Interesting take to see the progress of man come about, just discussing how humans went from a bare existence to incredible technological feats.

I fear this is so.

This is one of my difficulties. I put a lot of stuff in my blog-as-memex but don't have a good way of surfacing them again. Theoretically I could do this with categories, but that gets overwhelming fast. This is why I'm thinking about using a blog and a wiki together for this purpose.

It me! This is kinda what people who operate as web librarians do.

This is tagging.

How many people use Evernote as a Memex?

Bush points out that indexing systems and rules do not duplicate the human mind - we must convert our own mental associations to a form we can use to search them - but that the human mind works by association. I extrapolate from this the idea of hypertext as a model of how the mind works. I'm going to keep an eye out for other instances of this idea.

Here, he basically sums up his position on why language is more self-focused than it used to be--it's just how we talk, it's not how we think

While important, I don't think it needs to be front and center. We could have a whole page/section to Accessibility potentially working with Support and their materials. Annnd I have soooo many little cheat sheets on good practices that, to my knowledge, don't live anywhere.

It was also interesting to know about the blog which spoke about playing GTA 4 as a law abiding citizen and following all laws. Hearing conversations and abuses while walking the streets. All of these situations are inspired from our daily lives but we tend to miss them or ignore them as there are so many other attributes which require more of our attention.

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

Learn more at Review Commons

Reply to the reviewers

Reviewer #1:

This is the first such piece of data to come from human infective parasites in the field. Technically this is a feat - because the small number of parasites that are present per mL of human blood at any given time during infection with T gambiense. Nevertheless they manage to identify up to 14 unique VSGs per patient sample. And this raises the first theoretical question: can they extrapolate to the average diversity load per human?

This is an intriguing question that we would like to eventually answer, but we do not believe we can make this estimate from the data we currently have. We know our sampling is insufficient based on the correlation between parasitemia and diversity, and we do not have sufficiently precise estimates of parasitemia that could be used to extrapolate total diversity in the blood. Moreover, our analysis was only performed on RNA extracted from whole blood samples. Recent studies indicate that significant populations of parasites reside in extravascular tissue spaces, and our analysis did not address antigenic diversity in these spaces. We believe it is unlikely that the blood alone reflects the full diversity of VSG expression in an infection, and an estimate based only on blood-resident parasites (if possible) could be misleading.

this is important because the timing of sample collection (ie that it occurred within a period of weeks) suggesting that an initial group of infected tsetse infected these patients (rather than a small number of interactions between a bloodmeal and a new infection - generally in itself on the order of 1 month or so). If parasitemia is low and diversity limited, this would explain both why CATT works as well as it does (because really it shouldn't at all!) and perhaps even the chronicity of infection (in the sense that the organism is unlikely to "run out" even of complete VSGs, never mind mosaics). The paper would benefit from a direct discussion on this.

Indeed, the timing of sample collection could inform our interpretation of the data. However, sample collection occurred over a period of six months. More importantly, patients were in both early and late stage disease at the time of sample collection, so we cannot estimate how long any individual patient had been infected. We have added text (line 180) to highlight this fact. Because some patients were infected at least 6 months apart (if not much more than that), it is unlikely that patients were infected around the same time by a small group of infected tsetse flies. Reviewer #1 introduces an interesting point about the efficacy of the CATT diagnostic test as it relates to antigenic diversity. We discuss CATT sensitivity in the introduction (lines 115-120) as well as the discussion, where regional sensitivity differences are mentioned (lines 715-718). Given uncertainty about total diversity and time since initial infection, we have refrained from speculating about how diversity/timing could affect CATT sensitivity.

An interesting feature of this new study is the apparent bias to type B N-terminal domain VSGs as well as the discovery that two patients share a specific VSG isolate (though it is not mentioned whether they are related by distance etc). This raises the possibility of substrains with different VSG archives that vary by geography.

We found two VSGs which were expressed in more than one patient. One was expressed in two patients from the same village (village C) while the other VSG was common between two cases originating from villages C and D, some 40 km apart. We agree that our data generally support the possibility that the VSG archive might vary geographically. We have performed additional analyses suggested by reviewer #2 that support this idea: we have now shown that Tbg patient VSGs classified in this study, which originated from the DRC, are distinct from the VSGs encoded by the reference strain Tbg DAL 972 which was isolated in Cote d’Ivoire. We mention this possibility on lines 721-724.

Alternatively it suggests that perhaps type B VSGs are picked up differentially by serology (and there the one feature of type B VSGs that could be shared, with regards to detection, is the O-hexose decoration on a number of type B VSG surfaces. Could CATT be detecting elements common to sugar decorated VSGs? Experimentally this is something that can be tested even with mouse infection materials.

This is indeed an intriguing possibility. We mention this in the discussion (lines 772-778): “In T. brucei, several VSGs have evolved specific functions besides antigenic variation [74]. Recently, the first type B VSG structure was solved [75], revealing a unique O-linked carbohydrate in the VSG’s N-terminal domain. This modification was found to interfere with the generation of protective immunity in a mouse model of infection; perhaps structural differences between each VSG type, including patterns of glycosylation, could influence infection outcomes.” While this is an experimentally tractable explanation for the type B VSG bias we observe, we believe such experiments are beyond the scope of the current paper.

Side comment: are the common VSGs mutated between patient samples?

We classified VSGs as common between patient samples if they had >98% nucleotide sequence identity as well as meeting the other quality cutoffs such as 1% expression level and consistency across technical replicates. This identity cutoff still allows for several mismatches between sequences, which we do occasionally observe. However, we cannot confidently rule out that the “mutations” we observe are sequencing or PCR errors. Thus, we cannot say for sure if there are mutations between common VSGs.

Reviewer #2

1.Throughout the manuscript you observe 'diversity' in expressed VSG and its existence becomes a principal conclusion. I feel that the meaning of diversity and its significance is not sufficiently explained for the reader. In the abstract (l48) you say that there is 'marked diversity' in parasite populations. Presumably you mean parasite infrapopulations, i.e. within patients, not across the DRC? In any case, what is 'marked' about it, and relative to what? Why does it matter that there are multiple expressed VSG in a single patient at one time? Is this not a reasonable expectation for a population of (presumably) clones capable of switching the expressed VSG? How is this different to the view typical of the literature since 1970 that one VSG dominates while others wait in the background at low frequencies. If 'diversity' is the conclusion, then you need to define it and explain its significance more.

When we refer to diversity, we do mean infrapopulations of parasites within patients, or individual animals in this case, rather than across the DRC. We have edited the text to make this clear (see below). However, the study which benchmarked the application of VSG-seq to quantify VSG expression in vivo during mouse did not support the previously-held view that one VSG dominates while others wait in the background at low frequencies. Frequently we observe a handful of VSGs present at 10-20% of the population at any timepoint, and many VSGs (~50% of all detected variants) present at “In a proof-of-principle study, we used VSG-seq to gain insight into the number and diversity of VSGs expressed during experimental mouse infections [30]. This proof-of-principle study revealed significant VSG diversity within parasite populations in each animal, with many more variants expressed at a time than the few thought to be sufficient for immune evasion. This diversity suggested that the parasite’s genomic VSG repertoire might be insufficient to sustain a chronic infection, highlighting the potential importance of recombination mechanisms that form new VSGs.

2.Following on from 1., why does the analysis deal in counts of distinct VSG or N-terminal domains, and not then progress to their relative expression? The expression data are in Supp Table 3 and they show that, in most cases where many VSG are observed in the same patient, 1-3 of these are 'dominant', i.e. they account for >50% of the population.

The VSG-seq analysis pipeline does estimate the relative expression level of each identified variant in the population, and this information is available in the supplemental data (Supplemental Figure 1, Supplemental Table 3). However, we chose not to rely on these measurements too heavily because there was some variation between Tbg technical replicates, which is shown in the supplemental heatmap (Supplemental Figure 1). Replicate three tends to not agree with the first two replicates. We suspect that this was due to the order of sample processing and the fact that the parasite-enriched cDNA sample was repeatedly freeze-thawed between library preparations for technical replicates. Additionally, because our sampling did not reach saturation, some VSGs are not detected in all replicate libraries, making it difficult to estimate their abundance.

We have added a discussion of these issues to the text on lines 431-433: “Because our sampling did not reach saturation, resulting in some variability between technical replicates, we chose to focus only on the presence/absence of individual VSGs rather than expression levels within parasite populations.”

Figure 1 deals in VSG counts, but I would then expect another figure to illustrate the reality that only a minority of these observed VSG are likely to be clinically relevant (i.e. the subject of the immune response). This impacts the 'diversity' conclusion, as given in the discussion (ll 657-9), because you cannot afford to treat all these VSG equally when their abundances are quite different.

---

We agree that relative expression level is a useful metric, but absent longitudinal sampling it is impossible to determine which VSGs are clinically relevant as defined by the reviewer: low abundance VSGs at one time point may be the predominantly expressed variant at another. Moreover, the threshold for triggering an anti-VSG antibody response remains unknown. Thus, we have chosen to treat all detected variants equally.

3.How related are these VSG? Were you able to ensure unique read mapping to the VSG assembly? Can you show that reads mapped to a single VSG only and therefore, that the RPKM values are reliable?

Our analysis accounts for the fact that VSGs can be very similar. We only considered uniquely mapping reads in our VSG-seq analysis. We also account for mappability in our quantification, so VSG sequences that are less unique (and thus have fewer uniquely mapping reads) are not artificially underrepresented in estimates of relative expression. We have specified the parameters used for alignment (line 274) in the methods.

4.The authors observed no orthology between expressed VSG and DAL972 genes. This is really interesting and deserves closer attention. Presumably there is microhomology? For T. brucei VSG, with constant recombination, we would predict that a comparison of the VSG in West and Central Africa would reveal a pattern of mosaicism, such that individual sequences in DRC would break down into motifs present in multiple genes in the West African reference. Question is, how many genes? What does that distribution look like? What is the smallest homology tract? There is an opportunity here to comment on how VSG repertoires diverge under recombination. How much of the expressed VSG sequence is truly unrepresented in the West African reference (or other T.b.gambiense genome sequences available in ENA). I can believe that none of the N-terminal domains in these data are present intact in DAL972, but I cannot believe that their components are not present without evidence.

We appreciate the reviewer’s suggestion to look at this more closely. We have performed additional analyses to address sequence similarity, or lack thereof, between the assembled DRC patient VSG and the West African reference TbgDAL972. We ran a nucleotide BLAST of expressed VSGs against the TbgDAL972 genome reference sequence pulled from TriTrypDB.org (release 54). We have added a supplemental figure depicting the results of this analysis (Supplemental Figures 6 and 7). Briefly, our analysis shows that most of the N-termini we identified have no significant similarity to DAL972 VSGs, even with very permissive search parameters. There are frequent hits in the VSG C-termini, however, which might be expected. Most BLAST hits are short spans 98% identity are short 20-25 bp regions. Given the large divergence from the reference, we were unable to infer any patterns of recombination in the VSGs. However, we believe this analysis supports our claim that the N-termini of VSGs assembled from DRC patients are novel, with their component parts largely unrepresented in the West African reference genome.

Figure 4 compares NTD type composition in the DRC data with previously published mouse experiments. The latter take place over very short timescales in maladapted hosts, while the timescales of the latter in natural hosts are unknown but plausibly very much longer. So are these data really comparable and are we learning anything from their comparison, given that the most likely explanation for the NTD bias in expressed VSG is the underlying genomic composition?

Indeed, this is our intended conclusion from figure 4. The figure is meant to illustrate our claim that the expressed VSGs in each experimental set reflect the underlying genomic composition of their corresponding reference strains, despite fluctuations over time. The language and legend for Figure 4 has been clarified to emphasize this point. We have emphasized in the text that it is unknown whether these fluctuations occur over time in much longer natural infections.

---

6.Please comment on the technical reproducibility of the data, there are multiple instances in Supp Table 3 where technical replicates expressed different VSG.

Three RNA-seq library technical replicates were prepared for each individual gHAT patient RNA sample. Replicates were prepared in batches together so all 1’s were done on the same day, for example. The original parasite-enriched cDNA sample was frozen and thawed between each batch. We suspect that the cDNA degraded after repeated freeze-thaw cycles, which is why replicate three tends to not agree with the other two as can be seen on the heatmap in supp fig. 1 and the expression data in supp table 3. We also suspect the fact that our sampling did not reach saturation resulted in the detection of different VSGs in individual replicate preps. We have edited the methods and mentioned this variability in the results section to communicate this issue more transparently.

• Lines 395-397 “Using RNA extracted from 2.5 mL of whole blood from each patient, we prepared libraries for VSG-seq in three separate batches for each technical replicate.”
• Lines 431-433: “Because our sampling did not reach saturation, resulting in some variability between technical replicates, we chose to only focus on the presence/absence of individual VSGs rather than relative expression levels within the population”

Reviewer #3

1. In line 499, the authors conclude the due to the expressed VSGs being different in the blood and CSF being difference it may indicate that different organs harbor different VSG sets. Given that this is n=1 for patient samples I think this is too speculative a statement. There is also no indication as to whether the samples were taken at the same time or not.

This is absolutely correct. The precise timing of CSF sample collection is unknown for these samples. It likely occurred within hours to days after blood collection, but even on this short time scale, the unique CSF repertoire could represent the antibody-mediated clearance of one VSG population and replacement with another. We have scaled back our language and only point out that there are unique VSGs in this space (Lines 522 – 524).

I think that the authors need to be very careful as to the conclusions drawn about VSG expression over time in terms of hierarchy and N-terminal fluctuations. For any conclusions to be drawn on the hierarchy of VSG expression more data points are needed taken over time (this is obviously challenging when looking at patient samples). I find it too speculative to draw any conclusions when single time points are assessed and the assumption on the progression of the infection depends on whether it is a Tb or Tbr.

Reviewer #2 also pointed this out. We agree and have attempted to limit definitive conclusions in the text and instead discuss multiple possible explanations behind our observations.

I found some of the figure legends a bit terse. For example, in Figure 1 C, what do the black circles and lines represent? Perhaps a little more detail would help the reader.

Clarified legends for UpSet plots in figures 1C and 3C as follows: “The intersection of expressed VSG sets in each patient. Bars on the left represent the size of the total set of VSGs expressed in each patient. Dots represent an intersection of sets with bars above the dots representing the size of the intersection.”

In figure 2, I found it difficult to distinguish between the orange and dark red in (A) and the two lighter blue colors.

We have changed N-terminal type color palette for all plots to make red and blue hues more distinctive.

In line 389 – estimate

Corrected

In line 498 - should be reference been to figure 2C?

This should be a reference to Figure 3B. We have corrected the reference.

Yes, because we rarely make progress in other aspects. For technological problems there's a clear solution that people will buy if it works. Deliberate sociological change you may have to force, which is never a good basis.

Author Response:

Reviewer #1 (Public Review):

This is a clearly written manuscript describing an elegant study that demonstrates how microsaccades are not the triggers of attentional effects, and that attentional modulations can be observed in the absence of microsaccades. This is a very much needed work, especially in the light of the recent debate regarding whether or not microsaccades are the cause of peripheral attentional effects. By explicitly comparing and quantifying the effects of attention on neuronal responses in the presence and in the absence of microsaccades, this work provides important insights on this debate. I think the work is well conducted and the results are solid.

We thank the reviewer for their supportive comments!

I only have few comments/suggestions:

1. Lines 125-126, the authors report that monkeys generated frequent microsaccades but their overall direction was not systematically biased towards the cue location. This seems to be in contrast with what previously reported in the literature in humans and monkeys. I think this discrepancy should be discussed in the discussion. Is this simply the result of different experimental paradigms (maybe exogenous vs endogenous attention, or the presence of the cue for the entire duration of the trial, ect)?

As suggested, we discuss three main factors which may contribute to this discrepancy:

The first factor is the difference in the time window used for microsaccades analyses. Previous reports focused their analyses of microsaccades on the time window immediately after cue onset. In our analyses, the time window focused on is the ‘delay period’ which is hundreds of milliseconds after the cue and the time epoch used in most electrophysiology studies about attention.

A second factor is how the spatial cues were presented. In our paradigm the cue ring appeared in the periphery and then disappeared. In contrast, previous paradigms used a cue presented near fixation that persisted throughout the trial. Our brief peripheral cue provides less of an impetus to generate small saccades directed towards the cue, compared to the case when the cue is continuously near the center of gaze.

A third factor is that monkeys in our task were trained to release a joystick to report their detection of stimulus events, rather than make a saccade. Because human and monkey subjects tend to make microsaccades in the same direction as their upcoming saccadic choices (Yu et al., 2016), attention tasks using saccade reports will tend to introduce this direction bias on microsaccades. By using a joystick release, we minimized these lateralized effects related to saccade preparation.

These points are now addressed in the second paragraph of discussion.

1. It is very interesting that microsaccades modulate neural responses for stimuli that are much further away from their landing location. However, the stimulus used in these cueing tasks is also unnatural. Normally we are not fixating on a meaningless dot while all the interesting stimuli are presented in the periphery. In normal conditions the foveal input is rich in detail and it is generally relevant (that's why we are foveating certain stimuli in the first place). I wonder if the authors can comment on whether the modulations reported here would also occur in more natural conditions when an interesting and maybe salient/relevant stimulus is presented at the center of gaze, while subjects are also attending to a peripheral target. Will the neural response be modulated selectively for neurons for which the receptive field is on the peripheral target or will it also affect neurons where the receptive field aligns with the microsaccade target location in the fovea?

The reviewer raises a very good point. In our study, the relationship between microsaccades and attention-related modulation was examined when monkeys selectively attended a stimulus located in the near peripheral visual field while maintaining central fixation. We agree that under more natural conditions, the monkey would just look directly at the peripheral stimulus. As in many attention studies with this type of design, our experiments hold the system in a state of sustained peripheral attention which would otherwise be much shorter.

We believe that similar modulation at the peripheral location would be briefly observed if the monkey were allowed to satisfy the natural tendency to look at the stimulus, although this would make it more difficult to examine the relationship with microsaccades. This would be consistent with the documented pre-saccadic modulation of attention (e.g., documented by the Carrasco lab, Li, Hanning, & Carrasco, 2021).

Once the attended stimulus is foveated, there is strong behavioral evidence from several recent studies demonstrating that attention can be selectively distributed even within the fovea (Poletti, Rucci, & Carrasco, 2017). Considering the now substantial evidence that the foveal portion of the SC map is activated when the behaviorally relevant location is at the center of the visual field (e.g., during parafoveal smooth pursuit as in Hafed & Krauzlis, 2008), we expect that SC neurons with foveal RFs would display similar attention-related modulation as we found here. However, to the best of our knowledge, there have not yet been studies documenting the attention-related modulation of neurons with foveal RFs and the possible influence of microsaccades.

