inhibition will also directly affect the response to Salmonella challenge and control. Thus, in our experiments, to ensure that treatment only affects the response to BCG challenge, we were careful to limit aIFNg treatment to the early time points and allowed long resting period before Salmonella challenge.

      Furthermore, inhibition of IFNg at late time point was already tested in both Lee et al, and Tran et al. (PMID: 38036767, 38302603). The authors show that late blockage of IFNg signalling (days 14-21) is sufficient to prevent protection during a viral challenge. This would indeed imply that ongoing signalling is necessary in this context to generate protection, specifically also late signalling events. Furthermore, Lee at al., also observed a biphasic activation pattern of cytokines and recruited cells, suggesting that rather than continuous activation, sequential cell activation and signalling may be occurring.

      Respectfully, in our experiments we focus on the early time points based on our observations of early recruitment of CM-T cells (Figure S2. C-D). This was our main findings of this paper. We agree with the reviewer that future experiments are required to compare the differences in cell populations that are invovled in the early vs. late trained phenotpe dynamics.

      Minor points:

      Experimental conditions for the shown data are not consistently clear from the figure legends- would add more detail about the biological conditions.

      OK – done

      Figure 3E missing units on the legend

      OK – done

      Figure 4C middle panel missing y-axis label

      OK – done

      Line 40- remove "both"

      OK- done

      Line 156- Language could be clearer about what was described previously in contrast to the results shown in this work

      We have modified the text accordingly in the revised manuscript

      Reviewer #2:

      “A significant amount of work has already been performed for this study. The work is rich with data and description.”

      We thank the reviewer for acknowledging the importance of our work.

      Minor comments for the authors to consider:

      “BCG is widely recognised to induce trained immunity. In this study, Salmonella is used as secondary infection event. Why? What is role of Salmonella in this study? Does this study contribute to our understanding of the Salmonella infection process? What does this tell us about Salmonella/vaccines? Is there any evidence that BCG protects against Salmonella infection? “

      We thank the reviewer for this important comment. We now added to the introduction and the discussion the relevance of our study to the potential of BCG and trained immunity as an alternative heterologous vaccine approach to traditional vaccines that require strain-specific vaccine for each pathogen (lines 49-55 of the revised manuscript).

      “Figure 1E. RPM cannot be detected by scRNAseq?”

      The reviewer is correct. we excluded RPMs from the scRNA-seq analysis. As we discuss in the manuscript (lines 94-96), and in our previous publication (PMID: 34788598), RPM activation involves rapid cell death. As we are analyzing by scRNA-seq two weeks after BCG challenge, we only measured scRNA-seq of CD11b+ cells, which exclude RPMs, as we were worried that our transcriptional data would represent transcriptional signatures of dying cells, making interpretation of the data difficult.

      “Figures 1H and I. The CM-T macrophages are not represented? Are they contemplated within the CM population? Would be useful to see the contribution of CM-T to the total CM DEGs/pathways.”

      The reviewer is correct. CM-T cells are evident only after BCG challenge. Because of this, our analysis of DEGs induced in monocytes by BCG requires analysis of all monocytes together. Thus, we were careful throughout the manuscript to refer to CM when analyzing bulk RNA-seq data.

      “Lines 104-117. Can the authors summarise or move the text in this paragraph to discussion? Although it provides important context, it cuts the line of thought and reduces comprehension of this section. “

      OK – we moved this section to the discussion in the revised manuscript.

      “Line 127. Is it Fig 1I or 1F that the authors are referring to? “

      The reviewer is correct, and we changed the text in the revised manuscipt accordingly.

      “Figure 1J. x-axis labels CM cells but both text and figure legend refer to this panel as CM-T. If this is the case, please show data for CM and CM-T separately.”

      Please see our earlier point above that limits these analyses. As such we have also edited the text and figure legend to reflect this.

      “Lines 136-139. Please indicate that this can be found in Fig 1J.”

      OK – indicated in the revised manuscript

      “Line 152. Please add that STm infection occurred at 14 and 60 days post training.”

      OK – added

      “Lines 162-163. This is repeated from lines 89-90, maybe the reduction of RPMs can be only highlighted in this section so that the previous section can be just focused on the new CM-T population?”

      The reviewer is correct - we removed the mention of RPMs here, and mention them only later in the revised manuscript.

      “Line 163. The recruitment is CM or CM-T cells? Since they express CXCL9 (line 165 and Fig1J) could this be used as a marker for the CM-T population at this time point?”

      The reviewer is correct, and we thank him for this important comment. We now indicate that CXCL9+ is a marker for the CM-Ts population here and throughout the revised manuscript (lines 153-155 of the revised manuscript).

      “Line 173. The loss of CXCL9 at 60 dpi means that CM-T population disappears/reduces or returns to CM only? If the population is reduced, could it be related to the reduced STm infection control at 60 days?”

      OK– done. Referred to these cells as CM-Ts and suggested a correlation with protection loss in the text (lines 160-162 of the revised manuscript).

      “Figure 2D. Can the authors show if there is variation in the myeloid populations after PBS injection at different time points? Are the percentages shown only at 3 dpi? It is curious that at 30 dpi the transcriptome has a significant change for certain genes.”

      There are indeed variations across the PBS time points samples, which we demonstrate in Figure S2B. The percentages shown in the main figure for PBS reflect the mean of all time points, this is now stated in greater clarity in the revised manuscript (lines 151-152). We also noted an increase in the cell cycling genes at D30 for the control mice as well, and while still significant in BCG, we limited interpretation accordingly.

      “Line 208. The authors can highlight that the expression of STAT1 follows the same pattern as IFNg. Maybe even present the graphs side by side?”

      The reviewer is correct, and we have implemented their suggestion as such in the updated text (lines 192-195) and figure (Fig. 2H).

      “Line 213. Authors mention a replenishment of the RPM population - what time point are you referring to? At 60 dpi the population seems to be halved compared to 14 dpi. Later (line 230), authors refer to the replenishment as a repopulation by other cell types - is repopulation more correct than replenishment?”

      The reviewer is correct, and we thank the reviewer for this important comment. We now changed replenishment to repopulation (lines 95, 201), which is more accurate given the continued decreased percentage at later time points.

      Lines 214-222. It is not clear what is the conclusion from these experiments: is the recruitment of progenitors from the BM or by local signals?

      The reviewer is correct, we agree that the wording in the initial manuscript was imprecise. This experiment specifically tests whether trained bone marrow progenitors can sustain the observed TI signatures in a naive environment. By transplanting trained bone marrow into naive hosts, we demonstrate that progenitor programming alone is sufficient to maintain long-term SCA-1 expression in NCMs, without requiring ongoing local tissue signals. We now better clarify this text in the revised manuscript (lines 202-212).

      “Line 333-334. Where is the data that shows that upon Fedratinib RPMs have enhanced survival?”

      OK – We now indicate the figure in the revised manuscript.

    1. Author response:

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

      Reviewer #1:

      Chemogenetics validation

      Little validation is provided for the chemogenetic manipulations. The authors report that animals were excluded due to lack of expression but do not quantify/document the extent of expression in the animals that were included in the study.

      We thank the reviewer for raising this oversight. We have added additional examples of virus expression in sections from included and excluded animals in Figure 1 – Supplement 1. We also added additional comments on the extent of expression we observed in lines 92-95: “Post-experiment histology confirmed overlapping virus expression and TH-positive neurons in putative VTA near the injection site (-5.6 mm AP from bregma), as well as approximately 0.5 mm anterior and posterior (-5 to -6 mm AP).”

      There's no independent verification that VTA was actually inhibited by the chemogenetic manipulation besides the experimental effects of interest.

      While we did include animals expressing control virus to control for any effect of CNO administration itself, the reviewer is correct that we did not independently verify VTA neurons were inhibited. We have noted this limitation of the current study on lines 513-522 in the Discussion: “We did not directly measure the suppression of VTA neurons after CNO injection. Previous work in other brain areas found hM4Di activation suppressed firing rates to around 60% of baseline (Mahler et al., 2014; Chang et al., 2015), in addition to diminishing synaptic transmission even when spikes occurred (Stachniak et al., 2014). Combined with the incomplete expression of hM4Di in TH-positive neurons in our animals, we expect VTA activity was significantly but not completely suppressed. Because our results depend only on any degree of blunting differences in dopamine release at different reward locations, rather than the total absence of dopamine signaling, measuring the magnitude of suppression was not essential for our conclusions.”

      The authors report a range of CNO doses. What determined the dose that each rat received? Was it constant for an individual rat? If not, how was the dose determined? The authors may wish to examine whether any of their CNO effects were dependent on dose.

      The reviewer is completely correct that we omitted sufficient information regarding the dosage of CNO used in each animal and each session. We have included more details in the Methods lines 676-694, detailing both the doses and the rationale.

      The authors tested the same animal multiple times per day with relatively little time between recording sessions. Can they be certain that the effect of CNO wore off between sessions? Might successive CNO injections in the same day have impacted neural activity in the VTA differently? Could the chemogenetic manipulation have grown stronger with each successive injection (or maybe weaker due to something like receptor desensitization)? The authors could test statistically whether the effects of CNO that they report do not depend on the number of CNO injections a rat received over a short period of time.

      We thank the reviewer for bringing up the question of whether the order of sessions had an influence on the efficacy of CNO in inactivating VTA activity. To address this, we split our dataset in Experiment 1 into two based on what number session of the particular day it was: 1st sessions of the day vs. all subsequent sessions (2nd+ session of the day). Then, we examined the difference in sharp-wave ripple rate between the reward ends in Epoch 2, as in Figure 2D of the manuscript. Though the resulting number of sessions in each split of the dataset is too low to draw strong statistical conclusions, particularly for novel sessions, we see little evidence there is any systematic change in the effect of VTA inactivation as a function of session number in the day. We include this in the revised manuscript as Figure 2 – Supplement 3 and in the Results lines 255-258.

      Motivational considerations

      In a similar vein, running multiple sessions per day raises the possibility that rats' motivation was not constant across all data collection time points. The authors could test whether any measures of motivation (laps completed, running speed) changed across the sessions conducted within the same day.

      We thank the reviewer for this suggestion. We examined behavioral measures of motivation across sessions conducted within the same day. First, we calculated how many total laps each animal completed each session as a function of the session number of the day. In individual animals, this ranged from -2.8 to 4.1 laps per additional session number (mean 2.01), with an average total laps per session of 43.2 laps. Second, we calculated the median running velocity per session, across both running directions and all epochs, and checked how it varied across session number of the day. Per additional session in the day, this ranged from -3.6 to 8.6 cm/s difference across animals (mean 2.7 cm/s), with an average running velocity of 34.1 cm/s in total. Taken together, while we found little behavioral evidence of strong motivational changes across session, our animals may have been slightly more motivated in later sessions in the day, which also corresponded to later in the light cycle and closer to the dark cycle. We mention this information in Results lines 255-258, related to Figure 2 – Supplement 3.

      This is a particularly tricky issue, because my read of the methods is that saline sessions were only conducted as the first session of any recording day, which means there's a session order/time of day and potential motivational confound in comparing saline to CNO sessions.

      We have clarified the ordering of CNO and saline sessions in the Methods lines 697-702. Briefly, we avoided running CNO sessions before saline sessions in the same day, but either could be the first session of a day. That is, saline -> saline, saline -> CNO, and CNO -> CNO were all valid orderings. On days with more than two sessions, any number of repeated saline and CNO sessions was permitted, provided that as soon as a CNO session occurred, any subsequent sessions were also CNO.

      More generally, we shared this reviewer’s concern about potential confounds between drug and motivation. For novel sessions in Experiment 1, each animal had equal numbers of saline and CNO 1st and 2nd sessions of the day. For familiar sessions, animals had similar counts for 1st sessions of the day (experimental rats: 20 saline, 16 CNO; control rats: 17 saline, 15 CNO) but more CNO 2nd sessions of the day (experimental rats: 5 saline, 13 CNO; control rats: 5 saline, 10 CNO). There were occasionally 3rd or 4th sessions in a given day for some rats, and these were also approximately equal (experimental rat 2, 3rd sessions: 2 each of saline and CNO, 4th session: 1 saline; experimental rat 3 and 4, 3rd sessions: 1 each of saline and CNO; control rat 2, 3rd session: 1 saline).

      Statistics, statistical power, and effect sizes

      Throughout the manuscript, the authors employ a mixture of t-tests, ANOVAs, and mixed-effects models. Only the mixed effects models appropriately account for the fact that all of this data involves repeated measurements from the same subject. The t-tests are frequently doubly inappropriate because they both treat repeated measures as independent and are not corrected for multiple comparisons.

      We thank the reviewer for pointing out these issues with our statistical analyses in places. We have made the following improvements:

      Figure 1F-I, S1, reward end visit durations: We now use a linear mixed-effects model to analyze the difference in stopping period durations between epochs. For each session, we calculated the mean stopping duration for each reward end in each epoch, then modeled the difference between epochs as a function of drug and novelty, with animal-specific intercepts. For example, related to Figure 1F and also described in the Results, we modeled the stopping duration difference at the Unchanged reward end, Epoch 2 – Epoch 1, and found experimental rats had a significant intercept (Epoch 2 stops shorter than Epoch 1) and the drug × novelty interaction, while control rats had a significant intercept and novelty main effect. The other visit duration analysis shown in Figure 1 – Supplement 1 have similarly been updated.

      Figure 2D-E, ripple rate difference between reward ends in Epoch 2: We now use a linear mixed-effects model to analyze the difference between ripple rates at the Incr. and Unch. reward ends in Epoch 2. For each session, we calculated the mean ripple rate at each end in Epoch 2, then modeled the difference as a function of drug and novelty, with animal-specific intercepts. With the full stopping periods, for experimental rats, there was a significant intercept (ripple rate at Incr. greater than Unch.) and the model with drug included performed significantly better than the one without it (AIC<sub>nodrug</sub> – AIC<sub>full</sub> = 5.22). Control rats had a significant intercept and effect of novelty (greater difference with novelty), and the model excluding drug terms performed better (AIC<sub>nodrug</sub> – AIC<sub>full</sub> = -3.54). Results with the trimmed stopping periods were similar. These analyses are described in Results lines 253-266.   

      Figure 3D-E, ripple rate as a function of reward history: We now use a mixed-effects model that incorporates animal-specific intercepts. The results remained similar and have been updated in the text and legend.

      Figure 4D-K, replay rates as a function of drug, novelty, and directionality: We now use mixed-effects models that incorporate animal-specific intercepts rather than three-way ANOVA. The results remained similar and have been updated in the text and legend.

      The number of animals in these studies is on the lower end for this sort of work, raising questions about whether all of these results are statistically reliable and likely to generalize. This is particularly pronounced in the reward volatility experiment, where the number of rats in the experimental group is halved to just two. The results of this experiment are potentially very exciting, but the sample size makes this feel more like pilot data than a finished product.

      We have added additional emphasis in the text that the experimental group results of CNO inactivation in the volatile reward task should be confirmed with future work, in Discussion line 529-533. Because these experiments were performed on familiar tracks, we see them as corroborating/complementing the results from Experiment 1. Although the analysis assumes VTA inactivation had no effect, our pooling of all Experiment 2 data to display in Figure 3 – Supplement 2 maximized our ability to analyze the effects of volatile reward deliveries on sharp-wave ripple rates, lending further support to the main results shown in Figure 3.

      The effect sizes of the various manipulations appear to be relatively modest, and I wonder if the authors could help readers by contextualizing the magnitude of these results further. For instance, when VTA inactivation increases mis-localization of SWRs to the unchanged end of the track, roughly how many misplaced sharp-waves are occurring within a session, and what would their consequence be? On this particular behavioral task, it's not clear that the animals are doing worse in any way despite the mislocalization of sharp-waves. And it seems like the absolute number of extra sharp-waves that occur in some of these conditions would be quite small over the course of a session, so it would be helpful if the authors could speculate on how these differences might translate to meaningful changes in processes like consolidation, for instance.

      We thank the reviewer for this helpful suggestion to give some context to the difference in sharp-wave ripple numbers and the functional consequence of these changes. We agree completely that this task is almost certainly too simple for animals to show any performance deficit from these changes. We chose this precisely so we could examine the consequences of VTA inactivation to the sharp-wave ripple response to reward changes per se, without any confound of performance or memory changes that could also conceivably alter sharp-wave ripples. We have added both more context about the magnitude and consequence of these sharp-wave ripple changes as well as comments about the choice of this particular task (Discussion lines 522-529).  

      How directly is reward affecting sharp-wave rate?

      Changes in reward magnitude on the authors' task cause rats to reallocate how much time they spent at each end. Coincident with this behavioral change, the authors identify changes in the sharp-wave rate, and the assumption is that changing reward is altering the sharp-wave rate. But it also seems possible that by inducing longer pauses, increased reward magnitude is affecting the hippocampal network state and creating an occasion for more sharp-waves to occur. It's possible that any manipulation so altering rats' behavior would similarly affect the sharp-wave rate.

      For instance, in the volatility experiment, on trials when no reward is given sharp-wave rate looks like it is effectively zero. But this rate is somewhat hard to interpret. If rats hardly stopped moving on trials when no reward was given, and the hippocampus remained in a strong theta network state for the full duration of the rat's visit to the feeder, the lack of sharp-waves might not reflect something about reward processing so much as the fact that the rat's hippocampus didn't have the occasion to emit a sharp-wave. A better way to compute the sharp-wave rate might be to use not the entire visit duration in the denominator, but rather the total amount of time the hippocampus spends in a non-theta state during each visit. Another approach might be to include visit duration as a covariate with reward magnitude in some of the analyses. Increasing reward magnitude seems to increase visit duration, but these probably aren't perfectly correlated, so the authors might gain some leverage by showing that on the rare long visit to a low-reward end sharp-wave rate remains reliably low. This would help exclude the explanation that sharp-wave rate follows increases in reward magnitude simply because longer pauses allow a greater opportunity for the hippocampus to settle into a non-theta state.

      We thank the reviewer for these important comments. We have better clarified the analysis of sharp-wave ripple rate in the Results (lines 172-173). To speak to the main concern of the reviewer, we do only consider times during “stopping periods” when the rat is actually stationary. That is, ripple rate for each visit is calculated as (# of ripples / total stationary time), rather than the full duration the rat is at the track end. With respect to including visit duration as a covariate, the Poisson model takes the total stationary time of each visit into account, so that it is effectively predicting the number of events (ripples) per unit of time (seconds) given the particular experimental variables (reward condition, drug condition, etc.). We have added additional clarification of this in the Methods (line 834-836).

      The authors seem to acknowledge this issue to some extent, as a few analyses have the moments just after the rat's arrival at a feeder and just before departure trimmed out of consideration. But that assumes these sorts of non-theta states are only occurring at the very beginning and very end of visits when in fact rats might be doing all sorts of other things during visits that could affect the hippocampus network state and the propensity to observe sharp-waves.

      We hope that with the clarification provided above, this control analysis helps remove any potential effects of approaching/leaving behavior or differences in movement at the reward end that could alter sharp-wave ripple rates. 

      Minor issues

      The title/abstract should reflect that only male animals were used in this study.

      We have added this important information to the Abstract line 21.

      The title refers to hippocampal replay, but for much of the paper the authors are measuring sharp-wave rate and not replay directly, so I would favor a more nuanced title.

      We thank the reviewer for this suggestion. In the context of our work, we consider sharp-wave ripples as more-easily-detected markers for the occurrence of replay. Previous work from our lab (Ambrose et al., 2016) showed the effect of reward changes had very similar effects to both sharp-wave ripple rate and replay rate. We try to be explicit about viewing ripples as markers of replay content in both the Introduction and Discussion. Nevertheless, we do also demonstrate the title claim directly – by measuring replay and its spatial localization – therefore we feel comfortable with the title as it is.

      Relatedly, the interpretation of the mislocalization of sharp-waves following VTA inactivation suggests that the hippocampus is perhaps representing information inappropriately/incorrectly for consolidation, as the increased rate is observed both for a location that has undergone a change in reward and one that has not. However, the authors are measuring replay rate, not replay content. It's entirely possible that the "mislocalized" replays at the unchanged end are, in fact, replaying information about the changed end of the track. A bit more nuance in the discussion of this effect would be helpful.

      While we do show that replay content, in the form of reverse vs. forward replays, is altered with VTA inactivation, we take the reviewers point and completely agree. Especially in the context of the linear track, replays at either end could certainly be updating/consolidating information about both ends. We would argue our results suggest VTA is critical to localizing ripples and replay in more complex environments where this is not the case, but this is a hypothesis. We have added clarification and discussion of this point (Discussion lines 522-529).

      However, in response to the reviewer’s comment, we have now also examined non-locally-initiated replays specifically to determine whether the increased ripple rate at the Unch. reward end in novel CNO sessions was likely due to more non-local replay, but found no significant increases in non-local replay at either reward end in either drug condition or novelty condition. We have included this result as Figure 4 – Supplement 3, and note it in the Results lines 487-488.

      The authors use decoding accuracy during movement to determine which sessions should be included for decoding of replay direction. Details on cross-validation are omitted and would be appreciated. Also, the authors assume that sessions failed to meet inclusion criteria because of ensemble size, but this information is not reported anywhere directly. More info on the ensemble size of included/excluded sessions would be helpful.

      We have added additional information about the run decoding procedure and related session inclusion criteria, as well as about recorded ensemble sizes (lines 417-421). Briefly, mean ensemble sizes were significantly smaller for excluded sessions (cell count, mean±sem; included sessions: 26.1±1.1, excluded sessions: 9.5±1.6; two-sample t-test, t(133)=5.3, p<10<sup>-5</sup>). The average field size, defined as the number of spatial bins with greater than 1 hz firing rate, in excluded sessions was also larger (mean±sem, included sessions: 47.7±1.3, excluded sessions: 57.7±5.8; two-sample t-test, t(133)=-2.33, p<0.05), though the difference was less dramatic. Using a mixed effects model to predict position decoding error (as in Figure 4 – Supplement 2A) as a function of drug, novelty, cell count, and mean place field size, in both experimental and control groups cell count and field size were significant predictors: more cells and smaller average field size led to lower error. A similar model that instead predicted the fraction of running bins with correctly decoded running direction (as in Figure 4 – Supplement 2B), in neither group was field size significant, while cell count remained so: more cells led to more bins with running direction correctly classified. We include these analyses in the legend for the figure. With respect to cross validation of run decoding, because both the contribution of spikes in any single time bin to a neuron’s place field is extremely small and because we used run decoding accuracy simply to filter out sessions with poorer decoding, we did not use cross validation here.

      For most of the paper, the authors detect sharp-waves using ripple power in the LFP, but for the analysis of replay direction, they use a different detection procedure based on the population firing rate of recorded neurons. Was there a reason for this switch? It's somewhat difficult to compare reported sharpwave/replay rates of the analyses given that different approaches were used.

      We have added clarification for this change in detecting candidate events (lines 787-789). Briefly, sharp-wave ripples and spike density events are often but not always overlapping, such that there can be strong ripples with little spiking in the recorded ensemble or weak/absent ripples during vigorous spiking in the recorded ensemble. Because the decoding of replay content relies on spiking, our lab and others often use spike density or population burst events as candidate events. We have confirmed that the main results of Experiment 1 (e.g., Figure 2) remain the same if we use spike density events rather than sharp-wave ripples, but prefer to keep the use of sharp-wave ripples here for better comparison with Experiment 2 and to allow the inclusion of animals and sessions with low cell yield but clear ripples in the LFP.  

      Reviewer #2 (Recommendations For The Authors):

      Include additional histological data to confirm the extent of viral spread and precise tetrode placements. Providing detailed figures that clearly illustrate these aspects would strengthen the validity of the neural recordings and the specificity of the chemogenetic silencing.

      We thank the reviewer for this suggestion and have added additional information regarding virus expression in Figure 1 – Supplement 1. We also added additional comments on the extent of expression we observed in lines 92-95: “Post-experiment histology confirmed overlapping virus expression and TH-positive neurons in putative VTA near the injection site (-5.6 mm AP from bregma), as well as approximately 0.5 mm anterior and posterior (-5 to -6 mm AP).”

      While we do not show histological confirmation of hippocampal recording sites, the presence of sharp-wave ripples with upward deflections, presence of place cells, and recording coordinates and depth typical of dorsal CA1 made us confident in our recording location. We have noted these characteristics of our recordings in lines 128-131 in the Results: “Tetrodes were lowered to the pyramidal cell layer of dCA1, using the presence of sharp-wave ripples with upward deflections in the LFP, recording depth characteristic of dCA1, and spatially-restricted firing of place cells to confirm the recording location.”

      Address the variability in CNO dosing and timing before recordings. It is recommended to standardize the dose and ensure a consistent timing interval between CNO administration and the start of recordings to minimize variability in the effects observed across different subjects. Instead of collecting new data, the authors could report the data for each animal, indicating the dose and interval between the injection and the recording.

      We have further clarified the CNO dosing and timings in lines 676-702.

      In Figure 1F, explicitly state whether the data represent averages across multiple sessions and confirm if these observations are primarily from the initial novel sessions. This clarification will help in accurately interpreting the effects of novelty on the measured neural activities.

      We have changed the analyses shown in Figure 1F-I and Figure 1 – Supplement 1 thanks to the suggestions of Reviewer #1, but also more clearly spell out the analysis. Briefly, we average the durations for each condition within session (e.g., take the mean Unch. duration in Epoch 1), then perform the analysis across sessions. These data come from all sessions in Experiment 1, as described in lines 141-147, meaning there are around 2-3 times as many familiar sessions as novel sessions.

      Reconsider the reporting of marginal p-values (e.g., p=0.055). If the results are borderline significant, either more data should be collected to robustly demonstrate the effects or a statistical discussion should be included to address the implications of these marginal findings.

      We have removed the reporting of marginal p-values.

      Ensure that the axes and scales are consistent across similar figures (specifically mentioned for Figure 2A) to prevent misinterpretation of the data. Consider showing the average across all animals in 2A, similar to 2B and 2C.

      We have adjusted these axes to be consistent across all panels.

      Add a legend to the heatmap in Figure 4A to facilitate understanding of the data presented.

      We have added a heatmap to the figure and legend.

      Provide a detailed examination and discussion of the apparent contradictions observed in control data, particularly where experimental conditions with saline show increased reverse replay in novel environments, which is absent in familiar sessions. See Figures 4E and 4I.

      We thank the reviewer for noting that this feature of our data deserved discussion. We confirmed that the lack of an effect of reward on reverse replay rates in familiar sessions in control rats was due to generally low replay rates in these sessions. Replay rates have been observed to decrease as the familiarity of an environment or behavior increases, and the presence of the reward-related modulation of reverse replay in novel sessions in these animals is consistent with this observation. We now report in the Results lines 458-459 and 485-486 the low replay rates in this group in familiar sessions, and the likelihood that this is preventing any reward-related modulation from being detected.

      Include a more detailed analysis of place cell properties, such as firing rates and field sizes, especially in novel environments where VTA inactivation appears to alter spatial coding. Decoding error is lower during CNO administration - does this mean place fields are smaller/more accurate? This analysis could offer deeper insights into the mechanisms by which dopamine influences hippocampal neural representations and memory processes.

      We thank the reviewer for this helpful suggestion. We have expanded on our analysis of place field properties and decoding accuracy, describing properties of sessions with good enough decoding to be included compared to those that were excluded (lines 417-421). We also directly tested how decoding quality depended on several factors, including drug condition, novelty, number of cells recorded, and the average place field size of recorded cells (see legend for Figure 4 – Supplement 2). We found a small but significant effect of drug in experimental rats, but larger effects of number of recorded cells and average field size, that were also present in control animals.

      Correct the typo on line 722 from "In ANOVA" to "An ANOVA".

      We reworded this section and have corrected this error.

      Reviewer #3 (Recommendations For The Authors):

      The manuscript is clear and exciting. As a main criticism, I would have liked to see the effects on ripple duration not just the rate.

      We thank the reviewer for this interesting idea. We performed a new analysis, similar to our analysis on SWR rate, probing the effect of our experimental manipulations on SWR duration in experimental rats. We have added the results in Figure 2 – Supplement 4, and note them in the main text lines 195-198: “SWR duration was reduced in novel sessions, consistent with replays becoming longer with increased familiarity  (Berners-Lee et al., 2021), as well as in Epoch 2, but was otherwise unaffected by reward or drug (Figure 2 – Supplement 4).”

      I have a few other minor comments:

      (1) I find it a little disturbing and counterintuitive that statistical differences are not always depicted in the figure graphs (for example Figures 2A-E). If the authors don't like to use the traditional *, ** or *** they could either just use one symbol to depict significance or simply depict the actual p values.

      We thank the reviewer for this suggestion. We struggled with indicating significance values graphically in an intuitive way for interaction terms in the figures. We now added significance indicators in Figures 1F-I, added the significant model coefficients directly into Figure 2B-C, changed the analysis depicted in Figure 2D-E per Reviewer 1’s suggestions, and added significance indicators where previously missing in Figures 3 and 4.

      (2) Related to the point above: in the page 7 legend D and E, it would be advantageous for clarity of the experimental results to also perform post-hoc analyses as depicted in the graphs, rather than just describe the p-value of the 3way ANOVA;

      We thank the reviewer for this suggestion. Because the figure includes the mean and standard error of each condition, in addition to the significant effects of the mixed-effects model, we prefer the current format as it makes clearer the statistical tests that were performed while still allowing visual appreciation of differences between specific experimental conditions of interest to the reader.

      (3) According to Figure 1H, the duration of the reward visits can go up to 15s (or more). Yet in Figure 2A only the first 10sec were analyzed. While I understand the rationale for using the initial 10 seconds where there is a lot more data, the results of graphs of Figures A to C will not have the same data/rate as Figures D-F where I assume the entire duration of the visit is taken into account.

      A figure showing what happening to the ripple rate during the visits >10sec would help interpret the results of Figure 2.

      We thank the reviewer for these interesting suggestions. We clarify now that all these analyses of Experiment 1 use only the first 10 s of each stopping period in Method line 758-764. However, examining the longer stopping periods is an excellent suggestion, and we re-analyzed the Experiment 1 dataset using up to the first 20 s of each stopping period. The main results (e.g., Figure 2) remain the same:

      (1) Related to Figure 2B-C: For experimental rats, a mixed-effects generalized linear model predicting sharp-wave ripple rate as a function of reward end, block, drug, novelty, and interactions, had the following significant terms: drug (p<10<sup>-5</sup>), novelty (p<10<sup>-10</sup>), reward end × block (p<10<sup>-10</sup>), and reward end × block × drug (p<0.05). The same model in control rats had significant terms: reward end (p<0.05), novelty (p<10<sup>-4</sup>), reward end × block (p<10<sup>-10</sup>).

      (2) Related to Figure 2D-E: For experimental rats, we used a mixed-effects generalized linear model predicting the difference in sharp-wave ripple rate between the Incr. and Unch. reward ends in Epoch 2 as a function of novelty, drug, and their interaction. Model comparison found the full model performed better than a model removing the drug terms (AIC<sub>nodrug</sub> – AIC<sub>full</sub> = 2.94), while a model with only the intercept performed even worse (AIC<sub>intercept</sub> – AIC<sub>full</sub> = 13.76). For control rats, model comparison found the full model was equivalent to a model with only the intercept (AICintercept – AICfull = -0.36), with both modestly better than a model with no drug terms (AIC<sub>nodrug</sub> – AIC<sub>full</sub> = 1.38).

      We have added a remark that results remain the same using this longer time window in Methods line 758-764.

    1. Author response:

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

      Public Reviews:  

      Reviewer #1 (Public Review): 

      Summary: 

      The authors use an innovative behavior assay (chamber preference test) and standard calcium imaging experiments on cultured dorsal root ganglion (DRG) neurons to evaluate the consequences of global knockout of TRPV1 and TRPM2, and overexpression of TRPV1, on warmth detection. They find a profound effect of TRPM2 elimination in the behavioral assay, whereas elimination of TRPV1 has the largest effect on neuronal responses. These findings are of importance, as there is still substantial discussion in the field regarding the contribution of TRP channels to different aspects of thermosensation. 

      Strengths: 

      The chamber preference test is an important innovation compared to the standard two-plate test, as it depends on thermal information sampled from the entire skin, as opposed to only the plantar side of the paws. With this assay, and the detailed analysis, the authors provide strong supporting evidence for the role of TRPM2 in warmth avoidance. The conceptual framework using the Drift Diffusion Model provides a first glimpse of how this decision of a mouse to change between temperatures can be interpreted and may form the basis for further analysis of thermosensory behavior. 

      Weaknesses: 

      The authors juxtapose these behavioral data with calcium imaging data using isolated DRG neurons. Here, there are a few aspects that are less convincing. 

      (1) The authors study warmth responses using DRG neurons after three days of culturing. They propose that these "more accurately reflect the functional properties and abundance of warm-responsive sensory neurons that are found in behaving animals." However, the only argument to support this notion is that the fraction of neurons responding to warmth is lower after three days of culture. This could have many reasons, including loss of specific subpopulations of neurons, or any other (artificial?) alterations to the neurons' transcriptome due to the culturing. The isolated DRGs are not selected in any way, so also include neurons innervating viscera not involved in thermosensation. If the authors wish to address actual changes in sensory nerves involved in warmth sensing in TRPM2 or TRPV1 KO mice without disturbing the response profile as a result of the isolation procedure, other approaches would be needed (e.g. skin-nerve recordings or in vivo DRG imaging).  

      We agree that there could be several reasons as to why the responses of cultured DRGs are reduced compared to the acute/short-term cultures. It is possible ––and likely–– that transcriptional changes happen over the course of the culturing period. It is also possible that it is a mere coincidence that the 3-day cultures have a response profile more similar to the in vivo situation than the acute cultures. In the revised manuscript, we have therefore toned down the claim that the 3-day cultures mirror the native conditions more appropriately and included the sentence “However, whether 3-day cultures resemble native sensory neurons more closely than acute cultures in terms of their (transcriptional) identity is currently unknown.” (page 5). 

      We now also included a section “Limitations of the study” and bring this point up there as well and acknolwedge that longer culturing periods may cause changes in the neurons and may result in a drift away from their native state. 

      Nevertheless, our results clearly show that acute cultures have a response profile that is much more similar to damaged/”inflamed” neurons, irrespective of any comparison to the 3 daycultures. Therefore, we believe, it is helpful to include this data to make scientists aware that acute cultures are very different to non-inflamed native/in vivo DRG neurons that many researchers use in their experiments.

      (2) The authors state that there is a reduction in warmth-sensitive DRG neurons in the TRPM2 knockout mice based on the data presented in Figure 2D. This is not convincing for the following reasons. First, the authors used t-tests (with FDR correction - yielding borderline significance) whereas three groups are compared here in three repetitive stimuli. This would require different statistics (e.g. ANOVA), and I am not convinced (based on a rapid assessment of the data) that such an analysis would yield any significant difference between WT and TRPM2 KO. Second, there seems to be a discrepancy between the plot and legend regarding the number of LOV analysed (21, 17, and 18 FOV according to the legend, compared to 18, 10, and 12 dots in the plot). Therefore, I would urge the authors to critically assess this part of the study and to reconsider whether the statement (and discussion) that "Trpm2 deletion reduces the proportion of warmth responders" should be maintained or abandoned. . 

      Yes, we agree that the statistical tests indicated by the referee are more appropriate/robust for the data shown in Figures 1F, 2D, and 4G.

      When we perform 2-way repeated measures ANOVA and subsequent multiple comparison test (with Dunnets correction) against Wildtype, for data shown in Fig. 2D, both the main effect (Genotype) and the interaction term (Stimulus x Genotype) are significant. The multiple comparison yields very similar result as in the current manuscript, with the difference that the TRPM2-KO data for the second stimulus (~36°C) is borderline significant (with a p-value of p=0.050).

      Due to the possible dependence of the repeated temperature stimuli and the variability of each stimulus between FOVs (Fig. 2C), it is possible that a mixed-effect model that accounts for these effects is more appropriate. 

      Similarly, for plots 1F and 4G, Genotype (either as main effect or as interaction with Time) is significant after a repeated measures two-way ANOVA. The multiple comparisons (with Bonferroni correction) only changed the results marginally at individual timepoints, without affecting the overall conclusions. The exception is Fig. 4G at 38°C, where the interaction of Time and Genotype is significant, but no individual timepoint-comparison is significant after Bonferroni correction.

      The main difference between the results presented above and the ones presented in the manuscript is the choice of the multiple comparison correction. We originally opted for the falsediscovery rate (FDR) approach as it is less prone to Type II errors (false negatives) than other methods such as Sidaks or Bonferroni, particularly when correcting for a large number of tests.

      However, we are mainly interested in whether the genotypes differ in their behavior in each temperature combination and the significant ANOVA tests for Fig. 1F and 4G support that point. The statistical test and comparison used in the original/previous version of the manuscript, comparing behavior at individual/distinct timepoints, are interesting, but less relevant (and potentially distracting), as we do not go into the details about the behavior at any given/distinct timepoint in the assay.

      Therefore, and per suggestion of the reviewer, we have updated the statistics in the revised version of the manuscript. Also, we now report the correct number of FOVs in the legend. The statistical details are now found in the legends of the respective figures.

      (3) It remains unclear whether the clear behavioral effect seen in the TRPM2 knockout animals is at all related to TRPM2 functioning as a warmth sensor in sensory neurons. As discussed above, the effects of the TRPM2 KO on the proportion of warmth-sensing neurons are at most very subtle, and the authors did not use any pharmacological tool (in contrast to the use of capsaicin to probe for TRPV1 in Figures S3 and S4) to support a direct involvement of TRPM2 in the neuronal warmth responses. Behavioral experiments on sensory-neuron-specific TRPM2 knockout animals will be required to clarify this important point

      As mentioned above, we have toned down the correlation between the cellular and behavioral data. 

      In the discussion we now clearly describe three possibilities as to why the Trpm2 knockout animals only show a subtle cellular thermal phenotype but a strong behavioral thermal preference phenotype: (i) permanent deletion of Trpm2 may result in developmental defects and/or compensatory mechanisms; (ii) The DRG population expressing Trpm2 may be more relevant for autonomic thermoregulation rather than behavioral responses to temperature; (iii) Trpm2 expression outside DRGs (possibly in the hypothalamic POA) may account for the altered thermal behavior. 

      (4) The authors only use male mice, which is a significant limitation, especially considering known differences in warmth sensing between male and female animals and humans. The authors state "For this study, only male animals were used, as we aimed to compare our results with previous studies which exclusively used male animals (7, 8, 17, 43)." This statement is not correct: all four mentioned papers include behavioral data from both male and female mice! I recommend the authors to either include data from female mice or to clearly state that their study (in comparison with these other studies) only uses male mice.  

      This is a valid point -- when our study started 7-8 years ago, we only used male mice (as did many other researchers) and this we would now do differently. We have now newly included a statement concerning this limitation in the “Limitations of this study” section of the manuscript. 

      Nevertheless, in the studies by Tan et al. And Vandevauw et al. only male animals were used for the behavioral experiments. Yarmolinsky et al.  And Paricio-Montesinons et al. used both males and females while, as far as we can tell, only Paricio-Montesions et al. Reported that no difference was observed between the sexes. 

      Wildtypes are all C57bl/6N from the provider Janvier. Generally, all lines are backcrossed to C57bl/6 mice and additionally inbreeding was altered every 4-6 generations by crossing to C57bl/6. Exactly how many times the Trp channel KOs have been backcrossed to C57bl/6 mice we cannot exactly state.

      Reviewer #2 (Public Review): 

      Summary: 

      The authors of the study use a technically well-thought-out approach to dissect the question of how far TRPV1 and TRPM2 are involved in the perception of warm temperatures in mice. They supplement the experimental data with a drift-diffusion model. They find that TRPM2 is required to trigger the preference for 31{degree sign}C over warmer temperatures while TRPV1 increases the fidelity of afferent temperature information. A lack of either channel leads to a depletion of warm-sensing neurons and in the case of TRPV1 to a deficit in rapid responses to temperature changes. The study demonstrates that mouse phenotyping can only produce trustworthy results if the tools used to test them measure what we believe they are measuring. 

      Strengths: 

      The authors tackle a central question in physiology to which we have not yet found sufficient answers. They take a pragmatic approach by putting existing experimental methods to the test and refining them significantly. 

      Weaknesses: 

      It is difficult to find weaknesses. Not only the experimental methods but also the data analysis have been refined meticulously. There is no doubt that the authors achieved their aims and that the results support their conclusions. 

      There will certainly be some lasting impact on the future use of DRG cultures with respect to (I) the incubation periods, (II) how these data need to be analyzed, and (III) the numbers of neurons to be looked at. 

      As for the CPT assay, the future will have to show if mouse phenotyping results are more accurate with this technique. I'm more fond of full thermal gradient environments. However, behavioural phenotyping is still one of the most difficult fields in somatosensory research.  

      We thank the referee and were happy to read that the referee finds our study valuable and insightful. 

      Reviewer #3 (Public Review):  

      Summary and strengths: 

      In the manuscript, Abd El Hay et al investigate the role of thermally sensitive ion channels TRPM2 and TRPV1 in warm preference and their dynamic response features to thermal stimulation. They develop a novel thermal preference task, where both the floor and air temperature are controlled, and conclude that mice likely integrate floor with air temperature to form a thermal preference. They go on to use knockout mice and show that TRPM2-/- mice play a role in the avoidance of warmer temperatures. Using a new approach for culturing DRG neurons they show the involvement of both channels in warm responsiveness and dynamics. This is an interesting study with novel methods that generate important new information on the different roles of TRPV1 and TRPM2 on thermal behavior. 

      Open questions and weaknesses: 

      (1) Differences in the response features of cells expressing TRPM2 and TRPV1 are central and interesting findings but need further validation (Figures 3 and 4). To show differences in the dynamics and the amplitude of responses across different lines and stimulus amplitudes more clearly, the authors should show the grand average population calcium response from all responsive neurons with error bars for all 3 groups for the different amplitudes of stimuli (as has been presented for the thermal stimuli traces). The authors should also provide a population analysis of the amplitude of the responses in all groups to all stimulus amplitudes. Prior work suggests that thermal detection is supported by an enhancement or suppression of the ongoing activity of sensory fibers innervating the skin. The authors should present any data on cells with ongoing activity. 

      We have now included grand average population analysis of the different groups in the revised version, this is found in Figure 2E and F. Based on the referee’s suggestion and the new analysis, we now can report a (subtle) cellular phenotype observed in DRG cultures of Trpm2 deficient animals: when averaging all warmth responses, the new analysis suggests that Trpm2-deficient cultures lack modulation of the response magnitude across the three increasing consecutive warmth stimuli (33°C, 36°C and 39°C).

      Concerning the point about ongoing activity: We are not sure if it is possible in neuronal cultures to faithfully recapitulate ongoing activity. Ongoing activity has been mostly recorded in skinnerve preparations (or in older studies in other types of nerve recordings) and there are only very few studies that show ongoing activity in cultured neurons and in those instances the ongoing activity only starts in sensory neuron cultures when cultured for even longer time periods than 3 days (Ref.: doi: 10.1152/jn.00158.2018). We have very few cells that show some spontaneous activity, but these are too few to draw any conclusions. In any case, nerve fibers might be necessary to drive ongoing activity which are absent from our cultures.

      (2) The authors should better place their findings in context with the literature and highlight the novelty of their findings. The introduction builds a story of a 'disconnect' or 'contradictory' findings about the role of TRPV1 and TRPM2 in warm detection. While there are some disparate findings in the literature, Tan and McNaughton (2016) show a role for TRPM2 in the avoidance of warmth in a similar task, Paricio et al. (2020) show a significant reduction in warm perception in TRPM2 and TRPV1 knock out lines and Yarmolinksy et al. (2016) show a reduction in warm perception with TRPV1 inactivation. All these papers are therefore in agreement with the authors finding of a role for these channels in warm behavior. The authors should change their introduction and discussion to more correctly discuss the findings of these studies and to better pinpoint the novelty of their own work.  

      Paricio-Montesinos et al. argue that TRPM8 is crucial for the detection of warmth, as TRPM8KO animals are incapable of learning the operant task. TRPM2-KO animals and, to a smaller extent TRPV1-KO animals, have reduced sensitivity in the task, but are still capable of learning/performing the task. However, in our chamber preference assay this is reversed: TRPM2-KO animals lose the ability to differentiate warm temperatures while TRPM8 appears to play no major role. A commonality between the two studies is that while TRPV1 affects the detection of warm temperatures in the different assays, this ion channel appears not to be crucial. 

      Similarly, Yarmolinsky et al. show that Trpv1-inactivation only increases the error rate in their operant assay (from ~10% to ~30%), without testing TRPM2. And Tan et al. show the importance of TRPM2 in the preference task, without testing for TRPV1. 

      More generally, the choice of the assay, being either an operant task (Paricio-Montesinos et al. and Yarmolinsky et al.) or a preference assay without training of the mice (Tan et al. and our data here), might be important and different TRP receptors may be relevant for different types of temperature assays, which we have now included at the end of the discussion section in the revised manuscript. While our results generally agree with the previous studies, they add a different perspective on the analysis of the behavior (with correlation to cellular data). We now edited the manuscript to highlight the advances more clearly. 

      Nevertheless, we believe that a discrepancy between cellular and behavioral data in the former studies exists and we kept this in the introduction. We hope that our data and suggestions of more nuanced analysis of cellular and behavioral responses, in particular also differences in their kinetics, may be helping to guide future studies.  

      (3) The responses of 60 randomly selected cells are shown in Figure 2B. But, looking at the TRPM2-/- data, warm responses appear more obvious than in WTs and the weaker responders of the WT group appear weaker than the equivalent group in the TRPV1-/- and TRPM2-/- data. This does not necessarily invalidate the results, but it may suggest a problem in the data selection. Because the correct classification of warm-sensitive neurons is central to this part of the study more validation of the classifier should be presented. For example, the authors could state if they trained the classifier using equal amounts of cells, show some randomly selected cells that are warm-insensitive for all genotypes, and show the population average responses of warm-insensitive neurons.  

      The classifier was trained on a balanced dataset of 1000 (500 responders and 500 nonresponders), manually labelled traces across all 5 temperature stimuli. The prediction accuracy was 98%. We have now described more clearly how the classifier was trained (See Materials and Methods) and include examples of responders and non-responders, the population averages of each class as well as a confusion matrix of the classification in the revised manuscript (Suppl. Figure 4A and B).

      (4) The interpretation of the main behavioral results and justification of the last figure is presented as the result of changes in sensing but differences in this behavior could be due to many factors and this needs clarification and discussion. (i) The authors mention that 'crucially temperature perception is not static' and suggest that there are fluctuating changes in perception over time and conclude that their modelling approach helps show changes in temperature detection. They imply that temperature perceptual threshold changes over time, but the mouse could just as easily have had exactly the same threshold throughout the task but their motivation (or some other cognitive variable) might vary causing them to change chamber. The authors should correct this. (ii) Likewise, from their fascinating and high-profile prior work the authors suggest a model of internal temperature sensing whereby TRPM2 expression in the hypothalamus acts as an internal sensory of body temperature. Given this, and the slow time course of the behavior in chambers with different ambient temperatures, couldn't the reason for the behavioral differences be due to central changes in hypothalamic processing rather than detection by skin temperature? If TRPM2-/- were selectively ablated from the skin or the hypothalamus (these experiments are not necessary for this paper) it might be possible to conclude whether sensation or body temperature is more likely the root cause of these effects but, without further experiments it is tough to conclude either way. (iii) Because the ambient temperature is controlled in this behavior, another hypothesis is that warm avoidance could be due to negative valence associated with breathing warm air, i.e. a result of sensation within the body in internal pathways, rather than sensing from the external skin. Overall, the authors should tone down conclusions about sensation and present a more detailed discussion of these points.  

      We are sorry that the statement including the phrase “crucially temperature perception is not static” was ambiguous; We have now deleted this statement and instead included different possibilities as to why mice may switch from one chamber to the other stochastically. 

      As the referee mentioned, it is possible that some other variable (motivation etc.) makes the mouse change the chamber; Nevertheless, we hypothesize that this variable (whatever it might be) is still modulated by temperature (at least this would be the likeliest explanation that we see).

      As for the aspect of internal/hypothalamic temperature sensing and its dependence on Trpm2: we have included this possibility in the discussion in the manuscript. 

      As for the point of negative valence mediated by breathing in warm air: yes, presumably this could also be possible. The aspect of valence is in interesting aspect by itself: would the mice be rather repelled from the (uncomfortable) hot plate or more attracted to the (more comfortable) thermoneutral plate, or both? Something to elucidate in a different study.

      (5) It is an excellent idea to present a more in-depth analysis of the behavioral data collected during the preference task, beyond 'the mouse is on one side or the other'. However, the drift-diffusion approach is complex to interpret from the text in the results and the figures. The results text is not completely clear on which behavioral parameters are analyzed and terms like drift, noise, estimate, and evidence are not clearly defined. Currently, this section of the paper slightly confuses and takes the paper away from the central findings about dynamics and behavioral differences. It seems like they could come to similar conclusions with simpler analysis and simpler figures. 

      We have now reassessed the description of the drift diffusion model and explain it more clearly, this can be found on page 5 – 8. We have considered whether it will be better to introduce the drift diffusion model at the beginning of the study, subsequent to Figure 1 but we believe this to better suited at the end, because, indeed, the cellular results (and differences in kinetic response parameters observed in DRG cultures of Trpv1 KO mice) prompted us to assess the behavior in this way. Thus, the order of experiments presented here, represents also more the natural path the study took. 

      (6) In Figure 2D the % of warm-sensitive neurons are shown for each genotype. Each data point is a field of view, however, reading the figure legend there appear to be more FOVs than data points (eg 10 data points for the TRPV1-/- but 17 FOVs). The authors should check this. 

      We have checked and corrected the number of FOVs mentioned in the legend, and the number shown in the Figure 2D and its legend are now in agreement. 

      (7) Can the authors comment on why animals with over-expression of TRPV1 spend more time in the warmest chamber to start with at 38C and not at 34C?  

      This is an interesting observation that we did not consider before. A closer look at Figure 4H reveals that the majority of the TRPV1-OX animals, have a proportionally long first visit to the 38°C room. We can only speculate why this is the case. We cannot rule out that this a technical shortcoming of the assay and how we conduced it – but we did not observe this for the wildtype mice, thus it is rather unlikely a technical problem. It is possible that this is a type of “freezing-” (or “startle-“) behavior when the animals first encounter the 38°C temperature. Freezing behaviors in mice can be observed when sudden/threatening stimuli are applied. It is possible that, in the TRPV1-overexpressing animals, the initial encounter with 38°C leads to activation of a larger proportion of cells (compared to WT controls), possibly signaling a “threatening” stimulus, and thus leading to this startle effect. However, such a claim would require additional experiments to test such a hypothesis more rigorously.

    1. Author response:

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

      eLife Assessment

      This study presents valuable findings on the potential of short-movie viewing fMRI protocol to explore the functional and topographical organization of the visual system in awake infants and toddlers. Although the data are compelling given the difficulty of studying this population, the evidence presented is incomplete and would be strengthened by additional analyses to support the authors' claims. This study will be of interest to cognitive neuroscientists and developmental psychologists, especially those interested in using fMRI to investigate brain organisation in pediatric and clinical populations with limited fMRI tolerance.

      We are grateful for the thorough and thoughtful reviews. We have provided point-bypoint responses to the reviewers’ comments, but first, we summarize the major revisions here. We believe these revisions have substantially improved the clarity of the writing and impact of the results.

      Regarding the framing of the paper, we have made the following major changes in response to the reviews:

      (1) We have clarified that our goal in this paper was to show that movie data contains topographic, fine-grained details of the infant visual cortex. In the revision, we now state clearly that our results should not be taken as evidence that movies could replace retinotopy and have reworded parts of the manuscript that could mislead the reader in this regard.

      (2) We have added extensive details to the (admittedly) complex methods to make them more approachable. An example of this change is that we have reorganized the figure explaining the Shared Response Modelling methods to divide the analytic steps more clearly.

      (3) We have clarified the intermediate products contributing to the results by adding 6 supplementary figures that show the gradients for each IC or SRM movie and each infant participant.

      In response to the reviews, we have conducted several major analyses to support our findings further:

      (1) To verify that our analyses can identify fine-grained organization, we have manually traced and labeled adult data, and then performed the same analyses on them. The results from this additional dataset validate that these analyses can recover fine-grained organization of the visual cortex from movie data.

      (2) To further explore how visual maps derived from movies compare to alternative methods, we performed an anatomical alignment control analysis. We show that high-quality maps can be predicted from other participants using anatomical alignment.

      (3) To test the contribution of motion to the homotopy analyses, we regressed out the motion effects in these analyses. We found qualitatively similar results to our main analyses, suggesting motion did not play a substantial role.

      (4) To test the contribution of data quantity to the homotopy analyses, we correlated the amount of movie data collected from each participant with the homotopy results. We did not find a relationship between data quantity and the homotopy results. 

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      Ellis et al. investigated the functional and topographical organization of the visual cortex in infants and toddlers, as evidenced by movie-viewing data. They build directly on prior research that revealed topographic maps in infants who completed a retinotopy task, claiming that even a limited amount of rich, naturalistic movie-viewing data is sufficient to reveal this organization, within and across participants. Generating this evidence required methodological innovations to acquire high-quality fMRI data from awake infants (which have been described by this group, and elsewhere) and analytical creativity. The authors provide evidence for structured functional responses in infant visual cortex at multiple levels of analyses; homotopic brain regions (defined based on a retinotopy task) responded more similarly to one another than to other brain regions in visual cortex during movie-viewing; ICA applied to movie-viewing data revealed components that were identifiable as spatial frequency, and to a lesser degree, meridian maps, and shared response modeling analyses suggested that visual cortex responses were similar across infants/toddlers, as well as across infants/toddlers and adults. These results are suggestive of fairly mature functional response profiles in the visual cortex in infants/toddlers and highlight the potential of movie-viewing data for studying finer-grained aspects of functional brain responses, but further evidence is necessary to support their claims and the study motivation needs refining, in light of prior research.

      Strengths:

      - This study links the authors' prior evidence for retinotopic organization of visual cortex in human infants (Ellis et al., 2021) and research by others using movie-viewing fMRI experiments with adults to reveal retinotopic organization (Knapen, 2021).

      - Awake infant fMRI data are rare, time-consuming, and expensive to collect; they are therefore of high value to the community. The raw and preprocessed fMRI and anatomical data analyzed will be made publicly available.

      We are grateful to the reviewer for their clear and thoughtful description of the strengths of the paper, as well as their helpful outlining of areas we could improve.

      Weaknesses:

      - The Methods are at times difficult to understand and in some cases seem inappropriate for the conclusions drawn. For example, I believe that the movie-defined ICA components were validated using independent data from the retinotopy task, but this was a point of confusion among reviewers. 

      We acknowledge the complexity of the methods and wish to clarify them as best as possible for the reviewers and the readers. We have extensively revised the methods and results sections to help avoid potential misunderstandings. For instance, we have revamped the figure and caption describing the SRM pipeline (Figure 5).

      To answer the stated confusion directly, the ICA components were derived from the movie data and validated on the (completely independent) retinotopy data. There were no additional tasks. The following text in the paper explains this point:

      “To assess the selected component maps, we correlated the gradients (described above) of the task-evoked and component maps. This test uses independent data: the components were defined based on movie data and validated against task-evoked retinotopic maps.” Pg. 11

      In either case: more analyses should be done to support the conclusion that the components identified from the movie reproduce retinotopic maps (for example, by comparing the performance of movie-viewing maps to available alternatives (anatomical ROIs, group-defined ROIs). 

      Before addressing this suggestion, we want to restate our conclusions: features of the retinotopic organization of infant visual cortex could be predicted from movie data. We did not conclude that movie data could ‘reproduce’ retinotopic maps in the sense that they would be a replacement. We recognize that this was not clear in our original manuscript and have clarified this point throughout, including in this section of the discussion:

      “To be clear, we are not suggesting that movies work well enough to replace a retinotopy task when accurate maps are needed. For instance, even though ICA found components that were highly correlated with the spatial frequency map, we also selected some components that turned out to have lower correlations. Without knowing the ground truth from a retinotopy task, there would be no way to weed these out. Additionally, anatomical alignment (i.e., averaging the maps from other participants and anatomically aligning them to a held-out participant) resulted in maps that were highly similar to the ground truth. Indeed, we previously[23] found that adult-defined visual areas were moderately similar to infants. While functional alignment with adults can outperform anatomical alignment methods in similar analyses[27], here we find that functional alignment is inferior to anatomical alignment. Thus, if the goal is to define visual areas in an infant that lacks task-based retinotopy, anatomical alignment of other participants’ retinotopic maps is superior to using movie-based analyses, at least as we tested it.” Pg. 21

      As per the reviewer’s suggestion and alluded to in the paragraph above, we have created anatomically aligned visual maps, providing an analogous test to the betweenparticipant analyses like SRM. We find that these maps are highly similar to the ground truth. We describe this result in a new section of the results:

      “We performed an anatomical alignment analog of the functional alignment (SRM) approach. This analysis serves as a benchmark for predicting visual maps using taskbased data, rather than movie data, from other participants. For each infant participant, we aggregated all other infant or adult participants as a reference. The retinotopic maps from these reference participants were anatomically aligned to the standard surface template, and then averaged. These averages served as predictions of the maps in the test participant, akin to SRM, and were analyzed equivalently (i.e., correlating the gradients in the predicted map with the gradients in the task-based map). These correlations (Table S4) are significantly higher than for functional alignment (using infants to predict spatial frequency, anatomical alignment > functional alignment: ∆<sub>Fisher Z</sub> M=0.44, CI=[0.32–0.58], p<.001; using infants to predict meridians, anatomical alignment > functional alignment: ∆<sub>Fisher Z</sub> M=0.61, CI=[0.47–0.74], p<.001; using adults to predict spatial frequency, anatomical alignment > functional alignment: ∆<sub>Fisher Z</sub> M=0.31, CI=[0.21–0.42], p<.001; using adults to predict meridians, anatomical alignment > functional alignment: ∆<sub>Fisher Z</sub> M=0.49, CI=[0.39–0.60], p<.001). This suggests that even if SRM shows that movies can be used to produce retinotopic maps that are significantly similar to a participant, these maps are not as good as those that can be produced by anatomical alignment of the maps from other participants without any movie data.” Pg. 16–17

      Also, the ROIs used for the homotopy analyses were defined based on the retinotopic task rather than based on movie-viewing data alone - leaving it unclear whether movie-viewing data alone can be used to recover functionally distinct regions within the visual cortex.

      We agree with the reviewer that our approach does not test whether movie-viewing data alone can be used to recover functionally distinct regions. The goal of the homotopy analyses was to identify whether there was functional differentiation of visual areas in the infant brain while they watch movies. This was a novel question that provides positive evidence that these regions are functionally distinct. In subsequent analyses, we show that when these areas are defined anatomically, rather than functionally, they also show differentiated function (e.g., Figure 2). Nonetheless, our intention was not to use the homotopy analyses to define the regions. We have added text to clarify the goal and novelty of this analysis.

      “Although these analyses cannot define visual maps, they test whether visual areas have different functional signatures.” Pg. 6

      Additionally, even if the goal were to define areas based on homotopy, we believe the power of that analysis would be questionable. We would need to use a large amount of the movie data to define the areas, leaving a low-powered dataset to test whether their function is differentiated by these movie-based areas.

      - The authors previously reported on retinotopic organization of the visual cortex in human infants (Ellis et al., 2021) and suggest that the feasibility of using movie-viewing experiments to recover these topographic maps is still in question. They point out that movies may not fully sample the stimulus parameters necessary for revealing topographic maps/areas in the visual cortex, or the time-resolution constraints of fMRI might limit the use of movie stimuli, or the rich, uncontrolled nature of movies might make them inferior to stimuli that are designed for retinotopic mapping, or might lead to variable attention between participants that makes measuring the structure of visual responses across individuals challenging. This motivation doesn't sufficiently highlight the importance or value of testing this question in infants. Further, it's unclear if/how this motivation takes into account prior research using movie-viewing fMRI experiments to reveal retinotopic organization in adults (e.g., Knapen, 2021). Given the evidence for retinotopic organization in infants and evidence for the use of movie-viewing experiments in adults, an alternative framing of the novel contribution of this study is that it tests whether retinotopic organization is measurable using a limited amount of movie-viewing data (i.e., a methodological stress test). The study motivation and discussion could be strengthened by more attention to relevant work with adults and/or more explanation of the importance of testing this question in infants (is the reason to test this question in infants purely methodological - i.e., as a way to negate the need for retinotopic tasks in subsequent research, given the time constraints of scanning human infants?).

      We are grateful to the reviewer for giving us the opportunity to clarify the innovations of this research. We believe that this research contributes to our understanding of how infants process dynamic stimuli, demonstrates the viability and utility of movie experiments in infants, and highlights the potential for new movie-based analyses (e.g., SRM). We have now consolidated these motivations in the introduction to more clearly motivate this work:

      “The primary goal of the current study is to investigate whether movie-watching data recapitulates the organization of visual cortex. Movies drive strong and naturalistic responses in sensory regions while minimizing task demands[12, 13, 24] and thus are a proxy for typical experience. In adults, movies and resting-state data have been used to characterize the visual cortex in a data-driven fashion[25–27]. Movies have been useful in awake infant fMRI for studying event segmentation[28], functional alignment[29], and brain networks[30]. However, this past work did not address the granularity and specificity of cortical organization that movies evoke. For example, movies evoke similar activity in infants in anatomically aligned visual areas[28], but it remains unclear whether responses to movie content differ between visual areas (e.g., is there more similarity of function within visual areas than between31). Moreover, it is unknown whether structure within visual areas, namely visual maps, contributes substantially to visual evoked activity. Additionally, we wish to test whether methods for functional alignment can be used with infants. Functional alignment finds a mapping between participants using functional activity – rather than anatomy – and in adults can improve signal-to-noise, enhance across participant prediction, and enable unique analyses[27, 32–34].” Pg. 3-4

      Furthermore, the introduction culminates in the following statement on what the analyses will tell us about the nature of movie-driven activity in infants:

      “These three analyses assess key indicators of the mature visual system: functional specialization between areas, organization within areas, and consistency between individuals.” Pg. 5

      Furthermore, in the discussion we revisit these motivations and elaborate on them further:

      [Regarding homotopy:] “This suggests that visual areas are functionally differentiated in infancy and that this function is shared across hemispheres[31].” Pg. 19

      [Regarding ICA:] “This means that the retinotopic organization of the infant brain accounts for a detectable amount of variance in visual activity, otherwise components resembling these maps would not be discoverable.” Pg. 19–20

      [Regarding SRM:] “This is initial evidence that functional alignment may be useful for enhancing signal quality, like it has in adults[27,32,33], or revealing changing function over development[45].” Pg. 21

      Additionally, we have expanded our discussion of relevant work that uses similar methods such as the excellent research from Knapen (2021) and others:

      “In adults, movies and resting-state data have been used to characterize the visual cortex in a data-driven fashion[25-27].” Pg. 4

      “We next explored whether movies can reveal fine-grained organization within visual areas by using independent components analysis (ICA) to propose visual maps in individual infant brains[25,26,35,42,43].” Pg. 9

      Reviewer #2 (Public Review):

      Summary:

      This manuscript shows evidence from a dataset with awake movie-watching in infants, that the infant brain contains areas with distinct functions, consistent with previous studies using resting state and awake task-based infant fMRI. However, substantial new analyses would be required to support the novel claim that movie-watching data in infants can be used to identify retinotopic areas or to capture within-area functional organization.

      Strengths:

      The authors have collected a unique dataset: the same individual infants both watched naturalistic animations and a specific retinotopy task. These data position the authors to test their novel claim, that movie-watching data in infants can be used to identify retinotopic areas.

      Weaknesses:

      To claim that movie-watching data can identify retinotopic regions, the authors should provide evidence for two claims:

      - Retinotopic areas defined based only on movie-watching data, predict retinotopic responses in independent retinotopy-task-driven data.

      - Defining retinotopic areas based on the infant's own movie-watching response is more accurate than alternative approaches that don't require any movie-watching data, like anatomical parcellations or shared response activation from independent groups of participants.

      We thank the reviewer for their comments. Before addressing their suggestions, we wish to clarify that we do not claim that movie data can be used to identify retinotopic areas, but instead that movie data captures components of the within and between visual area organization as defined by retinotopic mapping. We recognize that this was not clear in our original manuscript and have clarified this point throughout, including in this section of the discussion:

      “To be clear, we are not suggesting that movies work well enough to replace a retinotopy task when accurate maps are needed. For instance, even though ICA found components that were highly correlated with the spatial frequency map, we also selected some components that turned out to have lower correlations. Without knowing the ground truth from a retinotopy task, there would be no way to weed these out. Additionally, anatomical alignment (i.e., averaging the maps from other participants and anatomically aligning them to a held-out participant) resulted in maps that were highly similar to the ground truth. Indeed, we previously[23] found that adult-defined visual areas were moderately similar to infants. While functional alignment with adults can outperform anatomical alignment methods in similar analyses[27], here we find that functional alignment with infants is inferior to anatomical alignment. Thus, if the goal is to define visual areas in an infant that lacks task-based retinotopy, anatomical alignment of other participants’ retinotopic maps is superior to using movie-based analyses, at least as we tested it.” Pg. 21

      In response to the reviewer’s suggestion, we compare the maps identified by SRM to the averaged, anatomically aligned maps from infants. We find that these maps are highly similar to the task-based ground truth and we describe this result in a new section:

      “We performed an anatomical alignment analog of the functional alignment (SRM) approach. This analysis serves as a benchmark for predicting visual maps using taskbased data, rather than movie data, from other participants. For each infant participant, we aggregated all other infant or adult participants as a reference. The retinotopic maps from these reference participants were anatomically aligned to the standard surface template, and then averaged. These averages served as predictions of the maps in the test participant, akin to SRM, and were analyzed equivalently (i.e., correlating the gradients in the predicted map with the gradients in the task-based map). These correlations (Table S4) are significantly higher than for functional alignment (using infants to predict spatial frequency, anatomical alignment < functional alignment: ∆<sub>Fisher Z</sub> M=0.44, CI=[0.32–0.58], p<.001; using infants to predict meridians, anatomical alignment < functional alignment: ∆<sub>Fisher Z</sub> M=0.61, CI=[0.47–0.74], p<.001; using adults to predict spatial frequency, anatomical alignment < functional alignment: ∆<sub>Fisher Z</sub> M=0.31, CI=[0.21–0.42], p<.001; using adults to predict meridians, anatomical alignment < functional alignment: ∆<sub>Fisher Z</sub> M=0.49, CI=[0.39–0.60], p<.001). This suggests that even if SRM shows that movies can be used to produce retinotopic maps that are significantly similar to a participant, these maps are not as good as those that can be produced by anatomical alignment of the maps from other participants without any movie data.” Pg. 16–17

      Note that we do not compare the anatomically aligned maps with the ICA maps statistically. This is because these analyses are not comparable: ICA is run withinparticipant whereas anatomical alignment is necessarily between-participant — either infant or adults. Nonetheless, an interested reader can refer to the Table where we report the results of anatomical alignment and see that anatomical alignment outperforms ICA in terms of the correlation between the predicted and task-based maps.

      Both of these analyses are possible, using the (valuable!) data that these authors have collected, but these are not the analyses that the authors have done so far. Instead, the authors report the inverse of (1): regions identified by the retinotopy task can be used to predict responses in the movies. The authors report one part of (2), shared responses from other participants can be used to predict individual infants' responses in the movies, but they do not test whether movie data from the same individual infant can be used to make better predictions of the retinotopy task data, than the shared response maps.

      So to be clear, to support the claims of this paper, I recommend that the authors use the retinotopic task responses in each individual infant as the independent "Test" data, and compare the accuracy in predicting those responses, based on:

      -  The same infant's movie-watching data, analysed with MELODIC, when blind experimenters select components for the SF and meridian boundaries with no access to the ground-truth retinotopy data.

      -  Anatomical parcellations in the same infant.

      -  Shared response maps from groups of other infants or adults.

      -  (If possible, ICA of resting state data, in the same infant, or from independent groups of infants).

      Or, possibly, combinations of these techniques.

      If the infant's own movie-watching data leads to improved predictions of the infant's retinotopic task-driven response, relative to these existing alternatives that don't require movie-watching data from the same infant, then the authors' main claim will be supported.

      These are excellent suggestions for additional analyses to test the suitability for moviebased maps to replace task-based maps. We hope it is now clear that it was never our intention to claim that movie-based data could replace task-based methods. We want to emphasize that the discoveries made in this paper — that movies evoke fine-grained organization in infant visual cortex — do not rely on movie-based maps being better than alternative methods for producing maps, such as the newly added anatomical alignment.

      The proposed analysis above solves a critical problem with the analyses presented in the current manuscript: the data used to generate maps is identical to the data used to validate those maps. For the task-evoked maps, the same data are used to draw the lines along gradients and then test for gradient organization. For the component maps, the maps are manually selected to show the clearest gradients among many noisy options, and then the same data are tested for gradient organization. This is a double-dipping error. To fix this problem, the data must be split into independent train and test subsets.

      We appreciate the reviewer’s concern; however, we believe it is a result of a miscommunication in our analytic strategy. We have now provided more details on the analyses to clarify how double-dipping was avoided. 

      To summarize, a retinotopy task produced visual maps that were used to trace both area boundaries and gradients across the areas. These data were then fixed and unchanged, and we make no claims about the nature of these maps in this paper, other than to treat them as the ground truth to be used as a benchmark in our analyses. The movie data, which are collected independently from the same infant in the session, used the boundaries from the retinotopy task (in the case of homotopy) or were compared with the maps from the retinotopy task (in the case of ICA and SRM). In other words, the statement that “the data used to generate maps is identical to the data used to validate those maps” is incorrect because we generated the maps with a retinotopy task and validated the maps with the movie data. This means no double dipping occurred.

      Perhaps a cause of the reviewer’s interpretation is that the gradients used in the analysis are not clearly described. We now provide this additional description:  “Using the same manually traced lines from the retinotopy task, we measured the intensity gradients in each component from the movie-watching data. We can then use the gradients of intensity in the retinotopy task-defined maps as a benchmark for comparison with the ICA-derived maps.” Pg. 10

      Regarding the SRM analyses, we take great pains to avoid the possibility of data contamination. To emphasize how independent the SRM analysis is, the prediction of the retinotopic map from the test participant does not use their retinotopy data at all; in fact, the predicted maps could be made before that participant’s retinotopy data were ever collected. To make this prediction for a test participant, we need to learn the inversion of the SRM, but this only uses the movie data of the test participant. Hence, there is no double-dipping in the SRM analyses. We have elaborated on this point in the revision, and we remade the figure and its caption to clarify this point:

      We also have updated the description of these results to emphasize how double-dipping was avoided:

      “We then mapped the held-out participant's movie data into the learned shared space without changing the shared space (Figure 5c). In other words, the shared response model was learned and frozen before the held-out participant’s data was considered.

      This approach has been used and validated in prior SRM studies[45].” Pg. 14

      The reviewer suggests that manually choosing components from ICA is double-dipping. Although the reviewer is correct that the manual selection of components in ICA means that the components chosen ought to be good candidates, we are testing whether those choices were good by evaluating those components against the task-based maps that were not used for the ICA. Our statistical analyses evaluate whether the components chosen were better than the components that would have been chosen by random chance. Critically: all decisions about selecting the components happen before the components are compared to the retinotopic maps. Hence there is no double-dipping in the selection of components, as the choice of candidate ICA maps is not informed by the ground-truth retinotopic maps. We now clarify what the goal of this process is in the results:

      “Success in this process requires that 1) retinotopic organization accounts for sufficient variance in visual activity to be identified by ICA and 2) experimenters can accurately identify these components.” Pg. 10

      The reviewer also alludes to a concern that the researcher selecting the maps was not blind to the ground-truth retinotopic maps from participants and this could have influenced the results. In such a scenario, the researcher could have selected components that have the gradients of activity in the places that the infant has as ground truth. The researcher who made the selection of components (CTE) is one of the researchers who originally traced the areas in the participants approximately a year prior to the identification of ICs. The researcher selecting the components didn’t use the ground-truth retinotopic maps as reference, nor did they pay attention to the participant IDs when sorting the IC components. Indeed, they weren’t trying to find participant specific maps per se, but rather aimed to find good candidate retinotopic maps in general. In the case of the newly added adult analyses, the ICs were selected before the retinotopic mapping was reviewed or traced; hence, no knowledge about the participant-specific ground truth could have influenced the selection of ICs. Even with this process from adults, we find results of comparable strength as we found in infants, as shown below. Nonetheless, there is a possibility that this researcher’s previous experience of tracing the infant maps could have influenced their choice of components at the participant-specific level. If so, it was a small effect since the components the researcher selected were far from the best possible options (i.e., rankings of the selected components averaged in the 64th percentile for spatial frequency maps and the 68th percentile for meridian maps). We believe all reasonable steps were taken to mitigate bias in the selection of ICs.

      Reviewer #3 (Public Review):

      The manuscript reports data collected in awake toddlers recording BOLD while watching videos. The authors analyse the BOLD time series using two different statistical approaches, both very complex but do not require any a priori determination of the movie features or contents to be associated with regressors. The two main messages are that 1) toddlers have occipital visual areas very similar to adults, given that an SRM model derived from adult BOLD is consistent with the infant brains as well; 2) the retinotopic organization and the spatial frequency selectivity of the occipital maps derived by applying correlation analysis are consistent with the maps obtained by standard and conventional mapping.

      Clearly, the data are important, and the author has achieved important and original results. However, the manuscript is totally unclear and very difficult to follow; the figures are not informative; the reader needs to trust the authors because no data to verify the output of the statistical analysis are presented (localization maps with proper statistics) nor so any validation of the statistical analysis provided. Indeed what I think that manuscript means, or better what I understood, may be very far from what the authors want to present, given how obscure the methods and the result presentation are.

      In the present form, this reviewer considers that the manuscript needs to be totally rewritten, the results presented each technique with appropriate validation or comparison that the reader can evaluate.

      We are grateful to the reviewer for the chance to improve the paper. We have broken their review into three parts: clarification of the methods, validation of the analyses, and enhancing the visualization.

      Clarification of the methods

      We acknowledge that the methods we employed are complex and uncommon in many fields of neuroimaging. That said, numerous papers have conducted these analyses on adults (Beckman et al., 2005; Butt et al., 2015; Guntupalli et al., 2016; Haak & Beckman, 2018; Knapen, 2021; Lu et al., 2017) and non-human primates (Arcaro & Livingstone, 2017; Moeller et al., 2009). We have redoubled our efforts in the revision to make the methods as clear as possible, expanding on the original text and providing intuitions where possible. These changes have been added throughout and are too vast in number to repeat here, especially without context, but we hope that readers will have an easier time following the analyses now. 

      Additionally, we updated Figures 3 and 5 in which the main ICA and SRM analyses are described. For instance, in Figure 3’s caption we now add details about how the gradient analyses were performed on the components: 

      “We used the same lines that were manually traced on the task-evoked map to assess the change in the component’s response. We found a monotonic trend within area from medial to lateral, just like we see in the ground truth.” Pg. 11

      Regarding Figure 5, we reconsidered the best way to explain the SRM analyses and decided it would be helpful to partition the diagram into steps, reflecting the analytic process. These updates have been added to Figure 5, and the caption has been updated accordingly.

      We hope that these changes have improved the clarity of the methods. For readers interested in learning more, we encourage them to either read the methods-focused papers that debut the analyses (e.g., Chen et al., 2015), read the papers applying the methods (e.g., Guntupalli et al., 2016), or read the annotated code we publicly release which implements these pipelines and can be used to replicate the findings.

      Validation of the analyses

      One of the requests the reviewer makes is to validate our analyses. Our initial approach was to lean on papers that have used these methods in adults or primates (e.g., Arcaro, & Livingstone, 2017; Beckman et al., 2005; Butt et al., 2015; Guntupalli et al., 2016; Haak & Beckman, 2018; Knapen, 2021; Moeller et al., 2009) where the underlying organization and neurophysiology is established. However, we have made changes to these methods that differ from their original usage (e.g., we used SRM rather than hyperalignment, we use meridian mapping rather than traveling wave retinotopy, we use movie-watching data rather than rest). Hence, the specifics of our design and pipeline warrant validation. 

      To add further validation, we have rerun the main analyses on an adult sample. We collected 8 adult participants who completed the same retinotopy task and a large subset of the movies that infants saw. These participants were run under maximally similar conditions to infants (i.e., scanned using the same parameters and without the top of the head-coil) and were preprocessed using the same pipeline. Given that the relationship between adult visual maps and movie-driven (or resting-state) analyses has been shown in many studies (Beckman et al., 2005; Butt et al., 2015; Guntupalli et al., 2016; Haak & Beckman, 2018; Knapen, 2021; Lu et al., 2017), these adult data serve as a validation of our analysis pipeline. These adult participants were included in the original manuscript; however, they were previously only used to support the SRM analyses (i.e., can adults be used to predict infant visual maps). The adult results are described before any results with infants, as a way to engender confidence. Moreover, we have provided new supplementary figures of the adult results that we hope will be integrated with the article when viewing it online, such that it will be easy to compare infant and adult results, as per the reviewer’s request. 

      As per the figures and captions below, the analyses were all successful with the adult participants: 1) Homotopic correlations are higher than correlations between comparable areas in other streams or areas that are more distant within stream. 2) A multidimensional scaling depiction of the data shows that areas in the dorsal and ventral stream are dissimilar. 3) Using independent components analysis on the movie data, we identified components that are highly correlated with the retinotopy task-based spatial frequency and meridian maps. 4) Using shared response modeling on the movie data, we predicted maps that are highly correlated with the retinotopy task-based spatial frequency and meridian maps.

      These supplementary analyses are underpowered for between-group comparisons, so we do not statistically compare the results between infants and adults. Nonetheless, the pattern of adult results is comparable overall to the infant results. 

      We believe these adult results provide a useful validation that the infant analyses we performed can recover fine-grained organization.

      Enhancing the visualization

      The reviewer raises an additional concern about the lack of visualization of the results. We recognize that the plots of the summary statistics do not provide information about the intermediate analyses. Indeed, we think the summary statistics can understate the degree of similarity between the components or predicted visual maps and the ground truth. Hence, we have added 6 new supplementary figures showing the intensity gradients for the following analyses: 1. spatial frequency prediction using ICA, 2. meridian prediction using ICA, 3. spatial frequency prediction using infant SRM, 4. meridian prediction using infant SRM, 5. spatial frequency prediction using adult SRM, and 6. meridian prediction using adult SRM.

      We hope that these visualizations are helpful. It is possible that the reviewer wishes us to also visually present the raw maps from the ICA and SRM, akin to what we show in Figure 3A and 3B. We believe this is out of scope of this paper: of the 1140 components that were identified by ICA, we selected 36 for spatial frequency and 17 for meridian maps. We also created 20 predicted maps for spatial frequency and 20 predicted meridian maps using SRM. This would result in the depiction of 93 subfigures, requiring at least 15 new full-page supplementary figures to display with adequate resolution. Instead, we encourage the reader to access this content themselves: we have made the code to recreate the analyses publicly available, as well as both the raw and preprocessed data for these analyses, including the data for each of these selected maps.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      (1) As mentioned in the public review, the authors should consider incorporating relevant adult fMRI research into the Introduction and explain the importance of testing this question in infants.

      Our public response describes the several citations to relevant adult research we have added, and have provided further motivation for the project.

      (2) The authors should conduct additional analyses to support their conclusion that movie data alone can generate accurate retinotopic maps (i.e., by comparing this approach to other available alternatives).

      We have clarified in our public response that we did not wish to conclude that movie data alone can generate accurate retinotopic maps, and have made substantial edits to the text to emphasize this. Thus, because this claim is already not supported by our analyses, we do not think it is necessary to test it further.

      (3) The authors should re-do the homotopy analyses using movie-defined ROIs (i.e., by splitting the movie-viewing data into independent folds for functional ROI definition and analyses).

      As stated above, defining ROIs based on the movie content is not the intended goal of this project. Even if that were the general goal, we do not believe that it would be appropriate to run this specific analysis with the data we collected. Firstly, halving the data for ROI definition (e.g., using half the movie data to identify and trace areas, and then use those areas in the homotopy analysis to run on the other half of data) would qualitatively change the power of the analyses described here. Secondly, we would be unable to define areas beyond hV4/V3AB with confidence, since our retinotopic mapping only affords specification of early visual cortex. Thus we could not conduct the MDS analyses shown in Figure 2.

      (4) If the authors agree that a primary contribution of this study and paper is to showcase what is possible to do with a limited amount of movie-viewing data, then they should make it clearer, sooner, how much usable movie data they have from infants. They could also consider conducting additional analyses to determine the minimum amount of fMRI data necessary to reveal the same detailed characteristics of functional responses in the visual cortex.

      We agree it would be good to highlight the amount of movie data used. When the infant data is first introduced in the results section, we now state the durations:

      “All available movies from each session were included (Table S2), with an average duration of 540.7s (range: 186--1116s).” Pg. 5

      Additionally, we have added a homotopy analysis that describes the contribution of data quantity to the results observed. We compare the amount of data collected with the magnitude of same vs. different stream effect (Figure 1B) and within stream distance effect (Figure 1C). We find no effect of movie duration in the sample we tested, as reported below:

      “We found no evidence that the variability in movie duration per participant correlated with this difference [of same stream vs. different stream] (r=0.08, p=.700).” Pg. 6-7

      “There was no correlation between movie duration and the effect (Same > Adjacent: r=-0.01, p=.965, Adjacent > Distal: r=-0.09, p=.740).” Pg. 7

      (5) If any of the methodological approaches are novel, the authors should make this clear. In particular, has the approach of visually inspecting and categorizing components generated from ICA and movie data been done before, in adults/other contexts?

      The methods we employed are similar to others, as described in the public review.

      However, changes were necessary to apply them to infant samples. For instance, Guntupalli et al. (2016) used hyperalignment to predict the visual maps of adult participants, whereas we use SRM. SRM and hyperalignment have the same goal — find a maximally aligned representation between participants based on brain function — but their implementation is different. The application of functional alignment to infants is novel, as is their use in movie data that is relatively short by comparison to standard adult data. Indeed, this is the most thorough demonstration that SRM — or any functional alignment procedure — can be usefully applied to infant data, awake or sleeping. We have clarified this point in the discussion.

      “This is initial evidence that functional alignment may be useful for enhancing signal quality, like it has in adults[27,32,33], or revealing changing function over development[45], which may prove especially useful for infant fMRI[52].” Pg. 21

      (6) The authors found that meridian maps were less identifiable from ICA and movie data and suggest that this may be because these maps are more susceptible to noise or gaze variability. If this is the case, you might predict that these maps are more identifiable in adult data. The authors could consider running additional analyses with their adult participants to better understand this result.

      As described in the manuscript, we hypothesize that meridian maps are more difficult to identify than spatial frequency maps because meridian maps are a less smooth, more fine-grained map than spatial frequency. Indeed, it has previously been reported (Moeller et al., 2009) that similar procedures can result in meridian maps that are constituted by multiple independent components (e.g., a component sensitive to horizontal orientations, and a separate component sensitive to vertical components). Nonetheless, we have now conducted the ICA procedure on adult participants and again find it is easier to identify spatial frequency components compared to meridian maps, as reported in the public review.

      Minor corrections:

      (1) Typo: Figure 3 title: "Example retintopic task vs. ICA-based spatial frequency maps.".

      Fixed

      (2) Given the age range of the participants, consider using "infants and toddlers"? (Not to diminish the results at all; on the contrary, I think it is perhaps even more impressive to obtain awake fMRI data from ~1-2-year-olds). Example: Figure 3 legend: "A) Spatial frequency map of a 17.1-monthold infant.".

      We agree with the reviewer that there is disagreement about the age range at which a child starts being considered a toddler. We have changed the terms in places where we refer to a toddler in particular (e.g., the figure caption the reviewer highlights) and added the phrase “infants and toddlers” in places where appropriate. Nonetheless, we have kept “infants” in some places, particularly those where we are comparing the sample to adults. Adding “and toddlers” could imply three samples being compared which would confuse the reader.

      (3) Figure 6 legend: The following text should be omitted as there is no bar plot in this figure: "The bar plot is the average across participants. The error bar is the standard error across participants.".

      Fixed

      (4) Table S1 legend: Missing first single quote: Runs'.

      Fixed

      Reviewer #2 (Recommendations For The Authors):

      I request that this paper cite more of the existing literature on the fMRI of human infants and toddlers using task-driven and resting-state data. For example, early studies by (first authors) Biagi, Dehaene-Lambertz, Cusack, and Fransson, and more recent studies by Chen, Cabral, Truzzi, Deen, and Kosakowski.

      We have added several new citations of recent task-based and resting state studies to the second sentence of the main text:

      “Despite the recent growth in infant fMRI[1-6], one of the most important obstacles facing this research is that infants are unable to maintain focus for long periods of time and struggle to complete traditional cognitive tasks[7].”

      Reviewer #3 (Recommendations For The Authors):

      In the following, I report some of my main perplexities, but many more may arise when the material is presented more clearly.

      The age of the children varies from 5 months to about 2 years. While the developmental literature suggests that between 1 and 2 years children have a visual system nearly adult-like, below that age some areas may be very immature. I would split the sample and perhaps attempt to validate the adult SRM model with the youngest children (and those can be called infants).

      We recognize the substantial age variability in our sample, which is why we report participant-specific data in our figures. While splitting up the data into age bins might reveal age effects, we do not think we can perform adequately powered null hypothesis testing of the age trend. In order to investigate the contribution of age, larger samples will be needed. That said, we can see from the data that we have reported that any effect of age is likely small. To elaborate: Figures 4 and 6 report the participant-specific data points and order the participants by age. There are no clear linear trends in these plots, thus there are no strong age effects.

      More broadly, we do not think there is a principled way to divide the participants by age. The reviewer suggests that the visual system is immature before the first year of life and mature afterward; however, such claims are the exact motivation for the type of work we are doing here, and the verdict is still out. Indeed, the conclusion of our earlier work reporting retinotopy in infants (Ellis et al., 2021) suggests that the organization of the early visual cortex in infants as young as 5 months — the youngest infant in our sample — is surprisingly adult-like.

      The title cannot refer to infants given the age span.

      There is disagreement in the field about the age at which it is appropriate to refer to children as infants. In this paper, and in our prior work, we followed the practice of the most attended infant cognition conference and society, the International Congress of Infant Studies (ICIS), which considers infants as those aged between 0-3 years old, for the purposes of their conference. Indeed, we have never received this concern across dozens of prior reviews for previous papers covering a similar age range. That said, we understand the spirit of the reviewer’s comment and now refer to the sample as “infants and toddlers” and to older individuals in our sample as “toddlers” wherever it is appropriate (the younger individuals would fairly be considered “infants” under any definition).

      Figure 1 is clear and an interesting approach. Please also show the average correlation maps on the cortical surface.

      While we would like to create a figure as requested, we are unsure how to depict an area-by-area correlation map on the cortical surface. One option would be to generate a seed-based map in which we take an area and depict the correlation of that seed (e.g., vV1) with all other voxels. This approach would result in 8 maps for just the task-defined areas, and 17 maps for anatomically-defined areas. Hence, we believe this is out of scope of this paper, but an interested reader could easily generate these maps from the data we have released.

      Figure 2 results are not easily interpretable. Ventral and dorsal V1-V3 areas represent upper or lower VF respectively. Higher dorsal and ventral areas represent both upper and lower VF, so we should predict an equal distance between the two streams. Again, how can we verify that it is not a result of some artifacts?

      In adults, visual areas differ in their functional response properties along multiple dimensions, including spatial coding. The dorsal/ventral stream hypothesis is derived from the idea that areas in each stream support different functions, independent of spatial coding. The MDS analysis did not attempt to isolate the specific contribution of spatial representations of each area but instead tested the similarity of function that is evoked in naturalistic viewing. Other covariance-based analyses specifically isolate the contribution of spatial representations (Haak et al., 2013); however, they use a much more constrained analysis than what was implemented here. The fact that we find broad differentiation of dorsal and ventral visual areas in infants is consistent with adults (Haak & Beckman, 2018) and neonate non-human primates (Arcaro & Livingstone, 2017). 

      Nonetheless, we recognize that we did not mention the differences in visual field properties across areas and what that means. If visual field properties alone drove the functional response then we would expect to see a clustering of areas based on the visual field they represent (e.g., hV4 and V3AB should have similar representations). Since we did not see that, and instead saw organization by visual stream, the result is interesting and thus warrants reporting. We now mention this difference in visual fields in the manuscript to highlight the surprising nature of the result.

      “This separation between streams is striking when considering that it happens despite differences in visual field representations across areas: while dorsal V1 and ventral V1 represent the lower and upper visual field, respectively, V3A/B and hV4 both have full visual field maps. These visual field representations can be detected in adults[41]; however, they are often not the primary driver of function[39]. We see that in infants too: hV4 and V3A/B represent the same visual space yet have distinct functional profiles.” Pg. 8

      The reviewer raises a concern that the MDS result may be spurious and caused by noise. Below, we present three reasons why we believe these results are not accounted for by artifacts but instead reflect real functional differentiation in the visual cortex. 

      (1) Figure 2 is a visualization of the similarity matrix presented in Figure S1. In Figure S1, we report the significance testing we performed to confirm that the patterns differentiating dorsal and ventral streams — as well as adjacent areas from distal areas — are statistically reliable across participants. If an artifact accounted for the result then it would have to be a kind of systematic noise that is consistent across participants.

      (2) One of the main sources of noise (both systematic and non-systematic) with infant fMRI is motion. Homotopy is a within-participant analysis that could be biased by motion. To assess whether motion accounts for the results, we took a conservative approach of regressing out the framewise motion (i.e., how much movement there is between fMRI volumes) from the comparisons of the functional activity in regions. Although the correlations numerically decreased with this procedure, they were qualitatively similar to the analysis that does not regress out motion:

      “Additionally, if we control for motion in the correlation between areas --- in case motion transients drive consistent activity across areas --- then the effects described here are negligibly different (Figure S5).” Pg. 7

      (3) We recognize that despite these analyses, it would be helpful to see what this pattern looks like in adults where we know more about the visual field properties and the function of dorsal and ventral streams. This has been done previously (e.g., Haak & Beckman, 2018), but we have now run those analyses on adults in our sample, as described in the public review. As with infants, there are reliable differences in the homotopy between streams (Figure S1). The MDS results show that the adult data was more complex than the infant data, since it was best described by 3 dimensions rather than 2. Nonetheless, there is a rotation of the MDS such that the structure of the ventral and dorsal streams is also dissociable. 

      Figure 3 also raises several alternative interpretations. The spatial frequency component in B has strong activity ONLY at the extreme border of the VF and this is probably the origin of the strong correlation. I understand that it is only one subject, but this brings the need to show all subjects and to report the correlation. Also, it is important to show the putative average ICA for retinotopy and spatial frequencies across subjects and for adults. All methods should be validated on adults where we have clear data for retinotopy and spatial frequency.

      The reviewer notes that the component in Figure 3 shows strong negative response in the periphery. It is often the case, as reported elsewhere (Moeller et al., 2009), that ICA extracts portions of visual maps. To make a full visual map would require combining components into a composite (e.g., a component that has a high response in the periphery and another component that has a high response in the fovea). If we were to claim that this component, or others like it, could replace the need for retinotopic mapping, then we would want to produce these composite maps; however, our conclusion in this project is that the topographic information of retinotopic maps manifest in individual components of ICA. For this purpose, the analysis we perform adequately assesses this topography.

      Regarding the request to show the results for all subjects, we address this in the public response and repeat it here briefly: we have added 6 new figures to show results akin to Figure 3C and D. It is impractical to show the equivalent of Figure 3A and B for all participants, yet we do release the data necessary to see to visualize these maps easily.

      Finally, the reviewer suggests that we validate the analyses on adult participants. As shown in Figure S3 and reported in the public response, we now run these analyses on adult participants and observe qualitatively similar results to infants.

      How much was the variation in the presumed spatial frequency map? Is it consistent with the acuity range? 5-month-old infants should have an acuity of around 10c/deg, depending on the mean luminance of the scene.

      The reviewer highlights an important weakness of conducting ICA: we cannot put units on the degree of variation we see in components. We now highlight this weakness in the discussion:

      “Another limitation is that ICA does not provide a scale to the variation: although we find a correlation between gradients of spatial frequency in the ground truth and the selected component, we cannot use the component alone to infer the spatial frequency selectivity of any part of cortex. In other words, we cannot infer units of spatial frequency sensitivity from the components alone.” Pg. 20

      Figure 5 pipeline is totally obscure. I presumed that I understood, but as it is it is useless. All methods should be clearly described, and the intermediate results should be illustrated in figures and appropriately discussed. Using such blind analyses in infants in principle may not be appropriate and this needs to be verified. Overall all these techniques rely on correlation activities that are all biased by head movement, eye movement, and probably the dummy sucking. All those movements need to be estimated and correlated with the variability of the results. It is a strong assumption that the techniques should work in infants, given the presence of movements.

      We recognize that the SRM methods are complex. Given this feedback, we remade Figure 5 with explicit steps for the process and updated the caption (as reported in the public review).

      Regarding the validation of these methods, we have added SRM analyses from adults and find comparable results. This means that using these methods on adults with comparable amounts of data as what we collected from infants can predict maps that are highly similar to the real maps. Even so, it is not a given that these methods are valid in infants. We present two considerations in this regard. 

      First, as part of the SRM analyses reported in the manuscript, we show that control analyses are significantly worse than the real analyses (indicated by the lines on Figure 6). To clarify the control analysis: we break the mapping (i.e., flip the order of the data so that it is backwards) between the test participant and the training participants used to create the SRM. The fact that this control analysis is significantly worse indicates that SRM is learning meaningful representations that matter for retinotopy. 

      Second, we believe that this paper is a validation of SRM for infants. Infant fMRI is a nascent field and SRM has the potential to increase the signal quality in this population. We hope that readers will see these analyses as a proof of concept that SRM can be used in their work with infants. We have stated this contribution in the paper now.

      “Additionally, we wish to test whether methods for functional alignment can be used with infants. Functional alignment finds a mapping between participants using functional activity -- rather than anatomy -- and in adults can improve signal-to-noise, enhance across participant prediction, and enable unique analyses[27,32-34].” Pg. 4

      “This is initial evidence that functional alignment may be useful for enhancing signal quality, like it has in adults[27,32,33], or revealing changing function over development[45].” Pg. 21

      Regarding the reviewer’s concern that motion may bias the results, we wish to emphasize the nature of the analyses being conducted here: we are using data from a group of participants to predict the neural responses in a held-out participant. For motion to explain consistency between participants, the motion would need to be timelocked across participants. Even if motion was time-locked during movie watching, motion will impair the formation of an adequate model that can contain retinotopic information. Thus, motion should only hurt the ability for a shared response to be found that can be used for predicting retinotopic maps. Hence, the results we observed are despite motion and other sources of noise.

      What is M??? is it simply the mean value??? If not, how it is estimated?

      M is an abbreviation for mean. We have now expanded the abbreviation the first time we use it.

      Figure 6 should be integrated with map activity where the individual area correlation should be illustrated. Probably fitting SMR adult works well for early cortical areas, but not for more ventral and associative, and the correlation should be evaluated for the different masks.

      With the addition of plots showing the gradients for each participant and each movie (Figures S10–S13) we hope we have addressed this concern. We additionally want to clarify that the regions we tested in the analysis in Figure 6 are only the early visual areas V1, V2, V3, V3A/B, and hV4. The adult validation analyses show that SRM works well for predicting the visual maps in these areas. Nonetheless, it is an interesting question for future research with more extensive retinotopic mapping in infants to see if SRM can predict maps beyond extrastriate cortex.

      Occipital masks have never been described or shown.

      The occipital mask is from the MNI probabilistic structural atlas (Mazziotta et al., 2001), as reported in the original version and is shared with the public data release. We have added the additional detail that the probabilistic atlas is thresholded at 0% in order to be liberally inclusive. 

      “We used the occipital mask from the MNI structural atlas[63] in standard space -- defined liberally to include any voxel with an above zero probability of being labelled as the occipital lobe -- and used the inverted transform to put it into native functional space.” Pg. 27–28

      Methods lack the main explanation of the procedures and software description.

      We hope that the additions we have made to address this reviewer’s concerns have provided better explanations for our procedures. Additionally, as part of the data and code release, we thoroughly explain all of the software needed to recreate the results we have observed here.

    1. 赏析

      尼古拉斯·普桑(Nicolas Poussin)的《维纳斯将武器赠予埃涅阿斯》(Venus Presenting Arms to Aeneas)是一幅充满古典主义风格的杰作,描绘了罗马神话中维纳斯(Venus)为她的儿子埃涅阿斯(Aeneas)提供火神伏尔甘(Vulcan)打造的武器的场景。要赏析这幅画,我们可以从以下几个方面入手:

      1. 主题与叙事:

      这幅画取材于维吉尔(Virgil)的史诗《埃涅阿斯纪》(Aeneid)。故事讲述了特洛伊英雄埃涅阿斯在特洛伊陷落后,受命运的指引,率领幸存者前往意大利建立新的家园,最终成为罗马人的祖先。在旅途中,他受到了维纳斯的庇护。为了帮助儿子完成使命,维纳斯请求火神伏尔甘为他打造了一套精良的武器,包括盾牌、剑和盔甲。

      普桑选择描绘的正是维纳斯将这些神兵利器交给埃涅阿斯的瞬间。这个场景象征着神祇对英雄的支持,预示着埃涅阿斯肩负的重大使命。

      2. 构图与布局:

      • 稳定而平衡的构图: 普桑以其严谨的构图著称,这幅画也不例外。画面采用水平和垂直的线条进行分割,营造出一种稳定而平衡的视觉效果。人物的排列和姿态都经过精心设计,形成了一种和谐的构图关系。
      • 中心人物的突出: 维纳斯和埃涅阿斯位于画面的中心位置,是视觉的焦点。维纳斯伸出手臂,将武器递给埃涅阿斯,这一动作突出了她作为赠予者的角色。埃涅阿斯则以接受的姿态站在维纳斯面前,体现了他对母亲的敬意和对神助的感激。
      • 人物的群组安排: 画面中的其他人物,如小爱神丘比特(Cupid)和其他神祇,被巧妙地安排在维纳斯和埃涅阿斯周围,形成不同的群组,丰富了画面的层次感。

      3. 人物形象与表现:

      • 古典理想化的形象: 普桑深受古典艺术的影响,他笔下的人物形象都具有古典雕塑般的庄重和典雅。人物的姿态和表情都经过理想化的处理,展现出一种高贵和完美的形象。
      • 维纳斯的优雅与母爱: 维纳斯被描绘成一位美丽而优雅的女神,她的姿态和表情都流露出母性的温柔和关爱。她伸出手臂的动作既是赠予,也是一种保护和祝福。
      • 埃涅阿斯的英雄气概: 埃涅阿斯则被描绘成一位英俊而威武的英雄,他的眼神坚定,姿态庄重,展现出他肩负重任的责任感和使命感。

      4. 色彩与光线:

      • 和谐而丰富的色彩: 普桑善于运用色彩,他在这幅画中运用了丰富而和谐的色彩,营造出一种典雅而庄重的氛围。画面中的色彩既有明亮的色调,也有深沉的色调,相互映衬,增强了画面的视觉效果。
      • 清晰而柔和的光线: 画面的光线清晰而柔和,照亮了主要人物,突出了他们的形象和表情。光线的运用也增强了画面的立体感和空间感。

      5. 背景与环境:

      画面的背景是一片开阔的 landscape,远处的山峦和天空营造出一种宁静而壮阔的氛围。背景的描绘不仅丰富了画面的内容,也烘托了主题,暗示了埃涅阿斯即将展开的伟大征程。

      总结:

      《维纳斯将武器赠予埃涅阿斯》是普桑古典主义风格的代表作,它以严谨的构图、理想化的人物形象、和谐的色彩和光线,以及丰富的文化内涵,展现了古典艺术的魅力。通过赏析这幅画,我们可以更好地理解普桑的艺术风格,以及古典主义艺术的特点。

      一些可以进一步思考的问题:

      • 这幅画是如何体现古典主义艺术的特点的?
      • 维纳斯和埃涅阿斯的形象是如何塑造的?
      • 画面的构图、色彩和光线是如何为主题服务的?
      • 这幅画在艺术史上的地位和影响是什么?

      通过以上分析,相信你能够更深入地欣赏这幅伟大的作品。

    1. Reviewer #2 (Public review):

      Summary:

      In this paper, the authors investigated the admixture history of domestic cattle since they were introduced into Iberia, by studying genomic data from 24 ancient samples dated to ~2000-8000 years ago and comparing them to modern breeds. They aimed to (1) characterize genomic variation of skeletal remains and concordance (or discordance) with morphological features; (2) test for hybridization between wild aurochs and domestic cattle; (3) test for correlation between genetic ancestry and stable isotope levels (which are indicative of ecological niche); and (4) test for previously hypothesized higher aurochs ancestry in a modern breed of fighting bulls.

      Strengths:

      Overall, this study collects valuable new data and tests several important hypotheses regarding the evolutionary history and genomic variation of domestic cattle in Iberia, such as admixture between domestic and wild populations, and correlation between genome-wide aurochs ancestry and aggressiveness.

      Weaknesses:

      Most conclusions are well supported by the data presented, with the strengths and caveats of each analysis clearly explained. The presence of admixed individuals in prehistorical periods strongly support hybridization between wild and domestic populations, although the evidence for sex-biased introgression and ecological niche sharing is relatively weak. Lastly, the authors presented convincing evidence for relatively constant aurochs ancestry across all modern breeds, including the Lidia breed that has been bred for aggressiveness for centuries.

      Major comments:

      As the authors pointed out, a major limitation of this study is uncertainty in the "population identity" for most sampled individuals (i.e., whether an individual belonged to the domesticated or wild herd when they were alive). Based on chronology, morphology and genetic data, it is clear the Mesolithic samples from the Artusia and Mendandia sites are bona fide aurochs, but the "population identities" of individuals from the other two sites are much less certain. Indeed, archeological and morphological evidence from El Portalon supports the presence of both domestic animals and wild aurochs, which is echoed by the inter-individual heterogeneity in genetic ancestry. Despite the strong evidence of hybridization, it is unclear whether these admixed individuals were raised in the domestic population or lived in the wild population and hunted, limiting the authors' ability to draw conclusions regarding the direction of gene flow.

      In general, detecting sex-bias admixture is an inherently challenging problem, especially given limited data. The differential ancestry proportions (estimated by f4 ratios) on autosomes and X chromosome are indicative of sex-biased hybridization and consistent with previous mtDNA results and other non-genetic data. However, as shown in Fig 3, the confidence intervals of X and autosomal estimates overlap for all but a couple of individuals, despite the overall trend of the point estimates. Moreover, even if there is significant difference, it only suggests existence of sex-bias but does not speak to the extent (unless further quantitative argument is made). Statements such as "it was mostly aurochs males who contributed wild ancestry to domestic herds" is too strong and may be interpreted as extreme bias. The authors did a good job noting the caveats of this analysis and down-toned the statement in the main text, but claims regarding sex-bias hybridization that use the phrase "mostly" in the abstract and discussion need to be further weakened.

      The stable isotope analysis is very under-powered, due to issues of categorization of wild vs domestic Bos, as discussed by the authors. Although the considerable overlap in stable isotope values between domestic and wild groups is consistent with shared ecological niche, but the absence of evidence (ie significant difference between groups) is not evidence of absence. Two alternative, non-mutually exclusive scenarios are (1) prevalent errors in classification of wild vs domestic individuals; (2) different ecological niches share similar isotope profiles. Thus, the claim "suggesting that wild and domesticated groups often did not occupy different niches in Iberia" is still too strong.

    2. Reviewer #3 (Public review):

      Summary:

      Günther and colleagues leverage ancient DNA data to track the genomic history of one of the most important farm animals (cattle) in Iberia, a region showing peculiarities both in terms of cultural practices as well as a climatic refugium during the LGM, the latter of which could have allowed the survival of endemic lineages. They document interesting trends of hybridisation with wild aurochs over the last 8-9 millennia, including a stabilisation of auroch ancestry ~4000 years ago, at ~20%, a time coincidental with the arrival of domestic horses from the Pontic steppe. Modern breeds such as the iconic Lidia used in bullfighting or bull running retain a comparable level of auroch ancestry.

      Strengths:

      The generation of ancient DNA data has been proven crucial to unravel the domestication history of traditional livestock, and this is challenging due to the environmental conditions of the Iberian peninsula, less favourable to DNA preservation. The authors leverage samples unearthed from key archaeological sites in Spain, including the karstic system of Atapuerca. Their results provide fresher insights into past management practices and permit characterisation of significant shifts in hybridization with wild aurochs.

      Comments on revisions:

      The authors have satisfactorily addressed my previous concerns. Last questions:

      - How many MCMC iterations were run for Structf4? Can they show the likelihood of the last 10% of MCMC iterations? The results seem way too different for K = 4 vs. K = 5, but only for moo014 and moo019.

      - I guess the authors also lack an "a" superindex in Table 1 for moo019.

      - That Gyu2-related ancestry appears systematically for K=5 suggests that the Caucasus-related ancestry was already present in the pool that led to domesticates. Is it not important to discuss the implications of this possibility, for future analyses?

      - If monophyletic, why choose between Bed3 and CPC98 if both could be combined as a single population to further reduce qpAdm and f4 confidence intervals?

      - Why not combine all auroch Iberian samples as a single population for testing gene flow from this whole group of samples to ancient Iberian cattle? Would be the resulting coverage still too low?

      - What is subindex 1 in the denominator of the f4 ratio (main methods)?

      Thanks for your efforts

    3. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      My main concern is the use of the 700K SNP dataset. This set of SNPs suffers from a heavy ascertainment bias, which can be seen in the PCA in the supplementary material where all the aurochs cluster in the center within the variation of cattle. Given the coverage of some of the samples, multiple individuals would have less than 10K SNP covered. The majority of these are unlikely to be informative here given that they would just represent fixed positions between taurine and indicine or SNPs mostly variable in milk cattle breeds. The authors would get a much better resolution (i.e. many more SNPs to work with their very low genome coverage data) using the 1000 bull genome project VCF data set:

      https://www.ebi.ac.uk/ena/browser/view/PRJEB42783 which based on whole genome resequencing data from many cattle. This will certainly help with improving the resolution of qpAdm and f4 analysis, which have huge confidence intervals in most cases. Right now some individuals have huge confidence intervals ranging from 0 to 80% auroch ancestry...

      We thank the reviewer for this suggestion. We repeated our analyses with a SNP panel from Run 6 of the 1000 Bulls project presented in Naval-Sanchez et al 2020. This panel reduced standard errors and narrowed down confidence intervals for the ancient samples. Another consequence is that more single-source qpAdm models can now be rejected highlighting the abundance of hybridization. For our comparison to modern breeds, we still use the 700K dataset as it provides a set of different modern European cattle breeds.

      I agree with the authors that qpAdm is likely to give quite a noisy estimate of ancestry here (likely explain part of the issue I mentioned above). Although qpAdm is good for model testing here for ancestry proportion the authors instead could use an explicit f4 ratio - this would allow them to specify a model which would make the result easier to interpret.

      We have added ancestry estimates from f4 ratios to the manuscript and display them together with qpAdm and Struct-f4 (as suggested by reviewer #3) in our new Table 1. We decided to keep all three different estimates to illustrate that results are not consistent for all analyses. An additional feature of qpAdm is the possibility that two source models can be rejected and additional ancestries can be identified.

      The interpretation of the different levels of allele sharing on X vs autosome being the result of sex-bias admixture is not very convincing. Could these differences simply be due to a low recombination rate on the X chromosome and/or lower effective population size, which would lead to less efficient purifying selection?

      Following this comment (and another comment referring to the X chromosome analysis by reviewer #2), we decided to remove sex bias from the title of our study and add more information on the caveats of this analysis. While estimating ancestry on the X chromosome can be difficult, we also add that our patterns are consistent with what has been suggested based on ancient mitochondrial data (Verdugo et al 2019). For Neolithic Anatolia, it has been suggested that the insemination of domestic cows by auroch bulls has been intentional or even ritual (Peters et al 2012). A recent parallel archaeogenomic study also concluded sex-biased introgression from autosomal, X-chromosomal and Y-chromosomal data (Rossi et al 2024). As our results are consistent with these previous studies as well as the lower differentiation of modern breeds on the X chromosome (da Fonseca et al 2019), we still consider the general pattern of our results valid even if the exact extent of sex bias is difficult to assess.

      The authors suggest that 2 pop model rejection in some domestic population might be due to indicine ancestry, this seems relatively straightforward to test.

      We had already performed this analysis of modeling their ancestry from three sources using qpAdm. The results are shown in Supplementary Table S6 and we now refer to this more explicitly in the text: “The presence of indicine ancestry can be confirmed in a qpAdm analysis using three sources resulting in fitting models for all breeds (Supplementary Table S6).”

      The first sentence of the paper is a bit long-winded, also dogs were domesticated before the emergence of farming societies.

      We rephrased the first sentence to “Domestication of livestock and crops has been the dominant and most enduring innovation of the transition from a hunter-gathering lifestyle to farming societies.”

      It would be good to be specific about the number of genomes and coverage info in the last paragraph of the intro.

      This information is included in the first paragraph of the results section and we decided to not duplicate the numbers in the preceding introduction paragraph to retain a flow for the readers.

      Reviewer #2 (Public Review):

      Summary:

      In this paper, the authors investigated the admixture history of domestic cattle since they were introduced into Iberia, by studying genomic data from 24 ancient samples dated to ~2000-8000 years ago and comparing them to modern breeds. They aimed to (1) test for introgression from (local) wild aurochs into domestic cattle; (2) characterize the pattern of admixture (frequency, extent, sex bias, directionality) over time; (3) test for correlation between genetic ancestry and stable isotope levels (which are indicative of ecological niche); and (4) test for the hypothesized higher aurochs ancestry in a modern breed of fighting bulls.

      Strengths:

      Overall, this study collects valuable new data that are useful for testing interesting hypotheses, such as admixture between domestic and wild populations, and correlation between genome-wide aurochs ancestry and aggressiveness.

      Thank you for highlighting the importance of our study and the potential of our dataset.

      Weaknesses:

      Most conclusions are partially supported by the data presented. The presence of admixed individuals in prehistorical periods supports the hypothesized introgression, although this conclusion needs to be strengthened with an analysis of potential contamination. The frequency, sex-bias, and directionality of admixture remain highly uncertain due to limitations of the data or issues with the analysis. There is considerable overlap in stable isotope values between domestic and wild groups, indicating a shared ecological niche, but variation in classification criteria for domestic vs wild groups and in skeletal elements sampled for measurements significantly weakens this claim. Lastly, the authors presented convincing evidence for relatively constant aurochs ancestry across all modern breeds, including the Lidia breed which has been bred for aggressiveness for centuries. My specific concerns are outlined below.

      Contamination is a common concern for all ancient DNA studies. Contamination by modern samples is perhaps unlikely for this specific study of ancient cattle, but there is still the possibility of cross-sample contamination. The authors should estimate and report contamination estimates for each sample (based on coverage of autosomes and sex chromosomes, or heterozygosity of Y or MT DNA). Such contamination estimates are particularly important to support the presence of individuals with admixed ancestry, as a domestic sample contaminated with a wild sample (or vice versa) could appear as an admixed individual.

      We thank the reviewer for this suggestion. Due to our low coverage data, we focused on estimating contamination from the mitochondrial data by implementing the approach used by Green et al (2008). We make the code for this step available on Github. While most samples displayed low levels of contamination, we identified one sample (moo013a) with a surprisingly high (~50%) level of contamination which was excluded from further analysis.

      A major limitation of this study is uncertainty in the "population identity" for most sampled individuals (i.e., whether an individual belonged to the domesticated or wild herd when they were alive). Based on chronology, morphology, and genetic data, it is clear the Mesolithic samples from the Artusia and Mendandia sites are bona fide aurochs, but the identities of individuals from the other two sites are much less certain. Indeed, archeological and morphological evidence from El Portalon supports the presence of both domestic animals and wild aurochs, which is echoed by the inter-individual heterogeneity in genetic ancestry. Based on results shown in Fig 1C and Fig 2 it seems that individuals moo017, moo020, and possibly moo012a are likely wild aurochs that had been hunted and brought back to the site by humans. Although the presence of individuals (e.g., moo050, moo019) that can only be explained by two-source models strongly supports that interbreeding happened (if cross-contamination is ruled out), it is unclear whether these admixed individuals were raised in the domestic population or lived in the wild population and hunted.

      The reviewer is pointing out an important topic, the unknown identity of the studied individuals. We have revised the text making clear that we do not know whether the individuals were hunted or herded. At the same time, their genomic ancestry speaks for itself showing that there was hybridization between wild and domestic and that different individuals carried different degrees of wild ancestry. In the revised version, we have added the unknown identity as well as the fact that our results can be affected by both, changes in human hunting and herding practices over time. Regardless of the exact identity of the individuals, our results can still be seen as (a) evidence for hybridization and (b) changes in human practices (hunting and/or herding) and their relationship to bovids over time.

      Such uncertainty in "population identity" limits the authors' ability to make conclusions regarding the frequency, sex bias, and directionality of gene flow between domestic and wild populations. For instance, the wide range of ancestry estimates in Neolithic and Chalcolithic samples could be interpreted as evidence of (1) frequent recent gene flow or (2) mixed practices of herding and hunting and less frequent gene flow. Similarly, the statement about "bidirection introgression" (on pages 8 and 11) is not directly supported by data. As the genomic, morphological, and isotope data cannot confidently classify an individual as belonging to the domesticated or wild population, it seems impossible to conclude the direction of gene flow (if by "bidirection introgression" the authors mean something other than "bidirectional gene flow", they need to clearly explain this before reaching the conclusion.)

      We have removed “bidirectional introgression” from the text and replaced it with the more neutral term “hybridization”. Furthermore, we used the revision to mention at several places in the text that it is not clear whether the sequenced individuals were hunted and herded and that the observed pattern likely reflects changes in both hunting and herding practices.

      The f4 statistics shown in Fig 3B are insufficient to support the claim regarding sex-biased hybridization, as the f4 statistic values are not directly comparable between the X chromosome and autosomes. Because the effective population size is different for the X chromosome and autosomes (roughly 3:4 for populations with equal numbers of males and females), the expected amount of drift is different, hence the fraction of allele sharing (f4) is expected to be different. In fact, the observation that moo004 whose autosomal genome can be modeled as 100% domestic ancestry still shows a higher f4 value for the X chromosome than autosomes hints at this issue. A more robust metric to test for sex-biased admixture is the admixture proportion itself, which can be estimated by qpAdm or f4-ratio (see Patterson et al 2012). However, even with this method, criticism has been raised (e.g., Lazaridis and Reich 2017; Pfennig and Lachance, 2023). In general, detecting sex-bias admixture is a tough problem.

      In response to this comment and another comment by reviewer #1, we decided to remove sex bias from the title. In the revised version of our study, we have now switched this analysis from f4 statistics to comparing f4 ratios between the X chromosome and autosomes (Figure 3). Furthermore, we have added more information on the caveats of this analysis citing the articles mentioned by the reviewer. At the same time, we highlight that our patterns are consistent with what has been suggested based on ancient mitochondrial data (Verdugo et al 2019). Unfortunately, the low coverage data does not allow to call Y chromosomal haplotypes which would also allow an analysis of the paternal lineage. But our results are consistent with additional examples from the literature: For Neolithic Anatolia, it has been suggested that the insemination of domestic cows by auroch bulls has been intentional or even ritual (Peters et al 2012) and there is a lower differentiation of modern breeds on the X chromosome (da Fonseca et al 2019). A recent parallel archaeogenomic study also concluded sex-biased introgression from autosomal, X-chromosomal and Y-chromosomal data (Rossi et al 2024). Similar to the broader hybridization signal, our interpretation does not depend on the estimates for single individuals as we describe the broader pattern. As our results are consistent with previous results based on other types of data, we still consider the general pattern of our results valid even if the exact extent of sex bias is difficult to assess.

      In general, the stable isotope analysis seems to be very underpowered, due to the issues of variation in classification criteria and skeletal sampling location discussed by the authors in supplementary material. The authors claimed a significant difference in stable nitrogen isotope between (inconsistently defined) domestic cattle and wild aurochs, but no figures or statistics are presented to support this claim. Please describe the statistical method used and the corresponding p-values. The authors can consider including a figure to better show the stable isotope results.

      In combination with updated tables, we have added a supplementary figure showing the stable isotope results (S9). In light of the reanalysis of the genetic data, we have reassessed the genetic models used to assign species in the stable isotope analysis. We have provided more details of the statistical methods used and the p-values are given in the supplementary materials. There is a significant difference in the nitrogen isotope values when comparing B. taurus and B. primigenius (identified on morphology) but no other comparisons are significant at the p = 0.05 threshold. The reviewer highlights what we have mentioned in the supplementary material regarding the varied skeletal elements used for stable isotope analysis and the difficulty of assigning a species identity (as this depends on what criteria are used; morphological or some kind of genetic threshold of ancestry). Indeed, how to identify the species is at the heart of the paper. Given that identity could be defined in many ways, we have used 3 different genetic models to reflect this and the morphological categories, to help explore different possible scenarios. The reviewer is correct to point out that some of this analysis is not helped by the variety of skeletal elements used, but we have been careful not to over-interpret the results. The only samples that have nitrogen values higher than one standard deviation from the mean are domestic cattle, so it is not unreasonable to suggest that only domestic cattle have high nitrogen isotope values.

      Reviewer #3 (Public Review):

      Summary:

      Günther and colleagues leverage ancient DNA data to track the genomic history of one of the most important farm animals (cattle) in Iberia, a region showing peculiarities both in terms of cultural practices as well as a climatic refugium during the LGM, the latter of which could have allowed the survival of endemic lineages. They document interesting trends of hybridisation with wild aurochs over the last 8-9 millennia, including a stabilisation of auroch ancestry ~4000 years ago, at ~20%, a time coincidental with the arrival of domestic horses from the Pontic steppe. Modern breeds such as the iconic Lidia used in bullfighting or bull running retain a comparable level of auroch ancestry.

      Strengths:

      The generation of ancient DNA data has been proven crucial to unravel the domestication history of traditional livestock, and this is challenging due to the environmental conditions of the Iberian peninsula, less favourable to DNA preservation. The authors leverage samples unearthed from key archaeological sites in Spain, including the karstic system of Atapuerca. Their results provide fresher insights into past management practices, and permit characterisation of significant shifts in hybridization with wild aurochs.

      We thank the reviewer for their positive assessment of our work and for highlighting the strength and potential of the study.

      Weaknesses:

      - Treatment of post-mortem damage: the base quality of nucleotide transitions was recalibrated down to a quality score of 2, but for 5bp from the read termini only. In some specimens (e.g. moo022), the damage seems to extend further. Why not use dedicated tools (e.g. mapDamage), or check the robustness by conditioning on nucleotide transversions?

      We agree that using such a non-standard data preparation approach requires some testing. Since our main analyses are all based on f statistics, we compared f4 statistics and f4 ratios of our rescaled base quality data with data only using transversion sites. While estimates are highly correlated, the data set reduced to transversions produces larger confidence intervals in f4 ratios due to the lower number of sites. Consequently, we decided to use the rescaled data for all analyses displayed in main figures. We also prefer not to perform reference based rescaling as implemented in mapDamage as it might be sensitive to mapping bias (Günther & Nettelblad 2019).

      - Their more solid analyses are based on qpAdm, but rely on two single-sample donor populations. As the authors openly discuss, it is unclear whether CPC98 is a good proxy for Iberian aurochs despite possibly forming a monophyletic clade (the number of analysed sites is simply too low to assess this monophyly; Supplementary Table S2). Additionally, it is also unclear whether Sub1 was a fully unadmixed domestic specimen, depleted of auroch ancestry. The authors seem to suggest themselves that sex-biased introgression may have already taken place in Anatolia ("suggesting that sex-biased processes already took place prior to the arrival of cattle to Iberia").

      We expanded the discussion on this topic but removed the analysis of whether European aurochs form a clade due to the low number of sites. We do highlight that a recent parallel study on aurochs genomes confirmed that Western European aurochs form a clade, probably even originating from an Iberian glacial refugium (Rossi et al 2024). Even if minor structure in the gene pool of European aurochs might affect our quantitative results, it should not drive the qualitative pattern. The same should be the case for Sub1 as our tests would detect additional European aurochs ancestry that was not present in Sub1. The corresponding paragraph now reads:

      “A limitation of this analysis is the availability of genomes that can be used as representatives of the source populations as we used German and British aurochs to represent western European aurochs ancestry and a single Anatolian Neolithic to represent the original domestic cattle that was introduced into Europe. Our Mesolithic Iberian aurochs contained too little endogenous DNA to be used as a proxy aurochs reference and all Neolithic and Chalcolithic samples estimated with predominantly aurochs ancestry (including the 2.7x genome of moo014) already carry low (but significant) levels of domestic ancestry. However, the fact that all of these aurochs samples carried P mitochondria strongly suggests that western European aurochs can be considered monophyletic. Furthermore, a recent parallel study also concluded that Western European aurochs all form a clade (27). The Anatolian Sub1 might also not be depleted of any European aurochs ancestry and could not fully represent the original European Neolithic gene pool as also indicated by qpAdm and Struct-f4 identifying small proportions of other Asian ancestries in some Iberian individuals.

      While these caveats should affect our quantitative estimates of European aurochs ancestry, they should not drive the qualitative pattern as our tests would still detect any excess European aurochs ancestry that was not present in Neolithic Anatolia.”

      Alternatively, I recommend using Struct-f4 as it can model the ancestry of all individuals together based on their f4 permutations, including outgroups and modern data, and without the need to define pure "right" and "left" populations such as CPC98 and Sub1. It should work with low-coverage data, and allows us to do f4-based MDS plots as well as to estimate ancestry proportions (including from ghost populations).

      We thank the reviewer for this suggestion. We added Struct-f4 as an analysis but observed that it would not converge in an individual-based analysis due to the low coverage of most of our samples. We added Struct-f4 results for samples with >0.1X to the new Table 1, the results are similar to the results obtained using f4 ratios and (to a lower degree) the qpAdm results.

      - In the admixture graph analyses (supplementary results), the authors use population groups based on a single sample. If these samples are pseudohaploidised (or if coverage is insufficient to estimate heterozygosity - and it is at least for moo004 and moo014), f3 values are biased, implying that the fitted graph may be wrong. The graph shown in Fig S7 is in fact hard to interpret. For example, the auroch Gyu2 from Anatolia but not the auroch CPC98 also from Anatolia received 62% of ancestry from North Africa? The Neolithic samples moo004 and moo014 also show the same shocking disparity. I would consider re-doing this analysis with more than a sample per population group

      There seems to be some confusion relating to the sample identity in these figures. CPC98 is British and not Anatolian while Gyu2 is from the Caucasus and not Anatolia which would explain why they are different. Furthermore, moo004 is mostly of domestic ancestry while, moo014 is mostly of European aurochs ancestry according to our other analyses, which should explain why they also behave differently in this analysis. To avoid confusion and since this is a supplementary analysis from which we are not drawing any major conclusions, we decided to remove the graphs and the analysis from the study.

      Recommendations for the authors:

      Reviewer #2 (Recommendations For The Authors):

      Fig 3A: The red regression line is misleading. It seems to show that the average aurochs ancestry fraction has been steadily decreasing since ~8000 years ago, but the "averaging" is not meaningful as not all samples necessarily represent domestic cattle remains and the sample size is rather small. In other words, the samples are just a small, random collection of domestic and wild animals, and the average ancestry is subject to large sampling noise. I would suggest removing the regression line (along with the associated confidence interval) in this figure. It would also be helpful to label the samples with their IDs and morphology in the plot for cross-reference with other figures. Also, it is said in the legend that "Modern Iberian breeds... are added around date 0 with some vertical jitter". Do the authors mean "horizontal jitter" instead?

      Thank you for noticing this! We have removed the regression line and corrected the figure legend.

      Fig 2 vs Fig 3A: are the error bars the same in these two plots? They seem to be highly similar, if not identical, but the legends read very differently ("95% confidence interval by block-jackknife vs. on standard error"). Please explain.

      The figure legends have been corrected.

      Fig 3B: What do the error bars in Fig 3B mean? 95% confidence interval or one standard error? Please clarify in the legend.

      We have removed this figure and replaced it with a different way of displaying the results (now Figure 3). We ensured that the error bars are displayed consistently across figures.

      According to the f4 statistics shown in Fig 1C and Fig 3B, moo012b carries a relatively high amount of domestic ancestry. How is this compatible with the observation in Fig 2 that this individual can be modeled with 100% aurochs (i.e., aurochs as the single source)? Does this simply reflect the low genome coverage?

      moo012b is indeed one of the lowest coverage samples in our has at <0.02x sequencing depth. Even in our revised analysis using more sites, there is a discrepancy between the results of f4 statistics and qpAdm (suggesting mostly domestic ancestry) and f4 ratio suggesting mostly aurochs ancestry (Figure 1C and Table 1). We believe that this highlights the sensitivity of different methods to assumptions about the relationships of sources and potential “outgroups” which might not be well resolvable with low coverage data and in the presence of potentially complex admixture. Our general results, however, do not depend on the estimates for single individuals as our interpretations are based on the general pattern.

      I don't fully understand the rationale behind the statement "However, at some point, the herding practices must have changed since modern Iberian breeds show approximately 20-25% aurochs ancestry". Can the stable ancestry fraction from 4000 years to the present (relative to the highly variable ancestry before) reflect of discontinuation of hunting rather than changes in herding practices?

      We agree that this statement was not justified here, we rephrased the sentence to “In fact, from the Bronze Age onwards, most estimates overlap with the approximately 25% aurochs ancestry in modern Iberian cattle” and generally tried to make the text more nuanced on the issue of herding and hunting practices.

      Reviewer #3 (Recommendations For The Authors):

      Thanks for this interesting piece of work. The results are clearly presented, and I have no additional concerns other than those reflected in the public report, except perhaps:

      (i) trying to use more informative sample names (eg. including the date and location). It may facilitate reading without going back and forth to the table "Sample List".

      We have now added a main table listing our post-Mesolithic samples together with their age, site and estimated aurochs ancestry proportions. We hope that his table makes it easier for readers to follow our sample IDs.

      (ii) Briefly describe in the main the age of aurochs and Sub1 not generated in this study.

      Fixed.

    1. Reviewer #2 (Public review):

      uORFs, short open reading frames located in the 5' UTR, are pervasive in genomes. However, their roles in maintaining protein abundance are not clear. In this study, the authors propose that uORFs act as "molecular dam", limiting the fluctuation of the translation of downstream coding sequences. First, they performed in silico simulations using an improved ICIER model, and demonstrated that uORF translation reduces CDS translational variability, with buffering capacity increasing in proportion to uORF efficiency, length, and number. Next, they analzed the translatome between two related Drosophila species, revealing that genes with uORFs exhibit smaller fluctuations in translation between the two species and across different developmental stages within the same specify. Moreover, they identified that bicoid, a critical gene for Drosophila development, contains a uORF with substantial changes in translation efficiency. Deleting this uORF in Drosophila melanogaster significantly affected its gene expression, hatching rates, and survival under stress condition. Lastly, by leveraging public Ribo-seq data, the authors showed that the buffering effect of uORFs is also evident between primates and within human populations. Collectively, the study advances our understanding of how uORFs regulate the translation of downstream coding sequences at the genome-wide scale, as well as during development and evolution.

      The conclusions of this paper are mostly well supported by data, but some definitions and data analysis need to be clarified and extended.

      (1) There are two definitions of translation efficiency (TE) in the manuscript: one refers to the number of 80S ribosomes that complete translation at the stop codon of a CDS within a given time interval, while the other is calculated based on Ribo-seq and mRNA-seq data (as described on Page 7, line 209). To avoid potential misunderstandings, please use distinct terms to differentiate these two definitions.

      (2) Page 7, line 209: "The translational efficiencies (TEs) of the conserved uORFs were highly correlated between the two species across all developmental stages and tissues examined, with Spearman correlation coefficients ranging from 0.478 to 0.573 (Fig. 2A)." However, the authors did not analyze the correlation of translation efficiency of conserved CDSs between the two species, and compare this correlation to the correlation between the TEs of CDSs. These analyzes will further support the authors conclusion regarding the role of conserved uORFs in translation regulation.

      (3) Page 8, line 217: "Among genes with multiple uORFs, one uORF generally emerged as dominant, displaying a higher TE than the others within the same gene (Fig. 2C)." The basis for determining dominance among uORFs is not explained and this lack of clarification undermines the interpretation of these findings.

      (4) According to the simulation, the translation of uORFs should exhibit greater variability than that of CDSs. However, the authors observed significantly fewer uORFs with significant TE changes compared to CDSs. This discrepancy may be due to lower sequencing depth resulting in fewer reads mapped to uORFs. Therefore, the authors may compare this variability specifically among highly expressed genes.

      (5) If possible, the author may need to use antibodies against bicoid to test the effect of ATG deletion on bicoid expression, particularly under different developmental stages or growth conditions. According to the authors' conclusions, the deletion mutant should exhibit greater variability in bicoid protein abundance. This experiment could provide strong support for the proposed mechanisms.

    1. Reviewer #2 (Public review):

      This study by Cook and colleagues utilizes genomic techniques to examine gene regulation in the craniofacial region of the fat-tailed dunnart at perinatal stages. Their goal is to understand how accelerated craniofacial development is achieved in marsupials compared to placental mammals.

      The authors employ state-of-the-art genomic techniques, including ChIP-seq, transcriptomics, and high-quality genome assembly, to explore how accelerated craniofacial development is achieved in marsupials compared to placental mammals. This work addresses an important biological question and contributes a valuable dataset to the field of comparative developmental biology. The study represents a commendable effort to expand our understanding of marsupial development, a group often underrepresented in genomic studies.

      The dunnart's unique biology, characterized by a short gestation and rapid craniofacial development, provides a powerful model for examining developmental timing and gene regulation. The authors successfully identified putative regulatory elements in dunnart facial tissue and linked them to genes involved in key developmental processes such as muscle, skin, bone, and blood formation. Comparative analyses between dunnart and mouse chromatin landscapes suggest intriguing differences in deployment of regulatory elements and gene expression patterns.

      Strengths

      (1) The authors employ a broad range of cutting-edge genomic tools to tackle a challenging model organism. The data generated - particularly ChIP-seq and RNA-seq from craniofacial tissue - are a valuable resource for the community, which can be employed for comparative studies. The use of multiple histone marks in the ChIP-seq experiments also adds to the utility of the datasets.

      (2) Marsupial occupy an important phylogenetic position, but they remain an understudied group. By focusing on the dunnart, this study addresses a significant gap in our understanding of mammalian development and evolution. Obtaining enough biological specimens for these experiments studies was likely a big challenge that the authors were able to overcome.

      (3) The comparison of enhancer landscapes and transcriptomes between dunnarts and can serve as the basis of subsequent studies that will examine the mechanisms of developmental timing shifts. The authors also carried out liftover analyses to identify orthologous enhancers and promoters in mice and dunnart.

      Weaknesses and Recommendations

      (1) The absence of genome browser tracks for ChIP-seq data makes it difficult to assess the quality of the datasets, including peak resolution and signal-to-noise ratios. Including browser tracks would significantly strengthen the paper by provide further support for adequate data quality.

      (2) The first two figures of the paper heavily rely in gene orthology analysis, motif enrichment, etc, to describe the genomic data generated from the dunnart. The main point of these figures is to demonstrate that the authors are capturing the epigenetic signature of the craniofacial region, but this is not clearly supported in the results. The manuscript should directly state what these analyses aim to accomplish - and provide statistical tests that strengthen confidence on the quality of the datasets.

      (3) The observation that "promoters are located on average 106 kb from the nearest TSS" raises significant concerns about the quality of the ChIP-seq data and/or genome annotation. The results and supplemental information suggest a combination of factors, including unannotated transcripts and enhancer-associated H3K4me3 peaks - but this issue is not fully resolved in the manuscript. The authors should confirm that this is not caused by spurious peaks in the CHIP-seq analysis - and possibly improve genome annotation with the transcriptomic datasets presented on the study.

      (4) The comparison of gene regulation between a single dunnart stage (P1) and multiple mouse stages lacks proper benchmarking. Morphological and gene expression comparisons should be integrated to identify equivalent developmental stages. This "alignment" is essential for interpreting observed differences as true heterochrony rather than intrinsic regulatory differences.

      (5) The low conservation of putative enhancers between mouse and dunnart (0.74-6.77%) is surprising given previous reports of higher tissue-specific enhancer conservation across mammals. The authors should address whether this low conservation reflects genuine biological divergence or methodological artifacts (e.g., peak-calling parameters or genome quality). Comparisons with published studies could contextualize these findings.

      (6) Focusing only on genes associated with shared enhancers excludes potentially relevant genes without clear regulatory conservation. A broader analysis incorporating all orthologous genes may reveal additional insights into craniofacial heterochrony.

      In conclusion, this study provides an important dataset for understanding marsupial craniofacial development and highlights the potential of genomic approaches in non-traditional model organisms. However, methodological limitations, including incomplete genome annotation and lack of developmental benchmarking weaken the robustness and of the findings. Addressing these issues would significantly enhance the study's utility to the field and its ability to support the study's central conclusion that dunnart-specific enhancers drive accelerated craniofacial development.

    1. Plasmid, as a mobile genetic element, plays a pivotal role in facilitating the transfer of traits, such as antimicrobial resistance, among the bacterial community. Annotating plasmid-encoded proteins with the widely used Gene Ontology (GO) vocabulary is a fundamental step in various tasks, including plasmid mobility classification. However, GO prediction for plasmid-encoded proteins faces two major challenges: the high diversity of functions and the limited availability of high-quality GO annotations. Thus, we introduce PlasGO, a tool that leverages a hierarchical architecture to predict GO terms for plasmid proteins. PlasGO utilizes a powerful protein language model to learn the local context within protein sentences and a BERT model to capture the global context within plasmid sentences. Additionally, PlasGO allows users to control the precision by incorporating a self-attention confidence weighting mechanism. We rigorously evaluated PlasGO and benchmarked it against six state-of-the-art tools in a series of experiments. The experimental results collectively demonstrate that PlasGO has achieved commendable performance. PlasGO significantly expanded the annotations of the plasmid-encoded protein database by assigning high-confidence GO terms to over 95% of previously unannotated proteins, showcasing impressive precision of 0.8229, 0.7941, and 0.8870 for the three GO categories, respectively, as measured on the novel protein test set.

      This work has been peer reviewed in GigaScience (see paper), which carries out open, named peer-review. These reviews are published under a CC-BY 4.0 license and were as follows:

      Reviewer name: **David Burstein **

      Review content:

      In this paper, the authors introduce "PlasGO," a language model for GO annotation of plasmid proteins. The model takes into account two levels of representation: (1) the amino acid level, producing embeddings of the analyzed proteins based on a foundation protein language model, and (2) the plasmid gene level, where the aa-based embeddings are considered as part of a language model representing each protein in the genetic context in which it is encoded. This approach leverages the modular organization of different functions on plasmid genomes. Benchmarking performed by the authors against other deep-learning GO annotation algorithms demonstrates a considerable improvement of PlasGO over existing methods. The research is timely, well-performed, and clearly explained. Main issues: 1. The authors acknowledge that only a relatively small portion of the proteins in their database have GO term annotations, which may limit the model's ability to learn plasmid patterns effectively. As they correctly point out, an iterative approach could be useful to improve performance. Specifically, high-confidence GO annotations predicted by PlasGO could be used as input for another round of prediction, and this process can be repeated until no new reliable predictions are produced. Given that the authors have all the data and models required to run such an iterative search, I would warmly recommend doing so and reporting if and how the predictions improve. 2. The gLM model (Hwang et al.) is highly similar to PlasGO in terms of the general approach, combining protein embedding (ESM2 in gLM) with genomic contextual data. Discussing the differences between the approaches and comparing their performances would provide important context and highlight the novelty of PlasGO. 3. The agreement of the PlasGO prediction with the GO terms retrieved from sequence databases ("ground truth") was determined by calculating the ratio of terms shared between the high-confidence predictions and ground truth, divided by the number of high-confidence predictions. This measure is asymmetrical and might generate over-optimistic results. At the extreme, if the algorithm produces a very large number of predictions, this value will tend to be very high just because there are many more GO terms predicted than GO terms in the ground truth. I strongly recommend using a symmetrical measure, such as the Jaccard index. 4. The methodology for calculating average precision and recall is potentially skewed. The authors compute average precision over proteins with at least one annotation, ignoring proteins lacking annotation (instead of counting these as misclassifications). This approach makes sense given that numerous plasmid proteins lack GO annotations. However, the average recall is calculated across all proteins (N). For unannotated proteins, the correct classification is not defined. Since these cases are also considered in the measure of recall, I assume PlasGO high-confidence predictions were considered correct. This seems like a problematic assumption that might lead to skewed results. I would therefore suggest that unannotated proteins be omitted from the recall calculation, as was done in the precision calculation. 5. The authors identify and filter out "elusive" GO terms that are difficult to predict. This is reasonable in the scope of this paper, but since it is still a central limitation of PlasGO, I would suggest discussing (even if not implementing) approaches to improve the predictions in these challenging cases. 6. In Figures 8 and 9, a perfect AUPR of 1 is reported in several cases. Such perfect classification performances are highly unusual and warrant an examination to double-check this result and if it persists discuss the underlying reasons for these perfect results. 7. The masking approach during training is not entirely clear. If I understand correctly, annotated proteins are being masked during prediction. This is expected to lead to the loss of a lot of contextual information. On the other hand, during training, the unannotated proteins are masked, losing potentially informative sequence data. I would suggest splitting complete plasmids between train/test/validation sets, and if needed, performing cross-validation to cover the entire dataset. This way for each plasmid the entire protein sequence and context information will be used. 8. There seems to be somewhat of a contradiction between the two following statements appearing in the paper: (1) "CaLM, despite being a pre-trained PLM, did not surpass the top three tools using ProtTrans, which is consistent with the results reported in CaLM's paper" and (2) "Experimental results demonstrate that the protein representations derived from CaLM outperform other PLMs in the classification of GO terms." Furthermore, other PLMs, such as ESM, performed better at GO annotation prediction according to the CaLM paper. These might have been more appropriate for this task. CodonBERT, a codon-based PLM also based on ProtTrans, could also have been a suitable alternative.

      Minor issues:- To improve the reading flow of the paper, consider reordering the ablation section to precede the "Performance on the RefSeq test set" section, since the ablation studies section provides the rationale for the choices of architecture and foundation protein language model.- "We initially downloaded all available plasmids from the NCBI RefSeq database" - I would suggest specifying the query or approach used to acquire all plasmids from RefSeq.- I would recommend using the term "protein embedding" instead of "protein token," which may be misleading. The term "token embeddings" used in Figure 3 is more accurate than "protein token," and yet "protein embeddings" is probably the most accurate term in this case.- Figure 1: To provide an accurate depiction of representative plasmids, I suggest including unannotated genes in Figure 1.- Figure 4: "Global average pooling" was misspelled.- Figure 10: "The prediction precision of PlasGO is determined by calculating the ratio of the number of proteins in set A that are also present in set B to the total number of predicted high-confidence proteins (|A|)". If I understand the figure correctly, it should be "number of GO terms" instead of "number of proteins" in both cases.- A figure (or supplementary figure) depicting one of the plasmids with some of the high-confidence predictions in the case study section (along the same lines as Figure 1 but with a distinction between previously known and unknown annotations) could enhance the clarity and impact of the results.

    2. Plasmid, as a mobile genetic element, plays a pivotal role in facilitating the transfer of traits, such as antimicrobial resistance, among the bacterial community. Annotating plasmid-encoded proteins with the widely used Gene Ontology (GO) vocabulary is a fundamental step in various tasks, including plasmid mobility classification. However, GO prediction for plasmid-encoded proteins faces two major challenges: the high diversity of functions and the limited availability of high-quality GO annotations. Thus, we introduce PlasGO, a tool that leverages a hierarchical architecture to predict GO terms for plasmid proteins. PlasGO utilizes a powerful protein language model to learn the local context within protein sentences and a BERT model to capture the global context within plasmid sentences. Additionally, PlasGO allows users to control the precision by incorporating a self-attention confidence weighting mechanism. We rigorously evaluated PlasGO and benchmarked it against six state-of-the-art tools in a series of experiments. The experimental results collectively demonstrate that PlasGO has achieved commendable performance. PlasGO significantly expanded the annotations of the plasmid-encoded protein database by assigning high-confidence GO terms to over 95% of previously unannotated proteins, showcasing impressive precision of 0.8229, 0.7941, and 0.8870 for the three GO categories, respectively, as measured on the novel protein test set.

      This work has been peer reviewed in GigaScience (see paper), which carries out open, named peer-review. These reviews are published under a CC-BY 4.0 license and were as follows:

      Reviewer name: **Nguyen Quoc Khanh Le **

      Review content: 1. The manuscript introduces PlasGO, which leverages a hierarchical architecture for GO term prediction in plasmid-encoded proteins. However, the novelty of the approach could be questioned. While the combination of protein language models and BERT for GO prediction is innovative, similar methods have been applied in other contexts. 2. The study heavily relies on data from the RefSeq database, yet there is limited discussion on the quality and completeness of this data. The manuscript should address potential biases introduced by incomplete or incorrect GO annotations in the database. Moreover, the study uses protein sequences of up to 1K length, which might exclude relevant longer sequences, potentially limiting the model's applicability to all plasmid-encoded proteins. 3. The manuscript claims that PlasGO can generalize well to novel proteins, but this claim is based on a specific dataset. The model's generalizability should be tested on more diverse and independent datasets, including plasmids from different bacterial species or environmental contexts. 4. While the model's performance is quantitatively evaluated, the interpretability of the results remains unclear. The study should include an analysis of how well the model's predictions align with known biological functions and pathways. Additionally, it would be helpful to include examples where PlasGO provides novel insights that other models do not, thereby demonstrating its practical utility. 5. The manuscript does not provide detailed information on the computational resources required to train and run PlasGO. Given the complexity of the model, there are potential concerns about its scalability, particularly for larger plasmid datasets or in settings with limited computational power. 6. The manuscript compares PlasGO with several state-ofthe-art tools, but the comparison might not be fully exhaustive. Additionally, statistical significance tests for performance differences should be provided to support the comparative analysis. 7. Language models have been used in previous bioinformatics studies i.e., PMID: 37381841, PMID: 38636332. Therefore, the authors are suggested to refer to more works in this description to attract a broader readership. 8. The study should discuss any ethical considerations related to the use of public datasets, particularly regarding data privacy and consent if any sensitive data is involved. Furthermore, the potential commercial implications of the PlasGO tool, especially if it is used for proprietary research, should be addressed. 9. While the manuscript mentions that PlasGO's code will be made available, it is crucial to ensure that all aspects of the research are fully reproducible. 10. The hierarchical architecture and the use of extensive training data might lead to overfitting, especially given the high dimensionality of the input features. The manuscript should discuss the measures taken to prevent overfitting, such as regularization techniques, dropout, or cross-validation strategies. 11. The study could benefit from a more detailed discussion on the practical implications of using PlasGO in real-world plasmid research. How can this tool be integrated into existing workflows for plasmid function prediction? What are the potential limitations in practical applications?

    1. ​50%​​徽章说明

      这幅图是神圣罗马帝国查理五世(Charles V, Holy Roman Emperor)的皇室纹章,作为16世纪欧洲最强大的君主之一,查理五世的纹章象征了他统治下的广阔疆域和多元化的领地。以下是这幅纹章的详细解释:


      1. 中央盾徽

      中央的盾徽是整个纹章的核心,由多个象征不同领地的区域组成,展示了查理五世统治下的广阔帝国疆域:

      (1) 上方:卡斯蒂利亚和莱昂

      • 红色背景上的金色城堡(Castile): 代表卡斯蒂利亚王国。
      • 白底紫色狮子(León): 代表莱昂王国。
      • 这些象征查理五世作为西班牙国王(卡洛斯一世)的统治。

      (2) 阿拉贡和西西里

      • 黄底红条纹(Aragon): 代表阿拉贡王国。
      • 黑鹰(Sicily): 代表西西里王国。

      (3) 奥地利

      • 红底银条纹: 代表查理五世的奥地利哈布斯堡家族领地。

      (4) 布尔戈涅(勃艮第)

      • 蓝底金色带红色对角条纹的狮子: 代表上勃艮第。
      • 蓝底金色十字和银色百合花: 代表下勃艮第。

      (5) 那不勒斯

      • 象征那不勒斯王国的标志: 表明查理五世是意大利南部的重要统治者。

      (6) 格拉纳达

      • 石榴花(Granada): 位于盾徽底部,象征着格拉纳达王国,这标志着西班牙在伊比利亚半岛的完全统一。

      2. 黑色双头鹰

      • 黑色双头鹰:
      • 是神圣罗马帝国的传统标志,象征帝国权威和统治的广阔疆域。
      • 双头代表着查理五世既是神圣罗马帝国的皇帝,也是基督教世界的守护者。
      • 鹰头上的金色皇冠: 象征帝国的至尊地位。

      3. 帝国皇冠

      • 纹章顶部的皇冠是神圣罗马帝国的皇帝皇冠,象征查理五世作为神圣罗马帝国皇帝的身份。

      4. 金羊毛骑士团勋章

      • 盾徽周围环绕的是金羊毛骑士团的项链,表明查理五世是金羊毛骑士团的大团长。
      • 金羊毛骑士团:
      • 是中世纪最著名的骑士团之一,由勃艮第公爵于1430年创立,象征着贵族的骑士精神、忠诚和宗教信仰。

      5. “赫拉克勒斯之柱”

      • 盾徽两侧的两根柱子象征“赫拉克勒斯之柱”(Pillars of Hercules):
      • 左柱上的格言:“PLUS”
      • 右柱上的格言:“ULTRA”
      • 加起来是“Plus Ultra”,意思是“超越极限”,这是查理五世的个人格言,象征着他的帝国超越了已知世界的边界(尤其是美洲的发现和征服)。

      6. 水波纹和大西洋

      • 柱子底部的水波象征大西洋,强调查理五世的帝国不仅仅局限于欧洲,还扩展到了美洲大陆。

      7. 整体象征意义

      • 统一的帝国:
      • 纹章展示了查理五世统治的多元文化和多民族帝国,包括西班牙、意大利、神圣罗马帝国的德意志领地以及美洲的殖民地。
      • 世界性霸权:
      • 赫拉克勒斯之柱的“Plus Ultra”传达了查理五世作为世界性霸主的自信和权威。
      • 基督教世界的捍卫者:
      • 黑色双头鹰和金羊毛勋章也显示了查理五世作为天主教世界主要领导者的地位。

      历史背景

      • 查理五世(1500-1558)是欧洲历史上最强大的君主之一。他是哈布斯堡王朝的核心人物,通过继承和联姻获得了广泛的领土,包括:
      • 西班牙(含美洲殖民地)。
      • 神圣罗马帝国的奥地利领地。
      • 勃艮第、尼德兰和意大利的部分地区。
      • 他统治的帝国被称为“日不落帝国”,因为他的疆域横跨多个大陆。

      总结

      这幅纹章是一幅恢弘的视觉象征,展示了查理五世对欧洲和美洲的广泛统治及其作为天主教世界领袖的地位。每个部分都代表了他庞大帝国的一部分,以及他在历史上的卓越地位。

    1. 皇家徽章

      这幅图是法国的皇家徽章,具体为法国国王和纳瓦拉国王联合的纹章(Grand Royal Coat of Arms of France and Navarre)。它代表了法国君主制的最高权威,象征着国家的主权和皇室的统治。以下是详细解释:


      1. 主要构成部分:

      (1) 中央盾徽:

      • 蓝色盾徽(左侧):
      • 上面绘有三个金色的百合花(Fleur-de-Lys),这是法国皇室的标志性纹章,象征着纯洁、王权和天主教信仰。
      • 百合花长期以来是法国的皇室象征,起源于卡佩王朝。

      • 红色盾徽(右侧):

      • 上面绘有金色链环,形成了复杂的几何图案,这是纳瓦拉国王的纹章(Kingdom of Navarre)。链环象征着骑士精神、忠诚和团结。
      • 纳瓦拉与法国合并后,这一标志成为法国皇室的一部分。

      (2) 王冠:

      • 盾徽顶部是法国国王的皇家皇冠。皇冠饰有珍珠、宝石和金色饰物,象征着君主的权威和荣耀。

      2. 配饰和装饰:

      (1) 天使支撑者:

      • 盾徽两侧分别站立着两位天使(圣像人物),手持旗帜。
      • 左侧天使的旗帜:蓝底上有金色百合花。
      • 右侧天使的旗帜:红底上是纳瓦拉的链环纹章。

      (2) 华盖与披风:

      • 盾徽后方的蓝色披风饰满了金色百合花图案,象征法国皇室。
      • 顶部的王冠与华盖设计突出了皇权的庄严。

      3. 格言和文字:

      (1) 上方格言:

      • “Lilia non laborant neque nent”(拉丁文):意思是“百合既不劳作也不纺织”,出自《圣经》,象征着法国皇室的尊贵天命。

      (2) 中间格言:

      • “Montjoie Saint Denis”:这是法国皇室的战斗口号,圣丹尼斯是法国的守护圣人。

      4. 装饰元素:

      • 金羊毛勋章(Order of the Golden Fleece):
      • 位于盾徽底部,象征法国国王与欧洲其他皇室的联系以及荣誉。

      • 圣灵勋章(Order of the Holy Spirit):

      • 是法国最高的骑士勋章,盾徽下方悬挂着这枚勋章。

      历史背景:

      • 这个徽章融合了法国王国和纳瓦拉王国的标志,象征了两国的合并。
      • 它在法国皇室鼎盛时期广泛使用,代表了法国的天主教传统、君主制权威以及其与欧洲其他国家的联系。

      这幅徽章在美学和象征意义上非常丰富,是法国历史和文化的重要象征,也是欧洲纹章学中的经典设计之一。

    2. 王储徽章

      这幅纹章是法国王室相关的徽章之一,可能与法国的“多芬”(Dauphin)有关。“多芬”是法国王储(即国王的法定继承人)的称号,这个纹章结合了法国皇室的百合花标志与多芬的象征性元素。以下是对纹章的详细解释:


      1. 中心盾徽

      中央的盾徽是纹章的核心部分,由四个区域组成,体现了法国皇室与多芬的结合: - 蓝色百合花(Fleur-de-Lys): - 蓝底金色百合花是法国皇室的传统标志,象征着法国王室的荣耀、纯洁和神圣权力。 - 这是法国卡佩王朝以来的经典符号。

      • 黄色与蓝色的海豚图案(Dolphin):
      • 海豚(多芬,Dauphin)是法国王储的象征,起源于“多芬内(Dauphiné)”地区。1349年,法王将该地区与王储的头衔永久绑定,因此海豚成为法国王储的专属象征。
      • 海豚在纹章中寓意智慧、守护与忠诚。

      2. 王冠

      • 盾徽上方的金色皇冠是法国王室的象征,表明纹章主人属于皇室。
      • 皇冠上装饰着百合花和宝石,象征法国君主制的荣耀和权威。

      3. 披风与华盖

      • 盾徽背后覆盖着装饰华丽的蓝色和白色披风:
      • 蓝色披风:饰满了金色百合花,进一步强调法国王室的身份。
      • 白色衬里:饰有貂皮图案,象征皇室的高贵和纯洁。

      4. 勋章环绕

      • 盾徽周围被象征骑士团的勋章环绕:
      • 金羊毛勋章(Order of the Golden Fleece):这是一枚欧洲王室和贵族常见的荣誉勋章,象征宗教和骑士精神。
      • 勋章表明纹章的主人不仅是法国皇室成员,还可能是骑士团的重要成员。

      5. 纹章整体象征

      这幅纹章通过结合法国皇室的百合花符号与多芬象征的海豚图案,表达了以下内容: 1. 纹章的主人是法国王储(多芬)。 2. 表现了法国王室的神圣性、荣耀和正统性。 3. 强调了多芬作为王储的独特身份与其对法国王国的继承权。


      6. 历史背景

      • 多芬称号的起源:
      • 法国“多芬”称号来源于1349年,当时的“多芬内”地区(Dauphiné)被卖给法国国王,但有条件要求王储必须使用“多芬”的称号。
      • 从此,多芬不仅是王储的称号,也成为一种象征,用于体现王室的正统性和继承体系。

      • 纹章的意义:

      • 这样的纹章不仅用于装饰,也是法律和政治意义上的标志,用于明确王储的地位和身份。

      总结

      这幅纹章完美融合了法国王室的象征(百合花)与多芬的独特标志(海豚)。它不仅是一件艺术品,更是中世纪和近代欧洲君主政治体系和文化的象征,表明了王储作为未来法国国王的合法地位和责任。

    1. 纹章解释

      这幅图是一幅典型的教会贵族纹章,常见于天主教会高阶神职人员的纹章设计,尤其是红衣主教(Cardinals)。以下是对图中元素的详细解读:


      1. 红色高帽(Galero)

      • 图顶部的红色宽边帽(Galero)是红衣主教身份的象征,标志着其在天主教会中的高级地位。
      • 红帽的历史
      • 它由教皇英诺森四世于1250年首次授予红衣主教,象征对天主教会和基督信仰的忠诚,以及在需要时为信仰献身的决心。

      2. 红色流苏(Tassels)

      • 帽子的两侧垂挂着一串红色流苏,每边共15个,分成五层。这种分层和数量的设计是红衣主教纹章的传统标志。
      • 流苏的象征:
      • 流苏的数量和排列代表了红衣主教的高位和崇高尊贵。

      3. 中央盾徽(Escutcheon)

      盾徽是纹章的核心部分,展示了红衣主教的家族标志或个人的象征性设计。

      • 设计内容:
      • 中央盾徽由红色和白色相间的三条倒V形条纹组成(称为“Chevron”图案),可能是家族徽章的一部分。
      • Chevron图案通常象征支持与保护,也可能代表家族的荣耀、荣誉或建筑相关的职业(例如支撑屋顶的梁架)。

      4. 皇冠(Crown)

      • 盾徽上方是一顶皇冠,这表明该红衣主教可能同时拥有贵族身份或王室背景。
      • 皇冠的意义:
      • 并非所有红衣主教的徽章都有皇冠,皇冠通常属于那些兼具宗教和贵族地位的神职人员,例如一些枢机主教或教会贵族。

      5. 披风与披布

      • 盾徽后方覆盖的披风饰有红色与蓝色图案,常见于贵族或高级神职人员的纹章,象征威严与尊贵。

      6. 勋章(Order Insignia)

      • 在盾徽下方悬挂着一枚勋章,可能与红衣主教获得的骑士团荣誉或宗教头衔相关。
      • 具体象征:
      • 勋章通常代表其宗教职责或参与的骑士团,例如圣灵勋章或金羊毛勋章。

      7. 白色背景

      • 白色背景是一种常见的天主教纹章设计风格,象征纯洁和信仰。

      8. 纹章意义总结

      这个纹章综合了宗教、家族和贵族元素,明确表示: - 此人为天主教会中的高级神职人员(红衣主教)。 - 他可能具有显赫的世俗背景(贵族或王室联系)。 - 纹章的设计传达了信仰、服务和对教会的忠诚,同时彰显了个人或家族的历史与地位。


      关于红衣主教纹章的历史和传统

      红衣主教的个人纹章在天主教会中非常重要: - 它不仅仅是身份象征,还展现了个人的家族背景、宗教承诺以及他在教会中的职责。 - 每位红衣主教在接受任命后都会设计或改进自己的纹章,这成为其个人历史的一部分。

      这幅纹章不仅具有象征意义,也反映了中世纪以来教会和贵族文化的融合。

    1. Time Vanquished by Love, Beauty and Hope (1627), Prado

      要欣赏西蒙·武埃(Simon Vouet)的名作《爱、美与希望战胜时间》(Time Vanquished by Love, Beauty and Hope),我们需要从以下几个方面入手:

      1. 了解作品的基本信息:

      • 画家: 西蒙·武埃(1590-1649),法国巴洛克时期最重要的画家之一,曾长期在意大利学习,深受卡拉瓦乔等人的影响,后回到法国,成为路易十三的首席宫廷画师。
      • 创作年代: 大约1627年(现藏于马德里普拉多博物馆的版本),或1645-46年(现藏于布尔日贝里博物馆的版本)。存在多个版本,细节略有不同。
      • 材质: 布面油画
      • 题材: 寓言画,描绘了爱、美与希望战胜时间的场景。

      2. 画面内容解读:

      这幅画描绘的是一个寓言场景,象征着爱情、美丽和希望能够战胜时间的流逝和死亡的必然性。画面中的主要人物和象征意义如下:

      • 时间(Time): 通常被描绘成一个长着翅膀的老人,手持镰刀或沙漏,象征着时间的流逝和破坏力。在武埃的画中,时间老人显得有些狼狈,正被其他人物制服,暗示了时间并非不可战胜。
      • 爱(Love): 通常以小爱神丘比特(Cupid)的形象出现,他手持弓箭,象征着爱情的力量。在一些版本中,维纳斯(Venus,爱与美的女神)也代表爱。
      • 美(Beauty): 通常以一位年轻美丽的女性形象出现,她象征着青春和美丽。在一些版本中,她直接就是维纳斯。有评论认为,武埃画中的“美”可能是以他的妻子维吉尼亚·韦齐(Virginia Vezzi)为模特创作的。
      • 希望(Hope): 通常以一位手持锚的女性形象出现,锚是希望的象征,代表着稳定和信念。

      画面中,爱、美与希望通常以一种活泼而富有动感的方式与时间抗争。例如,他们可能会抓住时间老人的翅膀、头发,甚至用花环或锚攻击他。这种描绘方式使得画面充满活力和乐观的情绪。

      3. 艺术风格分析:

      • 巴洛克风格: 作品具有典型的巴洛克风格特征,例如:
        • 强烈的动感和戏剧性: 人物姿态和构图都充满了动感,营造出一种紧张而富有戏剧性的氛围。
        • 丰富的光影效果: 画家运用明暗对比来突出人物和场景,增强了画面的立体感和表现力。
        • 丰富的色彩: 画面色彩丰富而华丽,营造出一种愉悦的视觉效果。
      • 意大利的影响: 武埃早年在意大利学习,受到了卡拉瓦乔等人的影响,画面中可以看到一些卡拉瓦乔式的明暗对比和人物造型。
      • 寓言性: 作品采用寓言的形式来表达深刻的主题,这是巴洛克时期艺术的常见特征。

      4. 不同版本之间的比较:

      武埃创作了多个版本的《爱、美与希望战胜时间》,其中最著名的两个版本分别藏于马德里普拉多博物馆和布尔日贝里博物馆。这两个版本在构图、人物和细节上略有不同,例如:

      • 普拉多博物馆的版本相对早期,构图较为紧凑,人物数量较少。
      • 布尔日贝里博物馆的版本相对晚期,构图更为复杂,人物数量更多,且加入了维纳斯。

      通过比较不同版本,我们可以更好地理解武埃在创作过程中的思考和变化。

      5. 作品的主题和象征意义:

      《爱、美与希望战胜时间》的主题是永恒的。它传达了这样一种信念:即使时间流逝,死亡不可避免,但爱情、美丽和希望仍然能够战胜时间的破坏力,给人以安慰和鼓舞。

      这幅画在当时也具有一定的政治寓意。在路易十三统治时期,法国经历了一段动荡的时期。这幅画可以被视为对王室的一种赞美,暗示了在国王的统治下,法国将能够克服困难,走向繁荣。

      欣赏要点总结:

      • 注意画面中人物的姿态和表情,感受他们之间的互动和情感。
      • 欣赏画家对光影和色彩的运用,以及画面所营造的氛围。
      • 理解作品的寓言主题和象征意义。
      • 如果有机会,可以比较不同版本的作品,从而更全面地了解这幅画。

      通过以上几个方面的分析,我们可以更好地欣赏西蒙·武埃的《爱、美与希望战胜时间》,并从中感受到艺术的魅力和深刻的内涵。

    1. Poging en voorbereiding verbinden strafbaarheid aan gedragingen waarvoor nog niet alle bestanddelen van een wettelijke d.o. zijn vervuld. Poging en voorbereiding vormen aldus een uitbreiding van strafrechtelijke aansprakelijkheid en zijn geen op zichzelf staande gedragingen.

      2 wettelijke restricties verbonden aan laten zien dat een onvoltooid delict minder ernstig wordt geacht dan een voltooide: 1. Poging en voorbereiding zijn uitsluitend strafbaar als het gaat om een voorgenomen misdrijf. 2. Bij poging wordt de strafmaximum met een derde verminderd, bij voorbereiding met de helft.

      Poging ex art. 45 lid 1 luidt: 'poging tot misdrijf is strafbaar, wanneer het voornemen van de dader zich door een begin van uitvoering heeft geopenbaard.' Er moet sprake zijn van een voornemen, en dit voornemen blijkt uit een begin van uitvoering.

      Voltooide en onvoltooide poging: Voltooide poging (delit manque) ziet op de situaties waarin de verdachte niet tot voltooiing van het misdrijf is gekomen, terwijl alles is gedaan om die voltooiing te bereiken. Een onvoltooide poging (tentative) ziet als er in een vroeg stadium de uitvoering van het misdrijf is verhinderd (externe factoren).

      Begin van uitvoering: Subjectieve leer --> stelt de gevaarlijke houding of gezindheid van de dader centraal en beschouwt als uitvoeringshandeling datgene wat als uitvoering van deze gezindheid is op te vatten Objectieve leer --> uitvoeringshandeling is pas datgene wat als daadwerkelijke uitvoering van het misdrijf zelf en dus als een objectieve breuk op de rechtsorde is te beschouwen. Niet iedere uiting van voornemen strafbaar gesteld, maar pas de uiting waarin een begin van uitvoering van het misdrijf wordt gezien. Sinds HR Uitzendbureau Cito is de benadering gematigd objectief te noemen: van begin van uitvoering is sprake indien de gedragingen naar hun uiterlijke verschijningsvormen worden beschouwd als te zijn gericht op de voltooiing van het misdrijf (HR bevrijding gevangene). Duidelijk is dat de maatstaf van de uiterlijke verschijningsvorm een overwegend objectieve leer oplevert. Dit komt ook naar voren in HR Grenswisselkantoor.

      De vraag of sprake is van een uitvoeringshandeling is vooral van belang wat de verdachten precies hebben gedaan, terwijl ook evident is dat bij het criterium van de uiterlijke verschijningsvorm grensgevallen denkbaar zijn. Voor de strafrechtelijke bestrijding van hennepteelt vormt volgens de HR het enkele aanwezig hebben van een voor de teelt van hennep ingerichte ruimte, niet reeds op zichzelf een gedraging die naar haar uiterlijke verschijningsvormen is gericht op de voltooiing van het telen. (HR Hennepteelt)

      De absoluut en relatief ondeugdelijke poging. Van een ondeugdelijke poging is sprake als de voltooiing van de poging onmogelijk blijkt te zijn. Absolute ondeugdelijkheid: als het middel of object altijd ondeugdelijk is Relatieve ondeugdelijkheid: als het middel of object slechts in dat specifieke geval ondeugdelijk is. 4 typen ondeugdelijke pogingssituaties: 1. Object absoluut ondeugdelijk: schieten op iemand die al overleden is. 2. Middel absoluut ondeugdelijk: in plaats van gif, poedersuiker in drankje doen 3. Object relatief ondeugdelijk: iemand steekt zijn hand in een lege kassa 4. Middel relatief ondeugdelijk: iemand doet gif in een drankje, maar te weinig om dodelijk te zijn

      Mangel al Tatbestand: Lijkt op een ondeugdelijke poging, maar is het niet. Iemand verkeert vanaf het begin al in de onmogelijkheid een delictsinhoud te vervullen, maar om een andere reden dan zijn gedrag en omdat het gebruiken object niet het gewenste gevolg tot stand kan brengen. Bijv. iemand die geen ambtenaar is kan geen ambtsdelict plegen.

    1. Twee soorten strafuitsluitingsgronden: 1. Rechtvaardigingsgronden: deze ontnemen de wederrechtelijkheid aan een gedraging. De in beginsel strafbare gedraging wordt gerechtvaardigd door een bijzondere omstandigheid. 2. Schulduitsluitingsgronden: deze ontnemen de verwijtbaarheid van de dader. De gedraging is wederrechtelijk en dus niet gerechtvaardigd, maar de verdachte valt geen verwijt te maken door een bijzondere omstandigheid.

      Onderscheid inwendige en uitwendige omstandigheden. Inwendig is in de persoon van de dader en uitwendig juist daarbuiten.

      Rechtvaardigingsgronden: Overmacht in de zin van noodtoestand art. 40 Sr: Overmacht is een rechtvaardigingsgrond omdat deze zich baseert op de keuze voor een handeling welke uit kracht van een veroorlovende norm toegestaan, en daarmee niet wederrechtelijk is. Hoofdregel: de pleger van het feit die voor de noodzaak zou kiezen, heeft uit een onderlig strijdige plichten en belangen de zwaarstwegende voor laten gaan. De voorwaarden voor overmacht in de zin van noodtoestand zijn: 1. Concrete en min of meer acute nood die bestaan in conflict van onderling onverzoenbare plichten of belangen. De ene plicht kan niet worden nageleefd zonder dat de andere plicht wordt verzaakt. 2. Zwaarstwegende plicht moet gekozen worden 3. Objectieve keuze tussen belangen of plichten: de vereisten van proportionaliteit en subsidiariteit worden nageleefd. Garantenstellung.

      Noodweer art. 41 lid 1 Sr. Eisen volgen uit HR Noodweer/Noodweerexces: 1. Aanranding: i) Zelfverdediging van eigen lijf, eerbaarheid of goed. Krachtens art. 41 Sr mag men onrecht tegen een ander op dezelfde condities afweren. ii) Goederen; verdediging van goederen is toegestaan bij daadwerkelijke aantasting van stoffelijk goed en bij schending van eigendomsrecht of beschikking van dat goed. 2. De aanranding moet wederrechtelijk zijn en niet voortvloeien uit een eigen recht of uit de rechtmatige oefening van overheidsbevoegdheid. 3. De aanranding moet ogenblikkelijk zijn; feitelijk begonnen zijn, of sprake zijn van een onmiddelijk dreigend gevaar. 4. Noodzakelijke verdediging, subsidiariteit. Dit houdt in dat het lichtste middel gekozen dient te worden om het doel te bereiken. 5. Geboden verdediging, proportionaliteit. Dit houdt in dat de verdediging zelf in verhouding staat met de aanranding. (Geldt ook Garantenstellung)

      Uitvoeren van wettelijk voorschrift art. 42 Sr. Dit is een algemene rechtvaardigingsgrond en maakt een feit dat ter uitvoering van een wettelijk voorschrift straffeloos is. Het is niet nodig als het bestanddeel wederrechtelijkheid in de d.o. is opgenomen.

      Bevoegd gegeven ambtelijk bevel art. 42 lid 1 Sr. Wie een ambtelijk bevel gehoorzaamt, verricht een rechtmatige handeling, omdat een ambtelijk bevel is terug te voeren tot de uitoefening van staatsgezag art. 43 lid 1 Sr. Deze RG ligt in het verlengde van het wettelijk voorschrift, aangezien geen gezag bevoegdelijk een bevel kan geven zonder een wettelijke grondslag, waarbij het bevel een concretisering is van een wettelijk voorschrift.

      Ontbreken materieelrechtelijke wederrechtelijkheid Hiervan is sprake indien een bepaalde regel wordt overtreden en dus strikt genomen in strijd met het objectieve recht wordt gehandeld en aldus sprake is van wederrechtelijkheid, maar met de gedraging wordt het juiste doel van de regeling bereikt.

      Schulduitsluitingsgronden: Ontoerekenbaarheid art. 39 Sr: Uitgangspunt is dat strafbaarheid gebaseerd moet worden op de toerekenbaarheid van ieder mens in de mate waarin deze voor zijn daden verantwoordelijk kan worden gehouden. Bij verminderde toerekenbaarheid wordt gesproken als in een geval een dader niet helemaal toerekenbaar of helemaal ontoerekenbaar wordt geacht. Lees in samenhang met 37a Sr. Toerekeningsbeslissing: 1. De verdachte moet ten tijde van het TLL feit hebben geleden aan een psychische stoornis of gebrekkige ontwikkeling der geestvermogens. 2. Onderzocht moet worden of de psychische stoornis van invloed is geweest op het TLL feit. Vaststellen in hoeverre een bepaalde geestelijke afwijking als de oorzaak van het gebeurde moet worden beschouwd en of en in hoeverre een schuldverwijt ruimte is. 3. Moet het feit aan de verdachte niet of verminderd worden toegerekend? Heeft de verdachte de stoornis op zichzelf afgeroepen?

      Psychische overmacht art. 40 Sr: Een kracht of dwang waartegen weerstand bieden redelijkerwijze niet is te eisen. Een psychische druk kan niet van worden gezegd dat de verdachte daaraan weerstand kon en hoefde te bieden. Uitgangspunt: de dader heeft gehandeld onder invloed van externe drang waaraan hij geen weerstand kon bieden en waaraan hij redelijkerwijze geen weerstand tegen hoefde te bieden. 1. Dwingende omstandigheden 2. Externe, van buiten komende psychische drang, waaraan weerstand bieden mogelijk of geboden is. 3. Acute psychische dwang, de dwingende omstandigheden moeten zich hebben voorgedaan op het tijdstip waarop de verdachte het strafbare feit heeft gepleegd. 4. Subsidiariteit en proportionaliteit spelen een rol, ook eventuele garantenstellung.

      Noodweerexces art. 41 lid 2 Sr Indien iemand zich tegen ogenblikkelijke, wederrechtelijke aanranding van eigen of andermans lijf, eerbaarheid of goed verdedigt maar daarbij de grenzen van proportionaliteit en subsidiariteit worden overschreden, zal een beroep op noodweer niet slagen. Soms wel noodweerexces. Vereisten geldig beroep HR Noodweer/Noodweerexces: 1. Noodweersituatie: ogenblikkelijke wederrechtelijke aanranding van lijf, eerbaarheid of goed 2. De betrokkene heeft de grenzen van noodzakelijke verdediging (proportionaliteit en subsidiariteit) in hevige gemoedsbeweging overschreden 3. Dubbele causaliteit: i) de hevige gemoedsbeweging veroorzaakt door de aanranding ii) de overschrijding van de grenzen moet zijn veroorzaakt door de hevige gemoedsbeweging. Er moet een excessieve reactie te verklaren zijn. Hierbij is het uitgangspunt de reactie van de gemiddelde, normale mens.

      Vormen noodweerexces: 1. Intensief noodweerexces: de aangevallene loopt direct te hard van stapel als gevolg van een hevige gemoedsbeweging en brengt te zwaar afweergeschut in. 2. Extensief noodweerexces: de aangevallene schiet door in de zelfverdediging. De noodweersituatie is ten einde en de aangevallene gaat door. 3. Tardief noodweerexces: de verdediging wordt pas ingezet op moment dat de noodweersituatie niet meer bestaat.

      Disproportionele gedragingen die werkelijk alle perken te buiten gaan, worden niet verontschuldigd (HR Ballenknijper)

      Onbevoegd gegeven ambtelijk bevel art. 43 lid 2 Sr. Er is bepaald dat onder omstandigheden van een onbevoegd gegeven ambtelijk bevel tot straffeloosheid kan leiden als deze door de ondergeschikte te goeder trouw als bevoegd gegeven werd beschouwd en indien de nakoming daarvan binnen de kring van zijn ondergeschiktheid was gelegen.

      Afwezigheid van alle schuld Denkbaar als het om geobjectiveerde bestanddelen gaat, dat wil zeggen delictsbestanddelen die onttrokken zijn aan het wettelijke schuldverband. De betekenis van de term schuld in AVAS moet worden onderscheiden van de betekenis van schuld als bestanddeel. De verdachte moet dit aannemelijk maken. De culpa bestaat uit grove, onachtzaamheid en voor de toepasselijkheid van AVAS is lichte schuld van toepassing.

      Feitelijke dwaling: (Error Facti) ingeval van misleiding door derden of misleidende informatie van derden, op wiens gezag de betrokkene redelijkerwijze mocht afgaan. Hieronder valt ook putatief noodweer, wanneer iemand denkt dat hij in een noodweersituatie bevind en dat niet is. Rechtsdwaling (error iuris): de betrokkene in redelijkheid en op deugdelijkheid van de AVAS had mogen vertrouwen. Er moet zijn gehandeld op advies van een deskundig te achten autoriteit, welke moet zijn verstrekt door een persoon of instantie.

      Culpa in causa: Indien de verdachte zichzelf verwijtbaar in een bepaalde gevaarlijke situatie heeft gebracht, zal een beroep op een strafuitsluitingsgrond niet slagen, omdat sprake is van culpa in causa (schuld in oorzaak). Het kan ook zijn dat de verdachte zichzelf in een bepaalde gevaarlijke situatie heeft gebracht, dat is dolus in causa (opzet in oorzaak): 1. Ontoerekenbaarheid: in praktijk wordt intoxicatie van welke aard dan ook gezien als een vorm van culpa in causa met betrekking tot het daaruit voortvloeiende geestestoestand gepleegde strafbare feit. 2. Overmacht: het kan zijn dat de persoon zichzelf willens en wetens in de situatie heeft gebracht waarin overmacht voorzienbaar ontstond. 3. Noodweerexces: iemand kan zich provocerend opstellen dat geweld van anderen als het ware wordt uitgelokt (HR Niet-betaalde taxirit).

      Argumenten de Hullu voor stelselmatige en strak onderscheidende aanpak van de strafuitsluitingsgronden: 1. Door systematisering zijn de vereisten voor het aanvaarden van exceptie sterk, wellicht te sterk, verzwaard. Door exceptie moet wederrechtelijkheid of schuld vervallen. 2. Door strikte systematisering kan het eigen, bijzondere karakter van een strafuitsluitingsgrond onder druk komen te staan. 3. Bijzondere excepties laten zich niet gemakkelijk in het schema van strafuitsluitingsgronden dwingen.

    1. 13

      To solve the expression: −2−(−4)+8+(−4)−(−7) Simplify the subtraction of negatives: −2−(−4)=−2+4=2 −(−7)=+7 The expression becomes: 2+8+(−4)+7 Combine the terms step by step: 2+8=10 10+(−4)=6 6+7=13

    1. Ce document est un guide pratique du Ministère de l’Éducation nationale et de la Jeunesse, édité en 2023-2024, destiné aux acteurs publics et associatifs pour encadrer l’attribution de subventions publiques aux associations.

      Il détaille la définition juridique de la subvention, la distinguant de la commande publique, et explique les modalités pratiques de son attribution (en numéraire ou en nature).

      Le guide présente ensuite les règles comptables et fiscales applicables, les types de subventions interdites (aux cultes, partis politiques, etc.), et propose des exemples de conventions.

      Son objectif principal est de promouvoir un partenariat équilibré et transparent entre les pouvoirs publics et les associations, en clarifiant les règles et les bonnes pratiques.

      SOMMAIRE * 1. Généralités sur la subvention p. 5 * 1.1. Définitions p. 5 * 1.2. Quelques chiffres p. 6 * 2. Pourquoi utiliser le régime de la subvention ? p. 8 * 2.1. Subvention ou commande publique, un choix d’action publique p. 8 * 2.2. « Les bonnes raisons » pratiques p. 8 * 2.3. Les conditions d’une collaboration réussie entre associations et collectivités p. 9 * 2.4. Bonnes pratiques partenariales associations / collectivités p. 10 * 3. Comment utiliser les différentes formes de subvention ? p. 11 * 3.1. Modalités pratiques de mise en œuvre de la subvention en numéraire p. 11 * 3.2. Modalités particulières de mise en œuvre de la subvention en nature p. 15 * 3.3. Recommandations de mise en œuvre du recueil d’initiatives p. 17 * 4. Autres règles connexes applicables aux subventions p. 18 * 4.1. Dans le domaine comptable p. 18 * 4.2. En matière fiscale –TVA p. 19 * 5. Les subventions particulières au regard du fonctionnement ou de l’activité du bénéficiaire p. 20 * 5.1. Les associations transparentes ou para-administratives p. 20 * 5.2. Les subventions interdites p. 21 * 6. Exemples p. 22 * Exemples de conventions attributives de subvention p. 22 * 7. Webographie p. 31

    1. L-13 and miR-5352 mimic have opposing effects on gene expression in ovine abomasal organoids.

      It might help get your point across/ be easier to interpret/learn from this figure if you 1) layered the functional enrichment analysis that you do on your differentially expressed genes in the next section onto this figure or 2) added some kind of functional grouping/color coding onto the gene names in all of these heatmaps. Otherwise, these heatmaps are pretty uninformative unless the reader knows offhand what all of these genes are, and would be just as good as a supp table. I think figures 4 and 5 would be more effective combined.

    1. Following electroporation, half of the total reaction was plated on ¼-salt L1 plates supplemented with 100 µg/ml nourseothricin. (d)

      It seems the 1/2 salt L1 plates were previously used to allow for bacterial conjugation, but it is less clear why reduced salt (1/2 or 1/4) plates were used in these electroporation experiments?

      Is it because of the protoplast's sensitivity to osmotic stress? or do you used reduced salt in the solid media plates to prevent the crashing out/precipitation that frequently occurs when making L1 agar plates?

      I'm essentially wondering if the low salt is addressing a physiological concern for the cells or a technical issue in the lab.

    1. Vídeo 6. Entrevista a Felwine Sarr

      Sobre #retos/sociopoliticos/pec3 > El desarrollo en África no puede estar medido por aquello que dicta Occidente. Cada contexto ha de poder decidir sobre lo que considera desarrollo. Además la cuestión de sostenibilidad es fundamental en África. [[Felwine Sarr]] no cree que el concepto sea puramente occidental ya que en África se tiene en cuenta la sostenibilidad -> la negociación con la naturaleza para ver qué sustracción, plantación o desarrollo se hace. Concepto de #epistemicidio como eso que ha ocurrido en África con la llegada de otra forma de mirar aquello que es importante en el saber, el compartir, el hacer.

    1. Circularity was defined as 4πSL–2, where S and L represent the cell area and perimeter, respectively. The highest value of 1 indicates a perfect circle, whereas the lowest value of 0 indicates a highly complex shape

      Examining the cell's eccentricity may be interesting if it captures something not reflected in the circularity calculation.

    1. Reviewer #1 (Public review):

      Summary:

      Meissner et al describe an update on the collection of split-GAL4 lines generated by a consortium led by Janelia Research Campus. This follows the same experimental pipeline described before and presents as a significant increment to the present collection. This will strengthen the usefulness and relevance of "splits" as a standard tool for labs that already use this tool and attract more labs and researchers to use it.

      Strengths:

      This manuscript presents a solid step to establish Split-GAL4 lines as a relevant tool in the powerful Drosophila toolkit. Not only the raw number of available lines contribute to the relevance of this tool in the "technical landscape" of genetic tools, but additional features of this effort contribute to the successful adoption. These include:

      (1) A description of expression patterns in the adult and larvae, expanding the "audience" for these tools<br /> (2) A classification of line combination according to quality levels, which provides a relevant criterion while deciding to use a particular set of "splits".<br /> (3) Discrimination between male and female expression patterns, providing hints regarding the potential role of these gender-specific circuits.<br /> (4) The search engine seems to be user-friendly, facilitating the retrieval of useful information.<br /> (5) An acknowledgement of the caveats and challenges that splits (like any other genetic tool) can carry.<br /> Overall, the authors employed a pipeline that maximizes the potential of the Split-GAL4 collection to the scientific community.

      Weaknesses:

      My concerns were resolved regarding the existence of caveats while using these tools that researchers should be aware of, particularly those using them for the first time.

    2. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      Meissner et al describe an update on the collection of split-GAL4 lines generated by a consortium led by Janelia Research Campus. This follows the same experimental pipeline described before and presents as a significant increment to the present collection. This will strengthen the usefulness and relevance of "splits" as a standard tool for labs that already use this tool and attract more labs and researchers to use it.

      Strengths:

      This manuscript presents a solid step to establish Split-GAL4 lines as a relevant tool in the powerful Drosophila toolkit. Not only does the raw number of available lines contribute to the relevance of this tool in the "technical landscape" of genetic tools, but additional features of this effort contribute to the successful adoption. These include:

      (1) A description of expression patterns in the adult and larvae, expanding the "audience" for these tools

      (2) A classification of line combination according to quality levels, which provides a relevant criterion while deciding to use a particular set of "splits".

      (3) Discrimination between male and female expression patterns, providing hints regarding the potential role of these gender-specific circuits.

      (4) The search engine seems to be user-friendly, facilitating the retrieval of useful information.

      Overall, the authors employed a pipeline that maximizes the potential of the Split-GAL4 collection to the scientific community.

      Weaknesses:

      The following aspects apply:

      The use of split-GAL4 lines has improved tremendously the genetic toolkit of Drosophila and this manuscript is another step forward in establishing this tool in the genetic repertoire that laboratories use. Thus, this would be a perfect opportunity for the authors to review the current status of this tool, addressing its caveats and how to effectively implement it into the experimental pipeline.

      (1) While the authors do bring up a series of relevant caveats that the community should be aware of while using split-GAL4 lines, the authors should take the opportunity to address some of the genetic issues that frequently arise while using the described genetic tools. This is particularly important for laboratories that lack the experience using split-GAL4 lines and wish to use them. Some of these issues are covertly brought up, but not entirely clarified.

      First, why do the authors (wisely) rescreen the lines using UAS-CsChrimson-mVenus? One reason is that using another transgene (such as UAS-GFP) and/or another genomic locus can drive a different expression pattern or intensities. Although this is discussed, this should be made more explicit and the readers should be aware of this.

      Second, it would be important to include a discussion regarding the potential of hemidriver lines to suffer from transvection effects whenever there is a genetic element in the same locus. These are serious issues that prevent a more reliable use of split-GAL4 lines that, once again, should be discussed.

      We added additional explanatory text to the discussion.

      (2) The authors simply mention that the goal of the manuscript is to "summarize the results obtained over the past decade.". A better explanation would be welcomed in order to understand the need of a dedicated manuscript to announce the availability of a new batch of lines when previous publications already described the Split-GAL4 lines. At the extreme, one might question why we need a manuscript for this when a simple footnote on Janelia's website would suffice.

      We added an additional mention of the cell type split-GAL4 collection at the relevant section and added more emphasis on the curation process adding value to the final selections. We feel that the manuscript is useful to document the methods used for the contained analysis and datasets and gives a starting point to the reader to go through the many split-GAL4 publications and images.

      Reviewer #2 (Public Review):

      Summary: This manuscript describes the creation and curation of a collection of genetic driver lines that specifically label small numbers of neurons, often just a single to handful of cell types, in the central nervous system of the fruit fly, Drosophila melanogaster. The authors screened over 77,000 split hemidriver combinations to yield a collection of 3060 lines targeting a range of cell types in the adult Drosophila central nervous system and 1373 lines characterized in third-instar larvae. These genetic driver lines have already contributed to several important publications and will no doubt continue to do so. It is a truly valuable resource that represents the cooperation of several labs throughout the Drosophila community.

      Strengths:

      The authors have thoughtfully curated and documented the lines that they have created, so that they may be maximally useful to the greater community. This documentation includes confocal images of neurons labeled by each driver line and when possible, a list of cell types labeled by the genetic driver line and their identity in an EM connectome dataset. The authors have also made available some information from the other lines they created and tested but deemed not specific or strong enough to be included as part of the collection. This additional resource will be a valuable aid for those seeking to label cell types that may not be included in the main collection.

      Weaknesses:

      None, this is a valuable set of tools that took many years of effort by several labs. This collection will continue to facilitate important science for years to come.

      We thank the reviewer for their positive feedback.

      Reviewer #3 (Public Review):

      Summary:

      The manuscript by Meissner et al. describes a collection of 3060 Drosophila lines that can be used to genetically target very small numbers of brain cells. The collection is the product of over a decade of work by the FlyLight Project Team at the Janelia Research Campus and their collaborators. This painstaking work has used the intersectional split-Gal4 method to combine pairs of so-called hemidrivers into driver lines capable of highly refined expression, often targeting single cell types. Roughly one-third of the lines have been described and characterized in previous publications and others will be described in manuscripts still in preparation. They are brought together here with many new lines to form one high-quality collection of lines with exceptional selectivity of expression. As detailed in the manuscript, all of the lines described have been made publicly available accompanied by an online database of images and metadata that allow researchers to identify lines containing neurons of interest to them. Collectively, the lines include neurons in most regions of both the adult and larval nervous systems, and the imaging database is intended to eventually permit anatomical searching that can match cell types targeted by the lines to those identified at the EM level in emerging connectomes. In addition, the manuscript introduces a second, freely accessible database of raw imaging data for many lower quality, but still potentially useful, split-Gal4 driver lines made by the FlyLight Project Team.

      Strengths:

      Both the stock collection and the image databases are substantial and important resources that will be of obvious interest to neuroscientists conducting research in Drosophila. Although many researchers will already be aware of the basic resources generated at Janelia, the comprehensive description provided in this manuscript represents a useful summary of past and recent accomplishments of the FlyLight Team and their collaborators and will be very valuable to newcomers in the field. In addition, the new lines being made available and the effort to collect all lines that have been generated that have highly specific expression patterns is very useful to all.

      Weaknesses:

      The collection of lines presented here is obviously somewhat redundant in including lines from previously published collections. Potentially confusing is the fact that previously published split-Gal4 collections have also touted lines with highly selective expression, but only a fraction of those lines have been chosen for inclusion in the present manuscript. For example, the collection of Shuai et al. (2023) describes some 800 new lines, many with specificity for neurons with connectivity to the mushroom body, but only 168 of these lines were selected for inclusion here. This is presumably because of the more stringent criteria applied in selecting the lines described in this manuscript, but it would be useful to spell this out and explain what makes this collection different from those previously published (and those forthcoming).

      We added more description of how this collection is focused on the best cell-type-specific lines across the CNS. An important requirement for inclusion was this degree of specificity across the CNS, while many prior publications had a greater emphasis on lines with a narrower focus of specificity.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Luckily for us, genetics is for the most part an exact science. However, there's still some "voodoo" in a lot of genetic combinations that the authors should disclose and be as clear as possible in the manuscript. This allows for the potential users to gauge expectations and devise a priori alternative plans.

      We attempted to comprehensively cover the caveats inherent in our genetic targeting approach.

      Minor points:

      (1) The authors mention that fly age should be controlled as expression can vary. Is there any reference to support this claim?

      We added a reference describing driver expression changes over development.

      (2) There should be a citation for "Flies were typically 1-5 days old at dissection for the cell type collection rescreening, 1-8 days old for other non-MCFO crosses and 3-8 days old for MCFO".

      We clarified that these descriptions were of our experimental preparations, not describing other citable work.

      Reviewer #3 (Recommendations For The Authors):

      General Points:

      Overall, the manuscript is very clear, but there are a couple of points where more explicit information would be useful. One of these is with respect to the issue of selectivity of targeting. The cell type specificity of lines is often referred to, but cell types can range from single pairs of neurons to hundreds of indistinguishable neurons with similar morphology and function. It would be useful if the authors explained whether their use of the term "cell type" distinguishes cell type from cell number. It would also be useful if lines that target many neurons of a single cell type were identified.

      We added further discussion of cell types vs. cell numbers. Our labeling strategy was not optimized for counting cell numbers labeled by each line. We believe EM studies are best positioned to comprehensively evaluate the number of cells making up each type.

      The second point relates to vagueness about the intended schedule for providing resources that will match (or allow matching of) neurons to the connectome. For example, on pp. 5-6 it is stated that: "In the future all of the neurons in these lines will be uniquely identified and linked to neurons reconstructed in the electron microscopy volume of the larva" but no timeline is provided. Similarly, for the adult neurons it is stated on p. 4 that: "Anatomical searching for comparison to other light microscopy (LM) and EM data is being made available." A more explicit statement about what resources are and are not yet available, a timeline for full availability, and an indication of how many lines currently have been matched to EM data would be helpful.

      During the review and revision period we have made progress on processing the images in the collection. We updated the text with the current status and anticipated timeline for completion.

      Specific Points:

      p. 4 "Although the lines used for these comparisons are not a random sample, the areas of greatest difference are in the vicinity of previously described sexual dimorphisms..." In the vicinity of is a very vague statement of localization. A couple of examples of what is meant here would be useful.

      We added example images to Figure 3.

      p. 5 "...may have specific expression outside our regions of interest." It's not clear what "our regions of interest" refers to here. Please clarify.

      We clarified that we were referring to the regions studied in the publications listed in Table 1.

      p. 5 "...lines that were sparse in VNC but dirty in the brain or SEZ..." A more quantitative descriptor than "dirty" would be helpful.

      We unfortunately did not quantify the extent of undesired brain/SEZ expression, but attempted to clarify the statement.

      p. 6 "...the images are being made instantly searchable for LM and EM comparisons at NeuronBridge..." Here again it is hard to know what is meant by "being made instantly searchable." How many have been made searchable and what is the bottleneck in making the rest searchable?

      We updated the text as described above. The bottleneck has been available processing capacity for the hundreds of thousands of included images.

      Figure 1 Supplemental File 2: The movie is beautiful, but it seems more useful as art than as a reference. Perhaps converting it to a pdf of searchable images for each line would make it more useful.

      We replaced the movie with a searchable PDF.

      Fig. 2(B) legend: "Other lines may have more than two types." It is not clear what "other lines" are being referred to.

      As part of making the quality evaluation more robust, we scored lines for the clear presence of three or more cell types. We updated the text accordingly.

      Fig. 2(C): Presumably the image shown is an example of variability in expression rather than weakness, but it is hard to know without a point of comparison. Perhaps show the expression patterns of other samples? Or describe briefly in the legend what other samples looked like?

      We added Figure 2 - figure supplement 1 with examples of variable expression in a split-GAL4 line.

    1. Reviewer #1 (Public review):

      Summary:

      Knudstrup et al. use two-photon calcium imaging to measure neural responses in the mouse primary visual cortex (V1) in response to image sequences. The authors presented mice with many repetitions of the same four-image sequence (ABCD) for four days. Then on the fifth day, they presented unexpected stimulus orderings where one stimulus was either omitted (ABBD) or substituted (ACBD). After analyzing trial-averaged responses of neurons pooled across multiple mice, they observed that stimulus omission (ABBD) caused a small, but significant, strengthening of neural responses but observed no significant change in the response to stimulus substitution (ACBD). Next, they performed population analyses of this dataset. They showed that there were changes in the correlation structure of activity and that many features about sequence ordering could be reliably decoded. This second set of analyses is interesting and exhibited larger effect sizes than the first results about predictive coding. However, concerns about the design of the experiment temper my enthusiasm.

      The most recent version of this manuscript makes a few helpful changes (entirely in supplemental figures--the main text figures are unchanged). It does not resolve any of the larger weaknesses of the experimental design, or even perform single-neuron tracking in the one case where it was possible (between similar FOVs shown in Supplemental Figure 1).

      Strengths:

      (1) The topic of predictive coding in the visual cortex is exciting, and this task builds on previous important work by the senior author (Gavornik and Bear 2014) where unexpectedly shuffling sequence order caused changes in LFPs recorded from visual cortex.

      (2) Deconvolved calcium responses were used appropriately here to look at the timing of the neural responses.

      (3) Neural decoding results showing that the context of the stimuli could be reliably decoded from trial-averaged responses were interesting. But I have concerns about how the data was formatted for performing these analyses.

      Weaknesses:

      (1) All analyses were performed on trial-averaged neural responses that were pooled across mice (except for Supplementary Figure 6, see below). Owing to differences between subjects in behavior, experimental preparation quality, and biological variability, it seems important to perform most analyses on individual datasets to assess how behavioral training might differently affect each animal.

      In the most recent draft, a single-mouse analysis was added for Figure 4C (Supplementary Figure 6). This effect of "representational drift" was not statistically quantified in either the single-mouse results or in the main text figure panel. Moreover, the apparent correlational drift could be accounted for by a reduction in SNR as a consequence of photobleaching.

      (2) The correlation analyses presented in Figure 3 (labeled the second Figure 2 in the text) should be conducted on a single-animal basis. Studying population codes constructed by pooling across mice, particularly when there is no behavioral readout to assess whether learning has had similar effects on all animals, appears inappropriate to me. If the results in Figure 3 hold up on single animals, I think that is definitely an interesting result.

      In the most recent draft, this analysis was still not performed on single mice. I was referring to the "decorrelation of responses" analysis in Figure 3, not the "representational drift" analysis in Figure 4. See my comments on Supplementary Figure 6 above.

      (3) On Day 0 and Day 5, the reordered stimuli are presented in trial blocks where each image sequence is shown 100 times. Why wasn't the trial ordering randomized as was done in previous studies (e.g. Gavornik and Bear 2014)? Given this lack of reordering, did neurons show reduced predictive responses because the unexpected sequence was shown so many times in quick succession? This might change the results seen in Figure 2, as well as the decoder results where there is a neural encoding of sequence order (Figure 4). It would be interesting if the Figure 4 decoder stopped working when the higher order block structure of the task were disrupted.

      In the rebuttal letter for the most recent draft, the authors refer to recent work in press (Hosmane et al. 2024) suggesting that because sleep may be important for plastic changes between sessions, they do not expect much change to be apparent within a session. However, they admit that this current study is too underpowered to know for sure--and do not cite or mention this yet unpublished work in the manuscript itself.

      As a control, I would be interested to at least know how much variance in neural responses is observed between intermediate "training" sessions with identical stimuli, e.g. between Day 1 and Day 4, but this is not possible as imaging was not performed on these days.

      Despite being referred to as "similar" I do not think early and late responses are clearly shown--aside from the histograms comparing "early traces" to "all traces" which include early traces in Figure 5B and Figure 6A. Showing variance in single-cell responses would be helpful to add in Supplementary Figure 3 and Supplementary Figure 4.

      (4) A primary advantage of using two-photon calcium imaging over other techniques like extracellular electrophysiology is that the same neurons can be tracked over many days. This is a standard approach that can be accomplished by using many software packages-including Suite2P (Pachitariu et al. 2017), which is what the authors already used for the rest of their data preprocessing. The authors of this paper did not appear to do this. Instead, it appears that different neurons were imaged on Day 0 (baseline) and Day 5 (test). This is a significant weakness of the current dataset.

      In the most recent draft, this concern has not been mitigated. Despite Supplementary Figure 1 showing similar FOVs, mostly different neurons were still extracted. In all other sessions, it is not reported how far apart the other recorded FOVs were from each other.

      The rebuttal comment that the PE statistic is computed on an individual cell within-session basis is reasonable. Moreover, the bootstrapped version of the PE analysis in Supplementary Figure 8 is an improvement of the main analysis in the paper. As a control, it would have been helpful to compute the stability of the PE ratio statistics between training days (e.g. between day 1 and day 4). How much change would have been observed when none is expected? Unfortunately, imaging was not performed on these training days so this analysis will not be readily possible to perform. Moreover, the PE statistic requires averaging across cells and trials and is therefore very likely to wash out many interesting effects. Even if it is the population response that is changing, why would it be the arithmetic mean that changes in particular vs. some other projection of the population activity? The experimental and analysis design of the paper here remains weak in my mind.

    2. Reviewer #2 (Public review):

      Knudstrup and colleagues investigate response to short and rapid sequences of stimuli in layer 2/3 of mouse visual cortex. To quote the authors themselves: "the work continues the recent tradition of providing ambiguous support for the idea that cortical dynamics are best described by predictive coding models". Unfortunately, the ambiguity here is largely a result of the choice of experimental design and analysis, and the data provide only incomplete support for the authors' conclusions.

      The authors have addressed some of the concerns of the first revision. However, many still remain.

      (1) From the first review: "There appears to be some confusion regarding the conceptual framing of predictive coding. Assuming the mouse learns to expect the sequence ABCD, then ABBD does not probe just for negative prediction errors, and ACBD not just positive prediction errors. With ABBD, there is a combination of a negative prediction error for the missing C in the 3rd position, and a positive prediction error for B in 3rd. Likewise, with ACBD, there is negative prediction error for the missing B at 2nd and missing C at 3rd, and a positive prediction error for the C in 2nd and B in 3rd. Thus, the authors' experimental design does not have the power to isolate either negative or positive prediction errors. Moreover, looking at the raw data in Figure 2C, this does not look like an "omission" response to C, more like a stronger response to a longer B. The pitch of the paper as investigating prediction error responses is probably not warranted - we see no way to align the authors' results with this interpretation."

      The authors acknowledge in their response that this is a problem, but do not appear to discuss this in the manuscript. This should be fixed.

      (2) From the first review: "Recording from the same neurons over the course of this paradigm is well within the technical standards of the field, and there is no reason not to do this. Given that the authors chose to record from different neurons, it is difficult to distinguish representational drift from drift in the population of neurons recorded. "

      The authors respond by pointing out that what they mean by "drift" is within day changes. This has been clarified. However, the analyses in Figures 3 and 5 still are done across days. Figure 3: "Experience modifies activity in PCA space ..." and figure 5: "Stimulus responses shift with training". Both rely on comparisons of population activity across days. This concern remains unchanged here. It would probably be best to remove any analysis done across days - or use data where the same neurons were tracked. Performing chronic two-photon imaging experiments without tracking the same neurons is simply bad practice (assuming one intends to do any analysis across recording sessions).

      (3) From the first revision: "The block paradigm to test for prediction errors appears ill chosen. Why not interleave oddball stimuli randomly in a sequence of normal stimuli? The concern is related to the question of how many repetitions it takes to learn a sequence. Can the mice not learn ACBD over 100x repetitions? The authors should definitely look at early vs. late responses in the oddball block. Also the first few presentations after block transition might be potentially interesting. The authors' analysis in the paper already strongly suggests that the mice learn rather rapidly. The authors conclude: "we expected ABCD would be more-or-less indistinguishable from ABBD and ACBD since A occurs first in each sequence and always preceded by a long (800 ms) gray period. This was not the case. Most often, the decoder correctly identified which sequence stimulus A came from." This would suggest that whatever learning/drift could happen within one block did indeed happen and responses to different sequences are harder to interpret."

      Again, the authors acknowledge the problem and state that "there is no indication that this is a learned effect". However, they provide no evidence for this and perform no analysis to mitigate the concern.

      (4) Some of the minor comments also appear unaddressed and uncommented. E.g. the response amplitudes are still shown in "a.u." instead of dF/F or z-score or spikes.

    3. Author response:

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

      Reviewer #1:

      (1) All analyses were performed on trial-averaged neural responses that were pooled across mice. Owing to differences between subjects in behavior, experimental preparation quality, and biological variability, it seems important to perform at least some analyses on individual analyses to assess how behavioral training might differently affect each animal.

      In order to image at a relatively fast rate (30Hz) appropriate to the experimental conditions, we restricted our imaging to a relatively small field of view (412x412um with 512x512 pixels). This entails a smaller number of ROIs per animal, which can lead to an unbalanced distribution of cells responsive to different stimuli for individual fields-of-view. We used the common approach of pooling across animals (Homann et al., 2021; Kim et al., 2019) to overcome limitations imposed by sampling a smaller number of cells per animal. In response to this comment, we included supplemental analyses (Sup.Fig. 6) showing that representational drift (which was not performed on trial-averaged data) looks substantially the same (albeit nosier) for individual animals as at the population level. Additional analyses (PE ratio, etc.) were difficult since the distribution of cells selective for individual stimuli is unbalanced between individual animals and few mice have multiple cells representing all of the different stimuli.

      (2) The correlation analyses presented in Figure 3 (labeled the second Figure 2 in the text) should be conducted on a single-animal basis. Studying population codes constructed by pooling across mice, particularly when there is no behavioral readout to assess whether learning has had similar effects on all animals, appears inappropriate to me. If the results in Figure 3 hold up on single animals, I think that is definitely an interesting result.

      We repeated the correlation analysis performed on mice individually and included them in the supplement (Supp. Fig. 6). The overall result generally mirrors the result found by pooling across animals.

      (3) On Day 0 and Day 5, the reordered stimuli are presented in trial blocks where each image sequence is shown 100 times. Why wasn't the trial ordering randomized as was done in previous studies (e.g. Gavornik and Bear 2014)? Given this lack of reordering, did neurons show reduced predictive responses because the unexpected sequence was shown so many times in quick succession? This might change the results seen in Figure 2, as well as the decoder results where there is a neural encoding of sequence order (Figure 4). It would be interesting if the Figure 4 decoder stopped working when the higher-order block structure of the task was disrupted.

      Our work builds primarily on previous studies (Gavornik & Bear, 2014; Price et al., 2023) that demonstrated clear changes in neural responses over days while employing a similar block structure. Notably, Price et al. found that trial number (within a block) was not a significant factor in the generation of prediction-error responses which strongly suggests short-term plasticity does not play a significant role in shaping responses within the block structure. This finding is consistent with our previous LFP recordings which have not revealed any significant plasticity occurring within a training session, a conclusion bolstered by a collaborative work currently in press (Hosmane et al. 2024, Sleep) revealing the requirement for sleep in sequence plasticity expression.

      It is possible that layer 2/3 adapts to sequences more rapidly than layer 4/5. While manual inspection does not reveal an obvious difference between early and late blocks in this dataset, the n for this subset is too small to draw firm conclusions. It is our view that the block structure provides the strongest comparison to previous work, but agree it would be interesting to randomize or fully interleave sequences in future studies to determine what effect, if any, short-term changes might have. 

      (4) A primary advantage of using two-photon calcium imaging over other techniques like extracellular electrophysiology is that the same neurons can be tracked over many days. This is a standard approach that can be accomplished by using many software packages-including Suite2P (Pachitariu et al. 2017), which is what the authors already used for the rest of their data preprocessing. The authors of this paper did not appear to do this. Instead, it appears that different neurons were imaged on Day 0 (baseline) and Day 5 (test). This is a significant weakness of the current dataset.

      The hypothesis being tested was whether expectation violations, as described in Keller & Mrsic-Flogel 2018, exist under a multi-day sequence learning paradigm. For this, tracking cells across days is not necessary as our PE metric compared responses of individual neurons to multiple stimuli within a single session. Given the speed/FOV tradeoff discussed above, we wanted to consider all cells irrespective of whether they were visible/active or trackable across days, especially since we would expect cells that learn to signal prediction errors to be inactive on day 0 and not selected by our segmentation algorithm. Though we did not compare the responses of single cells before/after training, we did analyze cells from the same field of view on days 0 and 5 (see Supp.Fig. 1) and not distinct populations.

      Reviewer #2:

      (1) There appears to be some confusion regarding the conceptual framing of predictive coding.

      Assuming the mouse learns to expect the sequence ABCD, then ABBD does not probe just for negative prediction errors, and ACBD is not just for positive prediction errors. With ABBD, there is a combination of a negative prediction error for the missing C in the 3rd position, and a positive prediction error for B in the 3rd. Likewise, with ACBD, there is a negative prediction error for the missing B at 2nd and missing C at 3rd, and a positive prediction error for the C in 2nd and B in 3rd. Thus, the authors' experimental design does not have the power to isolate either negative or positive prediction errors. Moreover, looking at the raw data in Figure 2C, this does not look like an "omission" response to C, but more like a stronger response to a longer B. The pitch of the paper as investigating prediction error responses is probably not warranted - we see no way to align the authors' results with this interpretation.

      The reviewer has identified a real problem with the framing of “positive” and “negative” prediction errors in context of sensory stimuli where substitution simultaneously introduces unexpected “positive” violation and “negative” omission. Simply put, even if there are separate mechanisms to represent positive and negative errors, there may be no way to isolate the positive response experimentally since an unexpected input always replaces the unseen expected input. For example, had a cell fired solely to ACBD (and not during either ABCD or ABCD), then whether it was signaling the unexpected occurrence of C or the unexpected absence of B would be inherently ambiguous. In either case, such a cell would have been labeled as C-responsive, and its activity would have been elevated compared with ABCD and would have been included in our substitution-type analysis of prediction errors. We accept that there is some ambiguity regarding the description in this particular case, but overall, this cell’s activity pattern would have informed the PE analysis for which the result was essentially null for the substitution-type violation ACBD.

      Omission, in which the sensory input does not change, may experimentally isolate the negative response though this is only true if there is a temporal expectation of when the change should have occurred. If A is predicting B in an ordinal sense but there is no expectation of when B will occur with respect to A, changing the duration of A would not be expected to produce an error signal since at any point in time B might still be coming and the expectation is not broken until something other than B occurs. With respect specifically to ABBD in our experiments, it is correct that the learned error responses take the form of stronger, sustained responses to B during the time C was expected. This is still in contrast to day 0 in which activation decays after a transient response to ABBD. The data shows that responses during an omitted element are altered with training and take the form of elevated responses to ABBD on day 5.As we say in our discussion, this is somewhat ambiguous evidence of prediction errors since it does emerges only with training and is generally consistent with the hypothesis being tested though it takes a different form than we expected it to.

      (2) Related to the interpretation of the findings, just because something can be described as a prediction error does not mean it is computed in (or even is relevant to) the visual cortex. To the best of our knowledge, it is still unclear where in the visual stream the responses described here are computed. It is possible that this type of computation happens before the signals reach the visual cortex, similar to mechanisms predicting moving stimuli already in the retina (https://pubmed.ncbi.nlm.nih.gov/10192333/). This would also be consistent with the authors' finding (in previous work) that single-cell recordings in V1 exhibit weaker sequence violation responses than the author's earlier work using LFP recordings.

      Our work was aimed at testing the specific hypothesis that PE responses, at the very least, exist in L2/3—a hypothesis that is well-supported under different experimental paradigms (often multisensory mismatch). Our aim was to test this idea under a sequence learning paradigm and connect it with previously found PE responses in L4. We don’t claim that it is the only place in which prediction errors may be computed or useful, especially since (as you mentioned), there is evidence for such responses in layer 4. But it is fundamentally important to predictive processing that we determine whether PE responses can be found in layer 2/3 under this passive sequence learning paradigm, whether or not they reflect upstream processes, feedback from higher areas, or entirely local computations. Our aim was to establish some baseline evidence for or against predictive processing accounts of L2/3 activity during passive exposure to visual sequences.

      (3) Recording from the same neurons over the course of this paradigm is well within the technical standards of the field, and there is no reason not to do this. Given that the authors chose to record from different neurons, it is difficult to distinguish representational drift from drift in the population of neurons recorded.

      Our discussion of drift refers to changes occurring within a population of neurons over the course of a single imaging session. We have added clarifying language to the manuscript to make this clear. Changes to the population-level encoding of stimuli over days are treated separately and with different analytical tools. Re. tracking single across days, please see the response to Reviewer #1, comment 4.

      (4) The block paradigm to test for prediction errors appears ill-chosen. Why not interleave oddball stimuli randomly in a sequence of normal stimuli? The concern is related to the question of how many repetitions it takes to learn a sequence. Can the mice not learn ACBD over 100x repetitions? The authors should definitely look at early vs. late responses in the oddball block. Also, the first few presentations after the block transition might be potentially interesting. The authors' analysis in the paper already strongly suggests that the mice learn rather rapidly. The authors conclude: "we expected ABCD would be more-or-less indistinguishable from ABBD and ACBD since A occurs first in each sequence and always preceded by a long (800 ms) gray period.

      This was not the case. Most often, the decoder correctly identified which sequence stimulus A came from." This would suggest that whatever learning/drift could happen within one block did indeed happen and responses to different sequences are harder to interpret.

      This work builds on previous studies that used a block structure to drive plasticity across days. We previously tested whether there are intra-block effects and found no indication of changes occurring within a block or withing a session (please see the response to Reviewer #1, comment 3 for further discussion). Observed drift does complicate comparison between blocks. There is no indication in our data that this is a learned effect, though future experiments could test this directly.

      (5) Throughout the manuscript, many of the claims are not statistically tested, and where they are the tests do not appear to be hierarchical (https://pubmed.ncbi.nlm.nih.gov/24671065/), even though the data are likely nested.

      We have modified language throughout the manuscript to be more precise about our claims. We used pooled data between mice and common parametric statistics in line with published literature. The referenced paper offers a broad critique of this approach, arguing that it increases the possibility of type 1 errors, though it is not clear to us that our experimental design carries this risk particularly since most of our results were negative. To address the specific concern, however we performed a non-parametric hierarchical bootstrap analysis (https://pmc.ncbi.nlm.nih.gov/articles/PMC7906290/) that re-confirmed the statistical significance of our positive results, see Supplemental Figure 8.

      (6) The manuscript would greatly benefit from thorough proofreading (not just in regard to figure references).

      We apologize for the errors in the manuscript. We caught the issue and passed on a corrected draft, but apparently the uncorrected draft was sent for review. The re-written manuscript addresses all identified issues.

      (7) With a sequence of stimuli that are 250ms in length each, the use of GCaMP6s appears like a very poor choice.

      We started our experiments using GCaMP6f but ultimately switched to GCaMP6s due to its improved sensitivity, brightness, and accuracy in spike detection (Huang et al., 2021). When combined with deconvolution (Pachitariu et al., 2018; Pnevmatikakis et al., 2016), we found GCaMP6s provides the most complete and accurate view of spiking within 40ms time bins. The inherent limitations of calcium imaging are more likely to be addressed using electrophysiology rather than a faster sensor in future studies.

      (8) The data shown are unnecessarily selective. E.g. it would probably be interesting to see how the average population response evolves with days. The relevant question for most prediction error interpretations would be whether there are subpopulations of neurons that selectively respond to any of the oddballs. E.g. while the authors state they "did" not identify a separate population of omission-responsive neurons, they provide no evidence for this. However, it is unclear whether the block structure of the experiments allows the authors to analyze this.

      We concluded that there is no clear dedicated subpopulation of omission-responding cells by inspecting cells with large PE responses (i.e., ABBD, see supplemental figure 3). Out of the 107 B-responsive cells on day 5, only one appeared to fire exclusively during the omitted stimulus. Average traces for all B-responsive cells are included in the supplement and we have updated the manuscript accordingly. Similarly, a single C-responsive cell was found with an apparently unique substitution error profile (ABCD and ACBD , supplemental figure 4).

      Our primary concern was to make sure that days 0 and 5 had the highest quality fields-of-view. In work leading up to this study, there were concerns that imaging on all intermediate days resulted in a degradation of quality due to photobleaching. We agree that an analysis of intermediate days would be interesting, but it was excluded due to these concerns. 

      Reviewer #3:

      (1) Experimental design using a block structure. The use of a block structure on test days (0 and 5) in which sequences were presented in 100 repetition blocks leads to several potential confounds. First, there is the potential for plasticity within blocks, which could alter the responses and induce learned expectations. The ability of the authors to clearly distinguish blocks 1 and 2 on Day 0 with a decoder suggests this change over time may be meaningful.

      Repeating the experiments with fully interleaved sequences on test days would alleviate this concern. With the existing data, the authors should compare responses from the first trials in a block to the last trials in a block.

      This block design likely also accounts for the ability of a decoder to readily distinguish stimulus A in ABCD from A in ABBD. As all ABCD sequences were run in a contiguous block separate from ABBD, the recent history of experience is different for A stimuli in ABCD versus ABBD. Running fully interleaved sequences would also address this point, and would also potentially mitigate the impact of drift over blocks (discussed below).

      As described in other responses, the block structure was chosen to align more closely with previous studies. We take the overall point though, and future studies will employ the suggested randomized or interleaved structure in addition to block structures to investigate the effects of short-term plasticity.

      (2) The computation of prediction error differs significantly for omission as opposed to substitutions, in meaningful ways the authors do not address. For omission errors, PE compares the responses of B1 and B2 within ABBD blocks. These responses are measured from the same trial, within tens of milliseconds of each other. In contrast, substitution PE is computed by comparing C in ABCD to C in ACBD. As noted above, the block structure means that these C responses were recorded in different blocks, when the state of the brain could be different. This may account for the authors' detection of prediction error for omission but not substitution. To address this, the authors should calculate PE for omission using B responses from ABCD.

      We performed the suggested analysis (i.e., ABBD vs ABCD) prior to submission but omitted it from the draft for brevity (the effect was the same as with ABBD vs ABBD). We have added the results of standardizing with ABCD as supplementary figure 3.

      (3) The behavior of responses to B and C within the trained sequence ABCD differs considerably, yet is not addressed. Responses to B in ABCD potentiate from d0-> d5, yet responses to C in the same sequence go down. This suggests there may be some difference in either the representation of B vs C or position 2 vs 3 in the sequence that may also be contributing to the appearance of prediction errors in ABBD but not ACBD. The authors do not appear to consider this point, which could potentially impact their results. Presenting different stimuli for A,B,C,D across mice would help (in the current paper B is 75 deg and C is 165 deg in all cases). Additionally, other omissions or substitutions at different sequence positions should be tested (eg ABCC or ABDC).

      We appreciate the suggestion. Ideally, we could test many different variants, but practical concerns regarding the duration of the imaging sessions prevented us from testing other interesting variations (such as ABCC) in the current study. We are uncertain as to how we should interpret the overall depressed response to element C seen on day 5, but since the effect is shared in both ABCD and ACBD, we don’t think it affected our PE calculations. 

      (4) The authors' interpretation of their PCA results is flawed. The authors write "Experience simplifies activity in principal component space". This is untrue based on their data. The variance explained by the first set of PCs does not change with training, indicating that the data is not residing in a lower dimensional ("simpler") space. Instead, the authors show that the first 5 PCs better align with their a priori expectations of the stimulus structure, but that does not mean these PCs necessarily represent more information about the stimulus (and the fact that the authors fail to see an improvement in decoding performance argues against this case). Addressing such a question would be highly interesting, but is lacking in the current manuscript. Without such analysis, referring to the PCs after training as "highly discretized" and "untangled" are largely meaningless descriptions that lack analytical support.

      We meant the terms “simpler”, “highly-discretized”, and “untangled” as qualitative descriptions of changes in covariance structure that occurred despite the maintenance of overall dimensionality. As the reviewer notes, the obvious changes in PC space appear to have had practically no effect on decodability or dimensionality, and we found this surprising and worth describing.

      (5) The authors report that activity sparsifies, yet provide only the fraction of stimulus-selective cells. Given that cell detection was automated in a manner that takes into account neural activity (using Suite2p), it is difficult to interpret these results as presented. If the authors wish to claim sparsification, they need to provide evidence that the total number of ROIs drawn on each day (the denominator for sparseness in their calculation) is unbiased. Including more (or less) ROIs can dramatically change the calculated sparseness.

      The authors mention sparsification as contributing to coding efficiency but do not test this. Training a decoder on variously sized subsets of their data on days 0 and 5 would test whether redundant information is being eliminated in the network over training.

      First, we provide evidence for sparseness using a visual responsiveness metric in addition to stimulus-selectivity. Second, it is true that Suite2p’s segmentation is informed by activity and therefore may possibly omit cells with very minimal activity. However, we detected a comparable number of cells on day 5 (n=1500) to day 0 (1368). We reportedly roughly half as many cells are stimulus-selective on day 5 compared with day 0. In order for that to have been a result of biased ROI segmentation, we would have needed to have detected closer to 2600 cells on day 5 rather than 1500.  Therefore, we consider any bias in the segmentation to have had little effect on the main findings.

      (6) The authors claim their results show representational drift, but this isn't supported in the data. Rather they show that there is some information in the structure of activity that allows a decoder to learn block ID. But this does not show whether the actual stimulus representations change, and could instead reflect an unrelated artifact that changes over time (responsivity, alertness, bleaching, etc). To actually assess representational drift, the authors should directly compare representations across blocks (one could train a decoder on block 1 and test on blocks 2-5). In the absence of this or other tests of representational drift over blocks, the authors should remove the statement that "These findings suggest that there is a measurable amount of representational drift".

      “To actually assess representational drift, the authors should directly compare representations across blocks (one could train a decoder on block 1 and test on blocks 25)”: This is the exact analysis that was performed. Additionally, our analysis of pairwise correlations directly measures representational drift.

      “But this does not show whether the actual stimulus representations change, and could instead reflect an unrelated artifact that changes over time (responsivity, alertness, bleaching, etc)”: We have repeated the decoder analysis using normalized population vectors (Supplementary Figure 5) which we believe directly addresses whether the observed drift is due to photobleaching or alertness that would affect the overall magnitudes of response vectors.

      Our analysis of block decoding reflects decoders trained on individual stimulus elements, and we show the average over all such decodings (we have clarified this in the text). For example, we trained a decoder on ABCD presentations from block 1 and tested only against ABCD from other blocks, which I believe is the test being suggested by the reviewer. Furthermore, we do show that representational similarity for all stimulus elements reduces gradually and more-or-less monotonically as the time between presentations increases. We believe this is a fairly straightforward test of representational drift as has been reported and used elsewhere (Deitch et al., 2021).

      (7) The authors allude to "temporal echoes" in a subheading. This term is never defined, or substantiated with analysis, and should be removed.

      We hoped the term ‘temporal echo’ would be understood in the context of rebounding activity during gray periods as supported by analysis in figure 6a. We have eliminated the wording in the updated manuscript.

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      Reply to the reviewers

      1. General Statements [optional]

      We thank the reviewers for their insightful comments regarding our study and for appreciating the range of experiments used, the depth of our study and the significance of our work. We also thank reviewers with expertise in evolutionary biology for highlighting the need for precise wrong of some parts of the manuscript and the need for balancing the various viewpoints on the current understanding of early metazoan evolution. A point-by-point response to each reviewer comment is given below. We believe that we can effectively address most reviewer comments in a revised version. The revised improved manuscript will be the first insightful study of intracellular signalling pathways in the context of early animal evolution. We thank the reviewer for noting that this study is highly impactful and can have a broader influence on the scientific community.

      2. Description of the planned revisions

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

      __ Summary: The researchers identified PIP4K (phosphatidylinositol 5 phosphate 4-kinase) as a lipid kinase that is specific to metazoans. In order to determine its conserved function across metazoans, they compared PIP4K activity in both early-branching metazoans and bilaterian animals. Biochemical assays demonstrated a conserved catalytic activity between the sponge Amphimedon queenslandica (AqPIP4K) and human PIP4K. In in-vivo experiments, AqPIP4K was found to rescue the reduced cell size, growth, and development phenotype in larvae of null mutant in Drosophila PIP4K. Based on these findings, the authors suggest that the function of PIP4K was established in early metazoans to facilitate intercellular communication. The experiments were well designed, and a range of biochemical, in vitro, and in vivo experiments were conducted.__

      __ That being said, there are some questions that require further discussion before we can fully accept the author's conclusion of an evolutionarily conserved function of PIP4K across metazoans.__

      Major comments:

      • The authors mentioned that PIP4K is metazoan-specific and involved in intercellular communication. How can we explain the presence of PIP4K in choanoflagellate genomes? Despite its high similarity with conserved domains and functionally important residues, experimental results with the PIP4K from Choanoflagellate (Monosiga brevicollis, MbPIP4K) such as Mass spectrometry-based kinase assay and mutant Drosophila PIP4K didn't show similar activity to sponge AqPIP4K. The authors suggested that "In the context of other ancient PIP4K it is possible that since choanoflagellates exist as both single-cell and a transient multicellular state and do not have the characteristics of metazoans, PIP4K does not play any important functional role in these." However, this explanation is not well justified; they need to provide a more detailed discussion on this. Response: PIP4K is found in the genome of the choanoflagellate, M.brevicollis. MbPIP4K has the requisite kinase domain and the critical residue in the activation loop (A381) required for PIP4K activity is also conserved with the Amphimedon enzyme. Despite this, MbPIP4K was unable to rescue the growth and cell size phenotype of dPIP4K mutants (dPIP4K29) unlike AqPIP4K.

      We have previously published a comparison of the in vitro activity versus in vivo function for the three PIP4K enzymes in the human genome (Mathre et.al PMID: __30718367). While all three human PIP4K isoforms can functionally rescue the Drosophila dPIP4K mutant, there is a nearly 104-fold difference for in vitro activity between them with PIP4K2C showing almost no in vitro activity. __The difference in in vitro enzyme activity between MbPIP4K and AqPIP4K is similarly notable. We would however highlight that this is more likely a reflection of the limitations of the in vitro PIP4K activity.

      However, while AqPIP4K can rescue function in vivo (rescue of fly mutant phenotypes) MbPIP4K could not when expressed in fly cells. This must imply that there are differences in the polypeptide sequences of AqPIP4K and MbPIP4K that allow the former but not the latter to couple to the Insulin PI3K signalling pathway in fly cells. Given that Amphimedon and Choanoflagellates are separated by 100-150 Mya in evolution, this is possible. Our data on expression of AqPIP4K and MbPIP4K in fly S2 cells shows that they do not have equivalent localization (Fig 2C). What are the differences in the two polypeptides that lead to this? We will perform a multiple sequence alignment using PIP4K sequences from multiple choanoflagellates and sponges to identify these differences.

      We will include the results of this analysis and an appropriate discussion in the revised manuscript.

      • Likewise, the PIP4K gene has been identified in cnidarians, which are a sister group to bilaterian animals. However, the Cnidaria HvPIP4K showed no activity in biochemical or functional assays. In comparison to sponges, cnidarians are relatively complex organisms, and I believe that PIP4K is highly important for intercellular communication, as it is in bilaterians. The authors attempted to explain this by suggesting that "Based on theories of parallel evolution between cnidarians and sponges during early metazoan evolution, it is possible that the PIP4K gene was retained functional in one lineage and not in other." However, I am not convinced by this statement.

      Response: This is a really interesting and challenging question from the reviewer. We are aware that both sponges (Porifera) and Cnidaria are examples of primitive metazoans separated by 80-90 Mya of evolution, yet while AqPIP4K shows activity and can functionally rescue dPIP4K mutants, HvPIP4K cannot. What does this mean?

      A key difference between sponges and cnidarians is that while cnidarians have a simple “nerve-net” like nervous system, sponges do not have such a mode of communication. Therefore, it is possible that PIP4K, which we propose works in the context of hormone-based communication, is functionally important in sponges.

      We are of course aware and acknowledge that in a like for like experimental system (Drosophila cells) our data shows that the two proteins behave differently, be it in terms of in vitro activity or in vivo function. This must imply inherent differences in the two polypeptides.

      What we propose to do is to compare available PIP4K sequences from multiple Porifera and Cnidaria genomes and try and understand differences in the protein sequence that might explain differences in function. These results and their implications will be included in the revised manuscript.

      • Please provide details of the databases (Uniprot-KB, NCBI sequence database, Pfam) versions. After identifying the specific PIP4K protein in each species (e.g. AqPIP4K and HvPIP4K), have you considered performing a reciprocal blast against the human genome to see if you have a top hit to PIP4K? Hence, the main focus of the project is on PIP4K as a metazoan-specific protein. We need to include a wider representation of non-bilaterian animals, including multiple species from sponges, ctenophores, placozoans, and cnidarians. Additionally, please check if homologues of PIP4K are present in other unicellular holozoans besides choanoflagellates. Response: We will add the NCBI IDs for all the sequences. We have carried out reciprocal blast to human proteome and then classified the selected sequences as PIP4K, we will add the results in the supplementary for the same. We will add more species of sponges, ctenophores, placozoans, and cnidarians in our analysis of PIP4K sequences. We will also include an analysis of other unicellular holozoans where genome sequence is available.

      • Authors suggested the identification of other components of the PI signaling pathway along with PIP4k in the sponge. What is the status of these PI signaling pathway genes in other non-bilaterians and choanoflagellates? Response: We will add the details of the same in the revised manuscript and agree that this will help enhance the interpretation of our results.

      • Phylogenetic tree of all PIP4K sequences (Figure 1C): How authors can be certain that the identified PIP4K sequences (e.g. AqPIP4K, HvPIP4K, and MbPIP4K) are indeed PIP4K, especially when there are several closely related proteins? It is important to conduct phylogenetic analysis alongside other PIP sequences (such as PI3K, PI4K, PIP5K, and PIP4K). If this analysis is carried out, the identified AqPIP4K, HvPIP4K, and MbPIP4K should be grouped together with human PIP4K in the same cluster. Response: As described in the methods, we have searched all the individual genomes analyzed for all PIK and PIPK enzyme sequences. We have marked the domains (using Pfam and Interpro) on these sequences and eliminated other PIK and PIPK sequences (such as PI3K, PI4K, PIP5K) and selected only PIP4K. To additionally confirm the distinction between PIP5K and PIP4K, we have manually inspected each sequence to establish the identity of the A381 amino acid residue in the activation loop. The identity of the amino acid at this position in the activation loop has been experimentally demonstrated to be an essential feature of PIP4K (Kunze et.al PMID: 11733501) and we have also confirmed this independently in a recent study (Ghosh et.al PMID: 37316298).

      We will perform the phylogenetic analysis of the phosphoinositide kinases in the format suggested by the reviewer and add it in the revision as a supporting evidence.

      Minor comments:

      • Line 157: Phylogenetic conservation of PIP4Ks: Please provide details about bootstrap analysis. Response: Will be added

      • Line 230: symbol correction 30{degree sign}C Response: Will be done

      • Line 429-430: "from early metazoans like Sponges, Cnidaria and Nematodes." Nematodes are not considered early metazoans. Response: Apologies for the typo. This will be corrected. We agree that nematodes are not early metazoans.

      • Line 477-478: "However, interestingly, MbPIP4K::GFP localizes only at the plasma membrane in S2 cells (Figure 2C)." This part was not further discussed. Can you please elaborate on why MbPIP4K::GFP localizes only at the plasma membrane in S2 cells? Response: We have discussed this point specifically in response to major comment by the reviewer and it will be addressed as described.

      • Line 598: "the earliest examples of metazoa, namely the coral A. queenslandica" A. queenslandica is a sponge, not coral. Response: Apologies for the error. We will correct it.

      • Line 602: "Amphimedon and human enzyme, although separated by 50Mya years of evolution" I think it's 500 million years ago, not 50 million years ago. Response: This typo will be corrected.

      • Line 612: "coordinated communication between the cells is the most likely function" the cell. Response: Will change the sentence accordingly

      • Line 614: "intracellular phosphoinositide signalling the identity of the hormone" missing full stop punctuation. Response: Will change the sentence accordingly

      • Line 802 - 804: "other by way of difference in colour. The sub clusters have been numbered (1- early metazoans, 2- Nematodes, 3- Arthropods, 4- Molluscs, 5- Vertebrates (isoform PIP4K2C), 6- Vertebrates (isoform PIP4K2A), 7- Vertebrates (isoform PIP4K2B)." In the Figure, I can't find numbers on the subclusters. Response: Will add the numbers in the figure.

      • Line 805- 807: "Phylogenetic analysis of selected PIP4K sequences from model organisms of interest. PIP4K from A. queenslandica has been marked in rectangular box." The rectangular box is missing in the figure. Response: Will change the figure accordingly

      • Figure 1C: full forms of species names are missing. Response: Will change the figure accordingly

      Reviewer #1 (Significance (Required):

      The data is presented well, and the authors used a wide range of assays to support their conclusion. The study is highly impactful and can have a broader influence on the scientific community, particularly in evolutionary molecular biology, development, and biochemistry.

      The study provides interesting findings; however, the reasons for PIP4K not being functional in cnidarians as in sponges and why PIP4K is present in unicellular holozoans but not functional are unclear.

      We thank the reviewer for appreciating the significance and impact of our study. The very helpful questions raised by the reviewer will help enhance the quality of our study even further. We will make every effort to address these queries.

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

      The manuscript by Krishnan et al. uses molecular phylogenetics, in vitro kinase assays, heterologous expression assays in Drosophila S2 cells and mutant complementation assays in yeast to study the evolution and function of putative PIP4 kinase genes from a sponge, a cnidarian and a choanoflagellate. Based on these experiments, the authors conclude that PIP4K is metazoan-specific and that the sponge PIP4K has conserved functions in selectively phosphorylating PI5P.

      The study is in principle of interest and it could all be valid data, but the large number of flaws in the data presentation and/or analysis just makes it hard to assess the quality and thus validity of the data and conclusions.

      We thank the reviewer for appreciating the potential interest in our findings of PIP4K function in early metazoans. We thank them for noting the need for correcting data presentation and these will be done in the revision.

      __ Major comments:__

      Overall, the manuscript lacks scientific rigor in the analysis and representation of the results, and the validity of many of the conclusions is therefore difficult to assess.

      Major problems are:

      (i) The authors base their study on the evolution of PIP4K genes on a deeply flawed concept of animal evolution. On multiple occasions, including the title, the authors refer to extant species (e.g. Amphimedon) as 'early metazoan', 'regarded as the earliest evolved metazoan' (l. 46-7) or 'the earliest examples of metazoans' just to name a few. This reflects a 'ladder-like' view on evolution that suggests that extant sponges are identical to early 'steps' of animal evolution.

      We thank the reviewer who is clearly vastly more experienced in the field of evolutionary biology for the possible imprecise/incorrect usage of the word “ancient metazoan”. As new entrants to this area of evolutionary biology, we have of course referred to the existing literature such as PMID: 20686567 to guide us. This paper describes the sequencing of the A. queenslandica genome. It is clear that there is perceived value in studying this sponge in the context of early animal evolution although we are aware of there are a multitude of sponges and not all of them may be of value in the study of early animal evolution. We will peruse the literature more carefully and revise the manuscript to provide a more balanced view of this very interesting but unresolved area.

      Also, the author's interpretation that one cluster of genes 'contained the sequences from early metazoans like sponges, cnidaria and nematodes' is referring to an outdated idea of animal phylogeny where nematodes were thought to be ancestrally simple organisms grouped as 'Acoelomata'. This idea of animal phylogeny was however disproven by molecular phylogenetics since the 1990ies.

      Response: We are aware that the field of animal classification is undergoing continuous evolution. While earlier classifications may have been based of the presence or otherwise of a coelom and/or other anatomical features, we are aware of the use of molecular phylogenetics.

      The phylogeny presented in Fig 1C is based on the sequence relationships between the PIP4K sequences from various animal genomes. Any errors in the labelling of groups such as that highlighted by the reviewer will be revised or corrected after a careful consideration of extant views in the field, which are somewhat varied.

      (ii) The description of taxa in the phylogenetic tree in Fig. 1B lacks any understanding of phylogenetic relationships between animals and other eukaryotic groups. What kind of taxa are 'invertebrates' or 'parasites'? And why would 'invertebrates' exclude cnidarians and sponges? Also, why is the outgroup of opisthokonts named 'Eukaryota'?? Are not all organisms represented on the tree eukaryotes?

      Response: We apologize for this imprecision in labelling taxa. This will be corrected.

      (iii) The methods part lacks any information about the type of analysis (ML, Bayesian, Parsimony?) used to perform the phylogenetic analysis shown in Fig. 1C. Also, the authors mention three distinct clusters (l.428) that are not labelled in the figure.

      Response: We will update the methods to include the additional details requested by the reviewer. Fig 1C will be re-labelled.

      (iv) The validity of the Western Blot is difficult to assess as the authors have cut away the MW markers. Without, it is for example difficult to assess the size differences visible between Hydra and Monosiga PIP4K-GFP proteins on Fig. 2B. Also, it has become standard practice to show the whole Western blot as supplementary data in order to assess the correct size of the bands and the specificity of the antibody. This is also missing from this manuscript.

      Response: Cropped Western blots have been shown to facilitate figure preparation in the main manuscript. The complete uncropped Western blots, in all cases, will be shared as Source data as is the standard practice for multiple journals in the review Commons portfolio.

      (v) The authors claim that AqPIP4K was able to convert PI3P into PI with very low efficiency (Figure 2E), but without further label in the figure or explanation, it remains unclear how the authors come to this conclusion.

      Response: We regret the typo in line 500 of the manuscript we have stated that “Further,……… was able to convert PI3P into PI with very low efficiency (Figure 2E).” What we intended to write was “Further,……… was able to convert PI3P into PI (3,4) P2 with very low efficiency (Figure 2E).” The efficiency with which this reaction takes place is very low and has been reported by us (Ghosh et.al PMID: 31652444) and others (Zhang et.al PMID: 9211928). At the exposure of the TLC shown in Fig 2E the PI(3,4)P2 spot cannot been seen. Much longer exposures of the TLC plate will be needed to see the PI(3,4)P2 spot. This will be corrected in a revised version of the manuscript.

      (vi) The box plots in Fig. 3C and D lack error bars and thus seem to be consisting of only single data points without replicates. Also, Fig. 3C is a quantification of Fig. 3B but it remains unclear what has been quantified and how. It is also unclear how %PIP2 was determined.

      Response: For Fig 3C, the colony count has been done from three replicates and the average has been considered to calculate the % growth for each genotype. We will include error bars and clarify this in the revised figure legend. For Fig 3D, the PIP2/PIP ratio has been calculated from biological replicates and average has been represented in the graphs. The individual values can be provided as supplementary data.

      (vii) Throughout Fig. 4, I do not understand the genotypes indicated on the x-axis of the plots and below the images. I read the figure legends and manuscript describing these results at least 3 times, but cannot figure out what it all means. On Fig. 4C, what is the wild-type situation?

      Response: We apologize for the lack of precision in labelling the figures versus the figure legends. This will be corrected in the revision:

      The genotypes are as follows

      • w1118 (control) * Act-GAL4. This has been referred to as wild type in the figure legend and called Act-Gal4 in Fig4 panels A-E
      • dPIP4K29 – This refers to the protein null strain of dPIP4K. This strain is the background in which all reconstitutions of PIP4K genes have been done.
      • PIP4K transgene from A. queenslandica.
      • AqPIP4KKD Kinase dead PIP4K transgene from * queenslandica. In panels A, B, D and E, Act-GAL4: dPIP4K29* indicates the genetic background in which either AqPIP4K or AqPIP4KKD has been reconstituted.

      Reviewer #2 (Significance (Required)):

      If validated and put in the right phylogenetic context, the study is potentially contributing to expanding our knowledge on the evolution of metazoan-specific features, especially the evolution of proteins involved in cell-cell signalling and growth control. My field of expertise is broadly in evo-devo, molecular phylogentics, developmental genetics and cell biology. The in vitro lipid analysis seems interesting and potentially valid but I do not have sufficient expertise to evaluate its validity.

      We thank the reviewer for appreciating the novelty of our contribution and its potential to contribute to understanding the evolution of metazoan specific signalling systems, once appropriate corrections have been made. We also appreciate their positive comment on our in vitro experimental analysis. This paper is a big effort to not only perform phylogenetic analysis but address the emerging interpretations experimentally as much as possible.


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

      Summary In this manuscript, the authors investigate the evolutionary origins of metazoan Phosphatidylinositol phosphates (PIPs) signaling by elucidating the sequence and function of the PIP4K enzyme, which is crucial for converting PI5P to PI(4,5)P2 through phosphorylation. The authors have described PIP4K-like sequences distributed throughout metazoans and choanoflagellates through an extensive sequence screening. With in vitro and in vivo functional assays, the authors have shown that the sponge A. queenslandica PIP4K (AqPIP4K) is functionally similar to its human counterpart and highlight the major discovery of this study - that PIP4K protein function dates back to as early as sponges.

      We thank the reviewer for noting the major finding of our study and our efforts to experimentally validate, using multiple approaches, the findings of our detailed bioinformatics analysis of PIP4K gene distribution across the tree of life.

      Major comments

      There are two key limitations to this paper. Like the sponges, ctenophores are one of the earliest branching metazoans. They are not well addressed in the paper. Secondly, despite finding PIP4 homologs in choanoflagellates, the authors claim that PIP4 is metazoan-specific.

      We thank the reviewer for highlighting these two points; we recognize that both of these are important to address, to the extent that it is possible to do so. These will be addressed using the approaches detailed in the response to reviewer 1 comments.

      1. Line 46: A. queenslandica is the earliest branching metazoan. The phylogeny of sponges and ctenophores is not conclusively defined and hence, the statement must be rephrased. Despite the brief description of the evolution of metazoan lineage in the discussion section, ctenophores are missing from the phylogenetic tree. At least a sequence-level information PIP4K in ctenophores would strongly back the claims of the manuscript. Here is the link to the Mnemiopsis database. Response: We thank the reviewer for highlighting this point and pointing us to the Mnemiopsis database. We will most certainly analyse ctenophore genome sequences and add the ctenophore PIP4K sequence to the phylogeny, post analysis and the discussion will be modified to reflect the findings.

      Mentioning that choanoflagellates contain homologs of PIP4K contradicts the statement that PIP4K is metazoan-specific. As per Fig 1E., the domain organization of PIP4K is conserved among choanoflagellates and metazoans. What is the percent sequence similarity to the query? This could answer why it doesn't show activity in Drosophila rescues - the system might simply not be compatible with the choanoflagellate homolog. The same may apply to the cnidarian homolog HvPIP4K. Further evidence is needed before concluding that MbPIP4K doesn't phosphorylate PIP5. It is additionally fascinating that MbPIP4K localizes at the plasma membrane unlike other homologs - this function might be choano-specific. Overall, PIP4K's possible origin in the choanoflagellate-metazoan common ancestor backs the current research that choanoflagellates indeed hold clues to understanding metazoan evolution. Further research is necessary before concluding (as in line 648) in the discussions section, where it is mentioned that "PIP4K does not play any important functional role in choanos".

      Response: We thank the reviewer for highlighting the very interesting but incompletely understood facets of our study vis-à-vis choanoflagellates versus metazoans. The proposal for additional analysis is indeed interesting and we will carry out these analysis and revise the text accordingly.

      __ Minor Comments__

      1. A detailed comparison of the sequence of the hydra PIP4K might help understand why it may not have worked like the sponge PIP4K. The discussion on the cnidarian PIP4K evolution is not convincing. It may not have worked because of it being expressed in a non-natural system. Structure prediction and comparison of proteins from different early branching animals should be used. Response: Thank you for these suggestions to understand why the cnidarian PIP4K may not have been functional. We will perform the suggested analysis and incorporate the data into the revision.

      78 - Multicellularity evolved many times. Maybe say 'first evolved metazoans'

      Response: Thank you for the suggestion.

      Line 598 A. queenslandica is not a coral, it's a sponge.

      Response: Text will be changed accordingly

      Line 612 'thcells' à 'the cells'

      Response: Text will be changed.

      Line 623 - full stop missing after metazoans.

      Response: Text will be changed

      Figure 1B - Classification should be consistent - C. elegans is a species name, whereas ctenophores and vertebrates belong to a different classification. Invertebrates is not a scientific group. The edges of the lines of the phylogenetic tree don't join and they need to be arranged correctly.

      Response: The names in the phylogeny will be changed to maintain uniformity. The representation of the phylogeny will be changed as mentioned.

      Figure 2B The full blot could be shown in the supplement.

      Response: Full blot will be provided as source data on resubmission or included as supplementary based on the destination journal’s specification.


      Optional

      1. Heterologous overexpression does not always provide the full picture of the gene functionality. To make claims on the evolution of function, testing gene functions homologous systems can give a better picture. For example, performing in vitro kinase activity assays of MbPIP4K after overexpressing PIP4K in Monosiga brevicollis. would be a great. Data is missing also about the presence and function of ctenophore PIP4K. Overexpression of ctenophore-PIP4K in Drosophila for functional analyses could help in understanding the distribution/diversity of function of PIP4K in early animals. Response: We agree with the reviewer that heterologous expression may sometimes not replicate the biochemical environment of cells in the organism from which the gene being expressed was originally derived. Yet, heterologous expression experiments do sometimes provide an insight into properties solely dependent on the polypeptide with limited or no contribution from the cellular environment. In principle expressing PIP4K in M.brevicollis cells and then performing kinase assays would be a very good idea. However, we would like to highlight that till date there has been only one study where septins have been transfected in Choanoflagellates and their localization being observed. We are not set up to culture M. brevicollis and will be unable to do this for a revision of the current manuscript. However, we appreciate the importance of this experiment and will do this in collaboration with a choanoflagellate lab in a follow up study to this one.

      Ctenophores like cnidarians have two main layers of cells that sandwich a middle layer of jelly-like material, while, more complex animals have three main cell layers and no intermediate jelly-like layer. Hence ctenophores and cnidarians have traditionally been labelled diploblastic. Studies have shown that ctenophores and unicellular eukaryotes share ancestral metazoan patterns of chromosomal arrangements, whereas sponges, bilaterians, and cnidarians share derived chromosomal rearrangements. Conserved syntenic characters unite sponges with bilaterians, cnidarians, and placozoans in a monophyletic clade while ctenophores are excluded from this clustering, placing ctenophores as the sister group to all other animals. Ctenophore PIP4K sequence can be identified and compared as discussed before to other PIP4K sequences used in this study.

      Reviewer #3 (Significance (Required)):

      Significance: This is the first study that addresses PIP signaling pathway in early metazoans. The findings of this manuscript contribute to the understanding of second-messenger signaling and its link with the origin and evolution of metazoan multicellularity. PIP signaling is crucial in different metazoan aspects such as cytoskeletal dynamics, neurotransmission, and vesicle trafficking, and hence, plays a critical role in metazoan multicellularity. Through this study, it was interesting to see that some components of the PIP signaling pathway are conserved in yeast, but some, such as the PIP4K protein evolved at the brink of metazoan evolution, highlighting the need for complexity in metazoans and their close relatives - the facultatively multicellular choanoflagellates. Since this is a crucial pathway in human biology and has medical significance due to its role in tumorigenesis and cancer cell migration, this study serves the audience in basic research such as evolutionary biology, and applied research such as human medicine. My field of expertise is molecular biology, cell biology and microbiology, with specific expertise on choanoflagellates. Therefore, it is exciting to see the homologs of PIP4K present in choanoflagellates.

      __ Evidence, Reproducibility, and clarity:__

      The authors have made a clear case of why PIP4K needs to be studied. They have thoroughly mapped PIP4K throughout the tree of life. The results are clear and reproducible. With the findings of this study, they have linked the PIP signalling cascade and metazoan evolution. Using the heterologous expression of sponge A. queensladica PIP4K, they have made compelling evidence that AqPIP4K functions in PIP5 phosphorylation, as seen in humans and Drosophila. However, it was not convincing why the hydra PIP4K was not functional. It was also not convincing why the PIP4K is metazoan-only when there is a conserved sequence (with conserved domain structure) present in choanoflagellates.


      We thank the reviewer for appreciating the novelty and importance of our findings in multiple areas of basic biology related to early metazoans and basic biomedical sciences. We also note their comments on the clear and reproducible results presented. Points raised related to the lack of functionality of PIP4K from Hydra and choanoflagellates are noted and will be addressed as indicated in response to other reviewer comments.


      Experiments/Analysis to be done

      1. We will perform a multiple sequence alignment using PIP4K sequences from multiple choanoflagellates and sponges to identify these differences.
      2. What we propose to do is to compare available PIP4K sequences from multiple Porifera and Cnidaria genomes and try and understand differences in the protein sequence that might explain differences in function.
      3. We will add more species of sponges, ctenophores, placozoans, and cnidarians in our analysis of PIP4K sequences. We will also include an analysis of other unicellular holozoans where genome sequence is available.
      4. We will perform the phylogenetic analysis of the phosphoinositide kinases in the format suggested by the reviewer and add it in the revision as a supporting evidence.
      5. Structure prediction and comparison of proteins from different early branching animals should be used.
      6. Uniformity of terminology and alignment with conventions in the field of animal taxonomy
      7. NCBI ID of sequences to be added and include more non-bilaterian animals sequences in phylogeny- redo the phylogeny.
      8. Check for PI signalling genes in choanoflagellates
      9. More detailed description of phylogenetic analysis.
      10. Add complete Western blot as source data.
      11. *

      3. Description of the revisions that have already been incorporated in the transferred manuscript

      Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

      • *

      4. Description of analyses that authors prefer not to carry out

      • Expression of PIP4K in choanoflagellates and in vitro kinase assays with lysates. It is beyond our technical ability to perform these experiments at this stage.
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      Referee #3

      Evidence, reproducibility and clarity

      Summary

      In this manuscript, the authors investigate the evolutionary origins of metazoan Phosphatidylinositol phosphates (PIPs) signaling by elucidating the sequence and function of the PIP4K enzyme, which is crucial for converting PI5P to PI(4,5)P2 through phosphorylation. The authors have described PIP4K-like sequences distributed throughout metazoans and choanoflagellates through an extensive sequence screening. With in vitro and in vivo functional assays, the authors have shown that the sponge A. queenslandica PIP4K (AqPIP4K) is functionally similar to its human counterpart and highlight the major discovery of this study - that PIP4K protein function dates back to as early as sponges.

      Major comments

      There are two key limitations to this paper. Like the sponges, ctenophores are one of the earliest branching metazoans. They are not well addressed in the paper. Secondly, despite finding PIP4 homologs in choanoflagellates, the authors claim that PIP4 is metazoan-specific.

      1. Line 46: A. queenslandica is the earliest branching metazoan. The phylogeny of sponges and ctenophores is not conclusively defined and hence, the statement must be rephrased. Despite the brief description of the evolution of metazoan lineage in the discussion section, ctenophores are missing from the phylogenetic tree. At least a sequence-level information PIP4K in ctenophores would strongly back the claims of the manuscript. Here is the link to the Mnemiopsis database.
      2. Mentioning that choanoflagellates contain homologs of PIP4K contradicts the statement that PIP4K is metazoan-specific. As per Fig 1E., the domain organization of PIP4K is conserved among choanoflagellates and metazoans. What is the percent sequence similarity to the query? This could answer why it doesn't show activity in Drosophila rescues - the system might simply not be compatible with the choanoflagellate homolog. The same may apply to the cnidarian homolog HvPIP4K. Further evidence is needed before concluding that MbPIP4K doesn't phosphorylate PIP5. It is additionally fascinating that MbPIP4K localizes at the plasma membrane unlike other homologs - this function might be choano-specific. Overall, PIP4K's possible origin in the choanoflagellate-metazoan common ancestor backs the current research that choanoflagellates indeed hold clues to understanding metazoan evolution. Further research is necessary before concluding (as in line 648) in the discussions section, where it is mentioned that "PIP4K does not play any important functional role in choanos".

      Minor Comments

      1. A detailed comparison of the sequence of the hydra PIP4K might help understand why it may not have worked like the sponge PIP4K. The discussion on the cnidarian PIP4K evolution is not convincing. It may not have worked because of it being expressed in a non-natural system. Structure prediction and comparison of proteins from different early branching animals should be used.
      2. 78 - Multicellularity evolved many times. Maybe say 'first evolved metazoans'
      3. Line 598 A. queenslandica is not a coral, it's a sponge.
      4. Line 612 'thcells'  'the cells'
      5. Line 623 - full stop missing after metazoans.
      6. Figure 1B - Classification should be consistent - C. elegans is a species name, whereas ctenophores and vertebrates belong to a different classification. Invertebrates is not a scientific group. The edges of the lines of the phylogenetic tree don't join and they need to be arranged correctly.
      7. Figure 2B The full blot could be shown in the supplement.

      Optional

      1. Heterologous overexpression does not always provide the full picture of the gene functionality. To make claims on the evolution of function, testing gene functions homologously systems can give a better picture. For example, performing in vitro kinase activity assays of MbPIP4K after overexpressing PIP4K in Monosiga brevicollis. would be a great. Data is missing also about the presence and function of ctenophore PIP4K. Overexpression of ctenophore-PIP4K in Drosophila for functional analyses could help in understanding the distribution/diversity of function of PIP4K in early animals.

      Significance

      This is the first study that addresses PIP signaling pathway in early metazoans. The findings of this manuscript contribute to the understanding of second-messenger signaling and its link with the origin and evolution of metazoan multicellularity. PIP signaling is crucial in different metazoan aspects such as cytoskeletal dynamics, neurotransmission, and vesicle trafficking, and hence, plays a critical role in metazoan multicellularity. Through this study, it was interesting to see that some components of the PIP signaling pathway are conserved in yeast, but some, such as the PIP4K protein evolved at the brink of metazoan evolution, highlighting the need for complexity in metazoans and their close relatives - the facultatively multicellular choanoflagellates. Since this is a crucial pathway in human biology and has medical significance due to its role in tumorigenesis and cancer cell migration, this study serves the audience in basic research such as evolutionary biology, and applied research such as human medicine. My field of expertise is molecular biology, cell biology and microbiology, with specific expertise on choanoflagellates. Therefore, it is exciting to see the homologs of PIP4K present in choanoflagellates.

      Evidence, Reproducibility, and clarity:

      The authors have made a clear case of why PIP4K needs to be studied. They have thoroughly mapped PIP4K throughout the tree of life. The results are clear and reproducible. With the findings of this study, they have linked the PIP signalling cascade and metazoan evolution. Using the heterologous expression of sponge A. queensladica PIP4K, they have made compelling evidence that AqPIP4K functions in PIP5 phosphorylation, as seen in humans and Drosophila. However, it was not convincing why the hydra PIP4K was not functional. It was also not convincing why the PIP4K is metazoan-only when there is a conserved sequence (with conserved domain structure) present in choanoflagellates.

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      Referee #2

      Evidence, reproducibility and clarity

      The manuscript by Krishnan et al. uses molecular phylogenetics, in vitro kinase assays, heterologous expression assays in Drosophila S2 cells and mutant complementation assays in yeast to study the evolution and function of putative PIP4 kinase genes from a sponge, a cnidarian and a choanoflagellate. Based on these experiments, the authors conclude that PIP4K is metazoan-specific and that the sponge PIP4K has conserved functions in selectively phosphorylating PI5P.

      The study is in principle of interest and it could all be valid data, but the large number of flaws in the data presentation and/or analysis just makes it hard to assess the quality and thus validity of the data and conclusions.

      Major comments:

      Overall, the manuscript lacks scientific rigour in the analysis and representation of the results, and the validity of many of the conclusions is therefore difficult to assess.

      Major problems are:

      (i) The author base their study on the evolution of PIP4K genes on a deeply flawed concept of animal evolution. On multiple occassions, including the title, the authors refer to extant species (e.g. Amphimedon) as 'early metazoan', 'regarded as the earliest evolved metazoan' (l. 46-7) or 'the earliest examples of metazoans' just to name a few. This reflects a 'ladder-like' view on evolution that suggests that extant sponges are identical to early 'steps' of animal evolution. Also, the author's interpretation that one cluster of genes 'contained the sequences from early metazoans like sponges, cnidaria and nematodes' is referring to an outdated idea of animal phylogeny where nematodes were thought to be ancestrally simple organisms grouped as 'Acoelomata'. This idea of animal phylogeny was however disproven by molecular phylogenetics since the 1990ies.

      (ii) The description of taxa in the phylogenetic tree in Fig. 1B lacks any understanding of phylogenetic relationships between animals and other eukaryotic groups. What kind of taxa are 'invertebrates' or 'parasites'? And why would 'invertebrates' exclude cnidarians and sponges? Also, why is the outgroup of opisthokonts named 'Eukaryota'?? Are not all organisms represented on the tree eukaryotes?

      (iii) The methods part lacks any information about the type of analysis (ML, Bayesian, Parsimony?) used to perform the phylogenetic analysis shown in Fig. 1C. Also, the authors mention three distinct clusters (l.428) that are not labelled in the figure.

      (iv) The validity of the Western Blot is difficult to assess as the authors have cut away the MW markers. Without, it is for example difficult to assess the size differences visible between Hydra and Monosiga PIP4K-GFP proteins on Fig. 2B. Also, it has become standard practice to show the whole Western blot as supplementary data in order to assess the correct size of the bands and the specificity of the antibody. This is also missing from this manuscript.

      (v) The authors claim that AqPIP4K was able to convert PI3P into PI with very low efficiency (Figure 2E), but without further label in the figure or explanation, it remains unclear how the authors come to this conclusion.

      (vi) The box plots in Fig. 3C and D lack error bars and thus seem to be consisting of only single data points without replicates. Also, Fig. 3C is a quantification of Fig. 3B but it remains unclear what has been quantified and how. It is also unclear how %PIP2 was determined.

      (vii) Throughout Fig. 4, I do not understand the genotypes indicated on the x-axis of the plots and below the images. I read the figure legends and manuscript describing these results at least 3 times, but cannot figure out what it all means. On Fig. 4C, what is the wild-type situation?

      Significance

      If validated and put in the right phylogenetic context, the study is potentially contributing to expanding our knowledge on the evolution of metazoan-specific features, especially the evolution of proteins involved in cell-cell signalling and growth control.

      My field of expertise is broadly in evo-devo, molecular phylogentics, developmental genetics and cell biology. The in vitro lipid analysis seems interesting and potentially valid but I do not have sufficient expertise to evaluate its validity.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      The researchers identified PIP4K (phosphatidylinositol 5 phosphate 4-kinase) as a lipid kinase that is specific to metazoans. In order to determine its conserved function across metazoans, they compared PIP4K activity in both early-branching metazoans and bilaterian animals. Biochemical assays demonstrated a conserved catalytic activity between the sponge Amphimedon queenslandica (AqPIP4K) and human PIP4K. In in-vivo experiments, AqPIP4K was found to rescue the reduced cell size, growth, and development phenotype in larvae of null mutant in Drosophila PIP4K. Based on these findings, the authors suggest that the function of PIP4K was established in early metazoans to facilitate intercellular communication. The experiments were well designed, and a range of biochemical, in vitro, and in vivo experiments were conducted. That being said, there are some questions that require further discussion before we can fully accept the author's conclusion of an evolutionarily conserved function of PIP4K across metazoans.

      Major comments:

      • The authors mentioned that PIP4K is metazoan-specific and involved in intercellular communication. How can we explain the presence of PIP4K in choanoflagellate genomes? Despite its high similarity with conserved domains and functionally important residues, experimental results with the PIP4K from Choanoflagellate (Monosiga brevicollis, MbPIP4K) such as Mass spectrometry-based kinase assay and mutant Drosophila PIP4K didn't show similar activity to sponge AqPIP4K. The authors suggested that "In the context of other ancient PIP4K it is possible that since choanoflagellates exist as both single-cell and a transient multicellular state and do not have the characteristics of metazoans, PIP4K does not play any important functional role in these." However, this explanation is not well justified; they need to provide a more detailed discussion on this.
      • Likewise, the PIP4K gene has been identified in cnidarians, which are a sister group to bilaterian animals. However, the Cnidaria HvPIP4K showed no activity in biochemical or functional assays. In comparison to sponges, cnidarians are relatively complex organisms, and I believe that PIP4K is highly important for intercellular communication, as it is in bilaterians. The authors attempted to explain this by suggesting that "Based on theories of parallel evolution between cnidarians and sponges during early metazoan evolution, it is possible that the PIP4K gene was retained functional in one lineage and not in other." However, I am not convinced by this statement.
      • Please provide details of the databases (Uniprot-KB, NCBI sequence database, Pfam) versions. After identifying the specific PIP4K protein in each species (e.g AqPIP4K and HvPIP4K), have you considered performing a reciprocal blast against the human genome to see if you have a top hit to PIP4K? Hence, the main focus of the project is on PIP4K as a metazoan-specific protein. We need to include a wider representation of non-bilaterian animals, including multiple species from sponges, ctenophores, placozoans, and cnidarians. Additionally, please check if homologues of PIP4K are present in other unicellular holozoans besides choanoflagellates.
      • Authors suggested the identification of other components of the PI signaling pathway along with PIP4k in the sponge. What is the status of these PI signaling pathway genes in other non-bilaterians and choanoflagellates?
      • phylogenetic tree of all PIP4K sequences (Figure 1C): How authors can be certain that the identified PIP4K sequences (e.g AqPIP4K, HvPIP4K, and MbPIP4K) are indeed PIP4K, especially when there are several closely related proteins? It is important to conduct phylogenetic analysis alongside other PIP sequences (such as PI3K, PI4K, PIP5K, and PIP4K). If this analysis is carried out, the identified AqPIP4K, HvPIP4K, and MbPIP4K should be grouped together with human PIP4K in the same cluster.

      Minor comments:

      • Line 157: Phylogenetic conservation of PIP4Ks: Please provide details about bootstrap analysis.
      • Line 230: symbol correction 30{degree sign}C
      • Line 429-430: "from early metazoans like Sponges, Cnidaria and Nematodes." Nematodes are not considered early metazoans.
      • Line 477-478: "However, interestingly, MbPIP4K::GFP localizes only at the plasma membrane in S2 cells (Figure 2C)." This part was not further discussed. Can you please elaborate on why MbPIP4K::GFP localizes only at the plasma membrane in S2 cells?
      • Line 598: "the earliest examples of metazoa, namely the coral A.queenslandica" A.queenslandica is a sponge, not coral.
      • Line 602: "Amphimedon and human enzyme, although separated by 50Mya years of evolution" I think it's 500 million years ago, not 50 million years ago.
      • Line 612: "co-ordinated communication between thcells is the most likely function" the cell.
      • Line 614: "intracellular phosphoinositide signalling The identity of the hormone" missing full stop punctuation.
      • Line 802 - 804: "other by way of difference in colour. The sub clusters have been numbered (1- early metazoans, 2- Nematodes, 3- Arthropods, 4- Molluscs, 5- Vertebrates (isoform PIP4K2C), 6- Vertebrates (isoform PIP4K2A), 7- Vertebrates (isoform PIP4K2B)." In the Figure, I can't find numbers on the subclusters.
      • Line 805- 807: "Phylogenetic analysis of selected PIP4K sequences from model organisms of interest. PIP4K from A.queenslandica has been marked in rectangular box." The rectangular box is missing in the figure.
      • Figure 1C: full forms of species names are missing.

      Significance

      The data is presented well, and the authors used a wide range of assays to support their conclusion. The study is highly impactful and can have a broader influence on the scientific community, particularly in evolutionary molecular biology, development, and biochemistry.

      The study provides interesting findings; however, the reasons for PIP4K not being functional in cnidarians as in sponges and why PIP4K is present in unicellular holozoans but not functional are unclear.

    1. Reviewer #1 (Public review):

      Summary:

      This work aims at understanding the role of thalamus POm in dorsal lateral striatum (DLS) projection in learning a sensorimotor associative task. The authors first confirm that POm forms "en passant" synapses with some of the DLS neuronal subtypes. They then perform a go/no-go associative task that consists of the mouse learning to discriminate between two different textures and to associate one of them with an action. During this task they either record the activity of the POm to DLS axons using endoscopy or silence their activity. They report that POm axons in the DLS are activated around the sensory stimulus but that the activity is not modulated by the reward. Last, they showed that silencing the POm axons at the level of DLS slows down learning the task.

      The authors show convincing evidence of projections from POm to DLS and that POm inputs to DLS code for whisking whatever the outcome of the task is. However, their results do not allow to conclude if more neurones are recruited during the learning process or if the already activated fibres get activated more strongly. Last, because POm fibres in the DLS are also projecting to S1, silencing the POm fibres in the DLS could have affected inputs in S1 as well and therefore, the slowdown in acquiring the task is not necessarily specific to the POm to DLS pathway.

      Strengths:

      One of the main strengths of the paper is to go from slice electrophysiology to behaviour to get an in-depth characterization of one pathway. The authors did a comprehensive description of the POm projections to the DLS using transgenic mice to unambiguously identify the DLS neuronal population. They also used a carefully designed sensorimotor association task, and they exploited the results in depth.

      It is a very nice effort to have measured the activity of the axons in the DLS not only after the mice have learned the task but throughout the learning process. It shows the progressive increase of activity of POm axons in the DLS, which could imply that there is a progressive strengthening of the pathway. The results show convincingly that POm axons in the DLS are not activated by the outcome of the task but by the whisker activity, and that this activity in average increases with learning.

      Weaknesses:

      One of the main targets of the striatum from thalamic input are the cholinergic neurons that weren't investigated here, is there information that could be provided?

      It is interesting to know that the POm projects to all neuronal types in the DLS, but this information is not used further down the manuscript so the only take-home message of Figure 1 is that the axons that they image or silence in the DLS are indeed connected to DLS neurons and not just passing fibres. In this line, are these axons the same as the ones projecting to S1? If this is the case, why would we expect a different behaviour of the axon activity at the DLS level compared to S1?

      The authors used endoscopy to measure the POm axons in the DLS activity, which makes it impossible to know if the progressive increase of POm response is due to an increase of activity from each individual neurons or if new neurons are progressively recruited in the process.

      The picture presented in Figure 4 of the stimulation site is slightly concerning as there are hardly any fibres in neocortical layer 1 while there seems to be quite a lot of them in layer 4, suggesting that the animal here was injected in the VB. This is especially striking as the implantation and projection sites presented in Figure 1 and 2 are very clean and consistent with POm injection.

      Comment after review: The weaknesses remain as concerns have not been addressed. The dataset is interesting but the interpretation, due partly to the lack of control (especially relative to VPM contamination), is difficult.

    2. Reviewer #3 (Public review):

      Yonk and colleagues investigate the role of the thalamostriatal pathway. Specifically, they studied the interaction of the posterior thalamic nucleus (PO) and the dorsolateral striatum in the mouse. First, they characterize connectivity by recording DLS neurons in in vitro slices and optogenetically activating PO terminals. PO is observed to establish depressing synapses onto D1 and D2 spiny neurons as well as PV neurons. Second, the image PO axons are imaged by fiber photometry in mice trained to discriminate textures. Initially, no trial-locked activity is observed, but as the mice learn PO develops responses timed to the audio cue that marks the start of the trial and precedes touch. PO does appear to encode the tactile stimulus type or outcome. Optogenetic suppression of PO terminals in striatum slow task acquisition. The authors conclude that PO provides a "behaviorally relevant arousal-related signal" and that this signal "primes" striatal circuitry for sensory processing.

      A great strength of this paper is its timeliness. Thalamostriatal processing has received almost no attention in the past, and the field has become very interested in the possible functions of PO. Additionally, the experiments exploit multiple cutting-edge techniques.

      There seem to be some technical/analytical weaknesses. The in vitro experiments appear to have some contamination of nearby thalamic nuclei by the virus delivering the opsin, which could change the interpretation. Some of the statistical analysis of these data also appear inappropriate. The correlative analysis of Pom activity in vivo, licking, and pupil could be more convincingly done.

      The bigger weakness is conceptual - why should striatal circuitry need "priming" by thalamus in order to process sensory stimuli? Why would such circuitry even be necessary? Why is a sensory signal from cortex insufficient? Why should the animal more slowly learn the task? How does this fit with existing ideas of striatal plasticity? It is unclear from the experiments that the thalamostriatal pathway exists for priming sensory processing. In fact the optogenetic suppression of the thalamostriatal pathway seems to speak against that idea.

      Comments on revisions:

      The authors have only tweaked the Discussion and not necessarily in ways that addressed our previous comments. They could have fairly easily analyzed the effect of distance of recording from injection site and compared subsets of data depending on contamination beyond PO (my comments 1 and 2) or effects of movements (3 and 4). Minimally, they could have given caveats in the Results and Discussion about these, and I would strongly encourage them to be explicit about the caveats. The analyses would probably be better.

      The suggestion that the effects have something to do with priming (5), seems a grasp for function of the circuit.

    3. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This work aims to understand the role of thalamus POm in dorsal lateral striatum (DLS) projection in learning a sensorimotor associative task. The authors first confirm that POm forms "en passant" synapses with some of the DLS neuronal subtypes. They then perform a go/no-go associative task that consists of the mouse learning to discriminate between two different textures and to associate one of them with an action. During this task, they either record the activity of the POm to DLS axons using endoscopy or silence their activity. They report that POm axons in the DLS are activated around the sensory stimulus but that the activity is not modulated by the reward. Last, they showed that silencing the POm axons at the level of DLS slows down learning the task.

      The authors show convincing evidence of projections from POm to DLS and that POm inputs to DLS code for whisking whatever the outcome of the task is. However, their results do not allow us to conclude if more neurons are recruited during the learning process or if the already activated fibres get activated more strongly. Last, because POm fibres in the DLS are also projecting to S1, silencing the POm fibres in the DLS could have affected inputs in S1 as well and therefore, the slowdown in acquiring the task is not necessarily specific to the POm to DLS pathway.

      We thank the reviewer for these constructive comments. The points are addressed below.  

      Strengths:

      One of the main strengths of the paper is to go from slice electrophysiology to behaviour to get an in-depth characterization of one pathway. The authors did a comprehensive description of the POm projections to the DLS using transgenic mice to unambiguously identify the DLS neuronal population. They also used a carefully designed sensorimotor association task, and they exploited the results in depth.

      It is a very nice effort to have measured the activity of the axons in the DLS not only after the mice have learned the task but throughout the learning process. It shows the progressive increase of activity of POm axons in the DLS, which could imply that there is a progressive strengthening of the pathway. The results show convincingly that POm axons in the DLS are not activated by the outcome of the task but by the whisker activity, and that this activity on average increases with learning.

      Weaknesses:

      One of the main targets of the striatum from thalamic input are the cholinergic neurons that weren't investigated here, is there information that could be provided?

      This is true of the parafascicular (Pf) thalamic nucleus, which has been well studied in this context. However, there is much less known about the striatal projections of other thalamic nuclei, including POm, and their inputs to cholinergic neurons. Anatomical tracing evidence from Klug et al. (2018), which mapped brain-wide inputs to striatal cholinergic (ChAT) interneurons, suggests that Pf provides the majority of thalamic innervation of striatal ChAT neurons compared to other thalamic nuclei. Many other thalamic nuclei, including POm, showed very little of no labeling, suggesting weak innervation of ChAT interneurons. However, it is possible that these thalamic nuclei, including POm, do provide functional innervation of ChAT interneurons that is not sufficiently assessed by anatomical tracing. Understanding the innervation patterns of POm-striatal projections beyond the three cell types we have studied here would be an important area of further study.

      It is interesting to know that the POm projects to all neuronal types in the DLS, but this information is not used further down the manuscript so the only take-home message of Figure 1 is that the axons that they image or silence in the DLS are indeed connected to DLS neurons and not just passing fibres. In this line, are these axons the same as the ones projecting to S1? If this is the case, why would we expect a different behaviour of the axon activity at the DLS level compared to S1?

      Tracing of single POm axons by Ohno et al. (2012) indicated that POm axons form a branched collateral that innervates striatum, while the main axon continues in the rostral-dorsal direction to innervate cortex. We think it is reasonable, based on the morphology, that our optogenetic suppression experiment restricted the suppression of glutamate release to this branch and avoided the other branches of the axon that project to cortex. However, testing this would require monitoring S1 activity during the POm-striatal axon suppression, which we did not do in this study.

      It is a very interesting question whether there could be different axon activity behavior in striatum versus S1. There is surprising evidence that POm synaptic terminals are different sizes in S1 and M1 and show different synaptic physiological properties depending on these cortical projection targets (Casas-Torremocha et al., 2022). Based on this, it is possible that POm-striatal synapses show distinct properties compared to cortex; however, this will need to be tested in future work.

      The authors used endoscopy to measure the POm axons in the DLS activity, which makes it impossible to know if the progressive increase of POm response is due to an increase of activity from each individual neuron or if new neurons are progressively recruited in the process.

      This is a good point. It would be necessary to perform chronic two-photon imaging of POm neurons (or chronic electrophysiological recordings) to determine whether the activity of individual neurons increased versus whether individual neuron activity levels remained similar but new neurons became active with learning. Even under baseline conditions, it is not known in detail what fraction of the population of POm neurons is active during sensory processing or behavior, highlighting how much is still to be discovered in this exciting area of neuroscience.

      The picture presented in Figure 4 of the stimulation site is slightly concerning as there are hardly any fibres in neocortical layer 1 while there seems to be quite a lot of them in layer 4, suggesting that the animal here was injected in the VB. This is especially striking as the implantation and projection sites presented in Figures 1 and 2 are very clean and consistent with POm injection.

      Although this image was selected to demonstrate the position of the POm injection site and optical fiber implant above striatal axons, the reviewer is correct that there appears to be mixed labeling of axons in L4 and L5a. In some cases, there was expression slightly outside the border of POm (see Fig. 1B, right), which might explain the cortical innervation pattern in this figure. While cortically bound VPM axons pass through the striatum, they do not form synaptic terminals until reaching the cortex (Hunnicutt et al., 2016). If, as may be the case, inhibitory opsins suppress release of neurotransmitter at synaptic terminals more effectively than action potential propagation in axons, it may be likely that optogenetic suppression of POm-striatal terminals is more effective than suppression of action potentials in off-target-labelled VPM axons of passage. Ideally, we could compare effects of suppression of POm-striatal synapses with POm-cortical synapses and VPM-cortical synapses, but this was outside the bandwidth of the present study.

      Reviewer #2 (Public Review):

      Summary:

      Yonk and colleagues show that the posterior medial thalamus (POm), which is interconnected with sensory and motor systems, projects directly to major categories of neurons in the striatum, including direct and indirect pathway MSNs, and PV interneurons. Activity in POm-striatal neurons during a sensory-based learning task indicates a relationship between reward expectation and arousal. Inhibition of these neurons slows reaction to stimuli and overall learning. This circuit is positioned to feed salient event activation to the striatum to set the stage for effective learning and action selection.

      Strengths:

      The results are well presented and offer interesting insight into an understudied thalamostriatal circuit. In general, this work is important as part of a general need for an increased understanding of thalamostriatal circuits in complex learning and action selection processes, which have generally received less attention than corticostriatal systems.

      Weaknesses:

      There could be a stronger connection between the connectivity part of the data - showing that POm neurons context D1, D2, and PV neurons in the striatum but with some different properties - and the functional side of the project. One wonders whether the POm neurons projecting to these subtypes or striatal neurons have unique signaling properties related to learning, or if there is a uniform, bulk signal sent to the striatum. This is not a weakness per se, as it's reasonable for these questions to be answered in future papers.

      We are very interested to understand the potentially distinct learning-related synaptic and circuit changes that potentially occur at the POm synapses with D1- and D2-SPNs and PV interneurons, and other striatal cell types. We agree that this would be an important topic for further investigation.

      All the in vivo activity-related conclusions stem from data from just 5 mice, which is a relatively small sample set. Optogenetic groups are also on the small side.

      We appreciate this point and agree that higher N can be important for observing robust effects. A factor of our experiments that helped reduce the number of animals used was the longitudinal design, with repeated measures in the same subjects. This allowed for the internal control of comparing learning effects in the same subject from naïve to expert stages and therefore increased robustness. Even with relatively small group sizes, results were statistically significant, suggesting that the use of more mice was unnecessary, which we considered consistent with best practice in the use of animals in research. We also note that our group sizes were consistent with other studies in the field.  

      Reviewer #3 (Public Review):

      Yonk and colleagues investigate the role of the thalamostriatal pathway. Specifically, they studied the interaction of the posterior thalamic nucleus (PO) and the dorsolateral striatum in the mouse. First, they characterize connectivity by recording DLS neurons in in-vitro slices and optogenetically activating PO terminals. PO is observed to establish depressing synapses onto D1 and D2 spiny neurons as well as PV neurons. Second, the image PO axons are imaged by fiber photometry in mice trained to discriminate textures. Initially, no trial-locked activity is observed, but as the mice learn PO develops responses timed to the audio cue that marks the start of the trial and precedes touch. PO does appear to encode the tactile stimulus type or outcome. Optogenetic suppression of PO terminals in striatum slow task acquisition. The authors conclude that PO provides a "behaviorally relevant arousal-related signal" and that this signal "primes" striatal circuitry for sensory processing.

      A great strength of this paper is its timeliness. Thalamostriatal processing has received almost no attention in the past, and the field has become very interested in the possible functions of PO. Additionally, the experiments exploit multiple cutting-edge techniques.

      There seem to be some technical/analytical weaknesses. The in vitro experiments appear to have some contamination of nearby thalamic nuclei by the virus delivering the opsin, which could change the interpretation. Some of the statistical analyses of these data also appear inappropriate. The correlative analysis of Pom activity in vivo, licking, and pupil could be more convincingly done.

      The bigger weakness is conceptual - why should striatal circuitry need "priming" by the thalamus in order to process sensory stimuli? Why would such circuitry even be necessary? Why is a sensory signal from the cortex insufficient? Why should the animal more slowly learn the task? How does this fit with existing ideas of striatal plasticity? It is unclear from the experiments that the thalamostriatal pathway exists for priming sensory processing. In fact, the optogenetic suppression of the thalamostriatal pathway seems to speak against that idea.

      We thank the reviewer for these constructive comments. The points are addressed below.

      Recommendations for the authors:

      Reviewer #2 (Recommendations For The Authors):

      Do POm neurons innervate CINs also? The connection between the PF thalamus and CINs is mentioned in a couple of places - one question is how unique are the input patterns for the POm versus adjacent sensorimotor thalamic regions, including the PF? This isn't a weakness per se but knowing the answer to that question would help in forming a more complete picture of how these different thalamostriatal circuits do or do not contribute uniquely to learning and action selection.

      Anatomical tracing evidence from Klug et al. (2018), which mapped brain-wide inputs to striatal cholinergic (ChAT) interneurons, suggests that Pf provides the majority of thalamic innervation of striatal ChAT neurons compared to other thalamic nuclei. Many other thalamic nuclei, including POm, showed very little or no labeling, suggesting weak innervation of ChAT interneurons. However, it is possible that these thalamic nuclei, including POm, do provide functional innervation of ChAT interneurons that is not sufficiently assessed by anatomical tracing.

      Another difference between Pf and other thalamic nuclei (likely including POm) comes from anatomical tracing evidence (Smith et al., 2014; PMID: 24523677) which indicates that Pf inputs form the majority of their synapses onto dendritic shafts of SPNs, while other thalamic nuclei form synapses onto dendritic spines. Understanding the innervation patterns of POm-striatal projections beyond the three cell types we have studied here, including ChAT neurons and subcellular localization, would be an important area of further study.

      It would be useful to know to what extent these POm-striatum neurons are activated generally during movement, versus this discrimination task specifically.

      We agree that distinguishing general movement-related activity from task-specific activity would be very useful. Earlier work (Petty et al., 2021) showed a close relationship between POm neuron activity, spontaneous (task-free) whisker movements, and pupil-indexed arousal in head-restrained mice. Oram et al. (2024; PMID: 39003286) recently recorded VPM and POm in freely moving mice during natural movements, finding that activity of both nuclei correlated with head and whisker movements. These studies indicate that POm is generally coactive with exploratory head and whisker movements.

      During task performance, the situation may change with training and attentional effects. For example, Petty and Bruno (2024) (https://elifesciences.org/reviewed-preprints/97188) showed that POm activity correlates more closely with task demands than tactile or visual stimulus modality. Our data indicate that POm axonal signals are increased at trial start during anticipation of tactile stimulus delivery and through the sensory discrimination period, then decrease to baseline levels during licking and water reward collection (Fig. 3). Results of Petty and Bruno (2024) together with ours suggest that POm is particularly active during the context of behaviorally relevant task performance. Thus, we think it is likely that, while pupil dilation indexes general movement and arousal, POm activity is more specific to movement and arousal associated with task engagement and behavioral performance. We have strengthened this point in the Discussion.

      Many of the data panels and text for legends/axes are quite small, and the stroke on line art is quite faint - overall figures could be improved from a readability standpoint.

      We thank the reviewer for their careful attention to the figures. 

      Reviewer #3 (Recommendations For The Authors):

      Major

      (1) Page 4, the Results regarding PSP and distance from injection site. The r-squared is the wrong thing to look at to test for a relationship. One should look at the p-value on the coefficient corresponding to the slope. The p-value is probably significant given the figures, in which case there may be a relationship contrary to what is stated. All the low r-squared value says is that, if there is a relationship, it does not explain a lot of the PSP variability.

      We thank the reviewer for alerting us this oversight. We have included the p value (p = 0.0293) in the figure and legend, and indicated that the relationship is “small but significant”.

      (2) Figure 1B suggests that the virus injections extend beyond POm and into other thalamic structures. Do any of the results change if the injections contaminating other nuclei are excluded from the analysis? I am not suggesting the authors change the figures/analyses. I am simply suggesting they double-check.

      We selected for injections that were predominantly expressing in POm as determined by post-hoc histological analysis (see Fig. 1, right). As above, we think that axons of passage that do not form striatal synapses are less likely to be suppressed than axons with terminals; however, this would need to be determined in further experiments. Because the preponderance of expression is within POm, we think the results would be similar even with a stricter selection criterion. 

      (3) The authors conclude that POm and licking are not correlated (bottom of page 6 pertaining to Figures 3A-F). The danger of these analyses is that they assume that GCaMP8 is a perfect linear reporter of POm spikes. The reliability of GCaMP8 has been quantified in some cell types, but not thalamic neurons, which have relatively higher firing rates.

      The reviewer is correct that the relationship between GCaMP8 fluorescence changes and spiking has not been sufficiently characterized in thalamic neurons, and that this would be important to do.

      What if the indicator is simply saturated late into the trial (after the average reaction time)? It would look like there is no response and one would conclude no correlation, but there could be a very strong correlation.

      While saturation is worthy of concern, the signal dynamics here argue against this possibility. The reason is that the signal increased in the early part of the trial and decreased by the end. If saturation was an issue, this would have been apparent during the initial increase. When the signal decreased in amplitude at the end of the trial, this indicates that the signal is not saturated because it is returning from a point closer to its maximum (and is becoming less saturated).

      Also, what happens between trials? Are the correlations the same, stronger, weaker? Ideally, the authors would analyze the data during and between trials.

      Between trials the signal did not show further changes in baseline beyond what was displayed at the start and end of behavioral trials. There were no consistent increases or decreases in signals between trials, except perhaps during strong whisking bouts. This is anecdotal because we did not analyze between-trial data. However, it is interesting and important to note that signals increased dramatically in amplitude from naïve, early learning to expert behavioral performance (Fig. 3), highlighting that POm-axonal signals relate to behavioral engagement and performance rather than spontaneous behaviors.  

      (4) Axonal activity could also appear more correlated with the pupil than licking because pupil dynamics are slow like the dynamics of calcium indicators. These kernels could artificially inflate the correlation. Ideally, the authors could consider these temporal effects. Perhaps they could deconvolve the temporal profiles of calcium and pupil before correlating? Or equivalently incorporate the profiles into their analysis?

      We analyzed the lick probability histograms, which had a temporal profile similar to the calcium signals (Fig. 3D,E), ruling out concerns about effects of temporal effects on correlations. It is also worth noting that we observed changes in correlations between calcium signals and pupil with learning stage (Fig. 3I), even though the temporal profiles (signal dynamics) are not changing. Thus, temporal effects of the signals themselves are not the driver of correlations, but rather the changes in relative timing between calcium signals and pupil, as occur with learning.