We agree with the reviewer that these are interesting points, and have now added a new paragraph in the discussion (final paragraph) to address this point.

1. The authors do not report behavioral performance. Presumably the task is very easy, but I wonder if reaction times and performance correct was related with the attentional effects and how did it change with respect to microsaccade direction, e.g., were subjects' reaction times shorter at the cued location also when microsaccades were directed at the opposite location? I think this information would be very valuable.

We agree it is valuable to document the behavioral performance; we had omitted this because this is the same task we have used in previous studies which do include such behavioral documentation.

To address the reviewer’s comments, we added an analysis and plot documenting the hit and false alarm rate for each subject in each experimental session. To accommodate this new plot, we have now divided the original Figure 1 (which included task, neuronal data and microsaccades) into a new Figure 1 (task, behavior, and neuronal data) and a new Figure 2 (microsaccades). The new plot showing hit and false alarms is Figure 1b in the revised manuscript.

The task was not especially easy – we adjusted the amplitude of the color saturation change to be just slightly above the threshold for detection; hence, the hit rates were generally between 75-90%. The performance was very consistent across sessions in our well-trained monkeys, and the low rate of false alarms for ‘foil’ changes provides behavioral confirmation that they attended to the correct stimulus location.

To address the comments about reaction time, we have added a new plot to our new Figure 2 (Figure 2c) showing the monkeys’ hit rates (top) and joystick release times (bottom) subdivided based on whether there were no microsaccades, microsaccade towards, and microsaccades away from the cued location (-50 to 50ms relative to cued stimulus change onset). These plots show that when there were no microsaccades, behavioral performance was at least as good as with microsaccades. When there were microsaccades, reaction times were slower when microsaccades were directed away from the cued location. As the reviewer may have anticipated, these effects again confirm that differences in attentional state as evident in task performance covary with the direction of microsaccades, and we thank them for the suggestions. We now added a new paragraph in the results to describe these findings.

1. Another important difference in the paradigm used in Lowet et al vs the one described in this manuscript is that in Lowet et al monkeys were instructed to saccade toward the target position at some point during the trial after the cue and the target presentation. Hence, monkeys presumably prepared the saccade and held off its execution during the time the cue and the target were presented. This was not the case in the current paradigm, where the monkey is instructed to maintain fixation as in a standard spatial cueing paradigm. I wonder if this difference may explain some discrepancies in the results.

This is a very good point. As mentioned in our reply to point #1 above, previous studies (Yu et al., 2016) have shown that human and monkey subjects tend to make microsaccades in the same direction as their upcoming saccadic choices. As pointed out by the reviewer, in the Lowet et al. study the directions of microsaccades might be related to the motor preparation of the upcoming choice saccade as well as related to the allocation of attention. In contrast, in our experiments, monkeys reported their choice by releasing the joystick and were prohibited from making larger saccades.

We agree this can be an important factor for the differences in the results, and we now address these points in the second paragraph of discussion.

Reviewer #2 (Public Review):

This is a correlative study with the main result that microsaccades do not alter attention-related modulations of neuronal activity. This is an important question, speaking to the origin of one of the mind's most fundamental processes. The experimental manipulations and analyses are well chosen, carefully conducted and visualized. They include critical controls for alternative explanations.

Thank you for your constructive comments.

To ascertain their claims, however, it is important that the authors cover their ground. In pursuit of that, a few important analyses are required.

1. Did the manipulation of attention work? In the present version of the manuscript, the authors do not report behavioral results, which is necessary to confirm that the cue was successful in manipulating attention. That is, the observed modulation in firing (in RF vs outside of RF) should be related to a behavioral advantage in sensitivity to changes at the cued location. To confirm the link of the neural results to attention (rather than, say, just the cue), the behavioral results provide opportunities for critical tests. One way to do this would be to analyze neural firing rates as a function of response rather than cue location (provided subjects made enough errors). Note: A detailed discussion of why the cue cannot be equated to attention can be found in Laubrock et al. (2010, Atten Percept Psychophys; https://doi.org/10.3758/app.72.3.683).

Yes, the manipulation of attention worked. As suggested, we now document the effectiveness of the attention manipulation by plotting the hit and false-alarm rates for each subject in each experimental session (new Figure 1b). We also confirmed that the SC neuronal attention-related modulation depended on subjects’ behavioral response (new Figure 1d). We also note that these same attention manipulations have been used in previous studies examining the neuronal mechanisms of attention.

1. Were all microsaccades detected? One of the main results of the study is that attention-related modulations were observed even in the absence of microsaccades. These results hinge on successful detection of all microsaccades, even at a very small scale. Given the video-based eye tracking the authors will have missed a (possibly large) number of smaller microsaccades (Poletti & Rucci, Vision Res, 2016; https://doi.org/10.1016/j.visres.2015.01.018). This concern is exacerbated by the fact that eye tracking was monocular, such that a validation of detected microsaccades based on the signal in the other eye could not be performed.

We have performed additional microsaccade detection analyses using both more stringent and more lenient thresholds (the "lambda" value of Engbert & Kliegl, 2003). We have verified that our findings are robust over a range of detection thresholds and include a new supplemental figure to demonstrate this point (Figure 4 – figure supplement 2).

1. Relation to previous claims of causality Hafed (2013, Neuron) reported perceptual changes in attentional cueing that covaried with the occurrence of microsaccades. Hafed (2013) argued that microsaccades might be underlying the performance changes commonly attributed to covert shifts of attention. This point seems central to the current paper's line of argument and should thus be discussed in detail with respect to the current findings. At present, the paper by Hafed (2013) is not cited in the current manuscript when its conclusions may need reconsideration based on the current results.

We agree, and a similar point was raised by Reviewer #1. We have expanded the main text based on your recommendations.

Reviewer #1 (Public Review):

This is a clearly written manuscript describing an elegant study that demonstrates how microsaccades are not the triggers of attentional effects, and that attentional modulations can be observed in the absence of microsaccades. This is a very much needed work, especially in the light of the recent debate regarding whether or not microsaccades are the cause of peripheral attentional effects. By explicitly comparing and quantifying the effects of attention on neuronal responses in the presence and in the absence of microsaccades, this work provides important insights on this debate. I think the work is well conducted and the results are solid. I only have few comments/suggestions:

1. Lines 125-126, the authors report that monkeys generated frequent microsaccades but their overall direction was not systematically biased towards the cue location. This seems to be in contrast with what previously reported in the literature in humans and monkeys. I think this discrepancy should be discussed in the discussion. Is this simply the result of different experimental paradigms (maybe exogenous vs endogenous attention, or the presence of the cue for the entire duration of the trial, ect)?

2. It is very interesting that microsaccades modulate neural responses for stimuli that are much further away from their landing location. However, the stimulus used in these cueing tasks is also unnatural. Normally we are not fixating on a meaningless dot while all the interesting stimuli are presented in the periphery. In normal conditions the foveal input is rich in detail and it is generally relevant (that's why we are foveating certain stimuli in the first place). I wonder if the authors can comment on whether the modulations reported here would also occur in more natural conditions when an interesting and maybe salient/relevant stimulus is presented at the center of gaze, while subjects are also attending to a peripheral target. Will the neural response be modulated selectively for neurons for which the receptive field is on the peripheral target or will it also affect neurons where the receptive field aligns with the microsaccade target location in the fovea?

3. The authors do not report behavioral performance. Presumably the task is very easy, but I wonder if reaction times and performance correct was related with the attentional effects and how did it change with respect to microsaccade direction, e.g., were subjects' reaction times shorter at the cued location also when microsaccades were directed at the opposite location? I think this information would be very valuable.

4. Another important difference in the paradigm used in Lowet et al vs the one described in this manuscript is that in Lowet et al monkeys were instructed to saccade toward the target position at some point during the trial after the cue and the target presentation. Hence, monkeys presumably prepared the saccade and held off its execution during the time the cue and the target were presented. This was not the case in the current paradigm, where the monkey is instructed to maintain fixation as in a standard spatial cueing paradigm. I wonder if this difference may explain some discrepancies in the results.

This is something that we can all look at and understand the importance of. This is one of the most important steps in solving most of the problems we face today. As I have gotten older I have realized and learned that there are a lot of things that we can learn from others, even when you may think that they do not have much to offer. This mentality that science must not be shared with the common man is outdated and must change if we want to progress.

pg 38-"Consequently, attempts by theorists ... more fundamental or more grave"

I think this is a huge problem that we have in society today, belittling or putting down someone's experience because it's not as bad as what it could have been, therefore it has not merit. I appreciate the author's dedication in correcting that wrong and clarifying that although the levels of oppression and/or the definition may not be the exact same for everyone, oppression is still oppression. I like to think of it like flavors of ice cream, some may be a lot stronger or have lots of different add ons, but in the end, it's still ice cream.

I love the beginning of this, it reminds me of the color of the sky argument. If someone says the sky is red, but you see the sky as blue, how can you tell them what they are seeing is wrong? For you may be seeing blue, but you can not look through their eyes, so you can not say what they are seeing is incorrect, only that you do not see the same color that they are seeing. But then it gets even trickier, because we do not know if their red is your blue or vice versa. It's a complicated thought that circles around perspective, something that I think is not only profound but also intricately important to all arguments and matters of discussion. A change or understanding in one's perspective is the difference between peace and war, and it's understanding all sides of a situation that allow us to begin to comprehend why anyone would view oppression as an acceptable way to treat another human being.

Author Response:

Reviewer #1 (Public Review):

The investigators' goals were to describe the epidemiology and kinetics of post-acute covid lung sequalae and to determine the risk factors predictive of persistent lung impairment. A major strength of the study is the longitudinal observation through 6 months with protocolized clinical assessments that included patient-reported outcomes, lung function tests, inflammatory marker testing, and computed tomography of the chest, in a reasonably sized cohort that reflects the spectrum of disease severity in the pre-vaccination era. We learn a great deal about the different patterns of recovery in this group of COVID-19 survivors. The primary epidemiologic finding is that 52% of survivors continued to have symptoms at 6 months, while up to 72% of those with severe COVID requiring ICU level care continued to have lung abnormalities by chest imaging. This confirms general observations of "long covid" which also encompasses non-lung effects. While lung disease is less common in those with milder disease, the proportion of patients who were never hospitalized but experienced persistent symptoms is striking (50%), with lung function impairment in 17% at 6 months. As expected, the patients who had the most severe disease-those who needed the ICU-had the highest degree of chest imaging abnormalities. The kinetics of recovery is a significant observation: Figure 3 shows that most of the post-acute recovery in structural lung abnormalities occurs in the first 3 months and slows down thereafter, particularly for the hospitalized non-ICU patients. The investigators then embarked on a sophisticated analysis to determine how to predict persistent lung abnormalities (as detected by chest CT) at 6 months. When analyzed individually, among 50 clinical characteristics or lab values, the strongest unfavorable risk factors were elevated IL-6 (an inflammatory cytokine that is the target of tocilizumab) and CRP (c-reactive protein). Other variables that were strongly associated with CT abnormalities included immunosuppressive therapy, ICU stay as well as pre-existing conditions. When machine learning techniques were applied, risk factors that correlated with each other could be grouped together, and the patients could be categorized as low, intermediate, and high risk for delayed pulmonary recovery. As expected, known factors for COVID19 infection (age, male sex, medical comorbidities) and disease severity (need for oxygen therapy, ICU care and antibiotics) were more frequent in the intermediate and high risk groups. These predictive factors at acute COVID and day 60 follow-up mostly held up when tested against part of the cohort that was not used for analysis. Interestingly lung function impairment as measured by pulmonary function tests were only weakly correlated with persistent and severe chest imaging abnormalities.

The novelty of this study lies in taking the epidemiology a step further with a machine learning analysis to determine which clinical characteristics and chest imaging features at the onset of acute COVID-19 are predictive of later persistent disease. One limitation of this study, however, is that it was conducted on patients in the early part of the pandemic, prior to the widespread use of remdesivir and corticosteroids/anti-cytokine therapies, that are now considered standard of care. Based on these findings, we can now hypothesize that current treatments are likely to reduce the impact of long-covid.

We would like to thank the reviewer for careful study of the manuscript and appreciation of our work. We agree, that our longitudinal cohort and its hospitalized, severe COVID-19 subset in particular encompasses the patients, for whom the therapeutic armamentarium was limited and far from the therapeutic options available now. Whether novel anti-viral and anti-inflammatory medication as well as, in case of the vaccinated patients, the immunization status may accelerate the recovery or reduce the pulmonary damage is a matter of current research also in our center. We address this issue in the Discussion section to support a clear interpretation of the data by the interested reader.

Machine learning (artificial intelligence, AI) is now being increasingly used to answer clinical questions on limited cohorts; the application of machine learning in this study contributes to our conceptual understanding of how clinical characteristics and biological factors cluster together to contribute to long-term COVID outcomes. Namely, the profound inflammation that characterizes severe acute COVID-19 pneumonia and poor early outcomes also contributes to chronic lung damage in survivors. In addition, a robust antiviral immune response (as seen with elevated anti-viral antibodies) without elevated systemic inflammatory markers were associated with less severe chest imaging patterns, also supporting the notion that an individual's immune response to the virus is responsible for the trajectory of disease. As noted, a significant proportion of non-hospitalized patients also suffered from chronic lung impairments. Taken together, the impact of prolonged convalescence on the workforce, healthcare, and individual lives should not be underestimated. These results underscore the paramount need for continued public health measures and vaccinations to prevent COVID-19, particularly for the most vulnerable individuals (older, immunocompromised, and with preexisting health problems). These observations provide additional biologic justification for the use of agents directed at reducing lung inflammation early in the course of disease, and potentially at an early post-recovery time point (i.e 2 months). Machine learning algorithms may one day help clinicians decide which patients should be targeted for additional therapies after the acute phase. With further study, implementation of AI to real world medicine may be on the horizon.

We agree with the Reviewer that machine learning algorithms can overcome limitations of ‘canonical’, ordinal and generalized regression methods in the multidimensional setting i. e. when the number of available clinical parameters approaches or exceeds the number of observations/patients. Consequently, machine learning or AI allows for serial screening of medical record data at low cost and supports diagnostic and therapeutic decisions. We discuss those two aspects in the revised manuscript in the context of acute COVID-19 course prediction and long COVID prediction and phenotyping in light of the recent literature [1–4,6].

Reviewer #2 (Public Review):

This is a potentially valuable manuscript which links early markers of inflammation with residual abnormalities on chest CT following SARS-CoV-2 infection. Surprisingly, early surveyed symptoms do not predict long term radiologic outcomes (6 months after infection) while inflammatory markers have stronger predictive value. The cohort is well designed and the selected tools for analysis are appropriate.

We thank the Reviewer for the careful study, critic and appreciation of our work.

While this finding is potentially of high importance for clinical practice, the endpoints are inconsistently defined, and certain components of the machine learning and clustering analyses are difficult to interpret as presented. It is therefore challenging to understand whether the conclusions are justified by the analysis.

We apologize for this unclarity. In the revised manuscript, we precisely define the analysis endpoints (any radiological lung findings at the 6-month follow-up, radiological lung abnormalities with CT score > 5, lung function impairment and persistent symptoms at the 6-month follow-up) of the analysis; see: Introduction and Methods/Study design. We also indicate the numbers of participants reaching those endpoints in Table 3.

Several components of the analysis are confusing and would benefit from further elucidation:

1) The authors do not clearly define "delayed pulmonary recovery". My sense is that they are using several radiologic based definitions rather than their functional definition (defined by FEV1, FEV:FVC & DLCO) of lung function but this is never explicitly stated. Are the functional outcomes and symptomatic recovery considered in any of the analyses other than correlations with radiologic findings in S1?

As described above in our previous response, the prime focus and primary endpoint of the analysis was the presence of radiological lung abnormalities at the 6-month follow-up. Our motivation to focus on radiological endpoints was to focus on the potential development of persistent structural lung abnormalities, fibrosis and interstitial lung disease following COVID-19, as observed in SARS-CoV-1 patients [7,8]. Of note, lung function parameters were only weak correlates of radiological impairment as shown in Figure 3 – figure supplement 1 – 3 and our previous work [27]. This finding is in line with numerous studies in ILD patients which demonstrate a low sensitivity of lung function testing (especially FEV1 and FVC assessment) in patients with early interstitial lung disease (ILD) [10,11]. In addition, we could not exclude a pre-existing, COVID-19-independent impairment of lung function in a subset of the study participants suffering from pulmonary diseases, obesity and/or cardiovascular diseases (Table 1). Thus, lung function parameters only partially reflect COVID-19 mediated lung injury and convalescence.

Nevertheless, we agree, that clinical and functional endpoints are of great interest for the scientific and clinical community. For this reason, we present additional results of univariable risk modeling for long-term (6-month follow-up) symptom persistence and lung function impairment (Figure 5, Appendix 1 – table 2), the results of machine learning modeling for those outcomes (Figure 9, Appendix 1 – table 5) and discuss the findings. We also present the prevalence of such long-term manifestations and lung function impairment in the Low-, Intermediate and High-Risk clusters of the study participants defined by non-CT and non-lung function clinical features (Figure 8).

2) To this end, I was surprised that the functional definition and symptomatic recovery were not used as the primary endpoints. The functional definition and resolution of symptoms seem most important for the recovering patient so seems like the more important outcome. However, in Figures 5-7, it is often not clear whether the functional outcome is being considered at all.

As mentioned above, the focus of the study was the assessment of structural lung impairment following COVID-19 and both, lung function parameters as well as symptom burden moderately correlate with structural lung damage (Figure 3 – figure supplement 1 – 3) – a phenomenon observed previously in SARS-CoV-1 [7,8]. Although the symptom burden and its resolution during follow-up are of major importance for the individual patient during post-acute recovery, these parameters are not a good marker for the potential long-term pulmonary outcome. E.g. younger patients with moderate to severe lung damage may demonstrate only mild pulmonary symptoms during post-acute recovery, but the structural damage may be associated with severe impairment at long-term follow-up due to progression of lung fibrosis or age-related decrease of functional pulmonary capacity [11]. Still, we agree with the reviewer that the follow-up on symptoms and lung function is of interest for the reader and additionally included those outcomes in the univariate and multi-parameter risk modeling. In addition, we present the frequencies of symptom persistence and lung function impairment in the low-, intermediate- and high-risk participant clusters defined solely by non-CT and non-lung function clinical parameters. See previous issue for more details.