      (5) The authors conclude that PO provides a "behaviorally relevant arousal-related signal" and that this signal "primes" striatal circuitry for sensory processing. The data here support the first part. It is not clear that the data support the second part, largely because it is vague what "priming" of sensory processing or "a key role in the initial stages of action selection (p.9) even means here. Why would such circuitry even be necessary? Why is a sensory signal from the cortex insufficient? Why should the animal more slowly learn the task? How does this fit with existing ideas of striatal plasticity? Some conceptual proposals from the authors, even if speculative and not offered as a conclusion, would be helpful.

      We appreciate these good points and have added further consideration and revision of the concept of priming and potential roles in an extensively revised Discussion section.

      (6) The photometry shows that PO turns on about 2 seconds before the texture presentation. PO's activity seems locked to the auditory cue, not the texture (Figure 2). This means that the attempt to suppress the thalamostriatal pathway with JAWS (Figure 4) is rather late, isn't it? Some PO signals surely go through. This seems to contradict the idea of priming above. It would be good if the authors could factor this into their narrative. Perhaps labelling the time of the auditory cue in Figure 4C would also be helpful.

      The start of texture presentation (movement of the texture panel toward the mouse) and auditory cue occur at the same time. To clarify this, we added a label “start tone” in Figure 4C and also in Figure 2C.

      For optogenetic (JAWS) suppression, we intentionally chose a time window between start tone onset and texture presentation, because our photometry experiments showed that this was when the preponderance of the signal occurred. However, the reviewer is correct that our chosen optogenetic suppression (JAWS) onset occurs shortly after the photometry signal has already started, potentially leaving the early photometry signal un-suppressed. Our motivation for choosing a restricted time window surrounding the texture presentation time was 1) to minimize illumination and potential heating of brain tissue; 2) to target a time window that avoids the auditory cue but covers stimulus presentation. We did not want to extend the duration of the suppression to before the trial started, because this could produce task-non-specific effects, such as distraction or loss of attention before the start of the trial.

      Even if some signal were getting through before suppression, we don’t think this contradicts the possibility of ‘priming’, because the process underlying priming would still be disrupted even if not totally suppressed. This would alter the temporal relationship between POm-striatal inputs and further corticostriatal inputs (from S1 and M1 cortex, for example). We have included further consideration of these points and possible relation to the priming concept in the Discussion.

      Minor

      (1) Page 5, "the sensitivity metric is artificially increased". What do you mean "artificially"? The mice are discriminating better. It is true that either a change in HR or FAR can cause the sensitivity metric to change, but there is nothing artificial or misleading about this.

      We removed the word artificial and clarified our definition of behaviorally Expert in this context:

      “Mice were considered Expert once they had reached ≥ 0.80 Hit Rate and ≤ 0.30 FA Rate for two consecutive sessions in lieu of a strict sensitivity (d’) threshold; we found this definition more intuitive because d’ is enhanced as Hit Rate and FA Rate approach their extremes (0 or 1)”

      (2) Page 7, "Upon segmentation (Figure S4G-J)". Do you mean "segregation by trial outcome"?

      Corrected.

      (3) Page 9, "POm projections may have discrete target-specific functions, such that POm-striatal inputs may play a distinct role in sensorimotor behavior compared to POm-cortical inputs". Would POm-cortical inputs not also be sensorimotor? The somatosensory cortex contains a lot of corticostriatal cells. It also has various direct and indirect links to the motor cortex as well.

      We have clarified the wording here to convey the possibility that POm signals could be received and processed differently by striatal versus cortical circuitry, and have moved this statement to later in the discussion for better elaboration.

      (4) The Methods state that male and female mice were used. Why not say how many of each and whether or not there are any sex-specific differences?

      We added the following information to the Methods:

      The number of male and female mice were as follows, by experiment type: 6 male, 4 female (electrophysiology); 3 male, 2 female (fiber photometry); 4 male, 5 female (optogenetics). Data were not analyzed for sex differences.

    1. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      In this series of studies, Locantore et al. investigated the role of SST-expressing neurons in the entopeduncular nucleus (EPNSst+) in probabilistic switching tasks, a paradigm that requires continued learning to guide future actions. In prior work, this group had demonstrated EPNSst+ neurons co-release both glutamate and GABA and project to the lateral habenula (LHb), and LHb activity is also necessary for outcome evaluation necessary for performance in probabilistic decision-making tasks. Previous slice physiology works have shown that the balance of glutamate/GABA co-release is plastic, altering the net effect of EPN on downstream brain areas and neural circuit function. The authors used a combination of in vivo calcium monitoring with fiber photometry and computational modeling to demonstrate that EPNSst+ neural activity represents movement, choice direction, and reward outcomes in their behavioral task. However, viral-genetic manipulations to synaptically silence these neurons or selectively eliminate glutamate release had no effect on behavioral performance in well-trained animals. The authors conclude that despite their representation of task variables, EPN Sst+ neuron synaptic output is dispensable for task performance.

      Strengths and Weaknesses:

      Overall, the manuscript is exceptionally scholarly, with a clear articulation of the scientific question and a discussion of the findings and their limitations. The analyses and interpretations are careful and rigorous. This review appreciates the thorough explanation of the behavioral modeling and GLM for deconvolving the photometry signal around behavioral events, and the transparency and thoroughness of the analyses in the supplemental figures. This extra care has the result of increasing the accessibility for non-experts, and bolsters confidence in the results.

      (1) To bolster a reader's understanding of results, we suggest it would be interesting to see the same mouse represented across panels (i.e. Figures 1 F-J, Supplementary Figures 1 F, K, etc i.e via the inclusion of faint hash lines connecting individual data points across variables.

      Thank you for the suggestion. The same mouse is now represented in Fig 1 and Fig 1—Figure Supplement 1 as a darkened circle so it can be followed across different panels. Photometry from this mouse was used as sample date in Figure 2b and Figure 2—figure supplement 1a-b.

      (2) Additionally, Figure 3E demonstrates that eliminating the 'reward' and 'choice and reward' terms from the GLM significantly worsens model performance; to demonstrate the magnitude of this effect, it would be interesting to include a reconstruction of the photometry signal after holding out of both or one of these terms, alongside the 'original' and 'reconstructed' photometry traces in panel D. This would help give context for how the model performance degrades by exclusion of those key terms.

      We have now added analyses and reconstructed photometry signals from GLMs excluding important predictors in Figure 3—figure supplement 1 and 2. We use the model where both “Direction and reward” were omitted as predictors for the GLM and showed photometry reconstructions aligned to behavioral events used for the full model (Figure 3—figure supplement 1) and partial model (Figure 3—figure supplement 2) to compare model performance.  

      (3) Finally, the authors claimed calcium activity increased following ipsilateral movements. However, Figure 3C clearly shows that both SXcontra and SXipsi increase beta coefficients. Instead, the choice direction may be represented in these neurons, given that beta coefficients increase following CXipsi and before SEipsi, presumably when animals make executive decisions. Could the authors clarify their interpretation on this point?

      We observe that calcium activity increases during ipsilateral choices as the animal moves toward the ipsilateral side port (e.g. CX<sub>ipsi</sub> to SE<sub>ipsi</sub>; Fig 2C and Fig 3C). The animal also makes other ipsiversive movements not during the “choice” phase of a trial such as when it is returning to the center port following a contralateral choice (e.g. SX<sub>Contra</sub> to CE; Fig 2—figure supplement 1F and Fig 3C). We also observe an increase in calcium activity during these ipsiversive movements (e.g. SX<sub>Contra</sub> to CE), but they are not as large as those observed during the choice phase (Fig 2—figure supplement 1G). Therefore, during the choice phase of a trial, activity contains signals related to ipsilateral movement and additional factors (e.g. executive decision making).    

      (4) Also, it is not clear if there is a photometry response related to motor parameters (i.e. head direction or locomotion, licking), which could change the interpretation of the reward outcome if it is related to a motor response; could the authors show photometry signal from representative 'high licking' or 'low licking' reward trials, or from spontaneous periods of high vs. low locomotor speeds (if the sessions are recorded) to otherwise clarify this point?

      Unfortunately, neither licks nor locomotion were recorded during the behavioral sessions when photometry was recorded. In Figure 2—figure supplement 1a we now show individual trials sorted by trial duration (time elapsed between CE and SE) to illustrate the dynamics of the photometry signal on fast vs slow trials within a session.  

      (5) There are a few limitations with the design and timing of the synaptic manipulations that would improve the manuscript if discussed or clarified. The authors take care to validate the intersectional genetic strategies: Tetanus Toxin virus (which eliminates synaptic vesicle fusion) or CRISPR editing of Slc17a6, which prevents glutamate loading into synaptic vesicles. The magnitude of effect in the slice physiology results is striking. However, this relies on the co-infection of a second AAV to express channelrhodopsin for the purposes of validation, and it is surely the case that there will not be 100% overlap between the proportion of cells infected.

      For the Tet-tox experiments in Figure 4 we estimate approximately 70±15% of EP<sup>Sst+</sup> neurons expressed Tet-tox based on our histological counts and published stereological counts in EP (Miyamoto and Fukuda, 2015). It is true that channelrhodopsin expression will not overlap 100% with cells infected by the other virus, indeed our in vitro synaptic physiology shows small residual postsynaptic currents following optogenetic stimulation either from incomplete blockade of synaptic release or neurons that expressed channelrhodopsin but not Tettx (Figure 4—figure supplement 1J-K). The same is shown for CRISPR mediated deletion of Slc17a6 (Fig 5 – Fig supplement 1J-K).  

      (6) Alternative means of glutamate packaging (other VGluT isoforms, other transporters, etc) could also compensate for the partial absence of VGluT2, which should be discussed.

      While single cell sequencing (Wallace et al, 2017) has shown EP<sup>Sst+</sup> neurons do not express Slc17a7/8 (vGlut1 or vGlut3) it is possible that these genes could be upregulated following CRISPR mediated deletion of Slc17a6, however we do not see evidence of this with our in vitro synaptic physiology (EPSCs are significant suppressed, Figure 5 – Fig supplement 1J-K) and therefore can conclude it is highly unlikely to occur to a significant degree in our experiments. This is now included in the Discussion.

      (7) The authors do not perform a complimentary experiment to delete GABA release (i.e. via VGAT editing), which is understandable, given the absence of an effect with the pan-synaptic manipulation. A more significant concern is the timing of these manipulations as the authors acknowledge. The manipulations are all done in well-trained animals, who continue to perform during the length of viral expression. Moreover, after carefully showing that mice use different strategies on the 70/30 version vs the 90/10 version of the task, only performance on the 90/10 version is assessed after the manipulation. Together, the observation that EPNsst activity does not alter performance on a well-learned, 90/10 switching task decreases the impact of the findings, as this population may play a larger role during task acquisition or under more dynamic task conditions. Additional experiments could be done to strengthen the current evidence, although the limitation is transparently discussed by the authors.

      As mentioned above, it is possible that a requirement for EP<sup>Sst+</sup> neurons could be revealed if the experiment was conducted with different parameters (either different reward probabilities, fluctuating reward probabilities within a session, or withholding additional training during viral expression). It is difficult to predict which version of the task, if any, would be most likely to reveal a requirement for EP<sup>Sst+</sup> neurons based on our results. We favor testing for EP<sup>Sst+</sup> function using a new behavioral paradigm that allows us to carefully examine task learning following EP manipulations in an independent study.

      (8) Finally, intersectional strategies target LHb-projecting neurons, although in the original characterization, it is not entirely clear that the LHb is the only projection target of EPNsst neurons. A projection map would help clarify this point.

      In a previous study we confirmed that EP<sup>Sst+</sup> neurons project exclusively to the LHb using cell-type specific rabies infection and examining all reported downstream regions for axon collaterals (Wallace et al 2017, Suppl. Fig 6F-G). When EP<sup>Sst+</sup> neurons were labeled we did not observe axon collaterals in known targets of EP such as ventro-antero lateral thalamus, red nucleus, parafasicular nucleus of the thalamus, or the pedunculopontine tegmental nucleus, only in the LHb. Additionally, using single cell tracing techniques, others have shown EP neurons that exclusively project to the LHb (Parent et al, 2001).

      Overall, the authors used a pertinent experimental paradigm and common cell-specific approaches to address a major gap in the field, which is the functional role of glutamate/GABA co-release from the major basal ganglia output nucleus in action selection and evaluation. The study is carefully conducted, their analyses are thorough, and the data are often convincing and thought-provoking. However, the limitations of their synaptic manipulations with respect to the behavioral assays reduce generalizability and to some extent the impact of their findings.

      Reviewer #2 (Public Review):

      Summary:

      This paper aimed to determine the role EP sst+ neurons play in a probabilistic switching task.

      Strengths:

      The in vivo recording of the EP sst+ neuron activity in the task is one of the strongest parts of this paper. Previous work had recorded from the EP-LHb population in rodents and primates in head-fixed configurations, the recordings of this population in a freely moving context is a valuable addition to these studies and has highlighted more clearly that these neurons respond both at the time of choice and outcome.

      The use of a refined intersectional technique to record specifically the EP sst+ neurons is also an important strength of the paper. This is because previous work has shown that there are two genetically different types of glutamatergic EP neurons that project to the LHb. Previous work had not distinguished between these types in their recordings so the current results showing that the bidirectional value signaling is present in the EP sst+ population is valuable.

      Weaknesses:

      (1) One of the main weaknesses of the paper is to do with how the effect of the EP sst+ neurons on the behavior was assessed.

      (a) All the manipulations (blocking synaptic release and blocking glutamatergic transmission) are chronic and more importantly the mice are given weeks of training after the manipulation before the behavioral effect is assessed. This means that as the authors point out in their discussion the mice will have time to adjust to the behavioral manipulation and compensate for the manipulations. The results do show that mice can adapt to these chronic manipulations and that the EP sst+ are not required to perform the task. What is unclear is whether the mice have compensated for the loss of EP sst+ neurons and whether they play a role in the task under normal conditions. Acute manipulations or chronic manipulations without additional training would be needed to assess this.

      Unfortunately, when mice are given a three week break from behavioral training (the time required to allow for adequate viral expression) behavioral performance on the task (p(highport), p(switch), trial number, trial time, etc.) is significantly degraded. Animals do eventually recover to previous performance levels, but this takes place during a 4-5 day “relearning” period. Here we sought to examine if EP<sup>Sst+</sup> neurons are required for continued task performance and chose to continue to train the animals following viral injection to avoid the “relearning” period that occurs following an extended break from behavioral training which may have made it difficult to interpret changes in behavioral performance due to the viral manipulation vs relearning.  

      Acute manipulations were not used because we planned to compare complete synaptic ablation (Tettx) and single neurotransmitter ablation (CRISPR Slc17a6) over similar time courses and we know of no acute manipulation that could achieve single neurotransmitter ablation. 

      (b) Another weakness is that the effect of the manipulations was assessed in the 90/10 contingency version of the task. Under these contingencies, mice integrate past outcomes over fewer trials to determine their choice and animals act closer to a simple win-stay-lose switch strategy. Due to this, it is unclear if the EP sst+ neurons would play a role in the task when they must integrate over a larger number of conditions in the less deterministic 70/30 version of the task.

      It is possible that a requirement for EP<sup>Sst+</sup> neurons could be revealed if the experiment was conducted with different parameters (either different reward probabilities, fluctuating reward probabilities within a session, or withholding additional training during viral expression). It is difficult to predict which version of the task, if any, would be most likely to reveal a requirement for EP<sup>Sst+</sup> neurons based on our results. We favor testing for EP<sup>Sst+</sup> function using a new behavioral paradigm that allows us to carefully examine task learning following EP manipulations in an independent study.

      The authors show an intriguing result that the EP sst+ neurons are excited when mice make an ipsilateral movement in the task either toward or away from the center port. This is referred to as a choice response, but it could be a movement response or related to the predicted value of a specific action. Recordings while mice perform movement outside the task or well-controlled value manipulations within the session would be needed to really refine what these responses are related to.

      If activity of EP<sup>Sst+</sup> neurons included a predicted value component, we would expect to see a change in activity during ipsilateral movements when the previous trial was rewarded vs unrewarded. This is examined in Fig 2—figure suppl. 2C, where we compare EP<sup>Sst+</sup> responses during ipsilateral trials when the previous trials were either rewarded (blue) or unrewarded (gray). We show that EP<sup>Sst+</sup> activity prior to side port entry (SE) is identical in these two trial types indicating that EP<sup>Sst+</sup> neurons do not show evidence of predicted value of an action in this context. Therefore, we conclude that increased EP<sup>Sst+</sup> activity during ipsilateral trials is primarily related to ipsilateral movement following CX (we call this the “choice” phase of the trial). We also show that other ipsiversive movements outside of the “choice” phase of a trial (such as the return to center port following a contralateral trial) show a smaller but significant increase in activity (Figure 2—figure supplement 1F-G). Therefore, whereas the activity observed during ipsilateral choice contains signals related to ipsilateral movement and additional factors, our data suggest that predicted value is not one of those factors. We will clarify this point and our definition of “choice” in the narrative.  

      (2) The authors conclude that they do not see any evidence for bidirectional prediction errors. It is not possible to conclude this. First, they see a large response in the EP sst+ neurons to the omission of an expected reward. This is what would be expected of a negative reward prediction error. There are much more specific well-controlled tests for this that are commonplace in head-fixed and freely moving paradigms that could be tested to probe this. The authors do look at the effect of previous trials on the response and do not see strong consistent results, but this is not a strong formal test of what would be expected of a prediction error, either a positive or negative. The other way they assess this is by looking at the size of the responses in different recording sessions with different reward contingencies. They claim that the size of the reward expectation and prediction error should scale with the different reward probabilities. If all the reward probabilities were present in the same session this should be true as lots of others have shown for RPE. Because however this data was taken from different sessions it is not expected that the responses should scale, this is because reward prediction errors have been shown to adaptively scale to cover the range of values on offer (Tobler et al., Science 2005). A better test of positive prediction error would be to give a larger-than-expected reward on a subset of trials. Either way, there is already evidence that responses reflect a negative prediction error in their data and more specific tests would be needed to formally rule in or out prediction error coding especially as previous recordings have shown it is present in previous primate and rodent recordings.

      We do not conclude that we see no evidence for RPE and the reviewer is correct in stating that a large increase in EP<sup>Sst+</sup> activity following omission of an expected reward would be expected of a negative reward prediction error. However, this observation alone is not strong enough evidence that EP<sup>Sst+</sup> neurons signal RPE. When we looked for additional evidence of RPE within our experiments we did not find consistent demonstrations of its existence in our data. When performing photometry measurements of dopamine release in the striatum, RPE signals are readily observed with a task identical to ours using trial history to as a modifier of reward prediction (Chantranupong, et al 2023). Of course, there could be a weaker more heterogeneous RPE signal in EP<sup>Sst+</sup> neurons that we cannot detect with our methods. As we state in the discussion, RPE signals may be present in a subset of individual neurons (as observed in Stephenson-Jones et al, 2016 and Hong and Hikosaka, 2008) which are below our detection threshold using fiber photometry. Additionally, Hong and Hikosaka, 2008 show that LHb-projecting GPi neurons show both positive and negative reward modulations which may obscure observation of RPE signals with photometry recordings that arise from population activity of genetically defined neurons.   

      (3) There are a lot of variables in the GLM that occur extremely close in time such as the entry and exit of a port. If two variables occur closely in time and are always correlated it will be difficult if not impossible for a regression model to assign weights accurately to each event. This is not a large issue, but it is misleading to have regression kernels for port entry and exits unless the authors can show these are separable due to behavioral jitter or a lack of correlation under specific conditions, which does not seem to be the case.

      It is true that two variables that are always correlated are redundant in a GLM. For example, center entry (CE) and center exit (CX) occur in quick succession in most trials and are highly correlated (Figure 1C). For this reason, when only one is removed as a predictor from the model but not the other there is a very small change in the MSE of the fit (Figure 3E, -CE or -CX). However, when both are removed model performance decreases further indicating that center-port nose-pokes do contribute to model performance (Figure 3E, -CE/CX). Due to the presence/absence of reward following side port entry there is substantial behavioral jitter (due to water consumption in rewarded trials) that the SE and SX are not always correlated, therefore the model performs worse when either are omitted alone, but even worse still when both SE/SX are omitted together (Figure 3E, -SE/SX). We will update Figure 3 and the narrative to make this more explicit.

      Reviewer #3 (Public Review):

      Summary:

      The authors find that Sst-EPN neurons, which project to the lateral habenula, encode information about response directionality (left vs right) and outcome (rewarded vs unrewarded). Surprisingly, impairment of vesicular signaling in these neurons onto their LHb targets did not impair probabilistic choice behavior.

      Strengths:

      Strengths of the current work include extremely detailed and thorough analysis of data at all levels, not only of the physiological data but also an uncommonly thorough analysis of behavioral response patterns.

      Weaknesses:

      Overall, I saw very few weaknesses, with only two issues, both of which should be possible to address without new experiments:

      (1) The authors note that the neural response difference between rewarded and unrewarded trials is not an RPE, as it is not affected by reward probability. However, the authors also show the neural difference is partly driven by the rapid motoric withdrawal from the port. Since there is also a response component that remains different apart from this motoric difference (Figure 2, Supplementary Figure 1E), it seems this is what needs to be analyzed with respect to reward probability, to truly determine whether there is no RPE component. Was this done?

      We thank the reviewer for this comment, we believe this is particularly important for unrewarded trials as SE and SX occur in rapid succession. In Figure 2—figure supplement 2A-B we now show the photometry signal from Rewarded and Unrewarded ipsilateral trials aligned to SX for different reward probabilities. We quantify the signals for different reward probabilities during a 500ms window immediately prior to SX but find no differences between groups.  

      (2) The current study reaches very different conclusions than a 2016 study by Stephenson-Jones and colleagues despite using a similar behavioral task to study the same Sst-EPN-LHb circuit. This is potentially very interesting, and the new findings likely shed important light on how this circuit really works. Hence, I would have liked to hear more of the authors' thoughts about possible explanations of the differences. I acknowledge that a full answer might not be possible, but in-depth elaboration would help the reader put the current findings in the context of the earlier work, and give a better sense of what work still needs to be done in the future to fully understand this circuit.

      For example, the authors suggest that the Sst-EPN-LHb circuit might be involved in initial learning, but play less of a role in well-trained animals, thereby explaining the lack of observed behavioral effect. However, it is my understanding that the probabilistic switching task forces animals to continually update learned contingencies, rendering this explanation somewhat less persuasive, at least not without further elaboration (e.g. maybe the authors think it plays a role before the animals learn to switch?).

      Also, as I understand it, the 2016 study used manipulations that likely impaired phasic activity patterns, e.g. precisely timed optogenetic activation/inhibition, and/or deletion of GABA/glutamate receptors. In contrast, the current study's manipulations - blockade of vesicle release using tetanus toxin or deletion of VGlut2, would likely have blocked both phasic and tonic activity patterns. Do the authors think this factor, or any others they are aware of, could be relevant?

      We have added further discussion of the Stephenson-Jones, et al 2016 study as well as the Lazaridis, et al 2019 study which shows no effect of phasic stimulation of EP when specifically manipulating EP<sup>Sst+</sup> (vGat+/vGlut2+) neurons rather than vGlut2+ neurons as in the Stephenson-Jones study.  

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      In some places, there seems to be a mismatch between referenced figures and texts. For example:

      (1) The authors described that 'This increase in activity was seen for all three reward probabilities tested (90/10, 80/20, and 70/30) and occurred while the animal was engaged in ipsiversive movements as similar increases were observed following side exit (SX) on contralateral trials as the animal was moving from the contralateral side port back to the center port (Figure 2-Figure Supplement 1c)', but supplement 1c is not about calcium dynamics around the SX event. I presume they mean Figure 2-Figure Supplement 1d.

      Yes, this will be corrected in the revised manuscript.

      (2) The authors explained that increased EPSst+ neuronal activity following an unrewarded outcome was partially due to the rapid withdrawal of the animal's snout following an unrewarded outcome however, differences in rewarded and unrewarded trials were still distinguishable when signals were aligned to side port exit indicating that these increases in EPSst+ neuronal activity on unrewarded trials were a combination of outcome evaluation (unrewarded) and side port withdrawal occurring in quick succession (SX, Figure 2 - Figure Supplement 1d). I presume that they mean Figure 2 - Figure Supplement 1e.

      Yes, this will be corrected in the revised manuscript.

      Minor suggestions related to specific figure presentation are below:

      Figure 2 and supplement figures:

      (1) Figure 2B: the authors may consider presenting outcome-related signals recorded from all trials, including both ipsilateral and contralateral events, and align signals to SE when reward consumption presumably begins, rather than aligning to CE.

      We have added sample recordings from ipsilateral and contralateral trials and sorted them by trial duration to allow for clearer presentation of activity following CE and SE (Figure 2—figure supplement 1a-b).

      (2) The authors described that 'This increase in activity was seen for all three reward probabilities tested (90/10, 80/20, and 70/30) and occurred while the animal was engaged in ipsiversive movements as similar increases were observed following side exit (SX) on contralateral trials as the animal was moving from the contralateral side port back to the center port (Figure 2-Figure Supplement 1c)', but supplement 1c is not about calcium dynamics around the SX event. I presume they mean Figure 2-Figure Supplement 1d.

      Yes, this will be corrected in the revised manuscript.

      (3) The authors explained that increased EPSst+ neuronal activity following an unrewarded outcome was partially due to the rapid withdrawal of the animal's snout following an unrewarded outcome however, differences in rewarded and unrewarded trials were still distinguishable when signals were aligned to side port exit indicating that these increases in EPSst+ neuronal activity on unrewarded trials were a combination of outcome evaluation (unrewarded) and side port withdrawal occurring in quick succession (SX, Figure 2 -Figure Supplement 1d). I presume that they mean Figure 2 -Figure Supplement 1e.

      Yes, this will be corrected in the revised manuscript.

      Figure 3 and supplement figures:

      (1) Figure 3C-F: it is hard to compare the amplitude of calcium signals between different behaviour events without a uniform y-axis.

      The scale for the y-axis on Figure 3C-D is uniform for all panels. Figure 3E is also uniform for all boxplots. The reviewer may be referring to Figure 2C-F, but the y-axis for all of the photometry data is uniform for all panels and the horizontal line represents zero. The y-axis for the quantification on the right of each panel is scaled to the max/min for each comparison.

      (2) Figure 3E is difficult to follow. The authors explained that the 'SE' variable is generated by collapsing the ipsilateral and contralateral port entries, and hence the variable has no choice of direction information. I assumed that the 'SX', 'CE', and 'CX' variables are generated similarly. It is not clear if this is the case for the 'side', 'centre' and 'choice' variables. The authors explained that 'omitting center port entry/exit together or individually also resulted in decreased GLM performance but to a smaller degree than the omission of choice direction (Figure 3e, "-Center")'. My understanding is that they created the Centre variable by collapsing ipsilateral and contralateral centre port entry/exit together. The Centre variable should have no choice of direction information. How is the Center variable generated differently from omitting centre port entry/exit together? I would ask the authors to explain the model and different variables a bit more thoroughly in the text.

      We apologize for the confusion. All ten variables used to train the full GLM are listed in Fig. 3C. In Figure 3E variable(s) were omitted to test how they contributed to GLM performance (data labeled “None” is the full model with all variables). Omitted variables are now defined as follows: -Rew = Rew+Unrew removed, -Direction = Ipsi/Contra designation removed and collapsed into CE, CX, SE, SX, -Direction & Rew = Ipsi/Contra info removed from all variables + Rew/Unrew removed, -CE/CX = Ipsi/Contra CE and CX removed, -CE = Ipsi/contra CE removed, -CX = Ipsi/contra CX removed, -SE/SX = Ipsi/Contra SE and SX removed, -SE = Ipsi/contra SE removed, -SX = Ipsi/contra SX removed. This clarification has also been added to the Generalized Linear Model section of Materials and Methods.

      Figure 5 and supplement figures:

      There are no representative and summary figures show the specificity and efficiency of oChief-tdTomato or Tetx-GFP expression. Body weight changes following virus injection are not well described.

      A representative image of Tettx GFP expression are shown in Fig. 4A and percent of infected EP<sup>Sst+</sup> neurons is described in the text (70±15.1% (mean±SD), 1070±230 neurons/animal, n=6 mice). Most oChief-tdTom animals were used for post-hoc electrophysiology experiments and careful quantification of viral expression was not possible. However, Slc17a6 deletion was confirmed in these animals (Fig. 5 – Fig supplement 1J-K) to confirm the manipulation was effective in the experimental group. A representative image of oChief-tdTom expression is shown in Fig. 5A.

      We now mention the body weight changes observed following Tettx injection in the narrative.

      Reviewer #2 (Recommendations For The Authors):

      (1) In the RFLR section you state that "this variable decays...", a variable can't decay only the value of a variable can change. Also, it is not mentioned what variable is being discussed. There are lots of variables in the model so this should be made clear.

      We now state, “This variable (β) changes over trials and is updated with new evidence from each new trial’s choice and outcome with an additional bias towards or away from its most recent choice (Figure 1-figure supplement 2A-C).”

      (2) I couldn't find in the results section, or the methods section the details for the Tet tx experiments, were mice trained and tested on 90/10 only? Were they trained while the virus was expressing etc? This should be added.

      In the methods section we state, ”For experiments where we manipulated synaptic release in EP<sup>Sst+</sup> neurons (Figures 4-5) we trained mice (reward probabilities 90/10, no transparent barrier present) to the following criteria for the 5 days prior to virus injection: 1) p(highport) per session was greater than or equal to 0.80 with a variance less than 0.003, 2) p(switch) per session was less than or equal to 0.15 with a variance less than 0.001, 3) the p(left port) was between 0.45-0.55 with a variance less than 0.005, and 4) the animal performed at least 200 trials in a session. The mean and variance for these measurements was calculated across the five session immediately preceding surgery. The criterion were determined by comparing performance profiles in separate animals and chosen based on when animals first showed stable and plateaued behavioral performance. Following surgery, mice were allowed to recover for 3 days and then continued to train for 3 weeks during viral expression. Data collected during the 5 day pre-surgery period was then compared to data collected for 10 sessions following the 3 weeks allotted for viral expression (i.e. days 22-31 post-surgery).”

      Reviewer #3 (Recommendations For The Authors):

      (1) The kernel in Figure 3C shows an activation prior to CE on "contra" trials that is not apparent in Figure 2C which shows no activation prior to CE on either contra or ipsi trials. Given that movement directionality prior to CE is dictated by the choice on the PREVIOUS trial, is the "contra" condition in 3C actually based on the previous trial? If so, this should be clarified.

      On most “contra” trials the animal is making an ipsiversive movement just prior to CE as it returns to the center from the contralateral side-port (as most trials are no “switch” trials). Therefore, an increase in activity is expected and shown most clearly following SX for contralateral trials in Fig 2 –Fig suppl 1F. A significant increase in activity prior to CE on contra trials compared to ipsi trials can also be seen in Fig 2C, its just not as large a change as the increase observed following CE for ipsi. trials. The comparison between activity observed during the two types of ipsiversive movements is now shown directly in Figure 2—figure supplement 1G.

      (2) Paragraph 7 of the discussion uses a phrase "by-in-large", which probably should be "by and large".

      Thank you for the correction.

      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 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.

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

      Sex breakdown has been added to figure legends for each experiment, full statistical reporting is now also include in the figure legends.

    1. Reviewer #3 (Public review):

      Summary:

      Bell and colleagues studied how different splice isoforms of voltage-gated CaV2 calcium channels affect channel expression, localization, function, synaptic transmission, and locomotor behavior at the larval Drosophila neuromuscular junction. They reveal that one mutually exclusive exon located in the fourth transmembrane domain encoding the voltage sensor is essential for calcium channel expression, function, active zone localization, and synaptic transmission. Furthermore, a second mutually exclusive exon residing in an intracellular loop containing the binding sites for Caβ and G-protein βγ subunits promotes the expression and synaptic localization of around ~50% of CaV2 channels, thereby contributing to ~50% of synaptic transmission. This isoform enhances release probability, as evident from increased short-term depression, is vital for homeostatic potentiation of neurotransmitter release induced by glutamate receptor impairment, and promotes locomotion. The roles of the two other tested isoforms remain less clear.

      Strengths:

      The study is based on solid data that was obtained with a diverse set of approaches. Moreover, it generated valuable transgenic flies that will facilitate future research on the role of calcium channel splice isoforms in neural function.

      Weaknesses:

      Comments on revisions:

      The authors addressed most points. However, from my point of view, the new data (somatodendritic cac currents in adult motoneurons of IS4B mutants without the pre-pulse, and localization of IS4A channels in the larval brain) do not strongly support that the IS4B exon is required for cacophony localization. According to their definition of localization, IS4B is required for cacophony channels to enter motoneuron boutons and to localize to active zones. In case of a true localization defect (without degradation, as they claim), IS4A channels should mislocalize to the soma, axon, or dendrite. However, they do not find them in motoneurons of IS4B mutants. Furthermore, I find the interpretation of the voltage clamp data in flight motoneurons rather difficult. On the one hand, sustained HVA cac currents are strongly attenuated/absent in IS4B mutants. On the other hand, total cac currents (without the -50 mV pre-pulse, not shown in the original submission) are less affected in IS4B mutants. Based on these data, they conclude that IS4B is required for sustained HVA cac currents and that IS4A channel isoforms are expressed and functional. How does this relate to a localization defect at the NMJ? Finally, detecting IS4A channels in other cell types and regions is not a strong argument for a localization defect at the NMJ. I, therefore, suggest toning down the conclusions regarding a localization defect in IS4B mutants/a role for the IS4B exon in cac localization. It should be also discussed how a splice isoform in S4 may result in no detectable cac channels at the NMJ or regulate subcellular channel localization.

      I have a few additional points, mainly related to the responses to my previous points:

      (1) The authors state "active zones at the NMJ contain only cac isoforms with the IS4B exon. Nevertheless, the small representative EPSC remaining in IS4B mutants suggests that there is synchronous release in the absence of IS4B (Fig. 3B). Are the small EPSCs in dIS4B (Fig. 3B) indeed different from noise/indicative of evoked release? If yes, which cac channels may drive these EPSCs? IS4A channels?<br /> (2) (Related to previous point 4) The authors argue that EPSC amplitudes are not statistically different between Canton S and IS4A mutants (Fig. 2F). However, the Canton S group appears undersampled, thus precluding conclusions based on statistics. Moreover, the effect size Canton S vs. dIS4A looks similar to the one of Canton S vs. dIS4A/dIS4B.<br /> (3) (Related to previous point 11): Can they cite a paper relating calcium channel inactivation to EPSC half width/decay kinetics to support their speculation that "decreased EPSC half width could be caused by significantly faster channel inactivation kinetics" (p. 42, l.42). In addition, many papers have demonstrated that mini decay kinetics provide valuable insights into GluR subunit composition at the Drosophila NMJ (e.g., Schmid et al., 2008 https://doi.org/10.1038/nn.2122). Thus, the statement "Mini decay kinetic analysis because this depends strongly on the distance of the recording electrode to the actual site of transmission in these large muscle cells" is not valid and should be revised.

    2. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      The manuscript by Bell et. al. describes an analysis of the effects of removing one of two mutually exclusive splice exons at two distinct sites in the Drosophila CaV2 calcium channel Cacophony (Cac). The authors perform imaging and electrophysiology, along with some behavioral analysis of larval locomotion, to determine whether these alternatively spliced variants have the potential to diversify Cac function in presynaptic output at larval neuromuscular junctions. The author provided valuable insights into how alternative splicing at two sites in the calcium channel alters its function.

      Strengths:

      The authors find that both of the second alternatively spliced exons (I-IIA and I-IIB) that are found in the intracellular loop between the 1st and second set of transmembrane domains can support Cac function. However, loss of the I-IIB isoform (predicted to alter potential beta subunit interactions) results in 50% fewer channels at active zones and a decrease in neurotransmitter release and the ability to support presynaptic homeostatic potentiation. Overall, the study provides new insights into Cac diversity at two alternatively spliced sites within the protein, adding to our understanding of how regulation of presynaptic calcium channel function can be regulated by splicing.

      Weaknesses:

      The authors find that one splice isoform (IS4B) in the first S4 voltage sensor is essential for the protein's function in promoting neurotransmitter release, while the other isoform (IS4A) is dispensable. The authors conclude that IS4B is required to localize Cac channels to active zones. However, I find it more likely that IS4B is required for channel stability and leads to the protein being degraded, rather than any effect on active zone localization. More analysis would be required to establish that as the mechanism for the unique requirement for IS4B.

      (1) We thank the reviewer for this important point. In fact, all three reviewers raised the same question, and the reviewing editor pointed out that caution or additional experiments were required to distinguish between IS4 splicing being important for cac channel localization versus channel stability/degradation. We provide multiple sets of experiments as well as text and figure revisions to strengthen our claim that the IS4B exon is required for cacophony channels to enter motoneuron presynaptic boutons and localize to active zones.

      a. If IS4B was indeed required for cac channel stability (and not for localization to active zones) IS4A channels should be instable wherever they are. This is not the case because we have recorded somatodendritic cacophony currents from IS4A expressing adult motoneurons that were devoid of cac channels with the IS4B exon. Therefore, IS4A cac channels are not instable but underlie somatodendritic voltage dependent calcium currents in these motoneurons. These new data are now shown in the revised figure 3C and referred to in the text on page 7, line 42 to page 8 line 9.

      b. Similarly, if IS4B was required for channel stability, it should not be present anywhere in the nervous system. We tested this by immunohistochemistry for GFP tagged IS4A channels in the larval CNS. Although IS4A channels are sparsely expressed, which is consistent with low expression levels seen in the Western blots (Fig. 1E), there are always defined and reproducible patterns of IS4A label in the larval brain lobes as well as in the anterior part of the VNC. This again shows that the absence of IS4A from presynaptic active zones is not caused by channel instability, because the channel is expressed in other parts of the nervous system. These data are shown in the new supplementary figure 1 and referred to in the text on page 15, lines 3 to 8.

      c. As suggested in a similar context by reviewers 1 and 2, we now show enlargements of the presence of IS4B channels in presynaptic active zones as well as enlargements of the absence of IS4A channels in presynaptic active zones in the revised figures 2A-C and 3A. In these images, no IS4A label is detectable in active zones or anywhere else throughout the axon terminals, thus indicating that IS4B is required for expressing cac channels in the axon terminal boutons and localizing it to active zones. Text and figure legends have been adjusted accordingly.

      d. Related to this, reviewer 1 also recommended to quantify the IS4A and ISB4 channel intensity and co-localization with the active zone marker brp (recommendation for authors). After following the reviewers’ suggestion to adjust the background values in IS4A and IS4B immunolabels to identical (revised Figs. 2A-C), it becomes obvious that IS4A channel are not detectable above background in presynaptic terminals or active zones, thus intensity is close to zero. We still calculated the Pearsons co-localization coefficient for both IS4 variants with the active zone marker brp. For IS4B channels the Pearson’s correlation coefficient is control like, just above 0.6, whereas for IS4A channels we do not find colocalization with brp (Pearson’s below 0.25). These new analyses are now shown in the revised figure 2D and referred to on page 6, lines 33 to 38.

      e. Consistent with our finding that IS4B is required for cac channel localization to presynaptic active zones, upon removal of IS4B we find no evoked synaptic transmission (Fig. 2 in initial submission, now Fig. 3B).

      Together these data are in line with a unique requirement of IS4B at presynaptic active zones (not excluding additional functions of IS4B), whereas IS4A containing cac isoforms are not found in presynaptic active zones and mediate different functions.

      Reviewer #2 (Public Review):

      This study by Bell et al. focuses on understanding the roles of two alternatively spliced exons in the single Drosophila Cav2 gene cac. The authors generate a series of cac alleles in which one or the other mutually exclusive exons are deleted to determine the functional consequences at the neuromuscular junction. They find alternative splicing at one exon encoding part of the voltage sensor impacts the activation voltage as well as localization to the active zone. In contrast, splicing at the second exon pair does not impact Cav2 channel localization, but it appears to determine the abundance of the channel at active zones.

      Together, the authors propose that alternative splicing at the Cac locus enables diversity in Cav2 function generated through isoform diversity generated at the single Cav2 alpha subunit gene encoded in Drosophila.

      Overall this is an excellent, rigorously validated study that defines unanticipated functions for alternative splicing in Cav2 channels. The authors have generated an important toolkit of mutually exclusive Cac splice isoforms that will be of broad utility for the field, and show convincing evidence for distinct consequences of alternative splicing of this single Cav2 channel at synapses. Importantly, the authors use electrophysiology and quantitative live sptPALM imaging to determine the impacts of Cac alternative splicing on synaptic function. There are some outstanding questions regarding the mechanisms underlying the changes in Cac localization and function, and some additional suggestions are listed below for the authors to consider in strengthening this study. Nonetheless, this is a compelling investigation of alternative splicing in Cav2 channels that should be of interest to many researchers.

      (2) We believe that the additional data on cac IS4A isoform localization and function as detailed above (response to public review 1) has strengthened the manuscript and answered some of the remaining questions the reviewer refers to. We are also grateful for the specific additional reviewer suggestions which we have addressed point-by-point and refer to below (section recommendations for authors).

      Reviewer #3 (Public Review):

      Summary:

      Bell and colleagues studied how different splice isoforms of voltage-gated CaV2 calcium channels affect channel expression, localization, function, synaptic transmission, and locomotor behavior at the larval Drosophila neuromuscular junction. They reveal that one mutually exclusive exon located in the fourth transmembrane domain encoding the voltage sensor is essential for calcium channel expression, function, active zone localization, and synaptic transmission. Furthermore, a second mutually exclusive exon residing in an intracellular loop containing the binding sites for Caβ and G-protein βγ subunits promotes the expression and synaptic localization of around ~50% of CaV2 channels, thereby contributing to ~50% of synaptic transmission. This isoform enhances release probability, as evident from increased short-term depression, is vital for homeostatic potentiation of neurotransmitter release induced by glutamate receptor impairment, and promotes locomotion. The roles of the two other tested isoforms remain less clear.

      Strengths:

      The study is based on solid data that was obtained with a diverse set of approaches. Moreover, it generated valuable transgenic flies that will facilitate future research on the role of calcium channel splice isoforms in neural function.

      Weaknesses:

      (1) Based on the data shown in Figures 2A-C, and 2H, it is difficult to judge the localization of the cac isoforms. Could they analyze cac localization with regard to Brp localization (similar to Figure 3; the term "co-localization" should be avoided for confocal data), as well as cac and Brp fluorescence intensity in the different genotypes for the experiments shown in Figure 2 and 3 (Brp intensity appears lower in the dI-IIA example shown in Figure 3G)? Furthermore, heterozygous dIS4B imaging data (Figure 2C) should be quantified and compared to heterozygous cacsfGFP/+.

      According to the reviewer’s suggestion, we have quantified cac localization relative to brp localization by computing the Pearson’s correlation coefficient for controls and IS4A as well as IS4B animals. These new data are shown in the revised Fig. 2D and referred to on page 6, lines 33-38. Furthermore, we now confirm control-like Pearson’s correlation coefficients for all exon out variants except ΔIS4B and show Pearson’s correlation coefficients for all genotypes side-by-side in the revised Fig. 4D (legend has been adjusted accordingly). In addition, in response to the recommendations to authors, we now provide selective enlargements for the co-labeling of Brp and each exon out variant in the revised figures 2-4. We have also adjusted the background in Fig. 2C (ΔIS4B) to match that in Figs. 2A and B (control and ΔIS4A). This allows a fair comparison of cac intensities following excision of IS4B versus excision of IS4A and control (see also Fig 3). Together, this demonstrates the absence of IS4A label in presynaptic active zones much clearer. As suggested, we have also quantified brp puncta intensity on m6/7 across homozygous exon excision mutants and found no differences (this is now stated for IS4A/IS4B in the results text on page 6, lines 37/38 and for I-IIA/I-IIB on page 8, lines 42-44.). We did not quantify the intensity of cacophony puncta upon excision of IS4B because the label revealed no significant difference from background (which can be seen much better in the images now), but the brp intensities remained control-like even upon excision of IS4B.

      (2) They conclude that I-II splicing is not required for cac localization (p. 13). However, cac channel number is reduced in dI-IIB. Could the channels be mis-localized (e.g., in the soma/axon)? What is their definition of localization? Could cac be also mis-localized in dIS4B? Furthermore, the Western Blots indicate a prominent decrease in cac levels in dIS4B/+ and dI-IIB (Figure 1D). How do the decreased protein levels seen in both genotypes fit to a "localization" defect? Could decreased cac expression levels explain the phenotypes alone?

      We have now precisely defined what we mean by cac localization, namely the selective label of cac channels in presynaptic active zones that are defined as brp puncta, but no cac label elsewhere in the presynaptic bouton (page 6, lines 18 to 20). On the level of CLSM microscopy this corresponds to overlapping cac puncta and brp puncta, but no cac label elsewhere in the bouton. Based on the additional analysis and data sets outlined in our response 1 (see above) we conclude that excision of IS4B does not cause channel mislocalization because we find reproducible expression patterns elsewhere in the nervous system as well as somatodendritic cac current in ΔIS4B (for detail see above). Therefore, the isoforms containing the mutually exclusive IS4A exon are expressed and mediate other functions, but cannot substitute IS4B containing isoforms at the presynaptic AZ. In fact, our Western blots are in line with reduced cac expression if all isoforms that mediate evoked release are missing, again indicating that the presynapse specific cac isoforms cannot be replaced by other cac isoforms. This is also in line with the sparse expression of IS4A throughout the CNS as seen in the new supplementary figure 1 (for detail see above).

      (3) Cac-IS4B is required for Cav2 expression, active zone localization, and synaptic transmission. Similarly, loss of cac-I-IIB reduces calcium channel expression and number. Hence, the major phenotype of the tested splice isoforms is the loss of/a reduction in Cav2 channel number. What is the physiological role of these isoforms? Is the idea that channel numbers can be regulated by splicing? Is there any data from other systems relating channel number regulation to splicing (vs. transcription or post-transcriptional regulation)?

      Our data are not consistent with the idea that splicing regulates channel numbers. Rather, splicing can be used to generate channels with specific properties that match the demand at the site of expression. For the IS4 exon pair we find differences in activation voltage between IS4A and IS4B channels (revised Fig. 3C), with IS4B being required for sustained HVA current. IS4A does not localize to presynaptic active zones at the NMJ and is only sparsely expressed elsewhere in the NS (new supplementary Fig. 1). By contrast, IS4B is abundantly expressed in many neuropils. Therefore, taking out IS4B takes out the more abundant IS4 isoform. This is consistent with different expression levels for IS4 isoforms that have different functions, but we do not find evidence for splicing regulating expression levels per se.

      Similarly, the I-II mutually exclusive exon pair differs markedly in the presence or absence of G-protein βγ binding sites that play a role in acute channel regulation as well the conservation of the sequence for β-subunit binding (see page 5, lines 9-17). Channel number reduction in active zones occurs specifically if expression of the cac channels with the G<sub>βγ</sub>-binding site as well as the more conserved β-subunit binding is prohibited by excision of the I-IIB exon (see Fig. 5F). Vice versa, excision of I-IIA does not result in reduced channel numbers. This scenario is consistent with the hypothesis that conserved β-subunit binding affects channel number in the active zone (see page 17, lines 3 to 6 and lines 33-36), but we have no evidence that I-II splicing per se affects channel number.

      (4) Although not supported by statistics, and as appreciated by the authors (p. 14), there is a slight increase in PSC amplitude in dIS4A mutants (Figure 2). Similarly, PSC amplitudes appear slightly larger (Figure 3J), and cac fluorescence intensity is slightly higher (Figure 3H) in dI-IIA mutants. Furthermore, cac intensity and PSC amplitude distributions appear larger in dI-IIA mutants (Figures 3H, J), suggesting a correlation between cac levels and release. Can they exclude that IS4A and/or I-IIA negatively regulate release? I suggest increasing the sample size for Canton S to assess whether dIS4A mutant PSCs differ from controls (Figure 2E). Experiments at lower extracellular calcium may help reveal potential increases in PSC amplitude in the two genotypes (but are not required). A potential increase in PSC amplitude in either isoform would be very interesting because it would suggest that cac splicing could negatively regulate release.

      There are several possibilities to explain this, but as none of the effects is statistically significant, we prefer to not investigate this in further depth. However, given that we cannot find IS4A in presynaptic active zones (revised figures 2C and 3A plus the new enlargements 2Ci and 3Ai, revised text page 6, lines 22 to 24 and 29 to 31, and page 7, second paragraph, same as public response 1D) IS4A channels cannot have a direct negative effect on release probability. Nonetheless, given that IS4A containing cac isoforms mediate functions in other neuronal compartments (see revised Fig. 3C) it may regulate release indirectly by affecting e.g. action potential shape. Moreover, in response to the more detailed suggestions to authors we provide new data that give additional insight.

      (5) They provide compelling evidence that IS4A is required for the amplitude of somatic sustained HVA calcium currents. However, the evidence for effects on biophysical properties and activation voltage (p. 13) is less convincing. Is the phenotype confined to the sustained phase, or are other aspects of the current also affected (Figure 2J)? Could they also show the quantification of further parameters, such as CaV2 peak current density, charge density, as well as inactivation kinetics for the two genotypes? I also suggest plotting peaknormalized HVA current density and conductance (G/Gmax) as a function of Vm. Could a decrease in current density due to decreased channel expression be the only phenotype? How would changes in the sustained phase translate into altered synaptic transmission in response to AP stimulation?

      Most importantly, sustained HVA current is abolished upon excision of IS4B (not IS4A, we think the reviewer accidentally mixed up the genotype) and presynaptic active zones at the NMJ contain only cac isoforms with the IS4B exon. This indicates that the cac isoforms that mediate evoked release encode HVA channels. The somatodendritic currents shown in the revised figure 3C (previously 2J) that remain upon excision of IS4B are mediated by IS4A containing cac isoforms. Please note that these never localize to the presynaptic active zone, and thus do not contribute to evoked release. Therefore, the interpretation is that specifically sustained HVA current encoded by IS4B cac isoforms is required for synaptic transmission. Reduced cac current density due to decreased channel expression is not the cause for impaired evoked release upon IS4B excision, but instead, the cause is the absence of any cac channels in active zones. IS4B-containing cac isoforms encode sustained HVA current, and we speculate that this might be a well suited current to minimize cacophony channel inactivation in the presynaptic active zone. Given that HVA current shows fast voltage dependent activation and fast inactivation upon repolarization, it is useful at large intraburst firing frequencies as observed during crawling (Kadas et al., 2017) without excessive cac inactivation (see page 15, Kadas, lines 16 to 20).

      However, we agree with the reviewer that a deeper electrophysiological analysis of splice isoform specific cac currents will be instructive. We have now added traces of control and ΔIS4B from a holding potential of -90 mv (revised Fig. 3C, bottom traces and revised text on page 7, line 43 to page 8, lines 1 to 10), and these are also consistent with IS4B mediating sustained HVA cac current. However, further analysis of activation and inactivation voltages and kinetics suffers form space clamp issues in recordings from the somata of such complex neurons (DLM motoneurons of the adult fly contain roughly 6000 µm of dendrites with over 4000 branches, Ryglewski et al., 2017, Neuron 93(3):632-645). Therefore, we will analyze the currents in a heterologous expression system and present these data to the scientific community as a separate study at a later time point.

      (6) Why was the STED data analysis confined to the same optical section, and not to max. intensity z-projections? How many and which optical sections were considered for each active zone? What were the criteria for choosing the optical sections? Was synapse orientation considered for the nearest neighbor Cac - Brp cluster distance analysis? How do the nearest-neighbor distances compare between "planar" and "side-view" Brp puncta?

      Maximum intensity z-projections would be imprecise because they can artificially suggest close proximity of label that is close by in x and y but far away in z. Therefore, the analysis was executed in xy-direction of various planes of entire 3D image stacks. We considered active zones of different orientations (Figs. 5C, D) to account for all planes. In fact, we searched the entire z-stacks until we found active zones of all orientations within the same boutons, as shown in figures 5C1-C6. The same active zone orientations were analyzed for all exon-out mutants with cac localization in active zones. The distance between cac and brp did not change if viewed from the side or any other orientation. We now explain this in more clarity in the results text on page 9, lines 23/24.

      (7) Cac clusters localize to the Brp center (e.g., Liu et al., 2011). They conclude that Cav2 localization within Brp is not affected in the cac variants (p. 8). However, their analysis is not informative regarding a potential offset between the central cac cluster and the Brp "ring". Did they/could they analyze cac localization with regard to Brp ring center localization of planar synapses, as well as Brp-ring dimensions?

      In the top views (planar) we did not find any clear offset in cac orientation to brp between genotypes. In such planar synapses (top views, Fig. 5D, left row) we did not find any difference in Brp ring dimensions. We did not quantify brp ring dimensions rigorously, because this study focusses on cac splice isoform-specific localization and function. Possible effects of different cac isoforms on brp-ring dimensions or other aspects of scaffold structure are not central to our study, in particular given that brp puncta are clearly present even if cac is absent from the synapse (Fig. 3A), indicating that cac is not instructive for the formation of the brp scaffold.

      (8) Given the accelerated PSC decay/ decreased half width in dI-IIA (Fig. 5Q), I recommend reporting PSC charge in Figure 3, and PPR charge in Figures 5A-D. The charge-based PPRs of dI-IIA mutants likely resemble WT more closely than the amplitude-based PPR. In addition, miniature PSC decay kinetics should be reported, as they may contribute to altered decay kinetics. How could faster cac inactivation kinetics in response to single AP stimulation result in a decreased PSC half-width? Is there any evidence for an effect of calcium current inactivation on PSC kinetics? On a similar note, is there any evidence that AP waveform changes accelerate PSC kinetics? PSC decay kinetics are mainly determined by GluR decay kinetics/desensitization. The arguments supporting the role of cac splice isoforms in PSC kinetics outlined in the discussion section are not convincing and should be revised.

      We agree that reporting charge in figure 3 is informative and do so in the revised text. Since the result (no significant difference in the PSCs between between CS, cac<sup>GFP</sup>, <sup>ΔI-IIA</sup>, and transheterozygous I-IIA/I-IIB, but significantly smaller values in ΔI-IIB) remained unchanged no matter whether charge or amplitude were analyzed, we decided to leave the figure as is and report the additional analysis in the text (page 8, lines 40 to 42). This way, both types of analysis are reported. Please note that EPSC amplitude is slightly but not significantly increased upon excision of I-IIA (Fig. 4J), whereas EPSC half amplitude width is significantly smaller (Fig. 5Q, now revised Fig 6R). Together, a tendency of increased EPSC amplitudes and smaller half amplitude width result in statistically insignificant changes in EPSC in ∆I-IIA (now discussed on page 15, lines 37 to 40). We also understand the reviewer’s concern attributing altered EPSC kinetics to presynaptic cac channel properties. We have toned down our interpretation in the discussion and list possible alterations in presynaptic AP shape or cac channel kinetics as alternative explanations (not conclusions; see revised discussion on page 15, line 40 to page 16, line 2). Moreover, we have quantified postsynaptic GluRIIA abundance to test whether altered PSC kinetics are caused by altered GluRIIA expression. In our opinion, the latter is more instructive than mini decay kinetic analysis because this depends strongly on the distance of the recording electrode to the actual site of transmission in these large muscle cells. Although we find no difference in GluRIIA expression levels we now clearly state that we cannot exclude other changes in GluR receptor fields, which of course, could also explain altered PSC kinetics. We have updated the discussion on page 16, lines 2/3 accordingly.

      (9) Paired-pulse ratios (PPRs): On how many sweeps are the PPRs based? In which sequence were the intervals applied? Are PPR values based on the average of the second over the first PSC amplitudes of all sweeps, or on the PPRs of each sweep and then averaged? The latter calculation may result in spurious facilitation, and thus to the large PPRs seen in dI-IIB mutants (Kim & Alger, 2001; doi: 10.1523/JNEUROSCI.21-2409608.2001).

      We agree that the PP protocol and analyses had to be described more precisely in the methods and have done so on page 23, lines 31 to 37 in the methods. Mean PPR values are based on the PPRs of each sweep and then averaged. We are aware of the study of Kim and Alger 2001 and have re-analyzed the PP data in both ways outlined by the reviewer. We get identical results with either analyses method. Spurious facilitation is thus not an issue in our data. We now explain this in the methods section along with the PPR protocol. The large spread seen in dI-IIB is indeed caused by reduced calcium influx into active zones with fewer channels, as anticipated by the reviewer (see next point).

      (10) Could the dI-IIB phenotype be simply explained by a decrease in channel number/ release probability? To test this, I propose investigating PPRs and short-term dynamics during train stimulation at lower extracellular Ca2+ concentration in WT. The Ca2+ concentration could be titrated such that the first PSC amplitude is similar between WT and dI-IIB mutants. This experiment would test if the increased PPR/depression variability is a secondary consequence of a decrease in Ca2+ influx, or specific to the splice isoform.

      In fact, the interpretation that decreased PSC amplitude upon I-IIB excision is caused mainly by reduced channel number is precisely our interpretation (see discussion page 14, last paragraph to page 15, first paragraph in the original submission, now page 16, second paragraph paragraph). In addition, we are grateful for the reviewer’s suggestion to triturate the external calcium such that the first PSC amplitude in matches in ∆I-IIB and control. This experiment tests whether altered short term plasticity is solely a function of altered channel number or whether additional causes, such as altered channel properties, also play into this. We triturated the first pulse amplitude in ∆I-IIB to match control and find that paired pulse ratio and the variance thereof are not different anymore. Therefore, the differences observed in identical external calcium can be fully explained by altered channel numbers. This additional dataset is shown in the revised figures 6D and E and referred to in the results section on page 10, lines 14 to 25 and the discussion on page16, lines 36 to 38.

      (11) How were the depression kinetics analyzed? How many trains were used for each cell, and how do the tau values depend on the first PSC amplitude? Time constants in the range of a few (5-10) milliseconds are not informative for train stimulations with a frequency of 1 or 10 Hz (the unit is missing in Figure 5H). Also, the data shown in Figures 5E-K suggest slower time constants than 5-10 ms. Together, are the data indeed consistent with the idea that dIIIB does not only affect cac channel number, but also PPR/depression variability (p. 9)?

      For each animal the amplitudes of all subsequent PSCs in each train were plotted over time and fitted with a single exponential. For depression at 1 and 10 Hz, we used one train per animal, and 5-6 animals per genotype (as reflected in the data points in Figs. 6I, M). This is now explained in more detail in the revised methods section (page 23, lines 39 to 41). The tau values are not affected by the amplitude of the first PSC. First, we carefully re-fitted new and previously presented depression data and find that the taus for depression at low stimulation frequencies (1 and 10Hz) are not affected by exon excisions at the I-II site. We thank the reviewer for detecting our error in units and tau values in the previous figure panels 5H and L (this has now been corrected in the revised figure panels 6I and M). Given that PSC amplitude upon I-IIB excision is significantly smaller than in controls and following I-IIA excision, we suspected that the time course of depression at low stimulation frequency is not significantly affected by the amount of calcium influx during the first PSC. To further test this, we followed the reviewer ’s suggestion and re-measured depression at 1 and 10 Hz for cac-GFP controls and for delta I-IIB in a higher external calcium concentration (1.8 mM), so that the first PSC was increased in amplitude in both genotypes (1.8 mM external calcium triturates the PSC amplitude in delta I-IIB to match that of controls measured in 0.5 mM external calcium, see revised Figs. 6H, L). Neither in control, nor in delta I-IIB did this affect the time course of synaptic depression (see revised Figs. 6I, M). This indicates that at low stimulation frequencies (1 and 10Hz) the time course of depression is not affected by mean quantal content. This is consistent with the paired pulse ratio at 100 ms interpulse interval shown in figures 6A-D. However, for synaptic depression at 1 Hz stimulation the variability of the data is higher for delta I-IIB (independent of external calcium concentration, see rev. Fig. 6I), which might also be due to reduced channel number in this genotype. Taken together, the data are in line with the idea that altered cac channel numbers in active zones are sufficient to explain all effects that we observe upon I-IIB excision on PPRs and synaptic depression at low stimulation frequencies. This is now clarified in the revised text on page 12, lines 3 to 7.

      (12) The GFP-tagged I-IIA and mEOS4b-tagged I-IIB cac puncta shown in Figure 6N appear larger than the Brp puncta. Endogenously tagged cac puncta are typically smaller than Brp puncta (Gratz et al., 2019). Also, the I-IIA and I-IIB fluorescence sometimes appear to be partially non-overlapping. First, I suggest adding panels that show all three channels merged. Second, could they analyze the area and area overlap of I-IIA and I-IIB with regard to each other and to Brp, and compare it to cac-GFP? Any speculation as to how the different tags could affect localization? Finally, I recommend moving the dI-IIA and dI-IIB localization data shown in Figure 6N to an earlier figure (Figure 1 or Figure 3).

      We now show panels with the two I-II cac isoforms merged in the revised figure 7H (previously 6N). We also tested merging all three labels as suggested, but found this not instructive for the reader. We thank the reviewer for pointing out that the Brp puncta appeared smaller than the cac puncta in some panels. We carefully went through the data and found that the Brp puncta are not systematically smaller than the cac puncta. Please note that punctum size can appear quite differently, depending on different staining qualities as well as different laser intensities and different point spread in different imaging channels. The purpose of this figure was not to analyze punctum size and labeling intensity, but instead, to demonstrate that I-IIA and I-IIB are both present in most active zones, but some active zones show only I-IIB labeling, as quantified in figure 7I. We did not follow the suggestion to conduct additional co-localization analyses and compare it with cac-GFP controls, because Pearson co-localization coefficients for cac-GFP and all exon-out variants analyzed, including delta I-IIA and delta I-IIB are presented in the revised figure 4D. Moreover, delta I-IIA and delta I-IIB show similar Manders 1 and 2 co-localization coefficients with Brp (see Figs. 4E, F). We do not want to speculate whether the different tags have any effect on localization precision. Artificial differences in localization precision can also be suggested by different antibodies, but we know from our STED analyses with identical tags and antibodies for all isoforms that I-IIA and I-IIB co-localize identically with Brp (see Figs. 5A-E). Finally, we prefer to not move the figure because we believe it is informative to show our finding that active zones usually contain both splice I-II variants together with the finding that only I-IIB is required for PHP.

      Recommendations for the authors:

      Reviewing Editor Comments:

      We thank you for your submission. All three reviewers urge caution in interpreting the S4 splice variant playing a role specifically in Cac localization, as opposed to just leading to instability and degradation. There are other issues with the electrophysiological experiments, a need for improved imaging and analyses, and some areas of interpretation detailed in the reviews.

      We agree that additional data was required to conclude that IS4 splicing plays a specific role in cac channel localization and is not just leading to channel instability and degradation. As outlined in detail in our response to reviewer 1, comment 1, we conducted several sets of experiments to support our interpretation. First, electrophysiological experiments show that upon removal of IS4B, which eliminates synaptic transmission at the larval NMJ and cac positive label in presynaptic active zones, somatodendritic cac current is reliably recorded (new data in revised figure 3C). This is not in line with a channel instability or degradation effect, but instead with IS4B containing isoforms being required and sufficient for evoked release from NMJ motor terminals, whereas IS4A isoforms are not sufficient for evoked release from axon terminals, but IS4A isoforms alone can mediate a distinct component of somatodendritic calcium current. Second, immunohostochemical analyses reveal that IS4A, which is not present in NMJ presynaptic active zones, is expressed sparsely, but in reproducible patterns in the larval brain lobes and in specific regions of the anterior VNC parts (new supplementary figure 1). Again, the absence of a IS4A-containing cac isoform from presynaptic active zones but their simultaneous presence in other parts of the nervous system is in accord with isoform specific localization, but not with general channel isoform instability. Third, enlargements of NMJ boutons with brp positive presynaptic active zones confirm the absence of IS4A and the presence of IS4B in active zones (these enlargements are now shown in the revised figures 2A-C, 3A, and 4A-C). Fourth, as suggested we have quantified the Pearson co-localization of IS4 isoforms with Brp in presynaptic active zones (revised Fig. 2D). This confirms quantitatively similar co-localization of IS4B and control with Brp, but no co-localization of IS4A with Brp. In fact, the labeling intensity of IS4A in presynaptic active zones is quantitatively not significantly different from background, no IS4A label is detected anywhere in the axon terminals at the NMJ, but we find IS4 label in the CNS. Together, these data strongly support our interpretation that the IS4 splice site plays a distinct role in cac channel localization. Figure legends as well as results and discussion section have been modified accordingly (the respective page and line numbers are listed in our-point-by-point responses).

      In addition, we have carefully addressed all other public comments as well as all other recommendations for authors by providing multiple new data sets, new image analyses, and revising text. Addressing the insightful comments of all three reviewers and the reviewing editor has greatly helped to make the manuscript better.

      Reviewer #1 (Recommendations For The Authors):

      The conclusion that the IS4B exon controls Cac localization to active zones versus simply being required for channel abundance is not well supported. The authors need to either mention both possibilities or provide stronger support for the active zone localization model if they want to emphasize this point.

      We agree and have included several additional data sets as outlined in our response to point 1 of reviewer 1 and to the reviewing editor (see above). These new data strongly support our interpretation that the IS4B exon controls Cac localization to active zones and is not simply required for channel abundance. The additions to the figures and accompanying text (including the respective figure panel, page, and line numbers) are listed in the point-bypoint responses to the reviewers’ public suggestions.

      Figure 2C staining for Cac localization in the delta 4B line is difficult to compare to the others, as the background staining is so high (muscles are green for example). As such, it is hard to determine whether the arrows in C are just background.

      We had over-emphasized the green label to show that there really is no cacophony label in active zones. However, we agree that this hampered image interpretation. Thus, we have adjusted brightness such that it matches the other genotypes (see new figure panel 2C, and figure 3A, bottom). Revising the figure as suggested by the reviewer shows much more clearly that IS4B puncta are detected exclusively in presynaptic active zones, whereas IS4A channels are not detectable in active zones or anywhere else in the axon terminal boutons. Quantification of IS4A label in brp positive active zones confirms that labeling intensity is not significantly above background (page 6, lines 29 to 31 and page 7, lines 19 to 21). Therefore, IS4A is not detectable in active zones at the NMJ.

      It seems more likely that the removal of the 4B exon simply destabilizes the protein and causes it to be degraded (as suggested by the Western), rather than mislocalizing it away from active zones. It's hard to imagine how some residue changes in the S4 voltage sensor would control active zone localization to begin with. The authors should note that the alternative explanation is that the protein is just degraded when the 4B exon is removed.

      Based on additional data and analyses, we disagree with the interpretation that removal of IS4B disrupts protein integrity and present multiple lines of evidence that support sparse expression of IS4A channels (ΔIS4B). As outlined in our response to reviewer 1 and to the reviewing editor, we show (1) in new immunohistochemical stainings (new supplementary figure 1) that upon removal of IS4B, sparse label is detectable in the VNC and the brain lobes (for detail see above). (2) In our new figure 3C, we show cacophony-mediated somatodendritic calcium currents recorded from adult flight motoneurons in a control situation and upon removal of IS4B that leaves only IS4A channels. This clearly demonstrates that IS4A underlies a substantial component of the HVA somatodendritic calcium current, although it is absence from axon terminals. This is in line with isoform specific functions at different locations, but not with IS4A instability/degradation. (3) We do not agree with the reviewer’s interpretation of the Western Blot data in figure 1E (formerly figure 1D). Together with our immunohistochemical data that show sparse cacophony IS4A expression, we think that the faint band upon removal of IS4B in a heterozygous background (that reduces labeled channels even further) reflects the sparseness of IS4A expression. This sparseness is not due to channel instability, but to IS4A functions that are less abundant than the ubiquitously expressed cac<sup>IS4B</sup> channels at presynaptic active zones of fast chemical synapses (see page 15, lines 24 to 29).

      If they really want to claim the 4B exon governs active zone localization, much higher quality imaging is required (with enlarged views of individual boutons and their AZs, rather than the low-quality full NMJ imaging provided). Similarly, higher resolution imaging of Cac localization at Muscle 12 (Figure 2H) boutons would be very useful, as the current images are blurry and hard to interpret. Figure 6N shows beautiful high-resolution Cac and Brp imaging in single boutons for the I-II exon manipulations - the authors should do the same for the 4B line. For all immuno in Figure 2, it is important to quantify Cac intensity as well. There is no quantification provided, just a sample image. The authors should provide quantification as they do for the delta I-II exons in Figure 3.

      We did as suggested and added figure panels to figure 2A-C and to new figures 3A (formerly part of figure 2 and 4A-C (formerly figure 3) showing magnified label at the NMJ AZs to better judge on cacophony expression after exon excision. These data are now referred to in the results section on page 6, lines 22 to 24, page 7, lines 18 to 21 and page 8, lines 17/18.

      As suggested, we now also provide quantification of co-localization with brp puncta as Pearson’s correlation coefficient for control, IS4B, and IS4A in the new figure panel 2D (text on page 6, lines 34 to 38). This further underscores control-like active zone localization of IS4B but no significant active zone localization of IS4A. As suggested, we quantified now also the intensity of IS4B label in active zones, and it was not different from control (see revised figure 4H and text on page 8, lines 38/39). We did not quantify the intensity of IS4A label, because it was not over background (text, page 6, lines 30/31).

      Reviewer #2 (Recommendations For The Authors):

      (1a) Questions about the engineered Cac splice isoform alleles:

      The authors using CRISPR gene editing to selectively remove the entire alternatively spliced exons of interest. Do the authors know what happens to the cac transcript with the deleted exon? Is the deleted exon just skipped and spliced to the next exon? Or does the transcript instead undergo nonsense-mediated decay?

      We do not believe that there is nonsense mediated mRNA decay, because for all exon excisions the respective mRNA and protein are made. Protein has been detected on the level of Western blotting and immunocytochemistry. Therefore, we are certain that the mRNA is viable for each exon excision (and we have confirmed this for low abundance cac protein isoforms by rt-PCR), but only subsets of cac isoforms can be made from mRNAs that are lacking specific exons. However, we can not make any statements as to whether the lack of specific protein isoforms exerts feedback on mRNA stability, the rate of transcription and translation, or other unknown effects.

      (1b) While it is clear that the IS4 exons encode part of the voltage sensor in the first repeat, are there studies in Drosophila to support the putative Ca-beta and G-protein beta-gamma binding sites in the I-II loop? Or are these inferred from Mammalian studies?

      To the best of our knowledge, there are no studies in Drosophila that unambiguously show Caβ and Gβγ binding sites in the I-II loop of cacophony. However, sequence analysis strongly suggests that I-IIB contains both, a Caβ as well as a Gβγ binding site (AID: α-interacting domain) because the binding motif QXXER is present. In mouse Cav2.1 and Ca<sub>v</sub>2.2 channels the sequence is QQIER, while in Drosophila cacophony I-IIB it is QQLER. In the alternative IIIA, this motif is not present, strongly suggesting that G<sub>βγ</sub> subunits cannot interact at the AID. However, as already suggested by Smith et al. (1998), based on sequence analysis, Ca<sub>β</sub> should still be able to bind, although possibly with a lower affinity. We agree that this information should be given to the reader and have revised the text accordingly on page 5, lines 9 to 17.

      (1c) The authors assert that splicing of Cav2/cac in flies is a means to encode diversity, as mammals obviously have 4 Cav2 genes vs 1 in flies. However, as the authors likely know, mammalian Cav2 channels also have various splice isoforms encoded in each of the 4 Cav2 genes. The authors should discuss in more detail what is known about the splicing of individual mammalian Cav2 channels and whether there are any homologous properties in mammalian channels controlled by alternative splicing.

      We agree and now provide a more comprehensive discussion of vertebrate Ca<sub>v</sub>2 splicing and its impact on channel function. In line to what we report in Drosophila, properties like G<sub>βγ</sub> binding and activation voltage can also be affected by alternative splicing in vertebrate Ca<sub>v</sub>2 channel, through the exon patterns are quite different from Drosophila. We integrated this part on page 14, first paragraph) in the revised discussion. The respective text is below for the reviewer’s convenience:

      “However, alternative splicing increases functional diversity also in mammalian Ca<sub>v</sub>2 channels. Although the mutually exclusive splice site in the S4 segment of the first homologous repeat (IS4) is not present in vertebrate Cav channels, alternative splicing in the extracellular linker region between S3 and S4 is at a position to potentially change voltage sensor properties (Bezanilla 2002). Alternative splice sites in rat Ca<sub>v</sub>2.1 exon 24 (homologous repeat III) and in exon 31 (homologous repeat IV) within the S3-S4 loop modulate channel pharmacology, such as differences in the sensitivity of Ca<sub>v</sub>2.1 to Agatoxin. Alternative splicing is thus a potential cause for the different pharmacological profiles of P- and Q-channels (both Ca<sub>v</sub>2.1; Bourinet et al. 1999). Moreover, the intracellular loop connecting homologous repeats I and II is encoded by 3-5 exons and provides strong interaction with G<sub>βγ</sub>-subunits (Herlitze et al. 1996). In Ca<sub>v</sub>2.1 channels, binding to G<sub>βγ</sub> subunits is potentially modulated by alternative splicing of exon 10 (Bourinet et al. 1999). Moreover, whole cell currents of splice forms α1A-a (no Valine at position 421) and α1A-b (with Valine) represent alternative variants for the I-II intracellular loop in rat Ca<sub>v</sub>2.1 and Ca<sub>v</sub>2.2 channels. While α1A-a exhibits fast inactivation and more negative activation, α1A-b has delayed inactivation and a positive shift in the IV-curve (Bourinet et al. 1999). This is phenotypically similar to what we find for the mutually exclusive exons at the IS4 site, in which IS4B mediates high voltage activated cacophony currents while IS4A channels activate at more negative potentials and show transient current (Fig. 3; see also Ryglewski et al. 2012). Furthermore, altered Ca<sub>β</sub> interaction have been shown for splice isoforms in loop III (Bourinet et al. 1999), similar to what we suspect for the I-II site in cacophony. Finally, in mammalian VGCCs, the C-terminus presents a large splicing hub affecting channel function as well as coupling distance to other proteins. Taken together, Ca<sub>v</sub>2  channel diversity is greatly enhanced by alternative splicing also in vertebrates, but the specific two mutually exclusive exon pairs investigated here are not present in vertebrate Ca<sub>v</sub>2 genes.”

      (1d) In Figure 1, it would be helpful to see the entire cac genomic locus with all introns/exons and the 4 specific exons targeted for deletion.

      We agree and have changed figure 1 accordingly.

      (2a) Cav2.IS4B deletion alleles:

      More work is necessary to explain the localization of Cac controlled by the IS4B exon. First, can the authors determine whether actual Cac channels are present at NMJ boutons? The authors seem to indicate that in the IS4B deletion mutants, some Cac (GFP) signal remains in a diffuse pattern across NMJ boutons. However, from the imaging of wild-type Cac-GFP (and previous studies), there is no Cac signal outside of active zones defined by the BRP signal. It would benefit the study to a) take additional, higher resolution images of the remaining Cac signal at NMJs in IS4B deletion mutants, and b) comment on whether the apparent remaining signal in these mutants is only observed in the absence of IS4Bcontaining Cac channels, or if the IS4A-positive channels are normally observed (but perhaps mis-localized?).

      We have conducted additional analyses to show convincingly that IS4A channels (that remain upon IS4B deletion) are absent from presynaptic active zone. Please see also responses to reviewers 1 and 3. By adjusting the background values in of CLSM images to identical values in control, delta IS4A, and delta IS4B, as well as by providing selective enlargements as suggested, the figure panels 2C, Ci and 3A now show much clearer, that upon deletion of IS4B no cac label remains in active zones or anywhere else in the axon terminal boutons (see text on page 6, lines 22 to 24). This is further confirmed by quantification showing the in IS4B mutants cac labeling intensity in active zones is not above background (see text on page 6, lines 27 to 31). We never intended to indicate that there was cac signal outside of active zones defined by the brp signal, and we now carefully went through the text to not indicate this possibility unintentionally anywhere in the manuscript.

      (2b) Do the authors know whether any presynaptic Ca2+ influx is contributed by IS4Apositive Cac channels at boutons, given the potential diffuse localization? There are various approaches for doing presynaptic Ca2+ imaging that could provide insight into this question.

      We agree that this is an interesting question. However, based on the revisions made, we now show with more clarity that IS4A channels are absent from the presynaptic terminal at the NMJ. IS4A labeling intensities within active zones and anywhere else in the axon terminals are not different from background (see text on page 6, lines 27 to 31 and revised Figs. 2C, Ci, and 3A with new selective enlargements in response to comments of both other reviewers). This is in line with our finding that evoked synaptic transmission from NMJ axon terminals to muscle cells is mostly absent upon excision of IS4B (see Fig. 3B). The very small amplitude EPSC (below 5 % of the normal amplitude of evoked EPSCs) that can still be recorded in the absence of IS4B is similar to what is observed in cac null mutant junctions and is mediated by calcium influx through another voltage gated calcium channels, a Ca<sub>v</sub>1 homolog named Dmca1D, as we have previously published (Krick et al., 2021, PNAS 118(28):e2106621118. Gathering additional support for the absence of IS4A from presynaptic terminals by calcium imaging experiments would suffer significantly from the presence of additional types of VGCCs in presynaptic terminals (for sure Dmca1D (Krick et al., 2021) and potentially also the Ca<sub>v</sub>3 homolog DmαG or Dm-α1T). Such experiments would require mosaic null mutants for cac and DmαG channels in a mosaic IS4B excision mutant, which, if feasible at all, would be very hard and time consuming to generate. In the light of the additional clarification that IS4A is not located in NMJ axon terminal boutons, as shown by additional labeling intensity analysis, revised figures with selective enlargement, and revised text, we feel confident to state that IS4A is not sufficient for evoked SV release.

      (2c) Mechanistically, how are amino acid changes in one of the voltage sensing domains in Cac related to trafficking/stabilization/localization of Cac to AZs?

      This is an exciting question that has occupied our discussions a lot. Some sorting mechanism must exist that recognizes the correct protein isoforms, just as sorting and transport mechanisms exist that transport other synaptic proteins to the synapse. We do not think that the few amino acid changes in the voltage sensor are directly involved in protein targeting. We rather believe that the cacophony variants that happen to contain this specific voltage sensor are selected for transport out to the synapse. There are possibilities to achieve this cell biological, but we have not further addressed potential mechanisms because we do not want enter the realms of speculation.

      (3) How are auxiliary subunits impacted in the Cac isoform mutants?

      Recent work by Kate O'Connor-Giles has shown that both Stj and Ca-Beta subunits localize to active zones along with Cac at the Drosophila NMJ. Endogenously tagged Stj and CaBeta alleles are now available, so it would be of interest to determine if Stj and particular Cabeta levels or localization change in the various Cac isoform alleles. This would be particularly interesting given the putative binding site for Ca-beta encoded in the I-II linker.

      We agree that the synthesis of the work of Kate O'Connor-Giles group and our study open up new avenues to explore exciting hypotheses about differential coupling of specific cacophony splice isoforms with distinct accessory proteins such as Caβ and α<sub>2</sub>δ subunits. However, this requires numerous full sets of additional experiments and is beyond the scope of this study.

      (4a) Interpretation of short-term plasticity in the I-IIB exon deletion:

      The changes in short-term plasticity presented in Figure 5 are interpreted as an additional phenotype due to the loss of the I-IIB exon, but it seems this might be entirely explained simply due to the reduced Cac levels. Reduced Cac levels at active zones will obviously reduce Ca2+ influx and neurotransmitter release. This may be really the only phenotype/function of the I-IIB exon. Hence, to determine whether loss of the I-IIB exon encodes any functions in short-term plasticity, separate from reduced Cac levels, the authors should compare short-term plasticity in I-IIB loss alleles compared to wild type with starting EPSC amplitudes are equal (for example by reducing extracellular Ca2+ levels in wild type to achieve the same levels at in Cac I-IIB exon deleted alleles). Reduced release probability, simply by reduced Ca2+ influx (either by reduced Cac abundance or extracellular Ca2+) should result in more variability in transmission, so I am not sure there is any particular function of the I-IIB exon in maintaining transmission variability beyond controlling Cac abundance at active zones.

      For two reasons we are particularly grateful for this comment. First, it shows us that we needed to explain much clearer that our interpretation is that changes in paired pulse ratios (PPRs) and in depression at low stimulation frequencies are a causal consequence of lower channel numbers upon I-IIB exon deletion, precisely as pointed out by the reviewer. We have carefully revised the text accordingly on page 10, lines 14-25, page 11, lines 3-7 and 22-28; page 16, lines 36-38. Second, the experiment suggested by the reviewer is superb to provide additional evidence that the cause of altered PPRs is in fact reduced channel number, but not altered channel properties. Accordingly, we have conducted additional TEVC recordings in elevated external calcium (1.8 mM) so that the single PSC amplitudes in I-IIB excision animals match those of controls in 0.5 mM extracellular calcium. This makes the amplitudes and the variance of PPR for all interpulse intervals tested control-like (see revised Figs. 6D, E). This strongly indicates that differences observed in PPRs as well as the variance thereof were caused by the amount of calcium influx during the first EPSC, and thus by different channel numbers in active zones.

      (4b) Another point about the data in Figure 5: If "behaviorally relevant" motor neuron stimulation and recordings are the goal, the authors should also record under physiological Ca2+ conditions (1.8 mM), rather than the highly reduced Ca2+ levels (0.5 mM) they are using in their protocols.

      Although we doubt that the effective extracellular calcium concentration that determines the electromotoric force for calcium to enter the ensheathed motoneuron terminals in vivo during crawling is known, we followed the reviewer’s suggestion partly and have repeated the high frequency stimulation trains for ΔI-IIB in 1.8 mM calcium. As for short-term plasticity this brings the charge conducted to values as observed in control and in ΔI-IIA in 0.5 mM calcium. Therefore, all difference observed in previous figure 5 (now revised figure 6) can be accounted to different channel numbers in presynaptic active zones. This is now explained on page 11, lines 19-28. For controls recordings at high frequency stimulation in higher external calcium (e.g. 2 mM) have previously been published and show significant synaptic depression (e.g. Krick et al., 2021, PNAS). Given that in the exon out variants we do not expect any differences except from those caused by different channel numbers, we did not repeat these experiments for control and ΔI-IIA.

      (5a) Mechanism of Cac's role in PHP :

      As the authors likely know, mutations in Cac were previously reported to disrupt PHP expression (see Frank et al., 2006 Neuron). Inexplicably, this finding and publication were not cited anywhere in this manuscript (this paper should also be cited when introducing PhTx, as it was the first to characterize PhTx as a means of acutely inducing PHP). In the Frank et al. paper (and in several subsequent studies), PHP was shown to be blocked in mutations in Cac, namely the CacS allele. This allele, like the I-IIB excision allele, reduces baseline transmission presumably due to reduced Ca2+ influx through Cac. The authors should at a minimum discuss these previous findings and how they relate to what they find in Figure 6 regarding the block in PHP in the Cac I-IIB excision allele.

      We thank the reviewer for pointing this out and apologize for this oversight. We agree that it is imperative to cite the 2006 paper by Frank et al. when introducing PhTx mediated PHP as well as when discussing cac the effects of cac mutants on PHP together with other published work. We have revised the text accordingly on page 12, lines 9-11 and 21-23 and on page 17, lines 29-33.

      In terms of data presentation in Fig. 6, as is typical in the field, the authors should normalize their mEPSC/QC data as a percentage of baseline (+PhTx/-PhTx). This makes it easier to see the reduction in mEPSC values (the "homeostatic pressure" on the system) and then the homeostatic enhancement in QC. Similarly, in Fig. 6M, the authors should show both mEPSC and QC as a percentage of baseline (wild type or non-GluRIIA mutant background).

      We agree and have changed figure presentation accordingly. Figure 7 (formerly figure 6) was updated as was the accompanying results text on page 12, lines 23-40.

      (6) Cac I-IIA and I-IIB excision allele colocalization at AZs:

      These are very nice and important experiments shown in Figures 6N and O, which I suggest the authors consider analyzing in further detail. Most significantly:

      (6i) The authors nicely show that most AZs have a mix of both Cac IIA and IIB isoforms. Using simple intensity analysis, can the authors say anything about whether there is a consistent stoichiometric ratio of IIA vs IIB at single AZs? It is difficult to extract actual numbers of IIA vs IIB at individual AZs without having both isoforms labeled mEOS4b, but as a rough estimate can the authors say whether the immunofluorescence intensity of IIA:IIB is similar across each AZ? Or is there broad heterogeneity, with some AZs having low vs high ratios of each isoform (as the authors suggest across proximal to distal NMJ AZs)?

      We agree and have conducted experiments and analyses to provide these data. We measured the cac puncta fluorescence intensities for heterozygous cac<sup>sfGFP</sup>/cac, cacIIIA<sup>sfGFP</sup>/cacI-IIB, and cacI-IIB<sup>sfGFP</sup>/cacI-IIA animals. We preferred this strategy, because intensity was always measured from cac puncta with the same GFP tag. Next, we normalized all values to the intensities obtained in active zones from heterozygous cac<sup>sfGFP</sup>/cac controls and then plotted the intensities of I-IIA versus I-IIB containing active zones side by side. Across junctions and animals, we find a consistent ratio 2:1 in the relative intensities of I-IIB and I-IIA, thus indicating on average roughly twice as many I-IIB as compared to I-IIA channels across active zones. This is consistent with the counts in our STED analysis (see Fig. 5F). These new data are shown in the new figure panel 7J and referred to on page 13, lines 10-16 in the revised text.

      (6ii) Intensity analysis of Cac IIA vs IIB after PHP: Previous studies have shown Cac abundance increases at NMJ AZs after PHP. Can the authors determine whether both Cac IIA vs IIB isoforms increase after PHP or whether just one isoform is targeted for this enhancement?

      We already show that PHP is not possible in the absence of I-IIB channels (see figure 7). However, we agree that it is an interesting question to test whether I-IIA channel are added in the presence of I-IIB channels during PHP, but we consider this a detail beyond the scope of this study.

      Minor points:

      (1) Including line numbers in the manuscript would help to make reviewing easier.

      We agree and now provide line numbers.

      (2) Several typos (abstract "The By contrast", etc).

      We carefully double checked for typos.

      (3) Throughout the manuscript, the authors refer to Cac alleles and channels as "Cav2", which is unconventional in the field. Unless there is a compelling reason to deviate, I suggest the authors stick to referring to "Cac" (i.e. cacdIS4B, etc) rather than Cav2. The authors make clear in the introduction that Cac is the sole fly Cav2 channel, so there shouldn't be a need to constantly reinforce that cac=Cav2.

      We agree and have changed all fly Ca<sub>v</sub>2 reference to cac.

      (4) In some figures/text the authors use "PSC" to refer to "postsynaptic current", while in others (i.e. Figure 6) they switch to the more conventional terms of mEPSC or EPSC. I suggest the authors stick to a common convention (mEPSC and EPSC).

      We have changed PSC to EPSC throughout.

      Reviewer #3 (Recommendations For The Authors):

      (1) The abstract could focus more on the results at the expense of the background.

      We agree and have deleted the second introductory background sentence and added information on PPRs and depression during low frequency stimulation.

      (2) What does "strict" active zone localization refer to? Could they please define the term strict?

      Strict active zone localization means that cac puncta are detected in active zones but no cac label above background is found anywhere else throughout the presynaptic terminal, now defined on page 6, lines 27-29.

      (3) Single boutons/zoomed versions of the confocal images shown in Figures 2A-C, 2H, and 3A-C would be very helpful.

      We have provided these panels as suggested (see above and revised figures 2-4). Figure 3 is now figure 4.

      (4) The authors cite Ghelani et al. (2023) for increased cac levels during homeostatic plasticity. I recommend citing earlier work making similar observations (Gratz et al., 2019; DOI: 10.1523/JNEUROSCI.3068-18.2019), and linking them to increased presynaptic calcium influx (Müller & Davis, 2012; DOI: 10.1016/j.cub.2012.04.018).

      We agree and have added Gratz et al. 2019 and Davis and Müller 2012 to the results section on page 12, lines 17/18 and lines 21-23, in the discussion on page 17, lines 29-33.

      (5) The data shown in Figure 3 does not directly support the conclusion of altered release probability in dI-IIB. I therefore suggest changing the legend's title.

      We have reworded to “Excisions at the I-II exon do not affect active zone cacophony localization but can alter cacsfGFP label intensity in active zones and PSC amplitude” as this is reflecting the data shown in the figure panels more directly.

      (6) It would be helpful to specify "adult flight muscle" in Figure 2J.

      We agree that it is helpful to specify in the figure (now revised figure 3C) that the voltage clamp recordings of somatodendritic calcium current were conducted in adult flight motoneurons and have revised the headline of figure panel 3C and the legend accordingly. Please note, these are not muscle cells but central neurons.

      (7) Do dIS4B/Cav2null MNs indeed show an inward or outward current at -90 to -70 mV/-40 and -50 mV, or is this an analysis artifact?

      No, this is due to baseline fluctuations as typical for voltage clamp in central neurons with more than 6000 µm dendritic length and more than 4000 dendritic branches.

      (8) Loss of several presynaptic proteins, including Brp (Kittel et al., 2006), and RBP (Liu et al., 2011), induce changes in GluR field size (without apparent changes in miniature amplitude). The statement regarding the Cav2 isoform and possible effects on GluR number (p. 8) should be revised accordingly.

      We understand and have done two things. First, we measured the intensity of GluRIIA immunolabel in ΔI-IIA, ΔI-IIB, and controls and found no differences. Second, we reworded the statement. It now reads on page 9, lines 1-6: “It seems unlikely that presynaptic cac channel isoform type affects glutamate receptor types or numbers, because the amplitude of spontaneous miniature postsynaptic currents (mEPSCs, Fig. 4K) and the labeling intensity of postsynaptic GluRIIA receptors are not significantly different between controls, I-IIA, and I-IIB junctions (see suppl. Fig. 2, p = 0.48, ordinary one-way ANOVA, mean and SD intensity values are 61.0 ± 6.9 (control), 55.8 ± 8.5 (∆I-IIA), 61.1 ± 17.3 (∆I-IIB)). However, we cannot exclude altered GluRIIB numbers and have not quantified GluR receptor field sizes.”

      (9) The statement relating miniature frequency to RRP size is unclear (p. 8). Is there any evidence for a correlation between miniature frequency to RRP size? Could the authors please clarify?

      We agree that this statement requires caution. Although there is some published evidence for a correlation of RRP size and mini frequency (Neuron, 2009 61(3):412-24. doi: 10.1016/j.neuron.2008.12.029 and Journal of Neuroscience 44 (18) e1253232024; doi: 10.1523/JNEUROSCI.1253-23.2024), which we now refer to on page 9, it is not clear whether this is true for all synapses and how linear such a relationship may be. Therefore, we have revised the text on page 9, lines 6-9. It now reads: “Similarly, the frequency of miniature postsynaptic currents (mEPSCs) remains unaltered. Since mEPSCs frequency has been related to RRP size at some synapses (Pan et al., 2009; Ralowicz et al., 2024) this indicates unaltered RRP size upon I-IIB excision, but we have not directly measured RRP size.”

      (10) Please define the "strict top view" of synapses (p. 8).

      Top view is what this reviewer referred to as “planar view” in the public review points 6 and 7. In our responses to these public review points we now also define “strict top view”, see page 9, lines 17-19.

      (11) Two papers are cited regarding a linear relationship between calcium channel number and release probability (p. 15). Many more papers could be cited to demonstrate a supralinear relationship (e.g., Dodge & Rahaminoff, 1967; Weyhersmüller et al., 2011 doi: 10.1523/JNEUROSCI.6698-10.2011). The data of the present study were collected at an extracellular calcium concentration of 0.5 mM, whereas Meideiros et al. (2023) used 1.5 mM. The relationship between calcium and release is supra-linear around 0.5 mM extracellular calcium (Weyhersmüller et al. 2011). This should be discussed/the statements be revised. Also, the reference to Meideiros et al. (2023) should be included in the reference list.

      We have now updated the Medeiros reference (updated version of that paper appeared in eLife in 2024) in the text and reference list. We agree that the relationship of the calcium concentration and P<sub>r</sub> can also be non-linear and refer to this on page 16, lines 26-32, but the point we want to make is to relate defined changes in calcium channel number (not calcium influx) as assessed by multiple methods (CLSM intensity measures and sptPALM channel counting) to release probability. We now also clearly state that we measured at 0.5 mM external calcium (page 16, lines 27/28) whereas Medeiros et al. 2024 measured at 1.5 mM calcium (page 16, lines 31/32).

      (12) Figure 6: Quantal content does not have any units - please remove "n vesicles".

      We have revised this figure in response to reviewer 2 (comment 5) and quantal content is now expressed as percent baseline, thus without units (see revised figure 7).

      (13) Figure 6C should be auto-scaled from zero.

      This has been fixed by revising that figure in response to reviewer 2 (comment 5)

      (14) The data supporting the statement on impaired motor behavior and reduced vitality of adult IS4A should be either shown, or the statement should be removed (p. 13). Any hypotheses as to why IS4A is important for behavior and or viability?

      As suggested, we have removed that statement.

      (15) They do not provide any data supporting the statement that changes in PSC decay kinetics "counteract" the increase in PSC amplitude (p. 14). The sentence should be changed accordingly.

      We agree and have down toned. It now reads on page 16, lines 7-9: “During repetitive firing, the median increase of PSC amplitude by ~10 % is potentially counteracted by the significant decrease in PSC half amplitude width by ~25 %...”.

      (16) How do they explain the net locomotion speed increase in dI    -IIA larvae? Although the overall charge transfer is not affected during the stimulus protocols used, could the accelerated PSC decay affect PSP summation (I would actually expect a decrease in summation/slower speed)? Independent of the voltage-clamp data, is muscle input resistance changed in dI-IIA mutants?

      Muscle input resistance is not altered in I-II mutants. We refer to potential causes of the locomotion effects of I-IIA excision in the discussion. On page 16, lines 12 to 21 it reads: “there is no difference in charge transfer from the motoneuron axon terminal to the postsynaptic muscle cell between ∆I-IIA and control. Surprisingly, crawling is significantly affected by the removal of I-IIA, in that the animals show a significantly increased mean crawling speed but no significant change in the number of stops. Given that the presynaptic function at the NMJ is not strongly altered upon I-IIA excision, and that I-IIA likely mediates also Ca<sub>v</sub>2 functions outside presynaptic AZs (see above) and in other neuron types than motoneurons, and that the muscle calcium current is mediated by Ca<sub>v</sub>1>/i> and Ca<sub>v</sub>3, the effects of I-IIA excision of increasing crawling speed is unlikely caused by altered pre- or postsynaptic function at the NMJ. We judge it more likely that excision of I-IIA has multiple effects on sensory and pre-motor processing, but identification of these functions is beyond the scope of this study.”

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript reports the results of an observational study conducted in Dar es Salaam, Tanzania, investigating potential associations between genetic variation in M. tuberculosis and human host vs. disease severity. The headline finding is that no such associations were found, either for host / bacillary genetics as main effects or for interactions between them.

      Strengths:

      Strengths of the study include its large size and rigorous approaches to classification of genetic diversity for host and bacillus.

      Weaknesses:

      (1) There are some limitations of the disease severity read-outs employed: X-ray scores and Xpert cycle thresholds from sputum analysis can only take account of pulmonary disease. CXR is an insensitive approach to assessing 'lung damage', especially when converted to a binary measure. What was the basis for selection of Ralph score of 71 to dichotomise patients? If outcome measures were analysed as continuous variables, would this have been more sensitive in capturing associations of interest?

      (2) There is quite a lot of missing data, especially for TB scores - could this have introduced bias? This issue should be mentioned in the discussion.

      (3) The analysis adjusted for age, sex, HIV status, age, smoking and cough duration - but not for socio-economic status. This will likely be a major determinant of disease severity. Was adjustment made for previous TB (i.e. new vs repeat episode) and drug-sensitivity of the isolate? Cough duration will effectively be a correlate/consequence of more severe disease - thus likely highly collinear with disease severity read-outs - not a true confounder. How does removal of this variable from the model affect results? Data on socioeconomic status should be added to models, or if not possible then lack of such data should be noted as a limitation.

      (4) Recruitment at hospitals may have led to selection bias due to exclusion of less severe, community cases. The authors already acknowledge this limitation in the Discussion however.

      (5) Introduction: References refer to disease susceptibility, but the authors should also consider the influences of host/pathogen genetics on host response - both in vitro (PMIDs 11237411, 15322056) and in vivo (PMID 23853590). The last of these studies encompassed a broader range of ethnic variation than the current study, and showed associations between host ancestry and immune response - null results from the current study may reflect the relative genetic homogeneity of the population studied.

    1. Reviewer #3 (Public review):

      Summary:

      The study demonstrates the effectiveness of a cost-effective closed-loop feedback system for modulating brain activity and behavior in head-fixed mice. Authors have tested real-time closed-loop feedback system in head-fixed mice two types of graded feedback: 1) Closed-loop neurofeedback (CLNF), where feedback is derived from neuronal activity (calcium imaging), and 2) Closed-loop movement feedback (CLMF), where feedback is based on observed body movement. It is a python based opensource system, and authors call it CLoPy. The authors also claim to provide all software, hardware schematics, and protocols to adapt it to various experimental scenarios. This system is capable and can be adapted for a wide use case scenario.

      Authors have shown that their system can control both positive (water drop) and negative reinforcement (buzzer-vibrator). This study also shows that using the close loop system mice have shown better performance, learnt arbitrary task and can adapt to change in the rule as well. By integrating real-time feedback based on cortical GCaMP imaging and behavior tracking authors have provided strong evidence that such closed-loop systems can be instrumental in exploring the dynamic interplay between brain activity and behavior.

      Strengths:

      Simplicity of feedback systems designed. Simplicity of implementation and potential adoption.

      Weaknesses:

      Long latencies, due to slow Ca2+ dynamics and slow imaging (15 FPS), may limit the application of the system.

      Major comments:

      (1) Page 5 paragraph 1: "We tested our CLNF system on Raspberry Pi for its compactness, general-purpose input/output (GPIO) programmability, and wide community support, while the CLMF system was tested on an Nvidia Jetson GPU device." Can these programs and hardware be integrated with windows-based system and a microcontroller (Arduino/ Tency). As for the broad adaptability that's what a lot of labs would already have (please comment/discuss)?

      (2) Hardware Constraints: The reliance on Raspberry Pi and Nvidia Jetson (is expensive) for real-time processing could introduce latency issues (~63 ms for CLNF and ~67 ms for CLMF). This latency might limit precision for faster or more complex behaviors, which authors should discuss in the discussion section.

      (3) Neurofeedback Specificity: The task focuses on mesoscale imaging and ignores finer spatiotemporal details. Sub-second events might be significant in more nuanced behaviors. Can this be discussed in the discussion section?

      (4) The activity over 6s is being averaged to determine if the threshold is being crossed before the reward is delivered. This is a rather long duration of time during which the mice may be exhibiting stereotyped behaviors that may result in the changes in DFF that are being observed. It would be interesting for the authors to compare (if data is available) the behavior of the mice in trials where they successfully crossed the threshold for reward delivery and in those trials where the threshold was not breached. How is this different from spontaneous behavior and behaviors exhibited when they are performing the test with CLNF?

    1. Reviewer #2 (Public review):

      Approach

      In this study, Yogesh et al. aimed at characterizing hemodynamic occlusion in two photon imaging, where its effects on signal fluctuations are underappreciated compared to that in wide field imaging and fiber photometry. The authors used activity-independent GFP fluorescence, GCaMP and GRAB sensors for various neuromodulators in two-photon and widefield imaging during a visuomotor context to evaluate the extent of hemodynamic occlusion in V1 and ACC. They found that the GFP responses were comparable in amplitude to smaller GCaMP responses, though exhibiting context-, cortical region-, and depth-specific effects. After quantifying blood vessel diameter change and surrounding GFP responses, they argued that GFP responses were highly correlated with changes in local blood vessel size. Furthermore, when imaging with GRAB sensors for different neuromodulators, they found that sensors with lower dynamic ranges such as GRAB-DA1m, GRAB-5HT1.0, and GRAB-NE1m exhibited responses most likely masked by the hemodynamic occlusion, while a sensor with larger SNR, GRAB-ACh3.0, showed much more distinguishable responses from blood vessel change.

      Strengths

      This work is of broad interest to two photon imaging users and GRAB developers and users. It thoroughly quantifies the hemodynamic driven GFP response and compares it to previously published GCaMP data in a similar context, and illustrates the contribution of hemodynamic occlusion to GFP and GRAB responses by characterizing the local blood vessel diameter and fluorescence change. These findings provide important considerations for the imaging community and a sobering look at the utility of these sensors for cortical imaging.

      Importantly, they draw clear distinctions between the temporal dynamics and amplitude of hemodynamic artifacts across cortical regions and layers. Moreover, they show context dependent (Dark versus during visual stimuli) effects on locomotion and optogenetic light-triggered hemodynamic signals.

      Most of the first generation neuromodulator GRAB sensors showed relatively small responses, comparable to blood vessel changes in two photon imaging, which emphasizes a need for improved the dynamic range and response magnitude for future sensors and encourages the sensor users to consider removing hemodynamic artifacts when analyzing GRAB imaging data.

      Weaknesses

      The largest weakness of the paper is that, while they convincingly quantify hemodynamic artifacts across a range of conditions, they do not quantify any methods of correcting for them. The utility of the paper could have been greatly enhanced had they tested hemodynamic correction methods (e.g. from Ocana-Santero et al., 2024) and applied them to their datasets. This would serve both to verify their findings-proving that hemodynamic correction removes the hemodynamic signal-and to act as a guide to the field for how to address the problem they highlight.

      The paper attributes the source of 'hemodynamic occlusion' primarily to blood vessel dilation, but leaves unanswered how much may be due to shifts in blood oxygenation. Figure 4 directly addresses the question of how much of the signal can be attributed to occlusion by measuring the blood vessel dilation, but notably fails to reproduce any of the positive transients associated with locomotion in Figure 2. Thus, an investigation into or at least a discussion of what other factors (movement? Hb oxygenation?) may drive these distinct signals would be helpful.

      Along these lines, the authors carefully quantified the correlation between local blood vessel diameter and GFP response (or neuropil fluorescence vs blood vessel fluorescence with GRAB sensors). To what extent does this effect depend on proximity to the vessels? Do GFP/ GRAB responses decorrelate from blood vessel activity in neurons further from vessels (refer to Figure 5A and B in Neyhart et al., Cell Reports 2024)?

      Raw traces are shown in Figure 2 but we are never presented with the unaveraged data for locomotion of stimulus presentation times, which limits the reader's ability to independently assess variability in the data. Inclusion of heatmaps comparing event aligned GFP to GCaMP6f may be of value to the reader.

      More detailed analysis of differences between the kinds of dynamics observed in GFP vs GCaMP6f expressing neurons could aid in identifying artifacts in otherwise clean data. The example neurons in Figure 2A hint at this as each display unique waveforms and the question of whether certain properties of their dynamics can reveal the hemodynamic rather than indicator driven nature of the signal is left open. Eg. do the decay rate and rise times differ significantly from GCaMP6f signals?

      The authors suggest that signal to noise ratio of an indicator likely affects the ability to separate hemodynamic response from the underlying fluorescence signal. Does the degree of background fluorescence affect the size of the artifact? If there was variation in background and overall expression level in the data this could potentially be used to answer this question. Could lower (or higher!) expression levels increase the effects of hemodynamic occlusion?<br /> The choice of the phrase 'hemodynamic occlusion' may cause some confusion as the authors address both positive and negative responses in the GFP expressing neurons, and there may be additional contributions from changes in blood oxygenation state.

      The choice of ACC as the frontal region provides a substantial contrast in location, brain movement, and vascular architecture as compared to V1. As the authors note, ACC is close to the superior sagittal sinus and thus is the region where the largest vascular effects are likely to occur. The reader is left to wonder how much of the ROI may or may not have included vasculature in the ACC vs V1 recordings as the only images of the recording sites provided are for V1. We are left unable to conclude whether the differences observed between these regions are due to the presence of visible vasculature, capillary blood flow or differences in neurovasculature coupling between regions. A less medial portion of M2 may have been a more appropriate comparison. At least, inclusion of more example imaging fields for ACC in the supplementary figures would be of value.

      In Figure 3, How do the proportions of responsive GFP neurons compare to GCaMP6f neurons?

      How is variance explained calculated in Figure 4? Is this from a linear model and R^2 value? Is this variance estimate for separate predictors by using single variable models? The methods should describe the construction of the model including the design matrix and how the model was fit and if and how cross validation was run.

      Cortical depth is coarsely defined as L2/3 or L5, without numerical ranges in depth from pia.

      Overall Assessment:

      This paper is an important contribution to our understanding of how hemodynamic artifacts may corrupt GRAB and calcium imaging, even in two-photon imaging modes. Certain useful control experiments, such as intrinsic optical imaging in the same paradigms, were not reported, nor were any hemodynamic correction methods investigated. Thus, this limits both mechanistic conclusions and the overall utility with respect to immediate applications by end users. Nevertheless, the paper is of significant importance to anyone conducting two-photon or widefield imaging with calcium and GRAB sensors and deserves the attention of the broader neuroscience and in-vivo imaging community.

    1. Reviewer #1 (Public review):

      Summary:

      In this manuscript, Kondo et al. developed a method to suppress somatic action potentials while recording spine calcium signals using two-photon imaging in the L2/3 visual cortex in response to visual stimuli. The authors identified different patterns of dendritic spine activation by visual stimuli and analyzed how the different patterns of spine responses may contribute to somatic visual responses. Their analysis results suggest that spines on dendrites with a clustered arrangement can potentially generate sharply tuned output.

      Strengths:

      This is an interesting study addressing a standing question of how previously reported pepper-and-salt-like distributed sensory inputs on individual spines may give rise to somatic sensory selectivity. The method of somatic inhibition to prevent bAPs appears new and effective. The measurements of spine activity are carefully done. The finding that a small number of spines located in the same branch with similar tuning properties would predict the somatic tuning is consistent with local dendritic nonlinear integration mechanisms.

      Weaknesses:

      (1) The demonstration of the effectiveness of soma-specific inhibition is inadequate. Figure 1 only provides a single example trace showing the inhibition of somatic visual responses. The authors should provide statistical analysis over grouped data. For the effect of soma-specific inhibition on spine activity, the authors provided mostly negative results, lacking effects on spine responses for both soma inhibition and bAP subtraction. This is confusing. One possible explanation is that bAPs normally have little influence on spine activity. However, this would conflict with the known fact that somatic APs can easily invade spines in L2/3 neurons (e.g., Chen et al., Nature 2011). Another possibility is that under the current experimental conditions, somatic APs were rarely evoked by the visual stimulus. The authors should also rule out the possibility that the spines they imaged are from different neurons than the ones with somatic inhibition. The authors may consider identifying those cases where somatic APs have a significant impact on spine activity or spine tuning and show how bAP inhibition influences the dendritic and spine responses.

      (2) Figure 4 shows that the proportion of spines with a preferred orientation similar to the soma (ΔOri {less than or equal to} 30{degree sign}) was 60%, which is surprisingly high. It is intriguing that without somatic AP invasion, there could be such a high degree of similarity between spine activity and somatic tuning. What is the ratio without soma inhibition? One could reason that with bAP invasion, there should be even more spines showing visual responses similar to those of the soma. Moreover, with such a high proportion of spines showing similar sensory tuning to the soma, it is inevitable that many branches contain more spines with similar tuning as the soma, exhibiting an apparent branch-specific clustering. While such apparent clustering may well predict somatic tuning, it primarily reflects a correlational relationship rather than a causal synaptic integration mechanism.

      (3) There has been extensive work studying how the integration of spine activity or sub-branch activity gives rise to somatic output. The proposed main contribution of this study is to use an improved method to inhibit somatic activity in order to more confidently measure spine-specific activity and examine the integration mechanisms. However, the results showed that the measured spine-specific activity under soma inhibition was not significantly different from that measured under normal conditions (see point 1). It becomes unclear how this new method contributes to obtaining new insights into the synaptic integration mechanism.

      (4) Figure 6 shows how the tuning similarity between spines depends on the distance between them. It is unclear what new information was acquired regarding the functional clustering of spines. This result can be largely explained by the overall higher proportion of similarly tuned spines (60%) compared to the soma's preferred orientations. Moreover, the authors did not demonstrate how such clustering may contribute to nonlinear synaptic integration.

      (5) The results shown in Figure 7 can again be largely explained by the static property of a higher proportion of spines tuned similarly to the soma. These results do not reveal any active dendritic integration mechanisms.

    2. Reviewer #2 (Public review):

      Summary:

      The paper from Kondo et al., addresses how the functional organization of synaptic inputs in 2/3 pyramidal neurons contributes to their output firing. Expressing GCamp6s to monitor calcium activity and the bi-stable inhibitory opsin SwiChR++ to inhibit the somatic activity of the imaged neurons, the authors were able to image up to ~5700 spines in basal dendrites from 6 neurons. Mapping the functional responses of such a large number of dendritic spines and relating it to the output firing of the parent neuron is a remarkable feat. The authors studied the clustering of similarly tuned spines within individual dendrites and found that while some dendrites are similarly tuned to the same orientation of the parent neuron, other dendrites exhibit tuning to other orientations and moreover a significant proportion of dendrites exhibit no tuning. Modelling work suggests that the clustering of spines in a small proportion of dendrites should suffice to give rise to the tuning of the parent cell.

      Strengths:

      (1) Removal of the potential confound of somatic firing via optogenetic inhibition is convincing and validates a useful tool for the neuroscientific community. As discussed by the authors the tool would be most valuable for the study of excitatory inputs in inhibitory neurons.

      (2) The comparison of optogenetic inhibition of somatic responses and isolation of spine-specific signals using the removal of backpropagating action potential by robust regression is an important control and constitutes an important affirmation of previously published work.

      (3) The large dataset size provides enough statistical power to test for clustering of similarly tuned spines in basal dendrites.

      (4) The study provides a useful replication of previously published results.

      (5) Modelling work in the study shows that as in the ferret visual cortex (Wilson et al., 2016), a combination of dendritic nonlinearity and spike thresholding contribute to the sharpness of orientation tuning in the mouse visual cortex.

      Weaknesses:

      (1) One of the main conclusions of the study, the classification of dendrites according to the presence or absence of visual responses, lacks quantification.

      (2) Some of the statistics employed in combination with shuffling controls are not adequate.

      (3) All the neurons imaged are very highly tuned (with a very high orientation selectivity index (OSI)). The performance of the models is evaluated by the correlation coefficient between the predicted and the measured somatic tuning curve. The high OSI of the neurons reduces the sensitivity of the evaluation of the models, as it results in extremely high or low correlation coefficients (Figure 8a). It would be important to recapitulate the results from the model for neurons with lower OSI, given that not all L2/3 neurons are so highly tuned.

      (4) It is very hard to understand how the modelling results relate to the experimental data, as the definitions of what constitutes a clustered dendrite in the model or in the experimental data are unclear.

    1. Reviewer #3 (Public review):

      Summary:

      The manuscript by Chang and colleagues provides compelling evidence that glia-derived Shriveled (Shv) modulates activity-dependent synaptic plasticity at the Drosophila neuromuscular junction (NMJ). This mechanism differs from the previously reported function of neuronally released Shv, which activates integrin signaling. They further show that this requirement of Shv is acute and that glial Shv supports synaptic plasticity by modulating neuronal Shv release and the ambient glutamate levels. However, there are a number of conceptual and technical issues that need to be addressed.

      Major comments

      (1) From the images provided for Fig 2B +RU486, the bouton size appears to be bigger in shv RNAi + stimulation, especially judging from the outline of GluR clusters.<br /> (2) The shv result needs to be replicated with a separate RNAi.<br /> (3) The phenotype of shv mutant resembles that of neuronal shv RNAi - no increased GluR baseline. Any insights why that is the case?<br /> (4) In Fig 3B, SPG shv RNAi has elevated GluR baseline, while PG shv RNAi has a lower baseline. In both cases, there is no activity induced GluR increase. What could explain the different phenotypes?<br /> (5) In Fig 4C, the rescue of PTP is only partial. Does that suggest neuronal shv is also needed to fully rescue the deficit of PTP in shv mutants?<br /> (6) The observation in Fig 5D is interesting. While there is a reduction in Shv release from glia after stimulation, it is unclear what the mechanism could be. Is there a change in glial shv transcription, translation or the releasing machinery? It will be helpful to look at the full shv pool vs the released ones.<br /> (7) In Fig 5E, what will happen after stimulation? Will the elevated glial Shv after neuronal shv RNAi be retained in the glia?<br /> (8) It would be interesting to see if the localization of shv differs based on if it is released by neuron or glia, which might be able to explain the difference in GluR baseline. For example, by using glia-Gal4>UAS-shv-HA and neuronal-QF>QUAS-shv-FLAG. It seems important to determine if they mix together after release? It is unclear if the two shv pools are processed differently.<br /> (9) Alternatively, do neurons and glia express and release different Shv isoforms, which would bind different receptors?<br /> (10) It is claimed that Sup Fig 2 shows no observable change in gross glial morphology, further bolstering support that glial Shv does not activate integrin. This seems quite an overinterpretation. There is only one image for each condition without quantification. It is hard to judge if glia, which is labeled by GFP (presumably by UAS-eGFP?), is altered or not.<br /> (11) The hypothesis that glutamate regulates GluR level as a homeostatic mechanism makes sense. What is the explanation of the increased bouton size in the control after glutamate application in Fig 6?<br /> (12) What could be a mechanism that prevents elevated glial released Shv to activate integrin signaling after neuronal shv RNAi, as seen in Fig 5E?<br /> (13) Any speculation on how the released Shv pool is sensed?

    1. Reviewer #2 (Public review):

      Summary:

      This study investigates in mice neural mechanisms generating sighs, which are periodic large-amplitude breaths occurring during normal breathing that subserve physiological pulmonary functions and are associated with emotional states such as relief, stress, and anxiety. Sighs are generated by a structure called the preBötzinger complex (preBötC) in the medulla oblongata that generates various forms of inspiratory activity including sighs. The authors have previously described a circuit involving neurons producing bombesin-related peptides Neuromedin B (NMB) and gastrin releasing peptide (GRP) that project to preBötC neurons expressing receptors for NMB (NMBRs) and GRP (GRPRs) and that activation of these preBötC neurons via these peptide receptors generates sighs. In this study the authors further investigated mechanisms of sigh generation by applying optogenetic and chemogenetic strategies to selectively activate the subpopulations of preBötC neurons expressing NMBRs and/or GRPRs, and a separate subpopulation of neurons expressing somatostatin (SST) but not NMBRs and GRPRs. The authors present convincing evidence that sigh-like inspirations can be evoked by photostimulation of the preBötC neurons expressing NMBRs or GRPRs. Photostimulation of SST neurons can independently evoke sighs, and chemogenetic inhibition of these neurons can abolish sighs. The results presented support the authors' conclusion that the preBötC neurons expressing NMBRs or GRPRs produce sighs via pathways to downstream SST neurons. Thus, these studies have identified some of the preBötC cellular elements likely involved in generating sighs.

      Strengths:

      (1) This study employs an effective combination of electrophysiological, transgenic, optogenetic, chemogenetic, pharmacological, and neuron activity imaging techniques to investigate sigh generation by distinct subpopulations of preBötC neurons in mice.

      (2) The authors extend previous studies indicating that there is a peptidergic circuit consisting of NMB and GRP expressing neurons that project from the parafacial (pF) nucleus region to the preBötC and provides sufficient input to generate sighs, since photoactivation of either pF NMB or GRP neurons evoke ectopic sighs in this study.

      (3) Solid evidence is presented that sighs can be evoked by direct photostimulation of preBötC neurons expressing NMBRs and/or GRPRs, and also a separate subpopulation of neurons expressing somatostatin (SST) but not NMBRs and GRPRs.

      (4) The mRNA-expression data presented from in situ hybridization indicates that most preBötC neurons expressing NMBR, GRPR (or both) are glutamatergic and excitatory.

      (5) Measurements in slices in vitro indicate that only the NMBR expressing neurons are normally rhythmically active during normal inspiratory activity and endogenous sigh activity.

      (6) Evidence is presented that activation of preBötC NMBRs and/or GRPRs is not necessary for sigh production, suggesting that sighs are not the unique product of the preBötC bombesin-peptide signaling pathway.

      (7) The novel conclusion is presented that the preBötC neurons expressing NMBRs and/or GRPRs produce sighs via the separate downstream population of preBötC SST neurons, which the authors demonstrate can independently generate sighs, whereas chemogenetic inhibition of preBötC SST neurons selectively abolishes sighs generated by activating NMBRs and GRPRs.

      Weaknesses:

      (1) While these studies have identified subpopulations of preBötC neurons capable of episodically evoking sigh-like inspiratory activity, mechanisms producing the normal slow sigh rhythm were not investigated and remain unknown.

      (2) The authors have addressed some of the reviewers' main technical concerns and issues relating to interpretation of the results in their rebuttal letter, but have minimally revised the manuscript. Accordingly, there remain important technical and interpretation issues requiring resolution in the revised manuscript.

      Comments on revisions:

      The authors have clarified in their rebuttal letter the rationale for utilizing two different photostimulation paradigms but have not incorporated any of this explanation in Methods, which would be helpful for readers.

    2. Reviewer #3 (Public review):

      Summary:

      This manuscript by Cui et al., studies the mechanisms for the generation of sighing, an essential breathing pattern. This is an important and interesting topic, as sighing maintains normal pulmonary function and is associated with various emotional conditions. However, the mechanisms of its generation remain not fully understood. The authors employed different approaches, including optogenetics, chemogenetics, intersectional genetic approach, and slice electrophysiology and calcium imaging, to address the question, and found several neuronal populations are sufficient to induce sighing when activated. Furthermore, ectopic sighs can be triggered without the involvement of neuromedin B (NMB) or gastrin releasing peptide (GRP) or their receptors in the preBötzinger Complex (preBötC) region of the brainstem. Additionally, activating SST neurons in the preBötC region induces sighing, even when other receptors are blocked. Based on these results, the authors concluded that increased excitability in certain neurons (NMBR or GRPR neurons) activates pathways leading to sigh generation, with SST neurons serving as a downstream component in converting regular breaths into sighs.

      Strengths:

      The authors employed a combination of various sophisticated approaches, including optogenetics, chemogenetics, intersectional genetic approach, and slice electrophysiology and calcium imaging, to precisely pinpoint the mechanism responsible for sigh generation. They utilized multiple genetically modified mouse lines, enabling them to selectively manipulate and observe specific neuronal populations involved in sighing.<br /> Using genetics and calcium imaging, the authors record the neuronal activity of NMBR and GRPR neurons, respectively, and identified their difference in activity pattern. Furthermore, by applying the intersectional approach, the authors were able to genetically target and manipulate several distinct neuronal populations, such as NMBR+, GRPR- neurons and GRPR+, NMBR- neurons, and conducted a detailed characterization of their functions in influencing sighing.

      Weaknesses:

      (1) The authors employed two conditions for optogenetic activation: long pulse photostimulation (LPP) and short pulse photostimulation (SPP), with durations ranging from 4-10s for LPP and 100-500 ms for SPP. These could generate huge variability in the experiments. The rationale behind the selection of these conditions in each experiment remains unclear in the manuscript. Additionally, it is not explained why these specific durations were chosen. Furthermore, the interpretation for the varied responses observed under these conditions is not provided. Clarification on the rationale and interpretation of these experimental parameters would enhance the understanding of the results. The description of the experiment conditions should be consistent throughout the manuscript.

      (2) Regarding the fiber optics, my understanding is that they are placed outside of the brainstem from the ventral side. Given the locations of the pF and preBötC neurons, could the differences in responses be attributed to the varying distances of each population from the ventral surface? In fact, in Figure 8, NMBR is illustrated as being closer to the ventral surface. Does it represent the actual location of these neurons?

      (3) The results of recording on NMBR neurons in Figure 4 were compelling. However, I'm curious why the recording of GRPR neurons and their response to the neuropeptide were not presented or examined. Additionally, considering the known cross-reaction between peptides and their receptors, it might be worthwhile to investigate how GRP modulates NMBR neurons and how NMB modulates GRPR neurons.

      (4) The authors found that activation of several preBötC populations, including NMBR, GRPR, and SST neurons, despite pharmacological inhibition of NMBR and GRPR, can still induce sighing, and concluded that "activation of preBötC NMBRs and/or GRPRs is not necessary for sigh production". I disagree with this conclusion. Even when the receptors are silenced, artificial (optogenetic or chemogenetic) activation could still activate the same downstream pathways. This cannot be used as evidence to claim that the receptors are not required for sighing in vivo, because it is possible that the receptors are still necessary for the activation of these neurons under natural conditions. For instance, while diaphragm activation induces breathing, it does not negate the crucial role of the nervous system in regulating this process in physiological conditions.

      (5) The authors noted varied responses upon activating specific subpopulations of the preBötC neurons, namely NMBR, GRPR, and SST neurons. Could these differences be attributed to variations in viral labeling efficiency among different mouse genetic lines? Are there discrepancies in the number of labeled neurons across the lines? Additionally, the authors did not thoroughly characterize the specificities of AAV targeting in their Cre and Flp lines. It's uncertain whether the AAV-labeled neurons are strictly restricted to the designated population without notable leakage into other populations. This is particularly crucial for the experiments manipulating SST neurons. If there's substantial labeling of NMBR or GRPR neurons, it could undermine the conclusions drawn. Further examination of the precision and selectivity of the labeling techniques is necessary to ensure the accurate interpretation of the experimental findings.

      (6) The authors have addressed some of the reviewers' concerns in the revision; however, many important issues remain unaddressed.

    3. Author response:

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

      (1) Reviewer 3: Moreover, the conclusion that preBötC NMBR and GRPR activations are unnecessary for sighing is not fully supported by the current experimental design. While the study shows that sighing can still be induced despite pharmacological inhibition of NMBR and GRPR, this does not conclusively prove that these receptors are not required under natural conditions. 

      We concluded that “NMBR and GRPR receptors are not necessary for sigh generation”. We acknowledge that under normal conditions these receptors almost certainly play a role; in fact, microinjection of saporin conjugated to bombesin, which presumably ablates NMBR<sup>+</sup> and GRPR<sup>+</sup> preBötC neurons, completely eliminated endogenous sighing activity in awake mice (Li et al., Nature, 2015). However, that study did not establish that the receptors per se are essential in this context, since the protocol ablated not just the receptors but also the preBötC neurons that happened to express these receptors. Here, we show that we could evoke sighs AFTER complete pharmacological blockade of NMBRs and GRPRs. Also, we show that sighs can be elicited by stimulation of a distinct subpopulation of preBötC neurons expressing the peptide somatostatin (SST<sup>+</sup>). These results demonstrate that sighs can be evoked in absence of activation of NMBRs and/or GRPRs, leading to the conclusion that NMBRs and/or GRPRs are not required for sighs but rather contribute to periodic sigh generation under normal conditions.

      (2) Reviewer 1: To make such a novel (and quite surprising) claim requires many more studies and the conclusion is dependent on how the authors have defined a sigh. Moreover, some data within the paper conflicts with this idea.

      Our definition of sighs was carefully chosen so that it applied across different experimental conditions, including in vitro slices, anesthetized or awake in vivo. We defined sighs as transient changes in minute ventilation on a time scale slower than eupneic breathing period, to avoid classifying breathing after vagotomy or under isoflurane anesthesia as “all-sigh breathing”. This is why induction of persistent large amplitude breaths (such as in Figures 5-6) were not counted as sighs.

      (3) Reviewer 2: Several key technical aspects of the study require further clarification to aid in interpreting the experimental results, including issues relating to the validation of the transgenic mouse lines and virally transduced expressions of proteins utilized for optogenetic and chemogenetic experiments, as well as justifying the optogenetic photostimulation paradigms used to evoke sighs.

      The rationale for using SPP and LPP stems from our published observations of the effects of optogenetic stimulation of various preBötC neuronal subpopulations. Thus, SPP and LPP evoke the same responses in GlyT2 (Sherman et al., 2015) and Dbx1 (Cui et al., 2016) neurons, while for other subpopulations, e.g., SST (Cui et al., 2015), the effects of SPP are markedly different from LPP. Hence, in this study we examined both. As effects of SPP and LPP of SST neurons were examined previously (Cui et al., 2016), these protocols were not repeated except for evoking sighs after blockade of NMBR/GRPRs. SPP of pF NMB or GRP did not evoke any respiratory responses and hence were not presented in any figures (see Results, section “Activation of Nmb- or Grp-expressing pF neurons induces sighs”).

      (4) Reviewer 3: however, the rationale and experimental details require further explanation, and their impacts on the conclusion require clarification. For instance, how and why the variability in optogenetic activation conditions could impact the experimental outcomes. 

      Refractory periods reported here for pF NMB, pF GRP, preBötC NMBR and preBötC GRPR were all obtained using the same intensity LPP. We acknowledge the possibility, even the likelihood that higher intensity LPP would shorten refractory periods. In line with this, we observed that ectopic sighs were evoked earlier during the LPP as the sigh phase progressed. As described in RESULTS, such effects were observed for pF NMB, pF GRP, preBötC NMBR and preBötC GRPR only and not for preBötC SST, which might suggest that timing of intrinsically generated sighs depends on the NMB-GRP signaling pathway, yet sigh production depends on the SST pathway.

    1. Author response:

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

      Reviewer #1 (Public Review):

      This is an elegant didactic exposition showing how dendritic plateau potentials can enable neurons to perform reliable 'binary' computations in the face of realistic spike time jitter in cortical networks. The authors make many good arguments, and the general concept underlying the paper is sound. A strength is their systematic progression from biophiysical to simplified models of single neurons, and their parallel investigation of spiking and binary neural networks, with training happening in the binary neural network.

      Reviewer #2 (Public Review):

      Summary:

      Artificial intelligence (AI) could be useful in some applications and could help humankind. Some forms of AI work on the platform of artificial neural networks (ANN). ANNs are inspired by real brains and real neurons. Therefore understanding the repertoire and logic of real neurons could potentially improve AANs. Cell bodies of real neurons, and axons of real neurons, fire nerve impulses (nerve impulses are very brief ~2 ms, and very tall ~100 mV). Dendrites, which comprise ~80% of the total neuronal membrane (80% of the total neuronal apparatus) typically generate smaller (~50 mV amplitude) but much longer (~100 ms duration) electrical transients, called glutamate-mediated dendritic plateau potentials. The authors have built artificial neurons capable of generating such dendritic plateau potentials, and through computer simulations the authors concluded that long-lasting dendritic signals

      (plateau potentials) reduce negative impact of temporal jitter occurring in real brain, or in

      AANs. The authors showed that in AANs equipped with neurons whose dendrites are capable of generating local dendritic plateau potentials, the sparse, yet reliable spiking computations may not require precisely synchronized inputs. That means, the real world can impose notable fluctuations in the network activity and yet neurons could still recognize and pair the related network events. In the AANs equipped with dendritic plateaus, the computations are very robust even when inputs are only partially synchronized. In summary, dendritic plateau potentials endow neurons with ability to hold information longer and connect two events which did not happen at the same moment of time. Dendritic plateaus circumvent the negative impact, which the short membrane time constants arduously inflict on the action potential generation (in both real neurons and model neurons). Interestingly, one of the indirect conclusions of the current study is that neurons equipped with dendritic plateau potentials may reduce the total number of cells (nodes, units) required to perform robust computations.

      Strengths:

      The majority of published studies are descriptive in nature. Researchers report what they see or measure. A smaller number of studies embark on a more difficult task, which is to explain the logic and rationale of a particular natural design. The current study falls into that second category. The authors first recognize that conduction delays and noise make asynchrony unavoidable in communication between circuits in the real brain. This poses a fundamental problem for the integration of related inputs in real (noisy) world. Neurons with short membrane time constants can only integrate coincident inputs that arrive simultaneously within 2-3 ms of one another. Then the authors considered the role for dendritic plateau potentials. Glutamate-mediated depolarization events within individual dendritic branches, can remedy the situation by widening the integration time window of neurons. In summary, the authors recognized that one important feature of neurons, their dendrites, are built-in to solve the major problems of rapid signal processing: [1] temporal jitter, [2] variation, [3] stochasticity, and [4] reliability of computation. In one word, the dendritic plateau potentials have evolved in the central nervous systems to make rapid CNS computations robust.

      Weaknesses:

      The authors made some unsupported statements, which should either be deleted, or thoroughly defended in the manuscript. But first of all, the authors failed to bring this study to the readers who are not experts in computational modeling or Artificial Neural Networks. Critical terms (syntax) and ideas have not been explained. For example: [1] binary feature space? [2] 13 dimensions binary vectors? [3] the binary network could still cope with the loss of information due to the binarization of the continuous coordinates? [4] accurate summation?

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      However, I have a number of specific points, listed below, that should be addressed. Most of them are relatively minor, but the authors should especially address point 10, which is a major point, by redoing the simulations affected by the erroneous value of the time constant, and by remaking the relevant figures based on the new simulations.

      Specific comments:

      (1) 7f "This feature is conspicuous because it is an order of magnitude longer than unitary synaptic inputs and axonal spikes.": — It is an order of magnitude longer than AMPA receptor-mediated synaptic currents (EPSCs), but more similar in time course to synaptic potentials (EPSPs) whose decay is governed by the passive membrane time constant (about 10 to 20 ms in pyramidal neurons in vivo) and which determines the lifetime of the 'memory' of the neuron for synaptic inputs under conditions of subthreshold, non-spiking dendritic integration. The quoted sentence should be rewritten accordingly.

      Following this suggestion, we have rewritten the sentence (l. 7) to: "This timescale is conspicuous, being many times longer than the fastest signalling processes in the nervous systems, including Excitatory Post-Synaptic Potentials (EPSPs) and axonal spikes."

      (2) 16ff "This is especially relevant to integration of inputs during high conductance states that are prevalent in-vivo. In these states the effective time constant of the neuronal membrane is extremely short and varies substantially depending on synaptic drive [13, 34, 49].": — The time-averaged synaptic conductance driven by sensory input in vivo is much less high than implied by this statement (e.g. see Fig. 4 of Haider et al. 2013 https://www.nature.com/articles/nature11665 ), and reduces the passive membrane time constant only by a small percentage. The energy cost of a high prevalence of highconductance states and extremely short membrane time constants would also exceed the energy budget of the brain (ref. 4). I would therefore suggest dropping this sentence.

      We have clarified this sentence thanks to the reviewer's suggestion. We meant that the instantaneous, rather than the time-averaged, conductance can be very big. To clarify this we have rewritten this section (l. 15): This is especially relevant to integration of inputs during high conductance states that are prevalent in vivo, where a typical neuron receives significant synaptic drive. In these states, the effective membrane time constant can be extremely short, and varies substantially depending on synaptic input.

      (3) l. 17f "As a consequence, computations that rely on passive summation of multiple inputs place punishing constraints on spike timing precision.": — Again, the passive membrane time constant is on the order of 10 ms and I would tone down this statement accordingly, removing the word 'punishing' for example.

      Following the suggestion, we have rewritten the sentence to (l. 18): "As a consequence, computations that rely on passive summation of multiple inputs would place strong constraints on spike timing precision."

      (4) l. 18ff "Dendritic action potentials, by contrast, have a consistently long duration that is ensured by the kinetic properties of voltage gated ion channels and NMDA receptors [54, 47, 10, 3]. These properties are largely determined by the amino acid sequence of receptor and channel proteins that are specifically expressed in dendrites [45, 44, 40]. This suggests dendritic properties are specifically tuned to produce localised, suprathreshold events that outlive rapid membrane fluctuations.": — Yes, but see also Attwell & Gibb 2005 ( https://www.nature.com/articles/nrn1784 ), especially the last two of their key points. The slow NMDA receptor decay kinetics (and therefore their high affinity for binding glutamate) may also be the consequence of a design goal to set the temporal coherence window for NMDA receptor-mediated synaptic plasticity such as STDP to be on the order of tens of milliseconds, somewhat longer than the membrane time constant.

      The reviewer is correct; other functions (e.g. synaptic plasticity) are also part of the dendrite's repertoire. To acknowledge this, we added a section (l. 34) where we mention that our idea does not conflict with, for example, synaptic plasticity.

      (5) l. 32f "Numerous studies point out that nonlinear summation in dendrites can make neurons computationally equivalent to entire networks of simplified point models, or 'units' in a traditional neural network [9, 21, 38, 40, 45, 48, 50, 51].": — See also Beniaguev et al. 2021 ( https://www.cell.com/neuron/pdf/S0896-6273(21)00501-8.pdf ), which also speaks to the next sentence.

      We thank the reviewer for the suggestion; the citation has been added.

      (6) Fig. 2E and F: the top of panel F corresponds to the top of panel E, but the bottom ofpanel F does not correspond to the bottom of panel E - it corresponds to a dendritic neuron with passive dendrites, not a point neuron. Panel E should be changed to reflect this fact.

      We have followed the suggestion to change the figure.

      (7) l. 49f "Despite these dendritic spikes being initiated at different times, they still sum in the soma, leading to a sodium spike there (Figure 2E).": — You probably mean Fig. 2D, and instead of a sodium spike (which could be misunderstood as local and dendritic) you triggered a sodium action potential. Likewise, Fig. 2B (right) shows the timescale of sodium action potentials at the soma (cf. l. 46).

      The error in the referencing to the figure has been corrected. The phrasing has also been changed to "a sodium action potential" (l. 56), following the reviewer's suggestion.

      (8) Please check the scale bars in Fig. 2D. Do they also apply to panel F below? If yes thatshould be stated.

      The scale bars are indeed the same; I have repeated them in the figure to avoid any confusion.

      (9) l. 68 "This time constant is consistent with the high-conductance state of pyramidalneurons in the cortex [6]":

      You do not need to invoke a high-conductance state to justify this time constant, which is indeed typical for the membrane time constant of pyramidal neurons in vivo.

      On a related note, Fig. 3B and its legend seem to assume that tau = 1 ms, and calls that one EPSP duration in the legend. An EPSC may have a decay time constant of 1 ms, but an EPSP will have a decay time constant of about 10 ms, similar to the membrane time constant. Fig. 3B (and therefore also the rest of Figure 3) seems to have been constructed with a value of tau that is too small by a factor of 10, and this should be corrected by remaking the figure. If tau = 1 ms was used also in Figure 4 then this figure also needs to be remade.

      Section 3.3 and Table 1 also use tau = 1 ms. This is unrealistic and needs to be changed an appropriate value of tau = 10 ms is given by the authors themselves in line 67. The incorrect value of tau in Table 1 causes other entries of the Table to be terribly wrong; a leak conductance of 1 µS would imply an input resistance of the neuron of 1 MOhm, but somatic input resistances of pyramidal neurons in vivo are on the order of 20 to 50 MOhm. The total capacitance of 1 nF is slightly too large, and should be adjusted to yield a membrane time constant of 10 ms given an appropriate leak conductance leading to an input resistance of about 20 to 50 MOhm. These are key numbers to get right for both Figures 3 and 4, especially if you want to be able to say "We have been careful to respect the essence of basic physiological facts while trying to build an abstraction of how elementary spiking computations might occur." (l. 215f).

      We thank the reviewer for catching this. We had actually already used tau = 10 ms, but had not yet updated the paper. Moreover, the somatic input resistance was indeed off. To rectify this, we have used the values: $Cm = 0.5 nF$, $\taum = 10 ms$, $Rm = 20 M \Ohm$, $gl = 0.05 \mu S$. Figure 3 was remade using these values, and Table 1 updated accordingly.

      (10) l. 158ff "The assumption that each neuron connects to one dendrite of an upstream neuron is actually grounded in physiology, although it may appear like a strong assumption at first glance: related inputs arrive at local clusters of spines synchronously [60].": — You probably mean "each neuron connects to one dendrite of a downstream neuron." And I would add "But see Beniaguev et al. 2022 https://www.biorxiv.org/content/10.1101/2022.01.28.478132v2.abstract " - your restrictive arrangement of inputs is probably not really needed, especially if postsynaptic neurons have more dendrites.

      The suggested wording was correct, and has been now incorporated (l. 166). I have also added the suggested citation.

      (11) I note that the plateaus in Fig. 4D are much shorter than those in Fig. 2D and F, but thisis a good thing: The experimental and simulation results in Fig. 2 are based on ref. 18, which used microiontophoresis of glutamate, leading to much slower glutamate concentration time courses at the dendritic NMDA receptors than synaptic release of glutamate would. The time courses of plateaus in Fig. 4 are much more in line with the NMDA plateau durations shown in ref. 21, especially their Figure 2B. These faster NMDA plateaus (or NMDA spikes as they are called in ref. 21) are based on synaptic release of glutamate in vivo, and on the faster NMDA receptor kinetics at physiological temperature compared to the old models with room temperature kinetics used in ref. 18.

      Here are two additional references that the authors might find interesting:

      Fisek et al. 2023 https://www.nature.com/articles/s41586-023-06007-6 Dudai et al. 2022 https://www.jneurosci.org/content/42/7/1184.full

      We thank the reviewer for the suggested references. The first has been added to the references in the introduction, on l. 28. The second has been added on l. 78.

      Reviewer #2 (Recommendations For The Authors):

      (1) In Fig. 3A, we observed some animal pictures, which were never explained in the figurecaption, or text of the manuscript. These pictures were probably explained at the lab meeting, so it is unnecessary to waste effort on these pictures in the manuscript draft.

      We agree with the reviewer; the figures have been removed.

      (2) Figure 1 has not been referenced anywhere in the manuscript text!

      Indeed, this had to be corrected, figure is now references on l. 9.

      (3) Line 45. "[18] triggered two NMDA spikes by glutamate uncaging at the indicated (red,blue) sites". [18] triggered one NMDA spike while recording at three locations simultaneously (two locations in dendrite and one location in the soma).

      The reviewer is correct here. The sentence has now been rephrased to "(ref.) triggered an NMDA spike by glutamate microiontophoresis while recording at the soma and the indicated (red, blue) sites in the dendrite." (l. 49)

      (4) Fig. 2B. The two labels, "Dendrite 2" and "Dendrite 1" incorrectly suggest that two traceswere recorded in two dendrites. These two traces were recorded in the same dendrite.

      We agree with the reviewer; labels have now been changed to "Dendrite site".

      (5) Line 45. "[18] triggered two NMDA spikes by glutamate uncaging at the indicated (red,blue) sites". - - One NMDA spike by "glutamate microiontophoresis".

      This is correct, the phrasing on (l. 50) has been changed accordingly.

      (6) Line 47. "... simulated glutamate releases 50 ms apart in the three dendritic sites indicatedin Figure 2C, thereby triggering three NMDA spikes at those sites. Despite these dendritic spikes being initiated at different times, they still sum in the soma, leading to a sodium spike there (Figure 2E)". A similar experiment has been performed in real cortical neurons (KD Oikonomu et al., 2012, PMID: 22934081), and could potentially be cited here. Briefly, Oikonomou et al. generated two dendritic plateau potentials in two dendritic branches and monitored the summation of these dendritic plateau potentials in the cell body.

      The reference has been added, on l. 54

      (7) Line 63. "We compared the behaviour of our simplified model with that of the full, detailedbiophysical model". Which detailed biophysical model? Please cite here the detailed biophysical model that you used for comparisons with your simplified abstract model.

      The reference to the paper has been added.

      (8) Line 65. "Figure 2F shows that spikes arriving at different times are summed in anintegrate and hold-like manner". In Fig. 2F, I am unable to see that spikes arriving at different times are summed in an integrate and hold-like manner. Which feature of Fig. 2F refers to the "hold-like manner"? Please explain in the manuscript.

      To clarify we have added "Figure 2F, top" in the text (l. 71).

      (9) Figure 2 caption. "(F) The voltage traces of the abstract model, with and without plateaus.Because of the extended time duration of the plateau potentials, they sum accurately to produce a somatic spike". I am unable to understand what an "accurate summation" in Fig. 2 is. Could the authors provide an illustrative example of a situation in which the neuronal potentials DID NOT sum accurately?

      To address this confusion, we have changed the wording to "...they are summed to reach threshold."

      (10) Line 75. "This is an important issue we intend to return to in future work". The authorspersonal plans should not be in the text discussing scientific results.

      We believe it is entirely reasonable to discuss scientific plans that are part of ongoing work, and this is quite common throughout the literature. Nonetheless, we have now reworded this to "This is an important issue for future work." (l. 81)

      (11) In Fig. 4F, the full-line and the dashed-line have not been identified! The readers are leftto guess.

      This has now been addressed both with text inserts in the figure, and specification in the figure caption.

      (12) Line 247. "would amount to scaling up the number of cells in a network to performcomputations that could, in principle, be performed by more robust single units". Did the authors mean to say: "would amount to scaling up the number of cells in a network to perform computations that could, in principle, be performed by a fewer (but more robust) single units"?

      We have replaced the sentence with the reviewer's suggestion (l. 259)

      (13) In the abstract, the authors repeat sentences: "the timescale of dendritic potentialsallows reliable integration of asynchronous inputs" and "nonlinear dendritic plateau potentials allow reliable integration of asynchronous spikes". Besides this being a bad writing style, the authors cannot decide if inputs to the model neuron are asynchronous, or spiking of the model neuron is asynchronous. Are these asynchronous spikes occurring in the neuron experiencing dendritic plateau potentials, or these asynchronous spikes occur in the neuronal network? This confusion of terms and ideas must be removed from the abstract.

      We have rewritten the second sentence, which now reads: "Using this model, we show that long-lived, nonlinear dendritic plateau potentials allow neurons to spike reliably when confronted with asynchronous input spikes."

      (14) In the abstract, the authors claim: "Our results provide empirically testable hypothesesfor the role of dendritic action potentials in cortical function". With great anticipation, I read throughout the manuscript, but I was unable to find one single experimental design that could support the authors' bald statement. In the text of the manuscript, the authors must carefully reveal the precise experimental outline that would test their specific hypothesis, or delete the untrue statement.

      We respectfully challenge the rather critical tone of the reviewer. The central hypothesis that plateaus enable robust summation, and that circuit level computations rely on this is an experimentally testable hypothesis. The precise experimental design of how to test such a hypothesis is always best left to an experimentalist to determine, as there are many possible means of doing this and each will depend on the preparation and methodology at hand. At the same time, we understand that there is an increasing culture of expecting explicit "testable hypotheses" spelled out to the reader. To satisfy this expectation while avoiding overly prescriptive ideas for how future work should proceed, we have now added more explicit descriptions of possible experimental tests in l. 231 and onwards.

      (15) Fig. 2F was submitted for review without a time scale, while at the same time the authorsheavily discuss specific numerical values for time intervals. Namely, the authors instruct readers to pay attention to a 10 ms time constant and 2-3 ms input decay (Fig. 2F), but they do not show the time scale in Fig. 2F.

      "We compared this to a situation where all inputs arrive at a soma with standard LIF dynamics and a 10 ms membrane time constant. This time constant is consistent with the high-conductance state of pyramidal neurons in the cortex [6]: Inputs decay after 2-3 ms, and fail to sum to spike threshold (Figure 2F, lower)".

      The time (and voltage) bars have now been added to Fig. 2F.

      (16) Line 75. "In the scope of what remains here we want to ask if integrate-and-hold isminimally feasible". This reviewer is unable to understand the meaning of the syntaxes "integrate-and-hold" and "minimally feasible" in the context of dendritic integration. This reviewer is worried that the majority of the journal readers would feel exactly the same. To alleviate this problem, the authors should explain both terms right here, in line 77.

      Integrate-and-hold is defined on line 57 (to be exact we write: "We refer to this behavior as “Leaky Integrate-and-Hold” (LIH)." To be more clear we could reuse the acronym LIH here, to emphasise that we are referring to the same thing. By 'minimally feasible' we mean biologically plausible given assumptions that are not strong. Can use another term, e.g. "biologically plausible under lenient assumptions".

      To address this point, we have rephrased the sentence as "In the scope of what remains here we want to ask if Leaky-Integrate-and-Hold (LIH) can easily and plausibly facilitate network computations with spikes." (l. 81), repeating the LIH definition.

      (17) Line 91. "Spikes arriving even slightly out of sync with each other introduces noise in themembrane potential ..." Introduce.

      The sentence has been fixed using the reviewer's correction.

      (18) The caption of the Fig. 3B was submitted for review without any explanation of thenormalization procedure used. Also, in the caption of the same figure, one cannot find explanation of the light-gray area surrounding the black curves. Also, the readers are left to wonder how the results of a simulation could possibly be greater than 1 in some simulation trials.

      We have added a description of the normalization and the shaded area to the caption of Fig. 3B.

      (19) Line 117. "We assumed that inputs to a network arrive at the dendrites within some timewindow, and their combined depolarisations are either sufficient to either elicit a dendritic spike or not, as shown in Figure 3". We could potentially compact the current text by deleting one instance of "either".

      We agree this is better writing; one of the occurrences of 'either' has been removed.

      (20) Line 127. "where incoming connections can be represented with a 1 (a spike arrives)..."Did you mean "a presynaptic spike arrives"?

      The sentence has been rewritten following the suggestion.

      (21) Line 134. "with each unit only having ..." Dendrite can be a unit. Dendritic spine can be aunit. Did you mean "with each unit (i.e. neuron) having ..."

      We have incorporated the suggestion.

      (22) Fig. 4, Caption. "Each point is a 2D input vector x, the colors represent the differentclasses". An effort was made to introduce 3 different classes. But then, no mention of "classes" thereafter. The three input vectors, mentioned in Line 170, perhaps represent the remnants of the class concept mentioned in the previous paragraph.

      We have now rewritten the sentence beginning with "These three input vectors ..." on l. 182 to emphasise that a correct answer means a correct classification.

      (23) Line 152. "The 2D input points were first projected onto a binary feature space, to obtain13D binary vectors". Did you mean to say: "The 2D input points (three classes, Fig. A) were first projected onto a binary feature space, to obtain three binary vectors; each 13D binary vector responding to a specific class".

      The sentence has been replaced with the reviewer's suggestion (l. 159).

      (24) Line 163. "Because our focus is to account for how transient signals can be summed andthresholded robustly, we are assuming that inhibition is implicitly accounted for in the lumped abstraction". Could you please explain your two ideas: [1] "inhibition is implicitly accounted for" and [2] "lumped abstraction", because this reviewer did not get neither idea.

      The reviewer is right that as it stood, the sentence was unclear. To clarify the point we have decided to expand upon that sentence and break it out as an individual paragraph (starting l. 171).

    1. Author response:

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

      Reviewer 1:

      This study is one in a series of excellent papers by the Forstmann group focusing on the ability of fMRI to reliably detect activity in small subcortical nuclei - in this case, specifically those purportedly involved in the hyper- and indirect inhibitory basal ganglia pathways. I have been very fond of this work for a long time, beginning with the demonstration of De Hollander, Forstmann et al. (HBM 2017) of the fact that 3T fMRI imaging (as well as many 7T imaging sequences) do not afford sufficient signal to noise ratio to reliably image these small subcortical nuclei. This work has done a lot to reshape my view of seminal past studies of subcortical activity during inhibitory control, including some that have several thousand citations.

      Comments on revised version:

      This is my second review of this article, now entitled "Multi-study fMRI outlooks on subcortical BOLD responses in the stop-signal paradigm" by Isherwood and colleagues.

      The authors have been very responsive to the initial round of reviews.

      I still think it would be helpful to see a combined investigation of the available 7T data, just to really drive the point home that even with the best parameters and a multi-study sample size, fMRI cannot detect any increases in BOLD activity on successful stop compared to go trials. However, I agree with the authors that these "sub samples still lack the temporal resolution seemingly required for looking at the processes in the SST." As such, I don't have any more feedback.

      We thank the reviewer for their positive feedback, and for their thorough and constructive comments on our initial submission. 

      Reviewer 2:

      This work aggregates data across 5 openly available stopping studies (3 at 7 tesla and 2 at 3 tesla) to evaluate activity patterns across the common contrasts of Failed Stop (FS) > Go, FS > stop success (SS), and SS > Go. Previous work has implicated a set of regions that tend to be positively active in one or more of these contrasts, including the bilateral inferior frontal gyrus, preSMA, and multiple basal ganglia structures. However, the authors argue that upon closer examination, many previous papers have not found subcortical structures to be more active on SS than FS trials, bringing into question whether they play an essential role in (successful) inhibition. In order to evaluate this with more data and power, the authors aggregate across five datasets and find many areas that are *more* active for FS than SS, including bilateral preSMA, GPE, thalamus, and VTA. They argue that this brings into question the role of these areas in inhibition, based upon the assumption that areas involved in inhibition should be more active on successful stop than failed stop trials, not the opposite as they observed.

      Since the initial submission, the authors have improved their theoretical synthesis and changed their SSRT calculation method to the more appropriate integration method with replacement for go omissions. They have also done a better job of explaining how these fMRI results situate within the broader response inhibition literature including work using other neuroscience methods.

      They have also included a new Bayes Factor analysis. In the process of evaluating this new analysis, I recognized the following comments that I believe justify additional analyses and discussion:

      First, if I understand the author's pipeline, for the ROI analyses it is not appropriate to run FSL's FILM method on the data that were generated by repeating the same time series across all voxels of an ROI. FSL's FILM uses neighboring voxels in parts of the estimation to stabilize temporal correlation and variance estimates and was intended and evaluated for use on voxelwise data. Instead, I believe it would be more appropriate to average the level 1 contrast estimates over the voxels of each ROI to serve as the dependent variables in the ROI analysis.

      We agree with the reviewer’s assertion that this approach could create estimation problems. However, in this instance, we turned off the spatial smoothing procedure that FSL’s FILM normally uses for estimating the amount of autocorrelation – thus, the autocorrelation was estimated based on each voxel’s timeseries individually. We also confirmed that all voxels within each ROI had identical statistics, which would not be the case if the autocorrelation estimates differed per voxel. We have added the following text to the Methods section under fMRI analysis: ROI-wise:

      Note that the standard implementation of FSL FILM uses a spatial smoothing procedure prior to estimating temporal autocorrelations which is suitable for use only on voxelwise data (Woolrich et al., 2001). We therefore turned this spatial smoothing procedure off and instead estimated autocorrelation using each voxel’s individual timeseries.

      Second, for the group-level ROI analyses there seems to be inconsistencies when comparing the z-statistics (Figure 3) to the Bayes Factors (Figure 4) in that very similar zstatistics have very different Bayes Factors within the same contrast across different brain areas, which seemed surprising (e.g., a z of 6.64 has a BF of .858 while another with a z of 6.76 has a BF of 3.18). The authors do briefly discuss some instances in the frequentist and Bayesian results differ, but they do not ever explain by similar z-stats yield very different bayes factors for a given contrast across different brain areas. I believe a discussion of this would be useful.

      We thank the reviewer for their keen observation, and agree that this is indeed a strange inconsistency. Upon reviewing this issue, we came across an error in our analysis pipeline, which led to inconsistent scaling of the parameter estimates between datasets. We corrected this error, and included new tables (Figures 3, 4, and Supplementary Figure 5) which now show improved correspondence between the frequentist results from FSL and the Bayesian results.

      We have updated the text of the Results section accordingly. In this revision, we have also updated all BFs to be expressed in log<sub>10</sub> form, to ensure consistency for the reader. Updates to the manuscript are given below.

      Results: Behavioural Analyses:

      Consistent with the assumptions of the standard horse-race model (Logan & Cowan, 1984), the median failed stop RT is significantly faster within all datasets than the median go RT (Aron_3T: p < .001, BF<sub>log10</sub> = 2.77; Poldrack_3T: p < .001, BF<sub>log10</sub> = 23.49; deHollander_7T: p < .001, B BF<sub>log10</sub> = 8.88; Isherwood_7T: p < .001, BF<sub>log10</sub> = 2.95; Miletic_7T: p = .0019, BF<sub>log10</sub> = 1.35). Mean SSRTs were calculated using the integration method and are all within normal range across the datasets.

      Results: ROI-wise GLMS: 

      To further statistically compare the functional results between datasets, we then fit a set of GLMs using the canonical HRF with a temporal derivative to the timeseries extracted from each ROI. Below we show the results of the group-level ROI analyses over all datasets using z-scores (Fig. 3) and log-transformed Bayes Factors (BF; Fig. 4). Note that these values were time-locked to the onset of the go signal. See Supplementary Figure 5 for analyses where the FS and SS trials were time-locked to the onset of the stop signal. To account for multiple comparisons, threshold values were set using the FDR method for the frequentist analyses. 

      For the FS > GO contrast, the frequentist analysis found significant positive z-scores in all regions bar left and right M1, and the left GPi. The right M1 showed a significant negative z-score; left M1 and GPi showed no significant effect in this contrast. The BFs showed moderate or greater evidence for the alternative hypothesis in bilateral IFG, preSMA, caudate, STN, Tha, and VTA, and right GPe. Bilateral M1 and left GPi showed moderate evidence for the null. Evidence for other ROIs was anecdotal (see Fig 4). 

      For the FS > SS contrast, we found significant positive z-scores in in all regions except the left GPi. The BFs showed moderate or greater evidence for right IFG, right GPi, and bilateral M1, preSMA, Tha, and VTA, and moderate evidence for the null in left GPi. Evidence for other ROIs was anecdotal (see Fig 4). 

      For the SS > GO contrast we found a significant positive z-scores in bilateral IFG, right Tha, and right VTA, and significant negative z-scores in bilateral M1, left GPe, right GPi, and bilateral putamen. The BFs showed moderate or greater evidence for the alternative hypothesis in bilateral M1 and right IFG, and moderate or greater evidence for the null in left preSMA, bilateral caudate, bilateral GPe, left GPi, bilateral putamen, and bilateral SN. Evidence for other ROIs was anecdotal (see Fig 4). 

      Although the frequentist and Bayesian analyses are mostly in line with one another, there were also some differences, particularly in the contrasts with FS. In the FS > GO contrast, the interpretation of the GPi, GPe, putamen, and SN differ. The frequentist models suggests significantly increased activation for these regions (except left GPi) in FS trials. In the Bayesian model, this evidence was found to be anecdotal in the SN and right GPi, and moderate in the right GPe, while finding anecdotal or moderate evidence for the null hypothesis in the left GPe, left GPi, and putamen. For the FS > SS contrast, the frequentist analysis showed significant activation in all regions except for the left GPi, whereas the Bayesian analysis found this evidence to be only anecdotal, or in favour of the null for a large number of regions (see Fig 4 for details).  

      Since the Bayes Factor analysis appears to be based on repeated measures ANOVA and the z-statistics are from Flame1+2, the BayesFactor analysis model does not pair with the frequentist analysis model very cleanly. To facilitate comparison, I would recommend that the same repeated measures ANOVA model should be used in both cases. My reading of the literature is that there is no need to be concerned about any benefits of using Flame being lost, since heteroscedasticity does not impact type I errors and will only potentially impact power.

      We agree with the reviewer that there are differences between the two analyses. The advantage of the z-statistics from FSL’s flame 1+2 is that these are based on a multi-level model in which measurement error in the first level (i.e., subject level) is taken into account in the group-level analysis. This is an advantage especially in the current paper since the datasets differ strongly in the degree of measurement error, both due to the differences in field strength and in the number of trials (and volumes). Although multilevel Bayesian approaches exist, none (except by use of custom code) allow for convolution with the HRF of a design matrix like typical MRI analyses. Thus, we extracted the participant-level parameter estimates (converted to percent signal change), and only estimated the dataset and group level parameters with the BayesFactor package. As such, this approach effectively ignores measurement error. However, despite these differences in the analyses, the general conclusions from the Bayesian and frequentist analyses are very aligned after we corrected for the error described above. The Bayesian results are more conservative, which can be explained by the unfiltered participantlevel measurement error increasing the uncertainty of the group-level parameter estimates. At worst, the BFs represent the lower bounds of the true effect, and are thus safe to interpret. 

      We have also included an additional figure (Supplementary Figure 7) that shows the correspondence between the BFs and the z scores. 

      Though frequentist statistics suggest that many basal ganglia structures are significantly more active in the FS > SS contrast (see 2nd row of Figure 3), the Bayesian analyses are much more equivocal, with no basal ganglia areas showing Log10BF > 1 (which would be indicative of strong evidence). The authors suggest that "the frequentist and Bayesian analyses are monst in line with one another", but in my view, this frequentist vs. Bayesian analysis for the FS > SS contrast seems to suggest substantially different conclusions. More specifically, the frequentist analyses suggest greater activity in FS than SS in most basal ganglia ROIs (all but 2), but the Bayesian analysis did not find *any* basal ganglia ROIs with strong evidence for the alternative hypothesis (or a difference), and several with more evidence for the null than the alternative hypothesis. This difference between the frequentist and Bayesian analyses seems to warrant discussion, but unless I overlooked it, the Bayesian analyses are not mentioned in the Discussion at all. In my view, the frequentist analyses are treated as the results, and the Bayesian analyses were largely ignored.

      The original manuscript only used frequentist statistics to assess the results, and then added Bayesian analyses later in response to a reviewer comment. We agree that the revised discussion did not consider the Bayesian results in enough detail, and have updated the manuscript throughout to more thoroughly incorporate the Bayesian analyses and improve overall readability. 

      In the Methods section, we have updated the fMRI analysis – general linear models (GLMs): ROIwise GLMs section to more thoroughly incorporate the Bayesian analyses as follows: 

      We compared the full model (H1) comprising trial type, dataset and subject as predictors to the null model (H0) comprising only the dataset and subject as predictor. Datasets and subjects were modeled as random factors in both cases. Since effect sizes in fMRI analyses are typically small, we set the scaling parameter on the effect size prior for fixed effects to 0.25, instead of the default of 0.5, which assumes medium effect sizes (note that the same qualitative conclusions would be reached with the default prior setting; Rouder et al., 2009). We divided the resultant BFs from the full model by the null model to provide evidence for or against a difference in beta weights for each trial type. To interpret the BFs, we used a modified version of Jeffreys’ scale (Andraszewicz et al., 2014; Jeffreys, 1939). To facilitate interpretation of the BFs, we converted them to the logarithmic scale. The approximate conversion between the interpretation of logarithmic BFs and standard interpretation on the adjusted Jeffreys’ scale can be found in Table 3.   

      The Bayesian results are also more incorporated into the Discussion as follows: 

      Evidence for the role of the basal ganglia in response inhibition comes from a multitude of studies citing significant activation of either the SN, STN or GPe during successful inhibition trials (Aron, 2007; Aron & Poldrack, 2006; Mallet et al., 2016; Nambu et al., 2002; Zhang & Iwaki, 2019). Here, we re-examined activation patterns in the subcortex across five different datasets, identifying differences in regional activation using both frequentist and Bayesian approaches. Broadly, the frequentist approach found significant differences between most ROIs in FS>GO and FS>SS contrasts, and limited differences in the SS>GO contrast. The Bayesian results were more conservative; while many of the ROIs showed moderate or strong evidence, some with small but significant z scores were considered only anecdotal by the Bayesian analysis. In our discussion, where the findings between analytical approaches differ, we focus mainly on the more conservative Bayesian analysis.

      Here, our multi-study results found limited evidence that the canonical inhibition pathways (the indirect and hyperdirect pathways) are recruited during successful response inhibition in the SST. We expected to find increased activation in the nodes of the indirect pathway (e.g., the preSMA, GPe, STN, SN, GPi, and thalamus) during successful stop compared to go or failed stop trials. We found strong evidence for activation pattern differences in the preSMA, thalamus, and right GPi between the two stop types (failed and successful), and limited evidence, or evidence in favour of the null hypothesis, in the other regions, such as the GPe, STN, and SN. However, we did find recruitment of subcortical nodes (VTA, thalamus, STN, and caudate), as well as preSMA and IFG activation during failed stop trials. We suggest that these results indicate that failing to inhibit one’s action is a larger driver of the utilisation of these nodes than action cancellation itself. 

      These results are in contention to many previous fMRI studies of the stop signal task as well as research using other measurement techniques such as local field potential recordings, direct subcortical stimulation, and animal studies, where activation of particularly the STN has consistently been observed (Alegre et al., 2013b; Aron & Poldrack, 2006; Benis et al., 2014; Fischer et al., 2017; Mancini et al., 2019; Wessel et al., 2016).

    1. 用拼图形式构建复杂的叙事结构

      《人生拼图版》(Life: A User's Manual,法文原名:La Vie mode d'emploi)是法国作家乔治·佩雷克(Georges Perec)的代表作,以其独特的结构和庞大的规模而闻名。它并非真正意义上的“拼图”,而是借用拼图的概念来构建一个极其复杂且精巧的叙事结构,展现了巴黎一座虚构公寓楼里的众多居民的生活片段。下面我将详细解释《人生拼图版》如何运用“拼图”形式构建其叙事结构:

      1. 公寓楼的网格结构:

      佩雷克将故事的舞台设定在一栋巴黎公寓楼的11号,这栋楼被想象成一个10x10的网格,共计100个“房间”(包括房间、楼梯间、电梯井等)。除了左下角的格子(被设定为空白)之外,其余99个格子分别对应着小说的一个章节。这种网格结构是小说的基本框架,它:

      • 提供了空间框架: 网格结构为故事提供了一个清晰的空间框架,将所有的人物和事件都安置在这个虚拟的空间中。
      • 限定了叙事顺序: 佩雷克使用了一种类似国际象棋中“骑士跳”的规则(即“马步”),来决定章节的叙述顺序。这种非线性的叙述方式打破了传统小说的时间顺序,使故事呈现出一种拼图般的感觉。

      2. “骑士跳”的叙事规则:

      “骑士跳”是《人生拼图版》最核心的结构性元素。它规定了章节之间的连接方式,使得故事的叙述并非按照线性顺序进行,而是以一种跳跃式的方式在公寓楼的各个“房间”之间穿梭。这种跳跃式的叙述方式:

      • 打乱了时间线: 读者并非按照时间顺序了解人物和事件,而是通过一个个独立的片段逐渐拼凑出故事的全貌。
      • 强调了空间的意义: 空间的布局和人物在空间中的位置关系变得尤为重要,因为章节之间的连接是由空间位置决定的。
      • 增加了阅读的难度和趣味性: 读者需要主动地将各个章节的信息联系起来,才能理解故事的整体脉络,这增加了阅读的难度,同时也带来了独特的阅读乐趣。

      3. 多重故事的交织:

      《人生拼图版》并非只有一个简单的故事,而是由众多独立的小故事交织而成。每个“房间”都讲述了一个或多个人物的故事,这些故事之间既有独立的完整性,又通过各种线索相互关联。这些故事:

      • 展现了生活的丰富性: 小说描绘了形形色色的人物,他们的职业、年龄、背景各不相同,展现了生活的丰富性和多样性。
      • 构建了复杂的社会网络: 人物之间的关系错综复杂,他们可能是邻居、亲戚、朋友或敌人,这些关系构成了一个庞大的社会网络。
      • 体现了偶然性和巧合: 人物之间的相遇和事件的发生往往是偶然的,体现了生活中充满了各种巧合。

      4. 细节的堆砌与整体的缺失:

      佩雷克在小说中堆砌了大量的细节,对每个“房间”的描述都极其详尽,包括房间的陈设、物品、气味等等。然而,由于叙述顺序的跳跃性和故事的碎片化,读者很难获得一个完整的故事线索。这种细节的堆砌与整体的缺失:

      • 营造了一种拼图的意象: 读者需要将这些碎片化的信息拼凑起来,才能逐渐理解故事的全貌,就像在拼一幅巨大的拼图。
      • 突出了生活的偶然性和不确定性: 生活本身就是由无数个碎片化的瞬间组成的,充满了偶然性和不确定性,小说通过这种方式恰好地表现了这一点。
      • 强调了阅读的主动性: 读者需要积极地参与到文本的构建中来,才能获得完整的阅读体验。

      总结:

      《人生拼图版》并非传统意义上的拼图游戏,它并没有一个预先设定的完整图像等待读者去拼凑。相反,它利用“拼图”的概念,通过网格结构、骑士跳的叙事规则、多重故事的交织以及细节的堆砌与整体的缺失等手法,构建了一个极其复杂且精巧的叙事结构。这种结构:

      • 挑战了传统的线性叙事模式: 它打破了时间顺序,强调了空间的意义,并突出了偶然性和巧合。
      • 强调了阅读的主动性: 它鼓励读者积极地参与到文本的构建中来,通过自己的理解和想象来完成故事的拼图。
      • 展现了生活的复杂性和多样性: 它通过众多人物的故事展现了生活的丰富性和多样性,以及人与人之间错综复杂的关系。

      《人生拼图版》是一部极具实验性和后现代主义特征的杰作,它以其独特的结构和庞大的规模而著称,对后世的文学创作产生了深远的影响。它不仅仅是一部小说,更是一次对文学形式的深刻探索。

    1. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      Chlamydia spp. has a biphasic developmental cycle consisting of an extracellular, infectious form called an elementary body (EB) and an intracellular, replicative form known as a reticular body (RB). The structural stability of EBs is maintained by extensive cross-linking of outer membrane proteins while the outer membrane proteins of RBs are in a reduced state. The overall redox state of EBs is more oxidized than RBs. The authors propose that the redox state may be a controlling factor in the developmental cycle. To test this, alkyl hydroperoxide reductase subunit C (ahpC) was overexpressed or knocked down to examine effects on developmental gene expression. KD of ahpC induced increased expression of EB-specific genes and accelerated EB production. Conversely, overexpression of ahpC delayed differentiation to EBs. The results suggest that chlamydial redox state may play a role in differentiation.

      Strengths:

      Uses modern genetic tools to explore the difficult area of temporal gene expression throughout the chlamydial developmental cycle.

      Weaknesses:

      The environmental signals triggering ahpC expression/activity are not determined.

      Thank you for your comments. Our data and those of others have shown that ahpC is expressed as a mid-developmental cycle gene (i.e., when RBs predominate in the population). This is true of most chlamydial genes, and the factors that determine developmental expression are not fully understood. As we noted in the Discussion, Chlamydia lacks AhpF/D orthologs, so it is not clear how AhpC activity is regulated. Related to determining environmental signals that trigger activity of AhpC, then this is a non-trivial issue in an obligate intracellular bacterium. Our assumption is that AhpC is constitutively active and that the increasing metabolic production of ROS eventually overcomes the innate (and stochastic) activity of AhpC to handle it, hence the threshold hypothesis. Importantly, the stochasticity is consistent with what we know about secondary differentiation in Chlamydia. We have tried to clarify these points in the Discussion.

      Reviewer #2 (Public Review):

      The factors that influence the differentiation of EBs and RBs during Chlamydial development are not clearly understood. A previous study had shown a redox oscillation during the Chlamydial developmental cycle. Based on this observation, the authors hypothesize that the bacterial redox state may play a role in regulating the differentiation in Chlamydia. To test their hypothesis, they make knock-down and overexpression strains of the major ROS regulator, ahpC. They show that the knock-down of ahpC leads to a significant increase in ROS levels leading to an increase in the production of elementary bodies and overexpression leads to a decrease in EB production likely caused by a decrease in oxidation. From their observations, they present an interesting model wherein an increase in oxidation favors the production of EBs.

      Major concern:

      In the absence of proper redox potential measurements, it is not clear if what they observe is a general oxidative stress response, especially when the knock-down of ahpC leads to a significant increase in ROS levels. Direct redox potential measurement in the ahpC overexpression and knock-down cells is required to support the model. This can be done using the roGFP-based measurements mentioned in the Wang et al. 2014 study cited by the authors.

      Thank you for this suggestion. It is definitely something that we are looking to implement. However, our current vectors don’t allow for roGFP2 in combination with inducible expression of a gene of interest. We will need to completely redesign our vectors, and, in Chlamydia, the validation of such new vectors together with ahpC OE or KD may literally take a year or longer.

      In lieu of this, we used the CellRox redox reactive dye to image live chlamydiae during normal growth or ahpC KD. During ahpC KD, these organisms are clearly much brighter than the control, uninduced conditions. These data are included as new Figure 5 to go along with the data we previously reported from the plate reader measurements. These data also clearly indicate that the readings we observed are from Chlamydia and not the host cell.

      As far as a general oxidative stress response, Chlamydia lacks any transcriptional regulators akin to OxyR. The response we’ve measured, earlier expression of genes associated with secondary differentiation, would be an odd stress response not consistent with a focused program to respond to oxidative stress. We added new RNAseq data further showing this effect of a global earlier increase in late gene transcripts.

      Reviewer #3 (Public Review):

      Summary:

      The study reports clearly on the role of the AhpC protein as an antioxidant factor in Chlamydia trachomatis and speculates on the role of AhpC as an indirect regulator of developmental transcription induced by redox stress in this differentiating obligate intracellular bacterium.

      Strengths:

      The question posed and the concluding model about redox-dependent differentiation in chlamydia is interesting and highly relevant. This work fits with other propositions in which redox changes have been reported during bacterial developmental cycles, potentially as triggers, but have not been cited (examples PMID: 2865432, PMID: 32090198, PMID: 26063575). Here, AhpC over-expression is shown to protect Chlamydia towards redox stress imposed by H2O2, CHP, TBHP, and PN, while CRISPRi-mediated depletion of AhpC curbed intracellular replication and resulted in increased ROS levels and sensitivity to oxidizing agents. Importantly, the addition of ROS scavengers mitigated the growth defect caused by AhpC depletion. These results clearly establish the role of AhpC affects the redox state and growth in Ct (with the complicated KO genetics and complementation that are very nicely done).

      Weaknesses:

      However, with respect to the most important implication and claims of this work, the role of redox in controlling the chlamydial developmental cycle rather than simply being a correlation/passenger effect, I am less convinced about the impact of this work. First, the study is largely observational and does not resolve how this redox control of the cell cycle could be achieved, whereas in the case of _Caulobacte_r, a clear molecular link between DNA replication and redox has been proposed. How would progressive oxidation in RBs eventually trigger the secondary developmental genes to induce EB differentiation? Is there an OxyR homolog that could elicit this change and why would the oxidation stress in RBs gradually accumulate during growth despite the presence of AhpC? In other words, the role of AhpC is simply to delay or dampen the redox stress response until the trigger kicks in, again, what is the trigger? Is this caused by increasing oxidative respiration of RBs in the inclusion? But what determines the redox threshold?

      Thank you for your comments. As the reviewer notes, our work clearly demonstrates that AhpC acts as an antioxidant in Chlamydia trachomatis. Further, we have shown that transcription of the late cycle genes is altered upon altered activity of AhpC, which acts as a proof of concept that redox is (one of) the key factor(s) controlling developmental cycle progression in Chlamydia. Our new RNAseq data indicate that a broad swath of well characterized late genes is activated, which contradicts the argument that what we’ve measured is a stress response (unless activation of late genes in Chlamydia is generally a stress response (not the case based on other models of stress) – in which case we would not be able to differentiate between these effects). We hypothesize that ROS production from the metabolic activities of RBs serves as a signal to trigger secondary differentiation from RBs to EBs. How this exact threshold is determined is currently unknown as Chlamydia does not have any annotated homolog for OxyR. It is beyond the scope of the present manuscript to identify and then characterize what specific factor(s) control(s) this response. We fully anticipate that multiple factors are likely impacted by increasing oxidation, so dissecting the exact contributions of any one factor will represent (a) potential separate manuscript(s). Nonetheless, this remains an overarching goal of the lab yet remains challenging given the obligate intracellular nature of Chlamydia. Strategies that would work in a model system, like Caulobacter, that can be grown in axenic media are not easily implemented in Chlamydia.

      As we noted above in another response, ahpC is transcribed as a mid-cycle gene with a peak of transcription corresponding to the RB phase of growth. We hypothesize that the gradual accumulation of ROS from metabolic activity will eventually supercede the ability of AhpC to detoxify it. This would result in any given RB asynchronously and stochastically passing this threshold (and triggering EB formation), which is consistent with what we know about secondary differentiation in Chlamydia.

      I also find the experiment with Pen treatment to have little predictive power. The fact that transcription just proceeds when division is blocked is not unprecedented. This also happens during the Caulobacter cell cycle when FtsZ is depleted for most developmental genes, except for those that are activated upon completion of the asymmetric cell division and that is dependent on the completion of compartmentalization. This is a smaller subset of developmental genes in caulobacter, but if there is a similar subset that depends on division on chlamydia and if these are affected by redox as well, then the argument about the interplay between developmental transcription and redox becomes much stronger and the link more intriguing. Another possibility to strengthen the study is to show that redox-regulated genes are under the direct control of chlamydial developmental regulators such as Euo, HctA, or others and at least show dual regulation by these inputs -perhaps the feed occurs through the same path.

      Comparisons to other model systems are generally of limited value with Chlamydia. All chlamydial cell division genes are mid-cycle (RB-specific) genes, just like ahpC. There is no evidence of a redox-responsive transcription factor (whether EUO, HctA, or another) that activates or represses a subset of genes in Chlamydia. Similarly, there is no evidence that redox directly and specifically impacts transcription of cell division genes based on our new RNAseq data. The types of experiments suggested are not easily implemented in Chlamydia, but we would certainly like to be able to do them.

      As it pertains to penicillin specifically, we and others have shown that treating chlamydiae with Pen blocks secondary differentiation (meaning late genes are not transcribed). Effectively, Pen treatment freezes the organism in an RB state with continued transcription of RB genes. What we have shown is that, even during Pen treatment (which blocks late gene transcription), ahpC KD can overcome this block, which shows that elevated oxidation is able to trigger late gene expression even when the organisms are phenotypically blocked from progressing to EBs. The comparison from our perspective to Caulobacter is of limited value.

      This redox-transcription shortcoming is also reflected in the discussion where most are about the effects and molecular mitigation of redox stress in various systems, but there is little discussion on its link with developmental transcription in bacteria in general and chlamydia.

      We have edited the Discussion to include a broader description of the results and included additional citations as suggested by the reviewer (PMID: 32090198, PMID: 26063575). However, we found one suggested article (PMID: 2865432) is not relevant to our study, so we didn’t cite it in our present manuscript. There may have been a typo, so feel free to provide us the correct PMID that can be cited.

      Reviewer #1 (Recommendations For The Authors):

      (1) Line 146. A minor point, but inclusion-forming units directly measure infectious EBs. In some cases, the particle-to-infectivity ratio approaches unity. I don't believe IFUs are a "proxy".

      Following reviewers comment we have modified the statement.

      (2) Figure 2E. Results are normalized to uninduced. The actual number of IFUs in the uninduced should be provided.

      In the revised version of the manuscript, we have provided actual number of IFUs at 24 and 48 hpi in the uninduced condition of both ahpC OE and EV.

      (3) Figures 3B&D. The shades of gray are not possible to distinguish. I'd suggest color or direct labeling.

      Following reviewer’s suggestion, in the latest version of the manuscript we have replaced gray shaded graphs with RGB colored graphs for better visualization and understanding.

      (4) Lines 217-224, Figure 4. Is it possible to get micrographs of the reporter retention in chlamydiae to demonstrate that it is chlamydial ROS levels that are being measured and not cellular?

      Following reviewer’s comment, we performed live-cell microscopy using uninfected HeLa cells and ahpC KD in the uninduced and induced conditions at 24 and 40 hpi. We have created new Fig. 5A with the quantitative ROS measurement graph done by the plate reader (old figure 4 E) and these new 24 hpi/40 hpi microscopy images (Fig 5B and S4).

      (5) The Discussion is overly long and redundant. Large portions of the discussion are simply a rehash of the Results listing by figure number the relevant conclusions.

      Following reviewer’s suggestion, the discussion is modified.

      Reviewer #2 (Recommendations For The Authors):

      (1) In Figure 2, ahpC is significantly overexpressed at 14 hpi. An IFA as in 2B for 14hpi will be useful. This will help to understand how quick the effect of ahpC overexpression is on development.

      We have added 14 hpi IFA of ahpC and EV as part of Fig 2B.

      (2) In Figure 2E, is there a reason that there is no increase in recoverable IFUs between 24h and 48h for the EV?

      The graph in 2E is % of uninduced. For more clarity, we have mentioned absolute IFUs of uninduced samples in the revised manuscript and IFU level at 48 hpi IFU is higher than the 24 hpi.

      (3) In Figure 3, Can relative levels of RB vs EB measured? This will provide a convincing case for the production of more EBs even when only less/more RBs are present. The same stands for Figure 4.

      We assumed that the comment is for Fig. 2 not the Fig. 3 and following reviewer’s constructive suggestion, we have attempted to resolve the issue. We normalized log10 IFUs/ml with log10 gDNA for 24 hpi and added as figure 2F and 4E. This may resolve the reviewer’s concern about the levels of RBs and EBs.

      (4) A colour-coded Figure 3B and D, instead of various shades of grey, will be easy for the reader to interpret.

      Agreed with the reviewer. For better visualization and understanding of the data, we have replaced gray shaded graphs with RGB colored graphs in the latest version of the manuscript.

      Reviewer #3 (Recommendations For The Authors):

      Other comments:

      (1) The first paragraph of the discussion should be deleted. It's not very useful or revealing and just delivers self-citations.

      Following reviewer’s suggestion, we rewrote the discussion.

      (2) The first paragraph of the results section does not present results. It's an intro.

      We incorporated this information into the Intro as suggested.

      (3) Has the redox difference between RBs and EBs been experimentally verified by these authors as depicted and claimed in Figure 1A with the cell-permeable, fluorogenic dye CellROX Deep Red for example? It is important to confirm this for EBs and RBs in this setup.

      The difference between redox status of RBs and EBs is studied and established before by previous studies such as Wang et al., 2014.

      (4) l77. Obligate intracellular alpha-proteobacteria also differentiate ... not only chlamydiae.

      We have modified the sentence.

      (5) l127. Is the redox state altered upon ahpC overexpression?

      The ahpC overexpression strain showed hyper resistance for the tested oxidizing agents (including the highest concentration tested) indicating highly reduced conditions as a result of higher activity of AhpC.

    1. Author response:

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

      We sincerely thank the Editor and the Reviewers for their time and effort in thoroughly reviewing our manuscript and providing valuable feedback. We hope we have addressed their comments effectively and improved the clarity of our manuscript as a result.

      The major revisions in the updated manuscript are as follows:

      (1) Immunization experiments using mRNA in Syrian hamsters were performed (Supplementary figures 2A, B and C).

      (2) An ELISPOT assay to evaluate cellular immunity in Syrian hamsters inoculated with BK2102 was conducted (Figure 2F).

      (3) IgA titers in BK2102-inoculated Syrian hamsters were successfully measured (Supplementary figure 2B).

      (4) New immunogenicity data for BK2102 in monkeys was additionally included (Supplementary figure 3B).

      (5) The discussion section has been thoroughly revised to integrate the new data.

      These results have been incorporated into the manuscript, and additional text has been added accordingly.

      Below, we provide point-by-point responses to the reviewers’ comments and concerns.

      Public Reviews:

      Reviewer #1:

      (1) A comparative safety assessment of the available m-RNA and live attenuated vaccines will be necessary. The comparison should include details of the doses, neutralizing antibody titers with duration of protection, tissue damage in the various organs, and other risks, including virulence reversal.

      We agree with the Reviewer’s comment regarding the lack of data to compare BK2102 with an mRNA vaccine. Unfortunately, we were unable to obtain commercially available mRNA vaccines for research purposes and could not produce mRNA vaccines of equivalent quality. As a result, a direct comparison of the safety profiles of BK2102 and mRNA vaccines was not possible. To address this, we conducted a GLP study with an additional twelve monkeys to evaluate the safety of BK2102. Following three intranasal inoculations of BK2102 at two-week intervals, no toxic effects were observed in any of the parameters assessed, including tissue damage, respiratory rate, functional observational battery (FOB), hematology, or fever. These results are detailed in lines 115-117.

      Furthermore, we compared the immunogenicity of BK2102 with that of an in-house prepared mRNA vaccine. The mRNA vaccine was designed to target the spike protein of SARS-CoV-2, and its immunogenicity was evaluated in hamsters. When serum neutralizing antibody titers were found to be comparable between the two, intranasal inoculation of BK2102 induced higher IgA levels in nasal wash samples compared to those from hamsters injected intramuscularly with the self-made mRNA vaccine (Supplementary figures. 2A and B, respectively). Additionally, while the mRNA vaccine induced Th1 and Th2 immune responses, as indicated by the detection of IgG1 and IgG2/3 (Supplementary figure. 2C), BK2102 mainly induced a Th1 response in hamsters. These explanatory sentences have been added to the manuscript (lines 140-150).

      (2) The vaccine's effect on primates is doubtful. The study fails to explain why only two of four monkeys developed neutralizing antibodies. Information about the vaccine's testing in monkeys is also missing: What was the level of protection and duration of the persistence of neutralizing antibodies in monkeys? Were the tissue damages and other risks assessed?

      We believe that the reason neutralizing antibody titers were observed in only 2 out of 4 monkeys in the immunogenicity study reported in the original manuscript is that only a single-dose was administered. We measured the neutralizing antibody titers in sera collected from monkeys used in the GLP study and confirmed the induction of neutralizing antibody in all 6 monkeys that received three inoculations of BK2102. This data has been included in a new figure (Supplementary figure 3B). While we would have liked to evaluate the persistence of immunity and conduct a protection study in monkeys, limitations related to facility availability and cost prevented us from doing so. As noted in (1), tissue injury and other risk assessments were evaluated in the GLP study, which showed no evidence of tissue injury or other toxic effects. These results are described in lines 113-117.

      (3) The vaccine's safety in immunosuppressed individuals or individuals with chronic diseases should be assessed. Authors should make specific comments on this aspect.

      In general, live-attenuated vaccines are contraindicated for immunosuppressed individuals or those with chronic conditions, and therefore BK2102 is also not intended for use in these patients.

      This information has been added to the Discussion section (lines 309-311).

      (4) The candidate vaccine has been tested with a limited number of SARS-CoV-2 strains. Of note, the latest Omicron variants have lesser virulence than many early variants, such as the alfa, beta, and delta strains.

      We have added the results of a protection study against the SARS-CoV-2 gamma strain to Supplementary figures 5A and B. No weight loss was observed in BK2102-inoculated hamsters following infection with the gamma strain. These results are described in lines 109-111, 158-162.

      (5) Limitations of the study have not been discussed.

      We apologize for the ambiguity in the description of the Limitations of this paper. One major limitation of this study is that, despite observing high immunogenicity in hamsters, it remains uncertain whether the same positive results would be achieved in humans. Differences in susceptibility exist between species, which are not solely attributed to weight differences. For instance, while a single dose of 10<sup>3</sup> PFU of BK2102 was sufficient to induce neutralizing antibodies in hamsters, a higher dose of 10<sup>7</sup> PFU in monkeys was required to induce antibodies in only about 50% of the monkeys. Additionally, two more challenges in development of BK2102 were added to the discussion. The first was the limited availability of analytical reagents for hamster models, which restricted the detailed immunological characterization of the response. Second, it took time to gather preclinical data due to the space-related restrictions of BSL3 facilities, which delayed the clinical trials for BK2102 until many individuals had already acquired immunity against SARS-CoV-2. It remains to be seen whether our candidate will be optimal for human use, as the immunogenicity of live-attenuated vaccines is generally influenced by pre-existing immunity.

      We added these considerations to the discussion section (lines 300-309).

      Reviewer #2:

      No major weaknesses were identified, however, this reviewer notes the following:

      The authors missed the opportunity to include a mRNA vaccine to demonstrate that the immunity and protection efficacy of their live attenuated vaccine BK2102 is better than a mRNA vaccine.

      One of the potential advantages of live-attenuated vaccines is their ability to induce mucosal

      immunity. It would be great if the authors included experiments to assess the mucosal immunity of their live-attenuated vaccine BK2102.

      We agree with the Reviewer’s suggestion regarding the importance of comparing BK2102 with the mRNA vaccine modality and evaluating the mucosal immunity induced by BK2102. In hamsters, under conditions where serum neutralizing antibody titers were equivalent, intranasal inoculation of BK2102 induced higher levels of antigen-specific IgA in nasal wash compared to intramuscular injection of the conventional mRNA vaccine. This new data has been added in Supplementary figures 2A and B, and corresponding sentences have been included in the Results and Discussion sections (lines 140-145, 292-299).

      Reviewer #3:

      Lack of a more detailed discussion of this new vaccine approach in the context of reported live-attenuated SARS-CoV-2 vaccines in terms of its advantages and/or weaknesses.

      sCPD9 and CoviLiv<sup>TM</sup>, two previously reported live-attenuated vaccines, achieve attenuation through codon deoptimization or a combination of codon deoptimization and FCS deletion. These two strategies affect viral proliferation but do not directly impact virulence. In contrast, the temperature sensitivity-related substitutions in NSP14 included in BK2102 selectively restrict the infection site, reducing the likelihood of lung infection and providing a safety advantage over the other live-attenuated vaccines. As mentioned in the response to comment (5) of Reviewer #1, a limitation of BK2102 is that its development began later than that of the previously reported live-attenuated vaccines. Consequently, we must consider the impact of pre-existing immunity in future human trials. Based on these points, we have added sentences discussing the advantages and disadvantages to the Discussion section (lines 302-305, 312-319).

      Antibody endpoint titers could be presented.

      Thank you for your suggestion. We calculated the antibody endpoint titers for Figure 2A and included the results in lines 105-107 of the revised manuscript.

      Lack of elaboration on immune mechanisms of protection at the upper respiratory tract (URT) against an immune evasive variant in the absence of detectable neutralizing antibodies.

      We appreciate the comment. The potential role of cellular and mucosal immunity in protection has been discussed in more detail in the revised manuscript, specifically in lines 283-295. According to the reference we initially cited, Hasanpourghadi et al. evaluated their adenovirus vector vaccine candidates and reported that the protection was enhanced by co-expression of the nucleocapsid protein rather than relying solely on the spike protein (Hasanpourghadi et al., Microbes Infect, 2023). Therefore, cellular immunity against the nucleocapsid and/or other viral proteins induced by BK2102 may also contribute to protection, as evidenced by more pronounced cellular immunity to the nucleocapsid detected through ELISPOT assay. Moreover, antigen-specific mucosal immunity was successfully detected in additional studies. The involvement of mucosal immunity in protection against mutant strains has been documented in the previously cited reference (Thwaites et al., Nat Commun, 2023). We have included these new data in Figure 2F and Supplementary figure 2B. Additionally, the results and discussion regarding the mechanisms of protection in the upper respiratory tract, in the absence of detectable neutralizing antibodies, have been incorporated into the revised lines 136-139, 143-145 and 283-295, respectively.

      Recommendations for the authors:

      Reviewer #2:

      Figure 1: Please include the LOD and statistical analysis in both panels. Please consider passaging the virus in Vero cell s, approved for human vaccine production, to assess the stability of BK2102 after serial passage in vitro, which is important for its implementation as a live-attenuated vaccine. The authors should consider evaluating viral replication in different cell lines, and also assessing the plaque phenotype.

      Thank you for your valuable comments. First, we have added the statistical analysis and the limit of detection (LOD) to Figure 1. In response to the comments regarding the stability of BK2102 after serial passage in Vero cells, as well as its replication and plaque phenotype in different cell lines, we manufactured test substances for GLP studies and clinical trials by passaging BK2102 in Vero cells, which are approved for human vaccine production. We confirmed that BK2102 is stable (data not shown). Additionally, we verified that BK2102 replicates in BHK, Vero E6, and Vero E6/TMPRSS2 cells, in addition to Vero cells. Among these options, we selected Vero cells due to their high proliferative capacity and ability to produce clear plaques.

      Figure 2: Please, include statistical analysis in panels A, B, and D. Please, include the LOD in panels A and D. Please, include viral titers from these experiments in hamsters and NHPs.

      First, we would like to note that Figure 2D has been replaced by Figure 2C in the revised manuscript, and the data on neutralizing antibody titers in non-human primates (NHPs), originally presented as Figure 2C, have been moved to the Supplementary figure 3A.

      We have added the statistical analysis to Figure 2B and C, as well as the LOD to Figure 2C. Figure 2A (Spike-specific IgG ELISA) was intended for qualitative evaluation based on OD values, so the LOD was not defined. We have also added a detailed description of virus titer in the Methods section under the headings “Evaluation of Immunogenicity in Hamsters” and “Evaluation of Immunogenicity in Monkeys”, and updated the information in the Figure legends of the revised manuscript (lines 451, 459, 468-474, 566-567, 576-578, 582-584, 661-662).

      Figure 3: Please, include the viral titers of the challenge virus in the NT and lungs.

      We have added the virus titers for the challenge experiments to the Results section under the heading “BK2102 induced protective immunity against SARS-CoV-2 infection” (lines 168-174).

      Figure 4: Please, include statistical analysis in panels B and C and evaluate viral titers.

      We have added the statistical analysis to Figure 4B and C. Unfortunately, all samples in Figure 4 were fixed in formalin for histopathological examination, so virus titers could not be measured. However, in past experiments, we measured viral titers in the nasal wash samples and lungs of hamsters three days post-infection with D614G and BK2102. We confirmed that infectious virus was detected in both the nasal wash and lungs of the hamsters infected with D614G strain (2.9 log10 PFU/mL and 5.3 log10 PFU/g, respectively), but not in the lungs of the hamsters with BK2102. The viral titers in the nasal wash of BK2102-infected hamsters were equivalent to those of the hamsters infected with the D614G wild-type strain (3.0 log10 PFU/mL). However, we did not include this data to the revised manuscript.

      Figure 5: Please, include viral titers in different tissues with the different vaccines (panels A and B). Please, include the body weight changes.  Finally, please, consider the possibility of challenging the vaccinated mice with the same SARS-CoV-2 strains used in the manuscript to demonstrate similar protection efficacy in this new ACE2 transgenic mice.

      The different tissues of Tg mice were not sampled, as no gross abnormalities were observed in organs other than lungs and brains during necropsy. We have added new data on the body weight of Tg mice after infection to Supplementary figures 9B and 9C in the revised manuscript, along with additional lines in the Results section (lines 228-230 and 247-248). Although we do not know the reason, we have observed that immunization of this animal model does not lead to an increase in antibody titers. Therefore, we do not consider this animal model suitable for the protection study as you suggested. However, it could be useful in passive immunization experiments.

      Supplementary Figure 1: Since most of the manuscript focuses on BK2102, the authors should consider removing the other live-attenuated vaccines (Supplementary Figure 1A).

      We agree with the Reviewer’s suggestion and have simplified the description for Supplementary Figure 1A (lines 93-97).

      Supplementary Figure 3: Please, include statistical analysis.

      In the revised manuscript, Supplementary Figure 3 from the original manuscript has been moved to Supplementary Figure 2D. The IgG subclass ELISA was intended for a qualitative evaluation based on OD values, and therefore the results were included in the Supplementary figure. However, we realized the description was not clear, so we added further clarification in the Results section (lines 145-147).

      Supplementary Figure 4: Please, include the viral titers in both infected and contact hamsters from this experiment.

      In the revised manuscript, Supplementary Figure 4 in the original manuscript has been moved to Supplementary Figure 6. Unfortunately, due to limited breeding space for the hamsters, we were unable to prepare groups for the evaluation of viral titer, and instead prioritized evaluation by body weight.

      Reviewer #3:

      (1) It would be helpful to discuss this new vaccine in the context of other reported live-attenuated vaccines in terms of its advantages and/or disadvantages.

      Please refer to our response to the Reviewer’s “first comment” above, as well as to the response in Public comment (5) of Reviewer #1. The modifications made in the manuscript are described in lines 302-305 and 312-319.

      (2) Figure 2A: end-point titers could be presented, other than OD values.

      This comment is addressed in the reviewer’s second public comment. The endpoint titer has been included in lines 105-107 of the revised manuscript.

      (3) Figure 2C: it is unclear why only 2 out of 4 NHPs show neutralization titers. This could be moved to a supplementary figure.

      As suggested by the Reviewer, Figure 2C of the original manuscript has been moved to Supplementary Figure 3A in the revised manuscript. In response Public comment (2) from Reviewer #1, we have also added new data on neutralizing antibodies in the monkeys as Supplementary figure 3B.

      (4) Figures 2E-F: bulk measurement of cytokine production in supernatants is not an optimal way to measure vaccine-induced Ag-specific T cells. ELISPOT or ICS are better. T-cell ELSIPOT for hamsters is available. This should at least be discussed.

      Please refer to our response to this Reviewer’s third public comment. We have added the new results in Figure 2F of the revised manuscript.

      (5) It is quite interesting that no N-specific cellular response was observed, given that it is a live-attenuated vaccine. What about N-specific binding Abs?

      We conducted the ELISPOT assay as suggested by the Reviewer and detected cellular immunity against both spike and nucleocapsid proteins (Figure 2F). We did not examine nucleocapsid-specific antibodies, as they do not contribute to the neutralizing activity; however, nucleocapsid-specific cellular immunity was confirmed.

      (6) Figure 3: limit of detection for virological assays could be labeled.

      We have added the LOD in Figures 3C, D, F and G.

      (7) Figures 3E-F: it is interesting to see that the vaccine elicits almost complete protection at URT against BA.5, despite no BA.5 neutralizing titers being detected at all. What mechanism of URT protection by BK2102 would the authors speculate? T cells or other Ab effector functions?

      Please refer to the response to this Reviewer’s third public comment. We have added new results regarding cellular and mucosal immunity (Figure 2F and Supplementary figure 2B) and discussed the mechanisms of protection in the upper respiratory tract in the absence of detectable neutralizing antibodies (lines 136-139, 143-145 and 283-295, respectively).

      (8) Figure 3I: the durability of protection is a strength of the study. Other than body weight changes, what about viral loads in the animals after the challenge?

      We primarily assessed the effect of the vaccine by monitoring changes in body weight, as the differences compared to the naïve group were clear. Unfortunately, we did not collect samples at different time points throughout the study, which prevented us from evaluating the viral titers.

      In addition, we made corrections to several other sections identified during the revision process. The revised parts are as follows:

      - In the Methods section under the title “Evaluation of BK2102 pathogenicity in hamsters”, the infectious virus titer of D614G strain has been corrected (line 478).

      - In the Methods section under the title “In vivo passage of BK2102 in hamsters”, infectious virus titer of BK2102 and A50-18 strain has been corrected (line 487).

      - The collection time of splenocytes after inoculation has been corrected in the figure legend of Figure 2D, (line 583).

      - There was an error in Figure 2D. The figure has been replaced with the appropriate version.

      - A new reference on NSP1 deletion (Ueno et al., Virology, 2024) has been added to the references.

      - Several methods have been described more clearly.

    1. Author response:

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

      Reviewer # 1 (Public Review):

      Summary:

      Inthispreprint, theauthorssystematicallyandrigorouslyinvestigatehowspecificclassesofresiduemutations alter the critical temperature as a proxy for the driving forces for phase separation. The work is well executed, the manuscript well-written, and the results reasonable and insightful.

      Strengths:

      The introductory material does an excellent job of being precise in language and ideas while summarizing the state of the art. The simulation design, execution, and analysis are exceptional and set the standard for these types of large-scale simulation studies. The results, interpretations, and Discussion are largely nuanced, clear, and well-motivated.

      We thank the reviewer for their assessment of our work and for highlighting the key strengths of the paper.

      Weaknesses:

      This is not exactly a weakness, but I think it would future-proof the authors’ conclusions to clarify a few key caveats associated with this work. Most notably, given the underlying implementation of the Mpipi model, temperature dependencies for intermolecular interactions driven by solvent effects (e.g., hydrophobic effect and charge-mediated interactions facilitated by desolvation penalties) are not captured. This itself is not a “weakness” per se, but it means I would imagine CERTAIN types of features would not be wellcaptured; notably, my expectation is that at higher temperatures, proline-rich sequences drive intermolecular interactions, but at lower temperatures, they do not. This is likely also true for the aliphatic residues, although these are found less frequently in IDRs. As such, it may be worth the authors explicitly discussing.

      We also thank the reviewer for pointing out that a more detailed discussion of the model limitations is needed. The original Mpipi model was designed to probe UCST-type transitions (that are associative in nature) of disordered sequences. The reviewer is correct, that in its current form, the model does not capture LCST-type transitions that depend on changes in solvation of hydrophobic residues with temperature. We have amended the discussion to highlight this fact.

      Similarly, prior work has established the importance of an alpha-helical region in TDP-43, as well as the role of aliphatic residues in driving TDP-43’s assembly (see Schmidt et al 2019). I recognize the authors have focussed here on a specific set of mutations, so it may be worth (in the Discussion) mentioning [1] what impact, if any, they expect transient or persistent secondary structure to have on their conclusions and [2] how they expect aliphatic residues to contribute. These can and probably should be speculative as opposed to definitive.

      Again - these are not raised as weaknesses in terms of this work, but the fact they are not discussed is a minor weakness, and the preprint’s use and impact would be improved on such a discussion.

      We agree with the reviewer that the effects of structural changes/propensities on these scaling behaviors would be an interesting and important angle to probe. We also comment on this in the discussion.

      Reviewer # 2 (Public Review):

      This is an interesting manuscript where a CA-only CG model (Mpipi) was used to examine the critical temperature (Tc) of phase separation of a set of 140 variants of prion-like low complexity domains (PLDs). The key result is that Tc of these PLDs seems to have a linear dependence on substitutions of various sticker and space residues. This is potentially useful for estimating the Tc shift when making novel mutations of a PLD. However, I have strong reservations about the significance of this observation as well as some aspects of the technical detail and writing of the manuscript.

      We thank the reviewer for their thoughtful and detailed feedback on the manuscript.

      (1) Writing of the manuscript: The manuscript can be significantly shortened with more concise discussions. The current text reads as very wordy in places. It even appears that the authors may be trying a bit too hard to make a big deal out of the observed linear dependence.

      The manuscript needs to be toned done to minimize self-promotion throughout the text. Some of the glaring examples include the wording “unprecedented”, “our research marks a significant milestone in the field of computational studies of protein phase behavior ..”, “Our work explores a new framework to describe, quantitatively, the phase behavior ...”, and others.

      We thank the reviewer for their suggestions on the writing of the manuscript. We understand the concern regarding the length and tone of the manuscript, and in response to their feedback, we have revised the language throughout the manuscript.

      There is really little need to emphasize the need to manage a large number of simulations for all 140 variants. Yes, some thoughts need to go into designing and managing the jobs and organizing the data, but it is pretty standard in computational studies. For example, large-scale protein ligand-free energy calculations can require one to a few orders of magnitude larger number of runs, and it is pretty routine.

      We fully agree with the reviewer that this aspect of the study is relatively standard in computational research and does not require special emphasis. In response, we have revised the manuscript to shorten the aforementioned section, focusing instead on the scientific insights gained from the simulations rather than the logistical challenges of managing them.

      When discussing the agreement with experimental results on Tm, it should be noted that the values of R > 0.93 and RMSD < 14 K are based on only 16 data points. I am not sure that one should refer to this as “extended validation”. It is more like a limited validation given the small data size.

      We thank the reviewer for their consideration of our validation set. Indeed, the agreement with experimental results is based on 16 data points, as this set represents the available published data at the time of writing of this manuscript. The term “extended validation” is used to signify that our current dataset builds upon previous validations (in Joseph, Reinhardt et al. Nat Comput. Sci. 2021), incorporating additional variants not previously examined. The metrics of an r>0.93 and a low RMSD indicate a strong agreement between the model and experiments, and an improvement with respect to other reported models. We are committed to continue validating our methods.

      Results of linear fitting shown in Eq 4-12 should be summarized in a single table instead of scattering across multiple pages.

      We considered the reviewer’s suggestion to compile all the laws into a single table. However, we believe it would be more effective for readers to reference each relationship directly where it is first discussed in the text. That said, we do include Table 1 in the original manuscript, which provides a summary of all the laws.

      The title may also be toned down a bit given the limited significance of the observed linear dependence.

      We respectfully disagree with the reviewer and believe that the current title accurately captures the scope of the manuscript.

      (2) Significance and reliability of Tc: Given the simplicity of Mpipi (a CA-only model that can only describe polymerchaindimension)andthelowcomplexitynatureofPLDs, thesequencecompositionitselfisexpected to be the key determinant of Tc. This is also reflected in various mean-field theories. It is well known that other factors will contribute, such as patterning (examined in this work as well), residual structures, and conformational preferences in dilute and dense phases. The observed roughly linear dependence is a nice confirmation but really unsurprising by itself. It appears how many of the constructs deviate from the expected linear dependence (e.g., Figure 4A) may be more interesting to explore.

      While linear dependencies in critical solution temperatures may appear expected for certain systems, for example, symmetric hard spheres, the heterogeneity of intrinsically disordered regions (IDRs), like prion-like domains (PLDs), make this finding notable. The simplicity of our linear scaling law belies the underlying complexity of multivalent interactions and sequence-dependent behaviors in a certain sequence regime, which has not been quantitatively characterized in this manner before. Likewise, although linear dependencies may be expected in simplified models, the real-world applicability and empirical validation of these laws in biologically relevant systems are not guaranteed. Our chemically based model provides the robustness needed to do that. The linear relationship observed is significant because it provides a predictive framework for understanding how specific mutations affect a diverse set of PLDs. The framework presented can be extended to other protein families upon the application of a validated model, which might or might not yield linear relationships depending on the cooperative effects of their collective behavior. This extends beyond confirming known theories—it offers a practical tool for predicting phase behavior based on sequence composition

      We agree with the reviewer that, while the overarching linear trend is clear, deviations from linearity observed in constructs like those in Figure 4A point to additional, and interesting, layers of complexity. These deviations offer interesting avenues for future research and suggest that while linearity might dominate PLD critical behavior, other factors may modulate this behavior under specific conditions.

      This is an excellent suggestion from the reviewer that, while it falls outside the scope of the current study, we are interested in exploring in the future.

      Finally, the relationships are all linear, they have been normalized in different ways—the strength of the study also lies in that. Instead of focusing solely on linearity, our study explores the physical mechanisms that underlie these relationships. This approach provides a more complete understanding of how sequence composition and the underlying chemistry of the mutated residues influence T<sub>c</sub.

      The assumption that all systems investigated here belong to the same universality class as a 3D Ising model and the use of Eqn 20 and 21 to derive Tc is poorly justified. Several papers have discussed this issue, e.g., see Pappu Chem Rev 2023 and others. Muthukumar and coworkers further showed that the scaling of the relevant order parameters, including the conserved order parameter, does not follow the 3D Ising model. More appropriate theoretical models including various mean field theories can be used to derive binodal from their data, such as using Rohit Pappu’s FIREBALL toolset. Imposing the physics of the 3D Ising model as done in the current work creates challenges for equivalence relationships that are likely unjustified.

      We thank the reviewer for raising this point and for highlighting the FIREBALL toolset. Based on our understanding, FIREBALL is designed to fit phase diagrams using mean-field theories, such as Flory–Huggins and Gaussian Cluster Theory. Our experience with this toolset suggests that it places a higher weight on the dilute arm of the binodal. However, in our slab simulations, we observe greater uncertainty in the density of the dilute arm. This leads to only a moderate fit of the data to the mean-field theories employed in the toolset. While we agree that there is no reason to assume the phase behavior of these systems is fully captured by the 3D Ising model, we expect that such a model will describe the behavior near the critical point better than mean-field theories. Testing our results further with different critical exponents would be valuable in assessing how these predictions compare to a broader set of experimental data. Additionally, we have made the raw data points for the phase diagrams available on our GitHub, enabling practitioners to apply alternative fitting methods.

      While it has been a common practice to extract Tc when fitting the coexistence densities, it is not a parameter that is directly relevant physiologically. Instead, Csat would be much more relevant to think about if phase separation could occur in cells.

      WhileitistruethatCsatisdirectlyrelevanttowhetherphaseseparationcanoccurincellsunder physiological conditions, T<sub>c</sub> should not be dismissed as irrelevant.T<sub>c</sub> provides fundamental insights into the thermodynamics of phase separation, reflecting the overall stability and strength of interactions driving condensate formation. This stability is crucial for understanding how environmental factors, such as temperature or mutations, might affect phase behavior. In Figure 2C and D we compare experimental C<sub>sat</sub> values with our predicted T<sub>c</sub> from simulations. These quantities are roughly inversely proportional to each other and so we expect that, to a first approximation, the relationships recovered for T<sub>c</sub> should hold when consideringC<sub>sat</sub> at a fixed temperature.

      Reviewer # 3 (Public Review):

      Summary:

      “Decoding Phase Separation of Prion-Like Domains through Data-Driven Scaling Laws” by Maristany et al. offers a significant contribution to the understanding of phase separation in prion-like domains (PLDs). The study investigates the phase separation behavior of PLDs, which are intrinsically disordered regions within proteins that have a propensity to undergo liquid-liquid phase separation (LLPS). This phenomenon is crucial in forming biomolecular condensates, which play essential roles in cellular organization and function. The authors employ a data-driven approach to establish predictive scaling laws that describe the phase behavior of these domains.

      Strengths:

      The study benefits from a robust dataset encompassing a wide range of PLDs, which enhances the generalizability of the findings. The authors’ meticulous curation and analysis of this data add to the study’s robustness. The scaling laws derived from the data provide predictive insights into the phase behavior of PLDs, which can be useful in the future for the design of synthetic biomolecular condensates.

      We thank the reviewer for highlighting the importance of our work and for their critical feedback.

      Weaknesses:

      While the data-driven approach is powerful, the study could benefit from more experimental validation. Experimental studies confirming the predictions of the scaling laws would strengthen the conclusions. For example, in Figure 1, the Tc of TDP-43 is below 300 K even though it can undergo LLPS under standard conditions. Figure 2 clearly highlights the quantitative accuracy of the model for hnRNPA1 PLD mutants, but its applicability to other systems such as TDP-43, FUS, TIA1, EWSR1, etc., may be questionable.

      In the manuscript, we have leveraged existing experimental data for the A1-LCD variants, extracting critical temperatures and saturation concentrations to compare with our model and scaling law predictions. We acknowledge that a larger set of experiments would be beneficial. By selecting sequences that are related, we hypothesize that the scaling laws described herein should remain robust. In the case of TDP-43, to our knowledge this protein does not phase separate on its own under standard conditions. In vitro experiments that report phase separation at/above 300 K involve either the use of crowding agents (such as dextran or PEG) or multicomponent mixtures that include RNA or other proteins. Therefore, our predictions for TDP-43 are consistent with experiments. In general, we hope that the scaling laws presented in our work will inspire other researchers to further test their validity.

      The authors may wish to consider checking if the scaling behavior is only observed for Tc or if other experimentally relevant quantities such as Csat also show similar behavior. Additionally, providing more intuitive explanations could make the findings more broadly accessible.

      In Figure 2C and D we compare experimental C<sub>sat</sub> values with our predicted T<sub>c</sub> from simulations. These quantities are roughly inversely proportional to each other and so we expect that, to a first approximation, the relationships recovered for T<sub>c</sub> should hold when considering C<sub>sat</sub> at a fixed temperature.

      The study focuses on a particular subset of intrinsically disordered regions. While this is necessary for depth, it may limit the applicability of the findings to other types of phase-separating biomolecules. The authors may wish to discuss why this is not a concern. Some statements in the paper may require careful evaluation for general applicability, and I encourage the authors to exercise caution while making general conclusions. For example, “Therefore, our results reveal that it is almost twice more destabilizing to mutate Arg to Lys than to replace Arg with any uncharged, non-aromatic amino acid...” This may not be true if the protein has a lot of negative charges.

      A significant number of proteins, in addition to those mentioned in the manuscript, that contain prion-like low complexity domains have been reported to exhibit phase separation behaviors and/or are constituents of condensates inside cells. We therefore expect these laws to be applicable to such systems and have further revised the text to emphasize this point. As the reviewer suggests, we have also clarified that the reported scaling of various mutations applies to these systems.

      I am surprised that a quarter of a million CPU hours are described as staggering in terms of computational requirements.

      We have removed the note on CPU hours from the manuscript. However, we would like to clarify that the amount of CPU hours was incorrectly reported. The correct estimate is 1.25 million hours, but this value was unfortunately misrepresented during the editing process. We thank the reviewer for catching this mistake on our part.

      Reviewer # 1 (Recommendations For The Authors):

      Some minor points here:

      “illustrating that IDPs indeed behave like a polymer in a good solvent [43]. ” Whether or not an IDP depends as a polymer in a good solvent depends on the amino acid sequence - the referenced paper selected a set of sequences that do indeed appear on average to map to a good-solvent-like polymer, but lest we forget SAXS experiments require high protein concentrations and until the recent advent of SEC-SAXS, your protein essentially needed to be near infinitely soluble to be measured. As such, this paper’s conclusions are, apparently, ignorant of the limitations associated with the data they are describing, drawing sweeping generalizations that are clearly not supported by a multitude of studies in which sequence-dependencies have led to ensembles with a scaling exponent far below 0.59 (See Riback et al 2017, Peng et al 2019, Martin et al 2020, etc).

      We thank the reviewer for raising this point. To avoid making incorrect generalizations and potentially misleading readers, we have removed the quoted statement from our manuscript.

      As of right now, the sequences are provided in a convenient multiple-sequence alignment figure. However, it would be important also to provide all sequences in an Excel table to make it easy for folks to compare.

      In addition to the sequence alignment figure, we now provide all tested sequences in an Excel table format in the GitHub repository.

      Maybe I’m missing it, but it would be extremely valuable if the coexistence points plot in all the figures were provided as so-called source data; this could just be on the GitHub repository, but I’m envisaging a scenario where for each sequence you have a 4 column file where Col1=concentration and Col2=temperature, col3=fit concentration and col4=fit temperature, such that someone could plot col1 vs. col2 and col3 vs. col4 and reproduce the binodals in the various figures. Given the tremendous amount of work done to achieve binodals:

      The coexistence points used to plot the figures are now provided in the GitHub, in a format similar to that suggested by the reviewer.

      It would be nice to visually show how finite size effects are considered/tested for (which they are very nicely) because I think this is something the simulation field should be thinking about more than they are.

      Thank you for highlighting this point. In our previous work (supporting information of the original Mpipi paper), we demonstrated a thorough approach by varying both the cross-sectional area of the box and the long axis while keeping the overall density constant. In this work, we verified that the cross-sectional area was larger than the average R<sub>g</sub> of the protein. We then maintained a fixed cross-sectional area to long-axis ratio, varying the number of proteins while keeping the overall density constant. We have updated Appendix 1–Figure 2 to clarify our procedure and revised the caption to better explain how we ensured the number of proteins was adequate.

      When explaining the law of reticular diameters, it would be good to explain where the 3.06 exponent comes from.

      Based on the reviewer’s suggestion, we have added to the text: “The constant 3.06 in the equation is a dimensionless empirical factor that was derived from simulations of the 3D Ising model.”

      The NCPR scale in Figure 5 being viridis is not super intuitive and may benefit from being seismic or some other r-w-b colormap just to make it easier for a reader to map the color to meaning.

      We thank the reviewer for this suggestion and have replaced the scale with a r-w-b colormap.

      The “sticker and spacer” framework has received critiques recently given its perceived simplicity. However, this work seems to clearly illustrate that certain types of residues have a large effect on Tc when mutated, whereas others have a smaller effect. It may be worth re-phrasing the sticker-spacer introduction not as “everyone knows aromatic/arginine residues are stickers” but as “aromatic and arginine residues have been proposed to be stickers, yet other groups have argued all residues matter equally” and then go on to make the point that while a black-and-white delineation is probably not appropriate, based on the data, certain residues ARE demonstrably more impactful on Tc than others, which is the definition of stickers. With this in mind, it may be useful to separate out a sticker and a spacer distribution in Figure 1D, because the different distribution between the two residues types is not particularly obvious from the overlapping points.

      We have revised the introduction of the sticker–spacer model in the manuscript for clarity. As the reviewer suggests, we have also separated the sticker and spacer distribution, which is now summarized in new Appendix 0–figure 8.

      Reviewer # 3 (Recommendations For The Authors):

      Figure 2 clearly highlights the quantitative accuracy of the model for hnRNPA1 PLD mutants, but its applicability to other systems such as TDP-43, FUS, TIA1, EWSR1, etc., may be questionable. The following sentence may be revised to reflect this: “Our extended validation set confirms that the Mpipi potential can ...”

      Based on the reviewer’s suggestion, we have revised the text: “Our validation set, which expands the range of proteins variants originally tested [32], highlights that the Mpipi potential can effectively capture the thermodynamic behavior of a wide range of hnRNPA1-PLD variants, and suggests that Mpipi is adequate for proteins with similar sequence compositions, as in the set of proteins analyzed in this study. In recent work by others [66], Mpipi was tested against experimental radius of gyration data for 137 disordered proteins and the model produced highly accurate results, which further suggests the applicability of the approach to a broad range of sequences.”

    1. Reviewer #3 (Public review):

      This manuscript examines the impact of congenital visual deprivation on the excitatory/inhibitory (E/I) ratio in the visual cortex using Magnetic Resonance Spectroscopy (MRS) and electroencephalography (EEG) in individuals whose sight was restored. Ten individuals with reversed congenital cataracts were compared to age-matched, normally sighted controls, assessing the cortical E/I balance and its interrelationship and to visual acuity. The study reveals that the Glx/GABA ratio in the visual cortex and the intercept and aperiodic signal are significantly altered in those with a history of early visual deprivation, suggesting persistent neurophysiological changes despite visual restoration.

      First of all, I would like to disclose that I am not an expert in congenital visual deprivation, nor in MRS. My expertise is in EEG (particularly in the decomposition of periodic and aperiodic activity) and statistical methods. Although the authors addressed some of the concerns of the previous version, major concerns and flaws remain in terms of methodological and statistical approaches along with the (over)interpretation of the results. Specific concerns include:

      (1 3.1) Response to Variability in Visual Deprivation<br /> Rather than listing the advantages and disadvantages of visual deprivation, I recommend providing at least a descriptive analysis of how the duration of visual deprivation influenced the measures of interest. This would enhance the depth and relevance of the discussion.

      (2 3.2) Small Sample Size<br /> The issue of small sample size remains problematic. The justification that previous studies employed similar sample sizes does not adequately address the limitation in the current study. I strongly suggest that the correlation analyses should not feature prominently in the main manuscript or the abstract, especially if the discussion does not substantially rely on these correlations. Please also revisit the recommendations made in the section on statistical concerns.

      (3 3.3) Statistical Concerns<br /> While I appreciate the effort of conducting an independent statistical check, it merely validates whether the reported statistical parameters, degrees of freedom (df), and p-values are consistent. However, this does not address the appropriateness of the chosen statistical methods.

      Several points require clarification or improvement:<br /> (4) Correlation Methods: The manuscript does not specify whether the reported correlation analyses are based on Pearson or Spearman correlation.<br /> (5) Confidence Intervals: Include confidence intervals for correlations to represent the uncertainty associated with these estimates.<br /> (6) Permutation Statistics: Given the small sample size, I recommend using permutation statistics, as these are exact tests and more appropriate for small datasets.<br /> (7) Adjusted P-Values: Ensure that reported Bonferroni corrected p-values (e.g., p > 0.999) are clearly labeled as adjusted p-values where applicable.<br /> (8) Figure 2C<br /> Figure 2C still lacks crucial information that the correlation between Glx/GABA ratio and visual acuity was computed solely in the control group (as described in the rebuttal letter). Why was this analysis restricted to the control group? Please provide a rationale.<br /> (9 3.4) Interpretation of Aperiodic Signal<br /> Relying on previous studies to interpret the aperiodic slope as a proxy for excitation/inhibition (E/I) does not make the interpretation more robust.<br /> (10) Additionally, the authors state:<br /> "We cannot think of how any of the exploratory correlations between neurophysiological measures and MRS measures could be accounted for by a difference e.g. in skull thickness."<br /> (11) This could be addressed directly by including skull thickness as a covariate or visualizing it in scatterplots, for instance, by representing skull thickness as the size of the dots.<br /> (12 3.5) Problems with EEG Preprocessing and Analysis<br /> Downsampling: The decision to downsample the data to 60 Hz "to match the stimulation rate" is problematic. This choice conflates subsequent spectral analyses due to aliasing issues, as explained by the Nyquist theorem. While the authors cite prior studies (Schwenk et al., 2020; VanRullen & MacDonald, 2012) to justify this decision, these studies focused on alpha (8-12 Hz), where aliasing is less of a concern compared of analyzing aperiodic signal. Furthermore, in contrast, the current study analyzes the frequency range from 1-20 Hz, which is too narrow for interpreting the aperiodic signal as E/I. Typically, this analysis should include higher frequencies, spanning at least 1-30 Hz or even 1-45 Hz (not 20-40 Hz).<br /> (13) Baseline Removal: Subtracting the mean activity across an epoch as a baseline removal step is inappropriate for resting-state EEG data. This preprocessing step undermines the validity of the analysis. The EEG dataset has fundamental flaws, many of which were pointed out in the previous review round but remain unaddressed. In its current form, the manuscript falls short of standards for robust EEG analysis. If I were reviewing for another journal, I would recommend rejection based on these flaws.<br /> (14) The authors mention:<br /> "The EEG data sets reported here were part of data published earlier (Ossandón et al., 2023; Pant et al., 2023)." Thus, the statement "The group differences for the EEG assessments corresponded to those of a larger sample of CC individuals (n=38) " is a circular argument and should be avoided."<br /> The authors addressed this comment and adjusted the statement. However, I do not understand, why not the full sample published earlier (Ossandón et al., 2023) was used in the current study?

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      Reply to the reviewers

      Overall comments:

      Reviewer #1:

      Evidence, reproducibility and clarity

      The study by Parker et al describes the innovative use of single-cell RNA sequencing to detect markers and traits of pollen. Using pollen allows detection of recombinant events allowing the ability to do quantitative trait mapping using gene expression as a trait. This led to the discovery of expected cis QTL, but there is an intriguing trans QTL as well. The trans eQTL was mapped to a candidate causal locus DUO1. This is exciting given its role in pollen development and will obviously be followed up on in future studies.

      We thank the reviewer for these kind comments.

      Overall, this is an exciting technological advance that will rapidly advance our ability to map pollen traits and arguably more importantly create high density recombination maps across organisms. I realize this is a proof of principle study and the questions below are intended to improve this already strong manuscript.

      We agree with the reviewer that the main conceptual advance in our manuscript is the novel methodology for meiotic recombination breakpoint identification and eQTL mapping using snRNA-seq.

      Significance

      The overall strength is the development of a method to map recombination using single-cell genomics of pollen. The weakness is the limitation to studying pollen traits at least for now. The other weakness is helping the reader apply this to their own research questions. This is easily addressable through updating the writing in a way that is more accessible.

      We thank the reviewer again for their praise of our work. Although we chose to focus on eQTL mapping in pollen at this stage, we believe that the methods we have developed could also be applied to other organisms and tissues, so long as there as genetic diversity between individual cells in the population. This was previously demonstrated using F4 segregant populations of C. elegans (Ben-David et al. 2021). We therefore state in the Discussion that “eQTL mapping with snRNA-seq is also possible in diploid cells from segregating populations, provided sufficiently high numbers of individuals are used as input”.

      The methods described in the study could be of great use to other researchers who wish to peform eQTL analyses. We therefore agree with both reviewers that the method should be made as transparent as possible in the paper. We have therefore updated the Results, Methods and Discussion sections to address the specific points of both reviewers about clarity.

      Reviewer #2:

      Evidence, reproducibility and clarity

      In the manuscript by Parker et al, the authors developed a methodology to scale up eQTL studies using single-nucleus RNA-Seq of meiotic products using Arabidopsis thaliana pollen. Each pollen grain, collected from an F1 hybrid between two inbred lines, is haploid and contains a unique combination of the two parental genomes, effectively replacing the F2 population typically used in QTL studies. Single-nucleus RNA-Seq served as both phenotype and genotype, as it was used also to infer recombination profiles. In their experiments, the authors used a mixture of pollen from five different crosses - each between the reference Arabidopsis accession and another accession - for the first experiment, followed by a repeat of one of the original crosses in a second experiment to increase coverage and show reproducibility. They describe their approach to genotyping, performing the eQTL analysis, and describe statistics of the cis- and trans-eQTLs. In particular, they identify and discuss in detail a strong trans-eQTL on chromosome 1 that significantly and reproducibly associate with the expression of hundreds of genes. The likely candidate gene underlying this trans-eQTL is DUO3, a transcription factor known to play a role in pollen development, although the authors acknowledge that further experiments are needed to show that this is the causal variant.

      As this is a novel methodology with the potential for widespread adoption by the community, most of my comments focus on expanding the details provided about the methodology and discussing its limitations. Additional clarity of information will help to ensure its reproducibility and wider applicability.

      We agree with the reviewer that the main advance demonstrated in our study is the novel method for eQTL mapping. As noted in our response to reviewer 1, we agree that the method should be as made as clear as possible for readers, so that they can apply it to their own research questions. We have therefore updated the Results, Methods and Discussion sections to address the specific points of both reviewers about clarity.

      Significance:

      The methodology developed in this study significantly advances the feasibility of eQTL studies. The ability to easily scale up the number of individuals analyzed provides unprecedented resolution for identifying underlying alleles. In addition, because the pollen from each cross can be collected and processed together, environmental and technical variables between individuals (in this case, pollen nuclei) are tightly controlled. This advantage is underlined by the discovery of a strong trans-eQTL, which is likely to play an important role in pollen biology, and whose different alleles are spread across natural populations. I am therefore very excited about the publication of this manuscript.

      We thank the reviewer for these very positive remarks.

      Specific Comments:

      Reviewer #1:

      1. What is the average maker resolution in bp and cM? What numbers of nuclei would be needed to profile to gain single gene resolution in Arabidopsis?

      For haplotyping and crossover analysis, we grouped informative reads into 25kb bins to reduce both the number of predictions required for haplotype inference, and the number of statistical tests required for eQTL mapping. We can therefore estimate the median distance between non-empty bins for each nucleus as a proxy for marker resolution resolution. We find that the median distances between non-empty bins across all nuclei are 350 kb and 500 kb for the first and second dataset respectively. To address this question, we have updated the Results section to include some analysis of marker distributions, and added histograms of distributions as Figure 2 – figure supplement 1A.

      The question of how many nuclei would be needed to gain single gene resolution of eQTL mapping is extremely difficult to answer, as the detection and resolution of eQTLs depends on several different factors:

      • First and foremost, as pointed out by the reviewer, the sample size i.e. number of nuclei profiled, makes a difference to the ability to detect eQTLs.
      • Secondly, as in all RNA-seq experiments the effect size of the measured change in gene expression has a large impact on the ability to detect eQTLs. eQTLs causing small effect size changes will therefore require more nuclei to detect than those with large effect size changes. This likely explains why we were able to detect a larger proportion of trans-eQTLs in the second dataset with more nuclei compared to the first dataset, since trans-eQTLs tend to have smaller effect size changes.
      • Finally, the rate of meiotic recombination around the eQTL locus has a large impact on the resolution of the mapped eQTL. Loci in low-recombining regions, such as close to or within the centromere, will likely never be mappable to single-gene resolution, even with extremely high numbers of nuclei, due to genetic-linkage over large regions of the genome. This is exemplified by the CPV1 locus that we mapped in the Col-0 x Db-1 cross, that maps to the centromere of Chromosome 1. Despite correlating with a relatively large effect size change in gene expression in PLL1 (Figure 6 – figure supplement 3B), we could only map this trans-eQTL within a 1.5 LOD drop interval of >10 Mb. One way to address the issue of resolution caused by crossover rate could be to use mutants such as recq4 or figl1 which increase the rate of recombination, as was demonstrated recently (Capilla-Pérez et al. 2024). In summary, the number of nuclei required to map an eQTL to single-gene resolution is not fixed, and depends on both the effect size of the change in expression, and the genomic location of the causal variant. We have added a new paragraph to the Discussion to address this question and provide some potential future solutions.
      1. It would be great if the authors could add a discussion of how the resolution of mapping could be improved and what it would take to get there?

      We agree this is an important question for future work. As mentioned in response to point 1 of Reviewer #1, we have added a new paragraph to the Discussion to address this question and provide some potential future solutions.

      1. Could this approach be feasible for species where there is not a reference genome?

      While this would require different methods to the ones used in our study, it is possible to identify and genetically map markers using single-cell sequencing of recombinant pollen without a reference sequence. For example, we have used single cell sequencing of hybrid pollen to assemble the genome of the pollen mother plant by providing linkage information (Sun et al. 2022; Campoy et al. 2020). We mention this in the Discussion, where we state: “it has been demonstrated that genotypes created using gamete single cell sequencing can be used to disentangle complex genome assemblies and resolve the haplotypes of polyploid species such as potato.”

      1. It is stated 67% are located with in 2Mb of a gene and technically that is is cis-, but there aren't really long range interactions in Arabidopsis (>30kb)...so are these really cis or trans? It might be worth considering how cis vs trans are defined. Basically, what is truly cis vs trans?

      We agree with the reviewer that eQTLs that are genuinely located more than 30 kb from a gene are likely to be trans-eQTLs in Arabidopsis. Our reasoning for using a conservative approach to classifying eQTLs as cis is due to the resolution of the mapping procedure, and the expectation that the majority of identifiable eQTLs willl act in cis, not in trans. By using a conservative threshold we hope to prevent the misclassification of cis eQTLs as trans. To better inform the reader, we provide histograms showing the distribution of distances from mapped eQTLs classified as cis to the gene which was used as a phenotype as Figure 3B and figure 6 – figure supplement 3A, and report the median distances from cis-eQTLs to the affected gene in the Results.

      1. What percent of the time was the actual crossover captured, if at all? Is this possible with snRNA-seq?

      Assessing the accuracy of crossover mapping without ground truth information would be complex. In future we hope to use simulations and/or samples with known recombination patterns to benchmark the quality of crossover calling. This is outside the scope of the current paper. However, without knowing the true locations of crossovers we can use the probabilities produced by the rHMM to estimate 95% confidence intervals on the locations of individual crossovers. We find that the 95% confidence intervals of called crossovers follow a bi-modal distribution depending on their proximity to the centromere. For crossovers that were predicted to occur in the chromosome arms, the median 95% confidence interval size was 1.1 Mb. For crossovers that are proximal to the centromere, or where lack of markers means that the haplotype of the centromere is ambiguous, then the median 95% confidence interval size was 8.2 Mb. We have now added information from these confidence intervals and corresponding plots showing the resolution of individual crossover calls to the Results and Figure 2 – figure supplement 1B.

      1. How many eQTL were there per locus?

      We detected an average of 0.14 and 0.63 eQTLs per expressed gene in the first and second datasets, respectively. We have added this information to the Results.

      1. How deep were the libraries sequenced and were they sequenced to saturation? In general, I did not find any sequencing summary statistics. How many reads were sequenced per library, per genotype etc, how many aligned, how many UMIs per cell, how many transcripts detected per cell. This will help give the reader a baseline for knowing what kind of quality is needed to successfully implement this strategy in their own lab.

      We thank the reviewer for this important comment. We have now added a table of sequencing statistics to the supplemental data as Supplementary file 1.

      __ Reviewer #2:__

      (1) Given the sparseness of snRNA-Seq data per nucleus/cell (inherent to single cell technologies), what happens to low expressed genes? Is any filtering done? For example, in the extreme case of a gene that is either undetected or has only a single read in some nuclei, would a sufficiently large number of nuclei theoretically allow the detection of an eQTL signal for that gene? Alternatively, does this method remain inherently blind to genes expressed below a certain threshold? Please discuss these limitations and prospects.

      We indeed applied a expression filtering threshold to remove lowly expressed genes from the analysis, before performing eQTL mapping. Specifically, we removed genes which were detectably expressed (i.e. with at least one mapping read) in fewer than 5% of the cells. This is stated in the Methods section entitled “eQTL mapping analysis”, and we have added clarifications to make the filtering method clearer.

      (2) The methods section states that FACS sorting was used to isolate 40,000 nuclei; however, the final datasets contained only 1,394 or 7,458 nuclei. Could you provide a detailed breakdown of the losses at each step of the filtering process? As this is a key factor in the overall efficiency of the method, it would be valuable to discuss the potential for increasing throughput in future implementations. Also, how the total yield increased fivefold between repeats - could you elaborate on the factors that contributed to this improvement?

      We apologise for the lack of precision in this section of the Methods in the first draft of the manuscript. We have now updated the relevant Methods sections to include more of the concrete statistics about the preparation of nuclei samples and single-nucleus library construction. The statistic 40,000 referred to the approximate average number of “events” that we generally aim to sort using the FACS machine. We have now removed this statistic from the Methods as it does not accurately reflect the numbers of events that were sorted in the case of these two libaries, which was in fact slightly higher__.__

      For the sample used to generate the first dataset, we sorted approximately 53,000 events. Some of these may in fact represent debris, and so the true number of sorted nuclei will be less than this amount. At the time that this sample was prepared, we did not have access to a cell counter to orthogonally validate the output of the FACS machine. After sorting, the nuclei were concentrated by centrifugation before loading onto the 10x Chromium controller. Although the aim of this centrifugation step was to concentrate the nuclei, it almost certainly causes some nuclei to burst and or clump together, resulting in losses. This may explain the low recovery rate of the first dataset.

      For the sample used to generate the second dataset, we sorted approximately 55,500 events and then measured the number of nuclei after sorting using a Luna FX cell counter. According to these estimates, the total number of nuclei in the sample was around 38,250 in 135µl volume. From this, 43µl containing approximately 13,150 nuclei was loaded onto the 10x Chromium controller, without centrifugation. According to the 10x Chromium next GEM single cell 3’ v3.1 user guide, the reported recovery rate of singlet barcodes for this number of input cells/nuclei is around 53%, or 7000 nuclei, which is in line with the 7458 that we recovered.

      The difference in yield between the first and second datasets may stem from a higher quality input sample with less debris, or from the removal of the centrifugation step from our protocol. Alternatively, it may result from advances in the 10x platform, kits and technology - the first dataset was collected in 2022, whilst the second was collected in 2024. There are many technical variables that differ between the two datasets - including the individuals who performed the experiment. This means that any prediction about the cause of the difference in yield can only really be speculative.

      (3) It is unclear what happened to the vegetative nuclei during this process. While the authors attribute the differences between the first and second experiments to handling, previous studies (Schoft et al. 2015) suggest that vegetative and sperm nuclei can be distinguished in FACS analysis after DNA staining. This suggests that, for future applications, it may be possible to refine this method to specifically focus on either vegetative or sperm nuclei by adjusting the gating parameters in FACS. The inclusion of the FACS sorting graphs with the gating used as a supplementary figure would also be helpful in understanding and replicating this aspect of the methodology.

      We agree with the reviewer that some of the loss of vegetative nuclei may result from the gating stragety applied during FACS. We have added a statement clarifying this to the Results. We are now working with fluorescent reporter lines that distinguish the sperm and vegetative nuclei, to determine more appropriate gating strategies for vegetative nuclei, and hope to improve the recovery of these nuclei in the future. As suggested by the reviewer, we have added the gating strategies of the two FACS experiments as supplementary Figure 1 – figure supplement 1, and Figure 6 - figure supplement 1.

      (4) For the benefit of future users, it would be helpful to discuss the following points: (1) Would you recommend using a combination of several parents, as in the first experiment, or limiting the analysis to two parents? (e.g. it seems some of the recombination patterns could not be called due to the mix of five crosses) What are the advantages and disadvantages of each approach? (2) How should one estimate the optimal number of nuclei/cells to use? Can you downsample the nuclei and see the effects of lower numbers on identified eQTLs? (3) Given that different single-cell RNA-Seq protocols involve trade-offs between the number of cells and the number of UMIs per cell in relation to cost, what strategy would you recommend to users to optimize their experiments?

      The design of experiments depends on the research goals and budget of the project. However, we do have some recommendations for mixing of different genotypes – namely, that care must be taken to select genotypes to pool which are sufficiently genetically distinct, since genetically similar genotypes will be harder to distiguish and demultiplex correctly. Where possible, pooling is invaluable as a way to control for technical variation. When pooling is not possible due to genetically indistiguishable genotypes, then experimental design and randomisation must be considered carefully to prevent confounding. We have added some recommendations in this regard to the Discussion.

      We addressed the question of number of nuclei on the detection and resolution of eQTLs in response to Reviewer #1 point 1. __We have added a new section to the Discussion to address this question. __In general it is hard to perform power analyses prior to conducting transcriptomic experiments, because the effect size of gene expression changes of interest are generally not known in advance. More general investigations of the trade off between number of cells and number of UMIs in single-nucleus sequencing experiments have been thoroughly investigated by other groups (Svensson et al. 2017; Mandric et al. 2020).

      (5) It is not entirely clear which exact linear model was used for the association study. Specifically: (1) How were the five parents included in the model? (2) Why was it necessary to correct for population structure in this case, given the controlled crosses? (3) How was technical variation accounted for, and how were principal components derived and incorporated into the analysis? (4) What is meant by "cell type control" and were the few VN included in the analysis? To ensure clarity and reproducibility, it would be helpful to provide more detailed explanations and to explicitly state the linear equation used for fitting.

      We apologise for the confusion as to the linear model used. __We have now updated the Methods section to make this clearer and explictly included the formula of the linear model. __For an experiment containing N pooled hybrids, for each barcode the predicted genotype of Parent 2 (as the first parent was always Col-0) was included in the model using (N - 1) dummy variables, and the predicted haplotype as a set of N continuous variables (with zero representing either the Col-0 allele, and one representing the Parent 2 allele). Despite the controlled crosses, the genotype of Parent 2 has to be controlled in the equation because the mix of five hybrids is similar to population structure, i.e. haplotypes that are only found in Kar-0 are reasonably correlated in the dataset, even when these haplotypes are completely unlinked, because only nuclei from the Col-0 x Kar-0 cross can share them. Controlling for Parental genotype prevents the detection of these as spurious correlations.

      In the initial models, cell type was not explicitly controlled but was captured primarily by principal component 1 of the PCA, which was used as a covariate. The vegetative nuclei were not excluded from the analysis, but likely did not contribute strongly due to their limited number. In the models where haplotype x cell type was modelled, cell type cluster was also explicitly used as a covariate. We have updated the Methods to make these points clearer.

      (6) To my understanding, utilizing the 10X platform with the ATAC-Seq option could provide a much more accurate recombination map. This approach would allow the inclusion of SNP information from non-transcribed regions and lowly expressed genes, which are often missed with current methods. Perhaps this is a useful consideration to add to the discussion as a potential improvement for future studies?

      We indeed already mention the possibility of using single nucleus ATAC-seq for crossover analysis in the Discussion section. In addition to the theoretical improvements to the recombination mapping mentioned by the reviewer, snATAC-seq could also be used for molecular QTL mapping, to identify so-called “chromatin-accessibility” or caQTLs. A limitation however, would be reduced power for QTL mapping, due to the noisier nature of the molecular phenotype: on a single cell level, chromatin accessibility is an inherently binary phenotype, i.e. either a read is identified in a peak or it is no, but the absence of a read in a peak is not necessarily evidence that the region is closed in that cell, due to sparsity and high levels of dropouts.

      (7) Could you clarify how the five parents from the larger panel referred to in the paper were selected? What criteria were used and how might this selection affect the results or applicability of the methodology?

      The selection of the five parents in the larger panel was determined by practical considerations. We performed a large number of crosses to Col-0 using available accessions for which there were available genome assemblies, that also had similar flowering times and vernalisation requirements. Only a proportion of these crosses were successful. From the remaining hybrids we then selected five which represented geographical diversity, and that we also felt should be genetically distinct enough to demultiplex using variants. We do not see how the selection could have affected the applicability or generalisability of the methodology.

      (8) In most of the analyses using the mixture of pollen from five crosses, the data are predominantly from sperm cells. It is not clear whether VN data were explicitly removed, or whether VN data were included at any stage of the analysis of the first experiment. Given that almost all the data are from sperm nuclei, it might be more accurate to consistently refer to results from this first dataset as "sperm" rather than using terms such as "pollen nuclei" or "pollen gene expression".

      To be clear, vegetative nuclei were not specifically removed from any analyses, however due to their low number in the first dataset we did not attempt to map vegetative nucleus specific eQTLs. We have updated the Methods to make this point clearer.

      (9) As many of the cis-eQTLs result from structural variations, in some cases related to the presence or absence of the gene in question itself, and given that expression quantification is performed relative to the reference genome, could you provide statistics on the following? Specifically, how often is gene expression higher when the haplotype is from the reference parent compared to the other parents? It would be helpful to break this down into different categories of identified eQTLs (cis vs. trans, and within cis, structural variants vs. other variations). This analysis would provide an estimate of the reference bias inherent in this quantification approach.

      The reviewer is correct that there will be some reference bias when it comes eQTLs caused specifically by gene presence-absence variation, because only genes which are present in the Araport11 annotation are tested for eQTLs. This means that genes which are present in Col-0 but absent in other accessions can be identified, whereas genes that are absent in Col-0 but present in other accessions cannot. __We have added a caveating statement to the Discussion to make this clear. __In aggregate, however, we do not see a strong bias gene expression change direction amongst genes with cis-eQTLs. In the Col-0 x Db-1 cross, for example, we see that 51.3% of genes with cis-eQTLs have higher expression in Db-1 than in Col-0 (𝛘2 p = 0.53).

      (10) The authors discuss some examples of PSV1 genes in the context of the cell cycle. Could you provide additional statistical measures to support these findings, such as GO enrichment analyses for these genes?

      We performed hypergeometric test analysis to test the enrichment of cell cycle factors reported in Supplementary File IX of Van Leene et al., 2010, amongst the genes with a PSV1 trans-eQTL (Van Leene et al. 2010). Of the 501 unique genes in this list, 112 were expressed in our snRNA-seq dataset to a sufficient level to be tested for eQTLs. Of these, 33 had a mappable trans-eQTL at the PSV1 locus. This represents a statistically significant enrichment of genes annotated as involved in the cell cycle (p = 0.032). We have added this analysis to the Results section.

      (11) The crosses were grown under slightly different conditions. While I do not suggest repeating the experiment, especially as the main PSV1 result was reproducible, it would be useful to determine whether pollen collected from these two conditions show similar gene expression patterns, even in bulk. This analysis could shed light on whether pollen gene expression is relatively insensitive to these environmental variations, and whether the second trans-eQTL CPV1 is specific to plants grown in 18C.

      We agree that the combination of pollen from two temperature conditions in the second experiment is not an ideally designed experiment. We had expected that differences caused by temperature variation would be identifiable as prinicipal components in the single nucleus sequencing data, however this was not obviously the case. Unfortunately, we do not have remaining pollen material from these samples to perform bulk RNA sequencing or qPCR analysis. Although we cannot rule out a temperature effect explaining CPV1, we believe that the most likely explanation for why this was not identified in the first dataset is that it is specific to vegetative nuclei, of which there were very few in the first dataset, and also perhaps to the Col-0 x Db-1 comparison (unlike PSV1 which appears to be shared in at least Col-0 x Db-1 and Col-0 x Rubezhnoe-1 sperm nuclei), meaning that there was much less power to detect it.

      (12) "Approximately 87.4% of cis-eQTLs were specific to sperm nuclei, likely reflecting the greater statistical power for sperm. " - This claim can be checked by downsampling the number of nuclei used in the sperm analysis to the same number as in the VN.

      In principal downsampling analysis could be used to test this hypothesis, however we feel it would unnecessarily add a confusing element to the manuscript. In future we will consider performing a thorough benchmarking and power analysis of the eQTL method, however we feel this is currently out of the scope of this “proof of principle” manuscript. __We have instead opted to remove this speculative statement from the manuscript. __

      (13) "This suggests either that CPV1 affects different sets of genes in sperm and vegetative nuclei, or possibly that there are two independent variants underlying CPV1 which affect sperm and vegetative gene expression respectively" - As done with the genes affected by PSV1, can you use the data from Ichino et al. to show in which cell types the genes affected by CPV1 alleles are expressed?

      As requested, we have added a UMAP-plot for the example CPV1 trans-eQTL affected gene PLL1 showing its expression in mature vegetative nuclei, as Figure 6 – figure supplement 4C.

      (14) "DUO3 is expressed at a low level however, and is only detectable in 14.1% of Col-0 × Db-1 nuclei," - Can you pseudo-bulk the nuclei according to the haplotype of PSV1 to get a better estimate of DUO3 expression levels in each allele? Or would this be equivalent to the linear model currently used?

      As the reviewer themself states, this approach would be somewhat equivalent to the linear model approach currently used, with the downside of not being able to control for other factors such as cell type or principal components.

      (15) "studies suggesting that Arabidopsis pollen is 2C (Friedman, 1999", - To my understanding Friedman 1999 reports that sperm are stopped in the middle of S phase and thus not with 2C genomic content.

      Thank you for this correction. We have now updated this statement to read: “studies suggesting that Arabidopsis pollen has a DNA content greater than 1C”.

      (16) Could you include a heatmap showing the called recombination profiles, similar to the background colors in Fig. 2C, for all nuclei arranged by their snRNA-Seq coverage? This would provide a clearer visualization of the data distribution and the relationship between coverage and accuracy of recombination patterns calling.

      We have added a heatmap as requested as Figure 2 – figure supplement 2.

      (17) Some figures ( & captions) are missing important details or could benefit from clarification: (1) In Fig. 2B, it is not defined what the orange represents. (2) In Figs. 3A and 6A, the size of the dots is not defined. (3) Aesthetic note: In Fig. 3B, the same colors as in Fig. 3A are used, although they represent different categories. I suggest modifying the color scheme for better clarity. (4) In Fig. 4A, it is unclear what "All" refers to. (5) In the caption for Fig. 4, panels (E) and (F) are mistakenly labeled as (B) and (C).

      We thank the reviewer for these important suggestions. We address them here point-by-point:

      • In the lower panels of figure 2B, the blue and orange lines represent the marker read distributions supporting the Col-0 and parent 2 haplotypes, respectively. We have updated the figure legend to clarify this.
      • The sizes of the points in figures 3A and 6A are proportional to the LOD score of the eQTLs. We have updated the figure legends to make this clear.
      • We have altered the colours of Figure 3B (now also relabeled as Figure 3C).
      • In Figure 4A, as well as Figure 4D, Figure 4 – figure supplement 1A and Figure 5 – figure supplement 1A, the black line “All” represents the negative log10 FDR from the log ratio test of all haplotypes, i.e. whether there is an overall association between a locus and the expression of the target gene, in any or all genotypes compared to Col-0. To make this clearer, we have updated the figure legends.
      • We thank the reviewer for spotting this oversight. We have now corrected the labelling of the figure legends. Ben-David, Eyal, James Boocock, Longhua Guo, Stefan Zdraljevic, Joshua S. Bloom, and Leonid Kruglyak. 2021. “Whole-Organism EQTL Mapping at Cellular Resolution with Single-Cell Sequencing.” ELife 10 (March). https://doi.org/10.7554/eLife.65857.

      Campoy, José A., Hequan Sun, Manish Goel, Wen-Biao Jiao, Kat Folz-Donahue, Nan Wang, Manuel Rubio, et al. 2020. “Gamete Binning: Chromosome-Level and Haplotype-Resolved Genome Assembly Enabled by High-Throughput Single-Cell Sequencing of Gamete Genomes.” Genome Biology 21 (1): 306.

      Capilla-Pérez, Laia, Victor Solier, Elodie Gilbault, Qichao Lian, Manish Goel, Bruno Huettel, Joost J. B. Keurentjes, Olivier Loudet, and Raphael Mercier. 2024. “Enhanced Recombination Empowers the Detection and Mapping of Quantitative Trait Loci.” Communications Biology 7 (1): 829.

      Mandric, Igor, Tommer Schwarz, Arunabha Majumdar, Kangcheng Hou, Leah Briscoe, Richard Perez, Meena Subramaniam, et al. 2020. “Optimized Design of Single-Cell RNA Sequencing Experiments for Cell-Type-Specific EQTL Analysis.” Nature Communications 11 (1): 5504.

      Schoft, Vera K., Nina Chumak, János Bindics, Lucyna Slusarz, David Twell, Claudia Köhler, and Hisashi Tamaru. 2015. “SYBR Green-Activated Sorting of Arabidopsis Pollen Nuclei Based on Different DNA/RNA Content.” Plant Reproduction 28 (1): 61–72.

      Sun, Hequan, Wen-Biao Jiao, Kristin Krause, José A. Campoy, Manish Goel, Kat Folz-Donahue, Christian Kukat, Bruno Huettel, and Korbinian Schneeberger. 2022. “Chromosome-Scale and Haplotype-Resolved Genome Assembly of a Tetraploid Potato Cultivar.” Nature Genetics 54 (3): 342–48.

      Svensson, Valentine, Kedar Nath Natarajan, Lam-Ha Ly, Ricardo J. Miragaia, Charlotte Labalette, Iain C. Macaulay, Ana Cvejic, and Sarah A. Teichmann. 2017. “Power Analysis of Single-Cell RNA-Sequencing Experiments.” Nature Methods 14 (4): 381–87.

      Van Leene, Jelle, Jens Hollunder, Dominique Eeckhout, Geert Persiau, Eveline Van De Slijke, Hilde Stals, Gert Van Isterdael, et al. 2010. “Targeted Interactomics Reveals a Complex Core Cell Cycle Machinery in Arabidopsis Thaliana.” Molecular Systems Biology 6 (1): 397.

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      Referee #2

      Evidence, reproducibility and clarity

      In the manuscript by Parker et al, the authors developed a methodology to scale up eQTL studies using single-nucleus RNA-Seq of meiotic products using Arabidopsis thaliana pollen. Each pollen grain, collected from an F1 hybrid between two inbred lines, is haploid and contains a unique combination of the two parental genomes, effectively replacing the F2 population typically used in QTL studies. Single-nucleus RNA-Seq served as both phenotype and genotype, as it was used also to infer recombination profiles. In their experiments, the authors used a mixture of pollen from five different crosses - each between the reference Arabidopsis accession and another accession - for the first experiment, followed by a repeat of one of the original crosses in a second experiment to increase coverage and show reproducibility. They describe their approach to genotyping, performing the eQTL analysis, and describe statistics of the cis- and trans-eQTLs. In particular, they identify and discuss in detail a strong trans-eQTL on chromosome 1 that significantly and reproducibly associate with the expression of hundreds of genes. The likely candidate gene underlying this trans-eQTL is DUO3, a transcription factor known to play a role in pollen development, although the authors acknowledge that further experiments are needed to show that this is the causal variant.

      As this is a novel methodology with the potential for widespread adoption by the community, most of my comments focus on expanding the details provided about the methodology and discussing its limitations. Additional clarity of information will help to ensure its reproducibility and wider applicability.

      1. Given the sparseness of snRNA-Seq data per nucleus/cell (inherent to single cell technologies), what happens to low expressed genes? Is any filtering done? For example, in the extreme case of a gene that is either undetected or has only a single read in some nuclei, would a sufficiently large number of nuclei theoretically allow the detection of an eQTL signal for that gene? Alternatively, does this method remain inherently blind to genes expressed below a certain threshold? Please discuss these limitations and prospects.
      2. The methods section states that FACS sorting was used to isolate 40,000 nuclei; however, the final datasets contained only 1,394 or 7,458 nuclei. Could you provide a detailed breakdown of the losses at each step of the filtering process? As this is a key factor in the overall efficiency of the method, it would be valuable to discuss the potential for increasing throughput in future implementations. Also, how the total yield increased fivefold between repeats - could you elaborate on the factors that contributed to this improvement?
      3. It is unclear what happened to the vegetative nuclei during this process. While the authors attribute the differences between the first and second experiments to handling, previous studies (e.g., Schoft et al. 2015) suggest that vegetative and sperm nuclei can be distinguished in FACS analysis after DNA staining. This suggests that, for future applications, it may be possible to refine this method to specifically focus on either vegetative or sperm nuclei by adjusting the gating parameters in FACS. The inclusion of the FACS sorting graphs with the gating used as a supplementary figure would also be helpful in understanding and replicating this aspect of the methodology.
      4. For the benefit of future users, it would be helpful to discuss the following points: (1) Would you recommend using a combination of several parents, as in the first experiment, or limiting the analysis to two parents? (e.g. it seems some of the recombination patterns could not be called due to the mix of five crosses) What are the advantages and disadvantages of each approach? (2) How should one estimate the optimal number of nuclei/cells to use? Can you downsample the nuclei and see the effects of lower numbers on identified eQTLs? (3) Given that different single-cell RNA-Seq protocols involve trade-offs between the number of cells and the number of UMIs per cell in relation to cost, what strategy would you recommend to users to optimize their experiments?
      5. It is not entirely clear which exact linear model was used for the association study. Specifically: (1) How were the five parents included in the model? (2) Why was it necessary to correct for population structure in this case, given the controlled crosses? (3) How was technical variation accounted for, and how were principal components derived and incorporated into the analysis? (4) What is meant by "cell type control" and were the few VN included in the analysis? To ensure clarity and reproducibility, it would be helpful to provide more detailed explanations and to explicitly state the linear equation used for fitting.
      6. To my understanding, utilizing the 10X platform with the ATAC-Seq option could provide a much more accurate recombination map. This approach would allow the inclusion of SNP information from non-transcribed regions and lowly expressed genes, which are often missed with current methods. Perhaps this is a useful consideration to add to the discussion as a potential improvement for future studies?

      Other comments (I quoted lines from the manuscript as there were no line numbers): 7. Could you clarify how the five parents from the larger panel referred to in the paper were selected? What criteria were used and how might this selection affect the results or applicability of the methodology? 8. In most of the analyses using the mixture of pollen from five crosses, the data are predominantly from sperm cells. It is not clear whether VN data were explicitly removed, or whether VN data were included at any stage of the analysis of the first experiment. Given that almost all the data are from sperm nuclei, it might be more accurate to consistently refer to results from this first dataset as "sperm" rather than using terms such as "pollen nuclei" or "pollen gene expression". 9. As many of the cis-eQTLs result from structural variations, in some cases related to the presence or absence of the gene in question itself, and given that expression quantification is performed relative to the reference genome, could you provide statistics on the following? Specifically, how often is gene expression higher when the haplotype is from the reference parent compared to the other parents? It would be helpful to break this down into different categories of identified eQTLs (cis vs. trans, and within cis, structural variants vs. other variations). This analysis would provide an estimate of the reference bias inherent in this quantification approach. 10. The authors discuss some examples of PSV1 genes in the context of the cell cycle. Could you provide additional statistical measures to support these findings, such as GO enrichment analyses for these genes? 11. The crosses were grown under slightly different conditions. While I do not suggest repeating the experiment, especially as the main PSV1 result was reproducible, it would be useful to determine whether pollen collected from these two conditions show similar gene expression patterns, even in bulk. This analysis could shed light on whether pollen gene expression is relatively insensitive to these environmental variations, and whether the second trans-eQTL CPV1 is specific to plants grown in 18C. 12. "Approximately 87.4% of cis-eQTLs were specific to sperm nuclei, likely reflecting the greater statistical power for sperm. " - This claim can be checked by downsampling the number of nuclei used in the sperm analysis to the same number as in the VN. 13. "This suggests either that CPV1 affects different sets of genes in sperm and vegetative nuclei, or possibly that there are two independent variants underlying CPV1 which affect sperm and vegetative gene expression respectively" - As done with the genes affected by PSV1, can you use the data from Ichino et al. to show in which cell types the genes affected by CPV1 alleles are expressed? 14. "DUO3 is expressed at a low level however, and is only detectable in 14.1% of Col-0 × Db-1 nuclei," - Can you pseudo-bulk the nuclei according to the haplotype of PSV1 to get a better estimate of DUO3 expression levels in each allele? Or would this be equivalent to the linear model currently used? 15. "studies suggesting that Arabidopsis pollen is 2C (Friedman, 1999", - To my understanding Friedman 1999 reports that sperm are stopped in the middle of S phase and thus not with 2C genomic content. 16. Could you include a heatmap showing the called recombination profiles, similar to the background colors in Fig. 2C, for all nuclei arranged by their snRNA-Seq coverage? This would provide a clearer visualization of the data distribution and the relationship between coverage and accuracy of recombination patterns calling. 17. Some figures ( & captions) are missing important details or could benefit from clarification: (1) In Fig. 2B, it is not defined what the orange represents. (2) In Figs. 3A and 6A, the size of the dots is not defined. (3) Aesthetic note: In Fig. 3B, the same colors as in Fig. 3A are used, although they represent different categories. I suggest modifying the color scheme for better clarity. (4) In Fig. 4A, it is unclear what "All" refers to. (5) In the caption for Fig. 4, panels (E) and (F) are mistakenly labeled as (B) and (C).

      Schoft, Vera K., Nina Chumak, János Bindics, Lucyna Slusarz, David Twell, Claudia Köhler, and Hisashi Tamaru. 2015. "SYBR Green-Activated Sorting of Arabidopsis Pollen Nuclei Based on Different DNA/RNA Content." Plant Reproduction 28 (1): 61-72.

      Significance

      The methodology developed in this study significantly advances the feasibility of eQTL studies. The ability to easily scale up the number of individuals analyzed provides unprecedented resolution for identifying underlying alleles. In addition, because the pollen from each cross can be collected and processed together, environmental and technical variables between individuals (in this case, pollen nuclei) are tightly controlled. This advantage is underlined by the discovery of a strong trans-eQTL, which is likely to play an important role in pollen biology, and whose different alleles are spread across natural populations. I am therefore very excited about the publication of this manuscript.

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      Referee #1

      Evidence, reproducibility and clarity

      The study by Parker et al describes the innovative use of single-cell RNA sequencing to detect markers and traits of pollen. Using pollen allows detection of recombinant events allowing the ability to do quantitative trait mapping using gene expression as a trait. This led to the discovery of expected cis QTL, but there is an intriguing trans QTL as well. The trans eQTL was mapped to a candidate causal locus DUO1. This is exciting given its role in pollen development and will obviously be followed up on in future studies.

      Overall, this is an exciting technological advance that will rapidly advance our ability to map pollen traits and arguably more importantly create high density recombination maps across organisms. I realize this is a proof of principle study and the questions below are intended to improve this already strong manuscript.

      1. What is the average maker resolution in bp and cM? What numbers of nuclei would be needed to profile to gain single gene resolution in Arabidopsis?
      2. It would be great if the authors could add a discussion of how the resolution of mapping could be improved and what it would take to get there?
      3. Could this approach be feasible for species where there is not a reference genome?
      4. It is stated 67% are located with in 2Mb of a gene and technically that is is cis-, but there aren't really long range interactions in Arabidopsis (>30kb)...so are these really cis or trans? It might be worth considering how cis vs trans are defined. Basically, what is truly cis vs trans?
      5. What percent of the time was the actual crossover captured, if at all? Is this possible with snRNA-seq?
      6. How many eQTL were there per locus?
      7. How deep were the libraries sequenced and were they sequenced to saturation? In general, I did not find any sequencing summary statistics. How many reads were sequenced per library, per genotype etc, how many aligned, how many UMIs per cell, how many transcripts detected per cell. This will help give the reader a baseline for knowing what kind of quality is needed to successfully implement this strategy in their own lab.

      Referees cross-commenting

      Seems our reviews are fairly consistent and positive. Both of us would like greater transparency with the method and how it can be used by other labs.

      Significance

      The overall strength is the development of a method to map recombination using single-cell genomics of pollen. The weakness is the limitation to studying pollen traits at least for now. The other weakness is helping the reader apply this to their own research questions. This is easily addressable through updating the writing in a way that is more accessible.

    1. Author response:

      We thank the editor and the three reviewers for the positive assessment and constructive feedback on how to improve our manuscript. We greatly appreciate that our work is considered valuable to the field, the recognition of the high-resolution model we presented, and the comments on our investigation of CisA’s role in the attachment and firing mechanism of the extended assembly. It is truly gratifying to know that our study contributes to expanding the current understanding of the biology of Streptomyces and the role of these functionally diverse and fascinating bacterial nanomachines.

      We have provided specific responses to each reviewer's comments below. In summary, we intend to address the following requested revisions:

      We will expand our bioinformatic analysis of CisA and provide additional information on the oligomeric state of CisA. We will also modify the text, figures, and figure legends to improve the clarity of our work and experimental procedures.

      Some reviewer comments would require additional experimental work, some of which would involve extensive optimization of experimental conditions. Because both lead postdoctoral researchers involved in this work have now left the lab, we currently do not have the capability to perform additional experimental work.

      Reviewer #1 (Public review):

      Contractile Injection Systems (CIS) are versatile machines that can form pores in membranes or deliver effectors. They can act extra or intracellularly. When intracellular they are positioned to face the exterior of the cell and hence should be anchored to the cell envelope. The authors previously reported the characterization of a CIS in Streptomyces coelicolor, including significant information on the architecture of the apparatus. However, how the tubular structure is attached to the envelope was not investigated. Here they provide a wealth of evidence to demonstrate that a specific gene within the CIS gene cluster, cisA, encodes a membrane protein that anchors the CIS to the envelope. More specifically, they show that:

      - CisA is not required for assembly of the structure but is important for proper contraction and CIS-mediated cell death

      - CisA is associated to the membrane (fluorescence microscopy, cell fractionation) through a transmembrane segment (lacZ-phoA topology fusions in E. coli)

      - Structural prediction of interaction between CisA and a CIS baseplate component<br /> - In addition they provide a high-resolution model structure of the >750-polypeptide Streptomyces CIS in its extended conformation, revealing new details of this fascinating machine, notably in the baseplate and cap complexes.

      All the experiments are well controlled including trans-complemented of all tested phenotypes.

      One important information we miss is the oligomeric state of CisA.

      While it would have been great to test the interaction between CisA and Cis11, to perform cryo-electron microscopy assays of detergent-extracted CIS structures to maintain the interaction with CisA, I believe that the toxicity of CisA upon overexpression or upon expression in E. coli render these studies difficult and will require a significant amount of time and optimization to be performed. It is worth mentioning that this study is of significant novelty in the CIS field because, except for Type VI secretion systems, very few membrane proteins or complexes responsible for CIS attachment have been identified and studied.

      We thank this reviewer for their highly supportive and positive comments on our manuscript. We are grateful for this reviewer’s recognition of the novelty of our study, particularly in the context of membrane proteins and complexes involved in CIS attachment.

      We agree that further experimental evidence on the direct interaction between CisA and Cis11 would have strengthened our model of CisA function. However, as noted by this reviewer, this additional work is technically challenging and currently beyond the scope of this study.

      We thank Reviewer #1 for suggesting discussing the potential oligomeric state of CisA. We will perform additional AlphaFold modelling of CisA and discuss the result of this analysis in the revised manuscript.

      Reviewer #2 (Public review):

      Summary:

      The overall question that is addressed in this study is how the S. coelicolor contractile injection system (CISSc) works and affects both cell viability and differentiation, which it has been implicated to do in previous work from this group and others. The CISSc system has been enigmatic in the sense that it is free-floating in the cytoplasm in an extended form and is seen in contracted conformation (i.e. after having been triggered) mainly in dead and partially lysed cells, suggesting involvement in some kind of regulated cell death. So, how do the structure and function of the CISSc system compare to those of related CIS from other bacteria, does it interact with the cytoplasmic membrane, how does it do that, and is the membrane interaction involved in the suggested role in stress-induced, regulated cell death? The authors address these questions by investigating the role of a membrane protein, CisA, that is encoded by a gene in the CIS gene cluster in S. coelicolor. Further, they analyse the structure of the assembled CISSc, purified from the cytoplasm of S. coelicolor, using single-particle cryo-electron microscopy.

      Strengths:

      The beautiful visualisation of the CIS system both by cryo-electron tomography of intact bacterial cells and by single-particle electron microscopy of purified CIS assemblies are clearly the strengths of the paper, both in terms of methods and results. Further, the paper provides genetic evidence that the membrane protein CisA is required for the contraction of the CISSc assemblies that are seen in partially lysed or ghost cells of the wild type. The conclusion that CisA is a transmembrane protein and the inferred membrane topology are well supported by experimental data. The cryo-EM data suggest that CisA is not a stable part of the extended form of the CISSc assemblies. These findings raise the question of what CisA does.

      We thank Reviewer #2 for the overall positive evaluation of our manuscript and the constructive criticism. 

      Weaknesses:

      The investigations of the role of CisA in function, membrane interaction, and triggering of contraction of CIS assemblies, are important parts of the paper and are highlighted in the title. However, the experimental data provided to answer these questions appear partially incomplete and not as conclusive as one would expect.

      We acknowledge that some aspects of our work have not been fully answered. We believe that providing additional experimental data is currently beyond the scope of this study. To improve this study, we will modify the text and clarify experimental procedures and figures where possible in the revised version of our manuscript.

      The stress-induced loss of viability is only monitored with one method: an in vivo assay where cytoplasmic sfGFP signal is compared to FM5-95 membrane stain. Addition of a sublethal level of nisin lead to loss of sfGFP signal in individual hyphae in the WT, but not in the cisA mutant (similarly to what was previously reported for a CIS-negative mutant). Technically, this experiment and the example images that are shown give rise to some concern. Only individual hyphal fragments are shown that do not look like healthy and growing S. coelicolor hyphae. Under the stated growth conditions, S. coelicolor strains would normally have grown as dense hyphal pellets. It is therefore surprising that only these unbranched hyphal fragments are shown in Fig. 4ab.

      We thank Reviewer #2 for their thoughtful criticism regarding our stress-induced viability assay and the data presented in Figure 4. We acknowledge the importance of ensuring that the presented images should reflect the physiological state of S. coelicolor under the stated growth conditions and recognize that hyphal fragments shown in Figure 4 do not fully capture the typical morphology of S. coelicolor. As pointed out by this reviewer, S. coelicolor grows in large hyphal clumps when cultured in liquid media, making the quantification of fluorescence intensities in hyphae expressing cytoplasmic GFP and stained with the membrane dye FM5-95 particularly challenging. To improve the image analysis and quantification of GFP and FM5-95-fluorescent intensities across the three S. coelicolor strains (wildtype, cisA deletion mutant and the complemented cisA mutant), we vortexed the cell samples briefly before imaging to break up hyphal clumps, increasing hyphal fragments. The hyphae shown in our images were selected as representative examples across three biological replicates. 

      Further, S. coelicolor would likely be in a stationary phase when grown 48 h in the rich medium that is stated, giving rise to concern about the physiological state of the hyphae that were used for the viability assay. It would be valuable to know whether actively growing mycelium is affected in the same way by the nisin treatment, and also whether the cell death effect could be detected by other methods.

      The reasoning behind growing S. coelicolor for 48 h before performing the fluorescence-based viability assay was that we (DOI: 10.1038/s41564-023-01341-x ) and others (e.g.: DOI: 10.1038/s41467-023-37087-7 ) previously showed that the levels of CIS particles peak at the transition from vegetative to reproductive/stationary growth, thus indicating that CIS activity is highest during this growth stage. The obtained results in this manuscript are in agreement with our previous study, in which we showed a similar effect on the viability of wildtype versus cis-deficient S. coelicolor strains (DOI: 10.1038/s41564-023-01341-x ) using nisin, the protonophore CCCP and UV light, and supported by biological replicate experiments and appropriate controls. Furthermore, our results are in agreement with the findings reported in a complementary study by Vladimirov et al. (DOI: 10.1038/s41467-023-37087-7 ) that used a different approach (SYTO9/PI staining of hyphal pellets) to demonstrate that CIS-deficient mutants exhibit decreased hyphal death. We agree that it would be interesting to test if actively growing hyphae respond differently to nisin treatment, and such experiments will be considered in future work. 

      Taken together, we believe that the results obtained from our fluorescence-based viability assay are consistent with data reported by others and provide strong experimental evidence that functional CIS mediate hyphal cell death. 

      The model presented in Fig. 5 suggests that stress leads to a CisA-dependent attachment of CIS assemblies to the cytoplasmic membrane, and then triggering of contraction, leading to cell death. This model makes testable predictions that have not been challenged experimentally. Given that sublethal doses of nisin seem to trigger cell death, there appear to be possibilities to monitor whether activation of the system (via CisA?) indeed leads to at least temporally increased interaction of CIS with the membrane.

      We thank this reviewer for their suggestions on how to test our model further. In the meantime, we have performed co-immunoprecipitation experiments using S. coelicolor cells that produced CisA-FLAG as bait and were treated with a sub-lethal nisin concentration for 0/15/45 min.  Mass spectrometry analysis of co-eluted peptides did not show the presence of CIS-associated peptides. While we cannot exclude the possibility that our experimental assay requires further optimization to successfully demonstrate a CisA-CIS interaction (e.g. optimization of the use of detergents to improve the solubilization of CisA from Streptomyces membrane, which is currently not an established method), an alternative and equally valid hypothesis is that the interaction between CIS particles and CisA is transient and therefore difficult to capture. We would like to mention that we did detect CisA peptides in crude purifications of CIS particles from nisin-stressed cells (Supplementary Table 2, manuscript: line 265/266), supporting our model that CisA associates with CIS particles in vivo.

      Further, would not the model predict that stress leads to an increased number of contracted CIS assemblies in the cytoplasm? No clear difference in length of the isolated assemblies if Fig. S7 is seen between untreated and nisin-exposed cells, and also no difference between assemblies from WT and cisA mutant hyphae.

      The reviewer is correct that there is no clear difference in length in the isolated CIS particles shown in Figure S7. This is in line with our results, which show that CisA is not required for the correct assembly of CIS particles and their ability to contract in the presence and absence of nisin treatment. The purpose of Figure S7 was to support this statement. We would like to note that the particles shown in Figure S7 were purified from cell lysates using a crude sheath preparation protocol, during which CIS particles generally contract irrespective of the presence or absence of CisA. Thus, we cannot comment on whether there is an increased number of contracted CIS assemblies in the cytoplasm of nisin-exposed cells. To answer this point, we would need to acquire additional cryo-electron tomograms (cyroET) of the different strains treated with nisin. We appreciate this reviewer's suggestions. However, cryoET is an extremely time and labour-intensive task, and given that we currently don’t know the exact dynamics of the CIS-CisA interaction following exogenous stress, we believe this experiment is beyond the scope of this work.

      The interaction of CisA with the CIS assembly is critical for the model but is only supported by Alphafold modelling, predicting interaction between cytoplasmic parts of CisA and Cis11 protein in the baseplate wedge. An experimental demonstration of this interaction would have strengthened the conclusions.

      We agree that direct experimental evidence of this interaction would have further strengthened the conclusions of our study, and we have extensively tried to provide additional experimental evidence. Unfortunately, due to the toxicity of CisA expression in E. coli and the transient nature of the interaction under our experimental conditions, we were unable to pursue direct biochemical or biophysical validation methods, such as co-purification or bacterial two-hybrid assays. While these challenges limited our ability to experimentally confirm the interaction, the AlphaFold predictions provided a valuable hypothesis and mechanistic insight into the role of CisA.

      The cisA mutant showed a similarly accelerated sporulation as was previously reported for CIS-negative strains, which supports the conclusion that CisA is required for function of CISSc. But the results do not add any new insights into how CIS/CisA affects the progression of the developmental life cycle and whether this effect has anything to do with the regulated cell death that is caused by CIS. The same applies to the effect on secondary metabolite production, with no further mechanistic insights added, except reporting similar effects of CIS and CisA inactivations.

      We thank this reviewer for their thoughtful feedback and for highlighting the connections between CisA, CIS function, and their effects on the developmental life cycle and secondary metabolite production in S. coelicolor. The main focus of this study was to provide further insight into how CIS contraction and firing are mediated in Streptomyces, and we used the analysis of accelerated sporulation and secondary metabolite production to assess the functionality of CIS in the presence or absence of CisA.

      We agree that we still don’t fully understand the nature of the signals that trigger CIS contraction, but we do know that the production of CIS assemblies seems to be an integral part of the Streptomyces multicellular life cycle as demonstrated in two independent previous studies (DOI: 10.1038/s41564-023-01341-x and DOI: 10.1038/s41467-023-37087-7 ). We propose that the assembly and firing of Streptomyces CIS particles could present a molecular mechanism to sacrifice only a part of the mycelium to either prevent the spread of local cellular damage or to provide additional nutrients for the rest of the mycelium and delay the terminal differentiation into spores and affect the production of secondary metabolites.

      We recognize the importance of understanding the regulation and mechanistic details underpinning the proposed CIS-mediated regulated cell death model. This will be further explored in future studies.

      Concluding remarks:

      The work will be of interest to anyone interested in contractile injection systems, T6SS, or similar machineries, as well for people working on the biology of streptomycetes. There is also a potential impact of the work in the understanding of how such molecular machineries could have been co-opted during evolution to become a mechanism for regulated cell death. However, this latter aspect remains still poorly understood. Even though this paper adds excellent new structural insights and identifies a putative membrane anchor, it remains elusive how the Streptomyces CIS may lead to cell death. It is also unclear what the advantage would be to trigger death of hyphal compartments in response to stress, as well as how such cell death may impact (or accelerate) the developmental progression. Finally, it is inescapable to wonder whether the Streptomyces CIS could have any role in protection against phage infection.

      We thank Reviewer #2 for their supportive assessment of our work. In the revised manuscript, we will briefly discuss the impact of functional CIS assemblies on Streptomyces development. We previously tested if Streptomyces could defend against phages but have not found any experimental evidence to support this idea. The analysis of phage defense mechanisms is an underdeveloped area in Streptomyces research, partly due to the currently limited availability of a diverse phage panel.

      Reviewer #3 (Public review):

      Summary:

      In this work, Casu et al. have reported the characterization of a previously uncharacterized membrane protein CisA encoded in a non-canonical contractile injection system of Streptomyces coelicolor, CISSc, which is a cytosolic CISs significantly distinct from both intracellular membrane-anchored T6SSs and extracellular CISs. The authors have presented the first high-resolution structure of extended CISSc structure. It revealed important structural insights in this conformational state. To further explore how CISSc interacted with cytoplasmic membrane, they further set out to investigate CisA that was previously hypothesized to be the membrane adaptor. However, the structure revealed that it was not associated with CISSc. Using fluorescence microscope and cell fractionation assay, the authors verified that CisA is indeed a membrane-associated protein. They further determined experimentally that CisA had a cytosolic N-terminal domain and a periplasmic C-terminus. The functional analysis of cisA mutant revealed that it is not required for CISSc assembly but is essential for the contraction, as a result, the deletion significantly affects CISSc-mediated cell death upon stress, timely differentiation, as well as secondary metabolite production. Although the work did not resolve the mechanistic detail how CisA interacts with CISSc structure, it provides solid data and a strong foundation for future investigation toward understanding the mechanism of CISSc contraction, and potentially, the relation between the membrane association of CISSc, the sheath contraction and the cell death.

      Strengths:

      The paper is well-structured, and the conclusion of the study is supported by solid data and careful data interpretation was presented. The authors provided strong evidence on (1) the high-resolution structure of extended CISSc determined by cryo-EM, and the subsequent comparison with known eCIS structures, which sheds light on both its similarity and different features from other subtypes of eCISs in detail; (2) the topological features of CisA using fluorescence microscopic analysis, cell fractionation and PhoA-LacZα reporter assays, (3) functions of CisA in CISSc-mediated cell death and secondary metabolite production, likely via the regulation of sheath contraction.

      Weaknesses:

      The data presented are not sufficient to provide mechanistic details of CisA-mediated CISSc contraction, as authors are not able to experimentally demonstrate the direct interaction between CisA with baseplate complex of CISSc (hypothesized to be via Cis11 by structural modeling), since they could not express cisA in E. coli due to its potential toxicity. Therefore, there is a lack of biochemical analysis of direct interaction between CisA and baseplate wedge. In addition, there is no direct evidence showing that CisA is responsible for tethering CISSc to the membrane upon stress, and the spatial and temporal relation between membrane association and contraction remains unclear. Further investigation will be needed to address these questions in future.

      We thank Reviewer #3 for the supportive evaluation and constructive criticism of our study in the public and non-public review. We appreciate your recognition of the technical limitations of experimentally demonstrating a direct interaction between CisA and CIS baseplate complex, and we agree that further investigations in the future will hopefully provide a full mechanistic understanding of the spatiotemporal interaction of CisA and CIS particular and the subsequent CIS firing.

      To further improve the manuscript, we will revise the text and clarify figures and figure legends as suggested in the non-public review.

      Discussion:

      Overall, the work provides a valuable contribution to our understanding on the structure of a much less understood subtype of CISs, which is unique compared to both membrane-anchored T6SSs and host-membrane targeting eCISs. Importantly, the work serves as a good foundation to further investigate how the sheath contraction works here. The work contributes to expanding our understanding of the diverse CIS superfamilies.

      Thank you.

    1. Reviewer #1 (Public review):

      Summary:

      Carter et al. present the eduWOSM imaging platform, a promising development in open-source microscopy for educational purposes. The paper outlines the construction and setup of this versatile microscope, demonstrating its capabilities through three key examples: single fluorophore tracking of tubulin heterodimers in gliding microtubules, 4D deconvolution imaging and tracking of chromosome movements in dividing human cells, and automated single-particle tracking in vitro and in live cells, with motion classified into sub-diffusive, diffusive, and super-diffusive behaviors.

      The paper is well-written and could be strengthened by providing more empirical data on its performance, addressing potential limitations, and offering detailed insights into its educational impact. The project holds great potential and more discussion on long-term support and broader applications would provide a more comprehensive view of its relevance in different contexts.

      Strengths:

      (1) The eduWOSM addresses a crucial need in education, providing research-quality imaging at a lower cost (<$10k). The fact that it is open-source adds significant value, enabling broad accessibility even in under resourced areas.<br /> (2) There is availability of extensive resources, including a dedicated website, YouTube channel, and comprehensive tutorial guides to help users replicate the microscope.<br /> (3) The compact, portable, and stable design makes it easy to build multiple systems for use in diverse environments, including crowded labs and classrooms. This is further enhanced by the fact multiple kind of imaging experiments can be run on the system, from live imaging to super-resolution imaging.<br /> (4) The paper highlights the user-friendly nature of the platform, with the imaging examples in the paper being acquired by undergrad students.

      Weaknesses:

      (1) The paper mentions the microscope is suitable not just for education but even for research purposes. This claim needs validation through quantitative comparison to existing research-grade microscopes in terms of resolution, signal-to-noise ratio, and other key metrics. Adding more rigorous comparisons would solidify its credibility for research use, which would immensely increase the potential of the microscope.<br /> (2) The open-source microscope field is crowded with various options catering to hobby, educational, and research purposes (e.g., openFLexure, Flamingo, Octopi, etc.). The paper would benefit from discussing whether any aspects set the eduWOSM platform apart or fulfill specific roles that other microscopes do not.<br /> (3) While the eduWOSM platform is designed to be user-friendly, the paper would benefit from discussing whether the microscope can be successfully built and operated by users without direct help from the authors. It's important to know if someone with basic technical knowledge, relying solely on the provided resources (website, YouTube tutorials, and documentation), can independently assemble, calibrate, and operate the eduWOSM.<br /> (4) Ensuring long-term support and maintenance of the platform is crucial. The paper would benefit from addressing how the eduWOSM developers plan to support updates, improvements, or troubleshooting.

    1. Cette transcription d'une conférence au Collège de France explore les stratégies éducatives familiales, mettant l'accent sur la socialisation culturelle plutôt que sur l'éducation scolaire.

      L'intervenant analyse trois piliers de cette socialisation : les objets culturels, les interactions parents-enfants, et l’exemple parental.

      Il souligne les inégalités et les discriminations liées à l’accès à la culture, notamment en ce qui concerne l’usage des écrans et les pratiques culturelles extra-scolaires.

      Enfin, il compare deux modèles éducatifs contrastés, la concerted cultivation et le natural growth, pour illustrer la diversité des approches parentales et leur impact sur le parcours scolaire des enfants.

      Sommaire minuté des points forts:

      Introduction (0:00 - 2:30):

      • Le sujet abordé est celui des pratiques culturelles des enfants et comment elles éclairent les stratégies éducatives des parents.
      • La perspective adoptée s'éloigne de l'éducation institutionnelle pour se concentrer sur la socialisation, un ensemble de pratiques incluant l'éducation mais qui la dépasse.
      • Il y a une confrontation entre le "métier d'enfant" et le "métier d'élève", qui ont des impératifs et des cadres différents.
      • L'exposé se centrera sur la socialisation culturelle familiale, notamment le rôle des parents.

      Les piliers de la socialisation culturelle (2:30 - 4:45):

      • Trois piliers sont généralement distingués: le système des objets (culture matérielle), les interactions éducatives avec les parents et les exemples parentaux.
      • L'accès aux objets culturels et les autorisations d'accès données aux enfants sont des éléments importants des stratégies éducatives.
      • Les interactions éducatives incluent les dynamiques relationnelles, les pratiques d'occupation du temps et les représentations de l'enfant et de la "bonne parentalité".
      • Les exemples parentaux, bien que moins documentés, définissent un champ des possibles pour les enfants.
      • Ces trois piliers construisent des "climats familiaux", qui peuvent être compris comme des stratégies de fait, sans intention éducative prégnante.

      Contexte actuel et particularités (4:45 - 7:30):

      • Le contexte actuel se caractérise par une forte emprise scolaire, avec une centralité de l'école dans la validation des compétences et le classement des individus.
      • Cette centralité crée un paradoxe douloureux dans un contexte de crispation économique et d'inflation des diplômes.
      • Il y a une forte pression à la "bonne parentalité", alimentée par un nombre croissant de rapports et de normes sociales.
      • Les discours de légitimation pour les loisirs, notamment culturels, avancent masqués et mettent en avant l'épanouissement personnel pour masquer des objectifs de bénéfices scolaires.

      Exemples d'activités et analyse (7:30 - 19:00):

      • Enfants et écrans:

      Les discours sur les écrans sont à charge et mettent l'accent sur les risques.

      L'usage réel des écrans est très différent des normes institutionnelles, servant à la régulation des temps et à l'intégration linguistique et sociale.

      • Langage et lecture:

      L'oralité est privilégiée dans les catégories peu diplômées, tandis que les catégories plus diplômées favorisent le livre.

      Les pères accentuent les différences dans les pratiques. Les enfants d'immigrés se mettent à lire moins malgré une plus grande exposition à l'oralité.

      • Pratiques en amateur:

      Les clubs et associations sont choisis pour doter les enfants de ressources éducatives, développer des passions et créer des liens sociaux.

      Ces activités sont très genrées et les parents les plus investis sont ceux qui ont le plus de capitaux scolaires.

      • Ecrans (suite):

      Les enfants des fractions intellectuelles accèdent aux écrans numériques plus tard, illustrant une stratégie d'effet retard.

      L'entrée à l'école renforce les normes institutionnelles et impacte différemment les fractions de la population.

      Conclusion (19:00 - 21:00):

      • Il faut déconstruire la normativité présente dans les discours sur les stratégies éducatives.
      • Les stratégies éducatives des familles populaires, même si elles diffèrent des normes institutionnelles, sont des tentatives positives d'émancipation.
      • Il faut distinguer deux modèles éducatifs: la "concerted cultivation" (culture concertée) et le "Natural growth" (croissance naturelle).
      • Ces deux modèles produisent des enfants qui ne s'autorisent pas de la même manière à parler aux adultes dans les institutions, avec des effets sur la scolarité.