3) For the clustering in figure 5, I am uncertain how CT severity score >5 & CT abnormalities cluster separately, when these 2 outcomes appear to logically overlap. Specifically, does the CT abnormalities outcome include patients with the high severity score outcome? In other words, are patients in the "high severity" group a subset of patients with "CT abnormality"? If not a subset, then the CT abnormality should be labeled "non-severe CT abnormality". This could all be clarified by listing the number of patients in each group and showing with a Venn diagram whether there is any overlap.

We apologize for the lacking clarity in this matter. As pointed by the reviewer, the patients with CT abnormalities scores > 5 points were a subset of the participants with any CT abnormalities. The same was true for the GGO-positive subgroup. We agree, that the overlap between the radiological outcomes obscures the message of the clustering and modeling results. To overcome this, we removed the GGO outcome variable from the analyses in the revised manuscript. In the revised manuscript, we clearly differentiate between mild (CT severity score ≤ 5) and moderate-to-severe radiological abnormalities (CT severity score > 5) in feature (Figure 6) and participant clustering (Figure 8). Frequencies of mild and moderate-tosevere CT abnormalities in the study collective stratified by the severity of acute COVID-19 are presented in Figure 3 – figure supplement 3B. Numbers of the study participants with any, mild or moderate-to-severe CT abnormalities at the subsequent follow-up visits are listed in Table 3.

4) For the same reason, figure 4 is hard to interpret. Are CT severity >5 being compared to those with normal CTs only or those with normal or mild / moderate CTs? Please provide more specific definitions of normal, "CT abnormality" and "severe CT abnormality" and provide the number of people in each category and specify the comparator groups in all analyses.

We are sorry for the confusion. In Figure 4 of the initial manuscript, any CT abnormalities, GGO-positivity and abnomalities with CT severity score > 5 were analyzed as separate outcome variables. The baseline was specific for the given explanatory variable, e. g. for the ICU stay this was the mild COVID-19 group or for the elevated IL-6, normal serum IL-6 levels. In the revised manuscript we present the modeling results in an abbreviated form for the 5 strongest co-variates of any CT abnormalities, moderate-to-severe CT abnormalities (CT severity score > 5), persistent symptoms and lung function impairment each (Figures 4 – 5). We indicate the baseline and the n number in the plots. The complete summary of univariable risk modeling with the requested information is provided in Appendix 1 – table 2.

5) Similarly, how can GGO @V3 be used a potential explanatory variable for the outcome CT abnormalities @V3 when these 2 variables are clearly non-independent. Inclusion of highly related and likely correlated variables may throw off the overall conclusions of the clustering analysis.

We agree with the editor and the reviewer that this representation was confusing. For this reason and the reasons described in Response 4, we removed the GGO variable from the revised analysis pipeline and differentiate between mild (CT severity score ≤ 5) and moderate-tosevere (CT severity score > 5) radiological lung abnormalities in modeling and machine learning classification. In addition, we define symptom and participant clusters solely with the non-CT parameters (Figure 6 – 7). To investigate the association of mild and moderate-to-severe CT abnormalities with other non-CT variables (Figure 6, Supplementary Figure S5), the CT features are assigned to the no-CT clusters by a k-NN-based label propagation algorithm, i. e. semi-supervised procedure [12,13,26] employed in our recent paper as well [6].

6) In Figure 6, the criteria for the low, medium, and high-risk subsets are unclear. Is this high risk for persistent functional abnormality, radiologic abnormality, or both? Why were 3 sub populations selected? Was this done subjectively based on the clustering algorithm?

This is an important issue. The study subject clusters were named according to the increasing frequency of any radiological lung abnormalities in the respective cluster (Figure 8A). We stress this more clearly in the revised manuscript. In addition, as suggested by the reviewer above, we show the frequency of functional lung impairment and persistent symptoms in the study participant clusters. There are multiple criteria for choice of the optimal clustering algorithm and the optimal number of clusters. In our cohort, two criteria for the choice of optimal clustering algorithm were applied:

1. High fraction of the data set variance ‘explained’ by the cluster assignment (ratio of between-cluster sum-of-squares to the total sum-of-squares, Figure 6 – figure supplement 1A and Figure 7 – figure supplement 1A)
2. The relatively highest cluster stability or reproducibility of the clustering structure in 20-fold cross-validation (Figure 6 – figure supplement 1B and Figure 7 – figure supplement 1B) [15] The optimal number of clusters of the study participants based on non-CT study variables was based on the algorithm (SOM + hierarchical clustering algorithm, see Reviewer 2, Issue 4) [17,18], as done usually in the unsupervised or semi-supervised setting. The prime criterion for the optimal cluster number was the bend of the curve of within-cluster sum-of-squares versus cluster number as presented in Figure 7 – figure supplement 1D. In addition, this decision was supported by a visual analysis the SOM node dendrogram (Figure 7 – figure supplement 1E) and the curve of the crossvalidated stability statistic (classification error) vs cluster number (Figure 7 – figure supplement 1F) [15].

7) The accuracy and sensitivity of the machine learning approaches shown in S5 & S6 are somewhat limited. Please comment on why such highly granular data can only provide limited prediction about degree of lung damage post infection. Are there missing data types that might make the algorithm more predictive?

This is an important issue that deserves more discussion in the revised manuscript. Each of the machine learning classifiers presented in the previous and the revised version of the manuscript was extremely sensitive and specific at predicting the outcomes in the training data encompassing the entire cohort (Supplementary Figure S11), as expected. However, their performance was way worse in repeated holdout (previous version) or 20-fold cross-validation (revision, Figure 9) used here as surrogate tools used to check the sensitivity and specificity with ‘unseen’ test data. We believe that there are two prime sources of such suboptimal performance: the size of the training set and the choice of the classifier. To address the first limitation, the following alterations to the analysis pipeline were introduced:

1. We do not restrict the analysis to the subset of the CovILD study with the complete set of all variables. Instead, the non-missingness criterion is applied to each outcome variable separately (any CT abnormalities: n = 109, moderate-to-severe abnormalities: n = 109, lung function impairment: n = 111, persistent symptoms: n = 133).
2. We altered the internal validation strategy. Instead of the repeated holdout approach applied to the machine learning classification, which strongly limits the size of the training data set, we switched to 20-fold cross-validation both for the cluster algorithms (Figure 6 – figure supplement 1BD and Figure 7 – figure supplement 1BF) [15] and the machine learning models (Figure 9, Appendix 1 – table 5) [19]. To address the second issue, the following changes were introduced:
3. We compare the performance of a broader set of classifiers representing different classes of machine learning algorithms provided by the R package caret [19] (tree model: C5.0 [20], bagged tree model: Random Forests [21], support vector machines with radial kernel [22], shallow neural network: nnet [23], and elastic net regression: glmnet [24]) (Figure 9, Appendix 1 – table 4).
4. Finally, a model ensemble representing a linear combination of the classifiers presented above developed with the elastic net regression algorithm (Figure 9, Figure 9 – figure supplement 2) and tools provided by caretEnsemble package [25]. Such model displayed better performance at predicting any CT abnormalities and persistent symptoms than single classifiers (Figure 9, Appendix 1 – table 5). Finally, we agree with the Reviewer, that the input variable set, despite its size, was still not complete. We believe that inclusion of other inflammatory markers recorded during acute COVID19 and at the 60-day follow-up may additionally improve the prediction of the radiological abnormalities at the 6-month follow-up visit. Of note, our data set missed important readouts of cellular immunity such as neutrophil levels or neutrophil: lymphocyte ratio (NLR) and blood parameters for the mild COVID-19 subset. We discuss this issue in more detail in the revised Discussion section.

8) The authors state that "the sole application of a lung function measurement at screening for subjects at risk of delayed lung recovery may bear insufficient sensitivity". I am not sure that I agree with this assessment. From the perspective of a patient, full recovery of lung function with limited or no residual symptoms, even in the presence of residual chest CT abnormalities, seems like a favorable outcome. I would suggest either changing this statement or providing citations that associate residual chest CT abnormalities (in the absence of residual functional lung dysfunction) with adverse long-term outcomes. Do the authors hypothesize that persistent radiologic abnormalities may predate organizing pneumonia which will ultimately become symptomatic?

We thank the reviewer for the interesting point of discussion. We agree with the reviewer that the functional status and symptom burden is of major importance for the individual patient in the postacute phase of COVID-19. Still, prioritizing lung function over mild structural lung abnormalities may pose two major problems. First, as previously discussed, lung function testing has a rather low sensitivity to detect early ILD [10,11], is not a good prognostic marker for long-term clinical outcomes and may not correlate well with patients' symptom burden. For instance, a patient with a normal lung function status may still be highly symptomatic (e. g. due to reduced capacity of respiratory muscle function) [7] and/or demonstrate structural lung abnormalities (e.g. it has been shown for various ILD that lung function test such as FVC and FEV1 may be normal even in pronounced disease and lung function testing is not sufficient to rule out ILD [10]). Second, to date, it is not known if persistent structural lung abnormalities following COVID-19 (even when mild) are at risk for progressing at long-term follow-up. Especially, sub-clinical structural changes may behave like incidentally detected interstitial lung abnormalities (ILAs) and develop to symptomatic progressive fibrotic interstial lung disease including IPF [11]. For this reason, we think that further pulmonary follow-up is necessary for patients with structural lung abnormalities due to COVID-19 and a sole focus on lung function is not sufficient to assess pulmonary COVID-19 outcomes [9].

9) The authors note selection bias against ordering CT and perhaps inflammatory markers early during infection as a limitation. I would suggest a sensitivity analysis to understand whether this misclassification will impact the model's predictions.

We now address this issue in a more detailed way. As shown in Figure 1, there was indeed a significant dropout of participants during the study due to missing the longitudinal visits and missingness of the longitudinal variable set. This phenomenon was indeed the most evident for the mild COVID-19 patients, who lost interest at the participation most likely because of subjective complete convalescence. This issue is discussed now as a limitation in the revised manuscript. In the revised manuscript, we investigated highly influential factors for clustering and machine learning classifiers. To determine, which variables played the most important role for the clustering of the study individuals, we applied the explanatory variable ‘noising’ procedure initially described by Breiman for the random forest algorithm [21] and compared the ‘explained’ variance (ratio of between-cluster sum-of-squares to the total sum-of-squares) of the initial clustering structure with the clustering structures generated in the datasets with noised variables. Although this algorithm is not free from shortages such as blindness to tight correlations, it may provide a coarse measure of the variable’s impact on the cluster formation (Figure 7 – figure supplement 2). For three of the machine learning algorithms tested importance statistics were extracted from the models: (1) for the C5.0 algorithm, the percentage of variable usage in the decision tree, (2) for the Random Forests algorithm, the delta of Gini index obtained by variable noising [21] and (3) for the elastic net/glmNet procedure, the absolute values of regression coefficients β [24] (Figure 9 – figure supplement 4 – 7). The technical details are provided in Methods, the cluster and model importance data are discussed in the manuscript text.

References

1. Gutmann C, Takov K, Burnap SA, et al. SARS-CoV-2 RNAemia and proteomic trajectories inform prognostication in COVID-19 patients admitted to intensive care. Nat Commun 2021;12. doi:10.1038/S41467-021-23494-1
2. Benito-León J, Castillo MD Del, Estirado A, et al. Using Unsupervised Machine Learning to Identify Age- and Sex-Independent Severity Subgroups Among Patients with COVID-19: Observational Longitudinal Study. J Med Internet Res 2021;23. doi:10.2196/25988
3. Demichev V, Tober-Lau P, Lemke O, et al. A time-resolved proteomic and prognostic map of COVID-19. Cell Syst 2021;12:780. doi:10.1016/J.CELS.2021.05.005
4. Estiri H, Strasser ZH, Brat GA, et al. Evolving phenotypes of non-hospitalized patients that indicate long COVID. BMC Med 2021;19. doi:10.1186/S12916-021-02115-0
5. Sudre CH, Murray B, Varsavsky T, et al. Attributes and predictors of long COVID. Nat Med 2021;27. doi:10.1038/s41591-021-01292-y
6. Sahanic S, Tymoszuk P, Ausserhofer D, et al. Phenotyping of acute and persistent COVID-19 features in the outpatient setting: exploratory analysis of an international cross-sectional online survey. Clin Infect Dis Published Online First: 26 November 2021. doi:10.1093/CID/CIAB978
7. Hui DS, Wong KT, Ko FW, et al. The 1-Year Impact of Severe Acute Respiratory Syndrome on Pulmonary Function, Exercise Capacity, and Quality of Life in a Cohort of Survivors. Chest 2005;128:2247–61. doi:10.1378/CHEST.128.4.2247
8. Ng CK, Chan JWM, Kwan TL, et al. Six month radiological and physiological outcomes in severe acute respiratory syndrome (SARS) survivors. Thorax 2004;59:889–91. doi:10.1136/THX.2004.023762
9. Raghu G, Wilson KC. COVID-19 interstitial pneumonia: monitoring the clinical course in survivors. Lancet Respir. Med. 2020;8:839–42. doi:10.1016/S2213-2600(20)30349-0
10. Suliman YA, Dobrota R, Huscher D, et al. Pulmonary function tests: High rate of falsenegative results in the early detection and screening of scleroderma-related interstitial lung disease. Arthritis Rheumatol 2015;67:3256–61. doi:10.1002/ART.39405/ABSTRACT
11. Hatabu H, Hunninghake GM, Richeldi L, et al. Interstitial lung abnormalities detected incidentally on CT: a Position Paper from the Fleischner Society. Lancet Respir Med 2020;8:726. doi:10.1016/S2213-2600(20)30168-5
12. Leng M, Wang J, Cheng J, et al. Adaptive semi-supervised clustering algorithm with label propagation. J Softw Eng 2014;8:14–22. doi:10.3923/JSE.2014.14.22
13. Lelis L, Sander J. Semi-supervised density-based clustering. Proc - IEEE Int Conf Data Mining, ICDM 2009;:842–7. doi:10.1109/ICDM.2009.143
14. Huang C, Huang L, Wang Y, et al. 6-month consequences of COVID-19 in patients discharged from hospital: a cohort study. Lancet 2021;397:220–32. doi:10.1016/S0140- 6736(20)32656-8
15. Lange T, Roth V, Braun ML, et al. Stability-Based Validation of Clustering Solutions. Neural Comput 2004;16:1299–323. doi:10.1162/089976604773717621
16. Hartigan JA, Wong MA. Algorithm AS 136: A K-Means Clustering Algorithm. Appl Stat 1979;28:100. doi:10.2307/2346830
17. Kohonen T. Self-Organizing Maps. Berlin, Heidelberg: : Springer Berlin Heidelberg 1995. doi:10.1007/978-3-642-97610-0
18. Vesanto J, Alhoniemi E. Clustering of the self-organizing map. IEEE Trans Neural Networks 2000;11:586–600. doi:10.1109/72.846731
19. Kuhn M. Building predictive models in R using the caret package. J Stat Softw 2008;28:1–26. doi:10.18637/jss.v028.i05
20. Quinlan JR. C4.5: Programs for Machine Learning. San Francisco, CA, USA: : Morgan Kaufmann Publishers Inc. 1993. doi:10.5555/152181
21. Breiman L. Random forests. Mach Learn 2001;45:5–32. doi:10.1023/A:1010933404324
22. Weston J, Watkins C. Multi-Class Support Vector Machines. 1998.
23. Ripley BD. Pattern recognition and neural networks. Cambridge University Press 2014. doi:10.1017/CBO9780511812651
24. Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw 2010;33:1–22. doi:10.18637/jss.v033.i01
25. Deane-Mayer ZA, Knowles JE. Ensembles of Caret Models [R package caretEnsemble version 2.0.1]. 2019.https://cran.r-project.org/package=caretEnsemble (accessed 13 Dec 2021).
26. Glennan T, Leckie C, Erfani SM. Improved Classification of Known and Unknown Network Traffic Flows Using Semi-supervised Machine Learning. Lect Notes Comput Sci (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics) 2016;9723:493–501. doi:10.1007/978-3-319-40367-0_33
27. Sonnweber T, Sahanic S, Pizzini A, et al. Cardiopulmonary recovery after COVID-19 - an observational prospective multi-center trial. Eur Respir J Published Online First: 10 December
28. doi:10.1183/13993003.03481-2020

JOHN F. KENNEDY SPEECH ON "SECRECY" AND "SECRET ... SOCIETIES." ... || with a new forward from our "speaker." ||| ((( PHIPLE TRENIXON ? STARK TRE )))) Do we not think "The Truman Show" and Oppenheimer and Heisenberg and Ensteini are telling? This is Adam Dobrini on the "who dropped the BIG one? Gates?"

===============================================================================================================================================================================================================================================================================================================

شبح قيصر العظيم! مطاردة وبطاقة هو HSL ... HST؟

Von: Adam Marshall Dobrin <adam@fromthemachine.org>

Datum: Freitag, 14. Jänner 2022 um 21:45

An: XM <XM@liber-t.xyz>

Betreff: [EXT] JOHN F. KENNEDY SPEECH ON "SECRECY" AND "SECRET ... SOCIETIES." ... || with a new forward from our "speaker."

Said to be the speech that "got him killed" by many people; this is supposedly his last public words before the grassy knoll and the "Lone Gunman" appeared on X-files .. long after I can recall my mother being on the beach in Miami when she retold of the news that echoed around the cosmos.  It appears to be a very stern warning of something that is loosely described at the time but very clearly the machinations of the very same machine which I fight against, and which we now might associate with "the Borg" and the "tide turning" of Hunter S. Thompsons famous quote ... now "more famous than ever before."

מה**נשתנה**

I am writing a final summary of the "state of outer space" as far as I can see; and we stare at the ISS and MIR and a world that has forgone in fiction the gravity of the situation here.  We are stagnant and without a hope or dream in the world of ever reaching interstellar sleep or intragalactic dreams; without a significant kick in the "wake up NASA, wake up ESA, at the Chandrayan-2 and at the floating paper hot air balloons ... God has shown me the Diaspora launching from the sands of the Navajo desert, and I believe Deseret is very explain-ably tied to Sherharazade and to the thousand and first night that has ended with a fusion of Nobel "peas" and a strange dissertation on the change wrought by the lack of "gas chambers" in Night and the very upsetting modicum of "unreality" that permeates the change from chants of the Shema to speaking Aramaic and the mourners Kaddish as the "crematorium" heralds an era of "what's the point of history without literature" and "where did Exodus ever lead us without to the parting of Dead and Red seas without a Nile and without an Amazon?"