      Points clés à retenir:

      • Différences de stratégies éducatives selon le milieu social:

      Les pratiques culturelles et l'accès aux objets culturels varient fortement selon le capital culturel et la position sociale des familles.

      • Rôle des exemples parentaux: Les pratiques des parents, même non intentionnelles, ont un impact majeur sur les trajectoires des enfants.

      • Impact des normes institutionnelles:

      L'école joue un rôle central dans la validation des compétences et la diffusion de normes, ce qui influence les pratiques familiales. * Diversité des stratégies éducatives:

      Il n'existe pas de "bonne" stratégie universelle, chaque famille met en place des pratiques qui répondent à son contexte et à ses aspirations.

    1. Reviewer #2 (Public review):

      Summary:

      The authors present a paper that attempts to tackle an important question, with potential impact far beyond the field of animal behavior research: what are the relative contributions of innate personality traits versus early life experience on individual behavior in the wild? The study, performed on Egyptian fruit bats that are caught in the wild and later housed in an outdoor colony, is solidly executed, and benefits greatly from a unique setup in which controlled laboratory experiments are combined with monitoring of individuals as they undertake undirected, free exploration of their natural environment.

      The primary finding of the paper is that there is a strong effect of early life experience on behavior in the wild, where individual bats that were exposed to an enriched environment as juveniles later travelled farther and over greater distances when permitted to explore and forage ad libitum, as compared with individual bats who were subjected to a more impoverished environment. Meanwhile, no prominent effect of innate "personality", as assessed by indices of indoor foraging behavior early on, before the bats were exposed to the controlled environmental treatment, was observed on three metrics of outdoor foraging behavior. The authors conclude that the early environment plays a larger role than innate personality on the behavior of adult bats.

      Strengths:

      (1) Elegant design of experiments and impressive combination of methods<br /> Bats used in the experiment were taken from wild colonies in different geographical areas, but housed during the juvenile stage in a controlled indoor environment. Bats are tested on the same behavioral paradigm at multiple points in their development. Finally, the bats are monitored with GPS as they freely explore the area beyond the outdoor colony.

      (2) Development of a behavioral test that yields consistent results across time<br /> The multiple-foraging box paradigm, in which behavioral traits such as overall activity, levels of risk-taking, and exploratoriness can be evaluated as creative, and suggestive of behavioral paradigms other animal behavior researchers might be able to use. It is especially useful, given that it can be used to evaluate the activity of animals seemingly at most stages of life, and not just in adulthood.

      Weaknesses:

      (1) Robustness and validity of personality measures<br /> Coming up with robust measures of "personality" in non-human animals is tricky. While this paper represents an important attempt at a solution, some of the results obtained from the indoor foraging paradigm raise questions as to the reliability of this task for assessing "personality".

      (2) Insufficient exploitation of data<br /> Between the behavioral measures and the very multidimensional GPS data, the authors are in possession of a rich data set. However, I don't feel that this data has been adequately exploited for underlying patterns and relationships. For example, many more metrics could be extracted from the GPS data, which may then reveal correlations with early measures of personality or further underscore the role of the early environment. In addition, the possibility that these personality measures might in combination affect outdoor foraging is not explored.

      (3) Interpretation of statistical results and definition of statistical models<br /> Some statistical interpretations may not be entirely accurate, particularly in the case of multiple regression with generalized linear models. In addition, some effects which may be present in the data are dismissed as not significant on the basis of null hypothesis testing.

      Below I have organized the main points of critique by theme, and ordered subordinate points by order of importance:

      (1) Assessing personality metrics and the indoor paradigm: While I applaud this effort and think the metrics used are justified, I see a few issues in the results as they are currently presented:<br /> (a) [Major] I am somewhat concerned that here, the foraging box paradigm is being used for two somewhat conflicting purposes: (1) assessing innate personality and (2) measuring changes in personality as a result of experience. If the indoor foraging task is indeed meant to measure and reflect both at the same time, then perhaps this can be made more explicit throughout the manuscript. In this circumstance, I think the authors could place more emphasis on the fact that the task, at later trials/measurements, begins to take on the character of a "composite" measure of personality and experience.

      (b) [Major] Although you only refer to results obtained in trials 1 and 2 when trying to estimate "innate personality" effects, I am a little worried that the paradigm used to measure personality, i.e. the stable components of behavior, is itself affected by other factors such as age (in the case of activity, Fig. 1C3, S1C1-2), the environment (see data re trial 3), and experience outdoors (see data re trials 4/5).

      Ideally, a study that aims to disentangle the role of predisposition from early-life experience would have a metric for predisposition that is relatively unchanging for individuals, which can stand as a baseline against a separate metric that reflects behavioral differences accumulated as a result of experience.

      I would find it more convincing that the foraging box paradigm can be used to measure personality if it could be shown that young bats' behavior was consistent across retests in the box paradigm prior to any environmental exposure across many baseline trials (i.e. more than 2), and that these "initial settings" were constant for individuals. I think it would be important to show that personality is consistent across baseline trials 1 and 2. This could be done, for example, by reproducing the plots in Fig. 1C1-3 while plotting trial 1 against trial 2. (I would note here that if a significant, positive correlation were to be found (as I would expect) between the measures across trial 1 and 2, it is likely that we would see the "habituation effect" the authors refer to expressed as a steep positive slope on the correlation line (indicating that bold individuals on trial 1 are much bolder on trial 2).)

      (c) Related to the previous point, it was not clear to me why the data from trial 2 (the second baseline trial) was not presented in the main body of the paper, and only data from trial 1 was used as a baseline.

      In the supplementary figure and table, you show that the bats tended to exhibit more boldness and exploratory behavior, but fewer actions, in trial 2 as compared with trial 1. You explain that this may be due to habituation to the experimental setup, however, the precise motivation for excluding data from trial 2 from the primary analyses is not stated. I would strongly encourage the authors to include a comparison of the data between the baseline trials in their primary analysis (see above), combine the information from these trials to form a composite baseline against which further analyses are performed, or further justify the exclusion of data as a baseline.

      (2) Comparison of indoor behavioral measures and outdoor behavioral measures<br /> Regarding the final point in the results, correlation between indoor personality on Trial 4 and outdoor foraging behavior: It is not entirely clear to me what is being tested (neither the details of the tests nor the data or a figure are plotted). Given some of the strong trends in the data - namely, (1) how strongly early environment seems to affect outdoor behavior, (2) how strongly outdoor experience affects boldness, measured on indoor behavior (Fig. 1D) - I am not convinced that there is no relationship, as is stated here, between indoor and outdoor behavior. If this conclusion is made purely on the basis of a p-value, I would suggest revisiting this analysis.

      (3) Use of statistics/points regarding the generalized linear models<br /> While I think the implementation of the GLMM models is correct, I am not certain that the interpretation of the GLMM results is entirely correct for cases where multivariate regression has been performed (Tables 4s and S1, and possibly Table 3). (You do not present the exact equation they used for each model (this would be a helpful addition to the methods), therefore it is somewhat difficult to evaluate if the following critique properly applies, however...)

      The "estimate" for a fixed effect in a regression table gives the difference in the outcome variable for a 1 unit increase in the predictor variable (in the case of numeric predictors) or for each successive "level" or treatment (in the case of categorical variables), compared to the baseline, the intercept, which reflects the value of the outcome variable given by the combination of the first value/level of all predictors. Therefore, for example, in Table 4a - Time spend outside: the estimate for Bat sex: male indicates (I believe) the difference in time spent outside for an enriched male vs. an enriched female, not, as the authors seem to aim to explain, the effect of sex overall. Note that the interpretation of the first entry, Environmental condition: impoverished, is correct. I refer the authors to the section "Multiple treatments and interactions" on p. 11 of this guide to evaluating contrasts in G/LMMS: https://bbolker.github.io/mixedmodels-misc/notes/contrasts.pdf

    1. Reviewer #3 (Public review):

      In this manuscript, Natarajan and colleagues report on the role of a prophage, termed SfPat, in the regulation of motility and biofilm formation by the marine bacterium Shewanella fidelis. The authors investigate the in vivo relevance of prophage carriage by studying the gut occupation patterns of Shewanella fidelis wild-type and an isogenic SfPat- mutant derivative in a model organism, juveniles of the marine tunicate Ciona robusta. The role of bacterial prophages in regulating bacterial lifestyle adaptation and niche occupation is a relatively underexplored field, and efforts in this direction are appreciated.

      While the research question is interesting, the work presented lacks clarity in its support for several major claims, and, at times, the authors do not adequately explain their data.

      Major concerns:

      (1) Prophage deletion renders the SfPat- mutant derivative substantially less motile and with a higher biofilm formation capacity than the WT (Fig. 2a-b). The authors claim the mutant is otherwise isogenic to the WT strain upon sequence comparison of draft genome sequences (I'll take the opportunity to comment here that GenBank accessions are preferable to BioSample accessions in Table 1). Even in the absence of secondary mutations, complementation is needed to validate functional associations (i.e., phenotype restoration). A strategy for this could be phage reintegration into the mutant strain (PMID: 19005496).

      (2) The authors claim that the downshift in motility (concomitant with an upshift in biofilm formation) is likely mediated by the activity of c-di-GMP turnover proteins. Specifically, the authors point to the c-di-GMP-specific phosphodiesterase PdeB as a key mediator, after finding lower transcript levels for its coding gene in vivo (lines 148-151, Fig. 2c), and suggesting higher activity of this protein in live animals (!)(line 229). I have several concerns here:<br /> (2.1) Findings shown in Fig. 2a-b are in vitro, yet no altered transcript levels for pdeB were recorded (Fig. 2c). Why do the authors base their inferences only on in vivo data?<br /> (2.2) Somewhat altered transcript levels alone are insufficient for making associations, let alone solid statements. Often, the activity of c-di-GMP turnover proteins is local and/or depends on the activation of specific sensory modules - in the case of PdeB, a PAS domain and a periplasmic sensor domain (PMID: 35501424). This has not been explored in the manuscript, i.e., specific activation vs. global alterations of cellular c-di-GMP pools (or involvement of other proteins, please see below). Additional experiments are needed to confirm the involvement of PdeB. Gaining such mechanistic insights would greatly enhance the impact of this study.<br /> (2.3) What is the rationale behind selecting only four genes to probe the influence of the prophage on Ciona gut colonization by determining their transcript levels in vitro and in vivo? If the authors attribute the distinct behavior of the mutant to altered c-di-GMP homeostasis, as may be plausible, why did the authors choose those four genes specifically and not, for example, the many other c-di-GMP turnover protein-coding genes or c-di-GMP effectors present in the S. fidelis genome? This methodological approach seems inadequate to me, and the conclusions on the potential implication of PdeB are premature.

      (3) The behavior of the WT strain and the prophage deletion mutant is insufficiently characterized. For instance, how do the authors know that the higher retention capacity reported for the WT strain with respect to the mutant (Fig. 3b) is not merely a consequence of, e.g., a higher growth rate? It would be worth investigating this further, ideally under conditions reflecting the host environment.

      (4) Related to the above, sometimes the authors refer to "retention" (e.g., line 162) and at other instances to "colonization" (e.g., line 161), or even adhesion (line 225). These are distinct processes. The authors have only tracked the presence of bacteria by fluorescence labeling; adhesion or colonization has not been assessed or demonstrated in vivo. Please revise.

      (5) The higher CFU numbers for the WT after 24 h (line 161) might also indicate a role of motility for successful niche occupation or dissemination in vivo. The authors could test this hypothesis by examining the behavior of, e.g., flagellar mutants in their in vivo model.

      (6) The endpoint of experiments with a mixed WT-mutant inoculum (assumedly 1:1? Please specify) was set to 1 h, I assume because of the differences observed in CFU counts after 24 h. In vivo findings shown in Fig. 3c-e are, prima facie, somewhat contradictory. The authors report preferential occupation of the esophagus by the WT (line 223), which seems proficient from evidence shown in Fig. S3. Yet, there is marginal presence of the WT in the esophagus in experiments with a mixed inoculum (Fig. 3d) or none at all (Fig. 3e). Likewise, the authors claim preferential "adhesion to stomach folds" by the mutant strain (line 225), but this is not evident from Fig. 3e. In fact, the occupation patterns by the WT and mutant strain in the stomach in panel 3e appear to differ from what is shown in panel 3d. The same holds true for the claimed "preferential localization of the WT in the pyloric cecum," with Fig. 3d showing a yellow signal that indicates the coexistence of WT and mutant.

      (7) In general, and especially for in vivo data, there is considerable variability that precludes drawing conclusions beyond mere trends. One could attribute such variability in vivo to the employed model organism (which is not germ-free), differences between individuals, and other factors. This should be discussed more openly in the main text and presented as a limitation of the study. Even with such intrinsic factors affecting in vivo measurements, certain in vitro experiments, which are expected, in principle, to yield more reproducible results, also show high variability (e.g., Fig. 5). What do the authors attribute this variability to?

      (8) Line 198-199: Why not look for potential prophage excision directly rather than relying on indirect, presumptive evidence based on qPCR?

    1. Reviewer #1 (Public review):

      Summary:

      This is an interesting theoretical study examining the viability of Virtual Circular Genome (VCG) model, a recently proposed scenario of prebiotic replication in which a relatively long sequence is stored as a collection of its shorter subsequences (and their compliments). It was previously pointed out that VCG model is prone to so-called sequence scrambling which limits the overall length of such a genome. In the present paper, additional limitations are identified. Specifically, it is shown that VCG is well replicated when the oligomers are elongated by sufficiently short chains from "feedstock" pool. However, ligation of oligomers from VCG itself results in a high error rate. I believe the research is of high quality and well written. However, the presentation could be improved and the key messages could be clarified.

      (1) It is not clear from the paper whether the observed error has the same nature as sequence scrambling<br /> (2) The authors introduce two important lengths LS1 and LS2 only in the conclusions and do not explain enough which each of them is important. It would make sense to discuss this early in the manuscript.<br /> (3) It is not entirely clear why specific length distribution for VCG oligomers has to be assumed rather than emerged from simulations.<br /> (4) Furthermore, the problem has another important length, L0 that is never introduced or discussed: a minimal hybridization length with a lifetime longer than the ligation time. From the parameters given, it appears that L0 is sufficiently long (~10 bases). In other words, it appears that the study is done is a somewhat suboptimal regime: most hybridization events do not lead to a ligation. Am I right in this assessment? If that is the case, the authors might want to explore another regime, L0<br /> Strengths:

      High-quality theoretical modeling of an important problem is implemented.

      Weaknesses:

      The conclusions are somewhat convoluted and could be presented better.

    1. Reviewer #1 (Public review):

      Summary:

      Persistence is a phenomenon by which genetically susceptible cells are able to survive exposure to high concentrations of antibiotics. This is especially a major problem when treating infections caused by slow growing mycobacteria such as M. tuberculosis and M. abscessus. Studies on the mechanisms adopted by the persisting bacteria to survive and evade antibiotic killing can potentially lead to faster and more effective treatment strategies.

      To address this, in this study, the authors have used a transposon mutagenesis based sequencing approach to identify the genetic determinants of antibiotic persistence in M. abscessus. To enrich for persisters they employed conditions, that have been reported previously to increase persister frequency - nutrient starvation, to facilitate genetic screening for this phenotype. M.abs transposon library was grown in nutrient rich or nutrient depleted conditions and exposed to TIG/LZD for 6 days, following which Tn-seq was carried out to identify genes involved in spontaneous (nutrient rich) or starvation-induced conditions. About 60% of the persistence hits were required in both the conditions. Pathway analysis revealed enrichment for genes involved in detoxification of nitrosative, oxidative, DNA damage and proteostasis stress. The authors then decided to validate the findings by constructing deletions of 5 different targets (pafA, katG, recR, blaR, Mab_1456c) and tested the persistence phenotype of these strains. Rather surprisingly only 2 of the 5 hits (katG and pafA) exhibited a persistence defect when compared to wild type upon exposure to TIG/LZD and this was complemented using an integrative construct. The authors then investigated the specificity of delta-katG susceptibility against different antibiotic classes and demonstrated increased killing by rifabutin. The katG phenotype was shown to be mediated through the production of oxidative stress which was reverted when the bacterial cells were cultured under hypoxic conditions. Interestingly, when testing the role of katG in other clinical strains of Mab, the phenotype was observed only in one of the clinical strains demonstrating that there might be alternative anti-oxidative stress defense mechanisms operating in some clinical strains.

      Strengths:

      While the role of ROS in antibiotic mediated killing of mycobacterial cells have been studied to some extent, this paper presents some new findings with regards to genetic analysis of M. abscessus susceptibility, especially against clinically used antibiotics, which makes it useful. Also, the attempts to validate their observations in clinical isolates is appreciated.

      Weaknesses:

      - Fig. 3 - 5 of the hits from the transposon screen were reconstructed as clean deletion strains and tested for persistence. However, only 1 (katG) gave a strong and 1 (Mab_1456c) exhibited a minor defect. Two of the clones did not show any persistence phenotype (blaR and recR) and one (pafA) showed a minor phenotype, however it was not clear if this difference was really relevant as the mutant exhibited differences at Day 0, prior to the addition of antibiotics. Considering these results from the validation, the conclusion would be that the Tn-seq approach to screen persistence defects is not reliable and is more likely to result in misses than hits.

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

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, Espejo et al describe a method, SICKO, that allows for long-term longitudinal examination of bacterial colonization in the gut of C. elegans. SICKO utilizes a well-plate format where single worms are housed in each well with a small NGM pad surrounded by an aversive palmitic acid barrier to prevent worms from fleeing the well. The main benefit of this method is that it captures longitudinal data across individual worms with the ability to capture tens to hundreds of worms at once. The output data of SICKO in the heatmap is also very clear and robustly shows bacterial colonization in the gut across a large sample size, which is far superior to the current gold standard of imaging 10-20 worms in a cross-sectional matter at various timepoints of aging. They then provide a few examples of how this method can be applied to understand how colonization correlates with animal health.

      Strengths:

      -The method presented in this manuscript is sure to be of great utility to the host-pathogen field of C. elegans. The method also allows for utilization of large sample sizes and a way to present highly transparent data, both of which are excellent for promoting rigor and reproducibility of science.<br /> -The manuscript also does a great job in describing the limitations of the system, which is always appreciated.<br /> -The methods section for the SICKO data analysis pipeline and the availability of the code on Github are strong pluses.

      Weaknesses:

      -There are minor weaknesses in the methods that could be addressed relatively easily by expanding the explanation of how to set up the individual worm chambers (see comment 1 below).

      I am making all my comments and suggestions to the reviewers public, as I believe these comments can be useful to the general readership as well. Comment 1 is important to make the methods more accessible and comment 2 is important to make the data presentation more accessible to a broader audience. However, comments 3-4 are things/suggestions that should be considered by the authors and future users of SICKO for interpretation of all the data presented in the manuscript.

      (1) The methods section needs to be described in more detail. Considering that this is a methods development paper, more detailed explanation is required to ensure that readers can actually adapt these experiments into their labs.<br /> (a) What is the volume of lmNGM in each well?<br /> (b) Recommended volume of bacteria to seed in each well?<br /> (c) A file for the model for the custom printed 3D adaptor should be provided.<br /> (d) There should be a bit more detail on how the chambers should be assembled with all the components. After reading this, I am not sure I would be able to put the chamber together myself.<br /> (e) What is the recommended method to move worms into individual wells? Manual picking? Pipetting in a liquid?<br /> (f) Considering that a user-defined threshold is required (challenging for non-experienced users), example images should be provided on what an acceptable vs. nonacceptable threshold would look like.

      (2) The output data in 1e is very nice - it is a very nice and transparent plot, which I like a lot. However, since the data is complex, a supplemental figure to explain the data better would be useful to make it accessible for a broader audience. For example, highlighting a few rows (i.e., individual worms) and showing the raw image data for each row would be useful. What I mean is that it would be useful to show what does the worm actually look like for a "large colony size" or "small colony size"? What is the actual image of the worm that represents the yellow (large), versus dark blue (small), versus teal (in the middle)? And also the transition from dark blue to yellow would also be nice to be shown. This can probably also just be incorporated into Fig. 1d by just showing what color each of those worm images from day 1 to day 8 would represent in the heat map (although I still think a dedicated supplemental figure where you highlight a few rows and show matching pictures for each row in image files would be better).

      (3) I am not sure that doing a single-time point cross-sectional data is a fair comparison since several studies do multi-timepoint cross-sectional studies (e.g., day 1, day 5, day 9). This is especially true for using only day 1 data - most people do gut colonization assays at later timepoints since the gut barrier has been shown to break down at older ages, not day 1. The data collected by SICKO is done every day across many individuals worms and is clearly superior to this type of cross-sectional data (even with multiple timepoints), and I think this message would be further strengthened by comparing it directly to cross-sectional data collected across more than 1 timepoint of aging.

      (4) The authors show that SICKO can detect differences in wild-type vs. pmk-1 loss of function and between OP50 and PA14. However, these are very dramatic conditions that conventional methods can easily detect. I would think that the major benefit of SICKO over conventional methods is that it can detect subtle differences that cross-sectional methods would fail to visualize. It might be useful to see how well SICKO performs for these more subtle effects (e.g., OP50 on NGM vs. bacteria-promoting media; OP50 vs. HT115; etc.).<br /> (a) Similar to the above comment, the authors discuss how pmk-1 has colonization-independent effects on host-pathogen interactions. Maybe using a more direct approach to affect colonization (e.g., perturbing gut actin function like act-5) would be better.

    1. Virtual Hermans - Lucas Dul

      Lucas Dul does an overview of affordable and available tools for typewriter repair as well as more advanced

      Basic Tools

      • screwdriver sets
        • Carpenter screwdrivers (come to a point) the point can slip and causecam out screws
        • Hollow ground - provide the most amount of torque and prevent cam-out problems (also called gunsmith He uses the 0623 Chapman set (the number is the date of international typewriter day) The large tip can be problematic
        • long reach screwdriver
        • magnetic screwdriver
        • tempered stainless steel ruler (as a screwdriver, especially
        • microdrivers (usually used for eyeglasses or electronics)
      • spring hooks (push/pull)
        • Fixture from an embroidery set with length for getting length
        • grab hooks
      • pliers
        • standard needle nose pliers
        • 45-90 degree pliers (he uses more often)
        • wire cutters (for modifying springs in machines and modifying links in machines)
        • parallel draw pieces (with heavy duty cutters)
      • Mechanics' wrench set
        • prefer cast ones
        • socket screwdrivers (fixed hex screwdriver) expecially for shift adjustment on the Royal Ps
        • Chapman's has a mini rachet 1/4" socket in it's 0623 set
      • Forceps especially a long pair for IBM Selectrics (via Duane Jensen)
      • Tweezers
      • Blowtorches
        • alcohol torches (for heating and bending metal)
        • soldering, brazing, and heat shrinking
        • small butane torch (cigarette lighter use)
      • Oilers with needlepoint applicator (he uses sewing machine oil)
        • One can use the surface tension of the oil to place a dot on the tip of a scewdriver (flat head) and then place the dot within a machine with reasonable precision
      • MIG Pliers - have cutouts for taking rubber off of old feedrollers (otherwise these pliers are used for welding); he describes it as the nutcracker of the typewriter world
      • strap wrench (especially for removing platen knobs to prevent damage)
      • knife (butter knife)
        • razor blade for trimming rubber (otherwise too thin for other applications)
      • flashlight (simple is fine)
      • marker (Sharpie)
        • marking orientation of removed parts (washes off with alcohol)
      • hammer
      • retainer clip pliers (especially for IBMs, Brothers, Swintecs) with spare e- and c-clips (some have thumbscrews for minimizing damage to clips) openers are more useful than "closers"
      • Bristol wrenches - looks like Allen Keys, but with star cross section for bristol locks in IBM machines
      • Hand crank (for IBM Selectrics) thread into the operational cam shaft

      Intermediate Tools

      • segment bearing rod (good for removing individual typebars)
      • drinking straw for ball bearings on royal portables and S-C portables and flat tops staggered 1/2" ball bearings with orbital gear (star-shaped) - snip opposite sides to insert orbital ring and ball bearing for holding and placement in typewriter
      • carpenter's pencil for marking

      Advanced/Specialty tools

      • t-bender for forming metal (exp. thin pieces)
      • 9 jaw pliers for bending typebars
      • peening pliers (for manipulating and stretching materials)
      • wheel benders (he doesn't use often)
      • eyelete tool for putting eyelets in typewritter ribbon
      • files (small/cheap) widen gaps inside of type guides when necessary or thinning out tight pieces

      Very specialized

      • Type slug solder jig or solder guide (30:52)
      • keyring pliers ($400 and above to purchase)
      • multimeter for checking circuit components on electric models. Primarily using Ohm setting to see if current is passing through parts, otherwise they're broken.

      Honorable mentions

      • center punch for drilling points and new screws
      • dental mirror for looking into machines
      • spring gauge to set 2lbs for desktop and 1lb for portables

      Q&A

      air compressors are useful for cleaning

      Don't damage screws on older machines.

      US used imperial screws until 1940/50s and machines after are all metric.

      3 dessert island tools<br /> - screwdrivers, pliers, spring hook

  6. Dec 2024
    1. Reviewer #2 (Public review):

      Summary:

      More and more genes and genetic loci are being linked to bone fragility disorders like osteoporosis and osteogenesis imperfecta through GWAS and clinical sequencing. In this study, the authors seek to develop a pipeline for validating these new candidate genes using crispant screening in zebrafish. Candidates were selected based on GWAS bone density evidence (4 genes) or linkage to OI cases plus some aspect of bone biology (6 genes). NGS was performed on embryos injected with different gRNAs/Cas9 to confirm high mutagenic efficacy, and off-target cutting was verified to be low. Bone growth, mineralization, density, and gene expression levels were carefully measured and compared across crispants using a battery of assays at three different stages.

      Strengths:

      (1) The pipeline would be straightforward to replicate in other labs, and the study could thus make a real contribution towards resolving the major bottleneck of candidate gene validation.

      (2) The study is clearly written and extensively quantified.

      (3) The discussion attempts to place the phenotypes of different crispant lines into the context of what is already known about each gene's function.

      (4) There is added value in seeing the results for the different crispant lines side by side for each assay.

      (5) Caveats to the interpretability of crispant data and limitations of their gene-focused analyses and RT-PCR assays are discussed.

      Weaknesses:

      (1) The study uses only well-established methods and is strategy-driven rather question/hypothesis-driven. This is in line with the researchers' primary goal of developing a workflow for rapid in vivo functional screening of candidate genes. However, this means that less attention is paid to what the results obtained for a given gene may mean regarding potential disease mechanisms, and how contradictions with prior reports of mouse or fish null mutant phenotypes might be explained.

      (2) Normalization to body size was not performed. Measurements of surface area covered by osteoblasts or mineralized bone (Fig. 1) are typically normalized to body size - especially in larvae and juvenile fish - to rule out secondary changes due to delayed or accelerated overall growth. This was not done here; the authors argue that "variations in growth were considered as part of the phenotypic outcome." This is reasonable, but because standard length was reported only for fish at 90 dpf (not significantly different in any line), the reader is not given the opportunity to consider whether earlier differences in, e.g. surface area covered by osteoblasts at 14 dpf, could be accounted for by delayed or accelerated overall growth. Images in Figure S5 were not taken at the same magnification, further confounding this effort.

      Comments on latest version:

      The authors have largely addressed my comments by making changes to the text.

      However, in response to one of my original comments ("It would be helpful to note the grouping of candidates into OI vs. BMD GWAS throughout the figures"), they added a sentence to this effect to the legends. However, because two of the lines were larval-lethal, the legends to Figs. S6-8 are now incorrect in referring to ten genes when only eight mutants are shown.

    2. Author response:

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

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      In this work, a screening platform is presented for rapid and cost-effective screening of candidate genes involved in Fragile Bone Disorders. The authors validate the approach of using crispants, generating FO mosaic mutants, to evaluate the function of specific target genes in this particular condition. The design of the guide RNAs is convincingly described, while the effectiveness of the method is evaluated to 60% to 92% of the respective target genes being presumably inactivated. Thus, injected F0 larvae can be directly used to investigate the consequences of this inactivation.

      Skeletal formation is then evaluated at 7dpf and 14dpf, first using a transgenic reporter line revealing fluorescent osteoblasts, and second using alizarin-red staining of mineralized structures. In general, it appears that the osteoblast-positive areas are more often affected in the crispants compared to the mineralized areas, an observation that appears to correlate with the observed reduced expression of bglap, a marker for mature osteoblasts, and the increased expression of col1a1a in more immature osteoblasts.

      Finally, the injected fish (except two lines that revealed high mortality) are also analyzed at 90dpf, using alizarin red staining and micro-CT analysis, revealing an increased incidence of skeletal deformities in the vertebral arches, fractures, as well as vertebral fusions and compressions for all crispants except those for daam2. Finally, the Tissue Mineral Density (TMD) as determined by micro-CT is proposed as an important marker for investigating genes involved in osteoporosis.

      Taken together, this manuscript is well presented, the data are clear and well analyzed, and the methods are well described. It makes a compelling case for using the crispant technology to screen the function of candidate genes in a specific condition, as shown here for bone disorders.

      Strengths:

      Strengths are the clever combination of existing technologies from different fields to build a screening platform. All the required methods are comprehe Zebrafish tanks_13062024nsively described.

      We would like to thank the reviewer for highlighting the strengths of our paper.  

      Weaknesses:

      One may have wished to bring one or two of the crispants to the stage of bona fide mutants, to confirm the results of the screening, however, this is done for some of the tested genes as laid out in the discussion.

      We thank the reviewer for their comment. We would like to point out that indeed similar phenotypes have been observed in existing models, as mentioned in the discussion section.

      Reviewer #2 (Public review):

      Summary:

      More and more genes and genetic loci are being linked to bone fragility disorders like osteoporosis and osteogenesis imperfecta through GWAS and clinical sequencing. In this study, the authors seek to develop a pipeline for validating these new candidate genes using crispant screening in zebrafish. Candidates were selected based on GWAS bone density evidence (4 genes) or linkage to OI cases plus some aspect of bone biology (6 genes). NGS was performed on embryos injected with different gRNAs/Cas9 to confirm high mutagenic efficacy and off-target cutting was verified to be low. Bone growth, mineralization, density, and gene expression levels were carefully measured and compared across crispants using a battery of assays at three different stages.

      Strengths:

      (1) The pipeline would be straightforward to replicate in other labs, and the study could thus make a real contribution towards resolving the major bottleneck of candidate gene validation.

      (2) The study is clearly written and extensively quantified.

      (3) The discussion attempts to place the phenotypes of different crispant lines into the context of what is already known about each gene's function.

      (4) There is added value in seeing the results for the different crispant lines side by side for each assay.

      We would like to thank the reviewer for highlighting the strengths of our paper.  

      Weaknesses:

      (1) The study uses only well-established methods and is strategy-driven rather than question/hypothesis-driven.

      We thank the reviewer for this correct remark. The mayor aim of this study was to establish a workflow for rapid in vivo functional screening of candidate genes across a broad range of FBDs. 

      (2) Some of the measurements are inadequately normalized and not as specific to bone as suggested:

      (a) The measurements of surface area covered by osteoblasts or mineralized bone (Figure 1) should be normalized to body size. The authors note that such measures provide "insight into the formation of new skeletal tissue during early development" and reflect "the quantity of osteoblasts within a given structure and [is] a measure of the formation of bone matrix." I agree in principle, but these measures are also secondarily impacted by the overall growth and health of the larva. The surface area data are normalized to the control but not to the size/length of each fish - the esr1 line in particular appears quite developmentally advanced in some of the images shown, which could easily explain the larger bone areas. The fact that the images in Figure S5 were not all taken at the same magnification further complicates this interpretation.

      We thank the reviewer for this detailed and insightful remark. We agree with the reviewer and recognize that the results may be influenced by size differences. However, we do not normalize for size, as variations in growth were considered as part of the phenotypic outcome. This consideration has been addressed in the discussion section.

      Line 335-338: ‘Although the measurements of osteoblast-positive and mineralized surface areas may be influenced by size differences among some of the crispants, normalization to size parameters was not conducted, as variations in growth were considered integral to the phenotypic outcome.’

      Line 369: ‘Phenotypic variability in these zebrafish larvae can be attributed to several factors, including crispant mosaicism, allele heterogeneity, environmental factors, differences in genomic background and development, and slightly variable imaging positioning.’

      (b) Some of the genes evaluated by RT-PCR in Figure 2 are expressed in other tissues in addition to bone (as are the candidate genes themselves); because whole-body samples were used for these assays, there is a nonzero possibility that observed changes may be rooted in other, non-skeletal cell types.

      We thank the reviewer for this valuable comment. We acknowledge that the genes assessed by RT-PCR are expressed in other tissues beyond bone. This consideration has been addressed in the discussion section.

      Line 362-365: “However, it is important to note that the genes evaluated by RT-PCR are not exclusively expressed in bone tissue. Since whole-body samples were used for expression analysis, there is a possibility that the observed changes in gene expression may be influenced by other non-skeletal cell types”.

      (3) Though the assays evaluate bone development and quality at several levels, it is still difficult to synthesize all the results for a given gene into a coherent model of its requirement.

      We appreciate the reviewer’s  remark. We acknowledge that the results for the larval stages exhibit variability, making it challenging to synthesize them into a coherent model. However, it is important to emphasize that all adult crispant consistently display a skeletal phenotype. Consequently, the feasibility and reproducibility of this screening method are primarily focusing on the adult stages. This consideration has been addressed in the discussion section of the manuscript.

      Line 391-399: ‘In adult crispants, the skeletal phenotype was generally more penetrant. All crispants showed malformed arches, a majority displayed vertebral fractures and fusions and some crispants exhibited distinct quantitative variations in vertebral body measurements. This confirmed the role of the selected genes in skeletal development and homeostasis and their involvement in skeletal disease and established the crispant approach as a valid approach for rapidly providing in vivo gene function data to support candidate gene identification.’

      (4) Several additional caveats to crispant analyses are worth noting:

      (a) False negatives, i.e. individual fish may not carry many (or any!) mutant alleles. The crispant individuals used for most assays here were not directly genotyped, and no control appears to have been used to confirm successful injection. The authors therefore cannot rule out that some individuals were not, in fact, mutagenized at the loci of interest, potentially due to human error. While this doesn't invalidate the results, it is worth acknowledging the limitation.

      We thank the reviewer for this valuable remark. We recognize the fact that working with crispants has certain limitations, including the possibility that some individuals may carry few or no mutant alleles. To address this issue, we use 10 individual crispants during the larval stage and 5 during the adult stage. Although some individuals may lack the mutant alleles, using multiple fish helps reduce the risk of false negatives.

      Furthermore, we perform NGS analysis on pools of 10 embryos from the same injection clutch as the fish used in the various assays to assess the indel efficiency. While there remains a possibility of false negatives, the overall indel efficiency, as indicated by our NGS analysis,  is high (>90%), thereby reducing the likelihood of having crispants with very low indel efficiency. We included this in the discussion.

      Line 387-390: ‘While there remains a possibility of false negatives, the overall indel efficiency, as indicated by our NGS analysis,  is high (>90%), thereby reducing the likelihood of having crispants with very low indel efficiency.’

      (b) Many/most loci identified through GWAS are non-coding and not easily associated with a nearby gene. The authors should discuss whether their coding gene-focused pipeline could be applied in such cases and how that might work.

      The authors thank the reviewer for this insightful comment. Our study is focused on strong candidate genes rather than non-coding variants. We recognize that the use of this workflow poses challenges for analyzing non-coding variants, which represents a limitation of the crispant approach. We have addressed this issue in the discussion section of the manuscript.

      Line 131: ‘Gene-based’

      Line 453: ‘Gene-based’

      Line 311-314: ‘It is important to note that this study focused on candidate genes for osteoporosis, not on the role of specific variants identified in GWAS studies. Non-coding variants for instance, which are often identified in GWAS studies,  present significant challenges in terms of functional validation and interpretation.’

      Reviewer #3 (Public review):

      Summary:

      The manuscript "Crispant analysis in zebrafish as a tool for rapid functional screening of disease-causing genes for bone fragility" describes the use of CRISPR gene editing coupled with phenotyping mosaic zebrafish larvae to characterize functions of genes implicated in heritable fragile bone disorders (FBDs). The authors targeted six high-confident candidate genes implicated in severe recessive forms of FBDs and four Osteoporosis GWAS-implicated genes and observed varied developmental phenotypes across all crispants, in addition to adult skeletal phenotypes.

      A major strength of the paper is the streamlined method that produced significant phenotypes for all candidate genes tested.

      We would like to thank the reviewer for highlighting the strengths of our paper.  

      A major weakness is a lack of new insights into underlying mechanisms that may contribute to disease phenotypes, nor any clear commonalities across gene sets. This was most evident in the qRT-PCR analysis of select skeletal developmental genes, which all showed varied changes in fold and direction, but with little insight into the implications of the results.

      We thank the reviewer for this insightful remark. We want to emphasize that this study focusses on establishing a new screening method for candidate genes involved in FBDs, rather than investigating the underlying mechanisms contributing to disease phenotypes. However, to investigate the underlying mechanisms in these crispants, the creation of bona fide mutants is necessary. We have included this consideration in the discussion.

      Furthermore, we acknowledge that the results for the larval stages exhibit variability, which can complicate the interpretation of these findings. This is particularly true for the RT-PCR analysis, where whole-body samples were used, raising the possibility that other tissues may influence the expression results. Therefore, our primary focus is on the adult stages, as all crispants display a skeletal phenotype at this age. We have elaborated on this point in the discussion.

      Line 462-463: ‘Moreover, to explore the underlying mechanisms contributing to disease phenotypes, it is essential to establish stable knockout mutants derived from the crispants’.

      Line 391-399: ‘In adult crispants, the skeletal phenotype was generally more penetrant. All crispants showed malformed arches, a majority displayed vertebral fractures and fusions and some crispants exhibited distinct quantitative variations in vertebral body measurements. This confirmed the role of the selected genes in skeletal development and homeostasis and their involvement in skeletal disease and established the crispant approach as a valid approach for rapidly providing in vivo gene function data to support candidate gene identification.’

      Ultimately, the authors were able to show their approach is capable of connecting candidate genes with perturbation of skeletal phenotypes. It was surprising that all four GWAS candidate genes (which presumably were lower confidence) also produced a result.

      We appreciate the reviewer’s comment. We would like to direct attention to the discussion section, where we offer a possible explanation for the observation that all four GWAS candidate genes produce a skeletal phenotype.

      Line 460-410: 'The more pronounced and earlier phenotypes in these zebrafish crispants are most likely attributed to the quasi knock-out state of the studied genes, while more common less impactful variants in the same genes result in typical late-onset osteoporosis (Laine et al., 2013) . This phenomenon is also observed in knock-out mouse models for these genes (Melville et al., 2014)(Coughlin et al., 2019).’

      These authors have previously demonstrated that crispants recapitulate skeletal phenotypes of stable mutant lines for a single gene, somewhat reducing the novelty of the study.

      We thank the reviewer for this comment and appreciate their concern. We have indeed demonstrated that crispants can recapitulate the skeletal phenotypes observed in stable mutant lines for the osteoporosis gene LRP5. However, we would like to highlight that the current study represents the first large-scale screening of candidate genes associated with bone disorders, including genes related to both OI and osteoporosis. We have included this information in both the abstract and the discussion

      Line 60-62: ‘We advocate for a novel comprehensive approach that integrates various techniques and evaluates distinct skeletal and molecular profiles across different developmental and adult stages.’

      Line 456-457: ‘While this work represents a pioneering effort in establishing a screening platform for skeletal diseases, it offers opportunities for future improvement and refinement.’

      Recommendations for the authors:

      Reviewer #1 (Recommendations for the authors):

      (1) Figure 1a: what does the differential shading of the bone elements represent? Explain in the legend.

      The differential shading doesn't represent anything specific. It's simply used to enhance the visual appeal and to help distinguish between the different structures. We removed the shading in the figure.

      (2) Supplementary Figures 2-5: should the numbering of these figures be also in order of appearance in the text? I understand that the authors prefer to associate the transgenic and the alizarin red-stained specimens, however, the reading would be easier that way.

      We changed this accordingly.

      (3) Lines 275-276: "no significant differences in standard length (Figure 4a)": should be Figure 4b.

      The suggested changes are incorporated in the manuscript.

      Line 276-277: ‘Among the eight crispants that successfully matured into adulthood, none exhibited significant differences in standard length and head size (n=5 fish per crispant) (Figure 4b).’

      (4) Line 277 "larger eye diameter": should be Figure 4b.

      The suggested changes are incorporated in the manuscript.

      Line 378: ‘However, esr1 crispants were observed to have notably larger eye diameters (Figure 4b).’

      (5) Line 280: "no obvious abnormalities were detected (Figure 4b,c)": should be Figure 4a, c. Note that the authors may reconsider the a, b, c numbering in Figure 4 by inverting a and b.

      The suggested changes are incorporated in the manuscript.

      Line 278-281: ‘All these crispants demonstrated various abnormalities in the caudal part of the vertebral column such as fusions, compressions, fractures, or arch malformations, except for daam2 crispants where no obvious abnormalities were detected (Figure 4a,c; Supplementary Figure 6).’

      (6) Table 2: This table, which recapitulates all the results presented in the manuscript, is in the end the centerpiece of the work. It is however difficult to read in its present form. Three suggestions:

      - Transpose it such that each gene has its own column, and the lines give the results for the different measurements

      - Place the measurements that result in "ns" for all crispants at the end (bottom) of the table.

      - Maybe bring the measurements at 7dpf, 14dpf, and 90 dpf together.

      We agree with the reviewer and have added a new table where we transposed the data. However, we chose not to place the measurements that resulted in 'ns' for all crispants at the end of the table, as we believe it is important to track the evolution of the phenotype over time. Where possible, we have grouped the measurements for 7 dpf and 14 dpf together.

      Reviewer #2 (Recommendations for the authors):

      (1) It would help to justify why these particular area measurements are appropriate for this set of candidate genes, which were selected based on putative links to bone quality rather than bone development.

      The selected methods are among the most commonly used to evaluate bone phenotypes. They are straightforward to reproduce, as well as cost- and time-effective. The strength of this approach lies in its use of simple, reproducible techniques that form the foundation for characterizing bone development.  Although the candidate genes were chosen based on their putative links to bone quality, early skeletal phenotypes can already be observed during bone development.

      The mineralized surface area of the total head and specific head structures was selected to evaluate the degree of mineralization in early skeletal development, as mineralization is a direct indicator of bone formation. Additionally, the osteoblast-positive surface areas were measured to provide insight into the formation of new skeletal tissue during early development. Osteoblasts, as active bone-forming cells, are essential for understanding bone growth and the dynamics of skeletal phenotypes.

      Examples in the manuscript:

      Line 212-214: ‘The osteoblast-positive areas in both the total head and the opercle were then quantified to gain insight into the formation of new skeletal tissue during early development.’

      Line 221-223: ‘Subsequently, Alizarin Red S (ARS) staining was conducted on the same 7 and 14 dpf crispant zebrafish larvae in order to evaluate the degree of mineralization in the early skeletal structures.’

      (2) Reword: The opercle bone is the earliest forming bone of the opercular series, and appears to be what the authors are referring to as the "operculum" at 7-14 dpf. The operculum is the larger structure (gill cover) in which the opercle is embedded. It would be more accurate to simply refer to the opercle at these stages.

      We agree with this comment and changed the text accordingly.

      (3) Define BMD and TMD at first usage.

      BMD and TMD are now defined in the manuscript.

      Line 41-43: ‘Six genes associated with severe recessive forms of Osteogenesis Imperfecta (OI) and four genes associated with bone mineral density (BMD), a key osteoporosis indicator, identified through genome-wide association studies (GWAS) were selected.’

      Line 286-288: ‘For each of the vertebral centra, the length, tissue mineral density (TMD), volume, and thickness were determined and tested for statistical differences between groups using a regression-based statistical test (Supplementary Figure 7).’

      (4) It would be helpful to note the grouping of candidates into OI vs. BMD GWAS throughout the figures.

      We agree with this comment and added this to all figure legends.

      ‘The first four genes are associated with the pathogenesis of osteoporosis, while the last six are linked to osteogenesis imperfecta’

      Reviewer #3 (Recommendations for the authors):

      Major points:

      (1) For the Results, it would be useful to the Reader to justify the selection of human candidate genes and their associated zebrafish orthologs to model skeletal functions. For example, what are variants identified from human studies, and do they impact functional domains? Are these domains and/or proteins conserved between humans/zebrafish? Is there evidence of skeletal expression in humans/zebrafish?

      Supplementary Table 4 lists the selected human candidate genes with reported mutations and/or polymorphisms associated with both skeletal and non-skeletal phenotypes. The table also includes additional findings from studies in mice and zebrafish. An extra column was now added to indicate gene conservation between human and zebrafish. We consulted UniProt (https://www.uniprot.org) and ZFIN (https://zfin.org) to assess the skeletal expression of these genes in human and zebrafish. All genes showed expression in the trabecular bone and/or bone marrow in humans, as well as in bone elements in zebrafish. We added this in the discussion.

      Line 309: ‘All selected genes show skeletal expression in both human and zebrafish.’

      Supplemental table 4 legend: ‘The conservation between human and zebrafish is reported in the last column.’

      As part of this, some version of Supplementary Table 4 might be included as a main display to introduce the targeted genes, ideally separated by rare (recessive OI) vs. common disease (osteoporosis). In the case of common disease and GWAS hits, how did authors narrow in on candidate genes (which often have Mbp-scale associated regions spanning multiple genes)? Further, what is the evidence that the mechanism of action of the GWAS variant is haploinsufficiency modeled by their crispant zebrafish?

      We have kept Supplementary Table 4 in the supplementary material but have referred to it earlier in the manuscript’s introduction. Consequently, the table has been renumbered from ‘Supplementary Table 4’  to ‘Supplementary Table 1’.

      The selection of genes potentially involved in the pathogenesis of osteoporosis is based on the data from the GWAS catalog, which annotates SNPs using the Ensemble mapping pipeline. The available annotation on their online search interface includes any Ensemble genes to which a SNP maps, or the closest upstream and downstream gene within a 50kb window. Four genes were selected for this screening method based on the criteria outlined in the results section. In this study, we aim to evaluate the general involvement of specific genes in bone metabolism, rather than to model a specific variant.

      Line 135-136 and 309-311: ‘An overview of the selected genes with observed mutant phenotypes in human, mice and zebrafish is provided in Supplementary Table 1.’

      (2) Using the crispant approach does not impact maternally-deposited RNAs that would dampen early developmental phenotypes. Considering the higher variability in larval phenotypes, perhaps the maternal effect plays a role. The authors might investigate developmental expression profiles of their genes using existing RNA-seq datasets such as from White et al (doi: 10.7554/eLife.30860).

      We thank the reviewer for this comment and agree with the possibility that maternally-deposited RNAs might have an impact on early developmental phenotypes. We included this in the discussion.

      Line 369-372: ‘Phenotypic variability in these zebrafish larvae can be attributed to several factors, including crispant mosaicism, allele heterogeneity, environmental factors, differences in genomic background and development, maternally-deposited RNAs, and slightly variable imaging positioning.’

      (3) While making comparisons within a clutch of mutant vs scrambled control is crucial, it is also important to ensure phenotypes are not specific to a single clutch. Do phenotypes remain consistent across different crosses/clutches?

      Yes, phenotypes remain consistent across different crosses and clutches. We included images from a second clutch in the Supplementary material (Supplementary Figure 8) and refereed to it in the discussion.

      Line 394-397: ‘Additionally, these skeletal malformations were consistently observed in a second clutch of crispants (Supplementary Figure 8), underscoring the reproducibility of these phenotypic features across independent clutches.’

      (4) Understanding that antibodies may not exist for many of the selected genes for zebrafish, authors should verify haploinsufficiency using an RT-qPCR of targeted genes in crispants vs. controls.

      We appreciate the reviewer’s suggestion to use RT-qPCR to examine expression levels of the targeted genes in crispants. However, previous experience suggests that relying on RNA expression to verify haploinsufficiency in zebrafish can be challenging. In zebrafish KO mutants, RT-qPCR often still detects gene transcripts, potentially due to incomplete nonsense-mediated decay (NMD) of the mutated mRNA, which may allow residual expression even in the absence of functional protein. As a more definitive approach, we prefer to use antibodies to confirm haploinsufficiency at the protein level. However, as the reviewer noted, generating and applying specific antibodies in zebrafish remains challenging.

      (5) Please indicate how parametric vs. non-parametric statistical tests were selected for datasets.

      We initially selected the parametric unpaired t-test, assuming the data were normally distributed with similar variances between groups. We verified the assumption of equal variances using the F-test, which was not significant across all assays. However, we did not assess the normality of the data directly, meaning we cannot confirm the normality assumption required for the t-test. Given this, we have opted to use the non-parametric Mann-Whitney U test, which does not require assumptions of normality, to ensure the robustness of our statistical analyses. We changed the Figures, the figure legends and the text accordingly.

      (6) In the figures and tables, I recommend adding notation showing the grouping of the first four genes as GWAS osteoporosis, the next three genes as osteoblast differentiation, the next two genes as bone mineralization, and the final gene as collagen transport to orient the reader. One might expect there to be a clustering of phenotypic outcomes based on the selection of genes, and it would be easier to follow this. This would be particularly useful to include in Table 2.

      Our primary objective is to assess the feasibility and reproducibility of the crispant screen rather than performing an in-depth pathway analysis or categorizing genes by biological processes. For this purpose, we have organized candidate genes based on their relevance to osteoporosis and Osteogenesis Imperfecta, without subdividing them further. We have clarified this focus in the figure legends, as suggested in an earlier recommendation.

      (7) For Figure 1, consider adding a smaller zoomed version of 1a embedded in each sub-figure with each measured element highlighted to improve readability.

      We agree with this comment and changed the figure accordingly.

      Minor points:

      (1) Table 2 could be simplified to improve readability. The headers have redundancies across columns with varied time points and could be merged.

      The suggested changes are incorporated in the manuscript (see earlier comment about this).

      (2) "BMD" is not defined in the Abstract. This is a personal preference, but there were numerous abbreviations in the text that made it difficult to follow at times.

      The suggested changes are incorporated in the manuscript (see earlier comment about this).

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript presents data demonstrating NopT's interaction with Nod Factor Receptors NFR1 and NFR5 and its impact on cell death inhibition and rhizobial infection. The identification of a truncated NopT variant in certain Sinorhizobium species adds an interesting dimension to the study. These data try to bridge the gaps between classical Nod-factor-dependent nodulation and T3SS NopT effector-dependent nodulation in legume-rhizobium symbiosis. Overall, the research provides interesting insights into the molecular mechanisms underlying symbiotic interactions between rhizobia and legumes.

      Strengths:

      The manuscript nicely demonstrates NopT's proteolytic cleavage of NFR5, regulated by NFR1 phosphorylation, promoting rhizobial infection in L. japonicus. Intriguingly, authors also identify a truncated NopT variant in certain Sinorhizobium species, maintaining NFR5 cleavage but lacking NFR1 interaction. These findings bridge the T3SS effector with the classical Nod-factor-dependent nodulation pathway, offering novel insights into symbiotic interactions.

      Weaknesses:

      (1) In the previous study, when transiently expressed NopT alone in Nicotiana tobacco plants, proteolytically active NopT elicited a rapid hypersensitive reaction. However, this phenotype was not observed when expressing the same NopT in Nicotiana benthamiana (Figure 1A). Conversely, cell death and a hypersensitive reaction were observed in Figure S8. This raises questions about the suitability of the exogenous expression system for studying NopT proteolysis specificity.

      (2) NFR5 Loss-of-function mutants do not produce nodules in the presence of rhizobia in lotus roots, and overexpression of NFR1 and NFR5 produces spontaneous nodules. In this regard, if the direct proteolysis target of NopT is NFR5, one could expect the NGR234's infection will not be very successful because of the Native NopT's specific proteolysis function of NFR5 and NFR1. Conversely, in Figure 5, authors observed the different results.

      (3) In Figure 6E, the model illustrates how NopT digests NFR5 to regulate rhizobia infection. However, it raises the question of whether it is reasonable for NGR234 to produce an effector that restricts its own colonization in host plants.

      (4) The failure to generate stable transgenic plants expressing NopT in Lotus japonicus is surprising, considering the manuscript's claim that NopT specifically proteolyzes NFR5, a major player in the response to nodule symbiosis, without being essential for plant development.

      Comments on revised version:

      This version has effectively addressed most of my concerns. However, one key issue remains unresolved regarding the mechanism of NopT in regulating nodule symbiosis. Specifically, the explanation of how NopT catabolizes NFR5 to regulate symbiosis is still not convincing within the current framework of plant-microbe interaction, where plants are understood to genetically control rhizobial colonization.

      While alternative regulatory mechanisms in plant-microbe interactions are plausible, the notion that the NRG234-secreted effector NopT could reduce its own infection by either suppressing plant immunity or degrading the symbiosis receptor remains unsubstantiated. I believe further revisions are needed in the discussion section to more clearly address and clarify these findings and any lingering uncertainties.

    2. Author response:

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

      eLife Assessment

      This valuable study reveals how a rhizobial effector protein cleaves and inhibits a key plant receptor for symbiosis signaling, while the host plant counters by phosphorylating the effector. The molecular evidence for the protein-protein interaction and modification is solid, though biological evidence directly linking effector cleavage to rhizobial infection is incomplete. With additional functional data, this work could have implications for understanding intricate plant-microbe dynamics during mutualistic interactions.

      Thank you for this positive comment. Our data strongly support the view that NFR5 cleavage by NopT impairs Nod factor signaling resulting in reduced rhizobial infection. However, other mechanisms may also have an effect on the symbiosis, as NopT targets other proteins in addition to NFR5. In our revised manuscript version, we discuss the possibility that negative NopT effects on symbiosis could be due to NopT-triggered immune responses. As mentioned in our point-by-point answers to the Reviewers, we included additional data into our manuscript. We would also like to point out that we are generally more cautious in our revised version in order to avoid over-interpreting the data obtained.

      Public Reviews:

      Reviewer #1 (Public Review):

      Bacterial effectors that interfere with the inner molecular workings of eukaryotic host cells are of great biological significance across disciplines. On the one hand they help us to understand the molecular strategies that bacteria use to manipulate host cells. On the other hand they can be used as research tools to reveal molecular details of the intricate workings of the host machinery that is relevant for the interaction/defence/symbiosis with bacteria. The authors investigate the function and biological impact of a rhizobial effector that interacts with and modifies, and curiously is modified by, legume receptors essential for symbiosis. The molecular analysis revealed a bacterial effector that cleaves a plant symbiosis signaling receptor to inhibit signaling and the host counterplay by phosphorylation via a receptor kinase. These findings have potential implications beyond bacterial interactions with plants.

      Thank you for highlighting the broad significance of rhizobial effectors in understanding legume-rhizobia interactions. We fully agree with your assessment and have expanded our Discussion (and Abstract) regarding the potential implications of our findings beyond bacterial interactions with plants. We mention the prospect of developing specific kinase-interacting proteases to fine-tune cellular signaling processes in general.

      Bao and colleagues investigated how rhizobial effector proteins can regulate the legume root nodule symbiosis. A rhizobial effector is described to directly modify symbiosis-related signaling proteins, altering the outcome of the symbiosis. Overall, the paper presents findings that will have a wide appeal beyond its primary field.

      Out of 15 identified effectors from Sinorhizobium fredii, they focus on the effector NopT, which exhibits proteolytic activity and may therefore cleave specific target proteins of the host plant. They focus on two Nod factor receptors of the legume Lotus japonicus, NFR1 and NFR5, both of which were previously found to be essential for the perception of rhizobial nod factor, and the induction of symbiotic responses such as bacterial infection thread formation in root hairs and root nodule development (Madsen et al., 2003, Nature; Tirichine et al., 2003; Nature). The authors present evidence for an interaction of NopT with NFR1 and NFR5. The paper aims to characterize the biochemical and functional consequences of these interactions and the phenotype that arises when the effector is mutated.

      Thank you for your positive feedback.  We have now emphasized the interdisciplinary significance of our work in the Introduction and Discussion of our revised manuscript. We highlight how the insights gained from our study can contribute to a better understanding of microbial interactions with eukaryotic hosts in general, and hope that our findings could benefit future research in the fields of pathogenesis, immunity, and symbiosis.

      We appreciate your detailed summary of our work, which is focused on NopT and its interaction with Nod factor receptors. To ensure that the readers can easily follow the rationale behind our work, we have included a more detailed explanation of how NopT was identified to target Nod factor receptors. In particular, we now better describe the test system (Nicotiana benthamiana cells co-expressing NFR1/NFR5 with a given effector of Sinorhizobium fredii NGR234). In addition, we provide now a more thorough background on the roles of NFR1 and NFR5 in symbiotic signaling and refer to the two Nature papers from 2003 on NFR1 and NFR5 (Madsen et al., 2003; Radutoiu et al., 2003).

      Evidence is presented that in vitro NopT can cleave NFR5 at its juxtamembrane region. NFR5 appears also to be cleaved in vivo. and NFR1 appears to inhibit the proteolytic activity of NopT by phosphorylating NopT. When NFR5 and NFR1 are ectopically over-expressed in leaves of the non-legume Nicotiana benthamiana, they induce cell death (Madsen et al., 2011, Plant Journal). Bao et al., found that this cell death response is inhibited by the coexpression of nopT. Mutation of nopT alters the outcome of rhizobial infection in L. japonicus. These conclusions are well supported by the data.

      We appreciate your recognition of the robustness of our conclusions. In the context of your comments, we made the following improvements to our manuscript:

      We included a more detailed description of the experimental conditions under which the cleavage of NFR5 by NopT was observed in vitro and in vivo. Furthermore, additional experiments were added to strengthen the evidence for NFR5 cleavage by NopT (Fig 3, S3, S6, and S14).

      We provided more comprehensive data on the phosphorylation of NopT by NFR1, including phosphorylation assays (Fig. 4) and mass spectrometry results (Fig. S7 and Table S1). These data provide additional information on the mechanism by which NFR1 inhibits the proteolytic activity of NopT.

      We expanded the discussion on the cell death response induced by ectopic expression of NFR1 and NFR5 in Nicotiana benthamiana. We also included further details from Madsen et al. (2011) to contextualize our findings within the known literature.

      We believe that these additions and clarifications have improved the significance and impact of our study.

      The authors present evidence supporting the interaction of NopT with NFR1 and NFR5. In particular, there is solid support for cleavage of NFR5 by NopT (Figure 3) and the identification of NopT phosphorylation sites that inhibit its proteolytic activity (Figure 4C). Cleavage of NFR5 upon expression in N. benthamiana (Figure 3A) requires appropriate controls (inactive mutant versions) that have been provided, since Agrobacterium as a closely rhizobia-related bacterium, might increase defense related proteolytic activity in the plant host cells.

      We appreciate your recognition of the importance of appropriate controls in our experimental design. In response to your comments, we revised our manuscript to ensure that the figures and legends provide a clear description of the controls used. We also included a more detailed description of our experimental design at several places. In particular, we have highlighted the use of the protease-dead version of NopT as a control (NopT<sup>C93S</sup>). Therefore, NFR5-GFP cleavage in N. benthamiana clearly depended on protease activity of NopT and not on Agrobacterium (Fig. 3A). In the revised text, we are now more cautious in our wording and don’t conclude at this stage that NopT proteolyzes NFR5. However, our subsequent experiments, including in vitro experiments, clearly show that NopT is able to proteolyze NFR5.

      We are convinced that these changes have improved the quality of our work.

      Key results from N. benthamiana appear consistent with data from recombinant protein expression in bacteria. For the analysis in the host legume L. japonicus transgenic hairy roots were included. To demonstrate that the cleavage of NFR5 occurs during the interaction in plant cells the authors build largely on western blots. Regardless of whether Nicotiana leaf cells or Lotus root cells are used as the test platform, the Western blots indicate that only a small proportion of NFR5 is cleaved when co-expressed with nopT, and most of the NFR5 persists in its full-length form (Figures 3A-D). It is not quite clear how the authors explain the loss of NFR5 function (loss of cell death, impact on symbiosis), as a vast excess of the tested target remains intact. It is also not clear why a large proportion of NFR5 is unaffected by the proteolytic activity of NopT. This is particularly interesting in Nicotiana in the absence of Nod factor that could trigger NFR1 kinase activity.

      Thank you for your comments regarding the cleavage of NFR5 by NopT and its functional implications. We acknowledge that our immunoblots indicate only a relatively small proportion of  the NFR5 cleavage product.  Possible explanations could be as follows:

      (1) The presence of full-length NFR5 does not preclude a significant impact of NopT on function of NFR5, as NopT is able to bind to NFR5. In other words, the NopT-NFR5 and NopT-NFR1 interactions at the plasmamembrane might influence the function of the NFR1/NFR5 receptor without proteolytic cleavage of NFR5. In fact, protease-dead NopT<sup>C93S</sup> expressed in NGR234Δ_nopT_ showed certain effects in L. japonicus (less infection foci were formed compared to NGR234Δ_nopT_ Fig. 5E).  In this context, it is worth mentioning that the non-acylated NopT<sup>C93S</sup> (Fig. 1B) and not<sub>USDA257</sub> (Fig. 6B) proteins were unable to suppress NFR1/NFR5-induced cell death in N. benthamina, but this could be explained by the lack of acylation and altered subcellular localization.

      (2) The cleaved NFR5 fraction, although small, may be sufficient to disrupt signaling pathways, leading to the observed phenotypic changes  (loss of cell death in N. benthamiana; altered infection in L. japonicus).

      (3) The used expression systems produce high levels of proteins in the cell. This may not reflect the natural situation in L. japonicus cells.

      (4) Cellular conditions could impair cleavage of NFR5 by NopT.  Expression of proteins in E. coli may partially result in formation of protein aggregates (inactive NopT; NFR5 resistant to proteolysis).

      (5) In N. benthamiana co-expressing NFR1/NFR5, the NFR1 kinase activity is constitutively active (i.e., does not require Nod factors), suggesting an altered protein conformation of the receptor complex, which may influence the proteolytic susceptibility of NFR5.

      (6) The proteolytic activity of NopT may be reduced by the interaction of NopT with other proteins such as NFR1, which phosphorylates NopT and inactivates its protease activity.

      In our revised manuscript version, we provide now quantitative data for the efficiency of NFR5 cleavage by NopT in different expression systems used (Supplemental Fig.  14).  We have also improved our Discussion in this context. Future research will be necessary to better understand loss of NFR5 function by NopT. 

      It is also difficult to evaluate how the ratios of cleaved and full-length protein change when different versions of NopT are present without a quantification of band strengths normalized to loading controls (Figure 3C, 3D, 3F). The same is true for the blots supporting NFR1 phosphorylation of NopT (Figure 4A).

      Thank you for pointing out this. Following your suggestions, we quantified the band intensities for cleaved and full-length NFR5 in our different expression systems (N. benthamiana, L. japonicus and E. coli). The protein bands were normalized to loading controls. The data are shown in the new Supplemental Fig. 14. Similarly, the bands of immunoblots supporting phosphorylation of NopT by NFR1 were quantified. The data on band intensities are shown in Fig.  4B of our revised manuscript. These improvements provide a clearer understanding of how the ratios of cleaved to full-length proteins change in different protein expression systems, and to which extent NopT was phosphorylated by NFR1.

      Nodule primordia and infection threads are still formed when L. japonicus plants are inoculated with ∆nopT mutant bacteria, but it is not clear if these primordia are infected or develop into fully functional nodules (Figure 5). A quantification of the ratio of infected and non-infected nodules and primordia would reveal whether NopT is only active at the transition from infection focus to thread or perhaps also later in the bacterial infection process of the developing root nodule.

      Thank you for highlighting this aspect of our study. In response to your comment, we have conducted additional inoculation experiments with L. japonicus plants inoculated with NGR234 and NGR234_ΔnopT_ mutant. The new data are shown in Fig 5A, 5E, and 5G. However, we could not find any uninfected nodules (empty) nodules when roots were inoculated with these strains and mention this observation in the Results section of our revised manuscript.

      Reviewer #2 (Public Review):

      Summary:

      This manuscript presents data demonstrating NopT's interaction with Nod Factor Receptors NFR1 and NFR5 and its impact on cell death inhibition and rhizobial infection. The identification of a truncated NopT variant in certain Sinorhizobium species adds an interesting dimension to the study. These data try to bridge the gaps between classical Nod-factor-dependent nodulation and T3SS NopT effector-dependent nodulation in legume-rhizobium symbiosis. Overall, the research provides interesting insights into the molecular mechanisms underlying symbiotic interactions between rhizobia and legumes.

      Strengths:

      The manuscript nicely demonstrates NopT's proteolytic cleavage of NFR5, regulated by NFR1 phosphorylation, promoting rhizobial infection in L. japonicus. Intriguingly, authors also identify a truncated NopT variant in certain Sinorhizobium species, maintaining NFR5 cleavage but lacking NFR1 interaction. These findings bridge the T3SS effector with the classical Nod-factor-dependent nodulation pathway, offering novel insights into symbiotic interactions.

      Weaknesses:

      (1) In the previous study, when transiently expressed NopT alone in Nicotiana tobacco plants, proteolytically active NopT elicited a rapid hypersensitive reaction. However, this phenotype was not observed when expressing the same NopT in Nicotiana benthamiana (Figure 1A). Conversely, cell death and a hypersensitive reaction were observed in Figure S8. This raises questions about the suitability of the exogenous expression system for studying NopT proteolysis specificity.

      We appreciate your attention to these plant-specific differences. Previous studies showed that NopT expressed in tobacco (N. tabacum) or in specific Arabidopsis ecotypes (with PBS1/RPS5 genes) causes rapid cell death (Dai et al. 2008; Khan et al. 2022). Khan et al. 2022 reported recently that cell death does not occur in N. benthamiana unless the leaves were transformed with PBS1/RPS5 constructs. Our data shown in Fig. S15 confirm these findings. As cell death (effector triggered immunity) is usually associated with induction of plant protease activities, we considered N. tabacum and A. thaliana plants as not suitable for testing NFR5 cleavage by NopT. In fact, no NopT/NFR5 experiments were not performed with these plants in our study.  In response to your comment, we now better describe the N. benthamiana expression system and cite the previous articles_. Furthermore,  We have revised the Discussion section to better emphasize effector-induced immunity in non-host plants and the negative effect of rhizobial effectors during symbiosis. Our revisions certainly provide a clearer understanding of the advantages and limitations of the _N.  benthamiana expression system.

      (2) NFR5 Loss-of-function mutants do not produce nodules in the presence of rhizobia in lotus roots, and overexpression of NFR1 and NFR5 produces spontaneous nodules. In this regard, if the direct proteolysis target of NopT is NFR5, one could expect the NGR234's infection will not be very successful because of the Native NopT's specific proteolysis function of NFR5 and NFR1. Conversely, in Figure 5, authors observed the different results.

      Thank you for this comment, which points out that we did not address this aspect precisely enough in the original manuscript version.  We improved our manuscript and now write that nfr1 and nfr5 mutants do not produce nodules (Madsen et al., 2003; Radutoiu et al., 2003) and that over-expression of either NFR1 or NFR5 can activate NF signaling, resulting in formation of spontaneous nodules in the absence of rhizobia (Ried et al., 2014). In fact, compared to the nopT knockout mutant NGR234_ΔnopT_, wildtype NGR234 (with NopT) is less successful in inducing infection foci in root hairs of L. japonicus (Fig. 5). With respect to formation of nodule primordia, we repeated our inoculation experiments with NGR234_ΔnopT_ and wildtype NGR234 and also included a nopT over-expressing NGR234 strain into the analysis. Our data clearly showed that nodule primordium formation was negatively affected by NopT. The new data are shown in Fig. 5 of our revised version. Our data show that NGR234's infection is not really successful, especially when NopT is over-expressed. This is consistent  with our observations that NopT targets Nod factor receptors in L. japonicus and inhibits NF signaling (NIN promoter-GUS experiments). Our findings indicate that NopT is an “Avr effector” for L. japonicus.  However, in other host plants of NGR234, NopT possesses a symbiosis-promoting role (Dai et al. 2008; Kambara et al. 2009). Such differences could be explained by different NopT targets in different plants (in addition to Nod factor receptors), which may influence the outcome of the infection process. Indeed, our work shows hat NopT can interact with various kinase-dead LysM domain receptors, suggesting a role of NopT in suppression or activation of plant immunity responses depending on the host plant. We discuss such alternative mechanisms in our revised manuscript version and emphasize the need for further investigation to elucidate the precise mechanisms underlying the observed infection phenotype and the role of NopT in modulating symbiotic signaling pathways. In this context, we would also like to mention the two new figures of our manuscript which are showing (i) the efficiency of NFR5 cleavage by NopT in different expression systems, (ii) the interaction between NopT<sup>C93S</sup> and His-SUMO-NFR5<sup>JM</sup>-GFP, and (iii) cleavage of His-SUMO-NFP<sup>JM</sup>-GFP by NopT (Supplementary Figs. S8 and S9).

      (3) In Figure 6E, the model illustrates how NopT digests NFR5 to regulate rhizobia infection. However, it raises the question of whether it is reasonable for NGR234 to produce an effector that restricts its own colonization in host plants.

      Thank you for mentioning this point. We are aware of the possible paradox that the broad-host-range strain NGR234 produces an effector that appears to restrict its infection of host plants. As mentioned in our answer to the previous comment, NopT could have additional functions beyond the regulation of Nod factor signaling. In our revised manuscript version, we have modified our text as follows:

      (1) We mention the potential evolutionary aspects of NopT-mediated regulation of rhizobial infection and discuss the possibility that interactions between NopT and Nod factor receptors may have evolved to fine-tune Nod factor signaling to avoid rhizobial hyperinfection in certain host legumes.

      (2) We also emphasize that the presence of NopT may confer selective advantages in other host plants than L. japonicus due to interactions with proteins related to plant immunity. Like other effectors, NopT could suppress activation of immune responses (suppression of PTI) or cause effector-triggered immunity (ETI) responses, thereby modulating rhizobial infection and nodule formation. Interactions between NopT and proteins related to the plant immune system may represent an important evolutionary driving force for host-specific nodulation and explain why the presence of NopT in NGR234 has a negative effect on symbiosis with L. japonicus but a positive one with other legumes.

      (4) The failure to generate stable transgenic plants expressing NopT in Lotus japonicus is surprising, considering the manuscript's claim that NopT specifically proteolyzes NFR5, a major player in the response to nodule symbiosis, without being essential for plant development.

      We also thank for this comment. We have revised the Discussion section of our manuscript and discuss now our failure to generate stable transgenic L. japonicus plants expressing NopT. We observed that the protease activity of NopT in aerial parts of L. japonicus had a negative effect on plant development, whereas NopT expression in hairy roots was possible. Such differences may be explained by different NopT substrates in roots and aerial parts of the plant. In this context, we also discuss our finding that NopT not only cleaves NFR5 but is also able to proteolyze other proteins of L. japonicus such as LjLYS11, suggesting that NopT not only suppresses Nod factor signaling, but may also interfere with signal transduction pathways related to plant immunity. We speculate that, depending on the host legume species, NopT could suppress PTI or induce ETI, thereby modulating rhizobial infection and nodule formation.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Overall the text and figure legends must be double-checked for correctness of scientific statements. The few listed here are just examples. There are more that are potentially damaging the perception by the readers and thus the value of the manuscript.

      The nopT mutant leads to more infections. In line 358 the statement: "...and the proteolysis of NFR5 are important for rhizobial infection", is wrong, as the infection works even better without it. It is, according to my interpretation of the results, important for the regulation of infection. Sounds a small difference, but it completely changes the meaning.

      We appreciate your thorough review and have taken the opportunity to correct this error. Following your suggestions, we carefully rephrased the whole text and figure legends to ensure that the scientific statements accurately reflect the findings of our study. We are convinced that these changed have increased the value of this study.

      In line 905 the authors state that NopTC indicates the truncated version of NopT after autocleavage by releasing about 50 a.a. at its N-terminus.

      They do not analyse this cleavage product to support this claim. So better rephrase.

      According to Dai et al. (2008), NopT expressed in E. coli is autocleaved. The N-terminal sequence GCCA obtained by Edman sequencing suggests that NopT was cleaved between M49 and G50.  We improved our manuscript and now write:

      (1) “A previous study has shown that NopT is autocleaved at its N-terminus to form a processed protein that lacks the first 49 amino acid residues (Dai et al., 2008)”

      (2) “However, NopT<sup>ΔN50</sup>, which is similar to autocleaved NopT, retained the ability to interact with NFR5 but not with NFR1 (Fig. S2D).”.

      In line 967: "Both NopT and NopTC after autocleavage exert proteolytic activities" This is confusing as it was suggested earlier that NopTc is a product of the autocleavage. There is no indication of another round of NopTc autocleavage or did I miss something?

      Thank you for bringing this inaccuracy to our attention. There is no second round of NopT autocleavage. We have corrected the text and write: “NopT and not<sup>C</sup> (autocleaved NopT) proteolytically cleave NFR5 at the juxtamembrane domain to release the intracellular domain of NFR5”

      Given the amount of work that went into the research, the presentation of the figures should be considerably improved. For example, in Figure 3F the mutant is not correctly annotated. In figure 5 the term infection foci and IT occur but it is not explained in the legend what these are, where they can be seen in the figure and how the researchers discriminated between the two events.

      In general, the labeling of the figure panels should be improved to facilitate the understanding. For example, in Figure 3 the panels switch between different host plant systems. The plant could be clarified for each panel to aid the reader. The asterisks are not in line with the signal that is supposed to be marked. And so on. I strongly advise to improve the figures.

      Thank you for your valuable suggestions. We acknowledge the importance of clear and informative figure presentation to enhance the understanding of our research findings. In response to your comments, we made a comprehensive revision of the figures to address the mentioned issues:

      (1) We corrected annotations of the mutant in Figure 3F to accurately represent the experimental conditions.

      (2) We revised the legend of Figure 5 and provide clear explanations of the terms "infection foci" and "IT" (infection threads) in the Methods section.

      (3) We improved the labeling of figure panels and improved the writing of the figure legend specifying the protein expression system (N. benthamiana, L. japonicus and E. coli, respectively). . We ensured that the asterisks indicating statistically significant results are properly aligned.

      Furthermore, we carefully reviewed each figure to enhance clarity and readability, including optimizing font size and line thickness. Captions and annotations were also revised.

      Figure 1

      • To verify that the lack of observed cell death is not linked to differential expression levels, an expression control Western blot is essential. In the expression control Western blot given in the supplemental materials (Supplemental fig. 1E), NFR5 is not visible in the first lane.

      We appreciate your comments on the control immunoblot which were made to verify the presence of NFR1, NFR5 and NopT in N. benthamiana.  However, as shown in Supplemental Fig. 1E, the intact NFR5 could not be immuno-detected when co-expressed with NFR1 and NopT. To ensure co-expression of NFR1/NFR5, A. tumefaciens carrying a binary vector with both NFR1 and NFR5 was used. In the revised version, we modified the figure legend accordingly and also included a detailed description of the procedure at lines 165-166

      • Labeling of NFR1/LjNFR1 should be kept consistent between the text and the figures. Currently, the text refers to both NFR1 and LjNFR1 and figures are labelled NFR1. The same is true for NFR5.

      Thank you for pointing out this inconsistency. We revised our manuscript and use now consistently NFR1 and NFR5 without a prefix to avoid any confusions.

      • A clearer description of how cell death was determined would be useful. In the selected pictures in panel D, leaves coexpressing nopT with Bax1 or Cerk1 appear very different from the pictures selected for NopM and AVr3a/R3a.

      We agree that a clearer description of our cell death experiments with N. benthamiana was necessary. We have re-worded the figure legend to provide more detailed information on the criteria used for assessing cell death. Additionally, we show now our images at higher resolution.

      • In panel D, the "Death/Total" ratio is only shown for leaf discs where nopT was coexpressed with the cell-death triggering proteins. Including the ratio for leaf discs where only the cell-death triggering protein (without nopT ) was expressed would make the figure more clear.

      Thank you for this suggestion. To provide a more comprehensive comparison, we included the "Cell death/Total" ratio for all leaf disc images shown in Fig. 1D. 

      Figure 2:

      • A: Split-YFP is not ideal as evidence for colocalization because of the chemical bond formed between the YFP fragments that may lead to artificial trapping/accumulation outside the main expression domains. Overall, the authors should revise if this figure aims to show colocalization or interaction. In the current text, both terms are used, but these are different interpretations.

      We appreciate your concern regarding the use of Split-YFP for colocalization analysis. We carefully reviewed the figure and corresponding text to ensure clarity in the interpretation of the results. The primary aim of this figure was to explore protein-protein interactions rather than strict colocalization. Protein-protein interactions have also been validated by other experiments of our work. We have revised the text accordingly and no longer emphasize on “co-localization”.

      • Given the focus on proteolytic activity in this paper, all blots need to be clearly labeled with size markers, and it would be good to include a supplemental figure with all other bands produced in the Western blot, regardless of their size. Without this, the results in panel 2D seem inconsistent with results presented in figure 3A, since NFR5 does not appear to be cleaved in the Western blot in 2D, but 3A shows cleavage when the same proteins (with different tags) are coexpressed in the same system.

      Thank you for bringing up this point. We ensured that all immunoblots are clearly labeled with size markers in our revised manuscript. We also carefully checked the consistency of the results presented in Figures 2D and Figure 3A and included appropriate clarifications in the revised manuscript. In Figure 2D, we show the bands at around 75 kD  (multi-bands would be detected below, including cleaved NFR5 by NopT, but also other non-specific bands).

      Figure 3:

      • In panel E, NopTC93S cannot cleave His-Sumo-NFR5JM-GFP, but it would be interesting to also show if NopTC93S can bind the NFR5JM fragment. It would also be useful to see this experiment done with the JM of NFP.

      Thank you for the suggestion. We agree that investigating the binding of NopT<sup>C93S</sup> to the NFR5<sup>JM</sup> fragment provides valuable insights into the interaction between NopT and NFR5. In our revised version, we show in the new Supplemental Fig. S4 that NopT interacts with NFR5JM and cleaves NFP<sup>JM</sup>. The Results section has been modified accordingly.

      • The panels in this figure require better labeling. In many panels, asterisks are misplaced relative to the bands they should highlight, and not all blots have size markers or loading controls.

      Thank you for bringing this to our attention. We carefully reviewed the labeling of all panels in Figure 3 to ensure accuracy and clarity. We ensured that asterisks are correctly placed in the figures. We also included size markers and loading controls to improve the quality of the shown immunoblots.

      • Since there is no clear evidence in this figure that the smear in the blot in panel C is phosphorylated NopT, it is recommended to provide a less interpretative label on the blot, and explain the label in the text.

      We appreciate your suggestion regarding the labeling of the blot in panel C of Fig. 3. We revised the label and provided a less interpretative designation in Fig. 3C. We also rephrased the figure legend and the text in the Results section as recommended.

      Figure 4

      • In B, a brief introduction in the text to the function of the Zn-phostag would make the figure easier to understand for more readers.

      Thank you for the suggestion. We agree and have provided a brief explanation in the Results section: “On such gels, a Zn<sup>2+</sup>-Phos-tag bound phosphorylated protein migrates slower than its unbound nonphosphorylated form. Furthermore, we have included the reference (Kato & Sakamoto, 2019) into the Methods section.

      Figure 5:

      • Change "Scar bar" to "Scale bar" in the figure captions

      Thank you for spotting that typo. We have corrected it.

      • Correct the references to the figures in the text

      We carefully reviewed the Figure 5 and made corresponding corrections to improve the quality of our manuscript Please check line 394-451.

      • It should be clarified what was quantified as "infection foci" (C, F, G)

      We revised the legend of Figure 5 and provide now explanations of the terms "infection foci" and "IT" (infection threads) in the Methods section.  Please check line 399-451.

      • It is recommended to use pictures that are from the same region of the plant root (the susceptible zone). The pictures in panel A appear to be from different regions, since the density of root hairs is different.

      Thank you for bringing this to our attention. We ensured that the images selected for panel A were from the same region of the plant root to guarantee consistency and accuracy of the comparison.

      • Panel G should be labeled so it is clearer that nopT is being expressed in L. japonicus transgenic roots.

      We have labeled this panel more clearly to help the reader understand that nopT was expressed in transgenic L. japonicus roots.

      • Panel F is missing statistical tests for ITs

      We apologize and have included the results of our statistical tests for ITs.

      Figure 6:

      • The model presented in panel E misrepresents the role of NFR5 according to the results in the paper. From the evidence presented, it is not clear if the observed rhizobial infection phenotype is due to reduced abundance of full-length NFR5, or if the cleaved NFR5 fragment is suppressing infection. Additionally, S. fredii should not be drawn so close to the plasma membrane, since the bacteria are located outside the cell wall when the T3SS is active.

      We appreciate your comment which helps us to improve the interpretation of our results. We agree that the model should accurately reflect the uncertainties regarding the role of NFR5. We revised the model (positioning of S. fredii etc.) and write in the Discussion:

      “NopT impairs the function of the NFR1/NFR5 receptor complex. Cleavage of NFR5 by NopT reduces its protein levels. Possible inhibitory effects of NFR5 cleavage products on NF signaling are unknown but cannot be excluded.”

      Reviewer #2 (Recommendations For The Authors):

      (1) Some minor weaknesses need addressing: In Figure 5A, the root hair density in the two images appears significantly different. Are these images representative of each treatment?

      We appreciate your attention to detail and the importance of ensuring that the images in Figure 5A are representative. We carefully reviewed our image selection process and confirm that the shown images are indeed representative of each treatment group. In our revised version, we show additional images and also improved the text in the figure legend. Furthermore, we performed additional GUS staining tests and the new data are shown in Fig 5A abd 5B.

      (2) Additionally, please ensure consistency in the format of genotype names throughout the manuscript. For instance, in Line 897, "Italy" should be used in place of "N. benthamiana."

      We thank you for pointing out the format of genotype names and corrected our manuscript as requested.

    1. Reviewer #1 (Public review):

      Summary:

      The authors introduced their previous paper with the concise statement that "the relationships between lineage-specific attributes and genotypic differences of tumors are not understood" (Chen et al., JEM 2019, PMID: 30737256). For example, it is not clear why combined loss of RB1 and TP53 is required for tumorigenesis in SCLC or other aggressive neuroendocrine (NE) cancers, or why the oncogenic mutations in KRAS or EGFR that drive NSCLC tumorigenesis are found so infrequently in SCLC. This is the main question addressed by the previous and current papers.

      One approach to this question is to identify a discrete set of genetic/biochemical manipulations that are sufficient to transform non-malignant human cells into SCLC-like tumors. One group reported transformation of primary human bronchial epithelial cells into NE tumors through a complex lentiviral cocktail involving inactivation of pRB and p53 and activation of AKT, cMYC and BCL2 (PARCB) (Park et al., Science 2018, PMID: 30287662). The cocktail previously reported by Chen and colleagues to transform human pluripotent stem-cell (hPSC)-derived lung progenitors (LPs) into NE xenografts was more concise: DAPT to inactivate NOTCH signaling combined with shRNAs against RB1 and TP53. However, the resulting RP xenografts lacked important characteristics of SCLC. Unlike SCLC, these tumors proliferated slowly and did not metastasize, and although small subpopulations expressed MYC or MYCL, none expressed NEUROD1.

      MYC is frequently amplified or expressed at high levels in SCLC, and here, the authors have tested whether inducible expression of MYC could increase the resemblance of their hPSC-derived NE tumors to SCLC. These RPM cells (or RPM T58A with stabilized cMYC) engrafted more consistently and grew more rapidly than RP cells, and unlike RP cells, formed liver metastases when injected into the renal capsule. Gene expression analyses reveled that RPM tumor subpopulations expressed NEUROD1, ASCL1 and/or YAP1.

      The hPSC-derived RPM model is a major advance over the previous RP model. This may become a powerful tool for understanding SCLC tumorigenesis and progression and for discovering gene dependencies and molecular targets for novel therapies. However, the specific role of cMYC in this model needs to be clarified.

      Recommended Revision:

      cMYC can drive proliferation, tumorigenesis or apoptosis in a variety of lineages depending on concurrent mutations. For example, in the Park et al., study, normal human prostate cells could be reprogrammed to form adenocarcinoma-like tumors by activation of cMYC and AKT alone, without manipulation of TP53 or RB1. In their previous manuscript, the authors carefully showed the role of each molecular manipulation in NE tumorigenesis. DAPT was required for NE differentiation of LPs to PNECs, shRB1 was required for expansion of the PNECs, and shTP53 was required for xenograft formation. cMYC expression could influence each of these steps, and importantly, could render some steps dispensable. For example, shRB1 was previously necessary to expand the DAPT-induced PNECs, as neither shTP53 nor activation of KRAS or EGFR had no effect on this population, but perhaps cMYC overexpression could expand PNECs even in the presence of pRB, or even induce LPs to become PNECs without DAPT. Similarly, both shRB1 and shTP53 were necessary for xenograft formation, but maybe not if cMYC is overexpressed. If a molecular hallmark of SCLC, such as loss of RB1 or TP53, has become dispensable with the addition of cMYC, this information is critically important in interpreting this as a model of SCLC tumorigenesis.

      To interpret the role of cMYC expression in hPSC-derived RPM tumors, we need to know what this manipulation does without manipulation of pRB, p53 or NOTCH, alone or in combination. There are 7 relevant combinations that should be presented in this manuscript: (1) cMYC alone in LPs, (2) cMYC + DAPT, (3) cMYC + shRB1, (4) cMYC + DAPT + shRB1, (5) cMYC + shTP53, (6) cMYC + DAPT + shTP53, and (7) cMYC + shRB1 + shTP53. Wild-type cMYC is sufficient; further exploration with the T58A mutant would not be necessary.

      Please present the effects of these combinations on LP differentiation to PNECs, expansion of PNECs as well as other lung cells, xenograft formation and histology, and xenograft growth rate and capacity for metastasis. If this could be clarified experimentally, and the results discussed in the context of other similar approaches such as the Park et al., paper, this study would be a major addition to the field.

    2. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review): 

      Summary: 

      The authors introduced their previous paper with the concise statement that "the relationships between lineage-specific attributes and genotypic differences of tumors are not understood" (Chen et al., JEM 2019, PMID: 30737256). For example, it is not clear why combined loss of RB1 and TP53 is required for tumorigenesis in SCLC or other aggressive neuroendocrine (NE) cancers, or why the oncogenic mutations in KRAS or EGFR that drive NSCLC tumorigenesis are found so infrequently in SCLC. This is the main question addressed by the previous and current papers. 

      One approach to this question is to identify a discrete set of genetic/biochemical manipulations that are sufficient to transform non-malignant human cells into SCLC-like tumors. One group reported the transformation of primary human bronchial epithelial cells into NE tumors through a complex lentiviral cocktail involving the inactivation of pRB and p53 and activation of AKT, cMYC, and BCL2 (PARCB) (Park et al., Science 2018, PMID: 30287662). The cocktail previously reported by Chen and colleagues to transform human pluripotent stem-cell (hPSC)-derived lung progenitors (LPs) into NE xenografts was more concise: DAPT to inactivate NOTCH signaling combined with shRNAs against RB1 and TP53. However, the resulting RP xenografts lacked important characteristics of SCLC. Unlike SCLC, these tumors proliferated slowly and did not metastasize, and although small subpopulations expressed MYC or MYCL, none expressed NEUROD1. 

      MYC is frequently amplified or expressed at high levels in SCLC, and here, the authors have tested whether inducible expression of MYC could increase the resemblance of their hPSC-derived NE tumors to SCLC. These RPM cells (or RPM T58A with stabilized cMYC) engrafted more consistently and grew more rapidly than RP cells, and unlike RP cells, formed liver metastases when injected into the renal capsule. Gene expression analyses revealed that RPM tumor subpopulations expressed NEUROD1, ASCL1, and/or YAP1. 

      The hPSC-derived RPM model is a major advance over the previous RP model. This may become a powerful tool for understanding SCLC tumorigenesis and progression and for discovering gene dependencies and molecular targets for novel therapies. However, the specific role of cMYC in this model needs to be clarified. 

      cMYC can drive proliferation, tumorigenesis, or apoptosis in a variety of lineages depending on concurrent mutations. For example, in the Park et al., study, normal human prostate cells could be reprogrammed to form adenocarcinoma-like tumors by activation of cMYC and AKT alone, without manipulation of TP53 or RB1. In their previous manuscript, the authors carefully showed the role of each molecular manipulation in NE tumorigenesis. DAPT was required for NE differentiation of LPs to PNECs, shRB1 was required for expansion of the PNECs, and shTP53 was required for xenograft formation. cMYC expression could influence each of these steps, and importantly, could render some steps dispensable. For example, shRB1 was previously necessary to expand the DAPT-induced PNECs, as neither shTP53 nor activation of KRAS or EGFR had no effect on this population, but perhaps cMYC overexpression could expand PNECs even in the presence of pRB, or even induce LPs to become PNECs without DAPT. Similarly, both shRB1 and shTP53 were necessary for xenograft formation, but maybe not if cMYC is overexpressed. If a molecular hallmark of SCLC, such as loss of RB1 or TP53, has become dispensable with the addition of cMYC, this information is critically important in interpreting this as a model of SCLC tumorigenesis.  

      The reviewer’s suggestion may be possible; indeed, in a recent report from our group (Gardner EE, et al., Science 2024) we have shown, using genetically engineered mouse modeling coupled with lineage tracing, that the cMyc oncogene can selectively expand Ascl1+ PNECs in the lung.

      We agree with the reviewer that not having a better understanding of the individual components necessary and/or sufficient to transform hESC-derived LPs is an important shortcoming of this current work. However, we would like to stress three important points about the comments:  1) tumors were reviewed and the histological diagnoses were certified by a practicing pulmonary pathologist at WCM (our co-author, C. Zhang); 2 )the observed  transcriptional programs were consistent with primary human SCLC; and 3) RB1-proficient SCLC is now recognized as a rare presentation of SCLC (Febrese-Aldana CA, et al., Clin. Can. Res. 2022. PMID: 35792876).

      To interpret the role of cMYC expression in hPSC-derived RPM tumors, we need to know what this manipulation does without manipulation of pRB, p53, or NOTCH, alone or in combination. Seven relevant combinations should be presented in this manuscript: (1) cMYC alone in LPs, (2) cMYC + DAPT, (3) cMYC + shRB1, (4) cMYC + DAPT + shRB1, (5) cMYC + shTP53, (6) cMYC + DAPT + shTP53, and (7) cMYC + shRB1 + shTP53. Wildtype cMYC is sufficient; further exploration with the T58A mutant would not be necessary. 

      We respectfully disagree that an interrogation of the differences between the phenotypes produced by wildtype and Myc(T58A) would not be informative. (Our view is confirmed by the second reviewer; see below.)    It is well established that Myc gene or protein dosage can have profound effects on in vivo phenotypes (Murphy DJ, et al., Cancer Cell 2008. PMID: 19061836). The “RPM” model of variant SCLC developed by Trudy Oliver’s lab relied on the conditional T58A point mutant of cMyc, originally made by Rob Wechsler-Reya. While we do not discuss the differences between Myc and Myc(T58A), it is nonetheless important to present our results with both the WT and mutant MYC constructs, as we are aware of others actively investigating differences between them in GEMM models of SCLC tumor development.

      We agree with the reviewer about the virtues of trying to identify the effects of individual gene manipulations; indeed our original paper (Chen et al., J. Expt. Med. 2019), describing the RUES2derived model of SCLC did just that, carefully dissecting events required to transform LPs towards a SCLC-like state. The central  purpose of the current study was to determine the effects of adding cMyc on the behavior of weakly tumorigenic SCLC-like cells cMyc.  Presenting data with these two alleles to seek effects of different doses of MYC protein seems reasonable.

      This reviewer considers that there should be a presentation of the effects of these combinations on LP differentiation to PNECs, expansion of PNECs as well as other lung cells, xenograft formation and histology, and xenograft growth rate and capacity for metastasis. If this could be clarified experimentally, and the results discussed in the context of other similar approaches such as the Park et al., paper, this study would be a major addition to the field.  

      Reviewer #2 (Public Review): 

      Summary: 

      Chen et al use human embryonic stem cells (ESCs) to determine the impact of wildtype MYC and a point mutant stable form of MYC (MYC-T58A) in the transformation of induced pulmonary neuroendocrine cells (PNEC) in the context of RB1/P53 (RP) loss (tumor suppressors that are nearly universally lost in small cell lung cancer (SCLC)). Upon transplant into immune-deficient mice, they find that RP-MYC and RP-MYC-T58A cells grow more rapidly, and are more likely to be metastatic when transplanted into the kidney capsule, than RP controls. Through single-cell RNA sequencing and immunostaining approaches, they find that these RPM tumors and their metastases express NEUROD1, which is a transcription factor whose expression marks a distinct molecular state of SCLC. While MYC is already known to promote aggressive NEUROD1+ SCLC in other models, these data demonstrate its capacity in a human setting that provides a rationale for further use of the ESC-based model going forward. Overall, these findings provide a minor advance over the previous characterization of this ESC-based model of SCLC published in Chen et al, J Exp Med, 2019. 

      We consider the findings more than a “minor” advance in the development of the model, since any useful model for SCLC would need to form aggressive and metastatic tumors.

      The major conclusion of the paper is generally well supported, but some minor conclusions are inadequate and require important controls and more careful analysis. 

      Strengths:

      (1) Both MYC and MYC-T58A yield similar results when RP-MYC and RP-MYCT58A PNEC ESCs are injected subcutaneously, or into the renal capsule, of immune-deficient mice, leading to the conclusion that MYC promotes faster growth and more metastases than RP controls. 

      (2) Consistent with numerous prior studies in mice with a neuroendocrine (NE) cell of origin (Mollaoglu et al, Cancer Cell, 2017; Ireland et al, Cancer Cell, 2020; Olsen et al, Genes Dev, 2021), MYC appears sufficient in the context of RB/P53 loss to induce the NEUROD1 state. Prior studies also show that MYC can convert human ASCL1+ neuroendocrine SCLC cell lines to a NEUROD1 state (Patel et al, Sci Advances, 2021); this study for the first time demonstrates that RB/P53/MYC from a human neuroendocrine cell of origin is sufficient to transform a NE state to aggressive NEUROD1+ SCLC. This finding provides a solid rationale for using the human ESC system to better understand the function of human oncogenes and tumor suppressors from a neuroendocrine origin. 

      Weaknesses:

      (1) There is a major concern about the conclusion that MYC "yields a larger neuroendocrine compartment" related to Figures 4C and 4G, which is inadequately supported and likely inaccurate. There is overwhelming published data that while MYC can promote NEUROD1, it also tends to correlate with reduced ASCL1 and reduced NE fate (Mollaoglu et al, Cancer Cell, 2017; Zhang et al, TLCR, 2018; Ireland et al, Cancer Cell, 2020; Patel et al, Sci Advances, 2021). Most importantly, there is a lack of in vivo RP tumor controls to make the proper comparison to judge MYC's impact on neuroendocrine identity. RPM tumors are largely neuroendocrine compared to in vitro conditions, but since RP control tumors (in vivo) are missing, it is impossible to determine whether MYC promotes more or less neuroendocrine fate than RP controls. It is not appropriate to compare RPM tumors to in vitro RP cells when it comes to cell fate. Upon inspection of the sample identity in S1B, the fibroblast and basal-like cells appear to only grow in vitro and are not well represented in vivo; it is, therefore, unclear whether these are transformed or even lack RB/P53 or express MYC. Indeed, a close inspection of Figure S1B shows that RPM tumor cells have little ASCL1 expression, consistent with lower NE fate than expected in control RP tumors. 

      We would like to clarify two points related to the conclusions that we draw about MYC’s ability to promote an increase in the neuroendocrine fraction in hESC-derived cultures:  1) The comparisons in Figures 4C were made between cells isolated in culture following the standard 50 day differentiation protocol, where, following generation of LPs around day 25, MYC was added to the other factors previously shown to enrich for a PNEC phenotype (shRB1, shTP53, and DAPT). Therefore, the argument that MYC increased the frequency of “neuroendocrine cells” (which we define by a gene expression signature) is a reasonable conclusion in the system we are using; and 2) following injection of these cells into immunocompromised mice, an ASCL1-low / NEUROD1-high presentation is noted (Supplemental Figures 1F-G). In the few metastases that we were able use to sequence bulk RNA, there is an even more pronounced increase in expression of NEUROD1 with a decrease in ASCL1.

      Some confusion may have arisen from our previous characterization of neuroendocrine (NE) cells using either ASCL1 or NEUROD1 as markers. To clarify, we have now designated cells positive for ASCL1 as classical NE cells and those positive for NEUROD1 as the NE variant. According to this revised classification, our findings indicate that MYC expression leads to an increase in the NEUROD1+ NE variant and a decrease in ASCL1+ classical NE cells. This adjustment has been reflected on the results section titled, “Inoculation of the renal capsule facilitates metastasis of the RUES2-derived RPM tumors” of the manuscript.  

      From the limited samples in hand, we compared the expression of ASCL1 and NEUROD1 in the weakly tumorigenic hESC RP cells after successful primary engraftment into immunocompromised mice. As expected, the RP tumors were distinguished by the lack of expression of NEUROD1, compared to levels observed in the RPM tumors.

      In addition, since MYC appears to require Notch signaling to induce  NE fate (cf Ireland et al), the presence of DAPT in culture could enrich for NE fate despite MYC's presence. It's important to clarify in the legend of Fig 4A which samples are used in the scRNA-seq data and whether they were derived from in vitro or in vivo conditions (as such, Supplementary Figure S1B should be provided in the main figure). Given their conclusion is confusing and challenges robustly supported data in other models, it is critical to resolve this issue properly. I suspect when properly resolved, MYC actually consistently does reduce NE fate compared to RP controls, even though tumors are still relatively NE compared to completely distinct cellular identities such as fibroblasts.

      We have clarified the source of tumor sequencing data and the platform (single cell or bulk) in Figure 4 and Supplemental Figure 1. To reiterate – the RNA sequencing results from paired metastatic and primary tumors from the RPM model are derived from bulk RNA;  the single cell RNA data in RP or RPM datasets are from cells in culture.  These distinctions are clarified in the legend to Supplemental Figure 1.

      (2) The rigor of the conclusions in Figure 1 would be strengthened by comparing an equivalent number of RP animals in the renal capsule assay, which is n = 6 compared to n = 11-14 in the MYC conditions.

      As we did not perform a power calculation to determine a sample size required to draw a level of statistical significance from our conclusions, this comment is not entirely accurate. Our statistical rigor was limited by the availability of samples from the RP tumor model.

      (3) Statistical analysis is not provided for Figures 2A-2B, and while the results are compelling, may be strengthened by additional samples due to the variability observed. 

      We acknowledge that the cohorts are relatively small but we have added statistical comparisons in Figure 2B. 

      (4a) Related to Figure 3, primary tumors and liver metastases from RPM or RPM-T58A-expressing cells express NEUROD1 by immunohistochemistry (IHC) but the putative negative controls (RP) are not shown, and there is no assessment of variability from tumor to tumor, ie, this is not quantified across multiple animals. 

      The results of H&E and IF staining for ASCL1, NEUROD1, CGRP, and CD56 in negative control (RP tumors) are presented in the updated Figure 3F-G.

      (4b) Relatedly, MYC has been shown to be able to push cells beyond NEUROD1 to a double-negative or YAP1+ state (Mollaoglu et al, Cancer Cell, 2017; Ireland et al, Cancer Cell, 2020), but the authors do not assess subtype markers by IHC. They do show subtype markers by mRNA levels in Fig 4B, and since there is expression of ASCL1, and potentially expression of YAP1 and POU2F3, it would be valuable to examine the protein levels by IHC in control RP vs. RPM samples.

      YAP1 positive SCLC is still somewhat controversial, so it is not clear what value staining for YAP1 offers beyond showing the well-established markers, ASCL1 and NEUROD1.  

      (5) Given that MYC has been shown to function distinctly from MYCL in SCLC models, it would have raised the impact and value of the study if MYC was compared to MYCL or MYCL fusions in this context since generally, SCLC expresses a MYC family member. However, it is quite possible that the control RP cells do express MYCL, and as such, it would be useful to show. 

      We now include Supplemental Figure S2 to illustrate four important points raised by this reviewer and others:  1) expression of MYC family members in the merged dataset (RP and RPM) is low or undetectable in the basal/fibroblast cultures; 2) MYC does have a weak correlation with EGFP in the neuroendocrine cluster when either WT MYC or T58A MYC is overexpressed; 3) MYCL and MYCN are detectable, but at low levels compared to CMYC; and 4) Expression of  ASCL1 is anticorrelated with MYC expression across the merged single cell datasets using RP and RPM models.

      Reviewer #3 (Public Review): 

      Summary: 

      The authors continue their study of the experimental model of small cell lung cancer (SCLC) they created from human embryonic stem cells (hESCs) using a protocol for differentiating the hESCs into pulmonary lineages followed by NOTCH signaling inactivation with DAPT, and then knockdown of TP53 and RB1 (RP models) with DOX inducible shRNAs. To this published model, they now add DOX-controlled activation of expression of a MYC or T58A MYC transgenes (RPM and RPMT58A models) and study the impact of this on xenograft tumor growth and metastases. Their major findings are that the addition of MYC increased dramatically subcutaneous tumor growth and also the growth of tumors implanted into the renal capsule. In addition, they only found liver and occasional lung metastases with renal capsule implantation. Molecular studies including scRNAseq showed that tumor lines with MYC or T58A MYC led surprisingly to more neuroendocrine differentiation, and (not surprisingly) that MYC expression was most highly correlated with NEUROD1 expression. Of interest, many of the hESCs with RPM/RPMT58A expressed ASCL1. Of note, even in the renal capsule RPM/RPMT58A models only 6/12 and 4/9 mice developed metastases (mainly liver with one lung metastasis) and a few mice of each type did not even develop a renal sub capsule tumor. The authors start their Discussion by concluding: " In this report, we show that the addition of an efficiently expressed transgene encoding normal or mutant human cMYC can convert weakly tumorigenic human PNEC cells, derived from a human ESC line and depleted of tumor suppressors RB1 and TP53, into highly malignant, metastatic SCLC-like cancers after implantation into the renal capsule of immunodeficient mice.". 

      Strengths: 

      The in vivo study of a human preclinical model of SCLC demonstrates the important role of c-Myc in the development of a malignant phenotype and metastases. Also the role of c-Myc in selecting for expression of NEUROD1 lineage oncogene expression. 

      Weaknesses: 

      There are no data on results from an orthotopic (pulmonary) implantation on generation of metastases; no comparative study of other myc family members (MYCL, MYCN); no indication of analyses of other common metastatic sites found in SCLC (e.g. brain, adrenal gland, lymph nodes, bone marrow); no studies of response to standard platin-etoposide doublet chemotherapy; no data on the status of NEUROD1 and ASCL1 expression in the individual metastatic lesions they identified. 

      We have acknowledged from the outset that our study has significant limitations, as noted by this reviewer, and we explained in our initial letter of response why we need to present this limited, but still consequential, story at this time. 

      In particular, while we have attempted orthotopic transplantations of RPM tumor cells into NSG mice (by tail vein or intra-pulmonary injection, or intra-tracheal instillation of tumor cells), these methods were not successful in colonizing the lung. Additionally, we have compared the efficacy of platinum/etoposide to that of removing DOX in established RPM subcutaneous tumors, but we chose not to include these data as we lacked a chemotherapy responsive tumor model, and thus could not say with confidence that the chemotherapeutic agants were active and that the RPM models were truly resistant to standard SCLC chemotherapy. In a discussion about other metastatic sites, we have now included the following text: 

      “In animals administered DOX, histological examinations showed that approximately half developed metastases in distant organs, including the liver or lung (Figure 1D). No metastases were observed in the bone, brain, or lymph nodes. For a more detailed assessment, future studies could employ more sensitive imaging methods, such as luciferase imaging.”

      Recommendations for the authors:

      Reviewer #2 (Recommendations For The Authors): 

      Technical points related to Major Weakness #1: 

      For Figure 4: Cells were enriched for EGFP-high cells only, under the hypothesis that cells with lower EGFP may have silenced expression of the integrated vector. Since EGFP is expressed only in the shRB1 construct, selection for high EGFP may inadvertently alter/exclude heterogeneity within the transformed population for the other transgenes (shP53, shMYC/MYC-T58A). Can authors include data to show the expression of MYC/MYC T58A in EGFP-high v -med v-low cells? MYC levels may alter the NEdifferentiation status of tumor cells. 

      Please now refer to Supplemental Figure S2.

      Related to the appropriateness of the methods for Figure 4C, the authors state, "We performed differential cluster abundance analysis after accounting for the fraction of cells that were EGFP+". If only EGFP+ cells were accounted for in the analysis for 4C, the majority of RP cells in the "Neuroendocrine differentiated" cluster would not be included in the analysis (according to EGFP expression in Fig S1A-B), and therefore inappropriately reduce NE identity compared to RPM samples that have higher levels of EGFP. 

      There is no consideration or analysis of cell cycling/proliferation until after the conclusion is stated. Yet, increased proliferation of MYC-high vs MYC-low cultures would enhance selection for more tumors (termed "NE-diff") than non-tumors (basal/fibroblast) in 2D cultures. 

      The expression of MYC itself isn't assessed for this analysis but assumed, and whether higher levels of MYC/MYC-T58A may be present in EGFP+ tumor cells that are in the NE-low populations isn't clear. Can MYC-T58A/HA also be included in the reference genome? 

      We did not include an HA tag in our reference transcriptome. For [some] answers to this and other related questions, please refer to Supplemental Figure S2.

      Reviewer #3 (Recommendations For The Authors): 

      (1) The experiments are all technically well done and clearly presented and represent a logical extension exploring the role of c-Myc in the hESC experimental model system. 

      We appreciate this supportive comment!

      (2) It is of great interest that both the initial RP model only forms "benign" tumors and that with the addition of a strong oncogene like c-myc, where expression is known to be associated with a very bad prognosis in SCLC, that while one gets tumor formation there are still occasional mice both for subcutaneous and renal capsule test sites that don't get tumors even with the injection of 500,000 RPM/RPMT58A cells. In addition, of the mice that do form tumors, only ~50% exhibit metastases from the renal sub-capsule site. The authors need to comment on this further in their Discussion. To me, this illustrates both how incredibly resistant/difficult it is to form metastases, thus indicating the need for other pathways to be activated to achieve such spread, and also represents an opportunity for further functional genomic tests using their preclinical model to systematically attack this problem. Obvious candidate genes are those recently identified in genetically engineered mouse models (GEMMs) related to neuronal behavior. In addition, we already know that full-fledged patient-derived SCLC when injected subcutaneously into immune-deprived mice don't exhibit metastases - thus, while the hESC RPM result is not surprising, it indicates to me the power of their model (logs less complicated genetically than a patient SCLC) to sort through a mechanism that would allow metastases to develop from subcutaneous sites. The authors can point these things out in their Discussion section to provide a "roadmap" for future research. 

      Although we remain mindful of the relatively small cohorts we have studied, the thrust of Reviewer #3’s comments is now included in the Discussion. And there is, of course, a lot more to do, and it has taken several years already to get to this point. Additional information about the prolonged gestation of this project and about the difficulties of doing more in the near future was described in our initial response to reviewers/Editor, included near the start of this letter.    

      (3) I will state the obvious that this paper would be much more valuable if they had compared and contrasted at least one of the myc family members (MYCL or MYCN) with the CMYC findings whatever the results would be. Most SCLC patients develop metastases, and most of their tumors don't express high levels of CMYC (and often use MYCL). In any event, as the authors Discuss, this will be an important next stage to test.

      We have acknowledged and explained the limitations of the work in several ways. Further, we were unaware of the relationship between metastases and the expression of MYC and MYCL1 noted by the reviewer; we will look for confirmation of this association in any future studies, although we have not encountered it in current literature.

      (4) Their assays for metastases involved looking for anatomically "gross" lesions. While that is fine, particularly given that the "gross" lesions they show in figures are actually pretty small, we still need to know if they performed straightforward autopsies on mice and looked for other well-known sites of metastases in SCLC patients besides liver and lung - namely lymph nodes, adrenal, bone marrow, and brain. I would guess these would probably not show metastatic growth but with the current report, we don't know if these were looked for or not. Again, while this could be a "negative" result, the paper's value would be increased by these simple data. Let's assume no metastases are seen, then the authors could further strengthen the case for the value of their hESC model in systematically exploring with functional genomics the requirements to achieve metastases to these other sites.

      We have included descriptions of what we found and didn’t find at other potential sites of metastasis in the results section, with the following sentences: 

      “In animals administered DOX, histological examinations showed that approximately half developed metastases in distant organs, including the liver or lung (Figure 1D). No metastases were observed in the bone, brain, or lymph nodes. For a more detailed assessment, future studies could employ more sensitive imaging methods, such as luciferase imaging.”

      (5) Related to this, we have no idea if the mice that developed liver metastases (or the one mouse with lung metastasis) had more than one metastatic site. They will know this and should report it. Again, my guess is that these were isolated metastases in each mouse. Again, they can indicate the value of their model in searching for programs that would increase the number of the various organs. 

      We appreciate the suggestion. We observed that one of the mice developed metastatic tumors in both the liver and lungs. This information has been incorporated into the Results section.

      (6) While renal capsule implantation for testing growth and metastatic behavior is reasonable and based on substantial literature using this site for implantation of patient tumor specimens, what would have increased the value of the paper is knowing the results from orthotopic (lung implantation). Whatever the results were (they occurred or did not occur) they will be important to know. I understand the "future experiments" argument, but in reading the manuscript this jumped out at me as an obvious thing for the authors to try. 

      We conducted orthotopic implantation several ways, including via intra-tracheal instillation of 0.5 million RP or RPM cells in PBS per mouse. However, none of the subjects (0/5 mice) developed tumor-like growths and the number of animals used was small. Further, this outcome could be attributed to biological or physical factors. For instance, the conducting airway is coated with secretory cells producing protective mucins and may not have retained the 0.5 million cells. This is one example that may have hindered effective colonization. Future adjustments, such as increasing the number of cells, embedding them in Matrigel, or damaging the airway to denude secretory cells and trigger regeneration might alter the outcomes. These ideas might guide future work to strengthen the utility of the models.

      (7) Another obvious piece of data that would have improved the value of this manuscript would be to know whether the RPM tumors responded to platin-etoposide chemotherapy. Such data was not presented in their first RP hESC notch inhibition paper (which we now know generated what the authors call "benign" tumors). While I realize chemotherapy responses represent other types of experiments, as the authors point out one of the main reasons they developed their new human model was for therapy testing. Two papers in and we are all still asking - does their model respond or not respond dramatically to platin-etoposide therapy? Whatever the results are they are a vital next step in considering the use of their model. 

      Please see the comments above regarding our decision not to include data from a clinical trial that lacked appropriate controls.

      (8) The finding of RPM cells that expressed NEUROD1, ASCL1, or both was interesting. From the way the data were presented, I don't have a clear idea which of these lineage oncogenes the metastatic lesions from ~11 different mice expressed. Whatever the result is it would be useful to know - all NEUROD1, some ASCL1, some mixed etc.

      Based on the bulk RNA-sequencing of a few metastatic sites (Figure 4H), what we can demonstrate is that all sites were NEUROD1 and expressed low or no detectable  ASCL1.

      (9) While several H&E histologic images were presented, even when I enlarged them to 400% I couldn't clearly see most of them. For future reference, I think it would be important to have several high-quality images of the RP, RPM, RPMT58A subcutaneous tumors, sub-renal capsule tumors, and liver and lung metastatic lesions. If there is heterogeneity in the primary tumors or the metastases it would be important to show this. The quality of the images they have in the pdf file is suboptimal. If they have already provided higher-quality images - great. If not, I think in the long run as people come back to this paper, it will help both the field and the authors to have really great images of their tumors and metastases. 

      We have attempted to improve the quality of the embedded images. Digital resolution is a tradeoff with data size – higher resolution images are always available upon request, but may not be suitable  for generation of figures in a manuscript viewed on-line.

    1. Author response:

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

      Reviewer 1 (Public Review):

      Summary:

      Here the authors convincingly identify and characterize the SERBP1 interactome and further define its role in the nucleus, where it is associated with complexes involved in splicing, cell division, chromosome structure, and ribosome biogenesis. Many of the SERBP1-associated proteins are RNA-binding proteins and SERBP1 exerts its impact, at least in part, through these players. SERBP1 is mostly disordered but along with its associated proteins displays a preference for G4 binding and can bind to PAR and be PARylated. They present data that strongly suggest that complexes in which SERBP1 participates are assembled through G4 or PAR binding. The authors suggest that because SERBP1 lacks traditional functional domains yet is clearly involved in distinct regulatory complexes, SERBP1 likely acts in the early steps of assembly through the recognition of interacting sites present in RNA, DNA, and proteins.

      Strengths:

      The data is very convincing and demonstrated through multiple approaches.

      Weaknesses:

      No weaknesses were identified by this reviewer.

      Reviewer #2 (Public Review):

      Summary:

      In this study the authors have used pull-down experiments in a cell line overexpressing tagged SERPINE1 mRNA binding protein 1 (SERBP1) followed by mass spectrometry-based proteomics, to establish its interactome. Extensive analyses are performed to connect the data to published resources. The authors attempt to connect SERBP1 to stress granules and Alzheimer's disease-associated tau pathology. Based on the interactome, the authors propose a cross-talk between SERBP1 and PARP1 functions.

      Strengths:

      The main strength of this study lies in the proteomics data analysis, and its effort to connect the data to published studies.

      Weaknesses:

      While the authors propose a feedback regulatory model for SERBP1 and PARP1 functions, strong evidence for PARylation modulating SERBP1 functions is lacking. PARP inhibition decreasing the amount of PARylated proteins associated with SERBP1 and likely all other PARylated proteins is expected. This study is also incomplete in its attempt to establish a connection to Alzheimer's disease related tauopathy. A single AD case is not sufficient, and frozen autopsy tissue shows unexplained punctate staining likely due to poor preservation of cellular structures for immunohistochemistry. There is a lack of essential demographic data, source of the tissue, brain regions shown, and whether there was an IRB protocol for the human brain tissue. The presence of phase-separated transient stress granules in an autopsy brain is unlikely, even if G3BP1 staining is present. Normally, stress granule proteins move to the cytoplasm under cellular stress, whereas SERBP1 becomes nuclear. The co-localization of abundant cytoplasmic G3BP1 and SERBP1 under normal conditions does not indicate an association with stress granules.

      Reviewer #3 (Public Review):

      Summary:

      A survey of SERBP1-associated functions and their impact on the transcriptome upon gene depletion, as well as the identification of chemical inhibitors upon gene over-expression.

      Strengths:

      (1) Provides a valuable resource for the community, supported by statistical analyses.

      (2) Offers a survey of different processes with correlation data, serving as a good starting point for the community to follow up.

      Weaknesses:

      (1) The authors provided numerous correlations on diverse topics, from cell division to RNA splicing and PARP1 association, but did not follow up their findings with experiments, offering little mechanistic insight into the actual role of SERBP1. The model in Figure 5D is entirely speculative and lacks data support in the manuscript.

      Our article includes several pieces of evidence that support SERBP1’s role in splicing, translation, cell division and association with PARP1. We respectfully disagree that the model in Figure 5D is speculative. The goal of our study was to generate initial evidence of SERBP1 involvement in different biological processes based on its interactome. The characterization of molecular mechanisms in all these scenarios requires a substantial amount work and will the topic of follow up manuscripts. 

      (2) Following up with experiments to demonstrate that their findings are real (e.g., those related to splicing defects and the PARylation/PAR-binding association) would be beneficial. For example, whether the association between PARP1 and SERBP1 is sensitive to PAR-degrading enzymes is unclear.

      We included experiments showing the interaction between endogenous SERBP1 and PARP1. Additionally, we demonstrated that SERBP1 interaction with PARP1 was disrupted when cells are treated with PARP inhibitors.

      (3) They did not clearly articulate how experiments were performed. For instance, the drug screen and even the initial experiment involving the pull-down were poorly described. Many in the community may not be familiar with vectors such as pSBP or pUltra without looking up details.

      We provided additional details about the vectors and expanded the description of experiments in results and figure legends.

      (4) The co-staining of SERBP1 with pTau, PARP1, and G3BP1 in the brain is interesting, but it would be beneficial to follow up with immunoprecipitation in normal and patient samples to confirm the increased physical association.

      Thank you for this suggestion. We performed instead a Proximity Ligation Assay (PLA) on human tissue. Data was included in Fig. 7B and C. PLA between pTau and SERBP1 confirmed interaction in AD cortices as well as SERBP1 with PARP1.

      (5) The combination index of 0.7-0.9 for PJ34 + siSERBP1 is weak. Could this be due to the non-specific nature of the drug against other PARPs? Have the authors looked into this possibility?

      The combination index could be considered weak in the case of U251 cells but not in the case of U343 cells. PJ34 has been shown to be mainly a PARP-1 inhibitor. Different PJ34 concentrations and different drugs will be examined in future studies. It is worth mentioning that in a genetic screening, SERBP1 has been shown to increase sensitivity to different PARP inhibitors (PMID: 37160887). This information is included in the manuscript.

      Reviewer #1 (Recommendations For The Authors):

      This is a really well-done piece of research that is written very well. The data are very convincing and the conclusions are well supported. Some wording in Figures 2B and D is pixelated and hard to read. All the figure legends could benefit from being expanded but this is especially true for Figures 2, 3, 7, and 8. There is a ton of data being presented and a very limited description of what was done and what is being concluded. Some of the content may not be fully comprehended by some readers with limited descriptions.

      We revised all figures to assure images are clear and their resolution is high. We expanded all figure legends to provide a better explanation of the experimental design.

      Reviewer #2 (Recommendations For The Authors):

      The "merged" pdf file is the same as the "article".

      Individual files were uploaded this time.

      The abstract should spell out acronyms, such as the name of the protein Serpine1 mRNA-binding protein 1 (SERBP1).

      This was not included since the abstract has a word limit.

      "SERBP1 (Serpine1 mRNA-binding protein 1) is a unique member of this group of RBPs". In what way is it unique?

      The text was modified to better explain SERBP1’s singularities.

      "RBPs containing IDRs and RGG motifs are particularly relevant in the nervous system. Their misfolding contributes to the formation of pathological protein aggregates in Alzheimer's disease (AD), Frontotemporal Lobar Dementia (FTLD), Amyotrophic Lateral Sclerosis (ALS), and Parkinson's disease (PD)" -> while TDP-43 and FUS in ALS/FTD may fit this description, it is not true for tau and amyloid-beta (AD) and alpha-synuclein (PD).

      "SERBP1 is a unique RBPs containing IDRs and RGG motifs yet lacks other readily recognizable, canonical or structured RNA binding motifs. Moreover, SERBP1 has been observed by our study and others as common Tau interactor in Alzheimer’s Disease (AD) brains. RBPs containing IDRs (e.g. TDP-43, FUS, hnRNPs, TIA1) have been shown self-aggregate and co-aggregate with pathogenic amyloids (Tau, Aβ-amyloid and α-Synuclein)  in AD, Frontotemporal Lobar Dementia (FTLD), Amyotrophic Lateral Sclerosis (ALS), and Parkinson's disease (PD) and this suggest that, like other IDRs RBPs, SERBP1 contributes to RNA dysmetabolism in neurodegenerative diseases”.

      While the authors propose a feedback regulatory model for SERBP1 and PARP1 functions, strong evidence for PARylation modulating SERBP1 functions is lacking. The fact that PARP inhibition decreases the amount of PARylated proteins associated with SERBP1 and likely all other PARylated proteins is expected and cannot count as evidence.

      We included data showing that treatment with PJ34 (PARP inhibitor) decreases SERBP1 interaction with PARP1 and G3BP1. We are currently conducting a more extensive analysis to identify SERBP1 PAR binding domain and the impact of PARP inhibition on its interactions and functions. These experiments will be included in a new manuscript.

      A single AD case is not sufficient.

      Sorry for the poor clarity. We included in the study 6 cases from age-matched controls and 6 cases of AD. We summarize all cases demographics, and the experimental application assigned to each case in Table 1. Moreover, we included a paragraph regarding Human tissue harvesting.

      Most western blot data are not quantified from multiple replicates, as required.

      Quantifications are now provided.

      FTLD - frontotemporal lobar degeneration (not dementia).

      This was corrected.

      Frozen autopsy tissue is problematic due to poor preservation. The staining presented here shows unexplained punctate staining likely due to poor preservation of cellular structures for immunohistochemistry.

      We included a paragraph regarding human tissue harvesting. We have successfully used frozen tissues in our previous studies, observing a well preserved neuronal and tissue structure (PMIDs: 32855391, 31532069 and 30367664)

      The presence of phase-separated stress granules in tissue is controversial since these are transient structures.

      Normally, stress granule proteins move to the cytoplasm under cellular stress, whereas SERBP1 becomes nuclear. The co-localization of abundant (and partially overexposed) cytoplasmic G3BP1 and SERBP1 under normal conditions is not evidence for association with stress granules. Does induction of stress granule formation lead to colocalization in stress granules? The H2O2 experiment suggests otherwise.

      RBPs implicated in stress response move to stress granules when cells are exposed to stress. SERBP1 has been shown to shuttle to stress granules and nucleus in stress conditions (PMID: 24205981). Our results are in agreement.

      Using co-IF, we observed some overlap between G3BP1 and SERBP1 in AD tissues. As shown in Fig. S6A and B, 50% of stress granules overlap with SERBP1 signal. On the contrary, it is hard to assess their relationship in aged-matched control brains where stress granules form and accumulate with a lower rate than in AD. SERBP1 is not very abundant in normal brains.  It is known that RNA-Binding Proteins aggregation and/or dysfunctional LLPS dysregulate stress granules formation and accumulation in AD and other proteinopathies (PMIDs 30853299, 27256390 and 31911437). However, it is too early to determine the role of SERBP1 and its contribution to stress granules formation and accumulation. We will examine this topic in future studies.

      There is a lack of essential demographics data (age, clinical diagnosis, path diagnosis, co-pathologies, Braak stage, etc.), source of the tissue (what brain bank?), brain regions shown, and whether there was informed consent for the collection and use of human brain tissue.

      We included the information requested in materials and methods section.

      Reviewer #3 (Recommendations For The Authors):

      The authors need to better explain their experimental rationale and approach in the main text, not just in the supplementary materials.

      We have extensively revised the text to provide a better description of experiments in the results section and figure legends.

    1. Reviewer #2 (Public review):

      Summary:

      The authors use a combination of techniques including viral genetics, in vitro reporters, and purified proteins and RNA to interrogate how the Japanese encephalitis virus maintains translation of its RNA to produce viral proteins after the host cell has shut down general translation as a means to block viral replication. They report a role for the RNA helicase DDX3 in promoting virus translation in a cap-independent manner through binding a dumbbell RNA structure in the 3' untranslated region previously reported to drive Japanese encephalitis virus cap-independent translation and a stem-loop at the viral RNA 5' end.

      Strengths:

      The authors clearly show that the Japanese encephalitis virus does not possess an IRES activity to initiate translation using a range of mono- and bi-cistronic mRNAs. Surprisingly, using a replicon system, the translation of a capped or uncapped viral RNA is reported to have the same translation efficiency when transfected into cells. The authors have applied a broad range of techniques to support their hypotheses.

      Weaknesses:

      (1) The authors' original experiments in Figure 1 where the virus is recovered following transfection of in vitro transcribed viral RNA with alternative 5' ends such as capped or uncapped ignore that after a single replication cycle of that transfected RNA, the subsequent viral RNA will be capped by the viral capping proteins making the RNA in all conditions the same.

      (2) The authors report that deletion of the dumbbell and the large 3' stem-loop RNA reduce replication of a Japanese encephalitis virus replicon. These structures have been reported for other flaviviruses to be important respectively for the accumulation of short flaviviral RNAs that can regulate replication and stability of the viral RNA that lacks a polyA tail. The authors don't show any assessment of RNA stability or degradation state.

      (3) The authors propose a model for DDX3 to drive 5'-3' end interaction of the Japanese encephalitis virus viral genome but no direct evidence for this is presented.

      (4) The authors' final model in Figure 10 proposes a switch from a cap-dependent translation system in early infection to cap-independent DDX3-driven translation system late in infection. The replicon data that measures translation directly however shows identical traces for capped and uncapped RNAs in all untreated conditions so that which mechanism is used at different stages of the infection is not clear.

    2. Author response:

      Reviewer #1 (Public review):

      Summary:

      In cells undergoing Flavivirus infection, cellular translation is impaired but the viruses themselves escape this inhibition and are efficiently translated. In this study, the authors use very elegant and direct approaches to identify the regions in the 5' and 3' UTRs that are important for this phenomenon and then use them to retrieve two cellular proteins that associate with them and mediate translational shutoff evasion (DDX3 and PABP1). A number of experimental approaches are used with a series of well-controlled experiments that fully support the authors' conclusions.

      Strengths:

      The work identifies the regions in the 5' and 3' UTRs of the viral genome that mediate the escape of JEV from cellular transcriptional shutoff, they evaluate the infectivity of the mutant viruses bearing or not these structures and even explore their pathogenicity in mice. They then identify the cellular proteins that bind to these regions (DDX3 and PABP1) and determine their role in translation blockade escape, in addition to examining and assessing the conservation of the stem-loop identified in JEV in other Flaviviridae.

      In almost all of their systematic analyses, translational effects are put in parallel with the replication kinetics of the different mutant viruses. The experimental thread followed in this study is rigorous and direct, and all experiments are truly well-controlled, fully supporting the authors' conclusions.

      We greatly appreciate the reviewer's recognition of this study. We elucidated the role of UTR in translation blockade escape of JEV from the perspective of the RNA structure of the UTR and its interaction with host proteins (DDX3 and PABP1), and we hope that this study could gain wider recognition.

      Reviewer #2 (Public review):

      Summary:

      The authors use a combination of techniques including viral genetics, in vitro reporters, and purified proteins and RNA to interrogate how the Japanese encephalitis virus maintains translation of its RNA to produce viral proteins after the host cell has shut down general translation as a means to block viral replication. They report a role for the RNA helicase DDX3 in promoting virus translation in a cap-independent manner through binding a dumbbell RNA structure in the 3' untranslated region previously reported to drive Japanese encephalitis virus cap-independent translation and a stem-loop at the viral RNA 5' end.

      Strengths:

      The authors clearly show that the Japanese encephalitis virus does not possess an IRES activity to initiate translation using a range of mono- and bi-cistronic mRNAs. Surprisingly, using a replicon system, the translation of a capped or uncapped viral RNA is reported to have the same translation efficiency when transfected into cells. The authors have applied a broad range of techniques to support their hypotheses.

      We are grateful for the reviewer’s recognition of the thoroughness and multi-faceted nature of our study.

      Weaknesses:

      (1) The authors' original experiments in Figure 1 where the virus is recovered following transfection of in vitro transcribed viral RNA with alternative 5' ends such as capped or uncapped ignore that after a single replication cycle of that transfected RNA, the subsequent viral RNA will be capped by the viral capping proteins making the RNA in all conditions the same.

      Thank you for your suggestion. We share the same viewpoint as the reviewer. After the first round of translation of the uncapped viral RNA, the subsequent viral RNA will inevitably be capped by the viral capping proteins. However, there is no doubt that the transfected cells do not contain viral capping proteins in the initial transfection stage, which directly proved that JEV possesses a cap-independent translation initiation mechanism.

      (2) The authors report that deletion of the dumbbell and the large 3' stem-loop RNA reduce replication of a Japanese encephalitis virus replicon. These structures have been reported for other flaviviruses to be important respectively for the accumulation of short flaviviral RNAs that can regulate replication and stability of the viral RNA that lacks a polyA tail. The authors don't show any assessment of RNA stability or degradation state.

      Thank you for your suggestion. We agree that a rigorous supplementary experiment for the assessment of RNA stability or degradation state is desirable. To address this, the relative amounts of viral RNA with the deletion of DB2 or sHP-SL will be determined by real-time RT-PCR analysis in transfected cells at multiple time points, which will allow us to test whether the deletion of the dumbbell and the large 3' stem-loop RNA reduce the RNA stability of JEV.

      (3) The authors propose a model for DDX3 to drive 5'-3' end interaction of the Japanese encephalitis virus viral genome but no direct evidence for this is presented.

      Thank you for your suggestion. In this study, we did not have direct evidence to suggest that DDX3 can drive the 5'-3' end interaction of the Japanese encephalitis virus viral genome, which is indeed a limitation of our research. In the revision, we will more explicitly discuss the interrelationship between DDX3 and 5'-3' UTR, as well as incorporate a discussion of these points into the main text, acknowledging the limitations of our current models.

      (4) The authors' final model in Figure 10 proposes a switch from a cap-dependent translation system in early infection to cap-independent DDX3-driven translation system late in infection. The replicon data that measures translation directly however shows identical traces for capped and uncapped RNAs in all untreated conditions so that which mechanism is used at different stages of the infection is not clear.

      Thank you for your suggestion. The replicon transfection system was used to evaluate the key viral element for cap-independent translation. We only monitored reporter gene expression from 2 hpt to 12 hpt, which can’t fully recapitulate the different stages of JEV infection. In the experimental results Figure 1 and Figure 1-figure supplement 1, we demonstrated that JEV significantly induced the host translational shutoff at 36 hpi, while the expression level of viral protein gradually increased as infection went on, suggesting that JEV translation could evade the shutoff of cap-dependent translation initiation at the late stage of infection. As shown in the growth curves in Figure 5Q, JEV replicated to similar virus titers in WT and DDX3-KO cells from 12 hpi to 36 hpi, but higher level virus yields were observed in WT cells from 48 hpi, suggesting that DDX3 is important for JEV infection at the late stage. DDX3 was demonstrated to be critical for JEV cap-independent translation. Based on these data, we proposed that the DDX3-dependent cap-independent translation is employed by JEV to maintain efficient infection at the late stage when the cap-dependent translation imitation was suppressed.

      Reviewer #3 (Public review):

      Summary:

      This work is a valuable study that aims to decipher the molecular mechanisms underlying the translation process in Japanese encephalitis virus (JEV), a relevant member of the genus Flavivirus. The authors provide evidence that cap-independent translation, which has already been demonstrated for other flaviviruses, could also account in JEV. This process depends on the genomic 3' UTR, as previously demonstrated in other flaviviruses. Further, the authors find that cellular proteins such as DDX3 or PABP1 could contribute to JEV translation in a cap-independent way. Both DDX3 and PABP1 had previously been described to have a role in cellular protein synthesis and also in the translation step of other flaviviruses distinct from JEV; therefore, this work would expand the cap-independent translation in flaviviruses as a general mechanism to bypass the translation repression exerted by the host cell during viral infection. Further, the findings can be relevant for the development of specific drugs that could interfere with flaviviral translation in the future. Nevertheless, the conclusions are not fully supported by the provided results.

      Strengths:

      The results provide a good starting point to investigate the molecular mechanism underlying the translation in flaviviruses, which even today is an area of knowledge with many limitations.

      Thank you to the reviewer for providing positive feedback. The research on the molecular mechanism underlying cap-independent translation is still a limited field in the flaviviruses, and its mechanism has not been well elucidated at present. We only hope that this study could reveal a novel mechanism of translation initiation for flaviviruses.

      Weaknesses:

      The main limit of the work is related to the fact that the role of the 3' UTR structural elements and DDX3 is not only circumscribed to translation, but also to replication and encapsidation. In fact, some of the provided results suggest this idea. Particularly, it is intriguing why the virus titer can be completely abrogated while the viral protein levels are only partially affected by the knockdown of DDX3. This points to the fact that many of the drawn conclusions could be overestimated or, at least, all the observed effect cannot be attributed only to the DDX3 effect on translation. Finally, it is noteworthy that the use of uncapped transcripts could be misleading, since this is not the natural molecular context of the viral genome.

      Thank you for your suggestion. We agree with the reviewer's comments that the role of the 3' UTR structural elements and DDX3 may not only be circumscribed to translation. However, not as described by the reviewer, DDX3 knockdown did not completely abrogate JEV infection. As indicated in Figure 5E-5F, the recombinant virus was successfully rescued at 36 hpt and 48 hpt using the uncapped viral genomic RNA, although the viral titer rescued with the uncapped genomic RNA at 24 hpt was below the limit of detection. We have confirmed that the DB2 and sHP-SL elements in 3' UTR play a decisive role in the replication of viral RNA in our research (Figure 2G and Figure 2-figure supplement 4C), and we will further analyze the role of DDX3 in viral RNA replication and encapsidation, thereby clarifying the multiple functions of DDX3 in JEV life cycle. Meanwhile, we will incorporate a discussion of these points into the main text, acknowledging the limitations of our current research.

      To eliminate the misleading effects of using uncapped transcripts, we will use a natural molecular background of the viral genome with cap methylation deficiency. The methyltransferase (MTase) of the flavivirus NS5 protein catalyzes  N-7 and 2’-O methylations in the formation of the 5’-end cap of the genome, and the E218 amino acid of the NS5 protein MTase domain is one of the active sites of flavivirus methyltransferase (PLoS Pathogens. 2012. PMID:22496660; Journal of Virology. 2007. PMID: 1866096). We will construct a mutant virus of the E218A mutation to abolish 2'-O methylation activity and significantly reduce N-7 methylation activity and then analyze the roles of UTR structure and DDX3 in recombinant viruses with the type-I cap structure functional deficiency.

    1. Reviewer #1 (Public review):

      Summary:

      The authors revealed the cellular heterogeneity of companion cells (CCs) and demonstrated that the florigen gene FT is highly expressed in a specific subpopulation of these CCs in Arabidopsis. Through a thorough characterization of this subpopulation, they further identified NITRATE-INDUCIBLE GARP-TYPE TRANSCRIPTIONAL REPRESSOR 1 (NIGT1)-like transcription factors as potential new regulators of FT. Overall, these findings are intriguing and valuable, contributing significantly to our understanding of florigen and the photoperiodic flowering pathway. However, there is still room for improvement in the quality of the data and the depth of the analysis. I have several comments that may be beneficial for the authors.

      Strengths:

      The usage of snRNA-seq to characterize the FT-expressing companion cells (CCs) is very interesting and important. Two findings are novel: 1) Expression of FT in CCs is not uniform. Only a subcluster of CCs exhibits high expression level of FT. 2) Based on consensus binding motifs enriched in this subcluster, they further identify NITRATE-INDUCIBLE GARP-TYPE TRANSCRIPTIONAL REPRESSOR 1 (NIGT1)-like transcription factors as potential new regulators of FT.

      Weaknesses:

      (1) Title: "A florigen-expressing subpopulation of companion cells". It is a bit misleading. The conclusion here is that only a subset of companion cells exhibit high expression of FT, but this does not imply that other companion cells do not express it at all.<br /> (2) Data quality: Authors opted for fluorescence-activated nuclei sorting (FANS) instead of traditional cell sorting method. What is the rationale behind this decision? Readers may wonder, especially given that RNA abundance in single nuclei is generally lower than that in single cells. This concern also applies to snRNA-seq data. Specifically, the number of genes captured was quite low, with a median of only 149 genes per nucleus. Additionally, the total number of nuclei analyzed was limited (1,173 for the pFT:NTF and 3,650 for the pSUC2:NTF). These factors suggest that the quality of the snRNA-seq data presented in this study is quite low. In this context, it becomes challenging for the reviewer to accurately assess whether this will impact the subsequent conclusions of the paper. Would it be possible to repeat this experiment and get more nuclei?<br /> (3) Another disappointment is that the authors did not utilize reporter genes to identify the specific locations of the FT-high expressing cells (cluster 7 cells) within the CC population in vivo. Are there any discernible patterns that can be observed?<br /> (4) The final disappointment is that the authors only compared FT expression between the nigtQ mutants and the wild type. Does this imply that the mutant does not have a flowering time defect particularly under high nitrogen conditions?

    2. Author response:

      Reviewer #1 (Public review):

      Summary:

      The authors revealed the cellular heterogeneity of companion cells (CCs) and demonstrated that the florigen gene FT is highly expressed in a specific subpopulation of these CCs in Arabidopsis. Through a thorough characterization of this subpopulation, they further identified NITRATE-INDUCIBLE GARP-TYPE TRANSCRIPTIONAL REPRESSOR 1 (NIGT1)-like transcription factors as potential new regulators of FT. Overall, these findings are intriguing and valuable, contributing significantly to our understanding of florigen and the photoperiodic flowering pathway. However, there is still room for improvement in the quality of the data and the depth of the analysis. I have several comments that may be beneficial for the authors.

      Strengths:

      The usage of snRNA-seq to characterize the FT-expressing companion cells (CCs) is very interesting and important. Two findings are novel: 1) Expression of FT in CCs is not uniform. Only a subcluster of CCs exhibits high expression level of FT. 2) Based on consensus binding motifs enriched in this subcluster, they further identify NITRATE-INDUCIBLE GARP-TYPE TRANSCRIPTIONAL REPRESSOR 1 (NIGT1)-like transcription factors as potential new regulators of FT.

      We are pleased to hear that reviewer 1 noted the novelty and importance of our work. As reviewer 1 mentioned, we are also excited about the identification of a subcluster of companion cells with very high FT expression. We believe that this work is an initial step to describe the molecular characteristics of these FT-expressing cells. We are also excited to share our new findings on NIGT1_s as potential _FT regulators. We think that this finding attracts broader audiences, as the molecular factor that coordinates plant nutrition status with flowering time remains largely unknown despite its well-known plant phenomenon.

      Weaknesses:

      (1) Title: "A florigen-expressing subpopulation of companion cells". It is a bit misleading. The conclusion here is that only a subset of companion cells exhibit high expression of FT, but this does not imply that other companion cells do not express it at all.

      We agree with this comment, as we also did not intend to say that FT is not produced in other companion cells than the subpopulation we identified. We will revise the title to more accurately reflect the point.

      (2) Data quality: Authors opted for fluorescence-activated nuclei sorting (FANS) instead of traditional cell sorting method. What is the rationale behind this decision? Readers may wonder, especially given that RNA abundance in single nuclei is generally lower than that in single cells. This concern also applies to snRNA-seq data. Specifically, the number of genes captured was quite low, with a median of only 149 genes per nucleus. Additionally, the total number of nuclei analyzed was limited (1,173 for the pFT:NTF and 3,650 for the pSUC2:NTF). These factors suggest that the quality of the snRNA-seq data presented in this study is quite low. In this context, it becomes challenging for the reviewer to accurately assess whether this will impact the subsequent conclusions of the paper. Would it be possible to repeat this experiment and get more nuclei?

      We appreciate this comment; we noticed that we did not clearly explain the rationale of using single-nucleus RNA sequencing (snRNA-seq) instead of single-cell RNA-seq (scRNA-seq). As reviewer 1 mentioned, RNA abundance in scRNA-seq is higher than in snRNA-seq. To conduct scRNA-seq using plant cells, protoplasting is the necessary step. However, in our study, protoplasting has many drawbacks in isolating our target cells from the phloem. It is technically challenging to efficiently isolate protoplasts from highly embedded phloem companion cells from plant tissues. Usually, it requires a minimum of several hours of enzymatic incubation to protoplast companion cells and the efficiencies of protoplasting these cells are still low. For our analysis, restoring the time information within a day is also crucial. Therefore, we performed more speedy isolation method. In the revision, we will explain our rationale of choosing snRNA-seq due to the technical limitations.