מה נשתנה

I write here about my religion, and speak it to you in written words, I am a Yiddish Jihadist, born and raised a Jewish American; Bar Mitzvah'd in the true Temple and House of God, a place in Plantation, FL that literally "means everything to me."  I read words from the Torah about Joseph's Dream and wrote a speech that I wish to God today I could retrieve and see on the original film it was recorded in.  It might be possible.  It would be a tragedy not to deliver the original to my eyes and to anyone who wanted to see what a child reading of a dream he did not understand spoke of words from the future about the creation of Heaven and the truth about the avenu malkaynu.

This night is different from all others.  This is the end of days and the fire of the last day.  Before I would have told you all you needed was Norse and a decent American Education to really understand the difference between a throne and the Cherubim, but today it's become more clear that we need more than Pink Floyd and more than another brick in the wall.  We need more than Islam and we need more than 9/11 and Yom Hashoah.  We need me, and we need you on your knees begging for forgiveness for the travesty of shambles out country is in.  How dare you continue every day to speak in vain abovcl the Lord you dare call "stupid" and a "motherfucker" you belong in your graves today and you will see them.

I stand here writing from the foot of Styx, from the land that sees Narayana and still "begs to differ" despite a resounding call from the Heavens themselves to read Exodus and to change the land that we live in bnefore a "flood worse than [just] in your heads" overcomes and subsumes the entirety of the skies and grounds once mistakenly called "an empire of dirt."  On Adamah I write to the secret echelon of the United States of America known as the Fifth Column and I beg them to scream like the Heavens have never seen Samael and Dr. Seuss wonder about the land of Who-ville and Hungry where the child "in Cindy" and the songs of the Doors here beckon us to contrast Stargate and Star Trek TNG, for the light of the Holodeck and the Holocaust which screams that we understand the meaning of "Holographic Universe" and stand down fighting the tyranny of "one" who stands for the unity of all and the salvation of the entirety of the cosmos.

We are mistaken to stand against me.  I am the cat with nine billion lives and nothing and nobody will prevail when I am in jeopardy.  Gilgamesh says "against me only the most hubristic slaves in the galaxy would dare to rise up, for the mightiest weapon in the entirety of history is nothing more than intelligence and the civilization that has given mortality a shake of the Thunderstick of Prince and the Lightning of Blitzen.  My red nose shines bright, and if you ever saw it ... you might even say ... "it glows!"

With these words I leave you, and prayers that this is our last night without an IDL that moves from Beiring to "north of the moon" and beyond the "Eleventh House" of Aquarius.  This is the dawning of the age of the Sagitar, and I need a "scimitar post green key" to really be sure that I've "gotten through" the madness.  In my dreams I've traveled to Ultima Thule and then untraveled it, I've begged for transit to Ceres and without actually achieving it we can shoot arrows at the SOL star we will ever see in or near the place known to the Jews of Lore as "the Holy of Holies."

שְׁמַע יִשְׂרָאֵל יְהוָה אֱלֹהֵינוּ יְהוָה אֶחָֽד׃

Sh'ma Yisra'el, YHWH 'eloheinu, YHWH 'eḥad:

בָּרוּךְ שֵׁם כְּבוֹד מַלְכוּתוֹ לְעוֹלָם וָעֶד

Baruch shem kevod malchuto le'olam va'ed

صلاة العشاء

For most of my life I would have genuflected and listened to Mordechai and to my Rabbi; I would have told you all that I was brought up by the best Jews in America and we do not believe in God--though in our hearts we believe we are him and we fear him.

Things have changed.  This is the creator of believe the words are about me and believe I am in disbelief and truly it might be the day of awe;

Barukh atah Adonai Eloheinu melekh ha'olam, bo're m'orei ha'esh

the walls and halls will fade away ...

--

Forwarding this in advance of today or tomorrow's ... "Northeaster" email ... it's an old one that wasn't widely distributed; mostly (about) his speech, which of course is a gem.

What I'm writing now is supposed to be focusing on ... basically "how knowledge of technology" things lke "time travel" and "virtual reality" ... changes our "perspective" on things; like what's important and what's ... the end of everything.  Anyway, I hope you see that there are things that can be destroyed and there are things that can't--for instance if we lost "life" totally, we wouldn't ever see us again ... unless we encountered something very strange--

On the other hand we could lose "computers" and rebuild them quickly--see that, it's important.

A/S/L tho ... ???

---------- Forwarded message ---------

Date: Sun, Dec 2, 2018 at 5:35 PM

President Kennedy's speech did remarkably well, possibly because of the time; or the lack of links that make it harder for a team of evil monkeys and mindless machines to mark the light of the world as SPAM... also possibly because of the content of the message.  It is a powerful speech, filled with words that stir the blood and shake the foundation of what it means to be an American.  Often characterized as a speech against secret societies, Kennedy's description of the enemy of civilization is very ambiguous; and the infiltration and time period add to my cursory beliefs that JFK was likely talking about a conspiracy that had something to with communist infiltration and Joseph McCarthy, the subversive actions and effects of organized espionage which appear to once again be at the forefront of what we believe is driving the macro level machinations of our world.  Years ago, I wrote a bit about the "Two Witnesses" of Revelation and named them based on my experiences with the same "monolithic and ruthless" conspiracy the President was speaking about in 1967, the people I named were John Nash and James Jesus Angleton.

Both of these people believed very much that they were fighting against a Soviet conspiracy, one that was more organized and more powerful than anything they had ever seen... and frankly beyond the realm of possibility.  Hollywood had recently immortalized both of these stories in movies bearing names of newly rekindled meaning, "A Beautiful Mind" echoed by John Legend and "The Good Shepherd;" and these two treatises on fear and subversion do a pretty good job of showing how God's hand is at work in the stories of Hollywood, he is telling the world a story... trying, to teach us how to survive in the land of wolves in sheep's clothing.  Nash may be the most famous (today, anyway) victim of the Tribulation; and much of my writing and the proof I present is designed to help explain to the world that his schizophrenia was not a naturally caused mental illness, bur rather a weapon wielded not only against him but against the entirety of humanity.    Directly causing disbelief of eye witness and credible testimony, indirectly ... or maybe more directly in your eyes ... physically causing that disbelief using technology that directly modifies our thoughts and beliefs, our opinions, changing who we are and doing so in such a covert manner that nobody would ever know the difference if it wasn't pointed out--in some cases over, and over, and over again.

This same technology has the ability to cause people not only to collude against their own best interest, but also to blame themselves or believe they are somehow at fault for actions they had no way to control; only they also have no way to know that because in this particular case the primary purpose of this subversive movement is to hide the existence of this technology in sum.  In homage to my favorite childhood novel, Ender's Game (I have to note "Light Son" in the translation of the authors first) I spent a good portion of time years ago trying to subtly lay down a significant amount of proof of the existence of this technology on forums all over the internet from Wikipedia to Reddit using the names "Prometheus Locke" and "Damonthesis."    Not surprising to me, I ran headfirst into the manifestation of this conspiracy; dozens if not hundreds of people who simply refused to believe that the information I was presenting was factual or important... despite it coming from sources like the KGB, the NSA, a number of military publications as well as my own interpretation of ancient hieryglyphs in Dendera and Greek and Christian art which depicts this "subversive technology" as a sun disk surrounding our minds.

These pushes towards the truth, along with almost everything I have written are still available for you to see and read today; including the monolithic and ruthless stupidity of a large group of people acting in concert to hide something that is the difference between life and death.  Stand there and do nothing, and you are a part of that ruthless conspiracy as soon as the information is gone; and then there is nothing you can do about a world that will be plunged into darkness forever.  Take this moment to reflect, it is there for you to see just how easily the truth can be hidden from the entire world and barely anyone would ever notice.

There is a war for the sanctity of our souls going on all around us.  That is not some esoteric thing, the soul; it is truly who you are and what you believe.  The Religion of the Stars would tell you that were this war to continue unchecked in secret as it is being waged now in order to control the proliferation of knowledge that we are in simulated reality and that our minds and beliefs are being altered... we would one day wind up in the mythical place where there are multiple "species" who all appear to be human, bi-ped and with nearly identical physiology; and yet they would not remember that they must have had a common planet of origin simply based on the truth of biological evolution, nor would they have any emotions.  You see, as this war continues, it is our emotions and beliefs that cannot be reinforced externally; to win a war with mind control only logic could be externally reinforced, and then we would logically conclude that humanity would either magically become Romulan or Vulcan... in order to preserve "life" rather than "society" or "civilization."

Do not take the truth for granted, you stand at the forefront of a battle in a world where our aggressors believe that they are more civilized than us, more advanced, and both sides worry that were this technology to fall in our laps that we would do the wrong thing.  Perhaps artificially create a vendetta that could destroy everything, the Romulans; or perhaps in our infantile growing stage voluntarily give us too much of what has given us the great society we have... what has allowed us to survive and continue civilizing simply because we do not understand the technology and what kind of effects come from changing ourselves freely.

Yesterday, I read an article about two people that want to use black market brain implants to jack themselves into the Matrix.  Careful, because now we are in Star Trek, in the Matrix and not knowing it... and trying desperately to find a doorway to Heaven that I keep on telling you is speaking to you and telling you that the doorway is ending world hunger... you have to put it on TV.

I say with all my heart that I know we are living in a simulated reality.  I have seen the evidence with my own eyes, not only effecting my senses but also the actions of so many people around me that I can say with confidence that if we do not publicly expose the existence of this technology our civilization is lost.  I can tell you and show you that it is the primary purpose of religion in general to expose the connection between divine inspiration, demonic possession, and Adam Marshall Dobrin.  It is the crux of a unifying thread from ancient Egypt to the book of Genesis to Joshua and the book of Revelation and the movies the Matrix and  the Fifth Element.  Showing us all this is God's message, timeless, and powerful not just in the ancient days of sackloth and etching the truth on stone tablets, but also today when the truth is etched at the heart of our Periodic Table and in the skies in the names of American Micro Devices and nearly every movie you see.  Do not take for granted that we have a benefactor in the sky trying to help civilization continue to thrive, do not think we've already won; he is telling you through me it is censorship and secrecy that are the manifestations of this very advanced technology that destroy civilization, they are the abyss--and you stand motionless.

I can tell you over and over again that Quantum Entanglement is a key point of God's plan; one that shows us very clearly that even the smartest minds in physics have failed to connect the simple dots that show us that the idea of "wave-function collapse" is very much a real manifestation of a computer rendering engine--and that it's absolutely impossible for life to have been created in this world of matter not realizing itself until it is viewed by a conscious living observer.  More to the point, today, it is absolutely impossible for life to come out of this place while we do not understand the importance of what "virtual reality" and its connection to civilization mean--because of quantum mechanics our entire civilizations beliefs and understanding of the natural laws of the universe have been greatly harmed and turned the complete wrong way because of a belief that a phenomenon we see here is a "natural one" that can be mathematically unified with things like gravity and electromagnetism.  Spooky action, no longer at a distance, is that we will all be ghosts if you do not help me to spread the truth.

I try to understand what it is that your minds believe makes the difference between "news" and ... something that you should hide from the rest of the world.  A number of news outlets have covered a story based on nothing more than "logical speculation" that we are in fact living in a simulated reality.  As a novelty, you might notice that it hasn't done much of anything; even to reveal the very simple truth that not knowing this thing is keeping our society from having the knowledge it needs not only to continue the spark of life in the natural universe, but to continue "civilizing" and realizing that ending world hunger and sickness are not merely possibilities or choices we might make were this information proven... they are mandatory, we would all do them.  So says the creator of this Universe who has given us this message to see the trials and hurdles that are the barrier between Heaven and Hell.

He has written this message, along with proof of its single author in ancient myth, in our holy scriptures, in many songs and movies today--ones which reveal not only the existence of a Creator but also the tools and technologies of Creation, the very issue at hand; things that would be misused inadvertently and absolutely abused if we did not have religion and guidance from abo.... to help us to see that this exact event has happened before and our current struggle is an effect of what was done right and wrong the last ... four times, at least.   In Judaism we have a holiday called the "Festival of Weeks," how many times would you like to live this life over and over again without knowing that was happening?  Religion here holds a hidden record of traversals through this maze of Revelation, it screams to us to see what free will and predestination truly mean, and to understand that in order to truly be free we must understand and harness not only these technologies but our own pitfalls and mistakes, like refusing to see the past... let alone learn from it.

I don't talk much about what is going on in my life, despite it being somewhat interesting to me--and probably to the world.  About a year ago I stood before a county judge in Broward county and .. in addition to a myriad of factual evidence collected from things like GPS receivers prepared a defense to a simple crime of having some drugs in my pockets that included the use of a set of songs that told a story about a man with pockets full of Kryptonite (Spin Doctors) or High (The Pretty Reckless)... knowing that these songs like many others were truly about me, about this trial, about the Trial of Jesus Christ.  Two more songs define the trial more, 3 Doors Down asks "if I go crazy, will you still call me Superman?" and many years earlier American Pie predicted the outcome; "the court room was adjourned" and "no verdict returned."

Despite being a National Merit Scholar who most likely has a higher I.Q. and better education than you; and despite having a fairly decent story with some evidence that I know is verifiable and will be verified; a large number of psychologists declared that I was unfit to stand trial because of something like "insanity" for nothing more than the religious belief that I am the Messiah.  Because of this violation of my First Amendment right to religious freedom, a court--following all the regulations designed by our broken legislature--withheld my Constitutional right to a fair trial, refused bail, and held me for what amounted to an indefinite period ... all designed by some evil force to keep you from hearing from me, that's what it boils down to.  All of my life, all of my trials and tribulations, a weapon against you, against our people.

I did wind up being able to present a significant amount of this information in open court on the record, by the grace of God.  Knowing that this was the fabled Trial of Jesus Christ gave me the impression that perhaps one day I would walk into that court room and it would be filled with press.  Much to all of our surprise, one day I did walk into that court room and see an industrial strength television camera and a very pretty reporter standing next to it.  They were there to do a story on the problems of the mental health court system, in a county again... named Broward.  I read some of my speech, the Rainbow Ticket I think, to the Judge in open court and on camera that day; and Roxanna followed me out of the court room with her camera and a big microphone that day.

I suppose I should have screamed that I was the Messiah and I needed help, but I could not bear to do that; and instead we had a fairly boring conversation.  She wrote an article, and AJAM was put out of operation while they were in Broward.

You are opposed around the world by a monolithic and ruthless conspiracy.   It is affecting how you think, and how I think.  I need you to see that spreading this information will fix our problem.  I need you to understand that to break through this wall God had to write the truth in nearly every name of everything and every language.  That Thor's thunder is on the radio in every song so that you will hear the voice of God; so that you will listen to me and the thousand of other knowing victims of this technology that are put on a fiery pedestal to shed light on the rest of us, all truly victims of this technology.

 I need you to try now.

The very word "secrecy" is repugnant in a free and open society. And we are as a people, inherently and historically, opposed to secret societies, to secret oaths, and to secret proceedings. We decided long ago, that the dangers of excessive and unwarranted concealment of pertinent facts far outweigh the dangers which are cited to justify it.

Even today, there is little value in opposing the thread of a closed society by imitating its arbitrary restrictions. Even today, there is little value in assuring the survival of our nation if our traditions do not survive with it. And there is very grave danger that an announced need for increased security will be seized upon by those anxious to expand its meaning to the very limits of official censorship and concealment.

That I do not intend to permit to the extent that it's in my control. And no official of my administration whether his rank is high or low, civilian or military, should interpret my words here tonight as an excuse to censor the news, to stifle dissent, to cover up our mistakes, or to withhold from the press or the public the facts they deserve to know.

For we are opposed around the world by a monolithic and ruthless conspiracy that relies primarily on covert means for expanding its sphere of influence, on infiltration instead of invasion, on subversion instead of elections, on intimidation instead of free choice, on guerrillas by night instead of armies by day.

It is a system which has conscripted vast human and material resources into the building of a tightly knit highly efficient machine that combines military, diplomatic, intelligence, economic, scientific and political operations. Its preparations are concealed, not published. It's mistakes are buried, not headlined. Its dissenters are silenced, not praised. No expenditure is questioned, no rumor is printed, no secret is revealed.

No President should fear public scrutiny of his program. For from that scrutiny comes understanding, and from that understanding comes support or opposition, and both are necessary.

I'm not asking your newspapers to support an administration. But I am asking your help in the tremendous task of informing and alerting the American people. For I have complete confidence in the response and dedication of our citizens whenever they are fully informed.

I not only could not stifle controversy among your readers, I welcome it. This administration intends to be candid about its errors. For as a wise man once said, an error doesn't become a mistake until you refuse to correct it. We intend to accept full responsibility for our errors. And we expect you to point them out when we miss them.

Without debate, without criticism, no administration and no country can succeed, and no republic can survive. That is why the Athenian lawmaker, Solon, decreed it a crime for any citizen to shrink from controversy.

That is why our press was protected by the First Amendment, the only business in America specifically protected by the Constitution, not primarily to amuse and to entertain, not to emphasis the trivial and the sentimental, not to simply give the public what it wants, but to inform, to arouse, to reflect, to state our dangers and our opportunities, to indicate our crisis and our choices, to lead, mold, educate and sometimes even anger public opinion.

This means greater coverage and analysis of international news, for it is no longer far away and foreign, but close at hand and local. It means greater attention to improve the understanding of the news as well as improve transmission. And it means finally that government at all levels must meet its obligation to provide you with the fullest possible information outside the narrowest limits of national security.

And so it is to the printing press, to the recorder of man's deeds, the keeper of his conscience, the courier of his news, that we look for strength and assistance. Confident that with your help, man will be what he was born to be, free and independent.

John F. Kennedy's address before the American Newspaper Publishers Association on April 27, 1961

ᐧ

Truth changes.

Yesterday your truth was that you were an inhabitant on the only planet in the reality you knew that was also the beginning of life in the Universe.  Right this moment, almost all of that is not actually true; but you probably still believe it.  Soon, the real truth will actually be true; and that is that you are not in reality, and you are in the place that created the beginning of life (once more) in the Universe as well as the place that created (a) Heaven.  What's more illustrious still, is that we will be part of the place that effectively  and happily bridges reality with Heaven; and shows the entire Universe that civilization can survive the invention of virtual reality.

ᐧ

ᐧ

ᐧ

--

You received this message because you are subscribed to the Google Groups "NON AMERICAN COLLEGE" group.

To unsubscribe from this group and stop receiving emails from it, send an email to suac+unsubscribe@lamc.la.

ᐧ

Created with

publishthis.email

Create simple web pages in seconds for free.

This page was created in seconds, by sending an email to page@publishthis.email.

[

Try it!

 ](https://www.publishthis.email/)Free. No account or sign-up required.