      Here, reviewer 1 raised a concern about the quality of our snRNA-seq data, referring to the relatively low readcounts per nucleus. Although we believe that shallow reads do not necessaryily indicate low quality and are confident in the accuracy of our snRNA-seq data, as supported by the detailed follow-up experiments (e.g., imaging analysis in Fig. 4B), we agree that it is important to address this point in the revision and alleviate readers’ concerns regarding the data quality.

      (3) Another disappointment is that the authors did not utilize reporter genes to identify the specific locations of the FT-high expressing cells (cluster 7 cells) within the CC population in vivo. Are there any discernible patterns that can be observed?

      As we previously showed only limited spatial images of overlap between FT-expressing cells and other cluster 7 gene-expressing cells in Fig. 4B, this comment is understandable. To respond to it, we will include whole leaf images of FT- and cluster 7 gene-expressing cells to assess the spatial overlaps between FT and cluster 7 genes within a leaf.

      (4) The final disappointment is that the authors only compared FT expression between the nigtQ mutants and the wild type. Does this imply that the mutant does not have a flowering time defect particularly under high nitrogen conditions?

      To answer this question, we will include the flowering time measurement data of the nigtQ mutants grown on the soil with sufficient nitrogen sources.

      Reviewer #2 (Public review):

      This manuscript submitted by Takagi et al. details the molecular characterization of the FT-expressing cell at a single-cell level. The authors examined what genes are expressed specifically in FT-expressing cells and other phloem companion cells by exploiting bulk nuclei and single-nuclei RNA-seq and transgenic analysis. The authors found the unique expression profile of FT-expressing cells at a single-cell level and identified new transcriptional repressors of FT such as NIGT1.2 and NIGT1.4.

      Although previous researchers have known that FT is expressed in phloem companion cells, they have tended to neglect the molecular characterization of the FT-expressing phloem companion cells. To understand how FT, which is expressed in tiny amounts in phloem companion cells that make up a very small portion of the leaf, can be a key molecule in the regulation of the critical developmental step of floral transition, it is important to understand the molecular features of FT-expressing cells in detail. In this regard, this manuscript provides insight into the understanding of detailed molecular characteristics of the FT-expressing cell. This endeavor will contribute to the research field of flowering time.

      We are grateful that reviewer 2 recognizes the importance of transcriptome profiling of FT-expressing cells at the single-cell level.

      Here are my comments on how to improve this manuscript.

      (1) The most noble finding of this manuscript is the identification of NTGI1.2 as the upstream regulator of FT-expressing cluster 7 gene expression. The flowering phenotypes of the nigtQ mutant and the transgenic plants in which NIGT1.2 was expressed under the SUC2 gene promoter support that NIGT1.2 functions as a floral repressor upstream of the FT gene. Nevertheless, the expression patterns of NIGT1.2 genes do not appear to have much overlap with those of NIGT1.2-downstream genes in the cluster 7 (Figs S14 and F3). An explanation for this should be provided in the discussion section.

      We agree reviewer 2 that spatial expression patterns of NIGT1.2 and cluster 7 genes do not overlap much, and some discussion should be provided in the manuscript. Although we do not have a concrete answer for this phenomenon, NIGT1.2 may suppress FT gene expression in non-cluster 7 cells to prevent the misexpression of FT. Another possible explanation is that NIGT1.2 negatively affects the formation of cluster 7 cells. If so, cells with high NIGT1.2 gene expression hardly become cluster 7 cells. We will discuss it further in the discussion section in our revised manuscript.

      (2) To investigate gene expression in the nuclei of specific cell populations, the authors generated transgenic plants expressing a fusion gene encoding a Nuclear Targeting Fusion protein (NTF) under the control of various cell type-specific promoters. Since the public audience would not know about NTF without reading reference 16, some explanation of NTF is necessary in the manuscript. Please provide a schematic of constructs the authors used to make the transformants.

      As reviewer 2 pointed out, we lacked a clear explanation why we used NTF in this study. NTF is the fusion protein that consists of a nuclear envelope targeting domain, GFP, and biotin acceptor peptide. It was originally designed for the INTACT (isolation of nuclei tagged in specific cell types) method that enables us to isolate bulk nuclei from specific tissues. Although our original intention was profiling the bulk transcriptome of mRNAs that exist in nuclei of the FT-expressing cells using INTACT, we utilized our NTF transgenic lines for snRNA-seq analysis. To explain what NTF is to readers, we will include a schematic diagram of NTF.

    1. gemini 赏析

      欣赏布龙齐诺(Bronzino)的《维纳斯、丘比特、愚蠢与时间》(Venus, Cupid, Folly and Time)需要理解其复杂的寓意和风格。这幅画作是样式主义的杰作,以其优雅、复杂和略带情色的氛围而闻名。以下是一些欣赏这幅画作的关键点:

      1. 理解背景和委托:

      • 这幅画是16世纪中期(约1540-1545年)由意大利画家布龙齐诺为佛罗伦萨公爵科西莫一世·德·美第奇创作的,作为礼物送给法国国王弗朗索瓦一世。这说明这幅画作本身就带有政治和外交意味。
      • 样式主义是文艺复兴晚期的一种艺术风格,强调优雅、矫揉造作、复杂构图和夸张的人体比例。它反对文艺复兴盛期追求的自然和和谐。

      2. 解读主要人物和象征:

      这幅画充满了寓意象征,每个角色都代表着某种抽象概念:

      • 维纳斯(Venus):爱神,画面中心人物。她的姿势和表情既优雅又冷漠,暗示了爱情的复杂性和欺骗性。她手中握着金苹果,这是她在“帕里斯的评判”中获胜的象征。
      • 丘比特(Cupid):维纳斯的儿子,爱神。他与维纳斯亲吻,这个行为本身就具有乱伦的意味,暗示了情欲的禁忌和混乱。
      • 愚蠢(Folly/Pleasure):画面左侧,半人半蛇的形象。他/她(性别模糊)手持蜂巢,另一只手藏着一个果子,象征着短暂的快乐和诱惑。蜂巢也可能象征着情欲的甜蜜和痛苦(被蜜蜂蛰)。
      • 时间(Time/Father Time):画面上方,长着翅膀的老人。他试图拉开蓝色帷幕,揭示(或隐藏)正在发生的场景,象征着时间对一切的揭示和流逝。他的形象也可能象征着时间的审判。
      • 面具:画面右下角散落着一些面具,象征着欺骗、虚伪和伪装。
      • 其他人物:在丘比特身后,一个痛苦地撕扯头发的人物,通常被认为是“嫉妒”(Jealousy)或“痛苦”(Pain),暗示了爱情中常常伴随的负面情绪。

      3. 注意构图和风格:

      • 拥挤的构图:画面人物众多,彼此交织,创造了一种紧张和不安定的氛围。
      • 流畅的线条和优雅的姿势:人物的姿势都非常优雅和矫揉造作,体现了样式主义的特点。
      • 光滑的表面和鲜艳的色彩:画作的表面非常光滑,色彩鲜艳而富有光泽。
      • 冷漠的表情:人物的表情大多冷漠或复杂,缺乏真实的情感流露。

      4. 综合理解:

      这幅画作的含义非常复杂,没有唯一的解释。它探讨了爱情的复杂性、欺骗性、短暂性和痛苦,以及时间对一切的影响。它也可能暗示了情欲的危险和禁忌。

      欣赏的关键:

      • 细致观察:仔细观察每个细节,包括人物的姿势、表情、手中的物品等。
      • 理解象征:尝试理解每个角色和物品的象征意义。
      • 关注风格:欣赏样式主义的优雅、复杂和矫揉造作。
      • 多重解读:接受画作的多重解读,不要试图寻找唯一的正确答案。

      通过以上分析,你可以更深入地欣赏布龙齐诺的《维纳斯、丘比特、愚蠢与时间》,并理解其丰富的内涵。这幅画不仅仅是一幅美丽的画作,更是一部充满智慧和思考的艺术作品。

    1. Reviewer #3 (Public review):

      The manuscript by Lu et al. explores the role of the Arp2/3 complex and the actin nucleators N-WASP and WAVE in myoblast fusion during muscle regeneration. The results are clear and compelling, effectively supporting the main claims of the study. However, the manuscript could benefit from a more detailed molecular and cellular analysis of the fusion synapse. Additionally, while the description of macrophage extravasation from ghost fibers is intriguing, it seems somewhat disconnected from the primary focus of the work.

      Despite this, the data are robust, and the major conclusions are well supported. Understanding muscle fusion mechanism is still a widely unexplored topic in the field and the authors make important progress in this domain.

      I have a few suggestions that might strengthen the manuscript as outlined below.

      (1) Could the authors provide more detail on how they defined cells with "invasive protrusions" in Figure 4C? Membrane blebs are commonly observed in contacting cells, so it would be important to clarify the criteria used for counting this specific event.

      (2) Along the same line, please clarify what each individual dot represents in Figure 4C. The authors mention quantifying approximately 83 SCMs from 20 fibers. I assume each dot corresponds to data from individual fibers, but if that's the case, does this imply that only around four SCMs were quantified per fiber? A more detailed explanation would be helpful.

      (3) Localizing ArpC2 at the invasive protrusions would be a strong addition to this study. Furthermore, have the authors examined the localization of Myomaker and Myomixer in ArpC2 mutant cells? This could provide insights into potential disruptions in the fusion machinery.

      (4) As a minor curiosity, can ArpC2 WT and mutant cells fuse with each other?

      (5) The authors report a strong reduction in CSA at 14 dpi and 28 dpi, attributing this defect primarily to failed myoblast fusion. Although this claim is supported by observations at early time points, I wonder whether the Arp2/3 complex might also play roles in myofibers after fusion. For instance, Arp2/3 could be required for the growth or maintenance of healthy myofibers, which could also contribute to the reduced CSA observed, since regenerated myofibers inherit the ArpC2 knockout from the stem cells. Could the authors address or exclude this possibility? This is rather a broader criticism of how things are being interpreted in general beyond this paper.

    1. Latihan Graph
      • karena simpul ada 5, maka punya leader list yang elemennya ada 5. trailer list itu kotak dua kbawah yang ada 4 dan 1 di paling bawah.

      • trailer list akan menyatakan seluruh busur yang menghubungkan antara node tersebut ke node yang lain

      • contohnya node 1, nunjuk ke 2 dan 3. maka akan punya 2 trailer list yang menunjuk ke 2 dan 3

    Annotators

    1. Reviewer #1 (Public review):

      Summary:

      In this manuscript, Pakula et al. explore the impact of reactive oxygen species (ROS) on neonatal cerebellar regeneration, providing evidence that ROS activates regeneration through Nestin-expressing progenitors (NEPs). Using scRNA-seq analysis of FACS-isolated NEPs, the authors characterize injury-induced changes, including an enrichment in ROS metabolic processes within the cerebellar microenvironment. Biochemical analyses confirm a rapid increase in ROS levels following irradiation, and forced catalase expression, which reduces ROS levels, and impairs external granule layer (EGL) replenishment post-injury.

      Strengths:

      Overall, the study robustly supports its main conclusion and provides valuable insights into ROS as a regenerative signal in the neonatal cerebellum.

      Weaknesses:

      Below are specific comments and concerns:

      (1) The diversity of cell types recovered from scRNA-seq libraries of sorted Nes-CFP cells is unexpected, especially the inclusion of minor types such as microglia, meninges, and ependymal cells. The authors should validate whether Nes and CFP mRNAs are enriched in the sorted cells; if not, they should discuss the potential pitfalls in sampling bias or artifacts that may have affected the dataset, impacting interpretation.<br /> (2) The authors should de-emphasize that ROS signaling and related gene upregulation exclusively in gliogenic NEPs. Genes such as Cdkn1a, Phlda3, Ass1, and Bax are identified as differentially expressed in neurogenic NEPs and granule cell progenitors (GCPs), with Ass1 absent in GCPs. According to Table S4, gene ontology (GO) terms related to ROS metabolic processes are also enriched in gliogenic NEPs, neurogenic NEPs, and GCPs.<br /> (3) The authors need to justify the selection of only the anterior lobe for EGL replenishment and microglia quantification.<br /> (4) Figure 1K: The figure presents linkages between genes and GO terms as a network but does not depict a gene network. The terminology should be corrected accordingly.<br /> (5) Figure 1H and S2: The x-axis appears to display raw p-values rather than log10(p.value) as indicated. The x-axis should ideally show -log10(p.adjust), beginning at zero. The current format may misleadingly suggest that the ROS GO term has the lowest p-values.<br /> (6) Genes such as Ppara, Egln3, Foxo3, Jun, and Nos1ap were identified by bulk ATAC-seq based on proximity to peaks, not by scRNA-seq. Without additional expression data, caution is needed when presenting these genes as direct evidence of ROS involvement in NEPs.<br /> (7) The authors should annotate cell identities for the different clusters in Table S2.<br /> (8) Reiterative clustering analysis reveals distinct subpopulations among gliogenic and neurogenic NEPs. Could the authors clarify the identities of these subclusters? Can we distinguish the gliogenic NEPs in the Bergmann glia layer from those in the white matter?<br /> (9) In the Methods section, the authors mention filtering out genes with fewer than 10 counts. They should specify if these genes were used as background for enrichment analysis. Background gene selection is critical, as it influences the functional enrichment of gene sets in the list.<br /> (10) Figure S1C: The authors could consider using bar plots to better illustrate cell composition differences across conditions and replicates.<br /> (11) Figures 4-6: It remains unclear how the white matter microglia contribute to the recruitment of BgL-NEPs to the EGL, as the mCAT-mediated microglia loss data are all confined to the white matter.

    1. isUnerLeft(p) : → 1 + nbElmt(p↑.left)isUnerRight(p): → 1 + nbElmt(p↑.right)isBiner(p) : → 1 + nbElmt(p↑.left) + nbElmt(p↑.right)

      Fungsi dibuat seperti ini untuk mencegah NbElmt dengan basis 0.Oke, mari kita sederhanakan penjelasannya.

      Kenapa Basis 1 Butuh unerleft, unerright, dan isbiner?

      • Basis 1 adalah aturan di mana rekursi hanya berhenti kalau pohon punya satu simpul (akar saja).
      • Untuk memastikan rekursi tetap berjalan sesuai aturan basis 1, kita perlu tahu bentuk struktur pohon yang sedang diproses:
      • Pohon punya anak kiri saja (unerleft).
      • Pohon punya anak kanan saja (unerright).
      • Pohon punya dua anak (isbiner).

      Dengan kata lain, kita pecah bentuk pohon menjadi 3 kategori supaya fungsi bisa tahu ke mana rekursi harus berjalan (kiri saja, kanan saja, atau kiri dan kanan).


      Kenapa Bukan Basis 0?

      • Basis 0 berhenti kalau pohon kosong (NIL).
      • Tapi di basis 1, kita tidak menganggap pohon kosong sebagai bagian dari logika. Kita hanya peduli pada pohon yang punya minimal satu simpul.
      • Jadi, logika basis 1 menghindari pohon kosong dan memaksa fungsi hanya berhenti kalau pohon punya satu simpul saja.

      Contoh Sederhana

      Misalkan ada pohon seperti ini:

      A / \ B C / D

      Dengan Basis 1:

      1. Kalau pohon punya satu simpul (seperti D), langsung hitung dan berhenti.
      2. Kalau pohon punya anak kiri saja, lanjut ke kiri (contoh: B).
      3. Kalau pohon punya anak kanan saja, lanjut ke kanan.
      4. Kalau pohon punya dua anak (contoh: A), proses keduanya.

      Kode Sederhana

      c function NbElmt(p: BinTree) -> integer IF isOneElmt(p) THEN RETURN 1 ELSE IF unerleft(p) THEN RETURN 1 + NbElmt(LEFT(p)) ELSE IF unerright(p) THEN RETURN 1 + NbElmt(RIGHT(p)) ELSE IF isbiner(p) THEN RETURN 1 + NbElmt(LEFT(p)) + NbElmt(RIGHT(p))

      • isOneElmt(p): Kalau pohon cuma satu simpul, berhenti di situ.
      • unerleft(p): Kalau pohon cuma punya anak kiri, hitung akar + rekursi ke kiri.
      • unerright(p): Kalau pohon cuma punya anak kanan, hitung akar + rekursi ke kanan.
      • isbiner(p): Kalau pohon punya dua anak, hitung akar + rekursi kiri + rekursi kanan.

      Simpulan

      • Basis 1 fokus ke pohon dengan minimal satu simpul, bukan pohon kosong.
      • unerleft, unerright, dan isbiner membantu memecah struktur pohon supaya rekursi berjalan dengan aturan basis 1, tanpa kembali ke logika basis 0 (pohon kosong).

    Annotators

    1. 拜占庭艺术具有强烈的抽象性,远离了写实主义的表现。人物面容往往呈现出一种理想化、非自然的状态,不追求真实的生动表情,而是通过严谨的符号和象征来表达神圣性和神秘性。

      你提出的观点非常准确地概括了拜占庭艺术的重要特征之一:强烈的抽象性和对写实主义的偏离。拜占庭艺术并非不具备描绘现实的能力,而是出于其特定的宗教和文化目的,有意地选择了抽象和象征的表现方式。以下我将详细解释拜占庭艺术如何通过抽象手法来表达神圣性和神秘性:

      1. 理想化的人物形象:

      • 程式化的面容: 拜占庭艺术中的人物面容往往呈现出程式化的特征,例如:
        • 大而空洞的眼睛: 目光凝视远方,象征着与神灵的交流和超越世俗的境界。
        • 细长的鼻子和嘴唇: 强调人物的灵性和高贵。
        • 平直的面部轮廓: 减少面部的立体感,使人物显得更加庄严和肃穆。
      • 缺乏个性化的特征: 拜占庭艺术并不追求描绘人物的个性和情感,而是着重表现人物作为神圣形象的普遍性和永恒性。因此,人物之间的面容往往相似,缺乏明显的个体特征。
      • 修长的身形和僵硬的姿态: 人物通常身形修长,比例拉长,姿态僵硬,缺乏自然的动态和身体的重量感。这种表现方式旨在突出人物的超凡脱俗和精神性。

      2. 象征性的符号和色彩:

      • 金色背景: 金色是拜占庭艺术中最常用的色彩之一,象征着天堂的光辉、神圣和永恒。金色的背景使画面中的人物和场景脱离了现实世界,进入了一个超验的领域。
      • 特定的手势和姿态: 人物的手势和姿态通常具有特定的象征意义,例如:
        • 祝福的手势: 食指和中指伸直,其余手指弯曲,象征着基督的祝福。
        • 祈祷的姿势: 双手合十或向上举起,表达对上帝的敬畏和祈求。
      • 固定的图像程式: 拜占庭艺术中存在着许多固定的图像程式,例如:
        • 基督像: 通常以长发、胡须的形象出现,象征着他的智慧和权威。
        • 圣母像: 通常怀抱圣婴,象征着母性和神圣的爱。

      3. 远离自然主义的表现:

      • 缺乏透视和空间感: 拜占庭艺术并不注重描绘逼真的空间和透视关系,画面通常显得扁平,缺乏纵深感。这种处理方式旨在突出画面的象征性和精神性,而非对现实的模仿。
      • 非自然的比例和解剖: 人物的比例和解剖结构常常不符合自然规律,例如头部过大、身体细长等。这种变形的处理方式旨在强调人物的精神特质,而非外在的形体。

      4. 宗教目的的驱动:

      拜占庭艺术的抽象性和象征性并非出于艺术家技巧的不足,而是受到其深刻的宗教目的的驱动。拜占庭艺术家认为,艺术的目的是为了表达神圣的真理,而非描绘世俗的现实。通过抽象和象征的手法,他们试图超越物质世界的局限,引导观者进入一个精神和信仰的领域。

      总结:

      拜占庭艺术通过理想化的人物形象、象征性的符号和色彩、以及远离自然主义的表现手法,创造了一种独特的抽象风格。这种风格并非对现实的简单模仿,而是对神圣性和神秘性的深刻表达。它旨在引导观者超越物质世界,体验精神和信仰的崇高境界。

      要更深入地理解拜占庭艺术的抽象性,可以结合具体的作品进行分析,例如:

      • 圣索菲亚大教堂的镶嵌画: 这些镶嵌画以其金色的背景、程式化的人物形象和丰富的象征意义而闻名。
      • 圣像画: 圣像画是拜占庭艺术的重要组成部分,其人物形象通常具有高度的抽象性和象征性。

      通过对这些作品的观察和研究,你将能够更深刻地理解拜占庭艺术的独特魅力和精神内涵。

    1. Memori
      • F: memori kosong/blok kosong
      • T : terisi
      • NB Blok: banyak blok yg dikelola

      jadi kalo ada request 2 blok bakal cari emang exact 2 blok (kalo 4 blok diambil 2 doang gaakan mau karena bakal ga efisien dan ngerusak selanjutnya) jadi dicari yang eksak sama. (ini bestfit)

      yg langsung ketemu di awal (firstfit)

      best bakal iterasi sampe ujung kalo first yaudah sampe yang ada fit doang

    Annotators

    1. Reviewer #2 (Public review):

      Summary:

      Conceptually, this study is interesting and is the first attempt to account for the potentially interactive effects of seasonality and blood source on mosquito fitness, which the authors frame as a possible explanation for previously observed host-switching of Culex quinquefasciatus from birds to mammals in the fall. The authors hypothesize that if changes in fitness by blood source change between seasons, higher fitness on birds in the summer and on mammals in the autumn could drive observed host switching. To test this, the authors fed individuals from a colony of Cx. quinquefasciatus on chickens (bird model) and mice (mammal model) and subjected each of these two groups to two different environmental conditions reflecting the high and low temperatures and photoperiod experienced in summer and autumn in Córdoba, Argentina (aka seasonality). They measured fecundity, fertility, and hatchability over two gonotrophic cycles. The authors then used generalized linear mixed models to evaluate the impact of host species, seasonality, and gonotrophic cycle on fecundity, fertility, and hatchability. The authors were trying to test their hypothesis by determining whether there was an interactive effect of season and host species on mosquito fitness. This is an interesting hypothesis; if it had been supported, it would provide support for a new mechanism driving host switching. While the authors did report an interactive impact of seasonality and host species, the directionality of the effect was the opposite from that hypothesized. The authors have done a very good job of addressing many of the reviewer's concerns, especially by adding two additional replicates. Several minor concerns remain, especially regarding unclear statements in the discussion.

      Strengths:

      (1) Using a combination of laboratory feedings and incubators to simulate seasonal environmental conditions is a good, controlled way to assess the potentially interactive impact of host species and seasonality on the fitness of Culex quinquefasciatus in the lab.<br /> (2) The driving hypothesis is an interesting and creative way to think about a potential driver of host switching observed in the field.

      Weaknesses:

      (1) The methods would be improved by some additional details. For example, clarifying the number of generations for which mosquitoes were maintained in colony (which was changed from 20 to several) and whether replicates were conducted at different time points.<br /> (2) The statistical analysis requires some additional explanation. For example, you suggest that the power analysis was conducted a priori, but this was not mentioned in your first two drafts, so I wonder if it was actually conducted after the first replicate. It would be helpful to include further detail, such as how the parameters were estimated. Also, it would be helpful to clarify why replicate was included as a random effect for fecundity and fertility but as a fixed effect for hatchability. This might explain why there were no significant differences for hatchability given that you were estimating for more parameters.<br /> (3) A number of statements in the discussion are not clear. For example, what do you mean by a mixed perspective in the first paragraph? Also, why is the expectation mentioned in the second paragraph different from the hypothesis you described in your introduction?<br /> (4) According to eLife policy, data must be made freely available (not just upon request).

    2. Author response:

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

      We have carefully addressed all the reviewers' suggestions, and detailed responses are provided at the end of this letter. In summary:

      • We conducted two additional replicates of the study to obtain more robust and reliable data.

      • The Introduction has been revised for greater clarity and conciseness.

      • The Results section was shortened and reorganized to highlight the key findings more effectively.

      • The Discussion was modified according to the reviewers' suggestions, with a focus on reorganization and conciseness.

      We hope you find this revised version of the manuscript satisfactory.

      Reviewer #1 (Public Review):

      Summary:

      This study examines the role of host blood meal source, temperature, and photoperiod on the reproductive traits of Cx. quinquefasciatus, an important vector of numerous pathogens of medical importance. The host use pattern of Cx. quinquefasciatus is interesting in that it feeds on birds during spring and shifts to feeding on mammals towards fall. Various hypotheses have been proposed to explain the seasonal shift in host use in this species but have provided limited evidence. This study examines whether the shifting of host classes from birds to mammals towards autumn offers any reproductive advantages to Cx. quinquefasciatus in terms of enhanced fecundity, fertility, and hatchability of the offspring. The authors found no evidence of this, suggesting that alternate mechanisms may drive the seasonal shift in host use in Cx. quinquefasciatus.

      Strengths:

      Host blood meal source, temperature, and photoperiod were all examined together.

      Weaknesses:

      The study was conducted in laboratory conditions with a local population of Cx. quinquefasciatus from Argentina. I'm not sure if there is any evidence for a seasonal shift in the host use pattern in Cx. quinquefasciatus populations from the southern latitudes.

      Comments on the revision: 

      Overall, I am not quite convinced about the possible shift in host use in the Argentinian populations of Cx. quinquefasciatus. The evidence from the papers that the authors cite is not strong enough to derive this conclusion. Therefore, I think that the introduction and discussion parts where they talk about host shift in Cx. quinquefasciatus should be removed completely as it misleads the readers. I suggest limiting the manuscript to talking only about the effects of blood meal source and seasonality on the reproductive outcomes of Cx. quinquefasciatus

      As mentioned in the previous revision, we agree on the reviewer observation about the lack of evidence on seasonal shift in the host use pattern in Cx. quinquefasciatus populations from Argentina. We include this topic in the discussion.

      Additionally, we also added a paragraph in the discussion section to include the limitations of our study and conclusions. One of them is the fact that our results are based on controlled conditions experiments. Future studies are needed to elucidate if the same trend is found in the field.

      Reviewer #1 (Recommendations for the authors): 

      Abstract

      Line 73: shift in feeding behavior

      Accepted as suggested. 

      Discussion

      Line 258: addressed that Accepted as suggested.

      Line 263: blood is nutritionally richer

      Accepted as suggested.

      Reviewer #2 (Public Review): 

      Summary:

      Conceptually, this study is interesting and is the first attempt to account for the potentially interactive effects of seasonality and blood source on mosquito fitness, which the authors frame as a possible explanation for previously observed host-switching of Culex quinquefasciatus from birds to mammals in the fall. The authors hypothesize that if changes in fitness by blood source change between seasons, higher fitness on birds in the summer and on mammals in the autumn could drive observed host switching. To test this, the authors fed individuals from a colony of Cx. quinquefasciatus on chickens (bird model) and mice (mammal model) and subjected each of these two groups to two different environmental conditions reflecting the high and low temperatures and photoperiod experienced in summer and autumn in Córdoba, Argentina (aka seasonality). They measured fecundity, fertility, and hatchability over two gonotrophic cycles. The authors then used a generalized linear model to evaluate the impact of host species, seasonality, and gonotrophic cycle on fecundity, fertility, and hatchability. The authors were trying to test their hypothesis by determining whether there was an interactive effect of season and host species on mosquito fitness. This is an interesting hypothesis; if it had been supported, it would provide support for a new mechanism driving host switching. While the authors did report an interactive impact of seasonality and host species, the directionality of the effect was the opposite from that hypothesized. The authors have done a very good job of addressing many of the reviewer concerns, with several exception that continue to cause concern about the conclusions of the study. 

      Strengths:

      (1) Using a combination of laboratory feedings and incubators to simulate seasonal environmental conditions is a good, controlled way to assess the potentially interactive impact of host species and seasonality on the fitness of Culex quinquefasciatus in the lab.

      (2) The driving hypothesis is an interesting and creative way to think about a potential driver of host switching observed in the field. 

      (3) The manuscript has become a lot clearer and easier to read with the revisions - thank you to the authors for working hard to make many of the suggested changes. 

      Weaknesses:

      (1) The authors have decided not to follow the suggestion of conducting experimental replicates of the study. This is understandable given the significant investment of resources and time necessary, however, it leaves the study lacking support. Experimental replication is an important feature of a strong study and helps to provide confidence that the observed patterns are real and replicable. Without replication, I continue to lack confidence in the conclusions of the study. 

      We included replicates as suggested.  

      (2) The authors have included some additional discussion about the counterintuitive nature of their results, but the paragraph discussing this in the discussion was confusing. I believe that this should be revised. This is a key point of the paper and needs to be clear to the reader.

      Revised as suggested. 

      (3) There should be more discussion of the host switching observed in the two studies conducted in Argentina referenced by the authors. Since host switching is the foundation for the hypothesis tested in this paper, it is important to fully explain what is currently known in Argentina. 

      Accepted as suggested.

      (4) In some cases, the explanations of referenced papers are not entirely accurate. For example, when referencing Erram et al 2022, I think the authors misrepresented the paper's discussion regarding pre-diuresis- Erram et al. are suggesting that pre-diuresis might be the mechanism by which C. furens compensates for the lower nutritional value of avian blood, leading to no significant difference between avian/mammal blood on fecundity/fertility (rather than leading to higher fecundity on birds, as stated in this manuscript). The study performed by Erram et al. also didn't prove this phenomenon, they just suggest it as a possible mechanism to explain their results, so that should be made clear when referencing the paper. 

      Changed as suggested.

      (5) In some cases, the conclusions continue to be too strongly worded for the evidence available. For example, lines 322-324: I don't think the data is sufficient to conclude that a different physiological state is induced, nor that they are required to feed on a blood source that results in higher fitness. 

      Redaction was modified as suggested to tight our discussion with results.

      (6) There is limited mention of the caveat that this experiment performed with simulated seasonality that does not perfectly replicate seasonality in the field. I think this caveat should be discussed in the discussion (e.g. that humidity is held constant).

      This topic is now included in the discussion as suggested. 

      Reviewer #2 (Recommendations for the authors): 

      59-60: These terms should end with -phagic instead of -philic. These papers study blood feeding patterns, not preference. I understand that the Janssen papers calls it "mammalophilic" in their title, but this was an incorrect use of the term in their paper. There are some review papers that explain the difference in this terminology if it's helpful.

      Accepted as suggested. 

      73: edit to "in" feeding behavior 

      Accepted as suggested.

      77-78: Given that the premise of your study is based on the phenomenon of host switching, I suggest that you expand your discussion of these two papers. What did they observe? Which hosts did they switch from / to and how dramatic was the shift?

      Accepted as suggested. 

      79: replace acknowledged with experienced 

      Accepted as suggested.

      79-80: the way that this is written is misleading. It suggests that Spinsanti showed that seasonal variation in SLEV could be attributed to a host shift, which isn't true. This citation should come before the comma and then you should use more cautious language in the second half. E.g which MIGHT be possible to attribute to .... 

      Accepted as suggested.

      80-82: this is not convincing. Even if the Robin isn't in Argentina, Argentina does have migrating birds, so couldn't this be the case for other species of birds? Do any of the birds observed in previous blood meal analyses in Argentina migrate? If so, couldn't this hypothesis indeed play a role? 

      A paragraph about this topic was added to the discussion as suggested.

      90: hypotheses for what? The fall peak in cases? Or host switching? 

      Changed to be clearer.

      98: where was this mentioned before? I think "as mentioned before" can be removed. 

      Accepted as suggested.

      101: edit to "whether an interaction effect exists" 

      Accepted as suggested.

      104: edit to "We hypothesize that..." 

      Accepted as suggested.

      106: reported host USE changes, not host PREFERENCE changes, right? 

      All the terminology was change to host pattern and not preference to avoid confusion.

      200: Briefly reading Carsey and Harden, it looks like the methodology was developed for social science. Is there anything you can cite to show this applied to other types of data? If not, I think this requires more explanation in your MS. 

      This was removed as replicates were included.

      237-239: I think it is best not to make a definitive statement about greater/higher if it isn't statistically significant; I suggest modifying the sentences to state that the differences you are listing were not significantly different up front rather than at the end, otherwise if people aren't reading carefully, they may get the wrong impression. 

      Accepted as suggested.

      245: you only use the term MS-I once before and I forgot what it meant since it wasn't repeated, so I had to search back through with command-F. I suggest writing this out rather than using the acronym. 

      Accepted as suggested.

      249: edit to: "an interaction exists between the effect of..." 

      Accepted as suggested.

      253-254: greater compared to what? 

      Change for clearness. 258-260: edit for grammar 

      Accepted as suggested.

      260-262: edit for grammar; e.g. "However, this assumption lacks solid evidence; there is a scarcity of studies regarding nutritional quality of avian blood and its impact on mosquito fitness." 

      Accepted as suggested.

      263: edit: blood is nutritionally... 

      Accepted as suggested.

      264-267: This doesn't sound like an accurate interpretation of what the paper suggests regarding pre-diuresis in their discussion - they are suggesting that pre-diuresis might be the mechanism by which C. furens compensates for the lower nutritional value of avian blood, leading to no significant difference between avian/mammal blood on fecundity/fertility. They also don't show this, they just suggest it as a possible mechanism to explain their results. 

      This topic was removed given the restructuring of discussion.

      253-269: You should tie this paragraph back to your results to explicitly compare/contrast your findings with the previous literature. 

      Accepted as suggested.

      270-282: This paragraph would be a good place to explain the caveat of working in the laboratory - for example, humidity was the same across the two seasons which I'm guessing isn't the case in the field in Argentina. You can discuss what aspects of laboratory season simulation do not accurately replicate field conditions and how this can impact your findings. You said in your response to the reviewers that you weren't interested in measuring other variables (which is fair, and not expected!), but the beauty of the discussion section is to be able to think about how your experimental design might impact your results - one possibility is that your season simulation may not have produced the results produced by true seasonal shifts. 

      Accepted as suggested.

      279-281: You say your experiment was conducted within the optimal range, which would suggest that both summer and autumn were within that range, but then you only talk about summer as optimal in the following sentence. 

      Changed for clearness.

      281-282: You should clarify this sentence - state what the interaction has an effect on. 

      Accepted as suggested.

      283-291: I appreciate that your discussion now acknowledges the small sample size and the questions that remain unanswered due to the results being opposite to that of the hypothesis, but this paragraph lacks some details and in places doesn't make sense. 

      I think you need to emphasize which groups had small sample size and which conclusions that might impact. I also think you need to explain why the sample size was substantially smaller for some groups (e.g. did they refuse to feed on the mouse in the autumn?). I appreciate that sample sizes are hard to keep high across many groups and two gonotrophic periods, but unfortunately, that is why fitness experiments are so hard to do and by their nature, take a long time. I understand that other papers have even lower sample size, but I was not asked to review those papers and would have had the same critique of them. I don't believe that creating simulated data via a Monte Carlo approach can make up for generating real data. As I understand it from your explanation, you are parametrizing the Monte Carlo simulations with your original data, which was small to begin with for autumn mouse. Using this simulation doesn't seem like a satisfactory replacement for an experimental replicate in my opinion. I maintain that at least a second replicate is necessary to see whether the patterns that you have observed hold. 

      The performing of a power analysis and addition of more replicates tried to solve the issue of sample size. More about this critic is added in the discussion. The simulation approach was totally removed.

      Regarding the directionality of the interaction effect, I think this warrants more discussion. Lines 287-291 don't make sense to me. You suggest that feeding on birds in the autumn may confer a reproductive advantage when conditions are more challenging. But then why wouldn't they preferentially feed on birds in the autumn, rather than mammals? I suggest rewriting this paragraph to make it clearer. 

      Accepted as suggested.

      297: earlier mentioned treatments? Do you mean compared to the first gonotrophic cycle? This isn't clear. 

      Changed for clearness.

      302-303: Did you clarify whether you are allowed to reference unpublished data in eLife? 

      This was removed to follow the guidelines of eLife.

      316-317: "it becomes apparent" sounds awkward, I suggest rewording and also explaining how this conclusion was made. 

      Accepted as suggested.

      322-324: I think that this statement is too strongly worded. I don't think your data is sufficient to conclude that a different physiological state is induced, nor that they are required to feed on a blood source that results in higher fitness. Please modify this and make your conclusions more cautious and closely linked to what you actually demonstrated. 

      Accepted as suggested.

      325: change will perform to would have 

      Accepted as suggested.

      326: add to the sentence: "and vice versa in the summer" 

      Accepted as suggested.

      330: possible explanations, not explaining scenarios. 

      Accepted as suggested.

      517: I think you should repeat the abbreviation definitions in the caption to make it easier for readers, otherwise they have to flip back and forth which can be difficult depending on formatting.

      Accepted as suggested. 

      In general, I think that your captions need more information. I think the best captions explain the figure relatively thoroughly such that the reader can look at the figure and caption and understand without reading the paper in depth. (e.g. the statistical test used).

      Data availability: The eLife author instructions do say that data must be made available, so there should be a statement on data availability in your MS. I also suggest you make the code available.

      Accepted as suggested.

    1. Reviewer #2 (Public review):

      The authors developed the TaG-EM system to address challenges in multiplexing Drosophila samples for behavioral and transcriptomic studies. This system integrates DNA barcodes upstream of the polyadenylation site in a UAS-GFP construct, enabling pooled behavioral measurements and cell type tracking in scRNA-seq experiments. The revised manuscript expands on the utility of TaG-EM by demonstrating its application to complex assays, such as larval gut motility, and provides a refined analysis of its limitations and cost-effectiveness.

      Strengths

      (1) Novelty and Scope: The study demonstrates the potential for TaG-EM to streamline multiplexing in both behavioral and transcriptomic contexts. The additional application to labor-intensive larval gut motility assays highlights its scalability and practical utility.

      (2) Data Quality and Clarity: Figures and supplemental data are mostly clear and significantly enhanced in the revised manuscript. The addition of Supplemental Figures 18-21 addresses initial concerns about scRNA-seq data and driver characterization.

      (3) Cost-Effectiveness Analysis: New analyses of labor and cost savings (e.g., Supplemental Figure 8) provide a practical perspective.

      (4) Improvements in Barcode Detection and Analysis: Enhanced enrichment protocols (Supplemental Figures 18-19) demonstrate progress in addressing limitations of barcode detection and increase the detection rate of labeled cells.

      Weaknesses

      (1) Barcode Detection Efficiency: While improvements are noted, the low barcode detection rate (~37% in optimized conditions) limits the method's scalability in some applications, such as single-cell sequencing experiments with complex cell populations.

      (2) Sparse Labeling: Sparse labeling of cell populations, particularly in scRNA-seq assays, remains a concern. Variability in driver strength and regional expression introduces inconsistencies in labeling density.

      (3) Behavioral Applications: The utility of TaG-EM in quantifying more complex behaviors remains underexplored, limiting the generalizability of the method beyond simpler assays like phototaxis and oviposition.

      (4) Driver Line Characterization: While improvements in driver line characterization were made, variability in expression patterns and sparse labeling emphasize the need for further refinement of constructs and systematic backcrossing to standardize the genetic background.

    1. Author response:

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

      Reviewer #1 (Public Review):

      Summary:

      BMP signaling is, arguably, best known for its role in the dorsoventral patterning, but not in nematodes, where it regulates body size. In their paper, Vora et al. analyze ChIP-Seq and RNA-Seq data to identify direct transcriptional targets of SMA-3 (Smad) and SMA-9 (Schnurri) and understand the respective roles of SMA-3 and SMA-9 in the nematode model Caenorhabditis elegans. The authors use publicly available SMA-3 and SMA-9 ChIP-Seq data, own RNA-Seq data from SMA-3 and SMA-9 mutants, and bioinformatic analyses to identify the genes directly controlled by these two transcription factors (TFs) and find approximately 350 such targets for each. They show that all SMA-3-controlled targets are positively controlled by SMA-3 binding, while SMA-9-controlled targets can be either up or downregulated by SMA-9. 129 direct targets were shared by SMA-3 and SMA-9, and, curiously, the expression of 15 of them was activated by SMA-3 but repressed by SMA-9. Since genes responsible for cuticle collagen production were eminent among the SMA-3 targets, the authors focused on trying to understand the body size defect known to be elicited by the modulation of BMP signaling. Vora et al. provide compelling evidence that this defect is likely to be due to problems with the BMP signaling-dependent collagen secretion necessary for cuticle formation.

      We thank the reviewer for this supportive summary. We would like to clarify the status of the publicly available ChIP-seq data. We generated the GFP tagged SMA-3 and SMA‑9 strains and submitted them to be entered into the queue for ChIP-seq processing by the modENCODE (later modERN) consortium. Thus, the publicly available SMA-3 and SMA-9 ChIP-seq datasets used here were derived from our efforts.  Due to the nature of the consortium’s funding, the data were required to be released publicly upon completion. Nevertheless, our current manuscript provides the first comprehensive analysis of these datasets. We have updated the text to clarify this point.

      Strengths:

      Vora et al. provide a valuable analysis of ChIP-Seq and RNA-Seq datasets, which will be very useful for the community. They also shed light on the mechanism of the BMP-dependent body size control by identifying SMA-3 target genes regulating cuticle collagen synthesis and by showing that downregulation of these genes affects body size in C. elegans.

      Weaknesses:

      (1) Although the analysis of the SMA-3 and SMA-9 ChIP-Seq and RNA-Seq data is extremely useful, the goal "to untangle the roles of Smad and Schnurri transcription factors in the developing C. elegans larva", has not been reached. While the role of SMA-3 as a transcriptional activator appears to be quite straightforward, the function of SMA-9 in the BMP signaling remains obscure. The authors write that in SMA-9 mutants, body size is affected, but they do not show any data on the mechanism of this effect.

      We thank the reviewer for directing our attention to the lack of clarity about SMA-9’s function. We have revised the text to highlight what this study and others demonstrate about SMA-9’s role in body size. Simply stated, SMA-9 is needed together with SMA-3 to promote the expression of genes involved in one-carbon metabolism, collagens, and chaperones, all of which are required for body size. SMA-3 has additional, SMA-9-independent transcriptional targets, including chaperones and ER secretion factors, that also contribute to body size. Finally, SMA-9 regulates additional targets independent of SMA-3 that likely have a minimal role in body size. We have adjusted Figure 5 with new graphs of the original data to make these points more clear.

      (2) The authors clearly show that both TFs can bind independently of each other, however, by using distances between SMA-3 and SMA-9 ChIP peaks, they claim that when the peaks are close these two TFs act as complexes. In the absence of proof that SMA-3 and SMA-9 physically interact (e.g. that they co-immunoprecipitate - as they do in Drosophila), this is an unfounded claim, which should either be experimentally substantiated or toned down.

      We acknowledge that we have not demonstrated a physical interaction between SMA-3 and SMA-9 through a co-immunoprecipitation, and we have indicated in the text that a formal biochemical demonstration would be required to make this point. Moreover, we toned down the text by stating that our results suggest that either SMA-3 and SMA-9 frequently bind as either subunits in a complex or in close vicinity to each other along the DNA. As the reviewer has indicated, a physical interaction between Smads and Schnurris has been amply demonstrated in other systems. A limitation in these previous studies is that only a small number of target genes were analyzed. Our goal in this study was to determine how widespread this interaction is on a genomic scale. Our analyses demonstrate for the first time that a Schnurri transcription factor has significant numbers of both Smad-dependent and Smad-independent target genes. We have revised the text to clarify this point.

      (3) The second part of the paper (the collagen story) is very loosely connected to the first part. dpy-11 encodes an enzyme important for cuticle development, and it is a differentially expressed direct target of SMA-3. dpy-11 can be bound by SMA-9, but it is not affected by this binding according to RNA-Seq. Thus, technically, this part of the paper does not require any information about SMA-9. However, this can likely be improved by addressing the function of the 15 genes, with the opposing mode of regulation by SMA-3 and SMA-9.

      We appreciate this suggestion and have clarified in the text how SMA-9 contributes to collagen organization and body size regulation.

      (4) The Discussion does not add much to the paper - it simply repeats the results in a more streamlined fashion.

      We thank the reviewer for this suggestion. We have added more context to the Discussion.

      Reviewer #2 (Public Review):

      In the present study, Vora et al. elucidated the transcription factors downstream of the BMP pathway components Smad and Schnurri in C. elegans and their effects on body size. Using a combination of a broad range of techniques, they compiled a comprehensive list of genome-wide downstream targets of the Smads SMA-3 and SMA-9. They found that both proteins have an overlapping spectrum of transcriptional target sites they control, but also unique ones. Thereby, they also identified genes involved in one-carbon metabolism or the endoplasmic reticulum (ER) secretory pathway. In an elaborate effort, the authors set out to characterize the effects of numerous of these targets on the regulation of body size in vivo as the BMP pathway is involved in this process. Using the reporter ROL-6::wrmScarlet, they further revealed that not only collagen production, as previously shown, but also collagen secretion into the cuticle is controlled by SMA-3 and SMA-9. The data presented by Vora et al. provide in-depth insight into the means by which the BMP pathway regulates body size, thus offering a whole new set of downstream mechanisms that are potentially interesting to a broad field of researchers.

      The paper is mostly well-researched, and the conclusions are comprehensive and supported by the data presented. However, certain aspects need clarification and potentially extended data.

      (1) The BMP pathway is active during development and growth. Thus, it is logical that the data shown in the study by Vora et al. is based on L2 worms. However, it raises the question of if and how the pattern of transcriptional targets of SMA-3 and SMA-9 changes with age or in the male tail, where the BMP pathway also has been shown to play a role. Is there any data to shed light on this matter or are there any speculations or hypotheses?

      We agree that these are intriguing questions, and we are interested in the roles of transcriptional targets at other developmental stages and in other physiological functions, but these analyses are beyond the scope of the current study.

      (2) As it was shown that SMA-3 and SMA-9 potentially act in a complex to regulate the transcription of several genes, it would be interesting to know whether the two interact with each other or if the cooperation is more indirect.

      A physical interaction between Smads and Schnurri has been amply demonstrated in other systems. Our goal in this study was not to validate this physical interaction, but to analyze functional interactions on a genome-wide scale.

      (3) It would help the understanding of the data even more if the authors could specifically state if there were collagens among the genes regulated by SMA-3 and SMA-9 and which.

      We thank the reviewer for this suggestion. col-94 and col-153 were identified as direct targets of both SMA-3 and SMA-9. We noted this in the Discussion.

      (4) The data on the role of SMA-3 and SMA-9 in the regulation of the secretion of collagens from the hypodermis is highly intriguing. The authors use ROL-6 as a reporter for the secretion of collagens. Is ROL-6 a target of SMA-9 or SMA-3? Even if this is not the case, the data would gain even more strength if a comparable quantification of the cuticular levels of ROL-6 were shown in Figure 6, and potentially a ratio of cuticular versus hypodermal levels. By that, the levels of secretion versus production can be better appreciated.

      We previously showed that rol-6 mRNA levels are reduced in dbl-1 mutants at L2, but RNA-seq analysis did not find enough of a statistically significant change in rol-6 to qualify it as a transcriptional target and total levels of protein are also not significantly reduced in mutants. We added this information in the text.

      (5) It is known that the BMP pathway controls several processes besides body size. The discussion would benefit from a broader overview of how the identified genes could contribute to body size. The focus of the study is on collagen production and secretion, but it would be interesting to have some insights into whether and how other identified proteins could play a role or whether they are likely to not be involved here (such as the ones normally associated with lipid metabolism, etc.).

      We have added more information to the Discussion.

      Reviewer #1 (Recommendations For The Authors):

      Figure 1 - Figure 3: The authors might want to think about condensing this into two figures.

      To avoid confusion with the different workflows, we prefer to keep these as three separate figures.

      Figure 1a-b: Measurement unit missing on X.

      We added the unit “bps” to these graphs.

      Line 244-246: The authors should stress in the Results that they analyzed publicly available ChIP-Seq data, which was not generated by them, - not just by providing a reference to Kudron et al., 2018. As far as I understood, ChIP was performed with an anti-GFP antibody. Please mention this, and specify the information about the vendor and the catalog number in the Methods.

      We would like to clarify the status of the publicly available ChIP-seq data. We generated the GFP tagged SMA-3 and SMA‑9 strains and submitted them to be entered into the queue for ChIP-seq processing by the modENCODE (later modERN) consortium. Thus, the publicly available SMA-3 and SMA-9 ChIP-seq datasets used here were derived from our efforts.  Due to the nature of the consortium’s funding, the data were required to be released publicly upon completion. Nevertheless, our current manuscript provides the first comprehensive analysis of these datasets. We have clarified these issues in the text.  We have also added information regarding the anti-GFP antibody to the Methods.

      Line 267-270: The authors should either provide experimental evidence that SMA-3 and SMA-9 form complexes or write something like "significant overlap between SMA-3 and SMA-9 peaks may indicate complex formation between these two transcription factors as shown in Drosophila" - but in the absence of proof, this must be a point for the Discussion, not for the Results. Moreover, similar behavior of fat-6 (overlapping ChIP peaks) and nhr-114 (non-overlapping ChIP peaks) in SMA-3 and SMA-9 mutants may be interpreted as a circumstantial argument against SMA-3/SMA-9 complex formation (see Lines 342-348). Importantly, since ChIP-Seq data are available for a wide array of C. elegans TFs, it would be very useful to have an estimate of whether SMA-3/SMA-9 peak overlap is significantly higher than the peak overlap between SMA-3 and several other TFs expressed at the same L2 stage.

      We have clarified our goals regarding SMA-3 and SMA-9 interactions and softened our conclusions by indicating in the text that a formal biochemical demonstration would be required to demonstrate a physical interaction. Moreover, we toned down the text by stating that our results suggest that either SMA-3 and SMA-9 frequently bind as either subunits in a complex or in close vicinity to each other along the DNA. We have added an analysis of HOT sites to address overlap of binding with other transcription factors. We disagree with the interpretation that transcription factors with non-overlapping sites cannot act together to regulate gene expression; however, nhr-114 also has an overlapping SMA-3 and SMA-9 site, so this point becomes less relevant. We have clarified the categorization of nhr-114 in the text.

      Lines 272-292: The authors do not comment on the seemingly quite small overlap between the RNA-Seq and the ChIP-Seq dataset, but I think they should. They have 3205 SMA-3 ChIP peaks and 1867 SMA-3 DEGs, but the amount of directly regulated targets is 367. It is important that the authors provide information on the number of genes to which their peaks have been assigned. Clearly, this will not be one gene per peak, but if it were, this would mean that just 11.5% of bound targets are really affected by the binding. The same number would be 4.7% for the SMA-9 peaks.

      We have added a discussion of the discrepancy between binding sites and DEGs. The high number of additional sites classified as non-functional could represent the detection of weak affinity targets that do not have an actual biological purpose. Alternatively, these sites could have an additional role in DBL-1 signaling besides transcriptional regulation of nearby genes, or they could be regulating the expression of target genes at a far enough distance to not be detected by our BETA analysis as per the constraints chosen for the analysis. The difference between total binding sites and those associated with changes in gene expression underscores the importance of combining RNA-seq with ChIP-seq to identify the most biologically relevant targets. And as the reviewer indicated, more than one gene can be assigned to a single neighboring peak.

      Lines 294-323: I feel like there is a terminology problem, which makes reading very difficult. The authors use "direct targets" as bound genes with significant expression change, but then run into a problem when the gene is bound by SMA-9 and SMA-3, but significant expression change is only associated with one of the two factors. I am not sure this is consistent with the idea of the SMA3/SMA9 complex. Also, different modalities of the SMA3 and SMA9 effect in 15 cases can be explained by co-factors. Reading would be also simplified if the order of the panels in Figure 3 were different. Currently, the authors start their explanation by referring to the shared SMA-3/SMA-9 targets (Figures 3c-d), and only later come to Figure 3b. In general, the authors should start with a clear explanation of what is on the figure (currently starting on Line 313), otherwise, it is unclear why, if the authors only discuss common targets, it is not just 114+15=129 targets, but more.

      We have re-ordered the columns in Figure 3 to match the order discussed in the text. We also incorporated more precise language about regulation by SMA-3 and/or SMA-9 in the text.

      Lines 325-355: The chapter has a rather unfortunate name "Mechanisms of integration of SMA-3 and SMA-9 function", although the authors do not provide any mechanism. Using 3 target genes, they show that if the regulatory modality of SMA-3 and SMA-9 is the same (2 examples), there is no difference in the expression of the targets, but if the modalities are opposing (1 example), SMA-9 repressive action is epistatic to the SMA-3 activating action. Can this be generalized? The authors should test all their 15 targets with opposite regulations. Moreover, it seems obvious to ask whether the intermediate phenotype of the double-mutants can be attributed to the action of these 15 genes activated by SMA-3 and repressed by SMA-9. I would suggest testing this by RNAi. I would also suggest renaming the chapter to something better reflecting its content.

      We have removed the word “mechanism” from the title of this section. We also performed additional RT-PCR experiments on another 5 targets with opposing directions of regulation. The results from these genes are consistent with the result from C54E4.5, demonstrating that the epistasis of sma-9 is generalizable.

      Figure 4b: Why was a two-way ANOVA performed here? With the small number of measurements, I would consider using a non-parametric test.

      These data are parametric and the distribution of the data is normal, so we chose to use a parametric test (ANOVA).

      Lines 354-355. The authors offer two suggestions for the mechanism of the epistatic action of SMA-9 on SMA-3 in the case of C54E4.5, but this is something for the Discussion. If they want to keep it in the Results they should address this experimentally by performing SMA-3 ChIP-seq in the SMA-9 mutants and SMA-9 ChIP-Seq in the SMA-3 mutants.

      We moved these models to the discussion as suggested.

      Lines 365-367: "We expect that clusters of genes involved in fatty acid metabolism and innate immunity mediate the physiological functions of BMP signaling in fat storage and pathogen resistance, respectively." - This is pretty confusing since the Authors claim in the previous sentence that regulation of immunity by SMA-9 is TGF-beta independent.

      Co-regulation of immunity by BMP signaling and SMA-9 is already known. The novel insight is that SMA-9 may have an additional independent role in immunity. We have clarified the language to address this confusion.

      Lines 377, and 380: Please explain in non-C. elegans-specific terminology, what rrf-3 and LON-2 are (e.g. write "glypican LON-2" instead of just "LON-2") and add relevant references.

      We added information on the proteins encoded by these genes.

      Lines 382-384: I am not sure what the Authors mean here by "more limiting".

      We substituted the phrase “might have a more prominent requirement in mediating the exaggerated growth defect of a lon-2 mutant”.

      Lines 388-392: I found this very confusing. What were these 36 genes? Were these direct targets of SMA-3, SMA-9, or both? Top 36 targets? 36 targets for which mutants are available?

      The new Figure 5 clarifies whether target genes are SMA-3-exclusive, SMA-9-exclusive, or co-regulated. The text was also updated for clarity.

      Line 397: This is the first time the authors mention dpy-11 but they do not say what it is until later, and they do not say whether it is a target of SMA3/SMA9. Checking Figure 3, I found that it is among the 238 genes bound by both but upregulated only by SMA3. The authors need to explicitly state this - from this point on, they have a section for which SMA-9 appears to be irrelevant.

      We added the molecular function of dpy-11 at its first mention. Furthermore, we included the hypothesis that SMA-3 may regulate collagen secretion independently of SMA-9. Our subsequent results with sma-9 mutants disprove this hypothesis.

      Line 402: Is ROL-6 a SMA-3/SMA-9 target or just a marker gene?

      We previously showed that rol-6 mRNA levels are reduced in dbl-1 mutants at L2, but RNA-seq analysis did not find enough of a statistically significant change in rol-6 to qualify it as a transcriptional target and total levels of protein are also not significantly reduced in mutants. We added this information in the text.

      Line 421: I am not sure what "more skeletonized" means.

      Replaced with “thinner and skeletonized”

      Figure 2b and 2d legends: "Non-target genes nevertheless showing differential expression are indicated with green squares." (l. 581-582 and again l. 588-589) I think should be "Non-direct target genes...".

      Changed to “non-direct target genes”

      Figure 7 legend: Please indicate the scale bar size in the legend.

      Indicated the scale bar size in the legend.

      Figure 7: The ER marker is referred to as "ssGFP::KDEL" (in the image and Line 700), however in the text it is called "KDEL::oxGFP" (Line 419). Please use consistent naming.

      We fixed the inconsistent naming.

      All the experiment suggestions made are optional and can, in principle, be ignored if the authors tone down their claims (for example, the SMA-3/SMA-9 complex formation).

      Reviewer #2 (Recommendations For The Authors):

      (1) As a control: Have the authors found the known regulated genes among the differentially regulated ones?

      Previously known target genes such as fat-6 and zip-10 were identified here. We have added this information in the text.

      (2) How many repetitions were performed in Figure 4b? I am wondering as the deviation for C54E4.5 is quite large and that makes me worry that the significant differences stated are not robust.

      There were two biologically independent collections from which three cDNA syntheses were analyzed using two technical replicates per point.

      (3) Lines 333-336: Can you really make this claim that the antagonistic effects seen in the regulation of body size can be correlated with some targets being regulated in the opposite direction? I would assume that the situation is far more complex as SMADs also regulate other processes.

      We agree with the reviewer that multiple models could explain this antagonism, and we have added distinct alternatives in the text.

      (4) Lines 367-369: Add the respective reference please.

      We have added the relevant references.

    1. Reviewer #2 (Public review):

      Summary:

      Suzuki and colleagues aim to develop an in vitro organoid system to recapitulate the developmental process of the olfactory epithelium. The authors have succeeded in using a combination of niche factors to induce organoid development, which gives rise to multiple cell types including those with characteristics of mature olfactory sensory neurons. By comparing different cultural media in inducing lineage specification in the organoids, the authors show that the niche factors play an important role in the neuronal lineage whereas serum promotes the development of the respiratory epithelium. The authors further utilized single-cell RNASeq and trajectory analysis to demonstrate that the organoids recapitulate the developmental process of the olfactory epithelium and that some of the factory sensory neurons express only one receptor type per cell. Using these analyses, the authors proposed that a specific set of guidance modules are associated with individual receptor types to enable the formation of the factory map.

      Strengths:

      The strength of the paper is that the authors have demonstrated that olfactory epithelium organoids can develop from dissociated cells from embryonic or tissue. This provides a valuable tool for studying the development of processes of the factory epithelium in vitro. Defining various factors in the media that influence the development trajectories of various cell types also provides valuable information to guide further development of the method. Single-cell RNA-Seq experiments provide information about the developmental processes of the olfactory system.

      Weaknesses:

      The manuscript is also marked by a number of weaknesses. The premise of the studies is not well argued. The authors set out to use organoid culture to study the developmental process in order to unravel the mechanisms of single receptor choice, and its role in setting up the factory map. However, the paper has mostly focused on characterizing the organization rather than providing insights into the problem. The statement that the organoids can develop from single cells is misleading, because it's mostly likely that organoids develop after the dissociated cells form aggregates before developing into organoids. It is not known whether coarsely separated tissue chunks can develop into organoids with the same characteristics. Re-aggregation of the cells to form organoids is in and of itself is interesting. Unfortunately, the heterogeneity of the cells and how they contribute to the development of overnight is not explored. There is also a missed opportunity to compare single-cell RNASeq data from this study with existing ones. The in vitro system is likely to be different from embryonic development. It is critical to compare and determine how much the organoid is recapitulating the development of the OSNs in vivo. There are a number of comprehensive datasets from the OE in addition to that presented in the Fletcher paper. Finally, the quality of the functional assay (calcium imaging) of factory sensory neurons is poor. Experiments are of high quality are needed to verify the results.

      Major points:

      (1) Adding FBS in organoid culture medium has been shown to negatively affect the organoid formation and growth. Previous OE organoids culture method did not use FBS. Also, day 10 is an odd choice to compare the two conditions after showing day 20 of NF+ culture shows a better differentiation state. It is not known whether and how the differentiation may be different on day 20. Moreover, comparing Figure 2R to 2S, FBS treatment alone appears to have not only more Foxj1+ cells but also more Tuj1+ cells than NFs/FBS. This is inconsistent with the model. The authors should provide statistics for Tuj1+ cells as well.

      (2) As opposed to the statement in the manuscript, Plxnb2 had been shown to be expressed by the OSNs (Mclntyre et al. 2010; JNR), specifically in immature OSNs. It would be important to mention that Plxnb2 is expressed in OMP+ OSNs in the OE organoid system and its potential reasons to better guide the readers of the system mimicking the in vivo OSNs. Similarly, OSN expression of Cdh2 has been shown by Akins and colleagues. As Plxnb2 showed an expression pattern (immunofluorescence) with an anterior-posterior axis while Cdh2 expression level was not, it would be informative to show the odorant receptor types regarding the expression pattern of Plxnb2 (versus that of Cdh2) using single cell RNAseq data4.

      (3) There is no real layering of the organoids, although some cells show biases toward one side or the other in some regions of the organoid. The authors should not make a sweeping claim that the organoids establish layered structures.

      (4) Figure 2P, it is clear whether OMP is present in the cell bodies. The signal is not very convincing. Even the DAPI signal does not seem to be on a comparable scale compared to Figures 2N and 2O.

      (5) Annotation of the cell types in different single-cell RNA-Seq analysis. The iOSN is only marked in Figure 3A. In the marker expression panel, it appears that those marked as mOSN have high GAP43, which are an iOSN marker. These discrepancies are not detailed nor discussed.

      (6) The authors should merge the single-cell datasets from day 10 organoids cultured in NF-medium and FBS-medium to compare their differences.

      (7) The quality of the calcium imaging experiment is poor. Labeling and experimental details are not provided. The concentration of IVA, the manner of its delivery, and delivery duration are not provided. How many ROIs have been imaged, and what percentage of them responded to IVA? Do they respond to more than one odor? Do they respond to repeated delivery? There is no control for solution osmolarity. Cell body response was not recorded. Given that only a small number of cells express a receptor, it seems extraordinary that these axons respond to IVA receptors. The authors should also determine whether IVA receptor genes are found in their dataset.

    1. Reviewer #2 (Public review):

      Summary:

      With this report, I suggest what are in my opinion crucial additions to the otherwise very interesting and credible research manuscript "Cluster size determines morphology of transcription factories in human cells".

      Strengths:

      The manuscript in itself is technically sound, the chosen simulation methods are completely appropriate the figures are well-prepared, the text is mostly well-written spare a few typos. The conclusions are valid and would represent a valuable conceptual contribution to the field of clustering, 3D genome organization and gene regulation related to transcription factories, which continues to be an area of most active investigation.

      Weaknesses:

      However, I find that the connection to concrete biological data is weak. This holds especially given that the data that are needed to critically assess the applicability of the derived cross-over with factory size is, in fact, available for analysis, and the suggested experiments in the Discussion section are actually done and their results can be exploited. In my judgement, unless these additional analysis are added to a level that crucial predictions on TF demixing and transcriptional bursting upon TU clustering can be tested, the paper is more fitted for a theoretical biophysics venue than for a biology journal.

      Major points

      (1) My first point concerns terminology. The Merriam-Webster dictionary describes morphology as the study of structure and form. In my understanding, none of the analyses carried out in this study actually address the form or spatial structuring of transcription factories. I see no aspects of shape, only size. Unless the authors want to assess actual shapes of clusters, I would recommend to instead talk about only their size/extent. The title is, by the same argument, in my opinion misleading as to the content of this study.

      (2) Another major conceptual point is the choice of how a single TF:pol particle in the model relates to actual macromolecules that undergo clustering in the cell. What about the fact that even single TF factories still contain numerous canonical transcription factors, many of which are also known to undergo phase separation? Mediator, CDK9, Pol II just to name a few. This alone already represents phase separation under the involvement of different species, which must undergo mixing. This is conceptually blurred with the concept of gene-specific transcription factors that are recruited into clusters/condensates due to sequence-specific or chromatin-epigenetic-specific affinities. Also, the fact that even in a canonical gene with a "small" transcription factory there are numerous clustering factors takes even the smallest factories into a regime of several tens of clustering macromolecules. It is unclear to me how this reality of clustering and factory formation in the biological cell relates to the cross-over that occurs at approximately n=10 particles in the simulations presented in this paper.

      (3) The paper falls critically short in referencing and exploiting for analysis existing literature and published data both on 3D genome organization as well as the process of cluster formation in relation to genomic elements. In terms of relevant literature, most of the relevant body of work from the following areas has not been included:

      (i) mechanisms of how the clustering of Pol II, canonical TFs, and specific TFs is aided by sequence elements and specific chromatin states

      (ii) mechanisms of TF selectivity for specific condensates and target genomic elements

      (iii) most crucially, existing highly relevant datasets that connect 3D multi-point contacts with transcription factor identity and transcriptional activity, which would allow the authors to directly test their hypotheses by analysis of existing data

      Here, especially the data under point iii are essential. The SPRITE method (cited but not further exploited by the authors), even in its initial form of publication, would have offered a data set to critically test the mixing vs. demixing hypothesis put forward by the authors. Specifically, the SPRITE method offers ordered data on k-mers of associated genomic elements. These can be mapped against the main TFs that associate with these genomic elements, thereby giving an account of the mixed / demixed state of these k-mer associations. Even a simple analysis sorting these associations by the number of associated genomic elements might reveal a demixing transition with increasing association size k. However, a newer version of the SPRITE method already exists, which combines the k-mer association of genomic elements with the whole transcriptome assessment of RNAs associated with a particular DNA k-mer association. This can even directly test the hypotheses the authors put forward regarding cluster size, transcriptional activation, correlation between different transcription units' activation etc.

      To continue, the Genome Architecture Mapping (GAM) method from Ana Pombo's group has also yielded data sets that connect the long-range contacts between gene-regulatory elements to the TF motifs involved in these motifs, and even provides ready-made analyses that assess how mixed or demixed the TF composition at different interaction hubs is. I do not see why this work and data set is not even acknowledged? I also strongly suggest to analyze, or if they are already sufficiently analyzed, discuss these data in the light of 3D interaction hub size (number of interacting elements) and TF motif composition of the involved genomic elements.

      Further, a preprint from the Alistair Boettiger and Kevin Wang labs from May 2024 also provides direct, single-cell imaging data of all super-enhancers, combined with transcription detection, assessing even directly the role of number of super-enhancers in spatial proximity as a determinant of transcriptional state. This data set and findings should be discussed, not in vague terms but in detailed terms of what parts of the authors' predictions match or do not match these data.

      For these data sets, an analysis in terms of the authors' key predictions must be carried out (unless the underlying papers already provide such final analysis results). In answering this comment, what matters to me is not that the authors follow my suggestions to the letter. Rather, I would want to see that the wealth of available biological data and knowledge that connects to their predictions is used to their full potential in terms of rejecting, confirming, refining, or putting into real biological context the model predictions made in this study.

      References for point (iii):

      RNA promotes the formation of spatial compartments in the nucleus<br /> https://www.cell.com/cell/fulltext/S0092-8674(21)01230-7?dgcid=raven_jbs_etoc_email

      Complex multi-enhancer contacts captured by genome architecture mapping<br /> https://www.nature.com/articles/nature21411

      Cell-type specialization is encoded by specific chromatin topologies<br /> https://www.nature.com/articles/s41586-021-04081-2

      Super-enhancer interactomes from single cells link clustering and transcription<br /> https://www.biorxiv.org/content/10.1101/2024.05.08.593251v1.full

      For point (i) and point (ii), the authors should go through the relevant literature on Pol II and TF clustering, how this connects to genomic features that support the cluster formation, and also the recent literature on TF specificity. On the last point, TF specificity, especially the groups of Ben Sabari and Mustafa Mir have presented astonishing results, that seem highly relevant to the Discussion of this manuscript.

      (4) Another conceptual point that is a critical omission is the clarification that there are, in fact, known large vs. small transcription factories, or transcriptional clusters, which are specific to stem cells and "stressed cells". This distinction was initially established by Ibrahim Cisse's lab (Science 2018) in mouse Embryonic Stem Cells, and also is seen in two other cases in differentiated cells in response to serum stimulus and in early embryonic development:

      Mediator and RNA polymerase II clusters associate in transcription-dependent condensates<br /> https://www.science.org/doi/10.1126/science.aar4199

      Nuclear actin regulates inducible transcription by enhancing RNA polymerase II clustering<br /> https://www.science.org/doi/10.1126/sciadv.aay6515

      RNA polymerase II clusters form in line with surface condensation on regulatory chromatin<br /> https://www.embopress.org/doi/full/10.15252/msb.202110272

      If "morphology" should indeed be discussed, the last paper is a good starting point, especially in combination with this additional paper:

      Chromatin expansion microscopy reveals nanoscale organization of transcription and chromatin<br /> https://www.science.org/doi/10.1126/science.ade5308

      (5) The statement "scripts are available upon request" is insufficient by current FAIR standards and seems to be non-compliant with eLife requirements. At a minimum, all, and I mean all, scripts that are needed to produce the simulation outcomes and figures in the paper, must be deposited as a publicly accessible Supplement with the article. Better would be if they would be structured and sufficiently documented and then deposited in external repositories that are appropriate for the sharing of such program code and models.

    1. Reviewer #2 (Public review):

      Summary:

      ACVR2A is one of a handful of genes for which significant correlations between associated SNPs and the incidences of preeclampsia have been found in multiple populations. It is one of the TGFB family receptors, and multiple ligands of ACVR2A, as well as its coreceptors and related inhibitors, have been implicated in placental development, trophoblast invasion, and embryo implantation. This useful study builds on this knowledge by showing that ACVR2A knockout in trophoblast-related cell lines reduces trophoblast invasion, which could tie together many of these observations. Support for this finding is incomplete, as reduced proliferation may be influencing the invasion results. The implication of cross-talk between the WNT and ACRV2A/SMAD2 pathways is an important contribution to the understanding of the regulation of trophoblast function.

      Strengths:

      (1) ACVR2A is one of very few genes implicated in preeclampsia in multiple human populations, yet its role in pathogenesis is not very well studied and this study begins to address that hole in our knowledge.

      (2) ACVR2A is also indirectly implicated in trophoblast invasion and trophoblast development via its connections to many ligands, inhibitors, and coreceptors, suggesting its potential importance.

      (3) The authors have used multiple cell lines to verify their most important observations.

      Weaknesses:

      (1) There are a number of claims made in the introduction without attribution. For example, there are no citations for the claims that family history is a significant risk factor for PE, that inadequate trophoblast invasion of spiral arteries is a key factor, and that immune responses, and renin-angiotensin activity are involved.

      (2) The introduction states "As a receptor for activin A, ACVR2A..." It's important to acknowledge that ACVR2A is also the receptor for other TGFB family members, with varying affinities and coreceptors. Several TGFB family members are known to regulate trophoblast differentiation and invasion. For example, BMP2 likely stimulates trophoblast invasion at least in part via ACVR2A (PMID 29846546).

      (3) An alternative hypothesis for the potential role of ACVR2A in preeclampsia is its functions in the endometrium. In the mouse ACVR2A knockout in the uterus (and other progesterone receptor-expressing cells) leads to embryo implantation failure.

      (4) In the description of the patient population for placental sample collections, preeclampsia is defined only by hypertension, and this is described as being in accordance with ACOG guidelines. ACOG requires a finding of hypertension in combination with either proteinuria or one of the following: thrombocytopenia, elevated creatinine, elevated liver enzymes, pulmonary, edema, and new onset unresponsive headache.

      (5) I believe that Figures 1a and 1b are data from a previously published RNAseq dataset, though it is not entirely clear in the text. The methods section does not include a description of the analysis of these data undertaken here. It would be helpful to include at least a brief description of the study these data are taken from - how many samples, how were the PE/control groups defined, gestational age range, where is it from, etc. For the heatmap presented in B, what is the significance of the other genes/ why are they being shown? If the purpose of these two panels is to show differential expression specifically of ACVR2A in this dataset, that could be shown more directly.

      (6) More information is needed in the methods section to understand how the immunohistochemistry was quantified. "Quantitation was performed" is all that is provided. Was staining quantified across the whole image or only in anchoring villous areas? How were HRP & hematoxylin signals distinguished in ImageJ? How was the overall level of HRP/DAB development kept constant between the NC and PE groups?

      (7) In Figure 1E it is not immediately obvious to many readers where the EVT are. It is probably worth circling or putting an arrow to the little region of ACVR2A+ EVT that is shown in the higher magnification image in Figure 1E. These are actually easier to see in the pictures provided in the supplement Figure 1. Of note, the STB is also staining positive. This is worth pointing out in the results text.

      (8) It is not possible to judge whether the IF images in 1F actually depict anchoring villi. The DAPI is really faint, and it's high magnification, so there isn't a lot of context. Would it be possible to include a lower magnification image that shows where these cells are located within a placental section? It is also somewhat surprising that this receptor is expressed in the cytoplasm rather than at the cell surface. How do the authors explain this?

      (9) The results text makes it sound like the data in Figure 2A are from NCBI & Protein atlas, but the legend says it is qPCR from this lab. The methods do not detail how these various cell lines were grown; only HTR-SVNeo cell culture is described. Similarly, JAR cells are used for several experiments and their culture is not described.

      (10) Under RT-qPCR methods, the phrase "cDNA reverse transcription cell RNA was isolated..." does not make any sense.

      (11) The paragraph beginning "Consequently, a potential association..." is quite confusing. It mentions analyzing ACVR2A expression in placentas, but then doesn't point to any results of this kind and repeats describing the results in Figure 2a, from various cell lines.

      (12) The authors should acknowledge that the effect of the ACVR2A knockout on proliferation makes it difficult to draw any conclusions from the trophoblast invasion assays. That is, there might be fewer migrating or invading cells in the knockout lines because there are fewer cells, not because the cells that are there are less invasive. Since this is a central conclusion of the study, it is a major drawback.

      (13) The legend and the methods section do not agree on how many fields were selected for counting in the transwell invasion assays in Figure 3C. The methods section and the graph do not match the number of replicate experiments in Figure 3D (the number of replicate experiments isn't described for 3C).

      (14) Discussion says "Transcriptome sequencing analysis revealed low ACVR2A expression in placental samples from PE patients, consistent with GWAS results across diverse populations." The authors should explain this briefly. Why would SNPs in ACVR2A necessarily affect levels of the transcript?

      (15) "The expression levels of ACVR2A mRNA were comparable to those of tumor cells such as A549. This discovery suggested a potential pivotal role of ACVR2A in the biological functions of trophoblast cells, especially in the nurturing layer." Alternatively, ACVR2A expression resembles that of tumors because the cell lines used here are tumor cells (JAR) or immortalized cells (HTR8). These lines are widely used to study trophoblast properties, but the discussion should at least acknowledge the possibility that the behavior of these cells does not always resemble normal trophoblasts.

      (16) The authors should discuss some of what is known about the relationship between the TCF7/c-JUN pathway and the major signaling pathway activated by ACVR2A, Smad 2/3/4. The Wnt and TGFB family cross-talk is quite complex and it has been studied in other systems.

    1. gemini的赏析(关于戏剧化)

      要以雅各布·范·鲁伊斯达尔的《麦田》(The Wheatfields, 1670)为例来解释“戏剧化”,我们需要仔细观察这幅画的构图、光影、色彩以及整体氛围,看看鲁伊斯达尔是如何运用这些元素来创造出一种具有舞台剧效果的视觉冲击力和情感表现力的。

      虽然存在多幅鲁伊斯达尔名为“麦田”的作品,但通常被认为是代表作的是藏于卢浮宫的那一幅。以下分析主要基于对该作品的理解。

      《麦田》中的“戏剧化”表现:

      1. 光影的强烈对比: 这是最明显的“戏剧化”元素。《麦田》中,天空占据了画面很大的比例,厚重的云层遮蔽了大部分天空,只有几束阳光穿透云层,照射在远处的田野和房屋上。这种强烈的明暗对比,营造出了一种紧张、动荡的氛围,仿佛舞台剧中的聚光灯效果,突出了画面中的主体——金色的麦田和远处的房屋。被照亮的区域显得格外明亮,与周围的阴影形成鲜明对比,吸引了观者的目光,增强了画面的视觉冲击力。

      2. 构图的精心安排: 鲁伊斯达尔并没有简单地描绘一片麦田,而是精心安排了画面中的各种元素。蜿蜒的小路引导着观者的视线向画面深处延伸,远处的房屋和树木则构成了画面的焦点。前景中的植物和麦田的边缘则增加了画面的层次感和空间感。这种构图方式并非随机的自然景象,而是经过艺术家精心设计的,如同舞台剧的布景,引导观众的视线,并营造出一种身临其境的感觉。

      3. 天空的表现: 《麦田》中,天空的表现非常出色。厚重的云层、穿透云层的阳光、以及云层投下的阴影,都刻画得非常细腻。天空的变化不仅为画面增添了动感和戏剧性,也烘托了不同的气氛。阴沉的云层预示着风雨欲来,而穿透云层的阳光则带来了一丝希望和光明。这种天空的表现,如同舞台剧的背景,增强了画面的戏剧效果。

      4. 色彩的运用: 《麦田》的色彩运用也非常出色。金黄色的麦田与深沉的绿色、灰色和蓝色形成了鲜明的对比,突出了麦田的色彩。这种色彩的对比不仅增强了画面的视觉冲击力,也表达了艺术家对自然的赞美和热爱。

      5. 氛围的营造: 通过以上各种元素的综合运用,鲁伊斯达尔在《麦田》中营造出了一种独特的氛围。画面既有自然的宁静和祥和,又隐含着一种潜在的动荡和不安。这种复杂的氛围,使画面更具感染力,也更具“戏剧性”。

      总结:

      在《麦田》中,“戏剧化”并非指画面中发生了什么惊心动魄的故事,而是指鲁伊斯达尔通过对光影、构图、天空、色彩以及氛围的精心营造,使画面具有了强烈的视觉冲击力和情感表现力,如同舞台剧般引人入胜。他运用光影的对比来突出重点,运用构图来引导视线,运用天空来烘托气氛,运用色彩来增强表现力,所有这些都共同作用,最终成就了这幅极具“戏剧性”的风景画杰作。

      因此,当我们说鲁伊斯达尔的作品具有“戏剧化”特征时,我们指的是他运用绘画技巧,使画面超越了简单的自然再现,而具有了更深层次的艺术感染力和情感表达力。

    1. he Tao is infinite, eternal.Why is it eternal?It was never born;thus it can never die.Why is it infinite?It has no desires for itself;thus it is present for all beings.

      I found this to be quite confusing. I don't understand how proof for something being eternal is the fact that it was born. I think the only way to argue that something born is infinite is through religion which isn't something that everyone follows. Since this wouldn't be good proof I'm curious if he's arguing it from a different perspective that I missed.

    1. chatgpt赏析

      奥托·迪克斯(Otto Dix)的《七宗罪》(Die sieben Todsünden, 1933)是德国画家在纳粹政权初期创作的一幅反映社会与人性复杂性的作品。这幅画以浓厚的象征主义和表现主义风格,揭示了当时社会中的腐败、堕落和恐怖,结合宗教寓意和政治批判,为我们提供了深刻的艺术和历史解读空间。以下是欣赏这幅画的详细解析:


      画作背景

      1. 历史背景

      • 1933年是希特勒上台的第一年,纳粹开始对德国社会进行全面控制,许多艺术家、知识分子受到压迫。奥托·迪克斯作为一位尖锐的批判艺术家,他对社会的观察往往包含强烈的反思与控诉。
      • 《七宗罪》以宗教道德中的“骄傲、贪婪、色欲、嫉妒、暴怒、暴食和懒惰”作为主题,通过现代化的视觉语言表达了当时社会的道德衰败和政治压迫。

      2. 艺术风格

      • 这幅画延续了迪克斯新客观主义(Neue Sachlichkeit)的风格特点,但同时融入了表现主义和宗教画传统。通过夸张的形象和恐怖的氛围,他探讨人类在困境中的道德堕落。

      画面构成与人物象征

      画面描绘了多个怪诞而畸形的形象,每一个人物都象征着一宗罪。

      1. 中央人物
      2. 中央形象可能代表“骄傲”(Pride),这在宗教传统中是七宗罪的核心。这个形象可能带有权威者的特征,象征着当时纳粹政权的傲慢与霸权。
      3. 它通常以威胁的姿态或夸张的造型出现,目光令人不安。

      4. 周围人物

      5. 贪婪(Greed):可能以握住财富或食物的形象出现,夸张的面部表情暗示了过度占有的欲望。
      6. 色欲(Lust):可能以挑逗或扭曲的形象展现,表现出不健康的性欲和沉溺。
      7. 暴怒(Wrath):可能通过一个充满攻击性的姿态或咆哮的形象表现,象征社会中的暴力和冲突。
      8. 懒惰(Sloth):可能以一种松散或无力的姿态出现,反映出逃避责任和无所事事的状态。
      9. 暴食(Gluttony):体型臃肿或正在进食的形象象征着对物质和欲望的无节制索取。
      10. 嫉妒(Envy):带有贪婪目光或扭曲表情的形象,象征对他人拥有的事物的痛苦和敌意。

      11. 背景与整体氛围

      12. 背景通常表现为一个混乱、阴暗的空间,暗示社会的颓废和恐怖。
      13. 迪克斯运用了对比强烈的光影,使整个画面充满戏剧性和不安。

      艺术特点

      1. 夸张的形象与表现主义风格

      • 人物形象带有明显的变形和夸张特征,目的是表现人类内心的丑恶和堕落。
      • 这些形象似人非人,既有现实主义的细节,又融入了幻想和象征的元素。

      2. 色彩与情绪

      • 画作可能以阴冷的色调为主,突出焦虑和恐惧的氛围。
      • 迪克斯通过强烈的色彩对比(如深红、黑色和黄色)表现暴力和紧张情绪。

      3. 宗教隐喻与社会批判的结合

      • 《七宗罪》借用了宗教中关于道德堕落的概念,但他的批判目标是当代社会的腐败与暴力,尤其是纳粹政权对人性的压迫。
      • 通过这些象征化的人物,迪克斯揭示了人类内心的黑暗面以及政治体制如何利用这些罪恶特质。

      主题与象征意义

      1. 对纳粹的隐喻

      • 虽然画作表面上表现的是传统的七宗罪,但许多学者认为迪克斯借此影射了纳粹政权的统治方式。他通过这些丑陋的形象警示人们纳粹对社会和人性的摧残。

      2. 人性堕落的普遍性

      • 《七宗罪》不仅是对纳粹的批判,也是对整个人类社会的反思。迪克斯认为,无论是普通人还是掌权者,都有可能在压力下展现出这些罪恶特质。

      3. 宗教与道德的现代诠释

      • 通过将传统宗教主题置于现代社会语境中,迪克斯让观众思考道德与现实之间的矛盾。他似乎在暗示,社会的腐败往往源于个人的道德崩塌。

      欣赏方法

      1. 解读人物象征
      2. 仔细观察每个角色的细节,如动作、表情和服饰,尝试与七宗罪的概念对应起来。

      3. 感受画面的情绪

      4. 注意整体的阴暗氛围以及色彩和构图的运用,这些都传递了深刻的不安和批判性。

      5. 联系历史背景

      6. 将这幅画置于1933年的德国社会中思考,纳粹政权的崛起和对个人自由的压迫如何激发了迪克斯的创作。

      7. 从宗教隐喻到现代批判

      8. 思考画作如何通过传统宗教主题反映当时的社会现实,以及这种隐喻如何揭示更深层次的道德与政治问题。

      总结

      奥托·迪克斯的《七宗罪》是一幅融合宗教象征、社会批判和艺术创新的杰作。通过扭曲和夸张的形象,他揭示了人类内心的黑暗和当时社会的堕落。这幅画不仅是一种对纳粹政权的抗议,更是一种对人性和道德的深刻反思。欣赏时,可以从历史、艺术风格和象征意义等多个维度切入,感受其深刻的思想力量和视觉冲击力。

    1. chatgpt赏析

      这幅画是意大利文艺复兴时期艺术家提香(Titian)创作的作品之一,题为《佛罗拉》(Flora),创作于1515年至1520年左右,现收藏于佛罗伦萨的乌菲兹美术馆(Uffizi Gallery)。这是一幅经典的女性肖像画,以神话人物佛罗拉(Flora,罗马神话中的花神)为主题,同时也展现了文艺复兴时期艺术对女性美与自然的崇敬。以下是欣赏这幅画的详细指南:


      画面构成与第一印象

      这幅画描绘了一位年轻的女子,她身穿宽松的白色丝绸衣物,手中拿着花朵,眼神温柔而含蓄地注视远方。她的姿态优雅而自然,表现出一种既纯洁又感性的气质。背景为深色调,突显了人物形象的明亮与生动。


      艺术特点

      1. 色彩与光影

      • 提香以细腻的色彩过渡和光影效果塑造人物的立体感。白色的丝绸衣物通过光影的细致处理,呈现出柔软的质感。
      • 她的肤色与背景形成对比,突出了人物的温暖与生机。

      2. 构图与视线引导

      • 女子的姿态略微倾斜,视线看向画面外,给观众一种含蓄的神秘感。
      • 画作的构图非常紧凑,背景简洁,观众的注意力完全集中在人物身上。

      3. 衣饰与手中的花

      • 她身穿白色丝绸衣物,象征纯洁与高贵,而衣物的半敞开样式又带有一种感性的美感。
      • 手中的花是对佛罗拉身份的象征,代表自然、春天和生命的绽放。

      主题与内涵

      1. 佛罗拉的象征意义

      • 佛罗拉是罗马神话中的花神,与春天和自然的复苏相关联。画中的女子以优雅与纯净的形象再现了佛罗拉这一神话角色。
      • 花的象征意义不仅是自然的美,也暗示了女性的青春与活力。

      2. 纯洁与感性的结合

      • 提香通过衣物和表情的处理,表现出女性气质的双重性:纯洁与感性。她既是自然的象征,又具有某种神秘的吸引力。

      3. 文艺复兴的人文主义精神

      • 文艺复兴时期的艺术强调对人类美的探索和对古典文化的复兴。提香通过佛罗拉这一主题,表现了人性之美与自然之美的统一。

      艺术背景

      1. 提香的风格与技法

      • 作为威尼斯画派的代表人物,提香以丰富的色彩运用和柔和的光影处理著称。他的作品注重人物的情感表达和自然气息。
      • 《佛罗拉》是提香早期肖像画的代表作之一,体现了他对女性美的独特理解。

      2. 神话主题的流行

      • 文艺复兴时期的艺术家常常以古典神话为题材,通过寓意和象征来表现人文主义思想。这幅画不仅是对佛罗拉的描绘,也是对自然与人类关系的赞颂。

      3. 女性肖像的特殊地位

      • 在文艺复兴时期,女性肖像画是艺术家表达理想美的重要载体。提香以柔美的笔触和优雅的构图,赋予画中女性一种永恒的魅力。

      欣赏方法

      1. 观察色彩与质感
      2. 注意丝绸衣物的光泽感和人物肤色的细腻处理,感受提香在色彩和质感表现上的高超技艺。

      3. 体验情感与氛围

      4. 女子的目光与微笑带有一种温柔而含蓄的情感,给人一种静谧而深邃的氛围。观众可以试着与她的目光交流,感受她的情绪。

      5. 关注象征意义

      6. 花朵、丝绸衣物和女子的姿态共同构成了对佛罗拉身份的暗示,同时也是对青春与生命的赞美。

      7. 思考人物与背景的关系

      8. 深色背景使人物更加突出,仿佛从暗处走入光明,这种处理方式不仅增加了画面的戏剧性,也突显了人物的神圣感。

      总结

      《佛罗拉》是一幅集合了提香技艺与文艺复兴思想的杰作。它以柔和的色彩、优雅的构图和深刻的象征意义表现了女性美与自然美的完美结合。欣赏这幅画时,可以通过细腻的视觉体验感受提香的艺术天赋,同时通过佛罗拉这一主题反思人类与自然之间的和谐关系。这幅画不仅是视觉艺术的享受,也是人文精神的体现。

    1. chatgpt赏析

      詹姆斯·阿博特·麦克尼尔·惠斯勒(James Abbott McNeill Whistler)的《灰与黑的排列第一号》(Arrangement in Grey and Black No. 1, 1871),更为人熟知的名字是《惠斯勒的母亲》(Whistler’s Mother)。它是19世纪最具标志性的作品之一,被认为是西方肖像艺术中的经典。这幅画以其极简主义的风格、深刻的情感内涵和独特的形式理念而闻名。以下是欣赏这幅画的详细指南:


      画面构成

      画作描绘了一位老年女性(惠斯勒的母亲安娜·麦克尼尔·惠斯勒)端坐在一把椅子上,双手叠放在膝上,身穿黑色衣裙,背景是灰色的墙面和一幅黑白框画。画面简洁而克制,几乎没有多余的细节,突出主体的宁静感与沉稳的气质。


      艺术特点

      1. 极简构图

      • 画面以水平和垂直线条为主,椅子、墙面和窗帘的线条与母亲的姿态形成一种平衡。
      • 大面积的灰与黑形成强烈的色块对比,使整个画面极具稳定感和形式美感。

      2. 色调与氛围

      • 惠斯勒运用了灰色与黑色的层次变化,强调单一色调的丰富性。灰色的背景和黑色的服饰形成一种克制的情感表达,与人物的端庄姿态相呼应。
      • 这种色调传递了一种宁静、肃穆和永恒的气质,仿佛时间在这一刻静止。

      3. 光线与质感

      • 画面光线柔和,没有强烈的明暗对比。母亲的面部被精心刻画,展现了岁月的痕迹。
      • 黑色裙子的质感通过细腻的笔触表现,传递出一种优雅而低调的美。

      主题与内涵

      1. 母爱的象征

      • 虽然惠斯勒本人并未将这幅画定义为关于“母爱”的主题,但它被后世广泛解读为母爱的象征。母亲的沉静与端庄被视为家庭价值和传统的体现。

      2. 形式优先的艺术理念

      • 惠斯勒强调,这幅画的核心是色彩与形式的和谐,而非叙事内容。这种“为艺术而艺术”的理念是他艺术哲学的重要组成部分。
      • “排列”(Arrangement)一词在标题中的使用表明画家将作品视为一种视觉构图,而非情感叙事。

      3. 时间与永恒

      • 母亲的姿态和神情传递了一种跨越时间的安宁感。她的静止姿态与背景的简洁相结合,暗示了生命的短暂与永恒之间的对话。

      艺术背景

      1. 19世纪肖像艺术的创新

      • 在惠斯勒的时代,肖像画通常注重细节与身份的展示,如繁复的背景和人物的社会地位。然而,惠斯勒选择极简的方式,只关注构图、色调与氛围。
      • 这种简洁的风格影响了后来的现代主义艺术家。

      2. “为艺术而艺术”的先驱

      • 惠斯勒是“为艺术而艺术”理念的早期倡导者,他反对艺术仅服务于叙事或道德功能,认为艺术的核心是形式与色彩的美学。

      欣赏方法

      1. 感受画面的构图与形式
      2. 注意画面中的水平与垂直线条,如墙壁、窗帘与人物姿态的关系。这些线条形成了画面的结构骨架,使作品在视觉上极为平衡。

      3. 观察色彩的微妙变化

      4. 虽然画面以灰与黑为主调,但不同灰色的层次变化(墙面、裙子、背景画)展现了细腻的色彩控制。

      5. 体验人物的情感

      6. 尽管母亲的表情非常克制,但她的姿态与整体氛围传递了一种安静、坚韧的气质。观众可以从这种克制中感受到深刻的情感共鸣。

      7. 关注细节与质感

      8. 母亲的服饰、椅子的雕刻细节和背景画框的处理,尽显惠斯勒对形式美的执着追求。

      9. 理解作品的现代意义

      10. 这幅画不仅是关于母亲或家庭的纪念,也是对艺术本质的思考。它传递了一种纯粹的视觉体验,为后来的现代艺术奠定了基础。

      影响与意义

      1. 文化象征
      2. 这幅画已经超越了单纯的艺术作品,成为母爱、家庭和传统的象征,被用作各类文化传播的符号。

      3. 艺术史上的地位

      4. 它是现代主义艺术的先声之一,启发了后来的艺术家从形式和色彩的角度探索艺术。

      5. 大众的情感共鸣

      6. 虽然作品本身强调形式,但它的情感内涵——尤其是与母亲的联系——使其深受观众喜爱。

      总结

      《灰与黑的排列第一号》是一幅超越时代的作品,它的力量来自于极简的构图、深沉的情感内涵以及惠斯勒对艺术本质的深刻思考。欣赏这幅画时,既可以从其视觉形式的和谐美中获得美学满足,也可以从母亲形象中感受到温暖与敬意。这幅画是传统与现代、情感与形式的完美结合,具有跨越时空的艺术价值。

    2. chatgpt赏析

      这幅画是詹姆斯·阿博特·麦克尼尔·惠斯勒(James Abbott McNeill Whistler)的作品,标题为《夜曲:蓝与金——旧桥》(Nocturne: Blue and Gold – Old Battersea Bridge),创作于1872年至1875年间。它是惠斯勒“夜曲”系列的一部分,代表了他对色彩与氛围的独特探索。以下是对该作品的详细解读与欣赏方法:


      画面构成与视觉印象

      这幅画以伦敦泰晤士河上的巴特西桥为主题,桥梁的结构占据画面中央,远处是城市和河流的朦胧景象。整体色调以蓝色为主,带有金色点缀,营造出夜间静谧的氛围。桥下的河面上反射着微弱的光芒,一个孤独的身影在桥下走过,增强了画面的诗意感。


      艺术特点

      1. 色彩与光影的表现

      • 惠斯勒采用极简的调色板,画面以蓝色为主调,象征夜晚的静谧与深邃。点缀的金色光芒可能是星光或远处灯光的倒影,打破了单一色调的沉寂。
      • 这种微妙的色彩对比让画面充满张力,但又极为柔和,给予观众一种沉思的氛围。

      2. 构图与空间感

      • 巴特西桥的结构占据画面中心,形成一个视觉焦点,桥的高大垂直线条将观众的目光引向画面的深处。
      • 背景中的建筑和远处的景象被处理得极为简化,只留下朦胧的轮廓,增强了画面的广阔感与神秘感。

      3. 夜曲风格的运用

      • “夜曲”系列作品受音乐启发,注重情绪与氛围的表达。惠斯勒将绘画比作音乐,将作品视为色彩与形式的和谐交响,强调画面氛围胜过叙事内容。

      主题与内涵

      1. 对氛围的捕捉

      • 这幅画的主题是夜晚的宁静与朦胧之美,而非具体事件或叙事。观众在欣赏时,可以感受到夜晚独有的寂静与思考空间。
      • 惠斯勒通过色彩和构图唤起观众的情感共鸣,让人沉浸在画面的氛围之中。

      2. 都市与自然的对话

      • 巴特西桥不仅是画面的主体,也象征了工业革命后伦敦城市化的象征。惠斯勒用一种浪漫的方式捕捉了城市景观与自然之间的微妙平衡。

      3. 孤独与诗意

      • 画面中单独的身影增强了孤独感,与夜晚的宁静形成呼应。这种孤独既是个人的情感体验,也是一种对人类存在状态的思考。

      艺术背景与现代意义

      1. 对印象主义的影响

      • 惠斯勒与法国印象派画家几乎同时发展出对光线与氛围的兴趣,但他更加强调画面的抽象性与形式美感。可以说,他是介于浪漫主义与印象派之间的过渡性人物。
      • 他的夜曲系列作品对后来的抽象艺术家也产生了深远影响,尤其是对色彩与情绪的探索。

      2. 艺术理念:为艺术而艺术

      • 惠斯勒的“为艺术而艺术”理念在这幅作品中体现得淋漓尽致。他认为绘画不一定需要叙事内容,而应通过色彩和形式创造美的体验。

      欣赏方法

      1. 感受色彩与情绪
      2. 放慢视觉节奏,仔细感受蓝色调带来的冷静与思考,以及金色点缀提供的微弱温暖。色彩之间的对比是作品的核心之一。

      3. 观察光影效果

      4. 注意画面中光线的来源与分布,特别是桥下倒影与背景远处模糊的光点,这些光影为画面注入了生命力。

      5. 体验画面的氛围

      6. 不需要去寻找具体的“故事”,而是单纯沉浸在画面传递的情绪中,体会夜晚的诗意与安静。

      7. 思考人与自然的关系

      8. 桥梁、河流、城市与孤独的身影共同构成了画面,观众可以思考这些元素在工业化背景下如何传递自然与人造世界的对立与融合。

      总结

      《夜曲:蓝与金——旧桥》是惠斯勒艺术哲学的完美体现,它通过简约的构图和柔和的色彩处理,呈现出夜晚的宁静与深邃。欣赏这幅画时,不必关注细节的清晰度或叙事意义,而应专注于画面营造的情感氛围与色彩之间的微妙对话。这种纯粹的美学体验正是惠斯勒艺术的核心魅力。

    3. chatgpt欣赏

      这幅画是詹姆斯·阿博特·麦克尼尔·惠斯勒(James Abbott McNeill Whistler)的著名作品《白衣少女》(Symphony in White, No. 1: The White Girl),创作于1862年。这幅作品以其独特的美学理念和艺术处理方式成为了19世纪绘画史上的经典之作。以下是对其艺术特点与欣赏方式的解读:


      画面构成

      这幅画描绘了一位身穿白色长裙的红发女性站在画面中央,她的背景是简单的白色窗帘,脚下是带有狼皮和花朵的地毯。整幅画以白色为主调,通过细腻的层次变化传递出一种内敛的美感。


      艺术特点

      1. 以色彩为主题

      • 画作的标题特别提到“交响曲”(Symphony),这是惠斯勒的一种艺术理念:他将绘画视为与音乐类似的艺术形式,强调色彩和形式的和谐性。
      • 白色是画作的主色调,但画家巧妙地通过不同的白色调子和质感变化(如长裙的褶皱、窗帘的纹理)创造了丰富的视觉效果。

      2. 形式与简约美学

      • 画作的整体设计偏向极简,背景没有繁杂的细节,突出了人物的形象。
      • 这种“形式优先”的理念是惠斯勒的一大特点,他认为绘画的本质是形式和色彩,而不一定要讲述故事。

      3. 构图与人物姿态

      • 女性的姿态是静止而优雅的,既不是传统的肖像风格,也没有明显的叙事暗示。
      • 她手持一朵白色花朵,既象征纯洁,又可能传递某种微妙的情感或氛围。

      主题与内涵

      1. 纯粹形式的追求

      • 惠斯勒曾强调,这幅画不是为了表达某种叙事或寓意,而是对色彩和形式的探索。观众可以单纯地从白色的层次变化中感受到“美”的存在。
      • 这也是惠斯勒的绘画风格与传统叙事绘画的分野所在。

      2. 女性形象的象征性

      • 画中女子被认为代表了一种理想化的美与纯洁。她没有具体的身份或情感表达,而是被作为“艺术的主题”来表现。
      • 这种处理方式让她的形象具有一种永恒性,摆脱了世俗意义上的约束。

      3. 浪漫主义与象征主义的结合

      • 画中人物的静态美与背景的简洁处理,结合狼皮和花朵等细节,可能隐含了某种浪漫主义或象征主义的思考。
      • 狼皮象征野性与危险,而花朵则象征生命的脆弱,两者的对比可能暗示了人性中的对立元素。

      背景与艺术影响

      1. 对学院派的挑战

      • 在惠斯勒创作《白衣少女》的年代,学院派艺术仍占据主导地位,注重历史、宗教或神话题材的叙事性绘画。
      • 惠斯勒的作品则完全摆脱了叙事功能,成为一种“为艺术而艺术”的实验,直接挑战了传统艺术观念。

      2. 影响后世的现代主义

      • 这幅画被认为是现代主义绘画的先驱之一。惠斯勒的色彩观念和形式美学启发了后来的抽象艺术家,如蒙德里安和康定斯基。

      欣赏方法

      1. 观察色彩层次
      2. 注意画中白色的多样性:服装的布料、背景的窗帘、地毯上的纹理,每一种白色都有细微的差异。
      3. 思考这些不同白色如何塑造了画面的整体和谐感。

      4. 感受形式的和谐

      5. 画作虽然简单,但整体构图极为平衡:人物的位置、姿态与背景形成了一种内在的节奏感。

      6. 关注象征细节

      7. 女子的红发、手中的白花以及脚下的狼皮,都是画中不多的点缀元素,它们可能蕴含了某种对比性隐喻,值得细细品味。

      8. 体验画作氛围

      9. 尝试抛开“故事”或“寓意”的思考,单纯从视觉感官上感受这幅画带来的宁静、优雅与微妙情感。

      总结

      惠斯勒的《白衣少女》是一幅超越时代的作品,它通过简约的构图和细腻的色彩处理,展现了“为艺术而艺术”的理念。欣赏这幅画时,不必执着于寻找叙事或象征意义,而应专注于感受画面中形式与色彩的美学和谐,以及由此而生的独特艺术魅力。

    1. A1 初級文法Search:內容分類建議順序初級文法 10介詞:à / de + 城市和國家介詞1初級文法 11介詞:上下前後內介詞2初級文法 12介詞:離...很近 / 很遠 près de, loin de介詞3初級文法 26表示存在:il y a表達:空間4初級文法 13疑問形式:qui, que, c'est vs il est問答5初級文法 14c'est 和 il est 的分別問答6初級文法 17部分冠詞 - du, de la, des限定詞7初級文法 27比較級表達:比較8初級文法 28最高級表達:比較9初級文法 01第二組 -ir 動詞變位規則動詞10初級文法 02不規則動詞變位動詞11初級文法 03動詞 faire & jouer:活動與嗜好動詞12初級文法 04動詞 aller 與地方動詞13初級文法 05最近將來時 futur proche:aller + 不定式動詞14初級文法 06複合過去時 passé composé動詞15初級文法 07未完成過去時 imparfait動詞16初級文法 08複合過去時 vs 未完成過去時動詞17初級文法 09簡單將來時 futur simple動詞18初級文法 25基本時間標誌介詞:depuis, pendant, il y a...表達:時間19初級文法 15基本疑問詞問答20初級文法 16三種疑問句形式:雅語、日常語言、通俗語言問答21初級文法 18法文直接受詞 COD vs 間接受詞 COI總論22初級文法 19直接受詞代名詞 pronom COD:le, la, les...代詞23初級文法 20間接受詞代名詞 pronom COI:lui, leur代詞24初級文法 21代詞 en代詞25初級文法 22代詞 y代詞26初級文法 23重讀人稱代詞 pronom tonique:moi, toi, lui...代詞27初級文法 24關係代詞 pronom relatif:qui, que代詞28Showing 1 to 28 of 28 entries

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      A1 初級文法 Search: 內容 分類 建議順序 初級文法 10 介詞:à / de + 城市和國家 介詞 1 初級文法 11 介詞:上下前後內 介詞 2 初級文法 12 介詞:離...很近 / 很遠 près de, loin de 介詞 3 初級文法 26 表示存在:il y a 表達:空間 4 初級文法 13 疑問形式:qui, que, c'est vs il est 問答 5 初級文法 14 c'est 和 il est 的分別 問答 6 初級文法 17 部分冠詞 - du, de la, des 限定詞 7 初級文法 27 比較級 表達:比較 8 初級文法 28 最高級 表達:比較 9 初級文法 01 第二組 -ir 動詞變位規則 動詞 10 初級文法 02 不規則動詞變位 動詞 11 初級文法 03 動詞 faire & jouer:活動與嗜好 動詞 12 初級文法 04 動詞 aller 與地方 動詞 13 初級文法 05 最近將來時 futur proche:aller + 不定式 動詞 14 初級文法 06 複合過去時 passé composé 動詞 15 初級文法 07 未完成過去時 imparfait 動詞 16 初級文法 08 複合過去時 vs 未完成過去時 動詞 17 初級文法 09 簡單將來時 futur simple 動詞 18 初級文法 25 基本時間標誌介詞:depuis, pendant, il y a... 表達:時間 19 初級文法 15 基本疑問詞 問答 20 初級文法 16 三種疑問句形式:雅語、日常語言、通俗語言 問答 21 初級文法 18 法文直接受詞 COD vs 間接受詞 COI 總論 22 初級文法 19 直接受詞代名詞 pronom COD:le, la, les... 代詞 23 初級文法 20 間接受詞代名詞 pronom COI:lui, leur 代詞 24 初級文法 21 代詞 en 代詞 25 初級文法 22 代詞 y 代詞 26 初級文法 23 重讀人稱代詞 pronom tonique:moi, toi, lui... 代詞 27 初級文法 24 關係代詞 pronom relatif:qui, que 代詞 28 Showing 1 to 28 of 28 entries

    1. A2 初中級文法Search:內容分類建議順序初中級文法 08形容詞概論形容詞1初中級文法 12泛指詞 indéfinis代詞 / 限定詞2初中級文法 17基本時間空間表達補遺表達:時間、空間3初中級文法 09副詞概論副詞4初中級文法 11代名詞的順序代詞6初中級文法 01代詞式動詞的四種意義動詞7初中級文法 02命令式 impératif動詞9初中級文法 13關係代詞 pronom relatif:où, dont代詞9初中級文法 03條件式 conditionnel動詞10初中級文法 14關係代詞:ce qui, ce que, ce dont代詞10初中級文法 15複合關係代詞:auquel, duquel, pour lequel...代詞11初中級文法 10ne...pas 外的否定形式否定12初中級文法 16間接引語表達:引語13初中級文法 04過去分詞、現在分詞和副動詞 gérondif動詞14初中級文法 05被動語態動詞15初中級文法 06愈過去時 plus-que-parfait 和先將來時 futur anterieur動詞16初中級文法 18三種條件句表達:假設17初中級文法 07虛擬式 subjontif動詞18初中級文法 19邏輯關係表達:邏輯19Showing 1 to 19 of 19 entries

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    1. Author response:

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

      The revised manuscript contains new results and additional text. Major revisions:

      (1) Additional simulations and analyses of networks with different biophysical parameters and with identical time constants for E and I neurons (Methods, Supplementary Fig. 5).

      (2) Additional simulations and analyses of networks with modifications of connectivity parameters to further analyze effects of E/I assemblies on manifold geometry (Supplementary Fig. 6).

      (3) Analysis of synaptic current components (Figure 3 D-F; to analyze mechanism of modest amplification in Tuned networks). 

      (4) More detailed explanation of pattern completion analysis (Results).

      (5) Analysis of classification performance of Scaled networks (Supplementary Fig.8).

      (6) Additional analysis (Figure 5D-F) and discussion (particularly section “Computational functions of networks with E/I assemblies”) of functional benefits of continuous representations in networks with E-I assemblies. 

      Public Reviews: 

      Reviewer #1 (Public Review): 

      Summary: 

      Meissner-Bernard et al present a biologically constrained model of telencephalic area of adult zebrafish, a homologous area to the piriform cortex, and argue for the role of precisely balanced memory networks in olfactory processing. 

      This is interesting as it can add to recent evidence on the presence of functional subnetworks in multiple sensory cortices. It is also important in deviating from traditional accounts of memory systems as attractor networks. Evidence for attractor networks has been found in some systems, like in the head direction circuits in the flies. However, the presence of attractor dynamics in other modalities, like sensory systems, and their role in computation has been more contentious. This work contributes to this active line of research in experimental and computational neuroscience by suggesting that, rather than being represented in attractor networks and persistent activity, olfactory memories might be coded by balanced excitation-inhibitory subnetworks. 

      Strengths: 

      The main strength of the work is in: (1) direct link to biological parameters and measurements, (2) good controls and quantification of the results, and (3) comparison across multiple models. 

      (1) The authors have done a good job of gathering the current experimental information to inform a biological-constrained spiking model of the telencephalic area of adult zebrafish. The results are compared to previous experimental measurements to choose the right regimes of operation. 

      (2) Multiple quantification metrics and controls are used to support the main conclusions and to ensure that the key parameters are controlled for - e.g. when comparing across multiple models.  (3) Four specific models (random, scaled I / attractor, and two variant of specific E-I networks - tuned I and tuned E+I) are compared with different metrics, helping to pinpoint which features emerge in which model. 

      Weaknesses: 

      Major problems with the work are: (1) mechanistic explanation of the results in specific E-I networks, (2) parameter exploration, and (3) the functional significance of the specific E-I model. 

      (1) The main problem with the paper is a lack of mechanistic analysis of the models. The models are treated like biological entities and only tested with different assays and metrics to describe their different features (e.g. different geometry of representation in Fig. 4). Given that all the key parameters of the models are known and can be changed (unlike biological networks), it is expected to provide a more analytical account of why specific networks show the reported results. For instance, what is the key mechanism for medium amplification in specific E/I network models (Fig. 3)? How does the specific geometry of representation/manifolds (in Fig. 4) emerge in terms of excitatory-inhibitory interactions, and what are the main mechanisms/parameters? Mechanistic account and analysis of these results are missing in the current version of the paper. 

      We agree that further mechanistic insights would be of interest and addressed this issue at different levels:

      (1) Biophysical parameters: to determine whether network behavior depends on specific choices of biophysical parameters in E and I neurons we equalized biophysical parameters across neuron types. The main observations are unchanged, suggesting that the observed effects depend primarily on network connectivity (see also response to comment [2]).

      (2) Mechanism of modest amplification in E/I assemblies: analyzing the different components of the synaptic currents demonstrate that the modest amplification of activity in Tuned networks results from an “imperfect” balance of recurrent excitation and inhibition within assemblies (see new Figures 3D-F and text p.7). Hence, E/I co-tuning substantially reduces the net amplification in Tuned networks as compared to Scaled networks, thus preventing discrete attractor dynamics and stabilizing network activity, but a modest amplification still occurs, consistent with biological observations.

      (3) Representational geometry: to obtain insights into the network mechanisms underlying effects of E/I assemblies on the geometry of population activity we tested the hypothesis that geometrical changes depend, at least in part, on the modest amplification of activity within E/I assemblies (see Supplementary Figure 6). We changed model parameters to either prevent the modest amplification in Tuned networks (increasing I-to-E connectivity within assemblies) or introduce a modest amplification in subsets of neurons by other mechanisms (concentration-dependent increase in the excitability of pseudo-assembly neurons; Scaled I networks with reduced connectivity within assemblies). Manipulations that introduced a modest, input-dependent amplification in neuronal subsets had geometrical effects similar to those observed in Tuned networks, whereas manipulations that prevented a modest amplification abolished these effects (Supplementary Figure 6). Note however that these manipulations generated different firing rate distributions. These results provide a starting point for more detailed analyses of the relationship between network connectivity and representational geometry (see p.12).

      In summary, our additional analyses indicate that effects of E/I assemblies on representational geometry depend primarily on network connectivity, rather than specific biophysical parameters, and that the resulting modest amplification of activity within assemblies makes an important contribution. Further analyses may reveal more specific relationships between E/I assemblies and representational geometry, but such analyses are beyond the scope of this study.

      (2) The second major issue with the study is a lack of systematic exploration and analysis of the parameter space. Some parameters are biologically constrained, but not all the parameters. For instance, it is not clear what the justification for the choice of synaptic time scales are (with E synaptic time constants being larger than inhibition: tau_syn_i = 10 ms, tau_syn_E = 30 ms). How would the results change if they are varying these - and other unconstrained - parameters? It is important to show how the main results, especially the manifold localisation, would change by doing a systematic exploration of the key parameters and performing some sensitivity analysis. This would also help to see how robust the results are, which parameters are more important and which parameters are less relevant, and to shed light on the key mechanisms.  

      We thank the reviewer for raising this point. We chose a relatively slow time constant for excitatory synapses because experimental data indicate that excitatory synaptic currents in Dp and piriform cortex contain a prominent NMDA component. Nevertheless, to assess whether network behavior depends on specific choices of biophysical parameters in E and I neurons, we have performed additional simulations with equal synaptic time constants and equal biophysical parameters for all neurons. Each neuron also received the same number of inputs from each population (see revised Methods). Results were similar to those observed previously (Supplementary Fig.5 and p.9 of main text). We therefore conclude that the main effects observed in Tuned networks cannot be explained by differences in biophysical parameters between E and I neurons but is primarily a consequence of network connectivity.

      (3) It is not clear what the main functional advantage of the specific E-I network model is compared to random networks. In terms of activity, they show that specific E-I networks amplify the input more than random networks (Fig. 3). But when it comes to classification, the effect seems to be very small (Fig. 5c). Description of different geometry of representation and manifold localization in specific networks compared to random networks is good, but it is more of an illustration of different activity patterns than proving a functional benefit for the network. The reader is still left with the question of what major functional benefits (in terms of computational/biological processing) should be expected from these networks, if they are to be a good model for olfactory processing and learning. 

      One possibility for instance might be that the tasks used here are too easy to reveal the main benefits of the specific models - and more complex tasks would be needed to assess the functional enhancement (e.g. more noisy conditions or more combination of odours). It would be good to show this more clearly - or at least discuss it in relation to computation and function. 

      In the previous manuscript, the analysis of potential computational benefits other than pattern classification was limited and the discussion of this issue was condensed into a single itemized paragraph to avoid excessive speculation. Although a thorough analysis of potential computational benefits exceeds the scope of a single paper, we agree with the reviewer that this issue is of interest and therefore added additional analyses and discussion.

      In the initial manuscript we analyzed pattern classification primarily to investigate whether Tuned networks can support this function at all, given that they do not exhibit discrete attractor states. We found this to be the case, which we consider a first important result.

      Furthermore, we found that precise balance of E/I assemblies can protect networks against catastrophic firing rate instabilities when assemblies are added sequentially, as in continual learning. Results from these simulations are now described and discussed in more detail (see Results p.11 and Discussion p.13).

      In the revised manuscript, we now also examine additional potential benefits of Tuned networks and discuss them in more detail (see new Figure 5D-F and text p.11). One hypothesis is that continuous representations provide a distance metric between a given input and relevant (learned) stimuli. To address this hypothesis, we (1) performed regression analysis and (2) trained support vector machines (SVMs) to predict the concentration of a given odor in a mixture based on population activity. In both cases, Tuned E+I networks outperformed Scaled and _rand n_etworks in predicting the concentration of learned odors across a wide range mixtures (Figure 5D-F).  E/I assemblies therefore support the quantification of learned odors within mixtures or, more generally, assessments of how strongly a (potentially complex) input is related to relevant odors stored in memory. Such a metric assessment of stimulus quality is not well supported by discrete attractor networks because inputs are mapped onto discrete network states.

      The observation that Tuned networks do not map inputs onto discrete outputs indicates that such networks do not classify inputs as distinct items. Nonetheless, the observed geometrical modifications of continuous representations support the classification of learned inputs or the assessment of metric relationships by hypothetical readout neurons. Geometrical modifications of odor representations may therefore serve as one of multiple steps in multi-layer computations for pattern classification (and/or other computations). In this scenario, the transformation of odor representations in Dp may be seen as related to transformations of representations between different layers in artificial networks, which collectively perform a given task (notwithstanding obvious structural and mechanistic differences between artificial and biological networks). In other words, geometrical transformations of representations in Tuned networks may overrepresent learned (relevant) information at the expense of other information and thereby support further learning processes in other brain areas. An obvious corollary of this scenario is that Dp does not perform odor classification per se based on inputs from the olfactory bulb but reformats representations of odor space based on experience to support computational tasks as part of a larger system. This scenario is now explicitly discussed (p.14).

      Reviewer #2 (Public Review): 

      Summary: 

      The authors conducted a comparative analysis of four networks, varying in the presence of excitatory assemblies and the architecture of inhibitory cell assembly connectivity. They found that co-tuned E-I assemblies provide network stability and a continuous representation of input patterns (on locally constrained manifolds), contrasting with networks with global inhibition that result in attractor networks. 

      Strengths: 

      The findings presented in this paper are very interesting and cutting-edge. The manuscript effectively conveys the message and presents a creative way to represent high-dimensional inputs and network responses. Particularly, the result regarding the projection of input patterns onto local manifolds and continuous representation of input/memory is very Intriguing and novel. Both computational and experimental neuroscientists would find value in reading the paper. 

      Weaknesses: 

      that have continuous representations. This could also be shown in Figure 5B, along with the performance of the random and tuned E-I networks. The latter networks have the advantage of providing network stability compared to the Scaled I network, but at the cost of reduced network salience and, therefore, reduced input decodability. The authors may consider designing a decoder to quantify and compare the classification performance of all four networks. 

      We have now quantified classification by networks with discrete attractor dynamics (Scaled) along with other networks. However, because the neuronal covariance matrix for such networks is low rank and not invertible, pattern classification cannot be analyzed by QDA as in Figure 5B. We therefore classified patterns from the odor subspace by template matching, assigning test patterns to one of the four classes based on correlations (see Supplementary Figure 8). As expected, Scaled networks performed well, but they did not outperform Tuned networks. Moreover, the performance of Scaled networks, but not Tuned networks, depended on the order in which odors were presented to the network. This hysteresis effect is a direct consequence of persistent attractor states and decreased the general classification performance of Scaled networks (see Supplementary Figure 8 for details). These results confirm the prediction that networks with discrete attractor states can efficiently classify inputs, but also reveal disadvantages arising from attractor dynamics. Moreover, the results indicate that the classification performance of Tuned networks is also high under the given task conditions, which simulate a biologically realistic scenario.

      We would also like to emphasize that classification may not be the only task, and perhaps not even a main task, of Dp/piriform cortex or other memory networks with E/I assemblies. Conceivably, other computations could include metric assessments of inputs relative to learned inputs or additional learning-related computations. Please see our response to comment (3) of reviewer 1 for a further discussion of this issue. 

      Networks featuring E/I assemblies could potentially represent multistable attractors by exploring the parameter space for their reciprocal connectivity and connectivity with the rest of the network. However, for co-tuned E-I networks, the scope for achieving multistability is relatively constrained compared to networks employing global or lateral inhibition between assemblies. It would be good if the authors mentioned this in the discussion. Also, the fact that reciprocal inhibition increases network stability has been shown before and should be cited in the statements addressing network stability (e.g., some of the citations in the manuscript, including Rost et al. 2018, Lagzi & Fairhall 2022, and Vogels et al. 2011 have shown this).  

      We thank the reviewer for this comment. We now explicitly discuss multistability (see p. 12) and refer to additional references in the statements addressing network stability.

      Providing raster plots of the pDp network for familiar and novel inputs would help with understanding the claims regarding continuous versus discrete representation of inputs, allowing readers to visualize the activity patterns of the four different networks. (similar to Figure 1B). 

      We thank the reviewer for this suggestion. We have added raster plots of responses to both familiar and novel inputs in the revised manuscript (Figure 2D and Supplementary Figure 4A).

      Reviewer #3 (Public Review): 

      Summary: 

      This work investigates the computational consequences of assemblies containing both excitatory and inhibitory neurons (E/I assembly) in a model with parameters constrained by experimental data from the telencephalic area Dp of zebrafish. The authors show how this precise E/I balance shapes the geometry of neuronal dynamics in comparison to unstructured networks and networks with more global inhibitory balance. Specifically, E/I assemblies lead to the activity being locally restricted onto manifolds - a dynamical structure in between high-dimensional representations in unstructured networks and discrete attractors in networks with global inhibitory balance. Furthermore, E/I assemblies lead to smoother representations of mixtures of stimuli while those stimuli can still be reliably classified, and allow for more robust learning of additional stimuli. 

      Strengths: 

      Since experimental studies do suggest that E/I balance is very precise and E/I assemblies exist, it is important to study the consequences of those connectivity structures on network dynamics. The authors convincingly show that E/I assemblies lead to different geometries of stimulus representation compared to unstructured networks and networks with global inhibition. This finding might open the door for future studies for exploring the functional advantage of these locally defined manifolds, and how other network properties allow to shape those manifolds. 

      The authors also make sure that their spiking model is well-constrained by experimental data from the zebrafish pDp. Both spontaneous and odor stimulus triggered spiking activity is within the range of experimental measurements. But the model is also general enough to be potentially applied to findings in other animal models and brain regions. 

      Weaknesses: 

      I find the point about pattern completion a bit confusing. In Fig. 3 the authors argue that only the Scaled I network can lead to pattern completion for morphed inputs since the output correlations are higher than the input correlations. For me, this sounds less like the network can perform pattern completion but it can nonlinearly increase the output correlations. Furthermore, in Suppl. Fig. 3 the authors show that activating half the assembly does lead to pattern completion in the sense that also non-activated assembly cells become highly active and that this pattern completion can be seen for Scaled I, Tuned E+I, and Tuned I networks. These two results seem a bit contradictory to me and require further clarification, and the authors might want to clarify how exactly they define pattern completion. 

      We believe that this comment concerns a semantic misunderstanding and apologize for any lack of clarity. We added a definition of pattern completion in the text: “…the retrieval of the whole memory from noisy or corrupted versions of the learned input.”. Pattern completion may be assessed using different procedures. In computational studies, it is often analyzed by delivering input to a subset of the assembly neurons which store a given memory (partial activation). Under these conditions, we find recruitment of the entire assembly in all structured networks, as demonstrated in Supplementary Figure 3. However, these conditions are unlikely to occur during odor presentation because the majority of neurons do not receive any input.

      Another more biologically motivated approach to assess pattern completion is to gradually modify a realistic odor input into a learned input, thereby gradually increasing the overlap between the two inputs. This approach had been used previously in experimental studies (references added to the text p.6). In the presence of assemblies, recurrent connectivity is expected to recruit assembly neurons (and thus retrieve the stored pattern) more efficiently as the learned pattern is approached. This should result in a nonlinear increase in the similarity between the evoked and the learned activity pattern. This signature was prominent in Scaled networks but not in Tuned or rand networks. Obviously, the underlying procedure is different from the partial activation of the assembly described above because input patterns target many neurons (including neurons outside assemblies) and exhibit a biologically realistic distribution of activity. However, this approach has also been referred to as “pattern completion” in the neuroscience literature, which may be the source of semantic confusion here. To clarify the difference between these approaches we have now revised the text and explicitly described each procedure in more detail (see p.6). 

      The authors argue that Tuned E+I networks have several advantages over Scaled I networks. While I agree with the authors that in some cases adding this localized E/I balance is beneficial, I believe that a more rigorous comparison between Tuned E+I networks and Scaled I networks is needed: quantification of variance (Fig. 4G) and angle distributions (Fig. 4H) should also be shown for the Scaled I network. Similarly in Fig. 5, what is the Mahalanobis distance for Scaled I networks and how well can the Scaled I network be classified compared to the Tuned E+I network? I suspect that the Scaled I network will actually be better at classifying odors compared to the E+I network. The authors might want to speculate about the benefit of having networks with both sources of inhibition (local and global) and hence being able to switch between locally defined manifolds and discrete attractor states. 

      We agree that a more rigorous comparison of Tuned and Scaled networks would be of interest. We have added the variance analysis (Fig 4G) and angle distributions (Fig. 4H) for both Tuned I and Scaled networks. However, the Mahalanobis distances and Quadratic Discriminant Analysis cannot be applied to Scaled networks because their neuronal covariance matrix is low rank and not invertible_. To nevertheless compare these networks, we performed template matching by assigning test patterns to one of the four odor classes based on correlations to template patterns (Supplementary Figure 8; see also response to the first comment of reviewer 2). Interestingly, _Scaled networks performed well at classification but did not outperform Tuned networks, and exhibited disadvantages arising from attractor dynamics (Supplementary Figure 8; see also response to the first comment of reviewer 2). Furthermore, in further analyses we found that continuous representational manifolds support metric assessments of inputs relative to learned odors, which cannot be achieved by discrete representations. These results are now shown in Figure 5D-E and discussed explicitly in the text on p.11 (see also response to comment 3 of reviewer 1).

      We preferred not to add a sentence in the Discussion about benefits of networks having both sources of inhibition_,_ as we find this a bit too speculative.

      At a few points in the manuscript, the authors use statements without actually providing evidence in terms of a Figure. Often the authors themselves acknowledge this, by adding the term "not shown" to the end of the sentence. I believe it will be helpful to the reader to be provided with figures or panels in support of the statements.  

      Thank you for this comment. We have provided additional data figures to support the following statements:

      “d<sub>M</sub> was again increased upon learning, particularly between learned odors and reference classes representing other odors (Supplementary Figure 9)”

      “decreasing amplification in assemblies of Scaled networks changed transformations towards the intermediate behavior, albeit with broader firing rate distributions than in Tuned networks (Supplementary Figure 6 B)”  

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors): 

      Meissner-Bernard et al present a biologically constrained model of telencephalic area of adult zebrafish, a homologous area to the piriform cortex, and argue for the role of precisely balanced memory networks in olfactory processing. 

      This is interesting as it can add to recent evidence on the presence of functional subnetworks in multiple sensory cortices. It is also important in deviating from traditional accounts of memory systems as attractor networks. Evidence for attractor networks has been found in some systems, like in the head direction circuits in the flies. However, the presence of attractor dynamics in other modalities, like sensory systems, and their role in computation has been more contentious. This work contributes to this active line of research in experimental and computational neuroscience by suggesting that, rather than being represented in attractor networks and persistent activity, olfactory memories might be coded by balanced excitation-inhibitory subnetworks. 

      The paper is generally well-written, the figures are informative and of good quality, and multiple approaches and metrics have been used to test and support the main results of the paper. 

      The main strength of the work is in: (1) direct link to biological parameters and measurements, (2) good controls and quantification of the results, and (3) comparison across multiple models. 

      (1) The authors have done a good job of gathering the current experimental information to inform a biological-constrained spiking model of the telencephalic area of adult zebrafish. The results are compared to previous experimental measurements to choose the right regimes of operation. 

      (2) Multiple quantification metrics and controls are used to support the main conclusions and to ensure that the key parameters are controlled for - e.g. when comparing across multiple models.   (3) Four specific models (random, scaled I / attractor, and two variant of specific E-I networks - tuned I and tuned E+I) are compared with different metrics, helping to pinpoint which features emerge in which model. 

      Major problems with the work are: (1) mechanistic explanation of the results in specific E-I networks, (2) parameter exploration, and (3) the functional significance of the specific E-I model. 

      (1) The main problem with the paper is a lack of mechanistic analysis of the models. The models are treated like biological entities and only tested with different assays and metrics to describe their different features (e.g. different geometry of representation in Fig. 4). Given that all the key parameters of the models are known and can be changed (unlike biological networks), it is expected to provide a more analytical account of why specific networks show the reported results. For instance, what is the key mechanism for medium amplification in specific E/I network models (Fig. 3)? How does the specific geometry of representation/manifolds (in Fig. 4) emerge in terms of excitatory-inhibitory interactions, and what are the main mechanisms/parameters? Mechanistic account and analysis of these results are missing in the current version of the paper. 

      Precise balancing of excitation and inhibition in subnetworks would lead to the cancellation of specific dynamical modes responsible for the amplification of responses (hence, deviating from the attractor dynamics with an unstable specific mode). What is the key difference in the specific E/I networks here (tuned I or/and tuned E+I) which make them stand between random and attractor networks? Excitatory and inhibitory neurons have different parameters in the model (Table 1). Time constants of inhibitory and excitatory synapses are also different (P. 13). Are these parameters causing networks to be effectively more excitation dominated (hence deviating from a random spectrum which would be expected from a precisely balanced E/I network, with exactly the same parameters of E and I neurons)? It is necessary to analyse the network models, describe the key mechanism for their amplification, and pinpoint the key differences between E and I neurons which are crucial for this. 

      To address these comments we performed additional simulations and analyses at different levels. Please see our reply to comment (1) of the public review (reviewer 1) for a detailed description. We thank the reviewer for these constructive comments.

      (2) The second major issue with the study is a lack of systematic exploration and analysis of the parameter space. Some parameters are biologically constrained, but not all the parameters. For instance, it is not clear what the justification for the choice of synaptic time scales are (with E synaptic time constants being larger than inhibition: tau_syn_i = 10 ms, tau_syn_E = 30 ms). How would the results change if they are varying these - and other unconstrained - parameters? It is important to show how the main results, especially the manifold localisation, would change by doing a systematic exploration of the key parameters and performing some sensitivity analysis. This would also help to see how robust the results are, which parameters are more important and which parameters are less relevant, and to shed light on the key mechanisms.  

      We thank the reviewer for this comment. We have now carried out additional simulations with equal time constants for all neurons. Please see our reply to the public review for more details (comment 2 of reviewer 1).

      (3) It is not clear what the main functional advantage of the specific E-I network model is compared to random networks. In terms of activity, they show that specific E-I networks amplify the input more than random networks (Fig. 3). But when it comes to classification, the effect seems to be very small (Fig. 5c). Description of different geometry of representation and manifold localization in specific networks compared to random networks is good, but it is more of an illustration of different activity patterns than proving a functional benefit for the network. The reader is still left with the question of what major functional benefits (in terms of computational/biological processing) should be expected from these networks, if they are to be a good model for olfactory processing and learning. 

      One possibility for instance might be that the tasks used here are too easy to reveal the main benefits of the specific models - and more complex tasks would be needed to assess the functional enhancement (e.g. more noisy conditions or more combination of odours). It would be good to show this more clearly - or at least discuss it in relation to computation and function.

      Please see our reply to the public review (comment 3 of reviewer 1).

      Specific comments: 

      Abstract: "resulting in continuous representations that reflected both relatedness of inputs and *an individual's experience*" 

      It didn't become apparent from the text or the model where the role of "individual's experience" component (or "internal representations" - in the next line) was introduced or shown (apart from a couple of lines in the Discussion) 

      We consider the scenario that that assemblies are the outcome of an experience-dependent plasticity process. To clarify this, we have now made a small addition to the text: “Biological memory networks are thought to store information by experience-dependent changes in the synaptic connectivity between assemblies of neurons.”.

      P. 2: "The resulting state of "precise" synaptic balance stabilizes firing rates because inhomogeneities or fluctuations in excitation are tracked by correlated inhibition" 

      It is not clear what the "inhomogeneities" specifically refers to - they can be temporal, or they can refer to the quenched noise of connectivity, for instance. Please clarify what you mean. 

      The statement has been modified to be more precise: “…“precise” synaptic balance stabilizes firing rates because inhomogeneities in excitation across the population or temporal variations in excitation are tracked by correlated inhibition…”.

      P. 3 (and Methods): When odour stimulus is simulated in the OB, the activity of a fraction of mitral cells is increased (10% to 15 Hz) - but also a fraction of mitral cells is suppressed (5% to 2 Hz). What is the biological motivation or reference for this? It is not provided. Is it needed for the results? Also, it is not explained how the suppressed 5% are chosen (e.g. randomly, without any relation to the increased cells?). 

      We thank the reviewer for this comment. These changes in activity directly reflect experimental observations. We apologize that we forgot to include the references reporting these observations (Friedrich and Laurent, 2001 and 2004); this is now fixed.

      In our simulation, OB neurons do not interact with each other, and the suppressed 5% were indeed randomly selected. We changed the text in Methods accordingly to read: “An additional 75 randomly selected mitral cells were inhibited” 

      P. 4, L. 1-2: "... sparsely connected integrate-and-fire neurons with conductance-based synapses (connection probability {less than or equal to}5%)." 

      Specify the connection probability of specific subtypes (EE, EI, IE, II).  

      We now refer to the Methods section, where this information can be found. 

      “... conductance-based synapses (connection probability ≤5%, Methods)”  

      P. 4, L. 6-7: "Population activity was odor-specific and activity patterns evoked by uncorrelated OB inputs remained uncorrelated in Dp (Figure 1H)" 

      What would happen to correlated OB inputs (e.g. as a result of mixture of two overlapping odours) in this baseline state of the network (before memories being introduced to it)? It would be good to know this, as it sheds light on the initial operating regime of the network in terms of E/I balance and decorrelation of inputs.  

      This information was present in the original manuscript at (Figure 3) but we improved the writing to further clarify this issue: “ (…) we morphed a novel odor into a learned odor (Figure 3A), or a learned odor into another learned odor (Supplementary Figure 3B), and quantified the similarity between morphed and learned odors by the Pearson correlation of the OB activity patterns (input correlation). We then compared input correlations to the corresponding pattern correlations among E neurons in Dp (output correlation). In rand networks, output correlations increased linearly with input correlations but did not exceed them (Figure 3B and Supplementary Figure 3B)”

      P. 4, L. 12-13: "Shuffling spike times of inhibitory neurons resulted in runaway activity with a probability of ~80%, .."   Where is this shown? 

      (There are other occasions too in the paper where references to the supporting figures are missing). 

      We now provide the statistics: “Shuffling spike times of inhibitory neurons resulted in runaway activity with a probability of 0.79 ± 0.20”

      P. 4: "In each network, we created 15 assemblies representing uncorrelated odors. As a consequence, ~30% of E neurons were part of an assembly ..." 

      15 x 100 / 4000 = 37.5% - so it's closer to 40% than 30%. Unless there is some overlap? 

      Yes: despite odors being uncorrelated and connectivity being random, some neurons (6 % of E neurons) belong to more than one assembly.

      P. 4: "When a reached a critical value of ~6, networks became unstable and generated runaway activity (Figure 2B)." 

      Can this transition point be calculated or estimated from the network parameters, and linked to the underlying mechanisms causing it? 

      We thank the reviewer for this interesting question. The unstability arises when inhibitions fails to counterbalance efficiently the increased recurrent excitation within Dp. The transition point is difficult to estimate, as it can depend on several parameters, including the probability of E to E connections, their strength, assembly size, and others. We have therefore not attempted to estimate it analytically.

      P. 4: "Hence, non-specific scaling of inhibition resulted in a divergence of firing rates that exhausted the dynamic range of individual neurons in the population, implying that homeostatic   global inhibition is insufficient to maintain a stable firing rate distribution." 

      I don't think this is justified based on the results and figures presented here (Fig. 2E) - the interpretation is a bit strong and biased towards the conclusions the authors want to draw. 

      To more clearly illustrate the finding that in Scaled networks, assembly neurons are highly active (close to maximal realistic firing rates) whereas non-assembly neurons are nearly silent we have now added Supplementary Fig. 2B. Moreover, we have toned down the text: “Hence, non-specific scaling of inhibition resulted in a large and biologically unrealistic divergence of firing rates (Supplementary Figure 2B) that nearly exhausted the dynamic range of individual neurons in the population, indicating that homeostatic global inhibition is insufficient to maintain a stable firing rate distribution”

      P. 5, third paragraph: Description of Figure 2I, inset is needed, either in the text or caption. 

      The inset is now referred to in the text: ”we projected synaptic conductances of each neuron onto a line representing the E/I ratio expected in a balanced network (“balanced axis”) and onto an orthogonal line (“counter-balanced axis”; Figure 2I inset, Methods).”

      P. 5, last paragraph: another example of writing about results without showing/referring to the corresponding figures: 

      "In rand networks, firing rates increased after stimulus onset and rapidly returned to a low baseline after stimulus offset. Correlations between activity patterns evoked by the same odor at different time points and in different trials were positive but substantially lower than unity, indicating high variability ..." 

      And the continuation with similar lack of references on P. 6: 

      "Scaled networks responded to learned odors with persistent firing of assembly neurons and high pattern correlations across trials and time, implying attractor dynamics (Hopfield, 1982; Khona and Fiete, 2022), whereas Tuned networks exhibited transient responses and modest pattern correlations similar to rand networks." 

      Please go through the Results and fix the references to the corresponding figures on all instances. 

      We thank the reviewer for pointing out these overlooked figure references, which are now fixed.

      P. 8: "These observations further support the conclusion that E/I assemblies locally constrain neuronal dynamics onto manifolds." 

      As discussed in the general major points, mechanistic explanation in terms of how the interaction of E/I dynamics leads to this is missing. 

      As discussed in the reply to the public review (comment 3 of reviewer 1), we have now provided more mechanistic analyses of our observations.

      P. 9: "Hence, E/I assemblies enhanced the classification of inputs related to learned patterns."   The effect seems to be very small. Also, any explanation for why for low test-target correlation the effect is negative (random doing better than tuned E/I)? 

      The size of the effect (plearned – pnovel = 0.074; difference of means; Figure 5C) may appear small in terms of absolute probability, but it is substantial relative to the maximum possible increase (1 – p<sub>novel</sub> =  0.133; Figure 5C). The fact that for low test-target correlations the effect is negative is a direct consequence of the positive effect for high test-target correlations and the presence of 2 learned odors in the 4-way forced choice task. 

      P. 9: "In Scaled I networks, creating two additional memories resulted in a substantial increase   in firing rates, particularly in response to the learned and related odors"   Where is this shown? Please refer to the figure. 

      We thank the reviewer again for pointing this out. We forgot to include a reference to the relevant figure which has now been added in the revised manuscript (Figure 6C).

      P. 10: "The resulting Tuned networks reproduced additional experimental observations that were not used as constraints including irregular firing patterns, lower output than input correlations, and the absence of persistent activity" 

      It is difficult to present these as "additional experimental observations", as all of them are negative, and can exist in random networks too - hence cannot be used as biological evidence in favour of specific E/I networks when compared to random networks. 

      We agree with the reviewer that these additional experimental observations cannot be used as biological evidence favouring Tuned E+I networks over random networks. We here just wanted to point out that additional observations which we did not take into account to fit the model are not invalidating the existence of E-I assemblies in biological networks. As assemblies tend to result in persistent activity in other types of networks, we feel that this observation is worth pointing out.

      Methods: 

      P. 13: Describe the parameters of Eq. 2 after the equation. 

      Done.

      P. 13: "The time constants of inhibitory and excitatory synapses were 10 ms and 30 ms, respectively." 

      What is the (biological) justification for the choice of these parameters? 

      How would varying them affect the main results (e.g. local manifolds)? 

      We chose a relatively slow time constant for excitatory synapses because experimental data indicate that excitatory synaptic currents in Dp and piriform cortex contain a prominent NMDA component. We have now also simulated networks with equal time constants for excitatory and inhibitory synapses and equal biophysical parameters for excitatory and inhibitory neurons, which did not affect the main results (see also reply to the public review: comment 2 of reviewer 1).

      P. 14: "Care was also taken to ensure that the variation in the number of output connections was low across neurons"   How exactly?

      More detailed explanations have now been added in the Methods section: “connections of a presynaptic neuron y to postsynaptic neurons x were randomly deleted when their total number exceeded the average number of output connections by ≥5%, or added when they were lower by ≥5%.“

      Reviewer #2 (Recommendations For The Authors): 

      Congratulations on the great and interesting work! The results were nicely presented and the idea of continuous encoding on manifolds is very interesting. To improve the quality of the paper, in addition to the major points raised in the public review, here are some more detailed comments for the paper: 

      (1) Generally, citations have to improve. Spiking networks with excitatory assemblies and different architectures of inhibitory populations have been studied before, and the claim about improved network stability in co-tuned E-I networks has been made in the following papers that need to be correctly cited: 

      • Vogels TP, Sprekeler H, Zenke F, Clopath C, Gerstner W. 2011. Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks. Science 334:1-7. doi:10.1126/science.1212991 (mentions that emerging precise balance on the synaptic weights can result in the overall network stability) 

      • Lagzi F, Bustos MC, Oswald AM, Doiron B. 2021. Assembly formation is stabilized by Parvalbumin neurons and accelerated by Somatostatin neurons. bioRxiv doi: https://doi.org/10.1101/2021.09.06.459211 (among other things, contrasts stability and competition which arises from multistable networks with global inhibition and reciprocal inhibition)   • Rost T, Deger M, Nawrot MP. 2018. Winnerless competition in clustered balanced networks: inhibitory assemblies do the trick. Biol Cybern 112:81-98. doi:10.1007/s00422-017-0737-7 (compares different architectures of inhibition and their effects on network dynamics) 

      • Lagzi F, Fairhall A. 2022. Tuned inhibitory firing rate and connection weights as emergent network properties. bioRxiv 2022.04.12.488114. doi:10.1101/2022.04.12.488114 (here, see the eigenvalue and UMAP analysis for a network with global inhibition and E/I assemblies) 

      Additionally, there are lots of pioneering work about tracking of excitatory synaptic inputs by inhibitory populations, that are missing in references. Also, experimental work that show existence of cell assemblies in the brain are largely missing. On the other hand, some references that do not fit the focus of the statements have been incorrectly cited. 