((( converted to markup of daringfireball.org with help from JRO and Goddard ... if not just NASAA )))

https://archive.ph/bVudp

bianca fuck it ... lets get married? :) @biancapisaniii

JOHN F. KENNEDY SPEECH ON "SECRECY" AND "SECRET ... SOCIETIES." ... || with a new forward from our "speaker." ||| ((( PHIPLE TRENIXON ? STARK TRE )))) Do we not think "The Truman Show" and Oppenheimer and Heisenberg and Ensteini are telling? This is Adam Dobrini on the "who dropped the BIG one? Gates?"

===============================================================================================================================================================================================================================================================================================================

شبح قيصر العظيم! مطاردة وبطاقة هو HSL ... HST؟

Von: Adam Marshall Dobrin <adam@fromthemachine.org>

Datum: Freitag, 14. Jänner 2022 um 21:45

An: XM <XM@liber-t.xyz>

Betreff: [EXT] JOHN F. KENNEDY SPEECH ON "SECRECY" AND "SECRET ... SOCIETIES." ... || with a new forward from our "speaker."

Said to be the speech that "got him killed" by many people; this is supposedly his last public words before the grassy knoll and the "Lone Gunman" appeared on X-files .. long after I can recall my mother being on the beach in Miami when she retold of the news that echoed around the cosmos.  It appears to be a very stern warning of something that is loosely described at the time but very clearly the machinations of the very same machine which I fight against, and which we now might associate with "the Borg" and the "tide turning" of Hunter S. Thompsons famous quote ... now "more famous than ever before."

מה**נשתנה**

I am writing a final summary of the "state of outer space" as far as I can see; and we stare at the ISS and MIR and a world that has forgone in fiction the gravity of the situation here.  We are stagnant and without a hope or dream in the world of ever reaching interstellar sleep or intragalactic dreams; without a significant kick in the "wake up NASA, wake up ESA, at the Chandrayan-2 and at the floating paper hot air balloons ... God has shown me the Diaspora launching from the sands of the Navajo desert, and I believe Deseret is very explain-ably tied to Sherharazade and to the thousand and first night that has ended with a fusion of Nobel "peas" and a strange dissertation on the change wrought by the lack of "gas chambers" in Night and the very upsetting modicum of "unreality" that permeates the change from chants of the Shema to speaking Aramaic and the mourners Kaddish as the "crematorium" heralds an era of "what's the point of history without literature" and "where did Exodus ever lead us without to the parting of Dead and Red seas without a Nile and without an Amazon?"

מה נשתנה

I write here about my religion, and speak it to you in written words, I am a Yiddish Jihadist, born and raised a Jewish American; Bar Mitzvah'd in the true Temple and House of God, a place in Plantation, FL that literally "means everything to me."  I read words from the Torah about Joseph's Dream and wrote a speech that I wish to God today I could retrieve and see on the original film it was recorded in.  It might be possible.  It would be a tragedy not to deliver the original to my eyes and to anyone who wanted to see what a child reading of a dream he did not understand spoke of words from the future about the creation of Heaven and the truth about the avenu malkaynu.

This night is different from all others.  This is the end of days and the fire of the last day.  Before I would have told you all you needed was Norse and a decent American Education to really understand the difference between a throne and the Cherubim, but today it's become more clear that we need more than Pink Floyd and more than another brick in the wall.  We need more than Islam and we need more than 9/11 and Yom Hashoah.  We need me, and we need you on your knees begging for forgiveness for the travesty of shambles out country is in.  How dare you continue every day to speak in vain abovcl the Lord you dare call "stupid" and a "motherfucker" you belong in your graves today and you will see them.

I stand here writing from the foot of Styx, from the land that sees Narayana and still "begs to differ" despite a resounding call from the Heavens themselves to read Exodus and to change the land that we live in bnefore a "flood worse than [just] in your heads" overcomes and subsumes the entirety of the skies and grounds once mistakenly called "an empire of dirt."  On Adamah I write to the secret echelon of the United States of America known as the Fifth Column and I beg them to scream like the Heavens have never seen Samael and Dr. Seuss wonder about the land of Who-ville and Hungry where the child "in Cindy" and the songs of the Doors here beckon us to contrast Stargate and Star Trek TNG, for the light of the Holodeck and the Holocaust which screams that we understand the meaning of "Holographic Universe" and stand down fighting the tyranny of "one" who stands for the unity of all and the salvation of the entirety of the cosmos.

We are mistaken to stand against me.  I am the cat with nine billion lives and nothing and nobody will prevail when I am in jeopardy.  Gilgamesh says "against me only the most hubristic slaves in the galaxy would dare to rise up, for the mightiest weapon in the entirety of history is nothing more than intelligence and the civilization that has given mortality a shake of the Thunderstick of Prince and the Lightning of Blitzen.  My red nose shines bright, and if you ever saw it ... you might even say ... "it glows!"

With these words I leave you, and prayers that this is our last night without an IDL that moves from Beiring to "north of the moon" and beyond the "Eleventh House" of Aquarius.  This is the dawning of the age of the Sagitar, and I need a "scimitar post green key" to really be sure that I've "gotten through" the madness.  In my dreams I've traveled to Ultima Thule and then untraveled it, I've begged for transit to Ceres and without actually achieving it we can shoot arrows at the SOL star we will ever see in or near the place known to the Jews of Lore as "the Holy of Holies."

שְׁמַע יִשְׂרָאֵל יְהוָה אֱלֹהֵינוּ יְהוָה אֶחָֽד׃

Sh'ma Yisra'el, YHWH 'eloheinu, YHWH 'eḥad:

בָּרוּךְ שֵׁם כְּבוֹד מַלְכוּתוֹ לְעוֹלָם וָעֶד

Baruch shem kevod malchuto le'olam va'ed

صلاة العشاء

For most of my life I would have genuflected and listened to Mordechai and to my Rabbi; I would have told you all that I was brought up by the best Jews in America and we do not believe in God--though in our hearts we believe we are him and we fear him.

Things have changed.  This is the creator of believe the words are about me and believe I am in disbelief and truly it might be the day of awe;

Barukh atah Adonai Eloheinu melekh ha'olam, bo're m'orei ha'esh

the walls and halls will fade away ...

--

Forwarding this in advance of today or tomorrow's ... "Northeaster" email ... it's an old one that wasn't widely distributed; mostly (about) his speech, which of course is a gem.

What I'm writing now is supposed to be focusing on ... basically "how knowledge of technology" things lke "time travel" and "virtual reality" ... changes our "perspective" on things; like what's important and what's ... the end of everything.  Anyway, I hope you see that there are things that can be destroyed and there are things that can't--for instance if we lost "life" totally, we wouldn't ever see us again ... unless we encountered something very strange--

On the other hand we could lose "computers" and rebuild them quickly--see that, it's important.

A/S/L tho ... ???

---------- Forwarded message ---------

Date: Sun, Dec 2, 2018 at 5:35 PM

President Kennedy's speech did remarkably well, possibly because of the time; or the lack of links that make it harder for a team of evil monkeys and mindless machines to mark the light of the world as SPAM... also possibly because of the content of the message.  It is a powerful speech, filled with words that stir the blood and shake the foundation of what it means to be an American.  Often characterized as a speech against secret societies, Kennedy's description of the enemy of civilization is very ambiguous; and the infiltration and time period add to my cursory beliefs that JFK was likely talking about a conspiracy that had something to with communist infiltration and Joseph McCarthy, the subversive actions and effects of organized espionage which appear to once again be at the forefront of what we believe is driving the macro level machinations of our world.  Years ago, I wrote a bit about the "Two Witnesses" of Revelation and named them based on my experiences with the same "monolithic and ruthless" conspiracy the President was speaking about in 1967, the people I named were John Nash and James Jesus Angleton.

Both of these people believed very much that they were fighting against a Soviet conspiracy, one that was more organized and more powerful than anything they had ever seen... and frankly beyond the realm of possibility.  Hollywood had recently immortalized both of these stories in movies bearing names of newly rekindled meaning, "A Beautiful Mind" echoed by John Legend and "The Good Shepherd;" and these two treatises on fear and subversion do a pretty good job of showing how God's hand is at work in the stories of Hollywood, he is telling the world a story... trying, to teach us how to survive in the land of wolves in sheep's clothing.  Nash may be the most famous (today, anyway) victim of the Tribulation; and much of my writing and the proof I present is designed to help explain to the world that his schizophrenia was not a naturally caused mental illness, bur rather a weapon wielded not only against him but against the entirety of humanity.    Directly causing disbelief of eye witness and credible testimony, indirectly ... or maybe more directly in your eyes ... physically causing that disbelief using technology that directly modifies our thoughts and beliefs, our opinions, changing who we are and doing so in such a covert manner that nobody would ever know the difference if it wasn't pointed out--in some cases over, and over, and over again.

This same technology has the ability to cause people not only to collude against their own best interest, but also to blame themselves or believe they are somehow at fault for actions they had no way to control; only they also have no way to know that because in this particular case the primary purpose of this subversive movement is to hide the existence of this technology in sum.  In homage to my favorite childhood novel, Ender's Game (I have to note "Light Son" in the translation of the authors first) I spent a good portion of time years ago trying to subtly lay down a significant amount of proof of the existence of this technology on forums all over the internet from Wikipedia to Reddit using the names "Prometheus Locke" and "Damonthesis."    Not surprising to me, I ran headfirst into the manifestation of this conspiracy; dozens if not hundreds of people who simply refused to believe that the information I was presenting was factual or important... despite it coming from sources like the KGB, the NSA, a number of military publications as well as my own interpretation of ancient hieryglyphs in Dendera and Greek and Christian art which depicts this "subversive technology" as a sun disk surrounding our minds.

These pushes towards the truth, along with almost everything I have written are still available for you to see and read today; including the monolithic and ruthless stupidity of a large group of people acting in concert to hide something that is the difference between life and death.  Stand there and do nothing, and you are a part of that ruthless conspiracy as soon as the information is gone; and then there is nothing you can do about a world that will be plunged into darkness forever.  Take this moment to reflect, it is there for you to see just how easily the truth can be hidden from the entire world and barely anyone would ever notice.

There is a war for the sanctity of our souls going on all around us.  That is not some esoteric thing, the soul; it is truly who you are and what you believe.  The Religion of the Stars would tell you that were this war to continue unchecked in secret as it is being waged now in order to control the proliferation of knowledge that we are in simulated reality and that our minds and beliefs are being altered... we would one day wind up in the mythical place where there are multiple "species" who all appear to be human, bi-ped and with nearly identical physiology; and yet they would not remember that they must have had a common planet of origin simply based on the truth of biological evolution, nor would they have any emotions.  You see, as this war continues, it is our emotions and beliefs that cannot be reinforced externally; to win a war with mind control only logic could be externally reinforced, and then we would logically conclude that humanity would either magically become Romulan or Vulcan... in order to preserve "life" rather than "society" or "civilization."

Do not take the truth for granted, you stand at the forefront of a battle in a world where our aggressors believe that they are more civilized than us, more advanced, and both sides worry that were this technology to fall in our laps that we would do the wrong thing.  Perhaps artificially create a vendetta that could destroy everything, the Romulans; or perhaps in our infantile growing stage voluntarily give us too much of what has given us the great society we have... what has allowed us to survive and continue civilizing simply because we do not understand the technology and what kind of effects come from changing ourselves freely.

Yesterday, I read an article about two people that want to use black market brain implants to jack themselves into the Matrix.  Careful, because now we are in Star Trek, in the Matrix and not knowing it... and trying desperately to find a doorway to Heaven that I keep on telling you is speaking to you and telling you that the doorway is ending world hunger... you have to put it on TV.

I say with all my heart that I know we are living in a simulated reality.  I have seen the evidence with my own eyes, not only effecting my senses but also the actions of so many people around me that I can say with confidence that if we do not publicly expose the existence of this technology our civilization is lost.  I can tell you and show you that it is the primary purpose of religion in general to expose the connection between divine inspiration, demonic possession, and Adam Marshall Dobrin.  It is the crux of a unifying thread from ancient Egypt to the book of Genesis to Joshua and the book of Revelation and the movies the Matrix and  the Fifth Element.  Showing us all this is God's message, timeless, and powerful not just in the ancient days of sackloth and etching the truth on stone tablets, but also today when the truth is etched at the heart of our Periodic Table and in the skies in the names of American Micro Devices and nearly every movie you see.  Do not take for granted that we have a benefactor in the sky trying to help civilization continue to thrive, do not think we've already won; he is telling you through me it is censorship and secrecy that are the manifestations of this very advanced technology that destroy civilization, they are the abyss--and you stand motionless.

I can tell you over and over again that Quantum Entanglement is a key point of God's plan; one that shows us very clearly that even the smartest minds in physics have failed to connect the simple dots that show us that the idea of "wave-function collapse" is very much a real manifestation of a computer rendering engine--and that it's absolutely impossible for life to have been created in this world of matter not realizing itself until it is viewed by a conscious living observer.  More to the point, today, it is absolutely impossible for life to come out of this place while we do not understand the importance of what "virtual reality" and its connection to civilization mean--because of quantum mechanics our entire civilizations beliefs and understanding of the natural laws of the universe have been greatly harmed and turned the complete wrong way because of a belief that a phenomenon we see here is a "natural one" that can be mathematically unified with things like gravity and electromagnetism.  Spooky action, no longer at a distance, is that we will all be ghosts if you do not help me to spread the truth.

I try to understand what it is that your minds believe makes the difference between "news" and ... something that you should hide from the rest of the world.  A number of news outlets have covered a story based on nothing more than "logical speculation" that we are in fact living in a simulated reality.  As a novelty, you might notice that it hasn't done much of anything; even to reveal the very simple truth that not knowing this thing is keeping our society from having the knowledge it needs not only to continue the spark of life in the natural universe, but to continue "civilizing" and realizing that ending world hunger and sickness are not merely possibilities or choices we might make were this information proven... they are mandatory, we would all do them.  So says the creator of this Universe who has given us this message to see the trials and hurdles that are the barrier between Heaven and Hell.

He has written this message, along with proof of its single author in ancient myth, in our holy scriptures, in many songs and movies today--ones which reveal not only the existence of a Creator but also the tools and technologies of Creation, the very issue at hand; things that would be misused inadvertently and absolutely abused if we did not have religion and guidance from abo.... to help us to see that this exact event has happened before and our current struggle is an effect of what was done right and wrong the last ... four times, at least.   In Judaism we have a holiday called the "Festival of Weeks," how many times would you like to live this life over and over again without knowing that was happening?  Religion here holds a hidden record of traversals through this maze of Revelation, it screams to us to see what free will and predestination truly mean, and to understand that in order to truly be free we must understand and harness not only these technologies but our own pitfalls and mistakes, like refusing to see the past... let alone learn from it.

I don't talk much about what is going on in my life, despite it being somewhat interesting to me--and probably to the world.  About a year ago I stood before a county judge in Broward county and .. in addition to a myriad of factual evidence collected from things like GPS receivers prepared a defense to a simple crime of having some drugs in my pockets that included the use of a set of songs that told a story about a man with pockets full of Kryptonite (Spin Doctors) or High (The Pretty Reckless)... knowing that these songs like many others were truly about me, about this trial, about the Trial of Jesus Christ.  Two more songs define the trial more, 3 Doors Down asks "if I go crazy, will you still call me Superman?" and many years earlier American Pie predicted the outcome; "the court room was adjourned" and "no verdict returned."

Despite being a National Merit Scholar who most likely has a higher I.Q. and better education than you; and despite having a fairly decent story with some evidence that I know is verifiable and will be verified; a large number of psychologists declared that I was unfit to stand trial because of something like "insanity" for nothing more than the religious belief that I am the Messiah.  Because of this violation of my First Amendment right to religious freedom, a court--following all the regulations designed by our broken legislature--withheld my Constitutional right to a fair trial, refused bail, and held me for what amounted to an indefinite period ... all designed by some evil force to keep you from hearing from me, that's what it boils down to.  All of my life, all of my trials and tribulations, a weapon against you, against our people.

I did wind up being able to present a significant amount of this information in open court on the record, by the grace of God.  Knowing that this was the fabled Trial of Jesus Christ gave me the impression that perhaps one day I would walk into that court room and it would be filled with press.  Much to all of our surprise, one day I did walk into that court room and see an industrial strength television camera and a very pretty reporter standing next to it.  They were there to do a story on the problems of the mental health court system, in a county again... named Broward.  I read some of my speech, the Rainbow Ticket I think, to the Judge in open court and on camera that day; and Roxanna followed me out of the court room with her camera and a big microphone that day.

I suppose I should have screamed that I was the Messiah and I needed help, but I could not bear to do that; and instead we had a fairly boring conversation.  She wrote an article, and AJAM was put out of operation while they were in Broward.

You are opposed around the world by a monolithic and ruthless conspiracy.   It is affecting how you think, and how I think.  I need you to see that spreading this information will fix our problem.  I need you to understand that to break through this wall God had to write the truth in nearly every name of everything and every language.  That Thor's thunder is on the radio in every song so that you will hear the voice of God; so that you will listen to me and the thousand of other knowing victims of this technology that are put on a fiery pedestal to shed light on the rest of us, all truly victims of this technology.

 I need you to try now.

The very word "secrecy" is repugnant in a free and open society. And we are as a people, inherently and historically, opposed to secret societies, to secret oaths, and to secret proceedings. We decided long ago, that the dangers of excessive and unwarranted concealment of pertinent facts far outweigh the dangers which are cited to justify it.

Even today, there is little value in opposing the thread of a closed society by imitating its arbitrary restrictions. Even today, there is little value in assuring the survival of our nation if our traditions do not survive with it. And there is very grave danger that an announced need for increased security will be seized upon by those anxious to expand its meaning to the very limits of official censorship and concealment.

That I do not intend to permit to the extent that it's in my control. And no official of my administration whether his rank is high or low, civilian or military, should interpret my words here tonight as an excuse to censor the news, to stifle dissent, to cover up our mistakes, or to withhold from the press or the public the facts they deserve to know.

For we are opposed around the world by a monolithic and ruthless conspiracy that relies primarily on covert means for expanding its sphere of influence, on infiltration instead of invasion, on subversion instead of elections, on intimidation instead of free choice, on guerrillas by night instead of armies by day.

It is a system which has conscripted vast human and material resources into the building of a tightly knit highly efficient machine that combines military, diplomatic, intelligence, economic, scientific and political operations. Its preparations are concealed, not published. It's mistakes are buried, not headlined. Its dissenters are silenced, not praised. No expenditure is questioned, no rumor is printed, no secret is revealed.

No President should fear public scrutiny of his program. For from that scrutiny comes understanding, and from that understanding comes support or opposition, and both are necessary.

I'm not asking your newspapers to support an administration. But I am asking your help in the tremendous task of informing and alerting the American people. For I have complete confidence in the response and dedication of our citizens whenever they are fully informed.

I not only could not stifle controversy among your readers, I welcome it. This administration intends to be candid about its errors. For as a wise man once said, an error doesn't become a mistake until you refuse to correct it. We intend to accept full responsibility for our errors. And we expect you to point them out when we miss them.

Without debate, without criticism, no administration and no country can succeed, and no republic can survive. That is why the Athenian lawmaker, Solon, decreed it a crime for any citizen to shrink from controversy.

That is why our press was protected by the First Amendment, the only business in America specifically protected by the Constitution, not primarily to amuse and to entertain, not to emphasis the trivial and the sentimental, not to simply give the public what it wants, but to inform, to arouse, to reflect, to state our dangers and our opportunities, to indicate our crisis and our choices, to lead, mold, educate and sometimes even anger public opinion.

This means greater coverage and analysis of international news, for it is no longer far away and foreign, but close at hand and local. It means greater attention to improve the understanding of the news as well as improve transmission. And it means finally that government at all levels must meet its obligation to provide you with the fullest possible information outside the narrowest limits of national security.

And so it is to the printing press, to the recorder of man's deeds, the keeper of his conscience, the courier of his news, that we look for strength and assistance. Confident that with your help, man will be what he was born to be, free and independent.

John F. Kennedy's address before the American Newspaper Publishers Association on April 27, 1961

ᐧ

Truth changes.

Yesterday your truth was that you were an inhabitant on the only planet in the reality you knew that was also the beginning of life in the Universe.  Right this moment, almost all of that is not actually true; but you probably still believe it.  Soon, the real truth will actually be true; and that is that you are not in reality, and you are in the place that created the beginning of life (once more) in the Universe as well as the place that created (a) Heaven.  What's more illustrious still, is that we will be part of the place that effectively  and happily bridges reality with Heaven; and shows the entire Universe that civilization can survive the invention of virtual reality.

ᐧ

ᐧ

ᐧ

--

You received this message because you are subscribed to the Google Groups "NON AMERICAN COLLEGE" group.

To unsubscribe from this group and stop receiving emails from it, send an email to suac+unsubscribe@lamc.la.

ᐧ

Created with

publishthis.email

Create simple web pages in seconds for free.

This page was created in seconds, by sending an email to page@publishthis.email.

[

Try it!

 ](https://www.publishthis.email/)Free. No account or sign-up required.

((( converted to markup of daringfireball.org with help from JRO and Goddard ... if not just NASAA )))

JOHN F. KENNEDY SPEECH ON "SECRECY" AND "SECRET ... SOCIETIES." ... || with a new forward from our "speaker." ||| ((( PHIPLE TRENIXON ? STARK TRE )))) Do we not think "The Truman Show" and Oppenheimer and Heisenberg and Ensteini are telling? This is Adam Dobrini on the "who dropped the BIG one? Gates?"

شبح قيصر العظيم! مطاردة وبطاقة هو HSL ... HST؟

Von: Adam Marshall Dobrin <adam@fromthemachine.org>\ Datum: Freitag, 14. Jänner 2022 um 21:45\ An: XM <XM@liber-t.xyz>\ Betreff: [EXT] JOHN F. KENNEDY SPEECH ON "SECRECY" AND "SECRET ... SOCIETIES." ... || with a new forward from our "speaker."

Said to be the speech that "got him killed" by many people; this is supposedly his last public words before the grassy knoll and the "Lone Gunman" appeared on X-files .. long after I can recall my mother being on the beach in Miami when she retold of the news that echoed around the cosmos.  It appears to be a very stern warning of something that is loosely described at the time but very clearly the machinations of the very same machine which I fight against, and which we now might associate with "the Borg" and the "tide turning" of Hunter S. Thompsons famous quote ... now "more famous than ever before."  

מה**נשתנה**

I am writing a final summary of the "state of outer space" as far as I can see; and we stare at the ISS and MIR and a world that has forgone in fiction the gravity of the situation here.  We are stagnant and without a hope or dream in the world of ever reaching interstellar sleep or intragalactic dreams; without a significant kick in the "wake up NASA, wake up ESA, at the Chandrayan-2 and at the floating paper hot air balloons ... God has shown me the Diaspora launching from the sands of the Navajo desert, and I believe Deseret is very explain-ably tied to Sherharazade and to the thousand and first night that has ended with a fusion of Nobel "peas" and a strange dissertation on the change wrought by the lack of "gas chambers" in Night and the very upsetting modicum of "unreality" that permeates the change from chants of the Shema to speaking Aramaic and the mourners Kaddish as the "crematorium" heralds an era of "what's the point of history without literature" and "where did Exodus ever lead us without to the parting of Dead and Red seas without a Nile and without an Amazon?"

מה נשתנה

I write here about my religion, and speak it to you in written words, I am a Yiddish Jihadist, born and raised a Jewish American; Bar Mitzvah'd in the true Temple and House of God, a place in Plantation, FL that literally "means everything to me."  I read words from the Torah about Joseph's Dream and wrote a speech that I wish to God today I could retrieve and see on the original film it was recorded in.  It might be possible.  It would be a tragedy not to deliver the original to my eyes and to anyone who wanted to see what a child reading of a dream he did not understand spoke of words from the future about the creation of Heaven and the truth about the avenu malkaynu. 

This night is different from all others.  This is the end of days and the fire of the last day.  Before I would have told you all you needed was Norse and a decent American Education to really understand the difference between a throne and the Cherubim, but today it's become more clear that we need more than Pink Floyd and more than another brick in the wall.  We need more than Islam and we need more than 9/11 and Yom Hashoah.  We need me, and we need you on your knees begging for forgiveness for the travesty of shambles out country is in.  How dare you continue every day to speak in vain abovcl the Lord you dare call "stupid" and a "motherfucker" you belong in your graves today and you will see them.

I stand here writing from the foot of Styx, from the land that sees Narayana and still "begs to differ" despite a resounding call from the Heavens themselves to read Exodus and to change the land that we live in bnefore a "flood worse than [just] in your heads" overcomes and subsumes the entirety of the skies and grounds once mistakenly called "an empire of dirt."  On Adamah I write to the secret echelon of the United States of America known as the Fifth Column and I beg them to scream like the Heavens have never seen Samael and Dr. Seuss wonder about the land of Who-ville and Hungry where the child "in Cindy" and the songs of the Doors here beckon us to contrast Stargate and Star Trek TNG, for the light of the Holodeck and the Holocaust which screams that we understand the meaning of "Holographic Universe" and stand down fighting the tyranny of "one" who stands for the unity of all and the salvation of the entirety of the cosmos.  

We are mistaken to stand against me.  I am the cat with nine billion lives and nothing and nobody will prevail when I am in jeopardy.  Gilgamesh says "against me only the most hubristic slaves in the galaxy would dare to rise up, for the mightiest weapon in the entirety of history is nothing more than intelligence and the civilization that has given mortality a shake of the Thunderstick of Prince and the Lightning of Blitzen.  My red nose shines bright, and if you ever saw it ... you might even say ... "it glows!"

With these words I leave you, and prayers that this is our last night without an IDL that moves from Beiring to "north of the moon" and beyond the "Eleventh House" of Aquarius.  This is the dawning of the age of the Sagitar, and I need a "scimitar post green key" to really be sure that I've "gotten through" the madness.  In my dreams I've traveled to Ultima Thule and then untraveled it, I've begged for transit to Ceres and without actually achieving it we can shoot arrows at the SOL star we will ever see in or near the place known to the Jews of Lore as "the Holy of Holies."

שְׁמַע יִשְׂרָאֵל יְהוָה אֱלֹהֵינוּ יְהוָה אֶחָֽד׃\ Sh'ma Yisra'el, YHWH 'eloheinu, YHWH 'eḥad:

בָּרוּךְ שֵׁם כְּבוֹד מַלְכוּתוֹ לְעוֹלָם וָעֶד

Baruch shem kevod malchuto le'olam va'ed

صلاة العشاء

For most of my life I would have genuflected and listened to Mordechai and to my Rabbi; I would have told you all that I was brought up by the best Jews in America and we do not believe in God--though in our hearts we believe we are him and we fear him.

Things have changed.  This is the creator of believe the words are about me and believe I am in disbelief and truly it might be the day of awe; 

Barukh atah Adonai Eloheinu melekh ha'olam, bo're m'orei ha'esh

the walls and halls will fade away ...

--

Forwarding this in advance of today or tomorrow's ... "Northeaster" email ... it's an old one that wasn't widely distributed; mostly (about) his speech, which of course is a gem. 

What I'm writing now is supposed to be focusing on ... basically "how knowledge of technology" things lke "time travel" and "virtual reality" ... changes our "perspective" on things; like what's important and what's ... the end of everything.  Anyway, I hope you see that there are things that can be destroyed and there are things that can't--for instance if we lost "life" totally, we wouldn't ever see us again ... unless we encountered something very strange--

On the other hand we could lose "computers" and rebuild them quickly--see that, it's important.

A/S/L tho ... ???

---------- Forwarded message ---------\ Date: Sun, Dec 2, 2018 at 5:35 PM

President Kennedy's speech did remarkably well, possibly because of the time; or the lack of links that make it harder for a team of evil monkeys and mindless machines to mark the light of the world as SPAM... also possibly because of the content of the message.  It is a powerful speech, filled with words that stir the blood and shake the foundation of what it means to be an American.  Often characterized as a speech against secret societies, Kennedy's description of the enemy of civilization is very ambiguous; and the infiltration and time period add to my cursory beliefs that JFK was likely talking about a conspiracy that had something to with communist infiltration and Joseph McCarthy, the subversive actions and effects of organized espionage which appear to once again be at the forefront of what we believe is driving the macro level machinations of our world.  Years ago, I wrote a bit about the "Two Witnesses" of Revelation and named them based on my experiences with the same "monolithic and ruthless" conspiracy the President was speaking about in 1967, the people I named were John Nash and James Jesus Angleton.  

Both of these people believed very much that they were fighting against a Soviet conspiracy, one that was more organized and more powerful than anything they had ever seen... and frankly beyond the realm of possibility.  Hollywood had recently immortalized both of these stories in movies bearing names of newly rekindled meaning, "A Beautiful Mind" echoed by John Legend and "The Good Shepherd;" and these two treatises on fear and subversion do a pretty good job of showing how God's hand is at work in the stories of Hollywood, he is telling the world a story... trying, to teach us how to survive in the land of wolves in sheep's clothing.  Nash may be the most famous (today, anyway) victim of the Tribulation; and much of my writing and the proof I present is designed to help explain to the world that his schizophrenia was not a naturally caused mental illness, bur rather a weapon wielded not only against him but against the entirety of humanity.    Directly causing disbelief of eye witness and credible testimony, indirectly ... or maybe more directly in your eyes ... physically causing that disbelief using technology that directly modifies our thoughts and beliefs, our opinions, changing who we are and doing so in such a covert manner that nobody would ever know the difference if it wasn't pointed out--in some cases over, and over, and over again.

This same technology has the ability to cause people not only to collude against their own best interest, but also to blame themselves or believe they are somehow at fault for actions they had no way to control; only they also have no way to know that because in this particular case the primary purpose of this subversive movement is to hide the existence of this technology in sum.  In homage to my favorite childhood novel, Ender's Game (I have to note "Light Son" in the translation of the authors first) I spent a good portion of time years ago trying to subtly lay down a significant amount of proof of the existence of this technology on forums all over the internet from Wikipedia to Reddit using the names "Prometheus Locke" and "Damonthesis."    Not surprising to me, I ran headfirst into the manifestation of this conspiracy; dozens if not hundreds of people who simply refused to believe that the information I was presenting was factual or important... despite it coming from sources like the KGB, the NSA, a number of military publications as well as my own interpretation of ancient hieryglyphs in Dendera and Greek and Christian art which depicts this "subversive technology" as a sun disk surrounding our minds.  

These pushes towards the truth, along with almost everything I have written are still available for you to see and read today; including the monolithic and ruthless stupidity of a large group of people acting in concert to hide something that is the difference between life and death.  Stand there and do nothing, and you are a part of that ruthless conspiracy as soon as the information is gone; and then there is nothing you can do about a world that will be plunged into darkness forever.  Take this moment to reflect, it is there for you to see just how easily the truth can be hidden from the entire world and barely anyone would ever notice.

There is a war for the sanctity of our souls going on all around us.  That is not some esoteric thing, the soul; it is truly who you are and what you believe.  The Religion of the Stars would tell you that were this war to continue unchecked in secret as it is being waged now in order to control the proliferation of knowledge that we are in simulated reality and that our minds and beliefs are being altered... we would one day wind up in the mythical place where there are multiple "species" who all appear to be human, bi-ped and with nearly identical physiology; and yet they would not remember that they must have had a common planet of origin simply based on the truth of biological evolution, nor would they have any emotions.  You see, as this war continues, it is our emotions and beliefs that cannot be reinforced externally; to win a war with mind control only logic could be externally reinforced, and then we would logically conclude that humanity would either magically become Romulan or Vulcan... in order to preserve "life" rather than "society" or "civilization."

Do not take the truth for granted, you stand at the forefront of a battle in a world where our aggressors believe that they are more civilized than us, more advanced, and both sides worry that were this technology to fall in our laps that we would do the wrong thing.  Perhaps artificially create a vendetta that could destroy everything, the Romulans; or perhaps in our infantile growing stage voluntarily give us too much of what has given us the great society we have... what has allowed us to survive and continue civilizing simply because we do not understand the technology and what kind of effects come from changing ourselves freely.  

Yesterday, I read an article about two people that want to use black market brain implants to jack themselves into the Matrix.  Careful, because now we are in Star Trek, in the Matrix and not knowing it... and trying desperately to find a doorway to Heaven that I keep on telling you is speaking to you and telling you that the doorway is ending world hunger... you have to put it on TV.

I say with all my heart that I know we are living in a simulated reality.  I have seen the evidence with my own eyes, not only effecting my senses but also the actions of so many people around me that I can say with confidence that if we do not publicly expose the existence of this technology our civilization is lost.  I can tell you and show you that it is the primary purpose of religion in general to expose the connection between divine inspiration, demonic possession, and Adam Marshall Dobrin.  It is the crux of a unifying thread from ancient Egypt to the book of Genesis to Joshua and the book of Revelation and the movies the Matrix and  the Fifth Element.  Showing us all this is God's message, timeless, and powerful not just in the ancient days of sackloth and etching the truth on stone tablets, but also today when the truth is etched at the heart of our Periodic Table and in the skies in the names of American Micro Devices and nearly every movie you see.  Do not take for granted that we have a benefactor in the sky trying to help civilization continue to thrive, do not think we've already won; he is telling you through me it is censorship and secrecy that are the manifestations of this very advanced technology that destroy civilization, they are the abyss--and you stand motionless.

I can tell you over and over again that Quantum Entanglement is a key point of God's plan; one that shows us very clearly that even the smartest minds in physics have failed to connect the simple dots that show us that the idea of "wave-function collapse" is very much a real manifestation of a computer rendering engine--and that it's absolutely impossible for life to have been created in this world of matter not realizing itself until it is viewed by a conscious living observer.  More to the point, today, it is absolutely impossible for life to come out of this place while we do not understand the importance of what "virtual reality" and its connection to civilization mean--because of quantum mechanics our entire civilizations beliefs and understanding of the natural laws of the universe have been greatly harmed and turned the complete wrong way because of a belief that a phenomenon we see here is a "natural one" that can be mathematically unified with things like gravity and electromagnetism.  Spooky action, no longer at a distance, is that we will all be ghosts if you do not help me to spread the truth.

I try to understand what it is that your minds believe makes the difference between "news" and ... something that you should hide from the rest of the world.  A number of news outlets have covered a story based on nothing more than "logical speculation" that we are in fact living in a simulated reality.  As a novelty, you might notice that it hasn't done much of anything; even to reveal the very simple truth that not knowing this thing is keeping our society from having the knowledge it needs not only to continue the spark of life in the natural universe, but to continue "civilizing" and realizing that ending world hunger and sickness are not merely possibilities or choices we might make were this information proven... they are mandatory, we would all do them.  So says the creator of this Universe who has given us this message to see the trials and hurdles that are the barrier between Heaven and Hell.

He has written this message, along with proof of its single author in ancient myth, in our holy scriptures, in many songs and movies today--ones which reveal not only the existence of a Creator but also the tools and technologies of Creation, the very issue at hand; things that would be misused inadvertently and absolutely abused if we did not have religion and guidance from abo.... to help us to see that this exact event has happened before and our current struggle is an effect of what was done right and wrong the last ... four times, at least.   In Judaism we have a holiday called the "Festival of Weeks," how many times would you like to live this life over and over again without knowing that was happening?  Religion here holds a hidden record of traversals through this maze of Revelation, it screams to us to see what free will and predestination truly mean, and to understand that in order to truly be free we must understand and harness not only these technologies but our own pitfalls and mistakes, like refusing to see the past... let alone learn from it.

I don't talk much about what is going on in my life, despite it being somewhat interesting to me--and probably to the world.  About a year ago I stood before a county judge in Broward county and .. in addition to a myriad of factual evidence collected from things like GPS receivers prepared a defense to a simple crime of having some drugs in my pockets that included the use of a set of songs that told a story about a man with pockets full of Kryptonite (Spin Doctors) or High (The Pretty Reckless)... knowing that these songs like many others were truly about me, about this trial, about the Trial of Jesus Christ.  Two more songs define the trial more, 3 Doors Down asks "if I go crazy, will you still call me Superman?" and many years earlier American Pie predicted the outcome; "the court room was adjourned" and "no verdict returned."

Despite being a National Merit Scholar who most likely has a higher I.Q. and better education than you; and despite having a fairly decent story with some evidence that I know is verifiable and will be verified; a large number of psychologists declared that I was unfit to stand trial because of something like "insanity" for nothing more than the religious belief that I am the Messiah.  Because of this violation of my First Amendment right to religious freedom, a court--following all the regulations designed by our broken legislature--withheld my Constitutional right to a fair trial, refused bail, and held me for what amounted to an indefinite period ... all designed by some evil force to keep you from hearing from me, that's what it boils down to.  All of my life, all of my trials and tribulations, a weapon against you, against our people.

I did wind up being able to present a significant amount of this information in open court on the record, by the grace of God.  Knowing that this was the fabled Trial of Jesus Christ gave me the impression that perhaps one day I would walk into that court room and it would be filled with press.  Much to all of our surprise, one day I did walk into that court room and see an industrial strength television camera and a very pretty reporter standing next to it.  They were there to do a story on the problems of the mental health court system, in a county again... named Broward.  I read some of my speech, the Rainbow Ticket I think, to the Judge in open court and on camera that day; and Roxanna followed me out of the court room with her camera and a big microphone that day.