      The authors may consider referencing the following more pertinent studies on spiking networks to support the statement regarding attractor dynamics in the first paragraph in the Introduction (the current citations of Hopfield and Kohonen are for rate-based networks): 

      • Wong, K.-F., & Wang, X.-J. (2006). A recurrent network mechanism of time integration in perceptual decisions. Journal of Neuroscience, 26(4), 1314-1328. https://doi.org/10.1523/JNEUROSCI.3733-05.2006 

      • Wang, X.-J. (2008). Decision making in recurrent neuronal circuits. Neuron, 60(2), 215-234. https://doi.org/10.1016/j.neuron.2008.09.034  

      • F. Lagzi, & S. Rotter. (2015). Dynamics of competition between subnetworks of spiking neuronal networks in the balanced state. PloS One. 

      • Goldman-Rakic, P. S. (1995). Cellular basis of working memory. Neuron, 14(3), 477-485. 

      • Rost T, Deger M, Nawrot MP. 2018. Winnerless competition in clustered balanced networks: inhibitory assemblies do the trick. Biol Cybern 112:81-98. doi:10.1007/s00422-017-0737-7. 

      • Amit DJ, Tsodyks M (1991) Quantitative study of attractor neural network retrieving at low spike rates: I. substrate-spikes, rates and neuronal gain. Network 2:259-273. 

      • Mazzucato, L., Fontanini, A., & La Camera, G. (2015). Dynamics of Multistable States during Ongoing and Evoked Cortical Activity. Journal of Neuroscience, 35(21), 8214-8231. 

      We thank the reviewer for the references suggestions. We have carefully reviewed the reference list and made the following changes, which we hope address the reviewer’s concerns:

      (1) We adjusted References about network stability in co-tuned E-I networks.

      (2) We added the Lagzi & Rotter (2015), Amit et al. (1991), Mazzucato et al. (2015) and GoldmanRakic (1995) papers in the Introduction as studies on attractor dynamics in spiking neural networks. We preferred to omit the two X.J Wang papers, as they describe attractors in decision making rather than memory processes.

      (3) We added the Ko et al. 2011 paper as experimental evidence for assemblies in the brain. In our view, there are few experimental studies showing the existence of cell assemblies in the brain, which we distinguish from cell ensembles, group of coactive neurons. 

      (4) We also included Hennequin 2018, Brunel 2000, Lagzi et al. 2021 and Eckmann et al. 2024, which we had not cited in the initial manuscript.

      (5) We removed the Wiechert et al. 2010 reference as it does not support the statement about geometry-preserving transformation by random networks.

      (2) The gist of the paper is about how the architecture of inhibition (reciprocal vs. global in this case) can determine network stability and salient responses (related to multistable attractors and variations) for classification purposes. It would improve the narrative of the paper if this point is raised in the Introduction and Discussion section. Also see a relevant paper that addresses this point here: 

      Lagzi F, Bustos MC, Oswald AM, Doiron B. 2021. Assembly formation is stabilized by Parvalbumin neurons and accelerated by Somatostatin neurons. bioRxiv doi: https://doi.org/10.1101/2021.09.06.459211 

      Classification has long been proposed to be a function of piriform cortex and autoassociative memory networks in general, and we consider it important. However, the computational function of Dp or piriform cortex is still poorly understood, and we do not focus only on odor classification as a possibility. In fact, continuous representational manifolds also support other functions such as the quantification of distance relationships of an input to previously memorized stimuli, or multi-layer network computations (including classification). In the revised manuscript, we have performed additional analyses to explore these notions in more detail, as explained above (response to public reviews, comment 3 of reviewer 1). Furthermore, we have now expanded the discussion of potential computational functions of Tuned networks and explicitly discuss classification but also other potential functions. 

      (3) A plot for the values of the inhibitory conductances in Figure 1 would complete the analysis for that section. 

      In Figure 1, we decided to only show the conductances that we use to fit our model, namely the afferent and total synaptic conductances. As the values of the inhibitory conductances can be derived from panel E, we refrained from plotting them separately for the sake of simplicity. 

      (4) How did the authors calculate correlations between activity patterns as a function of time in Figure 2E, bottom row? Does the color represent correlation coefficient (which should not be time dependent) or is it a correlation function? This should be explained in the Methods section. 

      The color represents the Pearson correlation coefficient between activity patterns within a narrow time window (100 ms). We updated the Figure legend to clarify this: “Mean correlation between activity patterns evoked by a learned odor at different time points during odor presentation. Correlation coefficients were calculated between pairs of activity vectors composed of the mean firing rates of E neurons in 100 ms time bins. Activity vectors were taken from the same or different trials, except for the diagonal, where only patterns from different trials were considered.”

      (5) Figure 3 needs more clarification (both in the main text and the figure caption). It is not clear what the axes are exactly, and why the network responses for familiar and novel inputs are different. The gray shaded area in panel B needs more explanation as well.  

      We thank the reviewer for the comment. We have improved Figure 3A, the figure caption, as well as the text (see p.6). We hope that the figure is now clearer.

      (6) The "scaled I" network, known for representing input patterns in discrete attractors, should exhibit clear separation between network responses in the 2D PC space in the PCA plots. However, Figure 4D and Figure 6D do not reflect this, as all network responses are overlapped. Can the authors explain the overlap in Figure 4D? 

      In Figure 4D, activity of Scaled networks is distributed between three subregions in state space that are separated by the first 2 PCs. Two of them indeed correspond to attractor states representing the two learned odors while the third represents inputs that are not associated with these attractor states. To clarify this, please see also the density plot in Figure 4E. The few datapoints between these three subregions are likely outliers generated by the sequential change in inputs, as described in Supplementary Figure 8C.

      (7) The reason for writing about the ISN networks is not clear. Co-tuned E-I assemblies do not necessarily have to operate in this regime. Also, the results of the paper do not rely on any of the properties of ISNs, but they are more general. Authors should either show the paradoxical effect associated with ISN (i.e., if increasing input to I neurons decreases their responses) or show ISN properties using stability analysis (See computational research conducted at the Allen Institute, namely Millman et al. 2020, eLife ). Currently, the paper reads as if being in the ISN regime is a necessary requirement, which is not true. Also, the arguments do not connect with the rest of the paper and never show up again. Since we know it is not a requirement, there is no need to have those few sentences in the Results section. Also, the choice of alpha=5.0 is extreme, and therefore, it would help to judge the biological realism if the raster plots for Figs 2-6 are shown.

      We have toned down the part on ISN and reduced it to one sentence for readers who might be interested in knowing whether activity is inhibition-stabilized or not. We have also added the reference to the Tsodyks et al. 1997 paper from which we derive our stability analysis. The text now reads “Hence, pDp<sub>sim</sub> entered a balanced state during odor stimulation (Figure 1D, E) with recurrent input dominating over afferent input, as observed in pDp (Rupprecht and Friedrich, 2018). Shuffling spike times of inhibitory neurons resulted in runaway activity with a probability of 0.79 ± 0.20, demonstrating that activity was inhibition-stabilized (Sadeh and Clopath, 2020b, Tsodyks et al., 1997).”  

      We have now also added the raster plots as suggested by the reviewer (see Figure 2D, Supplementary Figure 1 G, Supplementary Figure 4). We thank the reviewer for this comment.

      (8) In the abstract, authors mention "fast pattern classification" and "continual learning," but in the paper, those issues have not been addressed. The study does not include any synaptic plasticity. 

      Concerning “continual learning” we agree that we do not simulate the learning process itself. However, Figure 6 show results of a simulation where two additional patterns were stored in a network that already contained assemblies representing other odors. We consider this a crude way of exploring the end result of a “continual learning” process. “Fast pattern classification” is mentioned because activity in balanced networks can follow fluctuating inputs with high temporal resolution, while networks with stable attractor states tend to be slow. This is likely to account for the occurrence of hysteresis effects in Scaled but not Tuned networks as shown in Supplementary

      Fig. 8.

      (9) In the Introduction, the first sentence in the second paragraph reads: "... when neurons receive strong excitatory and inhibitory synaptic input ...". The word strong should be changed to "weak".

      Also, see the pioneering work of Brunel 2000. 

      In classical balanced networks, strong excitatory inputs are counterbalanced by strong inhibitory inputs, leading to a fluctuation-driven regime. We have added Brunel 2000.

      (10) In the second paragraph of the introduction, the authors refer to studies about structural co-tuning (e.g., where "precise" synaptic balance is mentioned, and Vogels et al. 2011 should be cited there) and functional co-tuning (which is, in fact, different than tracking of excitation by inhibition, but the authors refer to that as co-tuning). It makes it easier to understand which studies talk about structural co-tuning and which ones are about functional co-tuning. The paper by Znamenski 2018, which showed both structural and functional tuning in experiments, is missing here. 

      We added the citation to the now published paper by Znamenskyi et al. (2024).  

      (11) The third paragraph in the Introduction misses some references that address network dynamics that are shaped by the inhibitory architecture in E/I assemblies in spiking networks, like Rost et al 2018 and Lagzi et al 2021. 

      These references have been added.

      (12) The last sentence of the fourth paragraph in the Introduction implies that functional co-tuning is due to structural co-tuning, which is not necessarily true. While structural co-tuning results in functional co-tuning, functional co-tuning does not require structural co-tuning because it could arise from shared correlated input or heterogeneity in synaptic connections from E to I cells.  

      We generally agree with the reviewer, but we are uncertain which sentence the reviewer refers to.

      We assume the reviewer refers to the last sentence of the second (rather than the fourth paragraph), which explicitly mentions the “…structural basis of E/I co-tuning…”. If so, we consider this sentence still correct because the “structural basis” refers not specifically to E/I assemblies, but also includes any other connectivity that may produce co-tuning, including the connectivity underlying the alternative possibilities mentioned by the reviewer (shared correlated input or heterogeneity of synaptic connections).

      (13) In order to ensure that the comparison between network dynamics is legit, authors should mention up front that for all networks, the average firing rates for the excitatory cells were kept at 1 Hz, and the background input was identical for all E and I cells across different networks.

      We slightly revised the text to make this more clear “We (…) uniformly scaled I-to-E connection weights by a factor of χ until E population firing rates in response to learned odors matched the corresponding firing rates in rand networks, i.e., 1 Hz”

      (14) In the last paragraph on page 5, my understanding was that an individual odor could target different cells within an assembly in different trials to generate trial to trail variability. If this is correct, this needs to be mentioned clearly. 

      This is not correct, an odor consists of 150 activated mitral cells with defined firing rates. As now mentioned in the Methods, “Spikes were then generated from a Poisson distribution, and this process was repeated to create trial-to-trial variability.”

      (15) The last paragraph on page 6 mentions that the four OB activity patterns were uncorrelated but if they were designed as in Figure 4A, dues to the existing overlap between the patterns, they cannot be uncorrelated. 

      This appears to be a misunderstanding. We mention in the text (and show in Figure 4B) that the four odors which “… were assigned to the corners of a square…” are uncorrelated.  The intermediate odors are of course not uncorrelated. We slightly modified the corresponding paragraph (now on page 7) to clarify this: “The subspace consisted of a set of OB activity patterns representing four uncorrelated pure odors and mixtures of these pure odors. Pure odors were assigned to the corners of a square and mixtures were generated by selecting active mitral cells from each of the pure odors with probabilities depending on the relative distances from the corners (Figure 4A, Methods).”

      (16) The notion of "learned" and "novel" odors may be misleading as there was no plasticity in the network to acquire an input representation. It would be beneficial for the authors to clarify that by "learned," they imply the presence of the corresponding E assembly for the odor in the network, with the input solely impacting that assembly. Conversely, for "novel" inputs, the input does not target a predefined assembly. In Figure 2 and Figure 4, it would be especially helpful to have the spiking raster plots of some sample E and I cells.  

      As suggested by the reviewer, we have modified the existing spiking raster plots in Figure 2, such that they include examples of responses to both learned and novel odors. We added spiking raster plots showing responses of I neurons to the same odors in Supplementary Figure 1F, as well as spiking raster plots of E neurons in Supplementary Figure 4A. To clarify the usage of “learned” and “novel”, we have added a sentence in the Results section: “We thus refer to an odor as “learned” when a network contains a corresponding assembly, and as “novel” when no such assembly is present.”.

      (17) In the last paragraph of page 8, can the authors explain where the asymmetry comes from? 

      As mentioned in the text, the asymmetry comes from the difference in the covariance structure of different classes. To clarify, we have rephrased the sentence defining the Mahalanobis distance: 

      “This measure quantifies the distance between the pattern and the class center, taking into account covariation of neuronal activity within the class. In bidirectional comparisons between patterns from different classes, the mean dM may be asymmetric if neural covariance differs between classes.”

      (18) The first paragraph of page 9: random networks are not expected to perform pattern classification, but just pattern representation. It would have been better if the authors compared Scaled I network with E/I co-tuned network. Regardless of the expected poorer performance of the E/I co-tuned networks, the result would have been interesting. 

      Please see our reply to the public review (reviewer 2).

      (19) Second paragraph on page 9, the authors should provide statistical significance test analysis for the statement "... was significantly higher ...". 

      We have performed a Wilcoxon signed-rank test, and reported the p-value in the revised manuscript (p < 0.01). 

      (20) The last sentence in the first paragraph on page 11 is not clear. What do the authors mean by "linearize input-output functions", and how does it support their claim? 

      We have now amended this sentence to clarify what we mean: “…linearize the relationship between the mean input and output firing rates of neuronal populations…”.

      (21) In the first sentence of the last paragraph on page 11, the authors mentioned “high variability”, but it is not clear compared with which of the other 3 networks they observed high variability.

      Structurally co-tuned E/I networks are expected to diminish network-level variability. 

      “High variability” refers to the variability of spike trains, which is now mentioned explicity in the text. We hope this more precise statement clarifies this point.

      (22) Methods section, page 14: "firing rates decreased with a time constant of 1, 2 or 4 s". How did they decrease? Was it an implementation algorithm? The time scale of input presentation is 2 s and it overlaps with the decay time constant (particularly with the one with 4 s decrease).  

      Firing rates decreased exponentially. We have added this information in the Methods section.

      Reviewer #3 (Recommendations For The Authors): 

      In the following, I suggest minor corrections to each section which I believe can improve the manuscript. 

      - There was no github link to the code in the manuscript. The code should be made available with a link to github in the final manuscript. 

      The code can be found here: https://github.com/clairemb90/pDp-model. The link has been added in the Methods section.

      Figure 1: 

      - Fig. 1A: call it pDp not Dp. Please check if this name is consistent in every figure and the text. 

      Thank you for catching this. Now corrected in Figure 1, Figure 2 and in the text.

      - The authors write: "Hence, pDpsim entered an inhibition-stabilized balanced state (Sadeh and Clopath, 2020b) during odor stimulation (Figure 1D, E)." and then later "Shuffling spike times of inhibitory neurons resulted in runaway activity with a probability of ~80%, demonstrating that activity was indeed inhibition-stabilized. These results were robust against parameter variations (Methods)." I would suggest moving the second sentence before the first sentence, because the fact that the network is in the ISN regime follows from the shuffled spike timing result. 

      Also, I'd suggest showing this as a supplementary figure. 

      We thank the reviewer for this comment. We have removed “inhibition-stabilized” in the first sentence as there is no strong evidence of this in Rupprecht and Friedrich, 2018. And removed “indeed” in the second sentence. We also provided more detailed statistics. The text now reads “Hence, pDpsim entered a balanced state during odor stimulation (Figure 1D, E) with recurrent input dominating over afferent input, as observed in pDp (Rupprecht and Friedrich, 2018). Shuffling spike times of inhibitory neurons resulted in runaway activity with a probability of 0.79 ± 0.20, demonstrating that activity was inhibition-stabilized (Sadeh and Clopath, 2020b).”

      Figure 2: 

      - "... Scaled I networks (Figure 2H." Missing ) 

      Corrected.

      - The authors write "Unlike in Scaled I networks, mean firing rates evoked by novel odors were indistinguishable from those evoked by learned odors and from mean firing rates in rand networks (Figure 2F)." 

      Why is this something you want to see? Isn't it that novel stimuli usually lead to high responses? Eg in the paper Schulz et al., 2021 (eLife) which is also cited by the authors it is shown that novel responses have high onset firing rates. I suggest clarifying this (same in the context of Fig. 3C). 

      In Dp and piriform cortex, firing rates evoked by learned odors are not substantially different from firing rates evoked by novel odors. While small differences between responses to learned versus novel odors cannot be excluded, substantial learning-related differences in firing rates, as observed in other brain areas, have not been described in Dp or piriform cortex. We added references in the last paragraph of p.5. Note that the paper by Schulz et al. (2021) models a different type of circuit.  

      - Fig. 2B: Indicate in figure caption that this is the case "Scaled I" 

      This is not exactly the case “Scaled I”, as the parameter 𝝌𝝌 (increased I to E strength) is set to 1.

      - Suppl Fig. 2I: Is E&F ever used in the manuscript? I couldn't find a reference. I suggest removing it if not needed. 

      Suppl. Fig 2I E&F is now Suppl Fig.1G&H. We now refer to it in the text: “Activity of networks with E assemblies could not be stabilized around 1 Hz by increasing connectivity from subsets of I neurons receiving dense feed-forward input from activated mitral cells (Supplementary Figure 1GH; Sadeh and Clopath, 2020).”

      Figure 3: 

      - As mentioned in my comment in the public review section, I find the arguments about pattern completion a little bit confusing. For me it's not clear why an increase of output correlations over input correlations is considered "pattern completion" (this is not to say that I don't find the nonlinear increase of output correlations interesting). For me, to test pattern completion with second-order statistics one would need to do a similar separation as in Suppl Fig. 3, ie measuring the pairwise correlation at cells in the assembly L that get direct input from L OB with cells in the assembly L that do not get direct input from OB. If the pairwise correlations of assembly cells which do not get direct input from OB increase in correlations, I would consider this as pattern completion (similar to the argument that increase in firing rate in cells which are not directly driven by OB are considered a sign of pattern completion). 

      Also, for me it now seems like that there are contradictory results, in Fig. 3 only Scaled I can lead to pattern completion while in the context of Suppl. Fig. 3 the authors write "We found that assemblies were recruited by partial inputs in all structured pDpsim networks (Scaled and Tuned) without a significant increase in the overall population activity (Supplementary Figure 3A)."   I suggest clarifying what the authors exactly mean by pattern completion, why the increase of output correlations above input correlations can be considered as pattern completion, and why the results differs when looking at firing rates versus correlations. 

      Please see our reply to the public review (reviewer 3).

      - I actually would suggest adding Suppl. Fig. 3 to the main figure. It shows a more intuitive form of pattern completion and in the text there is a lot of back and forth between Fig. 3 and Suppl. Fig. 3 

      We feel that the additional explanations and panels in Fig.3 should clarify this issue and therefore prefer to keep Supplementary Figure 3 as part of the Supplementary Figures for simplicity.  

      - In the whole section "We next explored effects of assemblies ... prevented strong recurrent amplification within E/I assemblies." the authors could provide a link to the respective panel in Fig. 2 after each statement. This would help the reader follow your arguments. 

      We thank the reviewer for pointing this out. The references to the appropriate panels have been added. 

      - Fig. 3A: I guess the x-axis has been shifted upwards? Should be at zero. 

      We have modified the x-axis to make it consistent with panels B and C.  

      - Fig. 3B: In the figure caption, the dotted line is described as the novel odor but it is actually the unit line. The dashed lines represent the reference to the novel odor. 

      Fixed.

      - Fig. 3C: The " is missing for Pseudo-Assembly N

      Fixed.

      - "...or a learned odor into another learned odor." Have here a ref to the Supplementary Figure 3B.

      Added.

      Figure 4:   

      - "This geometry was largely maintained in the output of rand networks, consistent with the notion that random networks tend to preserve similarity relationships between input patterns (Babadi and Sompolinsky, 2014; Marr, 1969; Schaffer et al., 2018; Wiechert et al., 2010)." I suggest adding here reference to Fig. 4D (left). 

      Added.

      - Please add a definition of E/I assemblies. How do the authors define E/I assemblies? I think they consider both, Tuned I and Tuned E+I as E/I assemblies? In Suppl. Fig. 2I E it looks like tuned feedforward input is defined as E/I assemblies. 

      We thank the reviewer for pointing this out. E/I assemblies are groups of E and I neurons with enhanced connectivity. In other words, in E/I assemblies, connectivity is enhanced not only between subsets of E neurons, but also between these E neurons and a subset of I neurons. This is now clarified in the text: “We first selected the 25 I neurons that received the largest number of connections from the 100 E neurons of an assembly. To generate E/I assemblies, the connectivity between these two sets of neurons was then enhanced by two procedures.”. We removed “E/I assemblies” in Suppl. Fig.2, where the term was not used correctly, and apologize for the confusion.

      - Suppl. Fig. 4: Could the authors please define what they mean by "Loadings" 

      The loadings indicate the contribution of each neuron to each principal component, see adjusted legend of Suppl. Fig. 4: “G. Loading plot: contribution of neurons to the first two PCs of a rand and a Tuned E+I network (Figure 4D).”

      - Fig. 4F: The authors might want to normalize the participation ratio by the number of neurons (see e.g. Dahmen et al., 2023 bioRxiv, "relative PR"), so the PR is bound between 0 and 1 and the dependence on N is removed. 

      We thank the reviewer for the suggestion, but we prefer to use the non-normalized PR as we find it more easily interpretable (e.g. number of attractor states in Scaled networks).

      - Fig. 4G&H: as mentioned in the public review, I'd add the case of Scaled I to be able to compare it to the Tuned E+I case. 

      As already mentioned in the public review, we thank the reviewer for this suggestion, which we have implemented.

      - Figure caption Fig. 4H "Similar results were obtained in the full-dimensional space." I suggest showing this as a supplemental panel. 

      Since this only adds little information, we have chosen not to include it as a supplemental panel to avoid overloading the paper with figures.

      Figure 5: 

      - As mentioned in the public review, I suggest that the authors add the Scaled I case to Fig. 5 (it's shown in all figures and also in Fig. 6 again). I guess for Scaled I the separation between L and M will be very good? 

      Please see our reply to the public review (reviewer 3).

      - Fig. 5A&B: I am a bit confused about which neurons are drawn to calculate the Mahalanobis distance. In Fig. 5A, the schematic indicates that the vector B from which the neurons are drawn is distinct from the distribution Q. For the example of odor L, the distribution Q consists of pure odor L with odors that have little mixtures with the other odors. But the vector v for odor L seems to be drawn only from odors that have slightly higher mixtures (as shown in the schematic in Fig. 5A). Is there a reason to choose the vector v from different odors than the distribution Q? 

      The distribution Q and the vector v consist of activity patterns across the same neurons in response to different odors. The reason to choose a different odor for v was to avoid having this test datapoint being included in the distribution Q. We also wanted Q to be the same for all test datapoints. 

      What does "drawn from whole population" mean? Does this mean that the vectors are drawn from any neuron in pDp? If yes, then I don't understand how the authors can distinguish between different odors (L,M,O,N) on the y-axis. Or does "whole population" mean that the vector is drawn across all assemblies as shown in the schematic in Fig. 5A and the case "neurons drawn from (pseudo-) assembly" means that the authors choose only one specific assembly? In any case, the description here is a bit confusing, I think it would help the reader to clarify those terms better.  

      Yes, “drawn from whole population” means that we randomly draw 80 neurons from the 4000 E neurons in pDp. The y-axis means that we use the activity patterns of these neurons evoked by one of the 4 odors (L, M, N, O) as reference. We have modified the Figure legend to clarify this: “d<sub>M</sub> was computed based on the activity patterns of 80 E neurons drawn from the four (pseudo-) assemblies (top) or from the whole population of 4000 E neurons (bottom). Average of 50 draws.”

      - Suppl Fig. 5A: In the schematic the distance is called d_E(\bar{Q},\bar{V}) while the colorbar has d_E(\bar{Q},\bar{Q}) with the Qs in different color. The green Q should be a V. 

      We thank the reviewer for spotting this mistake, it is now fixed.

      - Fig. 5: Could the authors comment on the fact that a random network seems to be very good in classifying patterns on it's own. Maybe in the Discussion? 

      The task shown in Figure 5 is a relatively easy one, a forced-choice between four classes which are uncorrelated. In Supplementary Figure 9, we now show classification for correlated classes, which is already much harder.

      Figure 6: 

      - Is the correlation induced by creating mixtures like in the other Figures? Please clarify how the correlations were induced. 

      We clarified this point in the Methods section: “The pixel at each vertex corresponded to one pure odor with 150 activated and 75 inhibited mitral cells (…) and the remaining pixels corresponded to mixtures. In the case of correlated pure odors (Figure 6), adjacent pure odors shared half of their activated and half of their inhibited cells.”. An explicit reference to the Methods section has also been added to the figure legend.

      - Fig. 6C (right): why don't we see the clear separation in PC space as shown in Fig. 4? Is this related to the existence of correlations? Please clarify. 

      Yes. The assemblies corresponding to the correlated odors X and Y overlap significantly, and therefore responses to these odors cannot be well separated, especially for Scaled networks. We added the overlap quantification in the Results section to make this clear. “These two additional assemblies had on average 16% of neurons in common due to the similarity of the odors.”

      - "Furthermore, in this regime of higher pattern similarity, dM was again increased upon learning, particularly between learned odors and reference classes representing other odors (not shown)." Please show this (maybe as a supplemental figure). 

      We now show the data in Supplementary Figure 9.

      Discussion: 

      - The authors write: "We found that transformations became more discrete map-like when amplification within assemblies was increased and precision of synaptic balance was reduced. Likewise, decreasing amplification in assemblies of Scaled networks changed transformations towards the intermediate behavior, albeit with broader firing rate distributions than in Tuned networks (not shown)." 

      Where do I see the first point? I guess when I compare in Fig. 4D the case of Scaled I vs Tuned E+I, but the sentence above sounds like the authors showed this in a more step-wise way eg by changing the strength of \alpha or \beta (as defined in Fig. 1). 

      Also I think if the authors want to make the point that decreasing amplification in assemblies changes transformation with a different rate distribution in scaled vs tuned networks, the authors should show it (eg adding a supplemental figure). 

      The first point is indeed supported by data from different figures. Please note that the revised manuscript now contains further simulations that reinforce this statement, particularly those shown in Supplementary Figure 6, and that this point is now discussed more extensively in the Discussion. We hope that these revisions clarify this general point.

      The data showing effects of decreasing amplification in assemblies is now shown in Supplementary Figure 6 (Scaled[adjust])

      - I suggest adding the citation Znamenskiy et al., 2024 (Neuron; https://doi.org/10.1016/j.neuron.2023.12.013), which shows that excitatory and inhibitory (PV) neurons with functional similarities are indeed strongly connected in mouse V1, suggesting the existence of E/I assembly structure also in mammals.

      Done.

    1. Author response:

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

      eLife assessment:

      Developing a reliable method to record ancestry and distinguish between human somatic cells presents significant challenges. I fully acknowledge that my current evidence supporting the claim of lineage tracing with fCpG barcodes is inadequate. I agree with Reviewer 1 that fCpG barcodes are essentially a cellular division clock that diverges over time. A division clock could potentially document when cells cease to divide during development, with immediate daughter cells likely exhibiting more similar barcodes than those that are less related. Although it remains uncertain whether the current fCpG barcodes capture useful biological information, refinement of this type of tool could complement other approaches that reconstruct human brain function, development, and aging.

      Due to my lack of clarity, the fCpG barcode was perceived to be a new type of cell classifier. However, it is fundamentally different. fCpG sites are selected based on their differences between cells of the same type, while traditional cell classifiers focus on sites with consistent methylation patterns in cells of the same type. Despite these opposing criteria, fCpG barcodes and traditional cell classifiers may align because neuron subtypes often share common progenitors. As a result, cells of the same phenotype are also closely related by ancestry, and ex post facto, have similar fCpG barcodes. fCpG barcodes are complementary to cell type classifiers, and potentially provide insights into aspects such as mitotic ages, diversity within a clade, and migration of immediate daughters---information which is otherwise difficult to obtain. The title has been modified to “Human Brain Ancestral Barcodes” to better reflect the function of the fCpG barcodes. The manuscript is edited to correct errors, and a new Supplement is added to further explain fCpG barcode mechanics and present new supporting data.

      Reviewer #1 (Public review):

      I thank Reviewer 1 for his constructive comments. Major noted weaknesses were 1) insufficient clarity and brevity of the methodology, 2) inconsistent or erroneous use of neurodevelopmental concepts, and 3) lack of consideration for alternative explanations.

      (1) The methodology is now outlined in detailed in a new Supplement, including simulations that indicate that the error rate consistent with the experimental data is about 0.01 changes in methylation per fCpG site per division.

      (2) Conceptual and terminology errors noted by the Reviewers are corrected in the manuscript.

      (3) I agree completely with the alternative explanation of Reviewer 1 that fCpGs are “a cellular division clock that diverges over 'time'”. Differences between more traditional cell type classifiers and fCpG barcodes are more fully outlined in the new Supplement.  Ancestry recorded by fCpGs and cell type classifiers are confounded because cells of the same phenotype typically have common progenitors---cells within a clade have similar fCpG barcodes because they are closely related. fCpG barcodes can compliment cell type classifiers with additional information such as mitotic ages, ancestry within a clade, and daughter cell migration.

      Reviewer #1 (Recommendations for the authors):

      (1) A lot of the interpretations suffer from an extremely loose/erroneous use of developmental concepts and a lack of transparency. For instance:

      a) The thalamus is not part of the brain stem

      Corrected.

      b) The pons contains cells other than inhibitory neurons in the data; the same is true for the hippocampus which contains multiple cell types

      Corrected to refer to the specific cell types in these regions.

      c) The author talks about the rostral-caudal timing a lot which is not really discussed to this degree in the cited references. Thus, it is also unclear how interneurons fit in this model as they are distinguished by a ventral-dorsal difference from excitatory neurons. Also, it is unclear whether the timing is really as distinct as claimed. For instance, inhibitory neurons and excitatory neurons significantly overlap in their birth timing. Finally, conceptually, it does not make sense to go by developmental timing as the author proposes that it is the number of divisions that is relevant. While they are somewhat correlated there are potentially stark differences.

      The manuscript attempts to describe what might be broadly expected when barcodes are sampled from different cell types and locations. As a proposed mitotic clock, the fCpG barcode methylation level could time when each neuron ceased division and differentiated. The wide ranges of fCpG barcode methylation of each cell type (Fig 2A) would be consistent with significant overlap between cell types. The manuscript is edited to emphasize overlapping rather than distinct sequential differentiation of the cell types.

      d) Neocortical astrocytes and some oligodendrocytes share a lineage, whereas a subset of oligodendrocytes in the cortex shares an origin with interneurons. This could confound results but is never discussed.

      The manuscript does not assess glial lineages in detail because neurons were preferentially included in the sampling whereas glial cells were non-systematically excluded. This sampling information is now included in the section “fCpG barcode identification”.

      e) Neocortical interneurons should be more closely related in terms of lineage-to-excitatory neurons than other inhibitory neurons of, for instance, the pons. This is not clearly discussed and delineated.

      This is not discussed. It may not be possible analyze these details with the current data. The ancestral tree reconstructions indicate that excitatory neurons that appear earlier in development (and are more methylated) are more often more closely related to inhibitory neurons.

      f) While there is some spread of excitatory neurons tangentially, there is no tangential migration at the scale of interneurons as (somewhat) suggested/implied here.

      The abstract and results have been modified to indicate greater inhibitory than excitatory neuron tangential migration, but that the extent of excitatory neuron tangential migration cannot be determined because of the sparse sampling and that barcodes may be similar by chance.

      g) The nature of the NN cells is quite important as cells not derived from the neocortical anlage are unlikely to share a developmental origin (e.g., microglia, endothelial cells). This should be clarified and clearly stated.

      The manuscript is modified to indicate that NN cells are microglial and endothelial cells. These cells have different developmental origins, and their data are present in Fig 2A, but are not further used for ancestral analysis.  

      (2) The presentation is often somewhat confusing to me and lacks detail. For instance:

      a) The methods are extremely short and I was unable to find a reference for a full pipeline, so other researchers can replicate the work and learn how to use the pipeline.

      The pipeline including python code is outlined in the new Supplement

      b) Often numbers are given as ~XX when the actual number with some indication of confidence or spread would be more appropriate.

      Data ranges are often indicated with the violin plots.

      c) Many figure legends are exceedingly short and do not provide an appropriate level of detail.

      Figure legends have been modified to include more detail

      d) Not defining groups in the figure legends or a table is quite unacceptable to me. I do not think that referring to a prior publication (that does not consistently use these groups anyway) is sufficient.

      The cell groups are based on the annotations provided with each single cell in the public databases.

      e) The used data should be better defined and introduced (number of cells, different subtypes across areas, which cells were excluded; I assume the latter as pons and hippocampus are only mentioned for one type of neuronal cells, see also above).

      The data used are present in Supplemental File 2 under the tab “cell summary H01, H02, H04”.

      f) Why were different upper bounds used for filtering for H01 and H02, and H04 is not mentioned? Why are inhibitory and excitatory neurons specifically mentioned (Lines 61-66)?

      The filtering is used to eliminate, as much as possible, cell type specific methylation, or CpG sites with skewed neuron methylation. The filtering eliminates CpG sites with high or low methylation within each of the three brains, and within the two major neuron subtypes. The goal is to enrich for CpG sites with polymorphic but not cell type specific methylation. This process is ad hoc as success criteria are currently uncertain. The extent of filtering is balanced by the need to retain sufficient numbers of fCpGs to allow comparisons between the neurons.

      g) What 'progenitor' does the author refer to? The Zygote? If yes, can the methylation status be tested directly from a zygote? There is no single progenitor for these cells other than the zygote. Does the assumption hold true when taking this into account? See, for instance, PMID 33737485 for some estimation of lineage bottlenecks.

      A brain progenitor cell can be defined as the common ancestor of all adult neurons, and is the first cell where each of its immediate daughter cell lineages yield adult neurons. The zygote is a progenitor cell to all adult cells, and barcode methylation at the start of conception, from the oocyte to the ICM, was analyzed in the new Supplement. The proposed brain progenitor cell with a fully methylated barcode was not yet evident even in the ICM.

      (3) I am generally not convinced that the fCpGs represent anything but a molecular clock of cell divisions and that many of the similarities are a function of lower division numbers where the state might be more homogenous. This mainly derives from the issues cited above, the lack of convincing evidence to the contrary, and the sparsity of the assessed data.

      Agree that the fCpG barcode is a mitotic clock that becomes polymorphic with divisions. As outlined in the new Supplement, ancestry and cell type are confounded because cells of the same type typically have a common progenitor.

      a) There appears little consideration or modeling of what the ability to switch back does to the lineage reconstruction.

      fCpG methylation flipping is further analyzed and discussed in the new Supplement.

      b) None of the data convinced me that the observations cannot be explained by the aforementioned molecular clock and systematic methylation similarities of cell types due to their cell state.

      See above

      (4) Uncategorized minor issues:

      a) The author should explain concepts like 'molecular clock hypothesis' (line 27) or 'radial unit hypothesis' (line 154), as they are somewhat complex and might not be intuitive to readers.

      The molecular clock hypothesis is deleted and the radial unit hypothesis is explained in more detail in the manuscript.

      b) Line 32: '[...] replication errors are much higher compared to base replication [...]'. I think this is central to the method and should be better explained and referenced. Maybe even through a schematic, as this is a central concept for the entire manuscript.

      The fCpG barcode mechanics are better explained in the new Supplement. With simulations, the fCpG flip rate is about 0.01 per division per fCpG.

      c) Line 41: 'neonatal'. Does the author mean to say prenatal? Most of the cells discussed are postmitotic before birth.

      Corrected to prenatal.

      d) Line 96: what does 'flip' mean in this context? Please also see the comment on Figure 2C.

      Edited to “chage”

      e) Lines 134-135: I am not sure whether the author claims to provide evidence for this question, and I would be careful with claims that this work does resolve the question here.

      Have toned down claims as evidence for my analysis is currently inadequate.

      f) Lines 192-193: I disagree as the fCpGs can switch back and the current data does not convince me that this is an improvement upon mosaic mutation analysis. In my mind, the main advantage is the re-analysis of existing data and the parallel functional insights that can be obtained.

      Lineage analysis is more straightforward with DNA sequencing, but with an error rate of ~10-9 per base per division, one needs to sequence a billion base pairs to distinguish between immediate daughter cells. By contrast, with an inferred error rate of ~10-2 per fCpG per division, much less sequencing (about a million-fold less) is needed to find differences between daughter cells.

      g) Lines 208-209: I would be careful with claims of complexity resolution given many of the limitations and inherent systematic similarities, as well as the potential of fCpGs to change back to an ancestral state later in the lineage.

      Have modified the manuscript to indicate the analysis would be more challenging due to back changes.

      h) There seem to be few figures that assess phenomena across the three brains. Even when they exist there is no attempt to provide any statistical analyses to support the conclusions or permutations to assess outlier status relative to expectations.

      The analysis could be more extensive, but with only three brains, any results, like this study itself, would be rightly judged inadequate.

      Figure 2B: there appears to be a higher number of '0s' for, for instance, inhibitory neurons compared to excitatory neurons. Is that correct and worth mentioning? The changing axes scales also make it hard to assess.

      Inhibitory neurons do appear to have more unmethylated fCpGs compared to excitatory neurons, but in general, most inhibitory fCpGs are methylated with a skew to fully methylated fCpGs, consistent with the barcode starting predominately methylated and inhibitory neurons generally appearing earlier in development relative to excitatory neurons.

      j) Figure 2C: I have several issues with this. A minor one is the use of 'Glial' which, I believe, does not appear anywhere else before this, so I am unclear what this curve represents. Generally, however, I am not sure what the y-axis represents, as it is not described in the methods or figure legend. I initially thought it was the cumulative frequency, but I do not think that this squares with the data shown in B. I appreciate the overall idea of having 'earlier'/samples with fewer divisions being shifted to the left, but it is very confusing to me when I try to understand the details of the plot.

      This graph is now better described in the legend. “Glial” cells are defined as oligodendrocytes and astrocytes. Other non-neuronal cells (such a microglial cells) have now been removed from the graph.

      This graph attempts to illustrate how it may be possible to reconstruct brain development from adult neurons, assuming barcodes are mitotic clocks that become polymorphic with cell division. The X axis is “time”, and the Y axis indicates when different cell types reach their adult levels. The cartoon indicates what is visually present along the X axis during development--- brainstem, then ganglionic eminences with a thin cortex, and finally the mature brain with a robust cortex. Time for the X axis is barcode methylation and starts at 100% and ends at 50% or greater methylation. The fCpG barcode methylation of each cell places it on this timeline and indicates when it ceased dividing and differentiated.

      The Y axis indicates the progressive accumulation of the final adult contents of each cell type during this timeline. Early in development, the brain is rudimentary and adult cells are absent. At 90% methylation, only the inhibitory neurons in the pons are present. At 80% methylation, some excitatory neurons are beginning to appear. Inhibitory neurons in the pons have reached their final adult levels and many other inhibitory neuron types are reaching adult levels. By 70% methylation, most inhibitory neurons have reached their adult levels, and more adult excitatory neurons (mainly low cortical neurons, L4-6) and glial cells are beginning to appear. By 60% methylation, inhibitory neurogenesis has largely finished. Adult excitatory neurons and glial cells are more abundant and reach their adult levels by 50% or greater cell barcode methylation levels.

      The graph illustrates a rough alignment between mitotic ages inferred by barcode methylation levels and the physical appearances of different neuronal types during development. Many neurons die during development, and this graph, if valid, indicates when neurons that survive to adulthood appear during development.

      k) Figure 4Bff: it is confusing to me that the text jumps to these panels after introducing Figure 5. This makes it very hard to read this section of the text.

      The Figures appear in the order they are first referred to in the text.

      l) Figure 5A: could any of this difference be explained by the shared lineage of excitatory neurons and dorsal neocortical glia?

      Not sure

      m) Figure 5B: after stating that interneurons have a higher lineage fidelity, the figure legend here states the opposite and I am somewhat confused by this statement.

      The legend and text have been clarified. Fig 5A restricts fidelity to within inhibitory cell types. Fig 5B compares between neuron subtypes, and illustrates more apparent inhibitory subtype switching, albeit there are more interneuron subtypes than excitatory subtypes.

      n) Figure 5E: generally, the use of tSNE for large pairwise distance analysis is often frowned upon (e.g., PMID 37590228), and I would reconsider this argument.

      This analysis was an attempt to illustrate that cells of the same phenotype based on their tSNE metrics can be either closely or more distantly related. Although the tSNE comparisons were restricted to subtypes (and not to the entire tSNE graph), tSNE are not designed for such comparisons. This graph and discussion are deleted. 

      Reviewer #2 (Public review):

      The manuscript by Shibata proposed a potentially interesting idea that variation in methylcytosine across cells can inform cellular lineage in a way similar to single nucleotide variants (SNVs). The work builds on the hypothesis that the "replication" of methylcytosine, presumably by DNMT1, is inaccurate and produces stochastic methylation variants that are inherited in a cellular lineage. Although this notion can be correct to some extent, it does not account for other mechanisms that modulate methylcytosines, such as active gain of methylation mediated by DNMT3A/B activity and activity demethylation mediated by TET activity. In some cases, it is known that the modulation of methylation is targeted by sequence-specific transcription factors. In other words, inaccurate DNMT1 activity is only one of the many potential ways that can lead to methylation variants, which fundamentally weakens the hypothesis that methylation variants can serve as a reliable lineage marker. With that being said (being skeptical of the fundamental hypothesis), I want to be as open-minded as possible and try to propose some specific analyses that might better convince me that the author is correct. However, I suspect that the concept of methylation-based lineage tracing cannot be validated without some kind of lineage tracing experiment, which has been successfully demonstrated for scRNA-seq profiling but not yet for methylation profiling (one example is Delgado et al., nature. 2022).

      I thank Reviewer 2 for the careful evaluation. The validation experiment example (Delgado et al.) introduced sequence barcodes in mice, which is not generally feasible for human studies.

      (1) The manuscript reported that fCpG sites are predominantly intergenic. The author should also score the overlap between fCpG sites and putative regulatory elements and report p-values. If fCpG sites commonly overlap with regulatory elements, that would increase the possibility that these sites being actively regulated by enhancer mechanisms other than maintenance methyltransferase activity.

      As mentioned for Reviewer 1, fCpGs are filtered to eliminate cell type specific methylation.

      (2) The overlap between fCpG and regulatory sequence is a major alternative explanation for many of the observations regarding the effectiveness of using fCpG sites to classify cell types correctly. One would expect the methylation level of thousands of enhancers to be quite effective in distinguishing cell types based on the published single-cell brain methylome works.

      As mentioned above, the manuscript did not clearly indicate that the fCpG barcode is not a cell type classifier. The distinctions between fCpG barcodes and cell type classifiers are better explained in the new Supplement.

      (3) The methylation level of fCpG sites is higher in hindbrain structures and lower in forebrain regions. This observation was interpreted as the hindbrain being the "root" of the methylation barcodes and, through "progressive demethylation" produced the methylation states in the forebrain. This interpretation does not match what is known about methylation dynamics in mammalian brains, in particular, there is no data supporting the process of "progressive demethylation". In fact, it is known that with the activation of DNMT3A during early postnatal development in mice or humans (Lister et al., 2013. Science), there is a global gain of methylation in both CH and CG contexts. This is part of the broader issue I see in this manuscript, which is that the model might be correct if "inaccurate mC replication" is the only force that drives methylation dynamics. But in reality, active enzymatic processes such as the activation of DNMT3A have a global impact on the methylome, and it is unclear if any signature for "inaccurate mC replication" survives the de novo methylation wave caused by DNMT3A activity.

      Reviewer 2 highlights a critical potential flaw in that any ancestral signal recorded by random replication errors could be overwritten by other active methylation processes. I cannot present data that indicates fCpG replication errors are never overwritten, but new data indicate barcode reproducibility and stability with aging.

      New data are also present where barcodes are compared between daughter cells (zygote to ICM) in the setting of active and passive demethylation, when germline methylation is erased. This new analysis shows that daughter cells in 2 to 8 cell embryos have more related barcodes than morula or ICM cells. The subsequent active remethylation by a wave of DNMT3A activity may underlie the observation that the barcode appears to start predominately methylated in brain progenitors.

      (3) Perhaps one way the author could address comment 3 is to analyze methylome data across several developmental stages in the same brain region, to first establish that the signal of "inaccurate mC replication" is robust and does not get erased during early postnatal development when DNMT3A deposits a large amount of de novo methylation.

      See above

      (4) The hypothesis that methylation barcodes are homogeneous among progenitor cells and more polymorphic in derived cells is an interesting one. However, in this study, the observation was likely an artifact caused by the more granular cell types in the brain stem, intermediate granularity in inhibitory cells, and highly continuous cell types in cortical excitatory cells. So, in other words, single-cell studies typically classify hindbrain cell types that are more homogenous, and cortical excitatory cells that are much more heterogeneous. The difference in cell type granularity across brain structures is documented in several whole-brain atlas papers such as Yao et al. 2023 Nature part of the BICCN paper package.

      As noted above, fCpG barcode polymorphisms and cell type differentiation are confounded because cells of the same phenotype tend to have common progenitors. The fCpG barcode is not a cell type classifier but more a cell division clock that becomes polymorphic with time. Although fCpG barcodes could be more polymorphic in cortical excitatory cells because there are many more types, fCpG barcodes would inherently become more polymorphic in excitatory cells because they appear later in development.

      (5) As discussed in comment 2, the author needs to assess whether the successful classification of cell types (brain lineage) using fCpG was, in fact, driven by fCpG sites overlapping with cell-type specific regulatory elements.

      Although unclear in the manuscript, the fCpG is not a cell classifier and the barcode is polymorphic between cells of the same type. fCpG barcodes can appear to be cell classifiers because cell types appear at different times during development, and therefore different cell types have characteristic average barcode methylation levels.

      (6) In Figure 5E, the author tried to address the question of whether methylation barcodes inform lineage or post-mitotic methylation remodeling. The Y-axis corresponds to distances in tSNE. However, tSNE involves non-linear scaling, and the distances cannot be interpreted as biological distances. PCA distances or other types of distances computed from high-dimensional data would be more appropriate.

      The Figure and discussion are deleted (similar comment by Reviewer 1)

      Reviewer #3 (Public review):

      Summary:

      In the manuscript entitled "Human Brain Barcodes", the author sought to use single-cell CpG methylation information to trace cell lineages in the human brain.

      Strengths:

      Tracing cell lineages in the human brain is important but technically challenging. Lineage tracing with single-cell CpG methylation would be interesting if convincing evidence exists.

      Weaknesses:

      As the author noted, "DNA methylation patterns are usually copied between cell division, but the replication errors are much higher compared to base replication". This unstable nature of CpG methylation would introduce significant problems in inferring the true cell lineage. The unreliable CpG methylation status also raises the question of what the "Barcodes" refer to in the title and across this study. Barcodes should be stable in principle and not dynamic across cell generations, as defined in Reference#1. It is not convincing that the "dynamic" CpG methylation fits the "barcodes" terminology. This problem is even more concerning in the last section of results, where CpG would fluctuate in post-mitotic cells.

      I thank Reviewer 3 for his thoughtful and careful evaluation. I think the “barcode” terminology is appropriate. Dynamic engineered barcodes such as CRISPR/Cas9 mutable barcodes are used in biology to record changes over time. The fCpG barcode appears to start with a single state in a progenitor cell and changes with cell division to become polymorphic in adult cells. Therefore, I think the description of a dynamic fCpG barcode is appropriate.

      Reviewer #3 (Recommendations for the authors):

      (1) As the author noted, "DNA methylation patterns are usually copied between cell division, but the replication errors are much higher compared to base replication". This unstable nature of CpG methylation would introduce significant problems in inferring the true cell lineage. To establish DNA methylation as a means for lineage tracing, one control experiment would be testing whether the DNA methylation patterns can faithfully track cell lineages for in vitro differentiated & visibly tracked cell lineages. Has this kind of experiment been done in the field?

      These types of experiments have not been performed to my knowledge and an appropriate tissue culture model is uncertain. New single cell WGBS data from the zygote to ICM indicate that more immediate daughter cells have more related barcodes even in the setting of active DNA demethylation.

      (2) The study includes assumptions that should be backed with solid rationale, supporting evidence, or reference. Here are a couple of examples:

      a) the author discarded stable CpG sites with <0.2 or >0.8 average methylation without a clear rationale in H02, and then used <0.3 and >0.7 for a specific sample H01.

      The filtering was ad hoc and was used to remove, as much as possible, CpG sites with cell type specific or patient specific methylation. CpG sites with skewed methylation are more likely cell type specific, whereas X chromosome CpG sites with methylation closer to 0.5 in male cells are more likely to be unstable. The ad hoc filtering attempted to remove cell specific CpGs sites while still retaining enough CpG sites to allow comparisons between cells.

      b) The author assumed that the early-formed brain stem would resemble progenitors better and have a higher average methylation level than the forebrain. However, this difference in DNA methylation status could reflect developmental timing or cell type-specific gene expression changes.

      This observation that brain stem neurons that appear early in development have highly methylated fCpG barcodes in all 3 brains supports the idea that the fCpG barcode starts predominately methylated. Alternative explanations are possible.

      (3) The conclusion that excitatory neurons undergo tangential migration is unclear - how far away did the author mean for the tangential direction? Lateral dispersion is known, but it would be striking that the excitatory neurons travel across different brain regions. The question is, how would the author interpret shared or divergent methylation for the same cell type across different brain regions?

      As noted with Reviewer 1, this analysis is modified to indicate that evidence of tangential migration is greater for inhibitory than excitatory neurons, but the extent of excitatory neuron migration is uncertain because of sparse sampling, and because fCpG barcodes can be similar by chance.

      (4) The sparsity and resolution of the single-cell DNA methylation data. The methylation status is detected in only a small fraction (~500/31,000 = 1.6%) of fCpGs per cell, with only 48 common sites identified between cell pairs. Given that the human genome contains over 28 million CpG sites, it is important to evaluate whether these fCpGs are truly representative. How many of these sites were considered "barcodes"?

      fCpG barcodes are distinct from traditional cell type classifiers, and how fCpGs are identified are better outlined in the new Supplement.

      (5) While focusing on the X-chromosome may simplify the identification of polymorphic fCpGs, the confidence in determining its methylation status (0 or 1) is questionable when a CpG site is covered by only one read. Did the author consider the read number of detected fCpGs in each cell when calculating methylation levels? Certain CpG sites on autosomes may also have sufficient coverage and high variability across cells, meeting the selection criteria applied to X-chromosome CpGs.

      In most cases, a fCpG site was covered by only a single read

      (6) The overall writing in the Title, the Main text, Figure legends, and Methods sections are overly simplified, making it difficult to follow. For instance, how did the author perform PWD analysis? How did they handle missing values when constructing lineage trees?

      There is not much introduction to lineage tracing in the human brain or the use of DNA methylation to trace cell lineage.

      These shortcomings are improved in the manuscript and with the new Supplement. The analysis pipeline including the Python programs are outlined and included as new Supplemental materials. IQ tree can handle the binary fCpG barcode data and skips missing values with its standard settings.

      Line 80: it is unclear: "Brain patterns were similar"

      Clarified

      Line 98: The meaning is unclear here: "Outer excitatory and glial progenitor cells are present" What are these glial progenitor cells and when/how they stop dividing?

      The glial cells are the oligodendrocytes and astrocytes. The main take away point is that these glial cells have low barcode methylation, consistent with their appearances later in development.

      Line 104: It is unclear if this is a conclusion or assumption -- "A progenitor cell barcode should become increasingly polymorphic with subsequent divisions." The "polymorphic" happens within the progenitors, their progenies, or their progenies at different time points.

      The statement is now clarified as an assumption in the manuscript.

      Similarly line 134 "Barcodes would record neuronal differentiation and migration." Is this a conclusion from this study or a citation? How is the migration part supported?

      The reasoning is better explained in the manuscript.  Migration can be documented if immediate daughter cells with similar barcodes are found in different parts of the adult brain, albeit analysis is confounded by sparse sampling and because barcodes may be similar by chance.

      Line 148 and 150: "Nearest neighbor ... neuron pairs" in DNA methylation status would conceivably reflect their cell type-specific gene expression, how did the author distinguish this from cell lineage?

      As noted above, because cells with similar phenotypes usually arise from common progenitors, cells within a clade are also usually related. However, the barcodes are still polymorphic within a clade and potentially add complementary information on mitotic ages, ancestry within a clade, and possible cell migration.

      Figure 3C: "Cells that emerge early in development" Where are they on the figure?

      Hindbrain neurons differentiate early in development and their barcodes are more methylated. The figure has been modified to label some of the values with their neuron types. Also, the older figure mistakenly included data from all 3 brains and now the data are only from brain H01.

      Figures 4D and 4E, distinguishing cell subtypes is challenging, as the same color palette is used for both excitatory and inhibitory neurons.

      Unfortunate limitations due to complexity and color limitations

      Figures 4 and 5, what are these abbreviations?

      The abbreviations are presented in Figure 1 and maintained in subsequent figures.

    1. Author response:

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

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      The authors intended to investigate the earliest mechanisms enabling self-prioritization, especially in the attention. Combining a temporal order judgement task with computational modelling based on the Theory of Visual Attention (TVA), the authors suggested that the shapes associated with the self can fundamentally alter the attentional selection of sensory information into awareness. This self-prioritization in attentional selection occurs automatically at early perceptual stages. Furthermore, the processing benefits obtained from attentional selection via self-relatedness and physical salience were separated from each other.

      Strengths:

      The manuscript is written in a way that is easy to follow. The methods of the paper are very clear and appropriate.

      Thank you for your valuable feedback and helpful suggestions. Please see specific answers below.

      Weaknesses:

      There are two main concerns:

      (1) The authors had a too strong pre-hypothesis that self-prioritization was associated with attention. They used the prior entry to consciousness (awareness) as an index of attention, which is not appropriate. There may be other processing that makes the stimulus prior to entry to consciousness (e.g. high arousal, high sensitivity), but not attention. The self-related/associated stimulus may be involved in such processing but not attention to make the stimulus easily caught. Perhaps the authors could include other methods such as EEG or MEG to answer this question.

      We found the possibility of other mechanisms to be responsible for “prior entry” interesting too, but believe there are solid grounds for the hypothesis that it is indicative of attention:

      First, prior entry has a long-standing history as in index of attention (e.g., Titchener, 1903; Shore et al., 2001; Yates and Nicholls, 2009; Olivers et al. 2011; see Spence & Parise, 2010, for a review.) Of course, other factors (like the ones mentioned) can contribute to encoding speed. However, for the perceptual condition, we systematically varied a stimulus feature that is associated with selective attention (salience, see e.g. Wolfe, 2021) and kept other features that are known to be associated with other factors such as arousal and sensitivity constant across the two variants (e.g. clear over threshold visibility) or varied them between participants (e.g. the colours / shapes used).

      Second, in the social salience condition we used a manipulation that has repeatedly been used to establish social salience effects in other paradigms (e.g., Li et al., 2022; Liu & Sui, 2016; Scheller et al., 2024; Sui et al., 2015; see Humphreys & Sui, 2016, for a review). We assume that the reviewer’s comment suggests that changes in arousal or sensitivity may be responsible for social salience effects, specifically. We have several reasons to interpret the social salience effects as an alteration in attentional selection, rather than a result of arousal or sensitivity:

      Arousal and attention are closely linked. However, within the present model, arousal is more likely linked to the availability of processing resources (capacity parameter C). That is, enhanced arousal is typically not stimulus-specific, and therefore unlikely affects the *relative* advantage in processing weights/rates of the self-associated (vs other-associated) stimuli. Indeed, a recent study showed that arousal does not modulate the relative division of attentional resources (as modelled by the Theory of Visual Attention; Asgeirsson & Nieuwenhuis, 2017). As such, it is unlikely that arousal can explain the observed results in relative processing changes for the self and other identities.

      Further, there is little reason to assume that presenting a different shape enhances perceptual sensitivity. Firstly, all stimuli were presented well above threshold, which would shrink any effects that were resulting from increases in sensitivity alone. Secondly, shape-associations were counterbalanced across participants, reducing the possibility that specific features, present in the stimulus display, lead to the measurable change in processing rates as a result of enhanced shape-sensitivity.

      Taken together, both, the wealth of literature that suggests prior entry to index attention and the specific design choices within our study, strongly support the notion that the observed changes in processing rates are indicative of changes in attentional selection, rather than other mechanisms (e.g. arousal, sensitivity).

      (2) The authors suggested that there are two independent attention processes. I suspect that the brain needs two attention systems. Is there a probability that the social and perceptual (physical properties of the stimulus) salience fired the same attention processing through different processing?

      We appreciate this thought-provoking comment. We conceptualize attention as a process that can facilitate different levels of representation, rather than as separate systems tuned to specific types of information. Different forms of representation, such as the perceptual shape, or the associated social identity, may be impacted by the same attentional process at different levels of representation. Indeed, our findings suggest that both social and perceptual salience effects may result from the same attentional system, albeit at different levels of representation. This is further supported by the additivity of perceptual and social salience effects and the negative correlation of processing facilitations between perceptually and socially salient cues. These results may reflect a trade-off in how attentional resources are distributed between either perceptually or socially salient stimuli.

      Reviewer #2 (Public review):

      Summary:

      The main aim of this research was to explore whether and how self-associations (as opposed to other associations) bias early attentional selection, and whether this can explain well-known self-prioritization phenomena, such as the self-advantage in perceptual matching tasks. The authors adopted the Visual Attention Theory (VAT) by estimating VAT parameters using a hierarchical Bayesian model from the field of attention and applied it to investigate the mechanisms underlying self-prioritization. They also discussed the constraints on the self-prioritization effect in attentional selection. The key conclusions reported were:

      (1) Self-association enhances both attentional weights and processing capacity

      (2) Self-prioritization in attentional selection occurs automatically but diminishes when active social decoding is required, and

      (3) Social and perceptual salience capture attention through distinct mechanisms.

      Strengths:

      Transferring the Theory of Visual Attention parameters estimated by a hierarchical Bayesian model to investigate self-prioritization in attentional selection was a smart approach. This method provides a valuable tool for accessing the very early stages of self-processing, i.e., attention selection. The authors conclude that self-associations can bias visual attention by enhancing both attentional weights and processing capacity and that this process occurs automatically. These findings offer new insights into self-prioritization from the perspective of the early stage of attentional selection.

      Thank you for your valuable feedback and helpful suggestions. Please see specific answers below.

      Weaknesses:

      (1) The results are not convincing enough to definitively support their conclusions. This is due to inconsistent findings (e.g., the model selection suggested condition-specific c parameters, but the increase in processing capacity was only slight; the correlations between attentional selection bias and SPE were inconsistent across experiments), unexpected results (e.g., when examining the impact of social association on processing rates, the other-associated stimuli were processed faster after social association, while the self-associated stimuli were processed more slowly), and weak correlations between attentional bias and behavioral SPE, which were reported without any p-value corrections. Additionally, the reasons why the attentional bias of self-association occurs automatically but disappears during active social decoding remain difficult to explain. It is also possible that the self-association with shapes was not strong enough to demonstrate attention bias, rather than the automatic processes as the authors suggest. Although these inconsistencies and unexpected results were discussed, all were post hoc explanations. To convince readers, empirical evidence is needed to support these unexpected findings.

      Thank you for outlining the specific points that raise your concern. We were happy to address these points as follows:

      a. Replications and Consistency: In our study, we consistently observed trends (relative reduction in processing speed of the self-associated stimulus) in the social salience conditions across experiments. While Experiment 2 demonstrated a significant reduction in processing rate towards self-stimuli, there was a notable trend in Experiment 1 as well.

      b. Condition-specific parameters: The condition-specific C parameters, though presenting a small effect size, significantly improved model fit. Inspecting the HDI ranges of our estimated C parameters indicates a high probability (85-89%) that processing capacity increased due to social associations, suggesting that even small changes (~2Hz) can hold meaningful implications within the context attentional selection.

      Please also note that the main conclusions about relative salience (self/other, salient/non-salient) are based on the relative processing rates. Processing rates are the product of the processing capacity (condition- but not stimulus dependent) and the attentional weight (condition and stimulus dependent). The latter is crucial to judge the *relative* advantage of the salient stimulus. Hence, the self-/salient stimulus advantage that is reflected in the ‘processing rate difference’ is automatically also reflected in the relative attentional weights attributed to the self/other and salient/non-salient stimuli. As such, the overall results of an automatic relative advantage of self-associated stimuli hold, independently of the change in overall processing capacity.

      c. Correlations: Regarding the correlations the reviewer noted, we wish to clarify that these were exploratory, and not the primary focus of our research. The aim of these exploratory analyses was to gauge the contribution of attentional selection to matching-based SPEs. As SPEs measured via the matching task are typically based on multiple different levels of processing, the contribution of early attentional selection to their overall magnitude was unclear. Without being able to gauge the possible effect sizes, corrected analyses may prevent detecting small but meaningful effects. As such, the effect sizes reported serve future studies to estimate power a priori and conduct well-powered replications of such exploratory effects. Additionally, Bayes factors were provided to give an appreciation of the strength of the evidence, all suggesting at least moderate evidence in favour of a correlation. Lastly, please note that effects that were measured within individuals and task (processing rate increase in social and perceptual decision dimensions in the TOJ task) showed consistent patterns, suggesting that the modulations within tasks were highly predictive of each other, while the modulations between tasks were not as clearly linked. We will add this clarification to the revised manuscript.

      d. Unexpected results: The unexpected results concerning the processing rates of other-associated versus self-associated stimuli certainly warrant further discussion. We believe that the additional processing steps required for social judgments, reflected in enhanced reaction times, may explain the slower processing of self-associated stimuli in that dimension. We agree that not all findings will align with initial hypotheses, and this variability presents avenues for further research. We have added this to the discussion of social salience effects.

      e. Whether association strength can account for the findings: We appreciate the scepticism regarding the strength of self-association with shapes. However, our within-participant design and control matching task indicate that the relative processing advantage for self-associated stimuli holds across conditions. This makes the scenario that “the self-association with shapes was not strong enough to demonstrate attention bias” very unlikely. Firstly, the relative processing advantage of self-associated stimuli in the perceptual decision condition, and the absence of such advantage in the social decision condition, were evidenced in the same participants. Hence, the strength of association between shapes and social identities was the same for both conditions. However, we only find an advantage for the self-associated shape when participants make perceptual (shape) judgements. It is therefore highly unlikely that the “association strength” can account for the difference in the outcomes between the conditions in experiment 1. Also, note that the order in which these conditions were presented was counter-balanced across participants, reducing the possibility that the automatic self-advantage was merely a result of learning or fatigue. Secondly, all participants completed the standard matching task to ascertain that the association between shapes and identities did indeed lead to processing advantages (across different levels).

      In summary, we believe that the evidence we provide supports the final conclusions. We do, of course, welcome any further empirical evidence that could enhance our understanding of the contribution of different processing levels to the SPE and are committed to exploring these areas in future work.

      (2) The generalization of the findings needs further examination. The current results seem to rely heavily on the perceptual matching task. Whether this attentional selection mechanism of self-prioritization can be generalized to other stimuli, such as self-name, self-face, or other domains of self-association advantages, remains to be tested. In other words, more converging evidence is needed.

      The reviewer indicates that the current findings heavily rely on the perceptual matching task, and it would be more convincing to include other paradigm(s) and different types of stimuli. We are happy to address these points here: first, we specifically used a temporal order paradigm to tap into specific processes, rather than merely relying on the matching task. Attentional selection is, along with other processes, involved in matching, but the TOJ-TVA approach allows tapping into attentional selection specifically.  Second, self-prioritization effects have been replicated across a wide range of stimuli (e.g. faces: Wozniak et al., 2018; names or owned objects: Scheller & Sui, 2022a, or even fully unfamiliar stimuli: Wozniak & Knoblich, 2019) and paradigms (e.g. matching task: Sui et al., 2012; cross-modal cue integration: e.g. Scheller & Sui, 2022b; Scheller et al., 2023; continuous flash suppression: Macrae et al., 2017; temporal order judgment: Constable et al., 2019; Truong et al., 2017). Using neutral geometric shapes, rather than faces and names, addresses a key challenge in self research: mitigating the influence of stimulus familiarity on results. In addition, these newly learned, simple stimuli can be combined with other paradigms, such as the TOJ paradigm in the current study, to investigate the broader impact of self-processing on perception and cognition.

      To the best of our knowledge, this is the first study showing evidence about the mechanisms that are involved in early attentional selection of socially salient stimuli. Future replications and extensions would certainly be useful, as with any experimental paradigm.

      (3) The comparison between the "social" and "perceptual" tasks remains debatable, as it is challenging to equate the levels of social salience and perceptual salience. In addition, these two tasks differ not only in terms of social decoding processes but also in other aspects such as task difficulty. Whether the observed differences between the tasks can definitively suggest the specificity of social decoding, as the authors claim, needs further confirmation.

      Equating the levels of social and perceptual salience is indeed challenging, but not an aim of the present study. Instead, the present study directly compares the mechanisms and effects of social and perceptual salience, specifically experiment 2. By manipulating perceptual salience (relative colour) and social salience (relative shape association) independently and jointly, and quantifying the effects on processing rates, our study allows to directly delineate the contributions of each of these types of salience. The results suggest additive effects (see also Figure 7). Indeed, the possibility remains that these effects are additive because of the use of different perceptual features, so it would be helpful for future studies to explore whether similar perceptual features lead to (supra-/sub-) additive effects. In either case, the study design allows to directly compare the effects and mechanisms of social and perceptual salience.

      Regarding the social and perceptual decision dimensions, they were not expected to be equated. Indeed, the social decision dimension requires additional retrieval of the associated identity, making it likely more challenging. This additional retrieval is also likely responsible for the slower responses towards the social association compared to the shape itself. However, the motivation to compare the effects of these two decisional dimensions lies in the assumption that the self needs to be task relevant. Some evidence suggests that the self needs to be task-relevant to induce self-prioritization effects (e.g., Woźniak & Knoblich, 2022). However, these studies typically used matching tasks and were powered to detect large effects only (e.g. f = 0.4, n = 18). As it is likely that lacking contribution of decisional processing levels (which interact with task-relevance) will reduce the SPE, smaller self-prioritization effects that result from earlier processing levels may not be detected with sufficient statistical power. Targeting specific processing levels, especially those with relatively early contributions or small effect sizes, requires larger samples (here: n = 70) to provide sufficient power. Indeed, by contrasting the relative attentional selection effects in the present study we find that the self does not need to be task-relevant to produce self-prioritization effects. This is in line with recent findings of prior entry of self-faces (Jubile & Kumar, 2021)

      Reviewer #2 (Recommendations for the authors):

      Suggestions:

      (1) The research questions should be revised to better align with the conclusions. For example, Q2 is phrased as "Does self-relatedness bias attentional selection at the level of the perceptual feature representation (shape) or at the level of the associated identity (social association)," which is unclear in its reference to "levels." A more appropriate phrasing would be whether the self-association bias occurs automatically or whether it depends on explicit social decoding.

      Thank you for this suggestion – we have revised the phrasing accordingly: “Does self-relatedness bias attentional selection automatically or does it require explicit social decoding?”

      (2) After presenting the data, it would be helpful to include one or two sentences summarizing the conclusions drawn from the data and how they relate to the research questions. Currently, readers are left to guess whether the results are consistent with the hypotheses.

      Thank you for this suggestion, which we think will enhance the clarity of the manuscript – we have added summary sentences when presenting the results:<br /> “This cross-experimental parameter inspection revealed that participants exhibited an attentional selection bias towards socially associated information. Interestingly, enhanced processing speed was observed for other-associated rather than self-associated information, a pattern that diverged from our prediction.”

      (1) “Results from experiment 2 demonstrated a faster, more automatic attentional selection for self-associated information when the decision did not require explicit social decoding. When the social identity had to be judged, processing speed for self-associated information decreased. Contrary to the hypothesis that social decoding is necessary for self-prioritization to emerge, these findings suggest that attentional selection can operate automatically to prioritize self-associated information. “

      (2) “Taken together, as also confirmed in the cross-experimental analysis, attentional selection favoured the other-related information when social identity had to be judged. In contrast, perceptual salience, as predicted, led to increased processing speed for the more salient stimulus. “

      (3) The identity of the "other" used in the experiments is unclear, making it uncertain whether the results are self-specific. It would be beneficial to compare the self condition with a control condition, such as a close friend vs. an unfamiliar other. Alternatively, the results may reflect attentional bias for familiar vs. unfamiliar individuals rather than self-specific bias.

      Thank you for this comment. Firstly, we would like to clarify that we have provided participants with a description of who the “other” is (see methods: “At the beginning of this task, participants were told that one of the two geometric shapes that was used in the TOJ task has been assigned to them, and the other shape has been assigned to another participant in the experiment – someone they did not know, but who was of similar age and gender”). We aimed to make the ‘other’ as concrete as possible, while maintaining a ‘stranger’ identity.

      Secondly, this specification is in line with the vast majority of the literature, which typically measures the effects of self-prioritization relative to the association with an unfamiliar other (stranger), or an unfamiliar and familiar other (e.g. friend, family member). They find that processing advantages that affect friend-related stimuli (friend-stimuli being processed faster than stranger-associated stimuli) are likely mediated by self-extension, that is, an association of the friend with the self. As such, SPEs, relative to familiar others, are typically smaller in size (see, e.g., Sui et al., 2012). They, however, are less stable and more variable than the self-prioritization effects measured relative to a stranger (see Scheller & Sui, 2022 JEP:HPP). Importantly, this is driven by the variability of the friend-associated stimulus, rather than the self or other-associated stimulus (see Figure 4 in main text and S5 in supplementary material in Scheller & Sui, 2022: https://durham-repository.worktribe.com/output/1210478/the-power-of-the-self-anchoring-information-processing-across-contexts). Effectively, this would suggest that choosing a familiar other as a reference would not only (a) lead to a smaller effect size, but also (b) be a less stable effect, which likely depends on the association the individual has to the other familiar person. In contrast, by associating the other shape with another participant in this experiment, we provide participants not only with a concrete representation of a stranger, but also maximise our ability to detect true effects, as these are likely to be larger and more stable.

      (4) The key aspects of the procedure (e.g., the order of different conditions) and its rationale need to be clearly explained before or during the presentation of the results. Currently, readers are left to infer certain details.

      Thank you for pointing this out. The methods that provide these details are outlined at the end of the document, however, we agree it would be useful to bring some of these details up. We have therefore revised the methods figure (Figure 3) to include an outline of the task type, order, and trial numbers. Task boxes are colour coded by the conditions that are listed in the results figures of the manuscript. We also added these details to the caption of Figure 3.

      “Task structures of Experiments 1 and 2. Both experiments started with a TOJ baseline task. In Experiment 1, only non-salient targets were presented, while in Experiment 2, perceptually salient and non-salient trials were included. These were presented in randomly intermixed order. Next, targets were associated with social identities. Associations were practiced using the matching task. Following association learning, which attaches social salience to the shapes, participants completed the same TOJ task as before. In Experiment 1, they completed one block using a social decision dimension, and one block using a perceptual decision dimension. The order of these blocks was counterbalanced across participants to reduce the influence of order effects in the results. In Experiment 2, perceptually salient and non-salient stimuli were presented in an intermixed fashion, and participants responded within the social decision dimension. Each task block was preceded by 8 (matching) to 14 (TOJ) practice trials.”

      (5) Certain imprecise terms used to describe the results, such as "slightly," "roughly," and "loosely," create confusion for the readers. The authors should take a clearer stance on the results and provide an explanation for why the data only "slightly," "roughly," or "loosely" support the findings.

      Thank you for highlighting this. We have provided a more concrete wording and details throughout (e.g., “target shapes’ were 30% bigger than the ‘background shapes”).

      Lastly, we have updated the formatting of the manuscript to provide higher fidelity figures, which were previously compromised by file conversion.

    1. Author response:

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

      eLife Assessment

      This provocative manuscript from presents valuable comparisons of the morphologies of Archaean bacterial microfossils to those of microbes transformed under environmental conditions that mimic those present on Earth during the same Eon, although the evidence in support of the conclusions is currently incomplete. The reasons include that taphonomy is not presently considered, and a greater diversity of experimental environmental conditions is not evaluated -- which is important because we ultimately do not know much about Earth's early environments. The authors may want to reframe their conclusions to reflect this work as a first step towards an interpretation of some microfossils as 'proto-cells,' and less so as providing strong support for this hypothesis. 

      Regarding the taphonomic alterations: The editor and reviewers are correct in pointing out this issue. Taphonomic alteration of the microfossils attains special significance in the case of microorganisms, as they lack rigid structures and are prone to morphological alterations during or after their fossilization. We are acutely aware of this issue and have conducted long-term experiments (lasting two years) to observe how cells die, decay, and get preserved. A large section of the manuscript (pages 11 to 20) and a substantial portion of the supplementary information is dedicated to understanding the taphonomic alterations. To the best of our knowledge, these are among the longest experiments done to understand the taphonomic alterations of the cells within laboratory conditions. 

      Recent reports by Orange et al. (1,2)  showed that under favorable environmental conditions, cells could be fossilized rather rapidly with little morphological modifications. We observed a similar phenomenon in this work. Cells in our study underwent rapid encrustation with cations from the growth media. We have analyzed the morphological changes over a period of 18 months. After 18 months, the softer biofilms got encrusted entirely in salt and turned solid (Fig. ). Despite this transformation, morphologically intact cells could still be observed within these structures. This suggests that the cells inhabiting Archaean coastal marine environments could undergo rather rapid encrustation, and their morphological features could be preserved in the geological record with little taphonomic alteration.    

      Regarding the environmental conditions: We are in total agreement with the reviewers that much is unknown about Archaean geology and its environmental conditions. Like the present-day Earth, Archaean Earth certainly had regions that greatly differed in their environmental conditions—volcanic freshwater ponds, brines, mildly halophilic coastal marine environments, and geothermal and hydrothermal vents, to name a few. Our experimental design focuses on one environment we have a relatively good understanding of rather than the rest of the planet, of which we know little. Below, we list our reasons for restricting to coastal marine environments and studying cells under mildly halophilic experimental conditions.  

      (1) Very little continental crust from Haden and early Archaean Eon exists on the presentday Earth. Much of our geochemical understanding of this time period was a result of studying the Pilbara Iron Formations and the Barberton Greenstone Belt. Geological investigations suggest that these sites were coastal marine environments. The salinity of coastal marine environments is higher than that of open oceans due to the greater water evaporation within these environments. Moreover, brines were discovered within pillow basalts within the Barberton greenstone belt, suggesting that the salinity within these sites is higher or similar to marine environments. 

      (2) We are not certain about the environmental conditions that could have supported the origin of life. However, all currently known Archaean microfossils were reported from coastal marine environments (3.8-2.4Ga). This suggests that proto-life likely flourished in mildly halophilic environments, similar to the experimental conditions employed in our study. 

      (3) The chemical analysis of Archaean microfossils also suggests that they lived in saltrich environments, as most, if not all, microfossils are closely associated, often encrusted in a thin layer of salt.  

      However, we concur with the reviewers that our interpretations should be reassessed if Archaean microfossils that greatly differ from the currently known microfossils are to be discovered or if new microfossils are to be reported from environments other than coastal marine sites.

      Public Reviews: 

      Reviewer #1 (Public Review): 

      Summary: 

      Microfossils from the Paleoarchean Eon represent the oldest evidence of life, but their nature has been strongly debated among scientists. To resolve this, the authors reconstructed the lifecycles of Archaean organisms by transforming a Gram-positive bacterium into a primitive lipid vesicle-like state and simulating early Earth conditions. They successfully replicated all morphologies and life cycles of Archaean microfossils and studied cell degradation processes over several years, finding that encrustation with minerals like salt preserved these cells as fossilized organic carbon. Their findings suggest that microfossils from 3.8 to 2.5 billion years ago were likely liposome-like protocells with energy conservation pathways but without regulated morphology. 

      Strengths: 

      The authors have crafted a compelling narrative about the morphological similarities between microfossils from various sites and proliferating wall-deficient bacterial cells, providing detailed comparisons that have never been demonstrated in this detail before. The extensive number of supporting figures is impressive, highlighting numerous similarities. While conclusively proving that these microfossils are proliferating protocells morphologically akin to those studied here is challenging, we applaud this effort as the first detailed comparison between microfossils and morphologically primitive cells. 

      Weaknesses: 

      Although the species used in this study closely resembles the fossils morphologically, it would be beneficial to provide a clearer explanation for its selection. The literature indicates that many bacteria, if not all, can be rendered cell wall-deficient, making the rationale for choosing this specific species somewhat unclear. While this manuscript includes clear morphological comparisons, we believe the authors do not adequately address the limitations of using modern bacterial species in their study. All contemporary bacteria have undergone extensive evolutionary changes, developing complex and intertwined genetic pathways unlike those of early life forms. Consequently, comparing existing bacteria with fossilized life forms is largely hypothetical, a point that should be more thoroughly emphasized in the discussion. 

      Another weak aspect of the study is the absence of any quantitative data. While we understand that obtaining such data for microfossils may be challenging, it would be helpful to present the frequencies of different proliferative events observed in the bacterium used. Additionally, reflecting on the chemical factors in early life that might cause these distinct proliferation modes would provide valuable context. 

      Regarding our choice of using modern organisms or this particular bacterial species: 

      Based on current scientific knowledge, it is logical to infer that cellular life originated as protocells; nevertheless, there has been no direct geological evidence for the existence of such cells on early Earth. Hence, protocells remain an entirely theoretical concept. Moreover, protocells are considered to have been far more primitive than present-day cells. Surprisingly, this lack of sophistication was the biggest challenge in understanding protocells. Designing experiments in which cells are primitive (but not as primitive as non-living lipid vesicles) and still retain a functional resemblance to a living cell does pose some practical challenges. Laboratory experiments with substitute (proxy) protocells almost always come with some limitations. Although not a perfect proxy, we believe protocells and protoplasts share certain characteristics. Having said that, we would like to reemphasize that protoplasts are not protocells. Our reasons for using protoplasts as model organisms and working with this bacterial species (Exiguobacterium Strain-Molly) are based on several scientific and practical criteria listed below.

      (1) Irrespective of cell physiology and intracellular complexity, we believe that protoplasts and protocells share certain similarities in the biophysical properties of their cytoplasm. We explained our reasoning in the manuscript introduction and in our previous manuscripts (Kanaparthi et al., 2024 & Kanaparthi et al., 2023). In short, to be classified as a cell, even a protocell should possess minimal biosynthetic pathways, a physiological mechanism of harvesting free energy from the surrounding (energy-yielding pathways), and a means of replicating its genetic material and transferring it to the daughter cells. These minimal physiological processes could incorporate considerable cytoplasmic complexity. Hence, the biophysical properties of the protocell cytoplasm could have resembled those of the cytoplasm of protoplasts, irrespective of the genomic complexity. 

      (2) Irrespective of their physiology, protoplasts exhibit several key similarities to protocells, such as their inherent inability to regulate their morphology or reproduction. This similarity was pointed out in previous studies (3). Despite possessing all the necessary genetic information, protoplasts undergo reproduction through simple physiochemical processes independent of canonical molecular biological processes. This method of reproduction is considered to have been erratic and rather primitive, akin to the theoretical propositions on protocells. Although protoplasts are fully evolved cells with considerable physiological complexity, the above-mentioned biophysical similarities suggest that the protoplast life cycle could morphologically resemble that of protocells (in no other aspect except for their morphology and reproduction).  

      (3) Physiologically or genomically different species of Gram-positive protoplasts are shown to exhibit similar morphologies. This suggests that when Gram-positive bacteria lose their cell wall and turn into a protoplast,  they reproduce in a similar manner independent of physiological or genome-based differences. As morphology and only morphology is key to our study, at least from the scope of this study, intracellular complexity is not a key consideration. 

      (4) This specific strain was isolated from submerged freshwater springs in the Dead Sea. This isolate and members of this bacterial genus are known to have been well acclimatized to growing in a wide range of salt concentrations and in different salt species. This is important for our study (this and previous manuscript), in which cells must be grown not only at high salt concentrations (1-15%) but in different salts like NaCl, MgCl<sub>2</sub>, and KCl. 

      (5) Our initial interest in this isolate was due to its ability to reduce iron at high salt concentrations. Given that most spherical microfossils are found in Archaean-banded iron formations covered in pyrite, this suggests that these microfossils could have been reducing oxidized iron species like Fe(III). Nevertheless, over the course of our study, we realized the complexities of live cell staining and imaging under anoxic conditions. Given that the scope of the manuscript is restricted only to comparing the morphologies, not the physiology, we abandoned the idea of growing cells under anoxic conditions.  

      Based on these observations, cell physiology may not be a key consideration, at least within the scope of studying microfossil morphology. However, we want to emphasize again that “We do not claim present-day protoplasts are protocells.”  

      Regarding the absence of quantitative data:

      We are unsure what the reviewer meant by the absence of quantitative data. Is it from the cell size/reproductive pathways perspective or from a microfossil/ecological perspective? At the risk of being portrayed in a bad light, we admit that we did not present quantitative data from either of these perspectives. In our defense, this was not due to our lack of effort but due to the practical limitations imposed by our model organism. 

      If the reviewer means the quantitative data regarding cell sizes and morphology: In our previous work, we studied the relationship between protoplast morphology, growth rate, and environmental conditions. In that study, we proposed that the growth rate is one factor that regulates protoplast morphology. Nevertheless, we did not observe uniformity in the sizes of the cells. This lack of uniformity was not just between the replicates but even among the cells grown within the same culture flask or the cells within the same microscopic field. Moreover, cells are often observed to be reproducing either by forming internal or external or by both these processes at the same time. The size and morphological differences among cells within a growth stage could be explained by the physiological and growth rate heterogenicity among cells. 

      Bacterial growth curves and their partition into different stages (lag, log & stationary), in general, represent the growth dynamics of an entire bacterial population. Nevertheless, averaging the data obscures the behavior of individual cells (4,5). It is known that genetically identical cells within a single bacterial population could exhibit considerable cell-to-cell variation in gene expression (6,7) and growth rates (8). The reason for such stochastic behavior among monoclonal cells has not been well understood. In the case of normal cells, morphological manifestation of these variations is restricted by a rigid cell wall. Given the absence of a cell wall in protoplasts, we assume such cell-to-cell variations in growth rate is manifested in cell morphology. This makes it challenging to quantitatively determine variations in cell sizes or the size increase in a statically robust manner, even in monoclonal cells. 

      Although this lack of uniformity in cell sizes should not be perceived as a limitation, this behavior is consistently observed among microfossils. Spherical microfossils of similar morphology but different sizes were reported from different microfossil sites (9,10). In this regard, both protoplasts and microfossils are very similar. 

      If the reviewer means the quantitative data from an ecological perspective: 

      Based on the elemental composition and the isotopic signatures of the organic carbon, we can deduce if these structures are of biological origin or not. However, any further interpretation of this data to annotate these microfossils to a particular physiology group is fraught with errors. Hence, we refrain from making any inferences about the physiology and ecological function of these microfossils. This lack of clarity on the physiology of microfossils reduces the chance of quantitative studies on their ecological functions. Moreover, we would like to re-emphasize that the scope of this work is restricted to morphological comparison and is not targeted at understanding the ecological function of these microfossils. This narrow objective also limits the nature of the quantitative data we could present.

      Moreover, developing a quantitative understanding of some phenomena could be technically challenging. Many theories on the origin of life, like chemical evolution, started with the qualitative observation that lightning could mediate the synthesis of biologically relevant organic carbon. Our quantitative understanding of this process is still being explored and debated even to this day.     

      Reviewer #2 (Public Review): 

      Summary: 

      In summary, the manuscript describes life-cycle-related morphologies of primitive vesiclelike states (Em-P) produced in the laboratory from the Gram-positive bacterium Exiguobacterium Strain-Molly) under assumed Archean environmental conditions. Em-P morphologies (life cycles) are controlled by the "native environment". In order to mimic Archean environmental conditions, soy broth supplemented with Dead Sea salt was used to cultivate Em-Ps. The manuscript compares Archean microfossils and biofilms from selected photos with those laboratory morphologies. The photos derive from publications on various stratigraphic sections of Paleo- to Neoarchean ages. Based on the similarity of morphologies of microfossils and Em-Ps, the manuscript concludes that all Archean microfossils are in fact not prokaryotes, but merely "sacks of cytoplasm". 

      Strengths: 

      The approach of the authors to recognize the possibility that "real" cells were not around in the Archean time is appealing. The manuscript reflects the very hard work by the authors composing the Em-Ps used for comparison and selecting the appropriate photo material of fossils. 

      Weaknesses: 

      While the basic idea is very interesting, the manuscript includes flaws and falls short in presenting supportive data. The manuscript makes too simplistic assumptions on the "Archean paleoenvironment". First, like in our modern world, the environmental conditions during the Archean time were not globally the same. Second, we do not know much about the Archean paleoenvironment due to the immense lack of rock records. More so, the Archean stratigraphic sections from where the fossil material derived record different paleoenvironments: shelf to tidal flat and lacustrine settings, so differences must have been significant. Finally, the Archean spanned 2.500 billion years and it is unlikely that environmental conditions remained the same. Diurnal or seasonal variations are not considered. Sediment types are not considered. Due to these reasons, the laboratory model of an Archean paleoenvironment and the life therein is too simplistic. Another aspect is that eucaryote cells are described from Archean rocks, so it seems unlikely that prokaryotes were not around at the same time. Considering other fossil evidence preserved in Archean rocks except for microfossils, the many early Archean microbialites that show baffling and trapping cannot be explained without the presence of "real cells". With respect to lithology: chert is a rock predominantly composed of silica, not salt. The formation of Em-Ps in the "salty" laboratory set-up seems therefore not a good fit to evaluate chert fossils. Formation of structures in sediment is one step. The second step is their preservation. However, the second aspect of taphonomy is largely excluded in the manuscript, and the role of fossilization (lithification) of Em-Ps is not discussed. This is important because Archean rock successions are known for their tectonic and hydrothermal overprint, as well as recrystallization over time. Some of the comparisons of laboratory morphologies with fossil microfossils and biofilms are incorrect because scales differ by magnitudes. In general, one has to recognize that prokaryote cell morphologies do not offer many variations. It is possible to arrive at the morphologies described in various ways including abiotic ones. 

      Regarding the simplistic presumptions on the Archaean Eon environmental conditions, we provided a detailed explanation of this issue in our response to the eLife evaluation. In short, we agree with the reviewer that little is known about the Archaean Eon environmental conditions at a planetary scale. Hence, we restricted our study to one particular environment of which we had a comparatively good understanding. The Archaean Eon spanned 2.5 billion years. However, most of the microfossil sites we discussed in the manuscript are older than 3 billion years, with one exception (2.4 billion years old Turee Creek microfossils). We presume that conditions within this niche (coastal marine) environment could not have changed greatly until 2Ga, after which there have been major changes in the ocean salt composition and salinities.

      In the manuscript, we discussed extensively the reasons for restricting our study to these particular environmental conditions. Further explanations of these choices are presented in our response to the eLife evaluation (also see our previous manuscript). In short, the fact that all known microfossils are restricted to coastal marine environments justifies the experimental conditions employed in our study. Nevertheless, we agree with the reviewer that all lab-based studies involve some extent of simplification. This gap/mismatch is even wider when it comes to studies involving origin or early life on Earth.

      We are not arguing that prokaryotes are not around at this time. The key message of the manuscript is that they are present, but they have not developed intracellular mechanisms to regulate their morphology and remained primitive in this aspect.  

      The sizes of the microfossils and cells from our study were similar in most cases. However, we agree with the reviewer that they deviated considerably in some cases, for example, S70, S73, and S83. These size variations are limited to sedimentary structures like laminations rather than cells. These differences should be expected as we try to replicate the real-life morphologies of biofilms that could have extended over large swats of natural environments in a 2ml volume chamber slide. More specifically, in Fig. S70, there is a considerable size mismatch. But, in Fig. S73, the sizes were comparable between A & C (of course, the size of our reproduction did not match B). In the case of Fig. S83, we do not see a huge size mismatch.      

      Reviewer #1 (Recommendations For The Authors): 

      We would like to provide several suggestions for changes in text and additions to data analysis. 

      39-41: It has been stated that reconstructing the lifecycle is the only way of understanding the nature of these microfossils. First of all, I would rephrase this to 'the most promising way', as there are always multiple approaches to comparing phenomena. 

      We agree with the reviewer's suggestion. The suggested changes have been made (line 41). 

      125: Please rephrase "under the environmental condition of early Earth" to "under experimental conditions possibly resembling the conditions of the Paleoarchean Eon". Now it sounds like the exact environmental conditions have been produced, which has already been debated in the discussion. 

      We agree with the reviewer's suggestion. The suggested changes have been made (line 127). 

      125: Please mention the fold change in size, the original size in numbers, and whether this change is statistically significant. 

      In the above sections of this document, we explained our reservations about presenting the exact number.

      128: Have you found a difference in the relative percentages of modes of reproduction? In other words, is there a difference in percentage between forming internal daughter cells or a string of external daughter cells? 

      We explained our reservations about presenting the exact number above. But this has been extensively discussed in our accompaining manuscript. We want to reemphasize that the scope of this manuscript is restricted to comparing morphologies rather than providing a mechanistic explanation of the reproduction process. 

      151: A similar model for endocytosis has already been described in proliferating wall-less cells (Kapteijn et al., 2023). In the discussion, please compare your results with the observations made in that paper. 

      This is an oversight on our part. The manuscript suggested by the reviewer has now been added (line 154 & 155).  

      163: Please use another word for uncanny. We suggest using 'strong resemblance'. 

      We changed this according to the reviewers' suggestion (line 168). 

      433: Please elaborate on why the results are not shown. This sounds like a statement that should be substantiated further. 

      To observe growth and simultaneously image the cells, we conducted these experiments in chamber slides (2ml volume). Over time, we observed cells growing and breaking out of the salt crust (Fig. S86, S87 & Movie 22) and a gradual increase in the turbidity of the media. Although not quantitative, this is a qualitative indication of growth. We did not take precise measurements for several reasons. This sample is precious; it took us almost two years to solidify the biofilm completely, as shown in Fig. S84A. Hence, it was in limited supply, which prevented us from inoculating these salt crusts into large volumes of fresh media. Given a long period of starvation, these cells often exhibited a long lag phase (several days), and there wasn't enough volume to do OD measurements over time. 

      We also crushed the solidified biofilm with a sterile spatula before transferring it into the chamber slide with growth media. This resulted in debris in the form of small solid particles, which interfered with our OD measurements. These practical considerations made it challenging to determine the growth precisely. Despite these challenges, we measured an OD of 4 in some chamber slides after two weeks of incubation. Given that these measurements were done haphazardly, we chose not to present this data. 

      456: Could you please double-check whether the description is correct for the figure? 8C and 8D are part of Figure 8B, but this is stated otherwise in the description. 

      We thank the reviewer for pointing it out. It has now been rectified (line 461-472).

      Reviewer #2 (Recommendations For The Authors): 

      We thank Reviewer #2  for carefully reading the manuscript and such an elaborate list of questions. The revisions suggested have definitely improved the quality of the manuscript. Here, we would like to address some of the questions that came up repeatedly below. One frequently asked question is regarding the letters denoting the individual figures within the images. For comparison purposes, we often reproduced previously published images. To maintain a consistent figure style, we often have to block the previous denotations with an opaque square and give a new letter. 

      The second question that appeared repeatedly below is the missing scale bars in some of the images within a figure. We often did not include a scale bar in the images when this image is an enlarged section of another image within the same figure.     

      Title: Please consider being more precise in the title. Microfossils are only one fossil group of "oldest life". Perhaps better: "On the nature of some microfossils in Archean rocks". (see also Line 37).  

      Authors’ response: The title conveys a broader message without quantitative insinuations. If our manuscript had been titled "On the nature of all known Archaean microfossils,” we should have agreed with the reviewer's suggestion and changed it to "On the nature of some microfossils in Archean rocks". As it is not, we respectfully decline to make this modification.     

      Abstract:  

      Line 41: "one way", not "the only way" 

      We agree with the reviewer’s comment, and necessary changes have been made (line 41).  

      Introduction: 

      Line 58f: "oldest sedimentary rock successions", not "oldest known rock formations". There are rocks of much older ages, but those are not well preserved due to metamorphic overprint, or the rocks are igneous to begin with. Minor issue: please note that "formations" are used as stratigraphic units, not so much to describe a rock succession in the field. 

      We agree with the reviewer’s comment and have made necessary changes (line 58).

      Line 67: Microfossils are widely accepted as evidence of life. Please rephrase. 

      We agree with the reviewer’s comment, and necessary changes have been made.

      Line 71 - 74: perhaps add a sentence of information here.

      We agree with the reviewer’s comment, and necessary changes have been made (line 71).

      Line 76: which "chemical and mineralogical considerations"? 

      This has been rephrased to “Apart from the chemical and δ<sup>13</sup>C-biomass composition” (line 76).

      Line 84ff: This is a somewhat sweeping statement. Please remember that there are microbialites in such rocks that require already a high level of biofilm organization. The existence of cyanobacteria-type microbes in the Archean is also increasingly considered. 

      We are aware of literature that labeled the clusters of Archaean microfossils as biofilms and layered structures as microbialites or stromatolite-like structures. However, the use of these terms is increasingly being discouraged. A more recent consensus among researchers suggests annotating these structures simply as sedimentary structures, as microbially induced sedimentary structures (MISS). 

      We respectfully disagree with the reviewer’s comment that Archaean microfossils exhibit a high level of biofilm organization. We are not aware of any studies that have conducted such comprehensive research on the architecture of Archaean biofilms. We are not even certain if these clusters of Archaean cells could even be labeled as biofilms in the true sense of the term. We presently lack an exact definition of a biofilm. In our study, we do see sedimentation and bacteria and their encapsulation in cell debris. From a broader perspective, any such aggregation of cells enclosed in cell debris could be annotated as a biofilm. However, more in-depth studies show that biofilm is not a random but a highly organized structure. Different bacterial species have different biofilm architectures and chemical composition. The multispecies biofilms in natural environments are even more complex. We do agree with the reviewer that these structures could broadly be labeled as biofilms, but we presently lack a good, if any, understanding of the Archaean biofilm architecture. 

      Regarding the annotation of microfossils as cyanobacteria, we respectfully disagree with the reviewer. This is not a new concept. Many of the Archaean microfossils were annotated as cyanobacteria at the time of their discovery. This annotation is not without controversy. With the advent of genome-based studies, researchers are increasingly moving away from this school of thought.  

      Line 101ff: The conditions on early Earth are unknown - there are many varying opinions. Perhaps simply state that this laboratory model simulates an Archean Earth environment of these conditions outlined. 

      This is a good idea. We thank the reviewer for this suggestion, and we made appropriate changes. 

      Line 112: manuscript to be replaced by "paper"? 

      This change has been made (line 114).

      Line 116: "spanned years" - how many years? 

      We now added the number of years in the brackets (line 118).

      Results: 

      Line 125: see comment for 101ff. 

      we made appropriate changes. 

      Figure 1: Caption: Please write out ICV the first time this abbreviation is used. Images: Note that some lettering appears to not fit their white labels underneath. (G, H, I, J0, and M). 

      We apologize; this is an oversight on our part. We now spell complete expansion of ICV, the first time we used this abbreviation. 

      We took these images from previously published work (references in the figure legend), so we must block out the previous figure captions. This is necessary to maintain a uniform style throughout the manuscript. 

      Line 152ff.: here would be a great opportunity to show in a graph the size variations of modern ICVs and to compare the variations with those in the fossil material. 

      In the above sections of this document, we explained our reservations about presenting the exact number.

      Line 159f.: Fig.1K - what is to see here? Maybe a close-up or - better - a small sketch would help? 

      Fig. 1K shows the surface depressions formed during the vesicle formation. The surface characteristics of EM-P and microfossils is very similar.   

      Line 161f.: reference?  

      The paragraph spanning lines 159 to 172 discusses the morphological similarities between EM-P and SPF microfossils. We rechecked the reference no 35 (Delarue 2019). This is the correct reference. We do not see a mistake if the reviewer meant the reference to the figures.    

      Line 164ff.: A question may be asked, how many fossils of the Strelley Pool population would look similar to the "modeled" ones. Questions may rise in which way the environmental conditions control such morphology variations. Perhaps more details? 

      This relationship between the environmental conditions and the morphology is discussed extensively in our previous work (11).  

      Line 193: what is meant by "similar discontinuous distribution of organic carbon"?

      This statement highlights similarities between EM-P and microfossils. The distribution of cytoplasm within the cells is not uniform. There are regions with and devoid of cytoplasm, which is quite unusual for bacteria. Some previous studies argued that this could indicate that these organic structures are of abiotic origin. Here, we show that EMP-like cells could exhibit such a patchy distribution of cytoplasm within the cell.    

      Line 218 - 291: The observations are very nice, however, the figures of fossil material in Figures 3 A, B, and C appear not to conform. Perhaps use D, E and I to K. Also, S48 does not show features as described here (see below).  

      We did not completely understand the reviewer’s question. As mentioned in the figure legend, both the microfossils and the cells exhibit string with spherical daughter cells within them. Moreover, there are also other similarities like the presence of hollow spherical structures devoid of organic carbon. We also saw several mistakes in the Fig. S48 legend. We have rectified them, and we thank the reviewer for pointing them out.   

      Line 293f: Title with "." at end?

      This change has been made.

      Line 298: predominantly in chert. In clastic material preservation of cells and pores is unlikely due to the common lack of in situ entombment by silica. 

      We rephrased this entire paragraph to better convey our message. Either way, we are not arguing that hollow pore spaces exist. As the reviewer mentioned, they will, of course, be filled up with silica. In this entire paragraph, we did not refer to hollow spaces. So, we are not entirely sure what the question was.     

      Line 324, 328-349: Please see below comments on the supplementary figures 51-62. Some of the interpretations of morphologies may be incorrect. 

      Please find our response to the reviewer’s comments on individual figures below.  

      Figure 5 A to D look interesting, however E to J appear to be unconvincing. What is the grey frame in D (not the white insert). 

      The grey color is just the background that was added during the 3D rendering process.  

      Figure 6 does not appear to be convincing. - Erase? 

      We did not understand the reviewer’s reservations regarding this figure. Images A-F within the figure show the gradual transformation of cells into honeycomb-like structures, and images G-J show such structures from the Archaean that are closely associated with microfossils. Moreover, we did not come up with this terminology (honeycomb-like). Previous manuscripts proposed it.  

      Line 379ff: S66 and 69, please see my comments below. Microfossils "were often discovered" in layers of organic carbon. 

      Please see our response below.   

      Line 393-403: Laminae? There are many ways to arrive at C-rich laminae, especially, if the material was compressed during burial. Basically, any type of biofilm would appear as laminae, if compressed. The appearance of thin layers is a mere coincidence. Note that the scale difference in S70, S73, as well as S83, is way too high (cm versus μm!) to allow any such sweeping conclusions. What are α- and β- laminations, the one described by Tice et al.? The arguments are not convincing.

      We propose that cells be compressed to form laminae. We answered this question above about the differences in the scale bars. Yes, we are referring to α- and β- laminations described by Tice et al.       

      Figure 7: This is an interesting figure, but what are the arguments for B and C, the fossil material, being a membrane? Debris cannot be distinguished with certainty at this scale in the insert of C. B could also be a shriveled-up set of trichomes.  

      We agree with the reviewer that debris cannot be definitely differentiated. Traditionally, annotations given to microfossil structures such as biofilm, intact cells, or laminations were all based on morphological similarities with existing structures observed in microorganisms. Given that the structures observed in our study are very similar to the microfossil structures, it is logical to make such inferences. Scales in A & B match perfectly well. The structure in C is much larger, but, as we mentioned in reply to one of the reviewer’s earlier questions, some of the structures from natural environments could not be reproduced at scale in lab experiments. Working in a 2 ml chamber slides does impose some restrictions.   

      Figure 8: The figure does not show any honeycomb patterns. The "gaps" in the Moodies laminae are known as lenticular particles in biofilms. They form by desiccated and shriveledup biofilm that mineralizes in situ. Sometimes also entrapped gases induce precipitation. Note also that the modelled material shows a kind of skin around the blobs that are not present in the Moodies material.  

      We agree that entrapped gas bubbles could have formed lenticular gaps. In the manuscript, we did not discount this possibility. However, if that is the case, one should explain why we often find clumps of organic carbon within these gaps. As we presented a step-by-step transformation of parallel layers of cells into laminations, which also had similar lenticular gaps, we believe this is a more plausible way such structures could have formed. In the end, there could have been more than one way such structures could have been formed. 

      We do see the honeycomb pattern in the hollow gaps. Often, the 3D-rendering of the STED images obscures some details. Hence, in the figure legend, we referred to the supplementary figures also show the sequence of steps involved in the formation of such a pattern.      

      Line 405-417: During deposition of clastic sediment any hollow space would be compressed during burial and settling. It is rare that additional pore space (except between the graingrain-contacts) remains visible, especially after consolidation. The exception would be if very early silicification took place filling in any pore space. What about EPS being replaced by mineralic substance? The arguments are not convincing. 

      We are suggesting that EPS or cell debris is rapidly encrusted by cations from the surrounding environment and gets solidified into rigid structures. This makes it possible for the structures to be preserved in the fossil record. We believe that hollow structures like the lenticular gaps will be filled up with silica. 

      We do not agree with the reviewer’s comment that all biological structures will be compressed. If this is true, there should be no intact microfossils in the Archaean sedimentary structures, which is definitely not the case.      

      Line 419-430: Lithification takes place within the sediment and therefore is commonly controlled by the chemistry of pore water and chemical compounds that derive from the dissolution of minerals close by. Another aspect to consider is whether "desiccation cracks" on that small scale may be artefacts related to sample preparation (?).  

      We agree that desiccation cracks could have formed during the sample preparation for SEM imaging, as this involves drying the biofilms. However, we observed that the sample we used for SEM is a completely solidified biofilm (Fig. S84), so we expect little change in its morphology during drying. Moreover, visible cracks and pointy edges were also observed in wet samples, as shown in Fig. S87.        

      Line 432 - 439: Please see comments on the supplementary material below.

      Please find our response to the reviewer’s comments on individual figures below.  

      Discussion:  

      Line 477f: "all known microfossil morphologies" - is this a correct statement? Also, would the Archean world provide only one kind of "EM-P type"? Morphologies of prokaryote cells (spherical, rod-shaped, filamentous) in general are very simple, and any researcher of Precambrian material will appreciate the difficulties in concluding on taxonomy. There are papers that investigate putative microfossils in chert as features related to life cycles. Microfossil-papers commonly appear not to be controversial give and take some specific cases.  

      We made a mistake in using the term “all known microfossil morphologies.” We have now changed it to “all known spherical microfossils” from this statement (line 483). However, we do not agree with the statement that microfossil manuscripts tend not to be controversial. Assigning taxonomy to microfossils is anything but controversial. This has been intensely debated among the scientific community.     

      Line 494-496: This statement should be in the Introduction.

      We agree with the reviewer’s comment. In an earlier version of the manuscript this statement was in the introduction. To put this statement in its proper context, it needs to be associated with a discussion about the importance of morphology in the identification of microfossils. The present version of the manuscript do not permit moving an entire paragraph into the introduction. Hence, we think making this statement in the discussion section is appropriate. 

      Line 484ff. The discussion on biogenicity of microfossils is long-standing (e.g., biogenicity criteria by Buick 1990 and other papers), and nothing new. In paleontology, modern prokaryotes may serve as models but everyone working on Archean microfossils will agree that these cannot correspond to modern groups. An example is fossil "cyanobacteria" that is thought to have been around already in the early Archean. While morphologically very similar to modern cyanobacteria, their genetic information certainly differed - how much will perhaps remain undisclosed by material of that high age.  

      Yes, we agree with the reviewer that there has been a longstanding conflict on the topic of biogenicity of microfossils. However, we have never come across manuscripts suggesting that modern microorganisms should only be used as models. If at all, there have been numerous manuscripts suggesting that these microfossils represent cyanobacteria, streptomycetes, and methanotrophs. Regarding the annotation of microfossils as cyanobacteria, we addressed this issue in one of the previous questions raised by the reviewer.    

      Line 498ff: Can the variation of morphology and sizes of the EM-Ps be demonstrated statistically? Line 505ff are very speculative statements. Relabeling of what could be vesicles as "microfossils" appears inappropriate. Contrary to what is stated in the manuscript, the morphologies of the Dresser Formation vesicles do not resemble the S3 to S14 spheroids from the Strelley Pool, the Waterfall, and Mt Goldsworthy sites listed in the manuscript. The spindle-shaped vesicles in Wacey et al are not addressed by this manuscript. What roles in mineral and element composition would have played diagenetic alteration and the extreme hydrothermal overprint and weathering typical for Dresser material? S59, S60 do not show what is stated, and the material derives from the Barberton Greenstone Belt, not the Pilbara.

      Please see the comments below regarding the supplementary images. 

      We did not observe huge variations in the cell morphology. Morphologies, in most cases, were restricted to spherical cells with intracellular vesicles or filamentous extensions. Regarding the sizes of the cells, we see some variations. However, we are reluctant to provide exact numbers. We have presented our reasons above.

      We respectfully disagree with the reviewer’s comments. We see quite some similarities between Dresser formation microfossils and our cells. Not just the similarities, we have provided step-by-step transformation of cells that resulted in these morphologies. We fail to see what exactly is the speculation here. The argument that they should be classified as abiotic structures is based on the opinion that cells do form such structures. We clearly show here that they can, and these biological structures resemble Dresser formation microfossils more closely than the abiotic structures. 

      Regarding the figures S3-S14. We think they are morphologically very similar. Often, it's not just comparing both images or making exact reproductions (which is not possible). We should focus on reproducing the distinctive morphological features of these microfossils.  

      We agree with the reviewer that we did not reproduce all the structures reported by Wacey’s original manuscript, such as spherical structures. We are currently preparing another manuscript to address the filamentous microfossils. These spindle-like structures will be addressed in this subsequent work. 

      We agree with the reviewer, we often have difficulties differentiating between cells and vesicles. This is not a problem in the early stages of growth. During the log phase, a significant volume of the cell consists of the cytoplasm, with hollow vesicles constituting only a minor volume (Fig. 1B or S1A). During the later growth stages (Fig. 1E7F or S11), cells were almost hollow, with numerous daughter cells within them. These cells often resemble hollow vesicles rather than cells. However, given these are biologically formed structures, and one could argue that these vesicles are still alive as there is still a minimal amount of cytoplasm (Fig. S27). Hence, we should consider them as cells until they break apart to release daughter cells. 

      Regarding Figures S59 and S60, we did not claim either of these microfossils is from Pilbara Iron Formations. The legend of Figure S59 clearly states that these structures are from Buck Reef Chert, originally reported by Tice et al., 2006 (Figure 16 in the original manuscript). The legend of Figure S60 says these structures were originally reported by Barlow et al., 2018, from the Turee Creek Formation. 

      Line 546f and 552: The sites including microfossils in the Archean represent different paleoenvironments ranging from marine to terrestrial to lacustrine. References 6 and 66 are well-developed studies focusing on specific stratigraphic successions, but cannot include information covering other Archean worlds of the over 2.5 Ga years Archean time.  

      All the Archaean microfossils reported to date are from volcanic coastal marine environments. We are aware that there are rocky terrestrial environments, but no microfossils have been reported from these sites. We are unaware of any Archaean microfossils reported from freshwater environments. 

      Line 570ff: The statements may represent a hypothesis, but the data presented are too preliminary to substantiate the assumptions.

      We believe this is a correct inference from an evolutionary, genomic, and now from a morphological perspective. 

      Figures:  

      Please check all text and supplementary figures, whether scale bars are of different styles within the figure (minor quibble). 

      S3 (no scale in C, D); S4, S5: Note that scale bars are of different styles. 

      We believe we addressed this issue above. 

      S6 D: depressions here are well visible - perhaps exchange with a photo in the main text? Note that scale bars are of different styles.  

      We agree that depressions are well visible in E. The same image of EM-P cell in E is also present in Fig. 1D in the main text.   

      S7: Scale bars should all be of the same style, if anyhow possible. Scale in D? 

      We believe we addressed this issue above. 

      S9: F appears to be distorted. Is the fossil like this? The figure would need additional indicators (arrows) pointing toward what the reader needs to see - not clear in this version. More explanation in the figure caption could be offered. 

      We rechecked the figure from the original publication to check if by mistake the figure was distorted during the assembly of this image. We can assure you that this is not the case. We are not sure what further could be said in the figure legend.     

      S13: What is shown in the inserts of D and E that is also visible in A and B? Here a sketch of the steps would help. 

      We did not understand the question.  

      S14: Scale in A, B? 

      We believe we addressed this issue above. 

      S15: Scales in A, E, C, D 

      We believe we addressed this issue above. 

      S16: scales in D, E, G, H, I, J?  

      We believe we addressed this issue above. 

      S17: "I" appears squeezed, is that so? If morphology is an important message, perhaps reduce the entire figure so it fits the layout. Note that labels A, B, C, and D are displaced. 

      As shown in several subsequent figures, the hollow spherical vesicles are compressed first into honeycomb-like structures, and they often undergo further compression to form lamination-like structures. Such images often give the impression that the entire figure is squashed, but this is not the case. If one examines the figure closely, you could see perfectly spherical vesicles together with laterally sqeezed structures. Regarding the figure labels, we addressed this issue above. 

      S18: The filamentous feature in C could also be the grain boundaries of the crystals. Can this be excluded as an interpretation? Are there microfossils with the cell membranes? That would be an excellent contribution to this figure. Note that scale bars are of different styles.

      If this is a one-off observation, we could have arrived at the reviewer's opinion. But spherical cells in a “string of beads” configuration were frequently reported from several sites, to be discounted as mere interpretation.    

      S19: The morphologies in A - insert appear to be similar to E - insert in the lower left corner. The chain of cells in A may look similar to the morphologies in E - insert upper right of the image. B - what is to see here? D - the inclusions do not appear spherical (?). Does C look similar to the cluster with the arrow in the lower part of image E? Note that scale bars are of different styles (minor quibble). A, B, C, and D appear compressed. Perhaps reduce the size of the overall image?  

      The structures highlighted (yellow box) in C are similar to the highlighted regions in E—the agglomeration of hollow vesicles. It is hard to get understand this similarity in one figure. The similarities are apparent when one sees the Movie 4 and Fig. S12, clearly showing the spherical daughter cells within the hollow vesicle. We now added the movie reference to the figure legend.    

      S20: A appears not to contribute much. The lineations in B appear to be diagenetic. However, C is suitable. Perhaps use only C, D, E? 

      We believe too many unrecognizable structures are being labeled as diagenetic. Nevertheless, we do not subscribe to the notion that these are too lenient interpretations. These interpretations are justified as such structures have not been reported from live cells. This is the first study to report that cells could form such structures. As we now reproduced these structures, an alternate interpretation that these are organic structures derived from microfossils should be entertained. 

      S 21: Note that scale bars are of different styles.  

      We believe we addressed this issue above. 

      S22: Perhaps add an arrow in F, where the cell opened, and add "see arrow" in the caption? Is this the same situation as shown in C (white arrow)? What is shown by the white arrow in A? Note that scale bars are of different styles.

      We did the necessary changes.  

      S23: In the caption and main text, please replace "&" with "and" (please check also the other figure captions, e.g. S24). Note that scale bars are of different styles. What is shown in F? A, D - what is shown here?

      We replaced “&” with “and.”  

      S24: Note that scale bars are of different styles. Note that Wacey et al. describe the vesicles as abiotic not as "microfossils"; please correct in figure caption [same also S26; 25; 28].

      We are aware of Prof. Dr. Wacey’s interpretations. We discuss it at length in the discussion section our manuscript. Based on the similarities between the Dresser formation structures and structures formed by EM-P, we contest that these are abiotic structures.  

      S25: Appears compressed; note different scale bars. 

      We believe we addressed this issue above. 

      S28: The label in B is still in the upper right corner; scale in D? What is to see in rectangles (blue and red) in A, B? In fossil material, this could be anything. 

      These figures are taken from a previous manuscript cited in the figure legend. We could not erase or modify these figures.  

      S33: "L"ewis; G appears a bit too diffuse - erase? Note that scale bars are of different styles.

      We believe we addressed this issue above. 

      S34: This figure appears unconvincing. Erase? 

      There are considerable similarities between the microfossils and structures formed by EM-P. If the reviewer expands a bit on what he finds unconvincing, we can address his reservations.    

      S35: It would be more convincing to show only the morphological similarities between the cell clusters. B and C are too blurry to distinguish much. Scales in D to F and in sketches? A appears compressed (?). 

      We rechecked the original manuscript to see if image A was distorted while making this figure, but this is not the case. Regarding B & C, cells in this image are faint as they are hollow vesicles and, by nature, do not generate too much contrast when imaged with a phase-contrast microscope. There are some limitations on how much we can improve the contrast. We now added scale bars for D-I. Similarly, faint hollow vesicles can be seen in Fig. S21 C & D, and Fig. 3H.  

      S36: Very nice; in B no purple arrow is visible. Note that scale bars are of different styles. S37 and S36 are very much the same - fuse, perhaps?  

      We are sorry for the confusion. There are purple arrows in Fig. S37B-D. 

      S38: this is a more unconvincing figure - erase? 

      Unconvincing in wahy sense. There are considerable similarities between the microfossils and structures formed by EM-P. If the reviewer expands a bit on what he finds unconvincing, we can address his reservations.

      S39: white rectangle in A? Arrow in A? Note that scale bars are of different styles.

      These are some of the unavoidable remnants from the image from the original publication. 

      S40: in F: CM, V = ?; Note that scale bars are of different style. 

      It’s an oversite on our part. We now added the definitions to the figure legaend. We thank the reviewer for pointing it out.  

      S41: Rectangles in D, E, F, G can be deleted? Scales and labels missing in photos lower right. 

      Those rectangles are added by the image processing software to the 3Drendered images. Regarding the missing scale bars in H & I they are the magnified regions of F. The scale bar is already present in F.   

      S42: appears compressed. G could be trimmed. Labels too small; scale in G? 

      This is a curled-up folded membrane. We needed to lower the resolution of some images to restrict the size of the supplement to journal size restrictions. It is not possible to present 85 figures in high resolution. But we assure you that the image is not laterally compressed in any manner.   

      S43: This figure appears to be unconvincing. Reducing to pairing B, C, D with L, K? Spherical inclusions in B? Scales in E to G? Similar in S44: A, B, E only? Note that scale bars are of different styles. 

      Figures I to K are important. They show not just the morphological similarities but also the sequence of steps through which such structures are formed. We addressed the issue of the scale bars above.  

      S45: A, B, and C appear to show live or subrecent material. How was this isolated of a rock? Note that scale bars are of different styles.  

      It is common to treat rocks with acids to dissolve them and then retrieve organic structures within them. This technique is becoming increasingly common. The procedure is quite extensively discussed in the original manuscript. We don’t see much differences in the scale bars of microfossils and EM-P cells, they are quite similar. 

      S46: A: what is to see here? Note that scale bars are of different styles. 

      There are considerable similarities between the folded fabric like organic structures with spherical inclusions and structures formed by EM-P. If the reviewer expands a bit on what he finds unconvincing, we can address his reservations.    

      S47: Perhaps enlarge B and erase A. Note that scale bars are of different styles. 

      S48: Image B appears to show the fossil material - is the figure caption inconsistent? There are no aggregations visible in the boxes in A. H is described in the figure caption but missing in the figure. Overall, F and G do not appear to mirror anything in A to E (which may be fossil material?). 

      S51; S52 B, C, E; S53: these figures appear unconvincing - erase? 

      Unconvincing in what sense? The structures from our study are very similar to the microfossils.   

      S54: North "Pole; scale bars in A to C =? 

      These figures were borrowed from an earlier publication referenced in the figure legend. That is the reason for the differences in the styles of scale bars.  

      S55: D and E appear not to contribute anything. Perhaps add arrow(s) and more explanation? Check the spelling in the caption, please. 

      D & E show morphological similarities between cells from our study and microfossils (A).   

      S56: Hexagonal morphologies may also be a consequence of diagenesis. Overall, perhaps erase this figure?  

      I certainly agree that could be one of the reasons for the hexagonal morphologies. Such geometric polygonal morphologies have not been observed in living organisms. Nevertheless, as you can see from the figure, such morphologies could also be formed by living organisms. Hence, this alternate interpretation should not be discounted.   

      S57: The figure caption needs improvement. Please add more description. What show arrows in A, what are the numbers in A? What is the relation between the image attached to the right side of A? Is this a close-up? Note that scale bars are of different styles. 

      We expanded a bit on our original description of the figure. However, we request the reviewer to keep in mind that the parts of the figure are taken from previous publication. We are not at liberty to modifiy them, like removing the arrows. This imposes some constrains. 

      S58: There are no honeycomb-shaped features visible. What is to see here? Erase this figure? 

      Clearly, one can see spherical and polygonal shapes within the Archaean organic structures and mat-like structures formed by EM-P.  

      S59 and S60: What is to see here? - Erase? 

      Clearly, one can see spherical and polygonal shapes within the Archaean organic structures and mat-like structures formed by EM-P in Fig. S59. Further disintegration of these honeycomb shaped mats into filamentous struructures with spherical cells attached to them can be seen in both Archaean organic structures and structures formed by EM-P.   

      S61: This figure appears to be unconvincing. B and F may be a good pairing. Note that scale bars are of different styles.  

      There are considerable similarities between the microfossils and structures formed by EM-P. If the reviewer expands a bit on what he finds unconvincing, we might be able to address his reservations.     

      S62: This figure appears to be unconvincing - erase?

      There are considerable similarities between the microfossils and structures formed by EM-P. If the reviewer expands a bit on what he finds unconvincing, we might be able to address his reservations.     

      S66: This figure is unconvincing - erase? 

      There are considerable similarities between the microfossils and structures formed by EM-P. If the reviewer expands a bit on what he finds unconvincing, we might be able to address his reservations.    

      S68: Scale in B, D, and E? 

      Image B is just a magnified image of a small portion of image A. Hence, there is no need for an additional scale bar. The same is true for images D and E. 

      S69: This figure appears to be unconvincing, at least the fossil part. Filamentous features are visible in fossil material as well, but nothing else. 

      We are not sure what filamentous features the reviewer is referring to. Both the figures show morphologically similar spherical cells covered in membrane debris.    

      S70 [as well as S82]: Good thinking here, but scales differ by magnitudes (cm to μm). Erase this figure? Very similar to Figure S73: Insert in C has which scale in comparison to B? Note that scale bars are of different styles.  

      We realize the scale bars are of different sizes. In our defense, our experiments are conducted in 1ml volume chamber slides. We don’t have the luxury of doing these experiments on a scale similar to the natural environments. The size differences are to be expected. 

      S71: Scale in E? 

      Image E is just a magnified image of a small portion of image D. Hence, we believe a scale bar is unnecessary. 

      S72: Scale in insert?  

      The insert is just a magnified region of A & C

      S75: This figure appears to be unconvincing. This is clastic sediment, not chert. Lenticular gaps would collapse during burial by subsequent sediment. - Erase? 

      Regarding the similarities, we see similar lenticular gaps within the parallel layers of organic carbon in both microfossils, and structures formed by EM-P.

      S76: A, C, D do not look similar to B - erase? Similar to S79, also with respect to the differences in scale. Erase? 

      Regarding the similarities, we see similar lenticular gaps within the parallel layers of organic carbon in both microfossils, and structures formed by EM-P. We believe we addressed the issue of scale bars above. 

      S80: A appears to be diagenetic, not primary. Erase? 

      These two structures share too many resemblances to ignore or discount just as diagenic structures - Raised filamentous structures originate out of parallel layers of organic carbon (laminations), with spherical cells within this filamentous organic carbon.  

      S85: What role would diagenesis play here? This figure appears unconvincing. Erase?

      We do believe that diagenesis plays a major role in microfossil preservation. However, we also do not suscribe to the notion that we should by default assign diagenesis to all microfossil features. Our study shows that there could be an alternate explanation to some of the observations.  

      S86 and S87: These appear unconvincing. What is to see here? Erase? 

      The morphological similarities between these two structures. Stellarshaped organic structures with strings of spherical daughter cells growing out of them.  

      S88: Does this image suggest the preservation of "salt" in organic material once preserved in chert?  

      That is one inference we conclude from this observation. Crystaline NaCl was previously reported from within the microfossil cells.    

      S89: What is to see here? Spherical phenomena in different materials? 

      At present, the presence of honeycomb-like structures is often considered to have been an indication of volcanic pumice. We meant to show that biofilms of living organisms could result in honeycomb-shaped patterns similar to volcanic pumice.

      References 

      Please check the spelling in the references. 

      We found a few references that required corrention. We now rectified them. 

      References  

      (1) Orange F, Westall F, Disnar JR, Prieur D, Bienvenu N, Le Romancer M, et al. Experimental silicification of the extremophilic archaea pyrococcus abyssi and methanocaldococcus jannaschii: Applications in the search for evidence of life in early earth and extraterrestrial rocks. Geobiology. 2009;7(4). 

      (2) Orange F, Disnar JR, Westall F, Prieur D, Baillif P. Metal cation binding by the hyperthermophilic microorganism, Archaea Methanocaldococcus Jannaschii, and its effects on silicification. Palaeontology. 2011;54(5). 

      (3) Errington J. L-form bacteria, cell walls and the origins of life. Open Biol. 2013;3(1):120143. 

      (4) Cooper S. Distinguishing between linear and exponential cell growth during the division cycle: Single-cell studies, cell-culture studies, and the object of cell-cycle research. Theor Biol Med Model. 2006; 

      (5) Mitchison JM. Single cell studies of the cell cycle and some models. Theor Biol Med Model. 2005; 

      (6) Kærn M, Elston TC, Blake WJ, Collins JJ. Stochasticity in gene expression: From theories to phenotypes. Nat Rev Genet. 2005; 

      (7) Elowitz MB, Levine AJ, Siggia ED, Swain PS. Stochastic gene expression in a single cell. Science. 2002; 

      (8) Strovas TJ, Sauter LM, Guo X, Lidstrom ME. Cell-to-cell heterogeneity in growth rate and gene expression in Methylobacterium extorquens AM1. J Bacteriol. 2007; 

      (9) Knoll AH, Barghoorn ES. Archean microfossils showing cell division from the Swaziland System of South Africa. Science. 1977;198(4315):396–8. 

      (10) Sugitani K, Grey K, Allwood A, Nagaoka T, Mimura K, Minami M, et al. Diverse microstructures from Archaean chert from the Mount Goldsworthy–Mount Grant area, Pilbara Craton, Western Australia: microfossils, dubiofossils, or pseudofossils? Precambrian Res. 2007;158(3–4):228–62. 

      (11) Kanaparthi D, Lampe M, Krohn JH, Zhu B, Hildebrand F, Boesen T, et al. The reproduction process of Gram-positive protocells. Sci Rep. 2024 Mar 25;14(1):7075.

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript describes two new sets of data involving budgerigar hearing: 1) auditory-nerve tuning curves (ANTCs), which are considered the 'gold standard' measure of cochlear tuning, and 2) stimulus-frequency otoacoustic emissions (SFOAEs), which are a more indirect measure (requiring some assumptions and transformations to infer cochlear tuning) but which are non-invasive, making them easier to obtain and suitable for use in all species, including humans. By using a tuning ratio (relating ANTC bandwidths and SFOAE delay) derived from another bird species (chicken), the authors show that the tuning estimates from the two methods are in reasonable agreement with each other over the range of hearing tested (280 Hz to 5.65 kHz for the ANTCs), and both show a slow monotonic increase in cochlear tuning quality over that range, as expected. These new results are then compared with (much) older existing behavioral estimates of frequency selectivity in the same species.

      Strengths:

      This topic is of interest, because there are some indications from the older behavioral literature that budgerigars have a region of best tuning, which the current authors refer to as an 'acoustic fovea', at around 4 kHz, but that beyond 5 kHz the tuning degrades. Earlier work has speculated that the source could be cochlear or higher (e.g., Okanoya and Dooling, 1987). The current study appears to rule out a cochlear source to this phenomenon.

      Weaknesses:

      The conclusions are rendered questionable by two major problems.

      The first problem is that the study does not provide new behavioral data, but instead relies on decades-old estimates that used techniques dating back to the 1970s, which have been found to be flawed in various ways. The behavioral techniques that have been developed more recently in the human psychophysical literature have avoided these well-documented confounds, such as nonlinear suppression effects (e.g., Houtgast, https://doi.org/10.1121/1.1913048; Shannon, https://doi.org/10.1121/1.381007; Moore, https://doi.org/10.1121/1.381752), perceptual confusion between pure-tone maskers and targets (e.g., Neff, https://doi.org/10.1121/1.393678), beats and distortion products produced by interactions between simultaneous maskers and targets (e.g., Patterson, https://doi.org/10.1121/1.380914), unjustified assumptions and empirical difficulties associated with critical band and critical ratio measures (Patterson, https://doi.org/10.1121/1.380914), and 'off-frequency listening' phenomena (O'Loughlin and Moore, https://doi.org/10.1121/1.385691). More recent studies, tailored to mimic to the extent possible the techniques used in ANTCs, have provided reasonably accurate estimates of cochlear tuning, as measured with ANTCs and SFOAEs (Shera et al., 2003, 2010; Sumner et al., 2010). No such measures yet exist in budgerigars, and this study does not provide any. So the study fails to provide valid behavioral data to support the claims made.

      The second, and more critical, problem can be observed by considering the frequencies at which the old behavioral data indicate a worsening of tuning. From the summary shown in the present Fig. 2, the conclusion that behavioral frequency selectivity worsens again at higher frequencies is based on four data points, all with probe frequencies between 5 and 6 kHz. Comparing this frequency range with the absolute thresholds shown in Fig. 3 (as well as from older budgerigar data) shows it to be on the steep upper edge of the hearing range. Thus, we are dealing not so much with a fovea as the point where hearing starts to end. The point that anomalous tuning measures are found at the edge of hearing in the budgerigar has been made before: Saunders et al. (1978) state in the last sentence of their paper that "the size of the CB rapidly increases above 4.0 kHz and this may be related to the fact that the behavioral audibility curve, above 4.0 kHz, loses sensitivity at the rate of 55 dB per octave."

      Hearing abilities are hard to measure accurately on the upper frequency edge of the hearing range, in humans as well as in other species. The few attempts to measure human frequency selectivity at that upper edge have resulted in quite messy data and unclear conclusions (e.g., Buus et al., 1986, https://doi.org/10.1007/978-1-4613-2247-4_37). Indeed, the only study to my knowledge to have systematically tested human frequency selectivity in the extended high frequency range (> 12 kHz) seems to suggest a substantial broadening, relative to the earlier estimates at lower frequencies, by as much as a factor of 2 in some individuals (Yasin and Plack, 2005; https://doi.org/10.1121/1.2035594) - in other words by a similar amount as suggested by the budgerigar data. The possible divergence of different measures at the extreme end of hearing could be due to any number of factors that are hard to control and calibrate, given the steep rate of threshold change, leading to uncontrolled off-frequency listening potential, the higher sound levels needed to exceed threshold, as well as contributions from middle-ear filtering. As a side note, in the original ANTC data presented in this study, there are actually very few tuning curves at or above 5 kHz, which are the ones critical to the argument being forwarded here. To my eye, all the estimates above 5 kHz in Fig. 3 fall below the trend line, potentially also in line with poorer selectivity going along with poorer sensitivity as hearing disappears beyond 6 kHz.

      The basic question posed in the current study title and abstract seems a little convoluted (why would you expect a behavioral measure to reflect cochlear mechanics more accurately than a cochlear-based emissions measure?). A more intuitive (and likely more interesting) way of framing the question would be "What is the neural/mechanical source of a behaviorally observed acoustic fovea?" Unfortunately, this question does not lend itself to being answered in the budgerigar, as that 'fovea' turns out to be just the turning point at the end of the hearing range. There is probably a reason why no other study has referred to this as an acoustic fovea in the budgerigar.

      Overall, a safe interpretation of the data is that hearing starts to change (and becomes harder to measure) at the very upper frequency edge, and not just in budgerigars. Thus, it is difficult to draw any clear conclusions from the current work, other than that the relations between ANTC and SFOAEs estimates of tuning are consistent in budgerigar, as they are in most (all?) other species that have been tested so far.

    2. Author response:

      We genuinely appreciate the reviewer critiques of our submitted paper, “Otoacoustic emissions but not behavioral measurements predict cochlear-nerve frequency tuning in an avian vocal-communication specialist.” We are planning a number of changes based on the reviewers’ helpful comments that we feel will substantially improve the manuscript and clarify its implications.

      We will add more support for the claim that budgerigars show unusual patterns of behavioral frequency tuning compared to other species. The original manuscript relied on previously published studies of budgerigar critical bands and psychophysical tuning curve to make this point (e.g., Fig. 1). Critical bands and psychophysical tuning curves have unfortunately not been studied in many bird species. Consequently, it was somewhat unclear (based on the information originally presented) whether the “unusual” behavioral tuning results shown in Fig. 1 reflect a hearing specialization in budgerigars or perhaps simply a general avian pattern attributable to declining audibility above 3-4 kHz (a point raised by both reviewers). Fortunately, behavioral critical-ratio results are available from a broader range of species. Albeit a less direct correlate of tuning, the results clearly highlight the unique hearing abilities of budgerigars in relation to other bird species as elaborated upon below.

      The critical ratio is the threshold signal-to-noise ratio for tone detection in wideband noise and partly depends on peripheral tuning bandwidth. Critical ratios have been studied in over a dozen bird species, the vast majority of which show similar thresholds to one another and monotonically increasing critical ratios for higher frequencies (by 2-3 dB/octave, similar to most mammals; reviewed by Dooling et al., 2000). By contrast, budgerigar critical ratios diverge markedly from other species at mid-to-high frequencies, with ~8 dB lower (more sensitive) thresholds from 3-4 kHz (Dooling & Saunders, 1975; Okanoya & Dooling, 1987; Farabaugh 1988; see Figs 5 & 6 in Okanoya & Dooling, 1987). The unusual critical-ratio function in budgerigars is not attributable to the audiogram and was hypothesized by Okanoya and Dooling (1987) to reflect specialized cochlear tuning or perhaps central processing mechanisms. A brief discussion of these studies will be added to the introduction, along with a new figure panel (for Fig. 1) illustrating these intriguing species differences in critical ratios.

      Another question was raised as to whether the simultaneous-masking paradigms and classic methods used to estimate behavioral tuning in budgerigars should be considered as valid, given newer forward-masking and notched-noise alternatives. We will expand the discussion of this issue in the revised manuscript. First, many of the methods from the classic budgerigar studies remain widely used in animal behavioral research (e.g., critical bands and ratios: Yost & Shofner, 2009; King et al., 2015; simultaneous masking: Burton et al., 2018). We therefore believe that it remains highly relevant to test and report whether these methods can accurately predict cochlear tuning. While forward-masking behavioral results are hypothesized to more accurately predict cochlear tuning humans (Shera et al., 2002; Joris et al., 2011; Sumner et al., 2018), evidence from nonhumans is controversial, with one study showing a closer match of forward-masking results to auditory-nerve tuning (ferret: Sumner et al., 2018), but several others showing a close match for simultaneous masking results (e.g., guinea pig, chinchilla, macaque; reviewed by Ruggero & Temchin, 2005; see Joris et al., 2011 for macaque auditory-nerve tuning). Moreover, forward- and simultaneous-masking results can often be equated with a simple scaling factor (e.g., Sumner et al., 2018). Given no real consensus on an optimal behavioral method, and seemingly limited potential for the “wrong” method to fundamentally transform the shape of the behavioral tuning quality function, it seems reasonable to accept previously published behavioral tuning estimates as essentially valid while also discussing limitations and remaining open to alternative interpretations.

      We will add clarification throughout the revision as to the specific behavioral measures used to quantify tuning in budgerigars (i.e., critical bands, psychophysical tuning curve, and critical ratios). This avoids potentially disparaging alternative behavioral methods that have not been tested. That the budgerigar behavioral data are “old” seems not particularly relevant considering that the methods are still used in animal behavioral research as noted previously. Rather, it seems important to clarify the specific behavioral techniques used to estimate budgerigar’s frequency tuning in the revised paper.

      Finally, we plan to add discussion of the apical-basal transition from the mammalian otoacoustic-emission literature, as suggested by reviewer 1, including how this concept might apply in budgerigars and other birds.

      References not already cited in the preprint:

      Burton JA, Dylla ME, Ramachandran R. Frequency selectivity in macaque monkeys measured using a notched-noise method. Hear Res. 2018 Jan;357:73-80. doi: 10.1016/j.heares.2017.11.012.

      King J, Insanally M, Jin M, Martins AR, D'amour JA, Froemke RC. Rodent auditory perception: Critical band limitations and plasticity. Neuroscience. 2015 Jun 18;296:55-65. doi: 10.1016/j.neuroscience.2015.03.053.

      Yost WA, Shofner WP. Critical bands and critical ratios in animal psychoacoustics: an example using chinchilla data. J Acoust Soc Am. 2009 Jan;125(1):315-23. doi: 10.1121/1.3037232. PMID: 19173418; PMCID: PMC2719489.

    1. Reviewer #3 (Public review):

      Summary:

      Using a combination of optogenetic tools and single-photon calcium imaging, the authors collected a set of high-quality data and conducted thorough analyses to demonstrate the importance of cholinergic input to the prelimbic cortex in probabilistic spatial learning, particularly pertaining to threat.

      Strengths:

      Given the importance of the findings, this paper will appeal to a broad audience in the systems, behavioural, and cognitive neuroscience community.

      Weaknesses:

      I have only a few concerns that I consider need to be addressed.

      (1) Can the authors describe the basic effect of cholinergic stimulation on PL neurons' activity, during pretraining, probabilistic, and random stages? From the plot, it seems that some neurons had an increase and others had a decrease in activity. What are the percentages for significant changes in activities, given the intensity of stimulation? Were these changes correlated with the neurons' selectivity for the location? If they happen to have the data, a dose-response plot would be very helpful too.

      (2) Figure 2B: The current sorting does not show the effects of puff and LED well. Perhaps it's best to sort based on the 'puff with no stim' condition in the middle, by the total activity in 2s following the puff, and then by the timing in the rise/drop of activity (from early to late). This way perhaps the optogenetic stimulation would appear more striking. Figure 3Aa and Ba have the same issue: by the current sorting, the effects are not very visible at all. Perhaps they want to consider not showing the cells that did not show the effect of puff and/or LED.

      Also, I would recommend that the authors use ABCD to refer to figure panels, instead of Aa, Ab, etc. This is very hard to follow.

      (3) The authors mentioned the laminar distribution of ACh receptors in discussion. Can they show the presence/absence of topographic distribution of neurons responding to puff and/or LED?

      (4) Figure 2C seems to show only neurons with increased activity to an air puff. It's also important to know how neurons with an inhibitory response to air-puff behaved, especially given that in tdTomato animals, the proportion of these neurons was the same as excitatory responders.

      (5) Page 5, lines 107 and 110: Following 2-way ANOVA, the authors used a 'follow-up 1-way rmANOVA' and 'follow-up t-test' instead of post hoc tests (e.g. Tukey's). This doesn't seem right. Please use post hoc tests instead to avoid the problem of multiple comparisons.

      (6) Figure 1H: in the running speed analysis, were all trials included, both LED+ and LED-? This doesn't affect the previous panels in Figure 1 but it could affect 1H. Did stimulation affect how the running speed recovers?

      On a related note, does a surprising puff/omission affect the running speed on the subsequent trial?

      (7) On Page 7, line 143, it says "In the absence of LED stimulation, the magnitude of their puff-evoked activity was reduced in ChrimsonR-expressing mice...", but then on line 147 it says "This group difference was not detected without the LED stimulation". I don't follow what is meant by the latter statement, it seems to be conflicting with line 143. The red curves in the left vs right panels do not seem different. The effect of air puff seems to differ, but is this due to a higher gray curve ('no puff' condition) in the ChrimsonR group?

      (8) Did the neural activity correlate with running speed? Since the main finding was the absence of difference in running speed modulation by probability in ChrimsonR mice, one would expect to see PL cells showing parallel differences.

    2. Author response:

      (1) We do not know that the mechanism mediating the behavioral changes observed involves acetylcholine at all. (Reviewer 1)

      The reviewer rightly pointed out the co-release of acetylcholine (ACh) and GABA from cholinergic terminals. We believe that the detected behavioral changes are because of the augmentation of this innate mixed chemical signal. We agree that identifying the receptor specificity is an essential next step; however, addressing this point requires a currently unavailable research tool to block cholinergic receptors for a few hundred milliseconds. This temporal specificity is vital because acetylcholine is released in the medial prefrontal cortex (mPFC) on two distinct timescales, the slow release over tens of minutes from the task onset and the fast release time-locked to salient stimuli (TelesGrilo Ruivo et al., 2017). Moreover, the former slow signal is far more robust than the latter phasic signal. The pharmacological experiments suggested by the reviewer will suppress both the tonic and phasic signals, making it difficult to interpret the results. Given the rapid technological advancement in this field, we hope to investigate the underlying mechanisms in detail in the future. 

      (2) It is unclear whether mPFC cells are signaling predictions versus prediction errors. (Reviewer 2)

      As the reviewer pointed out, mPFC cells signal the prediction of imminent outcomes (Baeg et al., 2001; Mulder et al., 2003; Takehara-Nishiuchi and McNaughton, 2008; Kyriazi et al., 2020).

      However, the key difference between prediction signals and prediction error signals is their time course. The prediction signals begin to arise before the actual outcome occurs, whereas the prediction error signals are emitted after subjects experience the presence or absence of the expected outcome. In all our analyses, cell activity was normalized by the activity during the 1-second window before the threat site entry (i.e., the reveal of actual outcome; Lines 655-659). Also, all the statistical comparisons were made on the normalized activity during the 500-msec window, starting from the threat site entry (Lines 669670). Because this approach isolated the change in cell activity after the actual outcome, we interpret the data in Figure 4C as prediction error signals. 

      (3) The task does not fully dissociate place field coding. (Reviewer 2)

      The present analysis included several strategies to dissociate outcome selectivity from location selectivity (Figure 4). First, we collapsed cell activity on two threat sites to suppress the difference in cell activity between the sites. Second, our analysis compared how cell activity at the same location differed depending on whether outcomes were expected or surprising (Figure 4C). Nevertheless, we can use the present data to investigate the spatial tuning of mPFC cells. Indeed, an earlier version of this manuscript included some characterizations of spatial tuning. However, these data were deemed irrelevant and distracting when this manuscript was reviewed for publication in a different journal. As such, these data were removed from the current version. We are in the process of publishing another paper focusing on the spatial tuning of mPFC cells and their learning-dependent changes. 

      (4) The basic effects of cholinergic terminal stimulation on mPFC cell activity are unclear. (Reviewers 1, 3)

      We acknowledge the lack of characterization of the optogenetic manipulation of cholinergic terminals on mPFC cell activity outside the task context. As outlined in the discussion section (Lines 309-321), cholinergic modulation of mPFC cell activity is highly complex and most likely varies depending on behavioral states. In addition, because we intended to augment naturally occurring threatevoked cholinergic terminal responses (Tu et al., 2022), our optogenetic stimulation parameters were 3-5 times weaker than those used to evoke behavioral changes solely by the optogenetic stimulation of cholinergic terminals (Gritton et al., 2016). Based on these points, we validated the optogenetic stimulation based on its effects on air-puff-evoked cell activity during the task (Figure 2C, 2D). 