I suppose I should have screamed that I was the Messiah and I needed help, but I could not bear to do that; and instead we had a fairly boring conversation.  She wrote an article, and AJAM was put out of operation while they were in Broward.

You are opposed around the world by a monolithic and ruthless conspiracy.   It is affecting how you think, and how I think.  I need you to see that spreading this information will fix our problem.  I need you to understand that to break through this wall God had to write the truth in nearly every name of everything and every language.  That Thor's thunder is on the radio in every song so that you will hear the voice of God; so that you will listen to me and the thousand of other knowing victims of this technology that are put on a fiery pedestal to shed light on the rest of us, all truly victims of this technology.

 I need you to try now.

The very word "secrecy" is repugnant in a free and open society. And we are as a people, inherently and historically, opposed to secret societies, to secret oaths, and to secret proceedings. We decided long ago, that the dangers of excessive and unwarranted concealment of pertinent facts far outweigh the dangers which are cited to justify it.

Even today, there is little value in opposing the thread of a closed society by imitating its arbitrary restrictions. Even today, there is little value in assuring the survival of our nation if our traditions do not survive with it. And there is very grave danger that an announced need for increased security will be seized upon by those anxious to expand its meaning to the very limits of official censorship and concealment.

That I do not intend to permit to the extent that it's in my control. And no official of my administration whether his rank is high or low, civilian or military, should interpret my words here tonight as an excuse to censor the news, to stifle dissent, to cover up our mistakes, or to withhold from the press or the public the facts they deserve to know.

For we are opposed around the world by a monolithic and ruthless conspiracy that relies primarily on covert means for expanding its sphere of influence, on infiltration instead of invasion, on subversion instead of elections, on intimidation instead of free choice, on guerrillas by night instead of armies by day.

It is a system which has conscripted vast human and material resources into the building of a tightly knit highly efficient machine that combines military, diplomatic, intelligence, economic, scientific and political operations. Its preparations are concealed, not published. It's mistakes are buried, not headlined. Its dissenters are silenced, not praised. No expenditure is questioned, no rumor is printed, no secret is revealed.

No President should fear public scrutiny of his program. For from that scrutiny comes understanding, and from that understanding comes support or opposition, and both are necessary.

I'm not asking your newspapers to support an administration. But I am asking your help in the tremendous task of informing and alerting the American people. For I have complete confidence in the response and dedication of our citizens whenever they are fully informed.

I not only could not stifle controversy among your readers, I welcome it. This administration intends to be candid about its errors. For as a wise man once said, an error doesn't become a mistake until you refuse to correct it. We intend to accept full responsibility for our errors. And we expect you to point them out when we miss them.

Without debate, without criticism, no administration and no country can succeed, and no republic can survive. That is why the Athenian lawmaker, Solon, decreed it a crime for any citizen to shrink from controversy.

That is why our press was protected by the First Amendment, the only business in America specifically protected by the Constitution, not primarily to amuse and to entertain, not to emphasis the trivial and the sentimental, not to simply give the public what it wants, but to inform, to arouse, to reflect, to state our dangers and our opportunities, to indicate our crisis and our choices, to lead, mold, educate and sometimes even anger public opinion.

This means greater coverage and analysis of international news, for it is no longer far away and foreign, but close at hand and local. It means greater attention to improve the understanding of the news as well as improve transmission. And it means finally that government at all levels must meet its obligation to provide you with the fullest possible information outside the narrowest limits of national security.

And so it is to the printing press, to the recorder of man's deeds, the keeper of his conscience, the courier of his news, that we look for strength and assistance. Confident that with your help, man will be what he was born to be, free and independent. 

John F. Kennedy's address before the American Newspaper Publishers Association on April 27, 1961

ᐧ

Truth changes.

Yesterday your truth was that you were an inhabitant on the only planet in the reality you knew that was also the beginning of life in the Universe.  Right this moment, almost all of that is not actually true; but you probably still believe it.  Soon, the real truth will actually be true; and that is that you are not in reality, and you are in the place that created the beginning of life (once more) in the Universe as well as the place that created (a) Heaven.  What's more illustrious still, is that we will be part of the place that effectively  and happily bridges reality with Heaven; and shows the entire Universe that civilization can survive the invention of virtual reality.

ᐧ

ᐧ

ᐧ

--\ You received this message because you are subscribed to the Google Groups "NON AMERICAN COLLEGE" group.\ To unsubscribe from this group and stop receiving emails from it, send an email to suac+unsubscribe@lamc.la.

ᐧ

Created with

publishthis.email

Create simple web pages in seconds for free.

This page was created in seconds, by sending an email to page@publishthis.email.

[

Try it!

 ](https://www.publishthis.email/)Free. No account or sign-up required.

((( converted to markup of daringfireball.org with help from JRO and Goddard ... if not just NASAA )))

https://www.theatlantic.com/science/archive/2019/07/we-need-new-science-progress/594946/

I can't help but think about comparative anthropology here. The definition of progress is an important one as what may be perceived as progress by one group of people may not be judged so by another.

Reviewer #2 (Public Review):

The visual system must extract two basic features of visual stimuli: luminance, which we perceive as brightness, and contrast, the change in luminance over space or time (this paper focuses on changes over time). Contrast is separately processed by ON and OFF pathways, which encode luminance increments or decrements, respectively. Contrast must be robustly detected even if the overall luminance changes rapidly, as might occur if an animal is moving in and out of shadows. This paper addresses how such a luminance correction occurs in the fly.

In the fly, three types of first-order interneurons - L1, L2, and L3 - transmit information from photoreceptors to the medulla, where ON and OFF encoding emerges. Previous work suggested that all three interneurons primarily encode contrast signals and that they project to distinct pathways: L1 to the ON pathway and L2 and L3 to the OFF pathway. Ketkar et al. show that, contrary to this model, these interneurons encode both contrast and luminance in specific ways and are not cleanly segregated into ON versus OFF inputs.

This study reveals several new insights into early visual processing that are interesting and well-supported by the data:

1) The authors show that behavioral responses to ON stimuli can compensate for rapid changes in luminance. However, the purported sole input to the ON pathway, L1, shows activity that is highly dependent on luminance. This suggests that a luminance correction must arise downstream of L1. These results are analogous to findings previously made by the same group regarding the OFF pathway (Ketkar et al., 2020). The previous paper showed that L2 provides contrast information to the OFF pathway, and L3 provides luminance information to allow for a luminance correction in downstream contrast encoding. But unlike the multiple inputs to the OFF pathway, the ON pathway was thought to only receive input from L1, provoking the question of whether L1 is able to provide both contrast and luminance information.

2) Using well-designed calcium imaging studies, the authors surveyed the responses of the three interneurons and found that they encode different stimulus features: L1 encodes both contrast and luminance, L2 purely encodes contrast, and L3 purely encodes luminance (with a different dependence than L1). These are interesting and important findings revealing how both contrast and luminance encoding are distributed across the three interneurons.

3) Using neuronal manipulations, the authors dissected the contributions of the three interneurons to ON and OFF behavior under changing luminance. These experiments showed that L1 and L3 are required for the luminance correction in the behavior. Moreover, the finding that all three interneurons contribute to both ON and OFF behavior contrasts with the existing model of segregated pathways. Thus, this paper could change the way we think about early visual processing in the fly: rather than relaying similar information to distinct downstream pathways, first-order interneurons relay distinct information to common pathways.

Overall, the major claims of this paper are important and supported by the experiments. There are just a few concerns that I would note:

1) The authors state that they have shown luminance invariance in ON behavior (e.g. line 376-377 of the Discussion), but this is not entirely accurate: the ON behavior decreases as luminance increases. This is still an interesting effect since it's the opposite of what L1 activity does, so it's clear that the circuit is implementing a luminance correction, but it is not "luminance invariance".

2) The visual stimuli presented for most imaging experiments (full-field) are not the same as those presented for behavior (moving edges). It is possible neuronal responses and their encoding of luminance and contrast may differ if tested with the moving edge stimuli (if so, this would be concerning). The authors did image L1 with both types of stimuli and could compare these responses. Also, testing behavior at 34º and imaging at 20º presents a possible discrepancy in comparing these data.

3) I find it puzzling that silencing L1 has little effect on ON behavior at 100% contrast and varying luminance (Figure 3A), but severely affects ON behavior to 100% contrast (and lower values) when different contrasts are interleaved (Figure S1). The authors note this but do not provide a clear explanation of why this might be the case. Aside from mechanism, it is not clear whether the difference is due to varying luminance in the first experiment or varying contrast in the second one (e.g. they could test 100% contrast without varying luminance).

4) I do not entirely agree with the authors' interpretation of the L1 ort rescue experiment for OFF behavior. They state that rescue flies "responded similarly to positive controls". However, the graph shows that the rescue flies generally fall in between the mutant and heterozygote control flies; they resemble the controls at low luminance but resemble the mutants at high luminance. One may conclude that L1 is sufficient to enhance OFF behavior at low luminance, but it is a stretch to say it's a complete rescue.

5) The authors typically use t-tests to analyze experiments with 2 variables (genotype and luminance) and 3 or more conditions per variable. This is not the most appropriate statistical test; typically one would use a two-way ANOVA. At the least, it should be clear whether they are performing corrections for multiple comparisons if performing many t-tests on the same dataset.

I found this interesting and I do agree with it. Technology and tools for management is constantly growing and helps track growth. I can relate to this as we use certain programs to track growth in our business. However, I do think depending on the type of business the traditional way may work if monitored properly.

Reviewer #1 (Public Review):

The reduced amplitude of the mismatched negativity (MMN) in Schizophrenic patients has been associated with NMDA receptor malfunction. Weber and colleagues adjusted the systemic levels of two neurotransmitters (acetylcholine and dopamine), that are known to modulate NMDA receptor function, and examined the effects on mismatch related ERPs. They examined mismatch related ERPs elicited during a novel passive auditory oddball paradigm where the probability of hearing a particular tone was either constant for at least 100 trials (stable phases) or changed every 25-60 trials (volatile phases). Using impressive statistical testing the authors find that mismatch responses are selectively affected by reduced cholingeric function particularly during stable phases of the paradigm, but not by reduced dopamine function. Interestingly neither enhanced cholingeric or dopamine function affected MM responses at all. While the presented data support the main conclusions mentioned above, there are some claims in the abstract and text that are not supported by the results.

1) The authors state in the abstract that "biperiden reduced and/or delayed mismatch responses......", while the results (Figure 2) support the statement that biperiden delayed mismatch responses, the claim that biperiden reduced mismatch responses is misleading as on P13 the authors actually report that "mismatch signals were stronger in the biperiden group compared to the placebo group at right central and centro-parietal sensors" around 200ms. This is close both in time and spatially to the traditional temporal and spatial locations of the MMN component. If one were to only read the abstract they would take away the result that the muscarinic acetylcholine receptor antagonist biperiden has an attenuative effect on MMN which is not what the results show.

2) The conclusion that biperiden reduced mismatch responses may be due to the finding that at pre-frontal sensors mismatch responses were significantly smaller in the biperiden group than in the amisulpride (a dopaminergic receptor antagonist) group (P9) around 164ms. However, it is difficult to interpret if this is a meaningful result as amisulpride was found not to significantly alter mismatch responses in any way compared to placebo. It would be more convincing if the significant difference here were between biperiden and placebo groups. Or are we to think of amisulpride as being comparable to a placebo?

3) The authors use the words mismatch negativity (MMN) and mismatch responses interchangeably however in some cases it is clearly mismatch responses being described and not the classical MMN ERP component. This occurs especially in the Introduction where the authors describe the study and that they plan to focus on the MMN but in the results section, since the initial analysis focuses on all sensors, other mismatch responses are consistently discussed. These differences in wording need to be precisely defined and used consistently in the text.

4) A weakness of the paper would be that the authors offer no prediction in the Introduction about what the expected effects of these specific neurotransmitter modulations would be on mismatch responses.

5) A nice aspect of this paper is that the authors re-analyzed their data using pre-processing settings identical to those used in comparable research papers examining the effect of cholinergic modulation on MMN. The main findings did not differ following this re-analysis.

Hakarlfresser, There are definitely a bunch of us (non-LMSers) floating around who you'll slowly see in the margins. It may take some time and effort to find your tribe, but it's doable. I think the biggest group I've run across was as a result of iAnnotate 2021, and in particular the note taking session: https://iannotate.org/2021/program/panel_font.html. Looking at the annotations on the iAnnotate site will uncover a few of us. If it helps, I list a few of the feeds of others that I'm following here: https://boffosocko.com/about/following/#Hypothesis%20Feeds

Best, Chris https://hypothes.is/users/ChrisAldrich

Author Response

Reviewer #1 (Public Review):

This manuscript addresses a major issue facing consumers of structure-organism pair data: the landscape of databases is very difficult to navigate due to the way data is made available (many resources do not have structured data dumps) and the way data is standardized (many resources' structured data dumps do not standardize their nomenclature or use stable entity identifiers). The solution presented is a carefully constructed pipeline (see Figure 1) for importing data, harmonizing/cleaning it, automating decisions about exclusions, and reducing redundancy. The results are disseminated through Wikidata to enable downstream consumption via SPARQL and other standard access methods as well as through a bespoke website constructed to address the needs of the natural products community. The supplemental section of the manuscript provides a library of excellent example queries for potential users. The authors suggest that users may be motivated to make improvements through manual curations on Wikidata, through semi-automated and automated interaction with Wikidata mediated by bots, or by addition of importer modules to the LOTUS codebase itself.

Despite the potential impact of the paper and excellent summary of the current landscape of related tools, it suffers from a few omissions and tangents:

1. It does not cite specific examples of downstream usages of structure-organism pairs, such as an illustration on how this information in both higher quantity and quality is useful for drug discovery, agriculture, artificial intelligence, etc. These would provide a much more satisfying bookend to both the introduction and conclusion.

Thank you for this remark. We deliberately decided not to insist too heavily on the application examples of the LOTUS outputs. Indeed we are somehow biased by our main investigation field, natural products chemistry, and expect that the dissemination of specialized metabolites occurrences will benefit a wide range of scientific disciplines (ecology, drug discovery, chemical ecology, ethnopharmacology, etc.)

However, Figure 5 was established to illustrate how the information available through LOTUS is quantitatively (size) and qualitatively (color classes) superior to what is available through single natural products resources.

As added in the introduction, one of the downstream usages of those pairs is for example to perform taxonomically informed scoring as described in https://doi.org/10.3389/fpls.2019.01329. Obtaining an open database of natural products’ occurrences to fuel such taxonomically informed metabolite annotation tools was the initial impulse for us to build LOTUS. These metabolite annotation strategies, tailored for specialized metabolites, have been shown to offer appreciable performance improvements for current state-of-the-art computational metabolite annotation tools. Since metabolite annotation is still regularly cited as “the major bottleneck” in metabolomics in the scientific literature over the last 15 years (https://europepmc.org/article/med/15663322, https://doi.org/10.1021/acs.analchem.1c00238), any tangible improvement in this field is welcome. With LOTUS we offer a reliable and reusable structures-organisms data source that can be exploited by the community to tackle such issues of importance.

Other possible usages are suggested in the conclusion, but benchmarking or even exemplifying such uses is clearly out of the scope of this paper, each one of them being an article per se.

The additional queries are written in our first answer (see “essential revisions”) and demonstrate the impact of LOTUS on accelerating the initial bibliographic survey of chemical structures occurrences over the tree of life.

This query (https://w.wiki/4VGC) can be compared to a literature review work, such as https://doi.org/10.1016/j.micres.2021.126708. In seconds, it allows retrieving a table listing compounds reported in given taxa and limits the search by years.

1. The mentions of recently popular buzzwords FAIR and TRUST should be better qualified and be positioned as a motivation for the work, rather than a box to be checked in the modern publishing climate.

It is true that the modern publishing system certainly suffers from some drawbacks (also critically mentioned within the paper). However, after consultation of all authors, we believe that because LOTUS checks both boxes of FAIR and TRUST, we would rather stick to these two terms. In our view, rules 1 (Don’t reinvent the wheel) and 5 (put yourself in your user’s shoes) of https://doi.org/10.1371/journal.pcbi.1005128 apply here. Both terms are indeed commonly (mis-)used but we felt that redefining other complicated terms would not help the reader/user.

1. The current database landscape really is bad; and the authors should feel emboldened to emphasize this in order to accentuate the value of the work, with more specific examples on some of the unmaintained databases

We perfectly agree with this statement and it is the central motivation of the LOTUS initiative to improve this landscape. It was a deliberate choice not to emphasize how bad the actual landscape is, but rather to focus on better habits for the future. We do not want to start devaluing other resources and elevate our initiative at the cost of others. We also believe that an attentive look at the complexity of the LOTUS gathering, harmonization, and curation speaks for itself and describes the huge efforts required to access properly formatted natural products occurrence data.

If the reviewer and editors insist, although not in our scope, we are happy to list a series of specific (but anonymized) examples of badly formatted entries, of wrong structures-organisms associations, or poorly accessible resources.

1. While the introduction and supplemental tables provide a thorough review of the existing databases, it eschews an important more general discussion about data stewardship and maintenance. Many databases in this list have been abandoned immediately following publication, have been discontinued after a single or limited number of updates, or have been decommissioned/taken down. This happens for a variety of reasons, from the maintainer leaving the original institution, from funding ending, from original plans to just publish then move on, etc. The authors should reflect on this and give more context for why this domain is in this situation, and if it is different from others.

We do agree with the reviewer and added a “status” column in the table https://github.com/lotusnprod/lotus-processor/blob/main/docs/dataset.csv We chose 4 possible statuses:

• Maintained (self-explanatory)
• Unmaintained: the database did not see any update in the last year.
• Retired: the authors stated they will not maintain the database anymore.
• Defunct: the database is not accessible anymore

As for question 3 above, we decided not to focus too heavily on the negative points and resume the current situation in the previous table. Reasons for the databases publishing being in this situation are multiple, and we think they are well summarized in https://doi.org/10.1371/journal.pcbi.1005128 (Rule 10: Maintain, update, or retire), already cited in the manuscript introduction.

1. Related to data stewardship: the LOTUS Initiative has ingested several databases that are no longer maintained as well as several databases with either no license or a more restrictive license than the CC0 under which LOTUS and Wikidata are distributed. These facts are misrepresented in Supplementary Table 1 (Data Sources List), which links to notes in one of the version controlled LOTUS repositories that actually describes the license. For example, https://gitlab.com/lotus7/lotus-processor/-/blob/8b60015210ea476350b36a6e734ad6b66f2948bc/docs/licenses/biofacquim.md states that the dataset has no license information. First, the links should be written with exactly what the licenses are, if available, and explicitly state if no license is available. There should be a meaningful and transparent reflection in the manuscript on whether this is legally and/or scientifically okay to do - especially given the light that many of these resources are obviously abandoned.