      (5) Some choices of statistical analyses are questionable (Reviewers 1, 3)

      We used the Kolmogorov-Smirnov (KS) test to investigate whether the distribution of cell responses differed between the two groups (Figure 2D) or changed with learning (Figure 3Ac, 3Bc). As seen in Figure 3Aa, some mPFC cells increased calcium activity in response to air-puffs, while others decreased. We expected that the manipulation or learning would alter these responses. If they are strengthened, the increased responses will become more positive, while the decreased responses will become more negative. If they are weakened, both responses will become closer to 0. Under such conditions, the shape of the distribution of cell response will change but not the median. The KS test can detect this, but not other tests sensitive to the difference in medians, such as Wilcoxon rank-sum tests. In Figure 2D, KS tests were applied to the independently sampled data from the control and ChrimsonRexpressing mice. In Figure 3Ac and 3Bc, we used all cells imaged in the first and fifth sessions. Considering that ~50% of them were longitudinally registered on both days, we acknowledge the violation in the assumption of independent sampling. In Figure 1D, we detected significant interaction between the group and sessions. Several approaches are appropriate to demonstrate the source of this interaction. We chose to conduct one-way ANOVA separately in each group to demonstrate the significant change in % adaptive choice across the sessions in the control group but not the ChrimsonR group. The cutoff for significance was adjusted with the Bonferroni correction in follow-up paired t-tests used in Figure 1F.

    1. Author response:

      Reviewer #1 (Public review):

      This manuscript presents an interesting exploration of the potential activation mechanisms of DLK following axonal injury. While the experiments are beautifully conducted and the data are solid, I feel that there is insufficient evidence to fully support the conclusions made by the authors.

      In this manuscript, the authors exclusively use the puc-lacZ reporter to determine the activation of DLK. This reporter has been shown to be induced when DLK is activated. However, there is insufficient evidence to confirm that the absence of reporter activation necessarily indicates that DLK is inactive. As with many MAP kinase pathways, the DLK pathway can be locally or globally activated in neurons, and the level of DLK activation may depend on the strength of the stimulation. This reporter might only reflect strong DLK activation and may not be turned on if DLK is weakly activated. The results presented in this manuscript support this interpretation. Strong stimulation, such as axotomy of all synaptic branches, caused robust DLK activation, as indicated by puc-lacZ expression. In contrast, weak stimulation, such as axotomy of some synaptic branches, resulted in weaker DLK activation, which did not induce the puc-lacZ reporter. This suggests that the strength of DLK activation depends on the severity of the injury rather than the presence of intact synapses. Given that this is a central conclusion of the study, it may be worthwhile to confirm this further. Alternatively, the authors may consider refining their conclusion to better align with the evidence presented.

      We wish to further clarify a striking aspect of puc-lacZ induction following injury: it is bimodal. It is either induced (in various injuries that remove all synaptic boutons), or not induced, including in injuries that spared only 1-2 remaining boutons. This was particularly evident for injuries that spared the NMJ on muscle 29, which is comprised of only a few boutons. In some instances, only a single bouton was evident on muscle 29. While our injuries varied enormously in the number of branches and boutons that were lost, we did not see a comparable variability in puc-lacZ induction.  In the revision we will include additional images to better demonstrate this observation.

      The reviewer (and others) fairly point out that our current study focuses on puc-lacZ as a reporter of Wnd signaling in the cell body. We consider this to be a downstream integration of events in axons that are more challenging to detect. It is striking that this integration appears strongly sensitized to the presence of spared synaptic boutons. Examination of Wnd’s activation in axons and synapses is a goal for our future work.

      As noted by the authors, DLK has been implicated in both axon regeneration and degeneration. Following axotomy, DLK activation can lead to the degeneration of distal axons, where synapses are located. This raises an important question: how is DLK activated in distal axons? The authors might consider discussing the significance of this "synapse connection-dependent" DLK activation in the broader context of DLK function and activation mechanisms.

      While it has been noted that inhibition of DLK can mildly delay Wallerian degeneration (Miller et al., 2009), this does not appear to be the case for retinal ganglion cell axons following optic nerve crush (Fernandes et al., 2014). It is also not the case for Drosophila motoneurons and NMJ terminals following peripheral nerve injury (Xiong et al., 2012; Xiong and Collins, 2012). Instead, overexpression of Wnd or activation of Wnd by a conditioning injury leads to an opposite phenotype - an increase in resiliency to Wallerian degeneration for axons that have been previously injured (Xiong et al., 2012; Xiong and Collins, 2012). The downstream outcome of Wnd activation is highly dependent on the context; it may be an integration of the outcomes of local Wnd/DLK activation in axons with downstream consequences of nuclear/cell body signaling.  The current study suggests some rules for the cell body signaling, however, how Wnd is regulated at synapses and why it promotes degeneration in some circumstances but not others are important future questions.

      For the reviewer’s suggestion, it is interesting to consider DLK’s potential contributions to the loss of NMJ synapses in a mouse model of ALS (Le Pichon et al., 2017; Wlaschin et al., 2023). Our findings suggest that the synaptic terminal is an important locus of DLK regulation, while dysfunction of NMJ terminals is an important feature of the ‘dying back’ hypothesis of disease etiology (Dadon-Nachum et al., 2011; Verma et al., 2022). We propose that the regulation of DLK at synaptic terminals is an important area for future study, and may reveal how DLK might be modulated to curtail disease progression. Of note, DLK inhibitors are in clinical trials (Katz et al., 2022; Le et al., 2023; Siu et al., 2018), but at least some have been paused due to safety concerns (Katz et al., 2022). Further understanding of the mechanisms that regulate DLK are needed to understand whether and how DLK and its downstream signaling can be tuned for therapeutic benefit.

      Reviewer #2 (Public review):

      Summary:

      The authors study a panel of sparsely labeled neuronal lines in Drosophila that each form multiple synapses. Critically, each axonal branch can be injured without affecting the others, allowing the authors to differentiate between injuries that affect all axonal branches versus those that do not, creating spared branches. Axonal injuries are known to cause Wnd (mammalian DLK)-dependent retrograde signals to the cell body, culminating in a transcriptional response. This work identifies a fascinating new phenomenon that this injury response is not all-or-none. If even a single branch remains uninjured, the injury signal is not activated in the cell body. The authors rule out that this could be due to changes in the abundance of Wnd (perhaps if incrementally activated at each injured branch) by Wnd, Hiw's known negative regulator. Thus there is both a yet-undiscovered mechanism to regulate Wnd signaling, and more broadly a mechanism by which the neuron can integrate the degree of injury it has sustained. It will now be important to tease apart the mechanism(s) of this fascinating phenomenon. But even absent a clear mechanism, this is a new biology that will inform the interpretation of injury signaling studies across species.

      Strengths:

      (1) A conceptually beautiful series of experiments that reveal a fascinating new phenomenon is described, with clear implications (as the authors discuss in their Discussion) for injury signaling in mammals.

      (2) Suggests a new mode of Wnd regulation, independent of Hiw.

      Weaknesses:

      (1) The use of a somatic transcriptional reporter for Wnd activity is powerful, however, the reporter indicates whether the transcriptional response was activated, not whether the injury signal was received. It remains possible that Wnd is still activated in the case of a spared branch, but that this activation is either local within the axons (impossible to determine in the absence of a local reporter) or that the retrograde signal was indeed generated but it was somehow insufficient to activate transcription when it entered the cell body. This is more of a mechanistic detail and should not detract from the overall importance of the study

      We agree. The puc-lacZ reporter tells us about signaling in the cell body, but whether and how Wnd is regulated in axons and synaptic branches, which we think occurs upstream of the cell body response, remains to be addressed in future studies.

      (2) That the protective effect of a spared branch is independent of Hiw, the known negative regulator of Wnd, is fascinating. But this leaves open a key question: what is the signal?

      This is indeed an important future question, and would still be a question even if Hiw were part of the protective mechanism by the spared synaptic branch. Our current hypothesis (outlined in Figure 4) is that regulation of Wnd is tied to the retrograde trafficking of a signaling organelle in axons. The Hiw-independent regulation complements other observations in the literature that multiple pathways regulate Wnd/DLK (Collins et al., 2006; Feoktistov and Herman, 2016; Klinedinst et al., 2013; Li et al., 2017; Russo and DiAntonio, 2019; Valakh et al., 2013). It is logical for this critical stress response pathway to have multiple modes of regulation that may act in parallel to tune and restrain its activation.

      Reviewer #3 (Public review):

      Summary:

      This manuscript seeks to understand how nerve injury-induced signaling to the nucleus is influenced, and it establishes a new location where these principles can be studied. By identifying and mapping specific bifurcated neuronal innervations in the Drosophila larvae, and using laser axotomy to localize the injury, the authors find that sparing a branch of a complex muscular innervation is enough to impair Wallenda-puc (analogous to DLK-JNK-cJun) signaling that is known to promote regeneration. It is only when all connections to the target are disconnected that cJun-transcriptional activation occurs.

      Overall, this is a thorough and well-performed investigation of the mechanism of spared-branch influence on axon injury signaling. The findings on control of wnd are important because this is a very widely used injury signaling pathway across species and injury models. The authors present detailed and carefully executed experiments to support their conclusions. Their effort to identify the control mechanism is admirable and will be of aid to the field as they continue to try to understand how to promote better regeneration of axons.

      Strengths:

      The paper does a very comprehensive job of investigating this phenomenon at multiple locations and through both pinpoint laser injury as well as larger crush models. They identify a non-hiw based restraint mechanism of the wnd-puc signaling axis that presumably originates from the spared terminal. They also present a large list of tests they performed to identify the actual restraint mechanism from the spared branch, which has ruled out many of the most likely explanations. This is an extremely important set of information to report, to guide future investigators in this and other model organisms on mechanisms by which regeneration signaling is controlled (or not).

      Weaknesses:

      The weakest data presented by this manuscript is the study of the actual amounts of Wallenda protein in the axon. The authors argue that increased Wnd protein is being anterogradely delivered from the soma, but no support for this is given. Whether this change is due to transcription/translation, protein stability, transport, or other means is not investigated in this work. However, because this point is not central to the arguments in the paper, it is only a minor critique.

      We agree and are glad that the reviewer considers this a minor critique; this is an area for future study. In Supplemental Figure 1 we present differences in the levels of an ectopically expressed GFP-Wnd-kinase-dead transgene, which is strikingly increased in axons that have received a full but not partial axotomy. We suspect this accumulation occurs downstream of the cell body response because of the timing. We observed the accumulations after 24 hours (Figure S1F) but not at early (1-4 hour) time points following axotomy (data not shown). Further study of the local regulation of Wnd protein and its kinase activity in axons is an important future direction.

      As far as the scope of impact: because the conclusions of the paper are focused on a single (albeit well-validated) reporter in different types of motor neurons, it is hard to determine whether the mechanism of spared branch inhibition of regeneration requires wnd-puc (DLK/cJun) signaling in all contexts (for example, sensory axons or interneurons). Is the nerve-muscle connection the rule or the exception in terms of regeneration program activation?

      DLK signaling is strongly activated in DRG sensory neurons following peripheral nerve injury (Shin et al., 2012), despite the fact that sensory neurons have bifurcated axons and their projections in the dorsal spinal cord are not directly damaged by injuries to the peripheral nerve. Therefore it is unlikely that protection by a spared synapse is a universal rule for all neuron types. However the molecular mechanisms that underlie this regulation may indeed be shared across different types of neurons but utilized in different ways. For instance, nerve growth factor withdrawal can lead to activation of DLK (Ghosh et al., 2011), however neurotrophins and their receptors are regulated and implemented differently in different cell types. We suspect that the restraint of Wnd signaling by the spared synaptic branch shares a common underlying mechanism with the restraint of DLK signaling by neurotrophin signaling. Further elucidation of the molecular mechanism is an important next step towards addressing this question.

      Because changes in puc-lacZ intensity are the major readout, it would be helpful to better explain the significance of the amount of puc-lacZ in the nucleus with respect to the activation of regeneration. Is it known that scaling up the amount of puc-lacZ transcription scales functional responses (regeneration or others)? The alternative would be that only a small amount of puc-lacZ is sufficient to efficiently induce relevant pathways (threshold response).

      While induction of puc-lacZ expression correlates with Wnd-mediated phenotypes, including sprouting of injured axons (Xiong et al., 2010), protection from Wallerian degeneration (Xiong et al., 2012; Xiong and Collins, 2012) and synaptic overgrowth (Collins et al., 2006), we have not observed any correlation between the degree of puc-lacZ induction (eg modest, medium or high) and the phenotypic outcomes (sprouting, overgrowth, etc). Rather, there appears to be a striking all-or-none difference in whether puc-lacZ is induced or not induced. There may indeed be a threshold that can be restrained through multiple mechanisms. We posit in figure 4 that restraint may take place in the cell body, where it can be influenced by the spared bifurcation.

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    1. Author response:

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

      Reviewer 1:

      We thank the reviewer for their comments and suggestions. We have made several edits to the paper to address these comments, including the addition of several new control experiments, corrections to mislabeled figures in Fig 2, and other additions to improve the clarity of several figures.

      This work is missing several controls that are necessary to substantiate their claims. My most important concern is that the optogenetic screen for neurons that alter pathogenic lawn occupancy does not have an accompanying control on non-pathogenic OP50 bacteria. Hence, it remains unclear whether these neuronal inhibition experiments lead to pathogen-specific or generalized lawn-leaving alterations. For strains that show statistical differences between - and + ATR conditions, the authors should perform follow-up validation experiments on non-pathogenic OP50 lawns to ensure that the observed effect is PA14-specific. Similarly, neuronal inhibition experiments in Figures 5E and H are only performed with naïve animals on PA14 - we need to see the latency to re-entry on OP50 as well, to make general conclusions about these neurons' role in pathogen-specific avoidance.

      We have added data from new control experiments to Fig. S1 (subfigures B, C) for both exit and re-entry dynamics on OP50. We find that inhibition of neurons produces different effects on both lawn entry and exit on PA14 compared to OP50. We observed that inhibition of neurons failed to change the re-entry dynamics for any of the lines which showed delayed latency to re-entry on PA14. Our results suggest that the neural control of re-entry dynamics we see are PA14 specific.

      My second major concern is regarding the calcium imaging experiments of candidate neurons involved in lawn re-entry behavior. Although the data shows that AIY, AVK, and SIA/SIB neurons all show reduced activity following pathogen exposure, the authors do not relate these activity changes to changes in behavior. Given the well-established links between these cells and forward locomotion, it is essential to not only report differences in activity but also in the relationship between this activity and locomotory behavior. If animals are paused outside of the pathogen lawn, these neurons may show low activity simply because the animals are not moving forward. Other forward-modulated neurons may also show this pattern of reduced activity if the animals remain paused. Given that the authors have recorded neural activity before and after contact with pathogenic bacteria in freely moving animals, they should also provide an analysis of the relationship between proximity to the lawn and the activity of these neurons.

      In response, we added an additional supplementary figure S7 to illustrate the role of each neuron in navigational control and added text to the discussion to better explain the role of each neuron type in the regulation of re-entry, in light of our previously published work on SIA in speed control.

      This work is missing methodological descriptions that are necessary for the correct interpretation of the results shown here. Figure 2 suggests that the determination of statistical significance across the optogenetic inhibition screen will be found in the Methods, but this information is not to be found there. At various points in the text, authors refer to "exit rate", "rate constant", and "entry rate". These metrics seem derived from an averaged measurement across many individual animals in one lawn evacuation assay plate. However "latency to re-entry" is only defined on a per-animal basis in the lawn re-exposure assay. These differences should be clearly stated in the methods section to avoid confusion and to ensure that statistics are computed correctly.

      Additional details have been added to the methods section to provide more in depth information on the statistical analysis performed. In brief, the latency to re-entry is calculated in the same way across all assays – re-entry events across replicate experiments for a given experimental condition are aggregated together and used to calculate relevant statistics.

      This work also contains mislabeled graphs and incorrect correspondence with the text, which make it difficult to follow the authors 'claims. The text suggests that Pdop-2::Arch3 and Pmpz-1::Arch3 show increased exit rates, whereas Figure 2 shows that Pflp-4::Arch3 but not Pmpz-1::Arch3 has increased exit rate. The authors should also make a greater effort to correctly and clearly label which type of behavioral experiment is used to generate each figure and describe the differences in experimental design in the main text, figure legends, and methods. Figure 2E depicts trajectories of animals leaving a lawn over a 2.5-minute interval but it is unclear when this time window occurs within the 18-hour lawn leaving assay. Likewise, Figure 2H depicts a 30-minute time window which has an unclear relationship to the overall time course of lawn leaving. This figure legend is also mislabeled as "Infected/Healthy", whereas it should be labeled "-/+ ATR".

      In Figures 2C and F, the x-axis labels are in a different order, making it difficult to compare between the 2 plots. Promoter names should be italicized. What does the red ring mean in Figure 2A? Figure 2 legend incorrectly states that four lines showed statistically significant changes for the Exist rate constant - only 2 lines are significant according to the figure.

      We thank the reviewer for identifying this embarrassing error. Figure 2C and F were flipped, and we have corrected this, we are sorry for the error. Promoter names have been italicized, and we have added additional text in the captions that the red ring is a ring light for background illumination of the worms. In addition, we have corrected the error in the figure legends from “Infected/Healthy” to “+/- ATR”.

      Lines in figure 2C and 2F are ordered by significance rather than keeping the same order in both. Majority feedback from colleagues suggested that this ordering was preferred.

      This work raises the interesting possibility that different sets of neurons control lawn exit and lawn re-entry behaviors following pathogen exposure. However, the authors never directly test this claim. To rigorously show this, the authors would need to show that lawn-exit-promoting neurons (CEPs, HSNs, RIAs, RIDs, SIAs) are dispensable for lawn re-entry behavior and that lawn re-entry promoting neurons (AVK, SIA, AIY, MI) are dispensable for lawn exit behavior in pathogen-exposed animals.

      We agree with the reviewer’s comments that there is insufficient evidence to show a complete decoupling of lawn exit and lawn re-entry. However, we note that our screen results show that only 1 line (dop-2) shows changes in both exit and re-entry dynamics upon neural inhibition (Fig. 2). This seems to suggest that at least some degree of neural control of re-entry is decoupled from exit.

      Please label graph axes with units in Figure 1 - instead of "Exit Rate" make it #exits per worm per hour, and make it more clear that Figures 1C and E have a different kind of assay than Figures 1A, B and D. There should be more consistency between the meaning of "pre/post" and "naive/infected/healthy" - and how many hours constitutes post.

      We have edited Figure 1 and made additions to the captions of figure 1 to make both points clearer. We have also standardized our language for subsequent figures (such as figure 5) to provide less ambiguity in pre/post and naïve/infected/healthy.

      Figure 5 - it should be made more clear when the stimulation/inhibition occurred in these experiments and how long they were recorded/analyzed.

      We have added additional details to the figure captions to make it clearer when the data was collected.

      Workspaces and code have been added under a data availability section in the manuscript.

      Reviewer 2:

      However, the paper's main weakness lies in its lack of a detailed mechanism explaining how the delayed reentry process directly influences the actual locomotor output that results in avoidance. The term 'delayed reentry' is used as a dynamic metric for quantifying the screening, yet the causal link between this metric and the mechanistic output remains unclear. Despite this, the study is well-structured, with comprehensive control experiments, and is very well constructed.

      We thank the reviewer for their comments and suggestions. We have added additional data and details to our work to cover these weaknesses, as can be seen in our responses to the suggestions below.

      (1) A key issue in the manuscript is the mechanistic link between the delayed process and locomotor output. AIY is identified as a crucial neuron in this process, but the specifics of how AIY influences this delay are not clear. For instance, does AIY decrease the reversal rate, causing animals to get into long-range search when they leave the bacterial lawn? Is there any relationship between pdf-2 expression and reversal rates? Given that AIY typically promotes long-range motion when activated, the suppression of this function and its implications on motion warrants further clarification.

      We have included additional data to explain how AIY might be able to regulate lawn entry behaviors and have added more to the discussion to explain how neural suppression might lead to changes in the behavior (new figure S7). Both AIY and SIA dynamics have been linked to worm navigation. In previous work (Lee 2019), we have demonstrated that SIA can control locomotory speed. Inhibition of SIA decreases locomotory speed, and as a result may serve to drive the increased latency of re-entry.

      AIY’s role in navigation has been previously established (Zhaoyu 2014), but we have added an additional supplementary figure and edited our discussion to further illustrate this point. As can be seen in the new figure S7, AIY neural activity undergoes a transition after removal from a bacterial lawn, going from low activity to high activity. This activity increase is correlated with a transition from a high reversal rate local search state to a long range search state characterized by longer runs. Inhibition of AIY during this long range search state increased the reversal rate resulting in a higher rate of re-orientations. This might serve as a part of the mechanistic explanation for AIY’s role in preventing lawn re-entry, as inhibition dramatically increased the rate of re-orientation, preventing worms from making directed runs into the bacterial lawn. However, there is an additional effect of the inhibition of AIY, not seen during food search. Inhibition of AIY in the context of a pathogenic bacterial lawn leads to stalling at the edge. Therefore, re-entry AIY could have an additional role in governing the animals movement, post exposure, upon contact with a pathogenic lawn.

      (2) I recommend including supplementary videos to visually demonstrate the process. These videos might help others identify aspects of the mechanism that are currently missing or unclear in the text.

      (4) The authors mention that the worms "left the lawn," but the images suggest that the worms do not stray far and remain around the perimeter. Providing videos could help clarify this observation and strengthen the argument by visually connecting these points

      Additional supplementary videos (1-3) taken at several stages of lawn evacuation have been added to visually demonstrate the process.

      (3) Regarding the control experiments (Figure 1E-G), the manuscript describes testing animals picked from a PA14-seeded plate and retesting them on different plates. It's crucial to clarify the differences between these plates. Specifically, the region just outside the lawn should be considered, as it is not empty and worms can spread bacteria around. Testing animals on a new plate with a pristine proximity region might introduce variables that affect their behavior.

      We have reworded the paper to make it clearer that these new conditions on a fresh PA14 lawn represent a different type of assay from the lawn evacuation assay. Fresh PA14 plates will indeed have a pristine proximity region compared to plates where the worms have spread the bacteria.

      These experiments were done to test if the evacuation effect is purely due to aversive signals left on the lawn or attractive signals left outside of the lawn. Given that worms are known to be able to leave compounds such as ascarosides to communicate with each other, we wanted to test that this lawn re-entry defect was not simply the result of deposited pheromones. Without any other method to remove such compounds, we relied on using fresh PA14 lawns instead to test this. We have updated the manuscript to clarify this point.

      (5) The manuscript notes that the PA14 strain was grown without shaking. Typically, growing this strain without agitation leads to biofilm formation. Clarifying whether there is a link between biofilm formation and avoidance behavior would add depth to the understanding of the experimental conditions and their impact on the observed behaviors.

      As the reviewer has noted, growth of PA14 without shaking might indeed lead to biofilm formation. This does represent a legitimate concern, as evidence from previous work has suggested that biofilm formation could be linked to pathogen avoidance as worms make use of mechanosensation to avoid pathogenic bacteria (Chang et al. 2011).  However, we do not observe substantial formation of biofilm in our cultured bacteria, likely since our growth time might be insufficient for sufficient biofilm formation to occur. We also note that our evacuation dynamics appear to be of similar timescale to results reported in previous work which used different growth conditions. As such, we believe that our growth conditions thus represent similar conditions as to those historically used in the lawn evacuation literature.

      Reviewer 3:

      Weaknesses:

      My only concern is that the authors should be more careful about describing their "compressed sensing-based approach". Authors often cite their previous Nature Methods paper, but should explain more because this method is critical for this manuscript. Also, this analysis is based on the hypothesis that only a small number of neurons are responsible for a given behavior. Authors should explain more about how to determine scarcity parameters, for example.

      We have added more details to our paper outlining some of the details involved in our compressed sensing approach. We go into more detail about how we chose sparsity parameters and note that our discovered neurons for re-entry appear to be robust over choice of sparsity parameters. These additional details can be found in both the paper body and the methods section.

      Line 45: This paragraph tries to mention that there should be "small sets of neurons" that can play key roles in integrating previous information to influence subsequent behavior. Is it valid as an assumption in the nervous systems?

      We want to clarify that what is important is not that there are ‘small sets of neurons’, but rather that these key neurons make up a small fraction of the total number of neurons in the nervous system. More correctly: the compressed sensing approach identifies information bottlenecks in the neural circuits, and the assumption is that the number of neurons in these bottlenecks are small. This is the underlying sparsity assumption being made here that allows us to utilize a compressed sensing based approach to identify these neurons. We have reworded this section to make it clear that what is important is not that the total number of neurons is small, but that they must be a small fraction of the total number of neurons in the nervous system.

      Line 125: "These approaches…" Authors repeatedly mentioned this statement to emphasize that their compressed sensing-based approach is the best choice. Are you really sure?

      We agree that there are several approaches that might allow for faster screening of the nervous system. For example, many studies approach the problem by looking at neurons with synapses onto a neuron already known to be implicated in the behavior or find neurons that express a key gene known to regulate the behavior of interest. These approaches utilize prior information to greatly reduce the pool of candidate neurons needed to be screened.

      In the absence of such prior information, we believe that our compressed sensing based approach allows a rapid way to perform an unbiased interrogation of the entire nervous system to identify key neurons at bottlenecks of neural circuits. Once these key neurons are identified, neurons upstream and downstream of these key neurons can be investigated in the future.  This approach gives us the added advantage of being able to identify neurons that do not connect to neurons that are already implicated in the behavior, or that don’t have clear genetic signatures in the behavior of interest. Our approach further allows for screening of neurons with no clear single genetic marker without the next to utilize intersectional genetic strategies.  We should not use the phrase “best choice” which might not be justified. We have reworded these statements, and we believe that compressed sensing based methods provide a complementary approach to those in the literature.

      Line 42: If authors refer to mushroom bodies and human hippocampus in relation to the significance of their work, authors should go back to these references in the Discussion and explain how their work is important.

      We thank the reviewer for this feedback, and we have added to our discussion to expand upon these points.

      Line 151: "the accelerated pathogen avoidance" Accelerated pathogen avoidance does not necessarily indicate the existence of the neural mechanism that inhibits the association of pathogenicity with microbe-specific cues (during early stages: first two hours).

      We agree with the reviewer’s statements that these results alone do not indicate the presence of an early avoidance mechanism. Other evidence for early avoidance mechanisms exists as seen in two choice assay experiments (Zhang 2005), and our results do seem to support this. However, we agree that early neural inhibition is insufficient evidence towards such a mechanism. We have thus removed this statement for accuracy.

    1. Reviewer #1 (Public review):

      Summary:

      In this manuscript by Lopez-Blanch and colleagues, 21 microexons are selected for a deep analysis of their impacts on behavior, development, and gene expression. The authors begin with a systematic analysis of microexon inclusion and conservation in zebrafish and use these data to select 21 microexons for further study. The behavioral, transcriptomic, and morphological data presented are for the most part convincing. Furthermore, the discussion of the potential explanations for the subtle impacts of individual microexon deletions versus loss-of-function in srrm3 and/or srrm4 is quite comprehensive and thoughtful. One major weakness: data presentation, methods, and jargon at times affect readability / might lead to overstated conclusions. However, overall this manuscript is well-written, easy to follow, and the results are of broad interest.

      Strengths:

      (1) The study uses a wide variety of techniques to assess the impacts of microexon deletion, ranging from assays of protein function to regulation of behavior and development.

      (2) The authors provide comprehensive analyses of the molecular impact of their microexon deletions, including examining how host-gene and paralog expression is affected.

      Weaknesses / Major Points:

      (1) According to the methods, it seems that srrm3 social behavior is tested by pairing a 3mpf srrm3 mutant with a 30dpf srrm3 het. Is this correct? The methods seem to indicate that this decision was made to account for a slower growth rate of homozygous srrm3 mutant fish. However, the difference in age is potentially a major confound that could impact the way that srrm3 mutants interact with hets and the way that srrm3 mutants interact with one another (lower spread for the ratio of neighbour in front value, higher distance to neighbour value). This reviewer suggests testing het-het behavior at 3 months to provide age-matched comparisons for del-del, testing age-matched rather than size-matched het-del behavior, and also suggests mentioning this in the main text / within the figure itself so that readers are aware of the potential confound.

      (2) Referring to srrm3+/+; srrm4-/- controls for double mutant behavior as "WT for simplicity" is somewhat misleading. Why do the authors not refer to these as srrm4 single mutants?

      (3) It's not completely clear how "neurally regulated" microexons are defined / how they are different from "neural microexons"? Are these terms interchangeable?

      (4) Overexpression experiments driving srrm3 / srrm4 in HEK293 cells are not described in the methods.

      (4) Suggest including more information on how neurite length was calculated. In representative images, it appears difficult to determine which neurites arise from which soma, as they cross extensively. How was this addressed in the quantification?

    2. Reviewer #2 (Public review):

      Summary:

      This manuscript explores in zebrafish the impact of genetic manipulation of individual microexons and two regulators of microexon inclusion (Srrm3 and Srrm4). The authors compare molecular, anatomical, and behavioral phenotypes in larvae and juvenile fish. The authors test the hypothesis that phenotypes resulting from Srrm3 and 4 mutations might in part be attributable to individual microexon deletions in target genes.

      The authors uncover substantial alterations in in vitro neurite growth, locomotion, and social behavior in Srrm mutants but not any of the individual microexon deletion mutants. The individual mutations are accompanied by broader transcript level changes which may resemble compensatory changes. Ultimately, the authors conclude that the severe Srrm3/4 phenotypes result from additive and/or synergistic effects due to the de-regulation of multiple microexons.

      Strengths:

      The work is carefully planned, well-described, and beautifully displayed in clear, intuitive figures. The overall scope is extensive with a large number of individual mutant strains examined. The analysis bridges from molecular to anatomical and behavioral read-outs. Analysis appears rigorous and most conclusions are well-supported by the data.

      Overall, addressing the function of microexons in an in vivo system is an important and timely question.

      Weaknesses:

      The main weakness of the work is the interpretation of the social behavior phenotypes in the Srrm mutants. It is difficult to conclude that the mutations indeed impact social behavior rather than sensory processing and/or vision which precipitates apparent social alterations as a secondary consequence. Interpreting the phenotypes as "autism-like" is not supported by the data presented.

    3. Reviewer #3 (Public review):

      Summary:

      Microexons are highly conserved alternative splice variants, the individual functions of which have thus far remained mostly elusive. The inclusion of microexons in mature mRNAs increases during development, specifically in neural tissues, and is regulated by SRRM proteins. Investigation of individual microexon function is a vital avenue of research since microexon inclusion is disrupted in diseases like autism. This study provides one of the first rigorous screens (using zebrafish larvae) of the functions of individual microexons in neurodevelopment and behavioural control. The authors precisely excise 21 microexons from the genome of zebrafish using CRISPR-Cas9 and assay the downstream impacts on neurite outgrowth, larvae motility, and sociality. A small number of mild phenotypes were observed, which contrasts with the more dramatic phenotypes observed when microexon master regulators SRRM3/4 are disrupted. Importantly, this study attempts to address the reasons why mild/few phenotypes are observed and identify transcriptomic changes in microexon mutants that suggest potential compensatory gene regulatory mechanisms.

      Strengths:

      (1) The manuscript is well written with excellent presentation of the data in the figures.

      (2) The experimental design is rigorous and explained in sufficient detail.

      (3) The identification of a potential microexon compensatory mechanism by transcriptional alterations represents a valued attempt to begin to explain complex genetic interactions.

      (4) Overall this is a study with a robust experimental design that addresses a gap in knowledge of the role of microexons in neurodevelopment.

    4. Author response:

      Reviewer #1 (Public review):

      Summary:

      In this manuscript by Lopez-Blanch and colleagues, 21 microexons are selected for a deep analysis of their impacts on behavior, development, and gene expression. The authors begin with a systematic analysis of microexon inclusion and conservation in zebrafish and use these data to select 21 microexons for further study. The behavioral, transcriptomic, and morphological data presented are for the most part convincing. Furthermore, the discussion of the potential explanations for the subtle impacts of individual microexon deletions versus loss-of-function in srrm3 and/or srrm4 is quite comprehensive and thoughtful. One major weakness: data presentation, methods, and jargon at times affect readability / might lead to overstated conclusions. However, overall this manuscript is well-written, easy to follow, and the results are of broad interest.

      We thank the Reviewer for their positive comments on our manuscript. In the revised version, we will try to improve readability, reduce jargon and avoid overstatements. 

      Strengths:

      (1) The study uses a wide variety of techniques to assess the impacts of microexon deletion, ranging from assays of protein function to regulation of behavior and development.

      (2) The authors provide comprehensive analyses of the molecular impact of their microexon deletions, including examining how host-gene and paralog expression is affected.

      Weaknesses / Major Points:

      (1) According to the methods, it seems that srrm3 social behavior is tested by pairing a 3mpf srrm3 mutant with a 30dpf srrm3 het. Is this correct? The methods seem to indicate that this decision was made to account for a slower growth rate of homozygous srrm3 mutant fish. However, the difference in age is potentially a major confound that could impact the way that srrm3 mutants interact with hets and the way that srrm3 mutants interact with one another (lower spread for the ratio of neighbour in front value, higher distance to neighbour value). This reviewer suggests testing het-het behavior at 3 months to provide age-matched comparisons for del-del, testing age-matched rather than size-matched het-del behavior, and also suggests mentioning this in the main text / within the figure itself so that readers are aware of the potential confound.

      Thank you for bringing up this point. For the tests shown in Figure 5, we indeed decided to match the srrm3 pairs by fish size since we thought this would be more comparable to the other lines both biologically and methodologically (in terms of video tracking, etc.). However, we are confident the results would be very similar if matched by age, since the differences in social interactions between the srrm3 homozygous mutants and their control siblings are very dramatic at any age. For example, this can be appreciated, in line with the Reviewer's suggestion, in Videos S2 and S3, which show groups of five 5 mpf fish that are either srrm3 mutants or controls. It can be observed that the behavior of 5 mpf control fish is very similar to those of 1 mpf fish pairs, with very small interindividual distances. We will nonetheless agree that this decision on the experimental design should be clearly stated in the text and figure legend and we will do so in the revised version.

      (2) Referring to srrm3+/+; srrm4-/- controls for double mutant behavior as "WT for simplicity" is somewhat misleading. Why do the authors not refer to these as srrm4 single mutants?

      We thought it made the interpretation of plots easier, but we will change this in the revised version.

      (3) It's not completely clear how "neurally regulated" microexons are defined / how they are different from "neural microexons"? Are these terms interchangeable?

      Yes, they are interchangeable. We will double check the wording to avoid confusion.

      (4) Overexpression experiments driving srrm3 / srrm4 in HEK293 cells are not described in the methods.

      Apologies for this omission. We will briefly described the methods; however, please note that the data was obtained from a previous publication (Torres-Mendez et al, 2019), where the detailed methodology is reported.

      (5) Suggest including more information on how neurite length was calculated. In representative images, it appears difficult to determine which neurites arise from which soma, as they cross extensively. How was this addressed in the quantification?

      We will add further details to the revised version. With regards to the specific question, we would like to mention that this has not been a very common problem for the time points used in the manuscript (10 hap and 24 hap). At those stages, it was nearly always evident how to track each individual neurite. Dubious cases were simply discarded. Of course, such cases become much more common at later time points (48 and 72 hap), not sure in this study.

      Reviewer #2 (Public review):

      Summary:

      This manuscript explores in zebrafish the impact of genetic manipulation of individual microexons and two regulators of microexon inclusion (Srrm3 and Srrm4). The authors compare molecular, anatomical, and behavioral phenotypes in larvae and juvenile fish. The authors test the hypothesis that phenotypes resulting from Srrm3 and 4 mutations might in part be attributable to individual microexon deletions in target genes.

      The authors uncover substantial alterations in in vitro neurite growth, locomotion, and social behavior in Srrm mutants but not any of the individual microexon deletion mutants. The individual mutations are accompanied by broader transcript level changes which may resemble compensatory changes. Ultimately, the authors conclude that the severe Srrm3/4 phenotypes result from additive and/or synergistic effects due to the de-regulation of multiple microexons.

      Strengths:

      The work is carefully planned, well-described, and beautifully displayed in clear, intuitive figures. The overall scope is extensive with a large number of individual mutant strains examined. The analysis bridges from molecular to anatomical and behavioral read-outs. Analysis appears rigorous and most conclusions are well-supported by the data.

      Overall, addressing the function of microexons in an in vivo system is an important and timely question.

      Weaknesses:

      The main weakness of the work is the interpretation of the social behavior phenotypes in the Srrm mutants. It is difficult to conclude that the mutations indeed impact social behavior rather than sensory processing and/or vision which precipitates apparent social alterations as a secondary consequence. Interpreting the phenotypes as "autism-like" is not supported by the data presented.

      The Reviewer is absolutely right and we apologize for this omission, since it was not our intention to imply that these social defects should be interpreted simply as autistic-like. It is indeed very likely that the main reason for the social alterations displayed by the srrm3's mutants are due to their impaired vision. We will add this discussion explicitly in the revised version. 

      Reviewer #3 (Public review):

      Summary:

      Microexons are highly conserved alternative splice variants, the individual functions of which have thus far remained mostly elusive. The inclusion of microexons in mature mRNAs increases during development, specifically in neural tissues, and is regulated by SRRM proteins. Investigation of individual microexon function is a vital avenue of research since microexon inclusion is disrupted in diseases like autism. This study provides one of the first rigorous screens (using zebrafish larvae) of the functions of individual microexons in neurodevelopment and behavioural control. The authors precisely excise 21 microexons from the genome of zebrafish using CRISPR-Cas9 and assay the downstream impacts on neurite outgrowth, larvae motility, and sociality. A small number of mild phenotypes were observed, which contrasts with the more dramatic phenotypes observed when microexon master regulators SRRM3/4 are disrupted. Importantly, this study attempts to address the reasons why mild/few phenotypes are observed and identify transcriptomic changes in microexon mutants that suggest potential compensatory gene regulatory mechanisms.

      Strengths:

      (1) The manuscript is well written with excellent presentation of the data in the figures.

      (2) The experimental design is rigorous and explained in sufficient detail.

      (3) The identification of a potential microexon compensatory mechanism by transcriptional alterations represents a valued attempt to begin to explain complex genetic interactions.

      (4) Overall this is a study with a robust experimental design that addresses a gap in knowledge of the role of microexons in neurodevelopment.

      Thank you very much for your positive comments to our manuscript.

    1. Reviewer #1 (Public review):

      Summary:

      Zhang et al. addressed the question of whether advantageous and disadvantageous inequality aversion can be vicariously learned and generalized. Using an adapted version of the ultimatum game (UG), in three phases, participants first gave their own preference (baseline phase), then interacted with a "teacher" to learn their preference (learning phase), and finally were tested again on their own (transfer phase). The key measure is whether participants exhibited similar choice preferences (i.e., rejection rate and fairness rating) influenced by the learning phase, by contrasting their transfer phase and baseline phase. Through a series of statistical modeling and computational modeling, the authors reported that both advantageous and disadvantageous inequality aversion can indeed be learned (Study 1), and even be generalised (Study 2).

      Strengths:

      This study is very interesting, it directly adapted the lab's previous work on the observational learning effect on disadvantageous inequality aversion, to test both advantageous and disadvantageous inequality aversion in the current study. Social transmission of action, emotion, and attitude have started to be looked at recently, hence this research is timely. The use of computational modeling is mostly appropriate and motivated. Study 2, which examined the vicarious inequality aversion in conditions where feedback was never provided, is interesting and important to strengthen the reported effects. Both studies have proper justifications to determine the sample size.

      Weaknesses:

      Despite the strengths, a few conceptual aspects and analytical decisions have to be explained, justified, or clarified.

      INTRODUCTION/CONCEPTUALIZATION<br /> (1) Two terms seem to be interchangeable, which should not, in this work: vicarious/observational learning vs preference learning. For vicarious learning, individuals observe others' actions (and optionally also the corresponding consequence resulting directly from their own actions), whereas, for preference learning, individuals predict, or act on behalf of, the others' actions, and then receive feedback if that prediction is correct or not. For the current work, it seems that the experiment is more about preference learning and prediction, and less so about vicarious learning. The intro and set are heavily around vicarious learning, and later the use of vicarious learning and preference learning is rather mixed in the text. I think either tone down the focus on vicarious learning, or discuss how they are different. Some of the references here may be helpful: Charpentier et al., Neuron, 2020; Olsson et al., Nature Reviews Neuroscience, 2020; Zhang & Glascher, Science Advances, 2020

      EXPERIMENTAL DESIGN<br /> (2) For each offer type, the experiment "added a uniformly distributed noise in the range of (-10 ,10)". I wonder what this looks like? With only integers such as 25:75, or even with decimal points? More importantly, is it possible to have either 70:30 or 90:10 option, after adding the noise, to have generated an 80:20 split shown to the participants? If so, for the analyses later, when participants saw the 80:20 split, which condition did this trial belong to? 70:30 or 90:10? And is such noise added only to the learning phase, or also to the baseline/transfer phases? This requires some clarification.

      (3) For the offer conditions (90:10, 70:30, 50:50, 30:70, 10:90) - are they randomized? If so, how is it done? Is it randomized within each participant, and/or also across participants (such that each participant experienced different trial sequences)? This is important, as the order especially for the learning phase can largely impact the preference learning of the participants.

      STATISTICAL ANALYSIS & COMPUTATIONAL MODELING<br /> (4) In Study 1 DI offer types (90:10, 70:30), the rejection rate for DI-AI averse looks consistently higher than that for DI averse (ie, the blue line is above the yellow line). Is this significant? If so, how come? Since this is a between-subject design, I would not anticipate such a result (especially for the baseline). Also, for the LME results (eg, Table S3), only interactions were reported but not the main results.

      (5) I do not particularly find this analysis appealing: "we examined whether participants' changes in rejection rates between Transfer and Baseline, could be explained by the degree to which they vicariously learned, defined as the change in punishment rates between the first and last 5 trials of the Learning phase." Naturally, the participants' behavior in the first 5 trials in the learning phase will be similar to those in the baseline; and their behavior in the last 5 trials in the learning phase would echo those at the transfer phase. I think it would be stronger to link the preference learning results to the change between the baseline and transfer phase, eg, by looking at the difference between alpha (beta) at the end of the learning phase and the initial alpha (beta).

      (6) I wonder if data from the baseline and transfer phases can also be modeled, using a simple Fehr-Schimdt model. This way, the change in alpha/beta can also be examined between the baseline and transfer phase.

      (7) I quite liked Study 2 which tests the generalization effect, and I expected to see an adapted computational modeling to directly reflect this idea. Indeed, the authors wrote, "[...] given that this model [...] assumes the sort of generalization of preferences between offer types [...]". But where exactly did the preference learning model assume the generalization? In the methods, the modeling seems to be only about Study 1; did the authors advise their model to accommodate Study 2? The authors also ran simulation for the learning phase in Study 2 (Figure 6), and how did the preference update (if at all) for offers (90:10 and 10:90) where feedback was not given? Extending/Unpacking the computational modeling results for Study 2 will be very helpful for the paper.

    2. Reviewer #2 (Public review):

      Summary:

      This study investigates whether individuals can learn to adopt egalitarian norms that incur a personal monetary cost, such as rejecting offers that benefit them more than the giver (advantageous inequitable offers). While these behaviors are uncommon, two experiments demonstrate that individuals can learn to reject such offers through vicarious learning - by observing and acting in line with a "teacher" who follows these norms. The authors use computational modelling to argue that learners adopt these norms through a sophisticated process, inferring the latent structure of the teacher's preferences, akin to theory of mind.

      Strengths:

      This paper is well-written and tackles a critical topic relevant to social norms, morality, and justice. The findings, which show that individuals can adopt just and fair norms even at a personal cost, are promising. The study is well-situated in the literature, with clever experimental design and a computational approach that may offer insights into latent cognitive processes. Findings have potential implications for policymakers.

      Weaknesses:

      Note: in the text below, the "teacher" will refer to the agent from which a participant presumably receives feedback during the learning phase.

      (1) Focus on Disadvantageous Inequity (DI): A significant portion of the paper focuses on responses to Disadvantageous Inequitable (DI) offers, which is confusing given the study's primary aim is to examine learning in response to Advantageous Inequitable (AI) offers. The inclusion of DI offers is not well-justified and distracts from the main focus. Furthermore, the experimental design seems, in principle, inadequate to test for the learning effects of DI offers. Because both teaching regimes considered were identical for DI offers the paradigm lacks a control condition to test for learning effects related to these offers. I can't see how an increase in rejection of DI offers (e.g., between baseline and generalization) can be interpreted as speaking to learning. There are various other potential reasons for an increase in rejection of DI offers even if individuals learn nothing from learning (e.g. if envy builds up during the experiment as one encounters more instances of disadvantageous fairness).

      (2) Statistical Analysis: The analysis of the learning effects of AI offers is not fully convincing. The authors analyse changes in rejection rates within each learning condition rather than directly comparing the two. Finding a significant effect in one condition but not the other does not demonstrate that the learning regime is driving the effect. A direct comparison between conditions is necessary for establishing that there is a causal role for the learning regime.

      (3) Correlation Between Learning and Contagion Effects:<br /> The authors argue that correlations between learning effects (changes in rejection rates during the learning phase) and contagion effects (changes between the generalization and baseline phases) support the idea that individuals who are better aligning their preferences with the teacher also give more consideration to the teacher's preferences later during generalization phase. This interpretation is not convincing. Such correlations could emerge even in the absence of learning, driven by temporal trends like increasing guilt or envy (or even by slow temporal fluctuations in these processes) on behalf of self or others. The reason is that the baseline phase is temporally closer to the beginning of the learning phase whereas the generalization phase is temporally closer to the end of the learning phase. Additionally, the interpretation of these effects seems flawed, as changes in rejection rates do not necessarily indicate closer alignment with the teacher's preferences. For example, if the teacher rejects an offer 75% of the time then a positive 5% learning effect may imply better matching the teacher if it reflects an increase in rejection rate from 65% to 70%, but it implies divergence from the teacher if it reflects an increase from 85% to 90%. For similar reasons, it is not clear that the contagion effects reflect how much a teacher's preferences are taken into account during generalization.

      (4) Modeling Efforts: The modelling approach is underdeveloped. The identification of the "best model" lacks transparency, as no model-recovery results are provided, and fits for the losing models are not shown, leaving readers in the dark about where these models fail. Moreover, the reinforcement learning (RL) models used are overly simplistic, treating actions as independent when they are likely inversely related (for example, the feedback that the teacher would have rejected an offer provides feedback that rejection is "correct" but also that acceptance is "an error", and the later is not incorporated into the modelling). It is unclear if and to what extent this limits current RL formulations. There are also potentially important missing details about the models. Can the authors justify/explain the reasoning behind including these variants they consider? What are the initial Q-values? If these are not free parameters what are their values?

      (5) Conceptual Leap in Modeling Interpretation: The distinction between simple RL models and preference-inference models seems to hinge on the ability to generalize learning from one offer to another. Whereas in the RL models learning occurs independently for each offer (hence to cross-offer generalization), preference inference allows for generalization between different offers. However, the paper does not explore RL models that allow generalization based on the similarity of features of the offers (e.g., payment for the receiver, payment for the offer-giver, who benefits more). Such models are more parsimonious and could explain the results without invoking a theory of mind or any modelling of the teacher. In such model versions, a learner learns a functional form that allows to predict the teacher's feedback based on said offer features (e.g., linear or quadratic form). Because feedback for an offer modulates the parameters of this function (feature weights) generalization occurs without necessarily evoking any sophisticated model of the other person. This leaves open the possibility that RL models could perform just as well or even show superiority over the preference learning model, casting doubt on the authors' conclusions. Of note: even the behaviourists knew that as Little Albert was taught to fear rats, this fear generalized to rabbits. This could occur simply because rabbits are somewhat similar to rats. But this doesn't mean little Alfred had a sophisticated model of animals he used to infer how they behave.

      (6) Limitations of the Preference-Inference Model: The preference-inference model struggles to capture key aspects of the data, such as the increase in rejection rates for 70:30 DI offers during the learning phase (e.g. Figure 3A, AI+DI blue group). This is puzzling.

      Thinking about this I realized the model makes quite strong unintuitive predictions that are not examined. For example, if a subject begins the learning phase rejecting the 70:30 offer more than 50% of the time (meaning the starting guilt parameter is higher than 1.5), then overleaning the tendency to reject will decrease to below 50% (the guilt parameter will be pulled down below 1.5). This is despite the fact the teacher rejects 75% of the offers. In other words, as learning continues learners will diverge from the teacher. On the other hand, if a participant begins learning to tend to accept this offer (guilt < 1.5) then during learning they can increase their rejection rate but never above 50%. Thus one can never fully converge on the teacher. I think this relates to the model's failure in accounting for the pattern mentioned above. I wonder if individuals actually abide by these strict predictions. In any case, these issues raise questions about the validity of the model as a representation of how individuals learn to align with a teacher's preferences (given that the model doesn't really allow for such an alignment).

    1. Reviewer #1 (Public review):

      Summary:

      This study highlights the strengths of using predictive computational models to inform C. elegans screening studies of compounds' effects on aging and lifespan. The authors primarily focus on all-trans retinoic acid (atRA), one of the 5 compounds (out of 16 tested) that extended C. elegans lifespan in their experiments. They show that atRA has positive effects on C. elegans lifespan and age-related health, while it has more modest and inconsistent effects (i.e., some detrimental impacts) for C. briggsae and C. tropicalis. In genetic experiments designed to evaluate contributing mediators of lifespan extension with atRA exposure, it was found that 150 µM of atRA did not significantly extend lifespan in akt-1 or akt-2 loss-of-function mutants, nor in animals with loss of function of aak-2, or skn-1 (in which atRA had toxic effects); these genes appear to be required for atRA-mediated lifespan extension. hsf-1 and daf-16 loss-of-function mutants both had a modest but statistically significant lifespan extension with 150 µM of atRA, suggesting that these transcription factors may contribute towards mediating atRA lifespan extension, but that they are not individually required for some lifespan extension. RNAseq assessment of transcriptional changes in day 4 atRA-treated adult wild-type worms revealed some interesting observations. Consistent with the study's genetic mutant lifespan observations, many of the atRA-regulated genes with the greatest fold-change differences are known regulated targets of daf-2 and/or skn-1 signaling pathways in C. elegans. hsf-1 loss-of-function mutants show a shifted atRA transcriptional response, revealing a dependence on hsf-1 for ~60% of the atRA-downregulated genes. On the other hand, RNAseq analysis in aak-2 loss-of-function mutants revealed that aak-2 is only required for less than a quarter of the atRA transcriptional response. All together, this study is proof of the concept that computational models can help optimize C. elegans screening approaches that test compounds' effects on lifespan, and provide comprehensive transcriptomic and genetic insights into the lifespan-extending effects of all-trans retinoic acid (atRA).

      Strengths:

      (1) A clearly described and well-justified account describes the approach used to prioritize and select compounds for screening, based on using the top candidates from a published list of computationally ranked compounds (Fuentealba et al., 2019) that were cross-referenced with other bioinformatics publications to predict anti-aging compounds, after de-selecting compounds previously evaluated in C. elegans as per the DrugAge database. 16 compounds were tested at 4-5 different concentrations to evaluate effects on C. elegans lifespan.

      (2) Robust experimental design was undertaken evaluating the lifespan effects of atRA, as it was tested on three strains each of C. elegans, C. briggsae, and C. tropicalis, with trial replication performed at three distinct laboratories. These observations extended beyond lifespan to include evaluations of health metrics related to swimming performance.

      (3) In-depth analyses of the RNAseq data of whole-worm transcriptional responses to atRA revealed interesting insights into regulator pathways and novel groups of genes that may be involved in mediating lifespan-extension effects (e.g., atRA-induced upregulation of sphingolipid metabolism genes, atRA-upregulation of genes in a poorly-characterized family of C. elegans paralogs predicted to have kinase-like activity, and disproportionate downregulation of collagen genes with atRA).

      Weaknesses:

      (1) The authors' computational-based compound screening approach led to a ~30% prediction success rate for compounds that could extend the median lifespan of C. elegans. However, follow-up experiments on the top compounds highlighted the fact that some of these observed "successes" could be driven by indirect, confounding effects of these compounds on the bacterial food source, rather than direct beneficial effects on C. elegans physiology and lifespan. For instance, this appeared to be the case for the "top" hit of propranolol; other compounds were not tested with metabolically inert or killed bacteria. In addition, there are no comparative metrics provided to compare this study's ~30% success rate to screening approaches that do not use computational predictions.

      (2) Transcriptomic analyses of atRA effects were extensive in this study, but evaluations and discussions of non-transcriptional effects of key proposed regulators (such as AMPK) were limited. For instance, non-transcriptional effects of aak-2/AMPK might account for its requirement for mediating lifespan extension effects, since aak-2 was not required for a major proportion of atRA transcriptional responses.

    2. Reviewer #3 (Public review):

      Summary:

      In this study, Banse et al., demonstrate that combining computer prediction with genetic analysis in distinct Caenorhabditis species can streamline the discovery of aging interventions by taking advantage of the diverse pool of compounds that are currently available. They demonstrate that through careful prioritization of candidate compounds, they are able to accomplish a 30% positive hit rate for interventions that produce significant lifespan extensions. Within the positive hits, they focus on all-trans retinoic acid (atRA) and discover that it modulates lifespan through conserved longevity pathways such as AKT-1 and AKT-2 (and other conserved Akt-targets such as Nrf2/SKN-1 and HSF1/HSF-1) as well as through AAK-2, a conserved catalytic subunit of AMPK. To better understand the genetic mechanisms behind lifespan extension upon atRA treatment, the authors perform RNAseq experiments using a variety of genetic backgrounds for cross-comparison and validation. Using this current state-of-the-art approach for studying gene expression, the authors determine that atRA treatment produces gene expression changes across a broad set of stress-response and longevity-related pathways. Overall, this study is important since it highlights the potential of combining traditional genetic analysis in the genetically tractable organism C. elegans with computational methods that will become even more powerful with the swift advancements being made in artificial intelligence. The study possesses both theoretical and practical implications not only in the field of aging but also in related fields such as health and disease. Most of the claims in this study are supported by solid evidence, but the conclusions can be refined with a small set of additional experiments or re-analysis of data.

      Strengths:

      (1) The criteria for prioritizing compounds for screening are well-defined and easy to replicate (Figure 1), even for scientists with limited experience in computational biology. The approach is also adaptable to other systems or model organisms.

      (2) I commend the researchers for doing follow-up experiments with the compound propranolol to verify its effect on lifespan (Figure 2 Supplement 2), given the observation that it affected the growth of OP50. To prevent false hits in the future, the reviewer recommends the use of inactivated OP50 for future experiments to remove this confounding variable.

      (3) The sources of variation (Figure 3, Figure Supplement 2) are taken into account and demonstrate the need for advancing our understanding of the lifespan phenotype due to inter-individual variation.

      (4) The addition of the C. elegans swim test in addition to the lifespan assays provides further evidence of atRA-induced improvement in longevity.

      (5) The RNAseq approach was performed in a variety of genetic backgrounds, which allowed the authors to determine the relationship between AAK-2 and HSF-1 regulation of the retinoic acid pathway in C. elegans, specifically, that the former functions downstream of the latter.

      Weaknesses:

      (1) The filtering of compounds for testing using the DrugAge database requires that the database is consistently updated. In this particular case, even though atRA does not appear in the database, the authors themselves cite literature that has already demonstrated atRA-induced lifespan extension, which should have precluded this compound from the analysis in the first place.

      (2) The threshold for determining positive hits is arbitrary, and in this case, a 30% positive hit rate was observed when the threshold is set to a lifespan extension of around 5% based on Figure 1B (the authors fail to explicitly state the cut-off for what is considered a positive hit).

      (3) The authors demonstrate that atRA extends lifespan in a species-specific manner (Figure 3). Specifically, this extension only occurs in the species C. elegans yet, the title implies that atRA-induced lifespan extension occurs in different Caenorhabditis species when it is clearly not the case. While the authors state that failure to observe phenotypes in C. briggsae and C. tropicalis is a common feature of CITP tests, they do not speculate as to why this phenomenon occurs.

      (4) There are discrepancies between the lifespan curves by hand (Figure 3 Figure Supplement 1) and using the automated lifespan machine (Figure 3 Supplement 3). Specifically, in the automated lifespan assays, there are drastic changes in the slope of the survival curve which do not occur in the manual assays. This may be due to improper filtering of non-worm objects, improper annotation of death times, or improper distribution of plates in each scanner.

      (5) The authors miss an opportunity to determine whether the lifespan extension phenotype attributed to the retinoic acid pathway is mostly transcriptional in nature or whether some of it is post-transcriptional. The authors even state "that while aak-2 is absolutely required for the longevity effects of atRA, aak-2 is required only for a small proportion (~1/4) of the transcriptional response", suggesting that some of the effects are post-transcriptional. Further information could have been obtained had the authors also performed RNAseq analysis on the tol-1 mutant which exhibited an enhanced response to atRA compared to wild-type animals, and comparing the magnitude of gene expression changes between the tol-1 mutant and all other genetic backgrounds for which RNAseq was performed.

    1. Reviewer #2 (Public review):

      This manuscript proposes that primary hepatocytes can replicate their DNA without the six-subunit ORC. This follows previous studies that examined mice that did not express ORC1 in the liver. In this study, the authors suppressed expression of ORC2 or ORC1 plus ORC2 in the liver.

      Comments:

      (1) I find the conclusion of the authors somewhat hard to accept. Biochemically, ORC without the ORC1 or ORC2 subunits cannot load the MCM helicase on DNA. The question arises whether the deletion in the ORC1 and ORC2 genes by Cre is not very tight, allowing some cells to replicate their DNA and allow the liver to develop, or whether the replication of DNA proceeds via non-canonical mechanisms, such as break-induced replication. The increase in the number of polyploid cells in the mice expressing Cre supports the first mechanism, because it is consistent with few cells retaining the capacity to replicate their DNA, at least for some time during development.

      (2) Fig 1H shows that 5 days post infection, there is no visible expression of ORC2 in MEFs with the ORC2 flox allele. However, at 15 days post infection, some ORC2 is visible. The authors suggest that a small number of cells that retained expression of ORC2 were selected over the cells not expressing ORC2. Could a similar scenario also happen in vivo?

      (3) Figs 2E-G shows decreased body weight, decreased liver weight and decreased liver to body weight in mice with recombination of the ORC2 flox allele. This means that DNA replication is compromised in the ALB-ORC2f/f mice.

      (4) Figs 2I-K do not report the number of hepatocytes, but the percent of hepatocytes with different nuclear sizes. I suspect that the number of hepatocytes is lower in the ALB-ORC2f/f mice than in the ORC2f/f mice. Can the authors report the actual numbers?

      (5) Figs 3B-G do not report the number of nuclei, but percentages, which are plotted separately for the ORC2-f/f and ALB-ORC2-f/f mice. Can the authors report the actual numbers?

      (6) Fig 5 shows the response of ORC2f/f and ALB-ORC2f/f mice after partial hepatectomy. The percent of EdU+ nuclei in the ORC2-f/f (aka ALB-CRE-/-) mice in Fig 5H seems low. Based on other publications in the field it should be about 20-30%. Why is it so low here? The very low nuclear density in the ALB-ORC2-f/f mice (Fig 5F) and the large nuclei (Fig 5I) could indicate that cells fire too few origins, proceed through S phase very slowly and fail to divide.

      (7) Fig 6F shows that ALB-ORC1f/f-ORC2f/f mice have very severe phenotypes in terms of body weight and liver weight (about on third of wild-type!!). Fig 6H and 6I, the actual numbers should be presented, not percentages. The fact that there are EYFP negative cells, implies that CRE was not expressed in all hepatocytes.

      (8) Comparing the EdU+ cells in Fig 7G versus 5G shows very different number of EdU+ cells in the control animals. This means that one of these images is not representative. The higher fraction of EdU+ cells in the double-knockout could mean that the hepatocytes in the double-knockout take longer to complete DNA replication than the control hepatocytes. The control hepatocytes may have already completed DNA replication, which can explain why the fraction of EdU+ cells is so low in the controls. The authors may need to study mice at earlier time points after partial hepatectomy, i.e. sacrifice the mice at 30-32 hours, instead of 40-52 hours.

      (9) Regarding the calculation of the number of cell divisions during development: the authors assume that all the hepatocytes in the adult liver are derived from hepatoblasts that express Alb. Is it possible to exclude the possibility that pre-hepatoblast cells that do not express Alb give rise to hepatocytes? For example the cells that give rise to hepatoblasts may proliferate more times than normal giving rise to a higher number of hepatoblasts than in wild-type mice.

      (10) My interpretation of the data is that not all hepatocytes have the ORC1 and ORC2 genes deleted (eg EYFP-negative cells) and that these cells allow some proliferation in the livers of these mice.

    2. Author response:

      eLife Assessment

      This descriptive manuscript builds on prior research showing that the elimination of Origin Recognition Complex (ORC) subunits does not halt DNA replication. The authors use various methods to genetically remove one or two ORC subunits from specific tissues and observe continued replication, though it may be incomplete. The replication appears to be primarily endoreduplication, indicating that ORC-independent replication may promote genome reduplication without mitosis. Despite similar findings in previous studies, the paper provides convincing genetic evidence in mice that liver cells can replicate and undergo endoreduplication even with severely depleted ORC levels. While the mechanism behind this ORC-independent replication remains unclear, the study lays the groundwork for future research to explore how cells compensate for the absence of ORC and to develop functional approaches to investigate this process. The reviewers agree that this valuable paper would be strengthened significantly if the authors could delve a bit deeper into the nature of replication initiation, potentially using an origin mapping experiment. Such an exciting contribution would help explain the nature of the proposed new type of Mcm loading, thereby increasing the impact of this study for the field at large.<br />

      We appreciate the reviewers’ suggestion. Till now we know of only one paper that mapped origins of replication in regenerating mouse liver, and that was published two months back in Cell (PMID: 39293447).  We want to adopt this method, but we do not need it to answer the question asked.  We have mapped origins of replication in ORC-deleted cancer cell lines and compared to wild-type cells in Shibata et al., BioRXiv (PMID: 39554186) (it is under review).  We report the following:  Mapping of origins in cancer cell lines that are wild type or engineered to delete three of the subunits, ORC1, ORC2 or ORC5 shows that specific origins are still used and are mostly at the same sites in the genome as in wild type cells. Of the 30,197 origins in wild type cells (with ORC), only 2,466 (8%) are not used in any of the three ORC deleted cells and 18,319 (60%) are common between the four cell types. Despite the lack of ORC, excess MCM2-7 is still loaded at comparable rates in G1 phase to license reserve origins and is also repeatedly loaded in the same S phase to permit re-replication. 

      Citation: Specific origin selection and excess functional MCM2-7 loading in ORC-deficient cells. Yoshiyuki Shibata, Mihaela Peycheva, Etsuko Shibata, Daniel Malzl, Rushad Pavri, Anindya Dutta. bioRxiv 2024.10.30.621095; doi: https://doi.org/10.1101/2024.10.30.621095 (PMID: 39554186)

      Public Reviews:

      Reviewer #1 (Public review):

      The origin recognition complex (ORC) is an essential loading factor for the replicative Mcm2-7 helicase complex. Despite ORC's critical role in DNA replication, there have been instances where the loss of specific ORC subunits has still seemingly supported DNA replication in cancer cells, endocycling hepatocytes, and Drosophila polyploid cells. Critically, all tested ORC subunits are essential for development and proliferation in normal cells. This presents a challenge, as conditional knockouts need to be generated, and a skeptic can always claim that there were limiting but sufficient ORC levels for helicase loading and replication in polyploid or transformed cells. That being said, the authors have consistently pushed the system to demonstrate replication in the absence or extreme depletion of ORC subunits.

      Here, the authors generate conditional ORC2 mutants to counter a potential argument with prior conditional ORC1 mutants that Cdc6 may substitute for ORC1 function based on homology. They also generate a double ORC1 and ORC2 mutant, which is still capable of DNA replication in polyploid hepatocytes. While this manuscript provides significantly more support for the ability of select cells to replicate in the absence or near absence of select ORC subunits, it does not shed light on a potential mechanism.

      The strengths of this manuscript are the mouse genetics and the generation of conditional alleles of ORC2 and the rigorous assessment of phenotypes resulting from limiting amounts of specific ORC subunits. It also builds on prior work with ORC1 to rule out Cdc6 complementing the loss of ORC1.

      The weakness is that it is a very hard task to resolve the fundamental question of how much ORC is enough for replication in cancer cells or hepatocytes. Clearly, there is a marked reduction in specific ORC subunits that is sufficient to impact replication during development and in fibroblasts, but the devil's advocate can always claim minimal levels of ORC remaining in these specialized cells.

      The significance of the work is that the authors keep improving their conditional alleles (and combining them), thus making it harder and harder (but not impossible) to invoke limiting but sufficient levels of ORC. This work lays the foundation for future functional screens to identify other factors that may modulate the response to the loss of ORC subunits.

      This work will be of interest to the DNA replication, polyploidy, and genome stability communities.

      Thank you.

      Reviewer #2 (Public review):

      This manuscript proposes that primary hepatocytes can replicate their DNA without the six-subunit ORC. This follows previous studies that examined mice that did not express ORC1 in the liver. In this study, the authors suppressed expression of ORC2 or ORC1 plus ORC2 in the liver.

      Comments:

      (1) I find the conclusion of the authors somewhat hard to accept. Biochemically, ORC without the ORC1 or ORC2 subunits cannot load the MCM helicase on DNA. The question arises whether the deletion in the ORC1 and ORC2 genes by Cre is not very tight, allowing some cells to replicate their DNA and allow the liver to develop, or whether the replication of DNA proceeds via non-canonical mechanisms, such as break-induced replication. The increase in the number of polyploid cells in the mice expressing Cre supports the first mechanism, because it is consistent with few cells retaining the capacity to replicate their DNA, at least for some time during development.

      In our study, we used EYFP as a marker for Cre recombinase activity. ~98% of the hepatocytes in tissue sections and cells in culture express EYFP, suggesting that the majority of hepatocytes successfully expressed the Cre protein to delete the ORC1 or ORC2 genes. To assess deletion efficiency, we employed sensitive genotyping and Western blotting techniques to confirm the deletion of ORC1 and ORC2 in hepatocytes isolated from Alb-Cre mice. Results in Fig. 2C and Fig. 6D demonstrate the near-complete absence of ORC2 and ORC1 proteins, respectively, in these hepatocytes.

      The mutant hepatocytes underwent at least 15–18 divisions during development. The inherited ORC1 or ORC2 protein present during the initial cell divisions, would be diluted to less than 1.5% of wild-type levels within six divisions, making it highly unlikely to support DNA replication, and yet we observe hepatocyte numbers that suggest there was robust cell division even after that point.

      Furthermore, the EdU incorporation data confirm DNA synthesis in the absence of ORC1 and ORC2. Specifically, immunofluorescence showed that both in vitro and in vivo, EYFP-positive hepatocytes (indicating successful ORC1 and ORC2 deletion) incorporated EdU, demonstrating that DNA synthesis can occur without ORC1 and ORC2.

      Finally, the Alb-ORC2f/f mice have 25-37.5% of the number of hepatocyte nuclei compared to WT mice (Table 2).  If that many cells had an undeleted ORC2 gene, that would have shown up in the genotyping PCR and in the Western blots.

      (2) Fig 1H shows that 5 days post infection, there is no visible expression of ORC2 in MEFs with the ORC2 flox allele. However, at 15 days post infection, some ORC2 is visible. The authors suggest that a small number of cells that retained expression of ORC2 were selected over the cells not expressing ORC2. Could a similar scenario also happen in vivo?

      This would not explain the significant incorporation of EdU in hepatocytes that do not have detectable ORC by Western blots and that are EYFP positive.  Also note that for MEFs we are delivering the Cre by AAV infection in vitro, so there is a finite probability that a cell will not receive Cre and will not delete ORC2.  However, in vivo, the Alb-Cre will be expressed in every cell that turns on albumin.  There is no escaping the expression of Cre.

      (3) Figs 2E-G shows decreased body weight, decreased liver weight and decreased liver to body weight in mice with recombination of the ORC2 flox allele. This means that DNA replication is compromised in the ALB-ORC2f/f mice.

      It is possible that DNA replication is partially compromised or may slow down in the absence of ORC2. However, it is important to emphasize that livers with ORC2 deletion remain capable of DNA replication, so much so that liver function and life span are near normal. Therefore, some kind of DNA replication has to serve as a compensatory mechanism in the absence of ORC2 to maintain liver function and support regeneration.

      (4) Figs 2I-K do not report the number of hepatocytes, but the percent of hepatocytes with different nuclear sizes. I suspect that the number of hepatocytes is lower in the ALB-ORC2f/f mice than in the ORC2f/f mice. Can the authors report the actual numbers?

      We show in Table 2 that the Alb-Orc2f/f mice have about 25-37.5% of the hepatocytes compared to the WT mice.

      (5) Figs 3B-G do not report the number of nuclei, but percentages, which are plotted separately for the ORC2-f/f and ALB-ORC2-f/f mice. Can the authors report the actual numbers?

      In all the FACS experiments in Fig. 3B-G we collect data for a total of 10,000 nuclei (or cells).  For Fig. 3E-G we divide the 10,000 nuclei into the bottom 40% on the EYFP axis (EYFP low, which is mostly EYFP negative) as the control group, and EYFP high (top 20% on the EYFP axis) test group.  We will mention this in the revision and label EYFP negative and positive as EYFP low and high.

      (6) Fig 5 shows the response of ORC2f/f and ALB-ORC2f/f mice after partial hepatectomy. The percent of EdU+ nuclei in the ORC2-f/f (aka ALB-CRE-/-) mice in Fig 5H seems low. Based on other publications in the field it should be about 20-30%. Why is it so low here? The very low nuclear density in the ALB-ORC2-f/f mice (Fig 5F) and the large nuclei (Fig 5I) could indicate that cells fire too few origins, proceed through S phase very slowly and fail to divide.

      The percentage of EdU+ nuclei in the ORC2f/f without Alb-Cre mice is 8%, while in PMID 10623657, the 10% of wild type nuclei incorporate  EdU at 42 hr post partial hepatectomy (mid-point between the 36-48 hr post hepatectomy that was used in our study).  The important result here is that in the ORC2f/f mice with Alb-Cre (+/-) we are seeing significant EdU incorporation. We will also correct the X-axis labels in 5F, 5I, 7E and 7F to reflect that those measurements were not made at 36 hr post-resection but later (as was indicated in the schematic in Fig. 5A).

      (7) Fig 6F shows that ALB-ORC1f/f-ORC2f/f mice have very severe phenotypes in terms of body weight and liver weight (about on third of wild-type!!). Fig 6H and 6I, the actual numbers should be presented, not percentages. The fact that there are EYFP negative cells, implies that CRE was not expressed in all hepatocytes.

      The liver to body weight ratio is what one has to look at, and it is 70% of the WT.  In females the liver and body weight are low (although in proportion to each other), which maybe is what the reviewer is talking about.  However, the fact that liver weight and body weight are not as low in males, suggest that this is a gender (hormone?) specific effect and not a DNA replication defect.  We have another paper also in BioRXiv (Su et al.) that suggests that ORC subunits have significant effect on gene expression, so it is possible that that is what leads to this sexual dimorphism in phenotype.

      The bottom 40% of nuclei on the EYFP axis in the FACS profiles (what was labeled EYFP negative but will now be called EYFP low) contains mostly non-hepatocytes that are genuinely EYFP negative.   Non-hepatocytes (bile duct cells, endothelial cells, Kupffer cells, blood cells) are a significant part of cells in the dissociated liver (as can be seen in the single cell sequencing results in PMID: 32690901).  Their presence does not mean that hepatocytes are not expressing Cre.  Hepatocytes mostly are EYFP positive, as can be seen in the tissue sections (where the hepatocytes take up most of visual field) and in cells in culture.  Also if there are EYFP negative hepatocyte nuclei in the FACS, that still does not rule out EYFP presence in the cytoplasm.  The important point from the FACS is that the EYFP high nuclei (which have expressed Cre for the longest period) are polyploid relative to the EYFP low nuclei.

      (8) Comparing the EdU+ cells in Fig 7G versus 5G shows very different number of EdU+ cells in the control animals. This means that one of these images is not representative. The higher fraction of EdU+ cells in the double-knockout could mean that the hepatocytes in the double-knockout take longer to complete DNA replication than the control hepatocytes. The control hepatocytes may have already completed DNA replication, which can explain why the fraction of EdU+ cells is so low in the controls. The authors may need to study mice at earlier time points after partial hepatectomy, i.e. sacrifice the mice at 30-32 hours, instead of 40-52 hours.

      The apparent difference that the reviewer comments on stems from differences in nuclear density in the images in Fig. 7G and 5G (also quantitated in Fig. 7F and 5F).  The quantitation in Fig. 7H and 5H show that the % of EdU plus cells are comparable (5-8%). 

      (9) Regarding the calculation of the number of cell divisions during development: the authors assume that all the hepatocytes in the adult liver are derived from hepatoblasts that express Alb. Is it possible to exclude the possibility that pre-hepatoblast cells that do not express Alb give rise to hepatocytes? For example the cells that give rise to hepatoblasts may proliferate more times than normal giving rise to a higher number of hepatoblasts than in wild-type mice.

      Single cell sequencing of mouse liver at e11 shows hepatoblasts expressing hepatocyte specific markers (PMID: 32690901).  All the cells annotated from the single-cell seq analysis are differentiated cells arguing against the possibility that undifferentiated endodermal cells (what the reviewer probably means by pre-hepatoblasts) exist at e11.  The following review (https://www.ncbi.nlm.nih.gov/books/NBK27068/) says: “The differentiation of bi-potential hepatoblasts into hepatocytes or BECs begins around e13 of mouse development. Initially hepatoblasts express genes associated with both adult hepatocytes (Hnf4α, Albumin) ...”  Thus, we can be certain that undifferentiated endodermal cells are unlikely to persist on e11 and that hepatoblasts at e11 express albumin.  Our calculation of number of cell divisions in Table 2 begins from e12.

      The reviewer maybe suggesting that ORC deletion leads to the immediate demise of hepatoblasts (despite having inherited ORC protein from the endodermal cells) causing undifferentiated endodermal cells to persist and proliferate much longer than in normal development.  We consider it unlikely, but if true it will be amazing new biology, both by suggesting that deletion of ORC immediately leads to the death of the hepatoblasts (despite a healthy reserve of inherited ORC protein) and by suggesting that there is a novel feedback mechanism from the death/depletion of hepatoblasts leading to the persistence and proliferation of undifferentiated endodermal cells.

      (10) My interpretation of the data is that not all hepatocytes have the ORC1 and ORC2 genes deleted (eg EYFP-negative cells) and that these cells allow some proliferation in the livers of these mice.

      Please see the reply in question #1.  Particularly relevant: “Finally, the Alb-ORC2f/f mice have 25-37.5% of the number of hepatocyte nuclei compared to WT mice (Table 2).  If that many cells had an undeleted ORC2 gene, that would have shown up in the genotyping PCR and in the Western blots.

      Reviewer #3 (Public review):

      Summary:

      The authors address the role of ORC in DNA replication and that this protein complex is not essential for DNA replication in hepatocytes. They provide evidence that ORC subunit levels are substantially reduced in cells that have been induced to delete multiple exons of the corresponding ORC gene(s) in hepatocytes. They evaluate replication both in purified isolated hepatocytes and in mice after hepatectomy. In both cases, there is clear evidence that DNA replication does not decrease at a level that corresponds with the decrease in detectable ORC subunit and that endoreduplication is the primary type of replication observed. It remains possible that small amounts of residual ORC are responsible for the replication observed, although the authors provide arguments against this possibility. The mechanisms responsible for DNA replication in the absence of ORC are not examined.

      Strengths:

      The authors clearly show that there are dramatic reductions in the amount of the targeted ORC subunits in the cells that have been targeted for deletion. They also provide clear evidence that there is replication in a subset of these cells and that it is likely due to endoreduplication. Although there is no replication in MEFs derived from cells with the deletion, there is clearly DNA replication occurring in hepatocytes (both isolated in culture and in the context of the liver). Interestingly, the cells undergoing replication exhibit enlarged cell sizes and elevated ploidy indicating endoreduplication of the genome. These findings raise the interesting possibility that endoreduplication does not require ORC while normal replication does.

      Weaknesses:

      There are two significant weaknesses in this manuscript. The first is that although there is clearly robust reduction of the targeted ORC subunit, the authors cannot confirm that it is deleted in all cells. For example, the analysis in Fig. 4B would suggest that a substantial number of cells have not lost the targeted region of ORC2. Although the western blots show stronger effects, this type of analysis is notorious for non-linear response curves and no standards are provided. The second weakness is that there is no evaluation of the molecular nature of the replication observed. Are there changes in the amount of location of Mcm2-7 loading that is usually mediated by ORC? Does an associated change in Mcm2-7 loading lead to the endoreduplication observed? After numerous papers from this lab and others claiming that ORC is not required for eukaryotic DNA replication in a subset of cells, we still have no information about an alternative pathway that could explain this observation.

      We do not see a significant deficit in MCM2-7 loading (amount and rate) in cancer cell lines where we have deleted ORC1, ORC2 or ORC5 genes separately in Shibata et al. bioRxiv 2024.10.30.621095; doi: https://doi.org/10.1101/2024.10.30.621095 (PMID: 39554186)

      The authors frequently use the presence of a Cre-dependent eYFP expression as evidence that the ORC1 or ORC2 genes have been deleted. Although likely the best visual marker for this, it is not demonstrated that the presence of eYFP ensures that ORC2 has been targeted by Cre. For example, based on the data in Fig. 4B, there seems to be a substantial percentage of ORC2 genes that have not been targeted while the authors report that 100% of the cells express eYFP.

      The PCR reactions in Fig. 4B are still contaminated by DNA from non-hepatocyte cells:  bile duct cells, endothelial, Kupfer cells and blood cells.  Under the microscope  culture we can recognize the hepatocytes unequivocally from their morphology. <2% of the hepatocyte cells in culture in Fig. 4C are EYFP-.

    1. 古斯塔夫·克里姆特通过其独特的装饰性语言和象征性主题,奠定了新艺术运动的艺术基础,并推动了现代艺术的发展。他的画作以华丽的金箔和复杂的象征语言,探索了人类情感、自然与精神的深刻主题,成为20世纪艺术史上的璀璨之星。

      要理解古斯塔夫·克里姆特作品中的“装饰性语言”,需要从以下几个方面入手:

      1. 什么是“装饰性”?

      在艺术语境中,“装饰性”通常指作品中注重视觉美感、强调线条、图案、色彩等元素的运用,而相对弱化对现实的逼真描绘。装饰性艺术往往具有平面化、图案化、程式化的特点,追求画面的形式美和视觉冲击力。

      2. 克里姆特作品中“装饰性语言”的具体表现:

      • 繁复的图案和纹样: 这是克里姆特作品最显著的特征之一。他大量运用各种几何图案、涡旋纹、螺旋纹、花卉纹等,将画面填充得满满当当,营造出华丽、繁复的视觉效果。这些图案并非单纯的装饰,往往具有象征意义,例如螺旋纹象征生命的轮回,涡旋纹象征宇宙的运动。
      • 金箔的运用: 克里姆特大量使用金箔,使画面金碧辉煌,极具视觉冲击力。金箔的使用不仅增强了画面的装饰性,也赋予作品一种宗教般的神秘感和象征性。
      • 平面化的处理: 克里姆特的作品往往弱化透视和体积感,强调画面的平面性。人物和背景常常融为一体,形成一个平面化的装饰图案。
      • 流畅的线条: 克里姆特善用流畅、优美的线条来勾勒人物和物体的轮廓,这些线条富有韵律感和装饰性。
      • 象征性的符号和主题: 克里姆特的作品常常描绘女性、爱情、生命、死亡等主题,并运用各种象征性的符号来表达这些主题。例如,他经常使用眼睛、嘴唇、花朵等符号来象征女性的魅力和生命力。

      3. “装饰性语言”在克里姆特作品中的作用:

      • 营造华丽的视觉效果: 克里姆特通过繁复的图案、金箔和流畅的线条,营造出极具视觉冲击力的画面,吸引观众的目光。
      • 表达象征意义: 装饰性的元素并非单纯的装饰,而是具有象征意义的符号,它们共同构建了作品的象征性语言,传达了克里姆特对生命、爱情、死亡等主题的思考。
      • 增强作品的艺术表现力: 克里姆特的“装饰性语言”突破了传统绘画的束缚,创造了一种独特的艺术风格,极大地丰富了艺术的表现力。

      4. “装饰性语言”与新艺术运动的关系:

      克里姆特是维也纳分离派的代表人物,而维也纳分离派是新艺术运动的重要分支。新艺术运动强调装饰性、自然形态和象征主义,追求艺术与生活的融合。克里姆特的“装饰性语言”与新艺术运动的理念高度契合,因此他被认为是新艺术运动的代表人物之一,他的作品也为新艺术运动奠定了重要的艺术基础。

      举例说明:

      以克里姆特的代表作《吻》(The Kiss)为例:

      • 画面中,男女主人公被各种几何图案和涡旋纹包围,这些图案不仅装饰了画面,也象征了爱情的缠绵和永恒。
      • 金箔的大量使用使画面金碧辉煌,营造出一种神圣的氛围。
      • 人物的轮廓线流畅优美,富有装饰性。

      这些元素共同构成了《吻》独特的“装饰性语言”,使其成为新艺术运动的经典之作。

      总结:

      克里姆特的“装饰性语言”并非简单的表面装饰,而是他表达思想和情感的重要手段。他通过繁复的图案、金箔、流畅的线条和象征性的符号,创造了一种独特的艺术风格,不仅为新艺术运动奠定了基础,也对现代艺术的发展产生了深远的影响。理解克里姆特的“装饰性语言”,有助于我们更深入地理解他的作品及其艺术价值。

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      Reply to the reviewers

      Reviewer #1

      General Comment. *Using ubiquitous and targeted heterologous expression of the honeybee venom peptide Apamin in Drosophila, the authors find that apamin has antimicrobial activity that is enhanced by membrane-tethering and dependent on the Drosophila pattern-recognition receptors PGRP-LA and PGRP-SC2. Expression of apamin in the Drosophila gut or ingestion of Apamin by honeybees has positive effects on gut health as shown by a number of metrics. *

      __ Answer: __We thank the reviewer for their insightful comments. We agree that the findings of this study are significant and have broad implications for understanding the antimicrobial properties of apamin. As suggested, we have further delved into the molecular mechanisms underlying apamin's antimicrobial activity, providing additional details on its interactions with target bacteria. We have also expanded our discussion on the role of membrane-tethering in enhancing apamin's activity and its potential impact on its localization. We believe that these additional illustrations strengthen our conclusions and provide a more comprehensive understanding of apamin's biological functions.

      Major comments:

      Comment 1. *The key conclusions are convincing and largely supported by the data as shown. The data is presented clearly, save for some areas in the results where the authors should be more explicit about the methods that were used as they affect the reader's interpretation of the results (see minor comments). *

      __ Answer: __We would like to express our gratitude to the reviewer for their constructive feedback and positive remarks regarding our manuscript. We are pleased to note that the reviewer found our key conclusions convincing and largely supported by the data presented. This affirmation encourages us as we strive to contribute meaningful insights to the field. We acknowledge the reviewer's suggestion to enhance clarity in certain areas of the Results section, particularly concerning the methods employed. We appreciate this guidance and have taken it into account. In our revised manuscript, we have made explicit revisions to ensure that the methodology is clearly articulated, thereby improving the reader's interpretation of our results. Thank you once again for your valuable feedback, which has undoubtedly strengthened our work. We look forward to your continued guidance as we finalize our manuscript.

      Comment 2. *If the authors wish to conclude that PGRP-LE and PGRP-LC are not required for the demonstrated functions of Apamin, the authors should do a double knock-down of PGRP-LC and LE together, as these pattern recognition receptors function partially redundantly in activation of the Imd pathway (e.g. doi: 10.1038/ni1356). *

      __ Answer:__ We appreciate reviewer's interesting suggestion to know PGRP-LE and LC's functions are redundant to activate Imd pathway or Apamin is totally independent of Imd pathway. As reviewer suggested, we have conducted double knockdown of PGRP-LE and PGRP-LC and showed that apamin still suppress bacterial infection regardless of these double knockdowns of these genes. This data suggests that apamin's antimicrobial function is totally not dependent on PGRP-LE or LC and open new questions about apamin's unique function as AMP. We added new data in Fig. 5d and described in main text as below:

      "Knockdown of PGRP-LC or LE, as well as their combined knockdown, did not affect the antimicrobial efficacy of apamin (Fig. 5b-d), suggesting that the antimicrobial properties of apamin are independent of PGRP-LC and LE functions (Fig. 5a)."

      Comment 3. *The Introduction and Discussion would benefit from providing more context that helps the reader understand the significance of the research. Where is apamin expressed in the honeybee? Is it likely to be ingested and have effects on gut health in natural conditions? Do honeybees have homologs of PGRP-LA and PGRP-SC2? Do these findings translate to the honeybee system in any way or are they restricted to heterologous expression in Drosophila? *

      __Answer: __We thank the reviewer for valuable suggestions. We agree that providing additional context on the natural role of apamin in honeybees and the relevance of our findings to the honeybee system is crucial.

      Natural expression and function of apamin: While apamin is primarily known for its neurotoxic effects, studies have suggested that it may also play a role in antimicrobial defense. While its specific expression pattern in honeybees is not fully understood, it is conceivable that it is mainly expressed in venom sacs according to research on biochemistry and pharmacology of apamin (Habermann, 1972; Schumacher et al, 1994; INOUE et al, 1987) . We have outlined this information in the Introduction section as follows:

      "Apamin, an 18 amino acid peptide neurotoxin, is one of the bioactive components of bee venom, making up 2%-3% of its total dry weight, naturally expressed in bee venom sacs (RIETSCHOTEN et al, 1975; E.H., 1976; Son et al, 2007; Zhou et al, 2010; Habermann, 1972)."

      Potential for ingestion and gut effects: Although direct evidence for apamin ingestion and its impact on gut health in natural conditions is limited, it is plausible that honeybees could be exposed to apamin through various means, including foraging and social interactions. However, artificial interference is the potential application method that we are more focusing on. We have included additional details regarding the function of apamin in the Introduction section as follows:

      "It is the smallest known neurotoxic polypeptide and exhibits elevated basicity and sulfur content, demonstrating prolonged action relative to other pharmacological agents influencing the central or peripheral nervous systems(Habermann, 1972)."

      Honeybee homologs of PGRPs: Concerning the honeybee PGRPs and their homologs in Drosophila, we have provided an explanation as follows:

      "While honeybees possess homologs of PGRP family, including PGRP-LC and PGRP-S2, their specific roles in response to apamin and other antimicrobial peptides remain to be elucidated(Larsen et al, 2019a)."

      Relevance to the honeybee system: While our study primarily utilized Drosophila as a model system, the conserved nature of innate immune pathways suggests that the findings may have broader implications for honeybee health. Future studies aimed at directly investigating the effects of apamin in honeybees will be essential to fully understand its role in their physiology and behavior. We have incorporated these points into the Discussion sections to provide a more comprehensive and informative overview of our research as below:

      "In conclusion, it is important to note that much of our understanding of the honeybee immune system is derived from studies conducted on the Drosophila model, owing to the evolutionary proximity of these two species (Larsen et al, 2019b). This close relationship allows for valuable insights into immune mechanisms that are conserved across species (Evans et al, 2006; Morfin et al, 2021). Research has demonstrated that the fruit fly Drosophila melanogaster serves as an effective model for studying the effects of insecticides on honeybees, particularly in understanding the sub-lethal impacts of neonicotinoids, which are known to affect pollinators significantly (Tasman et al, 2021).

      By investigating the function of honeybee AMPs within the Drosophila platform, we can further enhance our knowledge of immune responses and their implications. Just as research on Drosophila has significantly advanced our understanding of human genetic diseases (Bellen et al, 2010; Casci & Pandey, 2015; Bier, 2005; Perrimon et al, 2016; Rieder & Larschan, 2014; Bilder et al, 2021), studying honeybee AMPs in this context holds the potential to uncover novel therapeutic avenues and deepen our comprehension of immune function across taxa."

      Comment 4. *It is surprising that there is no speculation or hypothesis provided about why PGRP-LA and -SC2 may enhance apamin activity whereas other components are nonessential. It was a significant part of the paper but receives almost no discussion. *

      Answer: We thank the reviewer for highlighting this important point. The specific mechanism by which PGRP-LA and PGRP-SC2 enhance apamin's activity is an intriguing question that warrants further investigation. Our findings indicate that both PGRP-LA and PGRP-SC2 are crucial for the antimicrobial action of apamin, as their knockdown abolishes this effect, suggesting a specific functional relationship between these peptidoglycan recognition proteins and apamin's mechanism of action in the gut environment.

      PGRP-LA is known to play a significant regulatory role as positive regulator of immune responses, while PGRP-SC2 has been shown to promote gut immune homeostasis and prevent dysbiosis, which is essential for maintaining a balanced microbiome in Drosophila (Guo et al, 2014). The enhancement of apamin activity by these proteins could be attributed to their ability to modulate the immune response and facilitate a more effective antimicrobial environment, thereby allowing apamin to exert its effects more efficiently.

      Furthermore, our study aligns with previous research indicating that PGRP-SC2 can limit commensal dysbiosis and promote tissue homeostasis, which may enhance the overall efficacy of antimicrobial peptides like apamin in combating pathogenic bacteria (Guo et al, 2014). By leveraging the evolutionary insights gained from Drosophila, we can better understand how these mechanisms operate in honeybees, ultimately contributing to our knowledge of immune function across species. We have provided a detailed explanation of the potential roles of PGRP-LA and PGRP-SC2 in the action of apamin, as outlined below:

      "The PGRP-LA gene is located in a cluster with PGRP-LC and PGRP-LF, which encode a receptor and a negative regulator of the Imd pathway, respectively; structural predictions suggest that PGRP-LA may not directly bind to peptidoglycan, indicating a potential regulatory role for this PGRP in modulating immune responses (Gendrin et al, 2013). PGRP-SC2 possesses amidase activity, which means it can cleave the peptidoglycan layer of bacterial cell walls, rendering them susceptible to further degradation and ultimately leading to bacterial cell death. This amidase activity contributes to the insect's innate immune response by directly targeting and neutralizing bacterial threats (Takehana et al, 2002; Park et al, 2007; Paredes et al, 2011)."

      Comment 5. *Line 264: The fact that Rel knockdown did not impair antimicrobial activity of Apamin is a bit odd since upregulation of PGRP-SC2 upon infection is at least partially dependent on Rel (de Gregorio 2002, EMBO J), and the authors find that PGRP-SC2 is required for apamin activity. This is somewhat incongruous. *

      __Answer: __We thank the reviewer for highlighting this important point. The observation that Rel knockdown did not impair apamin's antimicrobial activity, despite its role in upregulating PGRP-SC2, is indeed intriguing.

      Several factors may contribute to this discrepancy:

      Redundancy in PGRP-SC2 regulation: It is possible that other transcription factors, in addition to Rel, may regulate PGRP-SC2 expression. Therefore, even in the absence of Rel, sufficient levels of PGRP-SC2 may be maintained to support apamin's activity(Bischoff et al, 2006) . Direct effects of apamin: Apamin may directly interact with bacterial cells or host immune cells and contribute to its antimicrobial activity, even in the absence of optimal PGRP-SC2 levels.

      We cited (de Gregorio 2002, EMBO J) paper and added explanation for this result as below:

      "It is known that the upregulation of PGRP-SC during infection is partially reliant on the Rel pathway (Gregorio et al, 2002). Our findings indicate that apamin can exert its antimicrobial activity independently of Rel's transcriptional activation function. This observation can be attributed to two key factors. First, there may be redundancy in the regulation of PGRP-SC2 expression, as other transcription factors could compensate for the absence of Rel, allowing sufficient levels of PGRP-SC2 to be maintained to support apamin's activity. Second, apamin may have direct interactions with bacterial cells or host immune cells, contributing to its antimicrobial effects even when optimal levels of PGRP-SC2 are not present. These mechanisms suggest that apamin can function effectively in the immune response, highlighting its potential as a versatile antimicrobial agent."

      Comment 6. *I cannot comment on the adequacy of the statistical analyses. Some recommendations to improve the methods: *

      *- Be specific about the kind of medium used to rear flies (provide or cite recipe). Different cornmeal-yeast media have very different compositions and can affect fly physiology and microbiome characteristics. *

      *- Specify flipping schedule (every 2-3 days?) - this also affects microbiome. *

      __Answer: __We thank the reviewer for their valuable comments. We agree that precise experimental details are crucial for reproducibility and accurate interpretation of results.

      To address the reviewer's specific concerns:

      Culture medium: We used a standard cornmeal-molasses-agar medium. The specific recipe for this medium is as follows: water add up to 5 L,agar 47g, inactive yeast 65.5g, corn flour 232.5g, soy flour 30g, molasses 350 ml, tegosept sol. 35g, propionic acid 12.5ml, phosphoric acid 2.5ml. Flipping schedule: Flies were flipped every 2-3 days to prevent overcrowding and maintain optimal culture conditions.

      We have included these details in the Methods section to enhance the clarity and reproducibility of our experiments.

      Minor comments:

      *- Line 90: Be specific about how the constructs differ from endogenous Melittin and Apamin. Do the endogenous versions have signal peptides? *

      Answer: The endogenous versions do not have signal peptides we have used, we have specified this in the manuscript for readers to have a better understanding as below:

      "To assess the functionality of genetically encoded honeybee VPs in the Drosophila model, we developed UAS-Melittin, and UAS-Apamin constructs that incorporate a previously characterized signal peptide at their N-termini (Choi et al, 2009), which original AMP and VP sequences do not have (Fig. 1a)."

      - Line 92: What is 'broad expression'? Ubiquitous? Specify driver or extent of expression.

      Answer: We have added "by tub-GAL4 driver"

      *- Line 93: Was this oral or septic P. aeruginosa infection? *

      Answer: We have added "oral"

      *- Lines 97-98: Melittin expressed genetically did not show activity against the one pathogen that was tested; making a broad statement without qualification about activity seems excessive. *

      Answer: We have added "against P. aeruginosa"

      *- Line 105: Various Gal4 drivers that express in different tissues or a similar subset of tissues? *

      Answer: We utilized tub-GAL4 and da-GAL4 in this part of screening, they both drive expression in ubiquitous tissues. Daughterless (da) involves in the transcriptional regulation of various processes, including oogenesis, neurogenesis, myogenesis, and cell proliferation. While tub-GAL4 is ubiquitous expression throughout most tissues and cell types in the Drosophila body. We have added "various ubiquitously expressing"

      *- Line 134: Present as a commensal? Pathobiont? Pathogen? *

      Answer: Apibacter raozihei is generally considered a commensal bacterium in the honeybee gut. We have added to manuscript "which is present as a commensal bacterium in the guts of".

      *- Line 149: Are Cyanobacteria naturally present in gut microbiota? What are photosynthetic bacteria doing as part of a gut microbiome? *

      Answer: While cyanobacteria are not typically found in the gut, cyanobacterial 16S rRNA-like sequences have been previously detected in human gut samples, bovine rumen, termite gut, and other animal intestines, suggesting the presence of a non-photosynthetic cyanobacterial lineage in these aphotic environments(Hu & Rzymski, 2022; Hongoh et al, 2003).

      *- Line 171: Where is apamin endogenously expressed in the honeybee? Only in the venom gland? Or in gut cells as done here in Drosophila? *

      Answer: Natural expression and function of apamin: While apamin is primarily known for its neurotoxic effects, studies have suggested that it may also play a role in antimicrobial defense. While its specific expression pattern in honeybees is not fully understood, it is conceivable that it is mainly expressed in venom sacs according to research on biochemistry and pharmacology of apamin (Habermann, 1972; Schumacher et al, 1994; INOUE et al, 1987) .

      *- Line 252: -LC and -LE work in a complementary/semi-redundant fashion, so single knockdown is not an effective method of indicating that they are not required for antimicrobial function. *

      Answer: We appreciate reviewer's interesting suggestion to know PGRP-LE and LC's functions are redundant to activate Imd pathway or Apamin is totally independent of Imd pathway. As reviewer suggested, we have conducted double knockdown of PGRP-LE and PGRP-LC and showed that apamin still suppress bacterial infection regardless of these double knockdowns of these genes. This data suggests that apamin's antimicrobial function is totally not dependent on PGRP-LE or LC and open new questions about apamin's unique function as AMP. We added new data in Fig. 5d and described in main text as below:

      "Knockdown of PGRP-LC or LE, as well as their combined knockdown, did not affect the antimicrobial efficacy of apamin (Fig. 5b-d), suggesting that the antimicrobial properties of apamin are independent of PGRP-LC and LE functions (Fig. 5a)."

      *- Lines 279-283: The bacterial infections that expression of these AMPs were tested against should be mentioned in the text, as all bacteria are not equivalent. *

      Answer: Added with "P. aeruginosa"

      *- Line 296: Challenged with which bacteria? *

      Answer: Added with "P. aeruginosa"

      *- Line 328: Provide brief explanation of what Ttk depletion is for reader context. *

      Answer: Added with short explanation as below:

      "which refers to the reduction or elimination of a protein called TTK (Monopolar Spindle 1 Kinase) that plays a crucial role in cell division, specifically in ensuring accurate chromosome segregation during mitosis (Mason et al, 2017)."

      *- Line 719: This should say, '5 days after eclosion'. *

      Answer: Corrected

      *- General comment on figures: The little icons used to denote what the figure is depicting (gut health, climbing, aging, etc.) are very effective. *

      Answer: We thank the reviewer for their appreciation on figures.

      *- General comment on figure titles: Use of the term 'infectious dose' throughout does not make sense. I think what the authors mean is 'pathogen load' as they are testing using CFUs. 'Infectious dose' should only be used to refer to the amount/OD of pathogen that was initially administered to establish an infection. Also, 'oral feeding' should be used throughout instead of 'orally feeding'. *

      Answer: We thank the reviewer for their insightful comment. We agree that the use of the term 'infectious dose' was inaccurate in certain contexts. We have revised the manuscript to use 'pathogen load' to refer to the number of CFUs administered or recovered, as this more accurately reflects the bacterial burden.

      We have also replaced 'orally feeding' with 'oral feeding' throughout the manuscript to improve clarity and consistency.

      We appreciate the reviewer's attention to detail and believe that these changes have significantly enhanced the clarity and accuracy of the manuscript.

      *- Figure 1O: Abrupt die-offs at 1000hrs and 2800hrs in the UAS-Melittin line suggest that lifespan experiment was only performed once and that die-offs may have been exacerbated due to infrequent flipping. This is perhaps not an issue as the lifespans appear to be quite different between the active line and control regardless. *

      Answer: We thank the reviewer for their careful observation. The abrupt die-offs in the UAS-Melittin line at 1000 hours and 2800 hours were unexpected. While we cannot definitively rule out the possibility that infrequent flipping might have contributed to these events, we believe that the overall lifespan difference between the experimental and control groups is substantial and likely reflects a genuine biological effect of Melittin overexpression.

      *- Figure 2F would be improved by putting the legend in the same descending order that the genotypes are displayed on the graph (tApamin infected, GFP infected, tApamin, GFP) *

      Answer: We have corrected error.

      *- Figure 3I: Unclear what small image inserted in the graph depicts. *

      Answer: This is an image of fly stem cells that is available for free licensing.

      - Figures 3N and 3O are verry low resolution and difficult to identify the differences that the authors *intend to show. *

      Answer: We have utilized a higher resolution image and revised the figure accordingly.

      - Figure 4 title is confusing. Do the authors mean, "Locomotion of flies expressing neuronal Apamin, sleep in flies with ubiquitous expression of Apamin, and Smurf results induced by different types of stress."?

      Answer: Corrected as below:

      "Locomotion of flies expressing neuronal tApaminDC, sleep in flies with ubiquitous expression of tApaminDC, and Smurf results induced by different types of stress."

      *- Figure 5: Some of these graphs are very cluttered and difficult to parse (particularly 5H). Suggest putting peptide sequences in figure title rather than underneath graphs to simplify and increase visual effectiveness. *

      Answer: We have improved by removing the sequences to figure legend part.

      *-Throughout: Methods section in particular could use a solid edit for grammar. Homogenize capitalization of "Gram-negative/-positive" and "gram-negative/-positive" *

      Answer: We have corrected error.

      *- Line 98: "an AMPs" should be "an AMP" *

      Answer: We have corrected error.

      *- Line 119: Incorrect grammar. Suggest, "which did not affect the lifespan of female flies and had only a slight effect on male flies" *

      Answer: We have corrected error.

      Reviewer #1 (Significance (Required)):

      *The paper reveals that apamin has antimicrobial properties. The intended significance seems to be an exploration of apamin for therapeutic potential in gut health, but this is not explicitly stated by the authors. The contribution mainly appears to be conceptual in nature. *

      *The findings appear to be in line with other recent in vitro results suggesting that apamin has antimicrobial properties (DOI: 10.9775/kvfd.2024.32125). *

      *Researchers interested in developing therapeutic applications for bee venom constituents or promoting gut health and microbiome balance will likely find this research of interest. *

      *My expertise is primarily in Drosophila molecular genetics and immunity. I have a broad understanding of Drosophila immune pathways, epithelial immunity, and infection dynamics. I do not feel qualified to comment on the statistics or data analysis aspects of this paper. *

      Answer: We sincerely appreciate the reviewer's positive feedback regarding our findings on the antimicrobial properties of apamin. We are grateful for the acknowledgment that our results align with recent in vitro studies, such as the one referenced (DOI: 10.9775/kvfd.2024.32125), which further supports the significance of our work. We have cited this paper in the Discussion section as below.

      "Our findings are consistent with recent in vitro studies demonstrating the antimicrobial and antibiofilm effects of apamin (AYDIN et al, 2024)."

      We recognize the reviewer's observation that our intended significance-specifically, the exploration of apamin's therapeutic potential for gut health-was not explicitly stated in the original manuscript. To address this, we have revised the Introduction and Discussion sections to clearly articulate our aim of investigating apamin as a candidate for promoting gut health and microbiome balance. We believe this clarification will enhance the conceptual contribution of our study and its relevance to researchers interested in therapeutic applications of bee venom constituents.

      "Apamin shows promising therapeutic potential for enhancing bee gut health by exhibiting antimicrobial properties that can help maintain a balanced microbiome. Its ability to modulate immune responses and promote gut integrity, particularly in the presence of harmful bacteria, positions apamin as a valuable candidate for developing strategies aimed at improving gut health in honeybees."

      Additionally, we appreciate the reviewer's expertise in Drosophila molecular genetics and immunity, and we are grateful for their insights regarding the broader implications of our research. We will ensure that our manuscript reflects these considerations more explicitly.

      Thank you once again for your valuable feedback, which has helped us improve the clarity and impact of our work.

      Reviewer #2

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

      General Comment. *The reviewer would like to thank the authors for their contributions to the research of animal venoms and their therapeutic value. The manuscript is very well and clearly written. Additionally, the choice of using a model organism such as D. melanogaster in the context of venoms research strengthens the manuscript by providing evidence that is both robust and broadly applicable, thus enhancing the manuscript's scientific merit and relevance to the field. *

      Answer: We would like to express our sincere gratitude to the reviewer for the positive feedback and thoughtful comments regarding our manuscript. We are pleased to hear that the reviewer appreciates our contributions to the research on animal venoms and their therapeutic potential. The reviewer's acknowledgment of the clarity and quality of our writing is particularly encouraging, as we strive to communicate our findings effectively. Additionally, we are glad that the choice of Drosophila melanogaster as a model organism was recognized for its ability to strengthen our research by providing robust and broadly applicable evidence. This endorsement enhances the scientific merit and relevance of our work within the field. Thank you once again for the constructive feedback, which has been invaluable in refining our manuscript.

      Comment 1. *What is the significance of that the biological property of apamin is independent of its disulfide bonds? Does it suggest that the core functional parts of apamin might not entirely depend on its stabilized structure? Could it mean that modifications to the molecule that disrupt disulfide bonds wouldn't necessarily eliminate all of its activity, which could be important in designing analogs or derivatives of apamin for research or therapeutic purposes etc.? This sentence is written in the abstract which means that it should be a key finding, and it should be clear and a given to the reader. However, it is not the case, and it should be stated more clearly. *

      Answer: We greatly appreciate the reviewer for the perceptive notation. The fact that the biological functioning of apamin needs no disulfide bonds should bring forth the attention of the scientists because it has further implications. This hints that apamin's major functional units are most likely to compose from its polypeptide instead of being rooted in the disulfide-stabilized tertiary structure(Habermann, 1972). The strategy can then lead to the optimization of apamin-based drugs with altered disulfide bridges granting them either higher activity or reduced toxicity. These changes can give apamin additional properties like stability, bioavailability, or selectivity, which make it suitable for research and applied use. We have included an explanation for this in both the Results and Discussion sections.

      "This finding suggests that the core functional components of apamin may not be entirely reliant on its stabilized structure."

      "We discovered that apamin lacking the C-terminus retains its function as an antimicrobial agent, despite missing one of its two disulfide bridges. This finding suggests that the core functional components of apamin may not be entirely dependent on its stabilized structure, indicating that modifications to the molecule that disrupt these disulfide bonds could still maintain some level of activity. These insights are vital for designing analogs or derivatives of apamin, as they pave the way for developing new compounds that could retain therapeutic potential even without the native disulfide bond configuration (Habermann, 1972)."

      Comment 2. *The authors well explained the evolutionary proximity between apamin producing Honeybees and D. melanogaster in order to justify the choice of the model organism which we can all agree on for genetics and developmental biology studies. However, when addressing the behavior of the insects (sleeping, locomotion, social etc.) which are driven by their ecological roles, evolutionary strategies, and social complexity. How much can you really tell about the role of apamin in the behavior of Honeybees (highly social and form colonies) by studying it on an insect (D. melanogaster) which has a completely different and divergent behavior (solitary and exhibit only few basic forms of social interaction)? *

      Answer: We appreciate the reviewer's insightful comment. While Drosophila melanogaster is an excellent model organism for investigating fundamental biological processes, we recognize the limitations of using it to fully comprehend the complex behavioral effects of apamin in honeybees. Nevertheless, our study establishes a foundational understanding of apamin's potential impact on behavior, including its effects on sleep and locomotion-core behavioral processes that are conserved across many organisms, including insects (Zimmerman et al, 2008).

      By employing Drosophila as a model, we were able to identify potential mechanisms of action for apamin, particularly regarding its effects on intestinal systems. Although honeybees and fruit flies exhibit ecological differences, there is substantial consensus and experimental evidence that many molecular pathways involved in immune responses are conserved between these species. Thus, while the interpretation of behavioral changes induced by apamin may be limited by the ecological and evolutionary divergence between honeybees and fruit flies, the molecular pathways governing the immune response in honeybees can be effectively studied using the Drosophila platform. This approach has previously revealed functions of genes related to human genetic diseases. We have clearly articulated this limitation and the advantages of using the fly model to study the honeybee immune system in the Discussion section as follows:

      "In conclusion, it is important to note that much of our understanding of the honeybee immune system is derived from studies conducted on the Drosophila model, owing to the evolutionary proximity of these two species (Larsen et al, 2019b). This close relationship allows for valuable insights into immune mechanisms that are conserved across species (Evans et al, 2006; Morfin et al, 2021). Research has demonstrated that the fruit fly Drosophila melanogaster serves as an effective model for studying the effects of insecticides on honeybees, particularly in understanding the sub-lethal impacts of neonicotinoids, which are known to affect pollinators significantly (Tasman et al, 2021).

      By investigating the function of honeybee AMPs within the Drosophila platform, we can further enhance our knowledge of immune responses and their implications. Just as research on Drosophila has significantly advanced our understanding of human genetic diseases (Bellen et al, 2010; Casci & Pandey, 2015; Bier, 2005; Perrimon et al, 2016; Rieder & Larschan, 2014; Bilder et al, 2021), studying honeybee AMPs in this context holds the potential to uncover novel therapeutic avenues and deepen our comprehension of immune function across taxa."

      Comment 3. *Please include the following references: *

      • Wehbe R, Frangieh J, Rima M, El Obeid D, Sabatier JM, Fajloun Z. Bee Venom: Overview of Main Compounds and Bioactivities for Therapeutic Interests. Molecules. 2019 Aug 19;24(16):2997. *

      • Nader RA, Mackieh R, Wehbe R, El Obeid D, Sabatier JM, Fajloun Z. Beehive Products as Antibacterial Agents: A Review. Antibiotics. 2021; 10(6):717. *

      Answer: We have incorporated the references mentioned above in appropriate sections of the manuscript. We appreciate the reviewer's suggestions.

      Reviewer #2 (Significance (Required)):

      The manuscript is very well and clearly written. Additionally, the choice of using a model organism such as D. melanogaster in the context of venoms research strengthens the manuscript by providing evidence that is both robust and broadly applicable, thus enhancing the manuscript's scientific merit and relevance to the field.

      Answer: We would like to express our sincere gratitude to the reviewer for their positive feedback regarding our manuscript. We are thrilled to hear that the clarity and quality of our writing were appreciated. Additionally, we are glad that the choice of Drosophila melanogaster as a model organism in our venoms research was recognized for its ability to provide robust and broadly applicable evidence. This endorsement underscores the scientific merit and relevance of our work within the field, and we appreciate the reviewer's acknowledgment of this important aspect. Thank you for your encouraging comments, which motivate us to continue exploring this vital area of research.

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

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      Using ubiquitous and targeted heterologous expression of the honeybee venom peptide Apamin in Drosophila, the authors find that apamin has antimicrobial activity that is enhanced by membrane-tethering and dependent on the Drosophila pattern-recognition receptors PGRP-LA and PGRP-SC2. Expression of apamin in the Drosophila gut or ingestion of Apamin by honeybees has positive effects on gut health as shown by a number of metrics.

      Major comments:

      The key conclusions are convincing and largely supported by the data as shown. The data is presented clearly, save for some areas in the results where the authors should be more explicit about the methods that were used as they affect the reader's interpretation of the results (see minor comments). If the authors wish to conclude that PGRP-LE and PGRP-LC are not required for the demonstrated functions of Apamin, the authors should do a double knock-down of PGRP-LC and LE together, as these pattern recognition receptors function partially redundantly in activation of the Imd pathway (e.g. doi: 10.1038/ni1356 ). The Introduction and Discussion would benefit from providing more context that helps the reader understand the significance of the research. Where is apamin expressed in the honeybee? Is it likely to be ingested and have effects on gut health in natural conditions? Do honeybees have homologs of PGRP-LA and PGRP-SC2? Do these findings translate to the honeybee system in any way or are they restricted to heterologous expression in Drosophila? It is surprising that there is no speculation or hypothesis provided about why PGRP-LA and -SC2 may enhance apamin activity whereas other components are nonessential. It was a significant part of the paper but receives almost no discussion. Line 264: The fact that Rel knockdown did not impair antimicrobial activity of Apamin is a bit odd since upregulation of PGRP-SC2 upon infection is at least partially dependent on Rel (de Gregorio 2002, EMBO J), and the authors find that PGRP-SC2 is required for apamin activity. This is somewhat incongruous.

      I cannot comment on the adequacy of the statistical analyses. Some recommendations to improve the methods:

      • Be specific about the kind of medium used to rear flies (provide or cite recipe). Different cornmeal-yeast media have very different compositions and can affect fly physiology and microbiome characteristics.
      • Specify flipping schedule (every 2-3 days?) - this also affects microbiome.

      Minor comments:

      Line 90: Be specific about how the constructs differ from endogenous Melittin and Apamin. Do the endogenous versions have signal peptides?

      Line 92: What is 'broad expression'? Ubiquitous? Specify driver or extent of expression.

      Line 93: Was this oral or septic P. aeruginosa infection?

      Lines 97-98: Melittin expressed genetically did not show activity against the one pathogen that was tested; making a broad statement without qualification about activity seems excessive.

      Line 105: Various Gal4 drivers that express in different tissues or a similar subset of tissues?

      Line 134: Present as a commensal? Pathobiont? Pathogen?

      Line 149: Are Cyanobacteria naturally present in gut microbiota? What are photosynthetic bacteria doing as part of a gut microbiome?

      Line 171: Where is apamin endogenously expressed in the honeybee? Only in the venom gland? Or in gut cells as done here in Drosophila?

      Line 252: -LC and -LE work in a complementary/semi-redundant fashion, so single knockdown is not an effective method of indicating that they are not required for antimicrobial function.

      Lines 279-283: The bacterial infections that expression of these AMPs were tested against should be mentioned in the text, as all bacteria are not equivalent.

      Line 296: Challenged with which bacteria?

      Line 328: Provide brief explanation of what Ttk depletion is for reader context.

      Line 719: This should say, '5 days after eclosion'.

      General comment on figures: The little icons used to denote what the figure is depicting (gut health, climbing, aging, etc.) are very effective.

      General comment on figure titles: Use of the term 'infectious dose' throughout does not make sense. I think what the authors mean is 'pathogen load' as they are testing using CFUs. 'Infectious dose' should only be used to refer to the amount/OD of pathogen that was initially administered to establish an infection. Also, 'oral feeding' should be used throughout instead of 'orally feeding'.

      Figure 1O: Abrupt die-offs at 1000hrs and 2800 hrs in the UAS-Melittin line suggest that lifespan experiment was only performed once and that die-offs may have been exacerbated due to infrequent flipping. This is perhaps not an issue as the lifespans appear to be quite different between the active line and control regardless.

      Figure 2F would be improved by putting the legend in the same descending order that the genotypes are displayed on the graph (tApamin infected, GFP infected, tApamin, GFP)

      Figure 3I: Unclear what small image inserted in the graph depicts.

      Figures 3N and 3O are verry low resolution and difficult to identify the differences that the authors intend to show.

      Figure 4 title is confusing. Do the authors mean, "Locomotion of flies expressing neuronal Apamin, sleep in flies with ubiquitous expression of Apamin, and Smurf results induced by different types of stress."?

      Figure 5: Some of these graphs are very cluttered and difficult to parse (particularly 5H). Suggest putting peptide sequences in figure title rather than underneath graphs to simplify and increase visual effectiveness.

      Throughout: Methods section in particular could use a solid edit for grammar. Homogenize capitalization of "Gram-negative/-positive" and "gram-negative/-positive"

      Line 98: "an AMPs" should be "an AMP"

      Line 119: Incorrect grammar. Suggest, "which did not affect the lifespan of female flies and had only a slight effect on male flies"

      Significance

      The paper reveals that apamin has antimicrobial properties. The intended significance seems to be an exploration of apamin for therapeutic potential in gut health, but this is not explicitly stated by the authors. The contribution mainly appears to be conceptual in nature.

      The findings appear to be in line with other recent in vitro results suggesting that apamin has antimicrobial properties (DOI: 10.9775/kvfd.2024.32125).

      Researchers interested in developing therapeutic applications for bee venom constituents or promoting gut health and microbiome balance will likely find this research of interest.

      My expertise is primarily in Drosophila molecular genetics and immunity. I have a broad understanding of Drosophila immune pathways, epithelial immunity, and infection dynamics. I do not feel qualified to comment on the statistics or data analysis aspects of this paper.

    1. 教父中,洗礼场景的宗教庄严与连环暗杀的强烈对比与讽刺效果。 属于蒙太奇剪辑,向电影《》奥德萨台阶场景

      虽然弗朗西斯·福特·科波拉的《教父》(1972)并没有直接复制《战舰波将金号》中“敖德萨阶梯”的场景,但在一些关键场景中,我们可以看到“敖德萨阶梯”的影响,尤其是在表现暴力、混乱和失去控制的场面时。这些影响主要体现在以下几个方面:

      1. 多重交叉剪辑和快速切换:

      “敖德萨阶梯”的核心是快速剪辑和不同视角的切换,营造出混乱和紧张感。《教父》中也有一些场景运用了类似的手法,例如:

      • 洗礼场景与连环谋杀的平行剪辑: 这是《教父》中最著名的蒙太奇段落之一。迈克尔·柯里昂在教堂为他的侄子举行洗礼仪式,庄严的宗教仪式与柯里昂家族成员同时进行的连环谋杀交叉剪辑。这种平行剪辑创造了强烈的对比和讽刺效果,一方面是神圣的仪式,另一方面是残酷的暴力,突出了迈克尔的冷酷和权力的扩张。这种多线叙事和快速切换的手法,与“敖德萨阶梯”中不同人物和事件的快速切换有异曲同工之妙。
      • 索洛佐和警长被杀的场景: 卢卡·布拉西被杀后,迈克尔与索洛佐和警长在餐厅会面,并最终将其二人枪杀。这个场景中也运用了快速剪辑和不同角度的切换,表现了事件的突发性和暴力性,虽然没有“敖德萨阶梯”那样大规模的混乱场面,但其剪辑手法仍然可以看到一定的影响。

      • 强调个体在群体暴力中的无助:

      “敖德萨阶梯”展现了人群在士兵枪口下的无助和恐慌。《教父》中虽然没有如此大规模的群体性屠杀,但在一些场景中也强调了个体在暴力面前的脆弱,例如:

      • 桑尼在收费站被枪杀的场景: 桑尼在开车前往妹妹家途中,在收费站遭到伏击,被乱枪扫射而死。这个场景虽然发生在个体身上,但其突然性和残酷性,以及个体在暴力面前的无力感,与“敖德萨阶梯”中平民在士兵枪口下的无助有相似之处。

      • 利用镜头运动和构图增强视觉冲击力:

      “敖德萨阶梯”中运用了大量的镜头运动和构图,例如俯拍、仰拍、跟踪镜头等,增强了画面的冲击力。《教父》中也善于运用镜头运动和构图来营造紧张气氛和表现暴力,例如:

      • 迈克尔在餐厅枪杀索洛佐和警长的场景: 这个场景中运用了特写镜头、中景镜头和全景镜头的切换,以及缓慢的推拉镜头,来表现迈克尔的紧张和决心,以及事件的突然爆发。

      • 象征性元素的运用:

      “敖德萨阶梯”中滚落的婴儿车是极具象征意义的元素。《教父》中虽然没有如此直接的象征性符号,但在一些场景中也运用了象征性的元素来表达主题,例如:

      • 橘子: 在《教父》系列电影中,橘子经常与死亡或不幸事件的发生联系在一起。

      总结:

      《教父》并没有照搬“敖德萨阶梯”的场景,但它借鉴了其一些核心的电影语言和表现手法,例如快速剪辑、对比、强调个体在暴力面前的无助、以及运用镜头运动和构图增强视觉冲击力。这些借鉴虽然并非直接的复制,但仍然可以看出“敖德萨阶梯”对《教父》的影响,尤其是在表现暴力和混乱的场景时。这体现了爱森斯坦的电影理论和实践对后世电影创作的深远影响。

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

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      1. General Statements

      We thank the reviewers for their thorough and positive evaluation of the manuscript.

      2. Point-by-point description of the revisions

      We revised the manuscript following the suggestions of the reviewers to make the article more concise and comprehensible to a wider audience. Specifically, we rearranged Section 5, rewrote the difficult-to-understand sections 5 and 6, and removed unnecessary or overlapping text in Introduction and Discussion. We have also addressed the specific points raised by the reviewers. The responses to individual points are detailed below.

      Reviewer 1:

      The reviewer did not ask for any changes to the manuscript.

      We thank the reviewer for the positive evaluation of the manuscript.

      Reviewer 2:

      1/ Title: Structure-based mechanism of RyR channel operation by calcium and magnesium ions

      The authors may consider using an alternative term instead of "operation".

      Thank you for the suggestion. We considered and discussed the term "RyR channel operation" very thoroughly with several colleagues, including native English speakers, and we found it to represent the complex RyR behavior in situ and in experiments most exactly. Alternative terms such as "control" suggest a one-way deterministic action from the ion binding to the protein state, which is not the case. The terms such as "modulation" implicate the presence of a higher RyR state-governing principle, such as phosphorylation, nitrosylation, binding of auxiliary proteins, etc.

      2/ Abstract: Please spell out CFF and MWC theorem.

      Thank you for the proposal. CFF was changed to caffeine; MWC was changed to Monod-Wyman-Changeaux

      3/ Line 87-88: "In striated muscle cells, RyR channels cluster at discrete sites of sarcoplasmic reticulum attached to the sarcolemma where electrical excitation triggers transient calcium release by activation of RyRs."

      There is no attachment between sarcoplasmic reticulum and sarcolemma, please rewrite.

      We respectfully disagree, since there is strong evidence for the existence of discrete contact sites between the sarcolemma and sarcoplasmic reticulum both at triads of skeletal muscle (Rossi et al., 2019) and at dyads of cardiac muscle (Mackrill, 2022), at which both membranes are firmly attached.

      However, to avoid potential misunderstanding, we changed the sentence to "In striated muscle cells, RyR channels cluster at the discrete sites of sarcoplasmic reticulum attached to the sarcolemma in triads or dyads, where electrical excitation triggers transient calcium release by activation of RyRs" (lines 86-87).

      4/ Lines 104-107: "Recently, mathematical modeling of the cardiac calcium release site (Iaparov et al., 2022) confirmed that Mg2+ ions could at the same time act as the negative competitor at the calcium activation site and as an inhibitor at the inhibition site. Unfortunately, the structural counterpart of RyR inactivation, an inhibitory binding site for divalent ions, has not been located yet in RyR structures."

      Note that the exact structural counterpart exists (Nayak et al., 2022, 2024), where Ca and Mg were found both at the activation and inhibition sites. The paragraph should be updated accordingly.

      We respectfully disagree. In the cited works of Nayak et al. (2022; 2024) it was shown that Ca and Mg ions bind firmly at the activation site. Both atoms were also observed at the ACP molecule bound at the ATP binding site. However, they were not observed at the divalent ion-binding inhibition site, which is distinct from the ATP binding site and resides in the loops of the EF-hand region.

      However, to clarify the meaning of the disputed sentence, we have changed it to: "Although binding of Ca2+ or Mg2+ to an inhibitory binding site has not been observed yet in RyR structures, a consensus is emerging that the EF-hand loops constitute this site (Gomez et al., 2016; Zheng and Wen, 2020; Nayak et al., 2024; Chirasani et al., 2024 )" (lines 107-109).

      5/ Lines 108-110: The activation of RyR by agonists was shown to be accompanied by a conformational change around the Ca2+ binding site that leads to a decrease in the free energy and to a concomitant increase of the Ca2+ binding affinity and a population shift between the closed and open conformations (Dashti et al., 2020).

      Please clarify to what state does the "decrease in free energy" refer, to the open or to the closed state?

      Thank you for the proposal. The text was changed to: "The activation of RyR by agonists was shown to be accompanied by a conformational change around the Ca2+ binding site that leads to a decrease in the free energy of the open state and concomitantly to an increase of the Ca2+ binding affinity of the activation site. As a result, the occurrence probability of a RyR state/conformation shifts from the closed toward the open (Dashti et al., 2020)" (lines 110-113).

      6/ Figure 2: please indicate if distances were measured between the C-alphas or side chains.

      Thank you for the proposal. The figure legend was modified to "Distances D1 between the Cα atoms of E4075 and R4736 or equivalent. Right - Distances D2 between the Cα atoms of K4101 and D4730 or equivalent."

      7/ Line 353-357: "These data suggest that interactions between the basic arginine residue R4736 and the acidic residues at the start of the initial helix E of the EF1-hand are specific for Ca2+-dependent inactivation in RyR1, whereas the interactions between the lysine K4101 that immediately follows the F helix of EF1 and the middle of the S23 loop (corresponding to D4730 and I4731 in RyR1) may play a part in the inactivation of both RyR1 and RyR2 isoforms.

      Sentence is unclear; please rewrite. Overall, the entire section "Spatial interactions between the EF-hand and S23* regions" should be simplified and shortened.

      Thank you for the proposal. The text was changed to: "These data suggest that interactions between the basic arginine residue R4736 and the acidic residues E4075 and D4079 are specific for Ca2+-dependent inactivation in RyR1, whereas the interactions between the lysine K4101 and the residues D4730 and I4731 (rRyR1 notation)* may play a part in the inactivation of both RyR1 and RyR2 isoforms." (lines 334-337).

      We did not find a way how to make the whole section simpler and shorter at the same time without losing clarity.

      8/ Lines 246-249 and Table 1. "all structures corresponding to rRyR1 residues 4063-4196 were<br /> subjected to energy minimization and submitted to the MIB2 server for evaluation of the ion binding score (IBS) of individual amino acid residues and the number of ion binding poses (NIBP) for Ca and Mg ions."

      Please elaborate on the "ion binding score" and "number of ion binding poses" concepts and provide reference for the MIB2 server.

      Thank you for the proposal. We added the reference for the server (Lu et al., 2022) (line 228) and added the information: "IBS values of individual residues are determined using sequence and structure conservation comparison with 409 and 209 respective templates from the PDB database for Ca2+ and Mg2+ (Lin et al., 2016) and assessing the similarity of the configuration of the residue to its configurations in known structures of its complexes with the given metal (Lu et al., 2012). Ion binding sites are determined by locally aligning the query protein with the metal ion-binding templates and calculating its score as the RMSD-weighted scoring function Z. The site is accepted if it has a scoring function Z>1, and based on the local 3D structure alignment between the query protein and the metal ion-binding template, the metal ion in the template is transformed into the query protein structure (Lin et al., 2016). The larger the IBS value, the higher the tendency of the residue to bind the ion. The larger the NIBP value, the larger the number of such complexes with acceptable structure" (lines 224-234).

      9/ Lines 460-466: Nine structural models of RyR were selected, and then these are referred to in the text only with the pdb code. The reviewer understands that it would be difficult to recapitulate all conditions but either a table in the main manuscript file or a minimal description in the text following the pdb code would increase clarity and help readers to follow the content.

      Thank you for the proposal. We added a new Table 2 "Model structures used for identifying the allosteric pathways" on line 452 that contains the required information, and inserted a reference to it in the text at line 446 "According to these criteria we selected five RyR1 model structures (Table 2)..."

      10/ Line 467: "In the selected structures, we identified residues with high allosteric coupling intensities (ACI) for both the inhibition and activation network and compared them with residues important for ligand binding and gating of RyR (Table 2)."

      Please define further the concept of "allosteric coupling intensities". The corresponding methods section appears to focus on the outputs of the OHM server without delving too much on the algorithm or principles followed. Is the allosteric coupling between neighboring residues, or reflect movement of the residues due to ligand binding? Is there a "reference" state or are the comparisons carried out within each allosteric state? This would help to introduce better the sections "The inhibition network" and "The activation network".

      Thank you for this suggestion. We have lately realized, considering both the server output and the original work of Wang et al. (2020), that a better term for the variable depicting the role of the residue in the allosteric pathway would be the residue importance RI rather than the ACI. The allosteric pathway is determined on the basis of the network of contacts between pairs of residues in the given structure. The more contacts are present between two residues, the higher is the probability that a perturbation will be propagated from one to the other residue (Eq. 3 of Wang et al. (2020)). An allosteric pathway is then defined as the pathway that transmits the signal the whole way from the allosteric site to the active site.

      Based on this we have changed in the manuscript the term "allosteric coupling intensity" to "residue importance" throughout the text and figures of the manuscript. It should be underlined, that this change has no effect whatsoever on presented data and conclusions. We inserted the following formulation in the Results section:

      "The term residue importance defines the extent to which the given residue is involved in the propagation of a perturbation from the allosteric site to the active site, i.e., the fraction of simulated perturbations transmitted through this particular residue. The more contacts are present between two residues, the higher is the probability that a perturbation will be propagated from one to the other residue (Wang et al., 2020)." (lines 439-443).

      We also inserted the following formulations into the Methods section: "The simulation of the perturbation propagation was performed 10 000 times per structure and pathway to estimate the values of residue importance." (lines 1093-1095), and we expanded the relevant sentence: "Allosteric pathways were traced using the server OHM (https://dokhlab.med.psu.edu/ohm/#/home, (Wang et al., 2020)), in which the allosteric pathway is determined on the basis of the network of contacts between pairs of residues in the given structure." (lines 1082-1084).

      11/ Figure 8: The figure would be more meaningful if the pathways were drawn in the context of the 3D structure.

      Thank you for the proposal. The pathways described in Fig. 8 are too complex for description in the RyR 3D structure, therefore they were not presented in the original manuscript. However, to follow the reviewer's proposal we have illustrated the pathways observed in the inactivated RyR1 channel (7tdg) and the open RyR2 channel (7u9) in Expanded View Figure EV1 and added the corresponding Expanded View Movie EV1 and EV2. These RyR structures were selected for displaying both the intra- and inter-monomeric inactivation pathways.

      12/ Lines 610-612: "The structure of the inactivated RyR2 has not been determined yet; however, it is plausible to suppose that it exists at high concentrations of divalent ions and differs from the inactivated RyR1 structure by the extent of EF-hand - S23* coupling. "

      The speculation would be more fit for the discussion section.

      Thank you for the proposal; however, the sentence introduces a logical supposition, necessary there for reasoning on the construction of the model. We reformulated the sentence to: "In the absence of a structure of the inactivated RyR2, the model assumes that such a structure exists at high concentrations of divalent ions and differs from the inactivated RyR1 structure by the extent of EF-hand - S23* coupling." (lines 573-575).

      13/ Lines 617-619: Closed and primed macrostates could be combined into a single closed macrostate of the model since both are closed and cannot be functionally distinguished at a constant ATP concentration.

      The rationale for combining closed with primed does not seem a good idea, especially since the authors also mention that "the primed state is structurally very close to the open state" (lines 925-926). If the COI model is based on the structural findings, in principle it seems that primed should be treated separately.

      Thank you for the proposal. The use of both the closed and primed states was crucial for solving the model. As a matter of fact, although the primed and closed states are in part structurally different, functionally they are identical, that is, closed. Consequently, to be distinguished in a functional model we would need to incorporate single-channel data obtained under conditions when the ratio of closed and primed channels was modulated under otherwise identical conditions. Unfortunately, such a set of data, for instance at a varying ATP concentration for a range of cytosolic Ca2+ concentrations, does not exist for either RyR1 or RyR2 channels. Moreover, while there are several RyR1 high-resolution structures in the primed state (such as the 7tzc that we used; 2.45 Å; Melville et al. (2022)), the resolution of the corresponding RyR2 structures (6jg3, 6jh6, 6jhn; 4.5 - 6.1 Å; Chi et al. (2019)) is not sufficient for determination of allosteric pathways. Fortunately, however, the two sets of conditions for RyR2 open probability data that were available in the literature turned out to represent activation of channels either selectively from the closed state (Fig. 10C), or almost selectively from the primed state (Fig. 10A, B). This allowed us to interpret the difference in the allosteric coefficients as a consequence of this fact.

      To better clarify the idea, the corresponding text of the Discussion was modified as follows (lines 926-931): "RyR channels can be considered mostly in the primed state under these conditions since the binding of ATP analogs induces the primed structural macrostate in RyRs even in the absence of Ca2+ (Cholak et al., 2023). Fortunately, the two sets of conditions for RyR2 open probability data that were available in the literature turned out to represent activation of channels either selectively from the closed state (Fig. 10C), or selectively from the primed state (Fig. 10A, B).", and "construction of such a model is at present hampered by the lack of open probability data at a sufficiently wide range of experimental conditions and the absence of high-resolution structures of WT RyR2 in the primed state" (lines 934-937).

      14/ Line 619. Please define the "COI" acronym. I assume it is closed, open and inactivated but this is not mentioned.

      We thank the reviewer for noticing the insufficiency. We expanded the specific sentence as follows: Therefore, we constructed the model of RyR operation, termed the COI (closed-open-inactivated) model, in which we assigned a functional macrostate corresponding to each of the closed, open, and inactivated structural macrostates (Figure 9A)" (line 582).

      15/ Figure 9: The diagrams are difficult to follow. Something that could improve it is to differentiate more between open and closed gates, but further elaboration would help the reader.

      We thank the reviewer for paying attention to details. The open state was differentiated in Figure 9 (after line 603) by adding a pore opening to the gate.

      To elaborate on the gating transitions and to keep the manuscript concise, we added a new Expanded View Figure EV2, which illustrates the relationship between the ion binding within macrostates and the transitions between macrostates.

      Nevertheless, for the complexity of the model, which would need a multidimensional presentation, we had to limit the illustration to only the binding of the first ions at the binding sites. We hope that it will help the reader to grasp the principle of the model function more easily.

      16/ One comment is that the manuscript is too long; the manuscript exceeds the typical length required by most journals. To enhance its suitability for publication, the content needs to be synthesized and streamlined. The manuscript is written for an audience specialized in the RyR field and may be challenging for outsiders or for readers unfamiliar with structure and/or biophysical models.

      We thank the reviewer for opening this problem. The specific contribution to the understanding of RyR operation communicated by this manuscript was achieved by the synergy of approaches coming from different fields of RyR research - the structural, the functional, and the synthetic/systems ones. This needed deep immersion into complex studies performed over several decades to unwrap their complementary contributions. Only then we could synthesize the stepwise advances and integrate the mosaic of partial discoveries into the COI model. When conceptualizing the manuscript we were also considering a two-paper version, one on structural aspects and the other on modeling aspects. We realized that the two papers would need to have a very high overlap at the allosteric mechanism to be understandable in separation and would be difficult to publish in the same journal. We also anticipated a typical side effect that structuralists and modelers would read just their parts and would not appreciate enough the feedback from alternative views - how to design and interpret future structural, functional, and modeling studies.

      Compacting the manuscript would be extremely difficult for us. In our view, the dense text would make it even more challenging for readers unfamiliar with some of the numerous approaches used here, as often happens to prominent multidisciplinary journals. Maybe it would be possible with the help of AI, but for now, we prefer to remain authentic.

      Nevertheless, we made some effort. To shorten the manuscript, we have removed the paragraph describing the timeline of the search for the RyR inhibition site that was originally on lines 126-151 and replaced it with the paragraph on lines 129-134: "The regulatory domains involved in both, activation and inactivation of RyRs (Figure 1) are located in the C-terminal quarter of the RyR. The Central domain participates in the Ca2+ binding activation site; the C-terminal domain bears several residues of Ca-, ATP- and caffeine-binding activation sites; the U-motif participates at the ATP- and caffeine-binding sites; the EF-hand region contains the putative Ca-binding pair EF1 and EF2; and the S23 loop bears one residue of the caffeine-binding site and two residues interacting with the EF-hand region of a neighboring monomer (Samso, 2017; Hadiatullah et al., 2022)". We also removed the statements about the proposed kinetic mechanism of inactivation by Nayak et al. (2022), originally on lines 175-184. Finally, we removed the discussion of the work of Gomez et al. (2016) originally on lines 882-889, since it fully overlapped with the statements in Results on lines 358-367 (now lines 338-347). We also moved the text of the subsection "Relationship between the COI model and RyR allosteric pathways" (originally lines 670-685) into subsection "Construction of the model of RyR operation", lines 592-603 and 645-662 of the revised version.

      17/ Another comment is the limited consideration of two relevant published works. One is by Chirasani et al. (2024), focused on allosteric pathways similar to the ones described here. The other work is by Nayak et al (2024), with cryo-EM structures of RyR1 focused on the interplay with Mg2+ and Ca2+. Overall, the manuscript would be strengthened by incorporating such related results in the literature.

      We thank the reviewer for the concerns, but we cannot fully agree. The paper of Chirasani et al. (2024 ) was cited in the manuscript as its online-first version, Chirasani et al. (2023). The manuscript now refers to the printed version proposed by the reviewer. The Chirasani et al. work was discussed on lines 870-881. The paper concentrates on the interaction between the EF-hand region and the S23 segment and its effect on RyR inactivation, which we referenced in the manuscript, but not on the allosteric pathways as mentioned by the reviewer. To broaden the consideration of this important work, we have introduced a more detailed discussion of Chirasani et al. (2024 ) by adding the following text to the manuscript: Lines 881-888: "Based on their structural analysis of the open RyR1 structure 5tal, Chirasani et al. (2024 ) proposed that narrowing the gap between the EF-hand domain and S23 loop, resulting in H-bonding interactions between the EF-hand residue K4101 and the S23 loop residue D4730, and those between the EF-hand residues E4075, Q4076, D4079 and the S23 loop residue R4736, is a consequence of the binding of Ca2+ to the EF-hands. However, our PDBePISA analysis revealed a similar number of interactions between the EF-hand region and the S23 loop not only in open and inactivated but also in primed RyR1 structures (Figure 3). The presence of EF hand-S23 hydrogen bonds in the primed and open RyR1 structures suggests that the proximity of the EF-hand domain and S23 loop is a structural trait distinguishing RyR1 from RyR2, not a consequence of Ca2+ binding to the EF hand.*"

      The data and ideas of the illuminating work of Nayak et al. (2024) were discussed and referred to in the manuscript in several places, originally lines 74, 77, 164 (Introduction), 311, 340 (Results), 892-893, and 971 (Discussion). To broaden consideration of this work, we have expanded the discussion of this paper by adding the text shown in bold into the Introduction: "Recent studies reporting RyR structure at a high divalent ion concentration provide only indirect support for the molecular mechanism of Ca2+/Mg2+-dependent inactivation. Wei et al. (2016) and Nayak et al. (2024) observed a change in the conformation of the RyR1 EF-hands in the presence of 100 µM Ca2+ and 10 mM Mg2+, respectively, compared to low-calcium or low-magnesium conditions." (lines 135-138) and in the Discussion (lines 889-891): "The recent RyR1 structure 7umz (Nayak et al., 2024) provided evidence of Mg2+ ion bound in the RyR activation site, thus confirming the functional studies that established competition between Ca2+ and Mg2+ at this activation site (Laver et al., 1997; Zahradnikova et al., 2003; Zahradnikova et al., 2010)."

      Reviewer 3:

      Minor comment: While I am not an expert in allosteric model construction and therefore cannot fully assess their methodological approach, I observed that the authors fixed a number of parameters to achieve model convergence. A more detailed explanation of the rationale behind these fixed parameters would enhance clarity. Currently, these parameters are not clearly specified in the text and are somewhat obscured by the broader description of all parameters included in the model.

      We thank the reviewer very much for this comment, which made us realize that the relevant sections were written in a too technical manner, without sufficient explanation of the ideas behind the derivation and optimization of the model. To clarify the rationale of this process, we have rewritten the subsection "Derivation of the model open probability equation" and the section "Description of RyR operation by the COI model". In the subsection "Derivation of the model open probability equation", we have explained the simplification of the full set of equations (Eqs. 3A-C) into Eqs. 4A-C (lines 642 - 666). In the section "Description of RyR operation by the COI model", we have explained the extent of over-parametrization and the rationale of reducing it by three methods: combining the data into groups with common parameter values; eliminating parameter interdependence by fixation of one parameter at a preset value taken from the literature or postulated a priori; and sharing parameter values between data groups when no significant difference between these values was observed (lines 683-685, 702-710, 719-740).

      We hope that these changes make the manuscript more comprehensible.

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