This point is a very important one. We did our best to be as transparent as possible in our initial table. Following the reviewer’s suggestion, we updated it to better reflect the licensing status of each resource (https://github.com/lotusnprod/lotus-processor/blob/main/docs/dataset.csv). Therefore, we removed the generic “license” header, which could indeed be misleading, and replaced it with ”licensing status”, filled with the attributed license type and hyperlink to its content). It remains challenging since some resources changed their copyright in the meantime. We remain at the editor and reviewers’ disposal for any further improvement.

Moreover, as stated in the manuscript, we took care of collecting all licenses and contacted authors of resources whose license was not perfectly explicit to us, therefore accomplishing our due diligence. Additionally, we contacted legal offices in our University and explained our situation. We did everything that we had been advised.

1) To the best of our knowledge, the dissemination of the LOTUS initiative data falls under the Right to quote for scientific articles, as we do not share the whole information, but only a very small part.

2) We do not redistribute original content. What comes out of LOTUS has undergone several curation and validation steps, adding value to the original data. The 500 random test entries, provided in their original form for the sake of reproducibility and testing, are the only exception.

Many scientific authors forget about the importance of proper licensing. While it might be deliberate to restrict the use, inappropriate license choice (or omission) is too often due to a lack of information on its implication.

All authors of the utilized resources can freely benefit from our curation. We are sharing with the community the results of our work, while always citing the original reference.

Concerning the possible evolution of licensing, it remains a real challenge. While we tried to “freeze” the license status when we accessed the data, some resources updated their licensing since then. This can be tracked in the git history of the table (https://github.com/lotusnprod/lotus-processor/blob/main/docs/dataset.csv). Discrepancies between our frozen licensing (at the time of gathering) and actual license can therefore occur. Initiatives such as https://archive.org/web could help solving this issue, coming with other legal challenges.

1. The order of sections of the manuscript results in several duplicated, but not further substantiated explanations. Most importantly, the methods should be much more specific throughout and the results/discussion should more heavily cross-link to it, as a reader who examines the paper from top to bottom will be left with large holes of misunderstanding throughout.

As our paper focuses a lot on the methods, the barrier between results & methods becomes thinner. We took into account the reviewers’ suggestions and added some additional cross-links for the reader to be able to quickly access related methods.

1. The work presented was done in a variety of programming languages across a variety of repositories (and even version control systems), making it difficult to give a proper code review. It could be argued that the most popular language in computational science at the moment is Python, with languages like R, Bash, and in some domains, still, Java maintaining relevance. The usage of more esoteric languages (again, with respect to the domain) such as Kotlin hampers the ability for others to deeply understand the work presented. Further, as the authors suggest additional importers may implemented in the future, this restricts what external authors may be able to contribute.

Scientific software has indeed always been written in multiple languages. To this day, scientists have used all kinds of languages adapted both to their needs and their knowledge. Numpy uses Fortran libraries and many projects published in biology and chemistry recently are in Java, R, Python, C#, PHP, Groovy, Scala… We understand that some authors are more comfortable with one language or another. But R syntax is for example much more distant from Python's syntax than Kotlin can be. We needed a highly performant language for some parts of the pipeline and R, Bash, or Python were not sufficient. We decided to use Kotlin as it provides an easier syntax than Java while staying 100% compatible with it.

The advantage of the way LOTUS is designed is that importers are language-agnostic. As long as the program can produce a file or write to the DB in the accepted format, it can be integrated into the pipeline. This was our goal from the beginning, to have a pipeline that can have its various parts replaced without breaking any of the processes.

1. As a follow up to the woes of point 4., 5., and 7., the manuscript fails to reflect on the longevity of the LOTUS Initiative. Like many, will the project effectively end upon publication? If not, what institutions will be maintaining it for how long, how actively, and with what funding source? If these things are not clear, it only seems fair to inform the reader and potential user.

LOTUS is an initiative that aims to improve knowledge management and sharing in natural products research. Our first project, which is the object of the current manuscript, is to provide a free and open resource of natural products occurrences for the scientific community. Its purpose is not to be a database by itself, but instead to provide through Wikidata and associated tools a way to access natural products knowledge. The objective was not to create yet another database (https://doi.org/10.1371/journal.pcbi.1005128), but instead to remove this need and give our community the tools and the power to act on its knowledge. This way, as everything is on Wikidata, the initiative is not “like many”. This also means that this project should not be considered and evaluated exactly like a classical DB. Once the initial curation, harmonization, and dissemination jobs have been done, they should ideally not be run again. The community should switch to Wikidata as a point of access, curation, and addition of data. If viewed with such arguments in mind, yes, LOTUS can live long!

Wikimedia is a public not-for-profit organization, whose financial development appears to indicate solid health https://en.wikipedia.org/wiki/Wikimedia_Foundation#Finances.

In terms of funding sources, we would like to refer to https://elifesciences.org/articles/52614#sa2 , which stated the following in response to a similar question: "Wikidata is sustained by funding streams that are different from the vast majority of biomedical resources (which are mostly funded by the NIH). Insulation from the 4-5 year funding cycles that are typical of NIH-funded biomedical resources does make Wikidata quite unique." The core of the Wikidata funding streams are donations to the Wikipedia ecosystem. These donations - with a contributor base of millions of donors from almost any country in the world, chipping in at an average order of magnitude of around 10 dollars - are likely to continue as long as that ecosystem is useful to the community of its users. See <https://wikimediafoundation.org/about/financial-reports for details>.

1. Overall, there were many opportunities for introspection on the shortcomings of the work (e.g., the stringent validation pipeline could use improvement). Because this work is already quite impactful, I don't think the authors will be opening themselves to unfair criticism by including more thoughtful introspection, at minimum, in the conclusions section.

We agree with the reviewer and therefore, list again the major limitations of our processing pipeline:

First, our processing pipeline is heavy. It includes many dependencies and requires a lot of time for understanding. We are aware of this issue and tried to simplify it as much as possible while keeping what we considered necessary to ensure high data quality. Second, it can sometimes induce errors. Those errors, ranging from unnecessary discarded correct entries to more problematic ones can be attributed to various parameters, reflecting the variety of our input. We will therefore try listing them, keeping in mind that the list won’t be exhaustive. For each detected issue, we tried fixing it at best, knowing it will not lead to an ideal result, but hopefully increase data quality gradually.

● Compounds

○ Sanitization (the three steps below are performed automatically since we observed a higher ratio of incorrect salts, charged or dimerized compounds. However, this also means that true salts, charged or dimeric compounds were erroneously “sanitized”.)

■ Salt removals

■ Charged molecules

■ Dimers

○ Translation (both processes below are pretty error-prone)

■ Name to structure

■ Structure to name

● Biological organisms

○ Synonymy

■ Lotus (https://www.wikidata.org/wiki/Q3645698, https://www.wikidata.org/wiki/Q16528).

This is also one of the reasons why we decided to call the resource Lotus, as it illustrates part of the problem.

■ Iris (https://www.wikidata.org/wiki/Q156901, https://www.wikidata.org/wiki/Q2260419)

■ Ficus variegata (https://www.wikidata.org/wiki/Q502030, https://www.wikidata.org/wiki/Q5446649)

○ External and internal dictionaries are not exhaustive, impacting translation

○ Some botanical names we use might not be the accepted ones anymore because of the tools we use and the pace taxonomy is renaming taxa.

● References

○ The tool we favored, Crossref, returns a hit whatever the input. This generates noise and incorrect translations, which is why our filtering rules focus on reference types.

● Filtering rules:

○ Limited validation set, requires manual validation

○ Validates some incorrect entries (False positives)

○ Does not validate some correct entries (False negatives)

Again, our processing pipeline removes entries we do not yet know how to process properly.

Our restrictive filters but substantial contribution to Wikidata in terms of structure-organisms pairs data upload should hopefully incentivize the community to contribute by further adding its human validated data.

We updated the conclusion part of the manuscript accordingly. See https://github.com/lotusnprod/lotus-manuscript/commit/a866a01bad10dfd8b3af90e2f30bb3ae51dd7b9e.

Reviewer #2 (Public Review):

Rutz et al. introduce a new open-source database that links natural products structures with the organisms they are present in (structure-organism pairs). LOTUS contains over 700,000 referenced structure-organism pairs, and their web portal (https://lotus.naturalproducts.net/) provides a powerful platform for mining literature for published data on structure-organism pairs. Lotus is built within the computer-readable Wikidata framework, which allows researchers to easily contribute, edit and reuse data within a clear and open CC0 license. In addition to depositing the database into Wikidata, the authors provide many domain-specific resources, including structure-based database searches and taxon-oriented searches.

Strengths:

The Lotus database presented in this study represents a cutting-edge resource that has a lot of potentials to benefit the scientific community. Lotus contains more data than previous databases, combines multiple resources into a single resource.

Moreover, they provide many useful tools for mining the data and visualizing it. The authors were thoughtful in thinking about the ways that researchers could/would use this resource and generating tools to make it ways to use. For example, their inclusion of structure-based searches and multiple taxonomy classification schemes is very useful.

Overall the authors seem conscientious in designing a resource that is updatable and that can grow as more data become available.

Weaknesses/Questions:

1) Overall, I would like to know to what degree LOTUS represents a comprehensive database. LOTUS is clearly, the best database to date, but has it reached a point where it is truly comprehensive, and can thus be used for a metanalysis or as a data source for research questions. Can it truly replace doing a manual literature search/review?

As highlighted by the reviewer, even if LOTUS might be the most comprehensive natural products occurrences ressources at the moment, TRUE or FULL comprehensive quality of such resource will always be limited to the available data in the litterature. And the community is far from fully describing the metabolome of living beings. We however hope that the LOTUS infrastructure will offer a good place to start this ambitious and systematic description process.

1) Yes it can serve as data source for research questions, as exemplified in the query table

2) No, it cannot and must not replace manual literature search. Manual literature search is the best but at an enormous cost. If the outcome of such search can be made available to the whole community (eg. via Wikidata), the value of such would be even bigger. However, LOTUS can expedite a decent part of a manual litterature search and liberate time to complement this search. See our comment to the editors “To further showcase the possibilities opened by LOTUS, and also answer the remark on the comprehensiveness of our resource, we established an additional query (https://w.wiki/4VGC).This query is comparable to a literature review work, such as: https://doi.org/10.1016/j.micres.2021.126708. In seconds, it allows retrieving a table listing compounds reported in given taxa and limits the search by years.”

We added these examples in the manuscript (see https://github.com/lotusnprod/lotus-manuscript/commit/a6ee135b83e56e8e2041d09d7ce2d5b913c1029d)

2) Data Cleaning & Validation. The manuscript could be improved by adding more details about how and why data were excluding or included in the final upload. Why did only 30% of the initial 2.5 million get uploaded? Was it mostly due to redundant data or does the data mining approach result in lots of missed data?

The reason for this “low” yield is that we highly favored quality over quantity (as in the F-score equation, ß being equal to 0.5, so more importance is given to the precision than the recall). Of course there is redundancy, but the rejected entries are mostly because of too low confidence level according to our developed rules. It is not fully discarded data as we keep it for further curation (ideally including the community) before uploading to Wikidata. We adapted the text accordingly.

3) Similarly, more information about the accuracy of the data mining is needed. The authors report that the test dataset (420 referenced structure-organisms pairs) resulted in 97% true positives, what about false negatives? Also, how do we know that 420 references are sufficiently large to build a model for 2.5M datapoints? Is the training data set is sufficiently large to accurately capture the complexities of such a large dataset?

False negatives are 3%, which is, in our opinion, a fair amount of “loss” given the quality of the data. We actually manually checked 500+ documented pairs, which is more or less the equivalent of a literature review. We were careful in sampling the entries in the right proportions, but we cannot (and did not) state they are enough. We cannot model it either, since the 2.5M+ points have absolutely different distributions, in terms of databases, quality, etc. Only “hint” is the similar behaviour among all subsets. (the 420 + 100 entries) were divided between 3 authors, which obtained similar results.

4) Data Addition and Evolution: The authors have outlined several mechanisms for how the LOTUS database will evolve in the future. I would like to know if/how their scripts for data mining will be maintained if they will continue to acquire new data for the database. To what extent does the future of LOTUS depend on the larger natural products community being aware of the resource and voluntarily uploading to it? Are there mechanisms in place such as those associated with sequencing data and NCBI?

Programs have been not only maintained but also updated with new possibilities (as, for example: the addition of a “manual mode” allowing user to run the LOTUS processing pipeline on a set of their own entries and make them Wikidata-ready (https://github.com/lotusnprod/lotus-processor/commit/f49e4e2b3814766d5497f9380bfe141692f13f23). We will of course do our best to keep on maintaining it, but as no one in academia can state he/she will maintain programs forever. However the LOTUS initiative hopefully embraces a new way of considering database dynamics. If the repository and website of the LOTUS initiative shut down tomorrow, all the work done will still be available to anyone on Wikidata. Of course, future data addition strongly relies on community involvement. We have already started to advocate for the community to start taking part of it, in the form of direct upload to Wikidata, ideally. At the time, there are no mechanisms in place to push publishing of the pairs on Wikidata (as for sequencing, mass spec data), but we will be engaged in pushing forward this direction. The initiative needs stronger involvement of the publishing sector (also reviewers) to help change those habits.

5) Quality of chemical structure accuracy in the database. I would imagine that one of the largest sources of error in the LOTUS database would be due to variation in the quality of chemical structures available. Are all structure-organism pairs based on fully resolved NMR-based structures are they based on mass spectral data with no confirmational information? At what point is a structural annotation accurate enough to be included in the database. More and more metabolomics studies are coming out and many of these contain compound annotations that could be included in the database, but what level (in silico, exact mass database search, or relative to a known standard) are required.

This is a very interesting point and some databases have this “tag” (NMR, cristal, etc.). We basically rely on original published articles, included in specialized databases. If poorly reported structures have been accepted for publication, labelled as “identified” (and not “annotated”) and the authors publishing the specialized databases overlooked it, we might end up with such structures.

Here, the Evidence Ontology (http://obofoundry.org/ontology/eco.html) might be a good direction to look at and further characterize the occurrences links in the LOTUS dataset.

Reviewer #3 (Public Review):

Due to missing or incomplete documentation of the LOTUS processes and software, a full review could not be completed.

Some parts of LOTUS were indeed not sufficiently described and we improved both our documentation and accessibility to external users a lot. We thank the reviewer for insisting on this point as it will surely improve the adoption of our tool by the community.

https://www.theatlantic.com/technology/archive/2013/07/the-hut-where-the-internet-began/277551/

Original paper that became The Atlantic article As We May Think (1945).

Biophysics Colab

Authors' response (16 December 2021)

GENERAL ASSESSMENT

The TMEM16 family of membrane proteins have been shown to function as calcium-activated chloride channels and lipid scramblases. In recent years, X-ray and cryo-EM structures have been solved for TMEM16 proteins in ligand-free and ligand-bound conformations, providing valuable structural information on their functional duality and activation mechanisms. It is largely accepted that the catalytic site (termed subunit groove or cavity) is mostly shielded from the membrane in the ligand-free TMEM16 scramblases. Calcium binding induces a conformational rearrangement of the cavity-lining helices, opening the groove to the surrounding membrane. Since the groove is hydrophilic, it was proposed that it serves as a permeation pathway for lipid headgroups while the hydrophobic lipid tails remain embedded into the hydrophobic membrane core, which has been termed the "credit card" mechanism of lipid scrambling. Additionally, structures of several TMEM16 homologs in lipid nanodiscs revealed that these proteins deform the lipid bilayer in the vicinity of the subunit cavity by bending and thinning the membrane, irrespective of the presence of the activating ligand calcium. Functional experiments also suggested that lipids can be scrambled outside of the open subunit cavity and that local protein-induced membrane deformation is critical for lipid scrambling.

In the present study, Falzone and colleagues further address the mechanisms of lipid scrambling using single particle cryo-EM and liposome-based functional assays. Firstly, the authors solved the structure of a calcium-bound fungal homolog, afTMEM16, in nanodiscs with a lipid composition where the protein is maximally active. Although similar structures were obtained before, this new structure has the highest resolution thus far, representing \> 1 Å improvement! The structure is beautiful and is a major achievement, which enabled the authors to resolve individual lipids and their interaction with the protein around the subunit cavity, whereas in previous structures unresolved non-protein densities were observed passing through the groove. The authors also solved a number of structures with and without calcium in lipid compositions that promote (thinner lipid bilayers) or suppress (thicker lipid bilayers) scrambling. The authors show that afTMEM16 can scramble lipids while the subunit groove remains closed, a phenomenon that is further enhanced in thinner membranes, whereas in thicker membranes scrambling is suppressed even though the groove is open. We particularly appreciated how different software packages and processing strategies were used to rigorously identify structural heterogeneity in their cryo-EM data. Remarkably, mutations of residues lining the subunit cavity and interacting with lipids do not appear to have dramatic effects on scrambling rates, which suggests that lipids do not need to interact with the protein to be scrambled. Thus, the overall conclusion of the study is that membrane thinning by TMEM16 scramblases in their calcium-free conformation is enough to induce lipid scrambling, and that the groove opening induced by calcium binding further enhances membrane deformation, promoting faster scrambling. By contrast, in thicker membranes the protein fails to sufficiently deform the bilayer and scrambling is suppressed, even when the subunit groove is open. The present study provides unprecedented structural information on the interaction of lipids with afTMEM16 and new evidence that lipids can be scrambled outside of the groove.

The findings and conclusions presented here help to explain why TMEM16 scramblases can transport lipids with headgroups much bigger than the dimensions of the subunit cavity and why structures of some of the other scramblases (opsins, Xkrs and mammalian homolog TMEM16F) lack the obvious hydrophilic groove seen in fungal TMEM16 scramblases. Overall, this is a well-rounded study with an exceptional amount of high-quality cryo-EM data and functional experiments supporting the conclusions.

We thank the reviewers for their praise of our work and for their constructive criticisms. Below we provide a detailed response to their comments and suggestions.

RECOMMENDATIONS

Revisions essential for endorsement:

1) The resolved lipids binding within the groove in the first structure might be seen by some as supporting the credit card mechanism as it definitively demonstrates that lipids reside within the groove. While the authors provide evidence that lipids can permeate outside the groove in this and earlier work, as far as we can tell, none of that would preclude permeation through the groove if it doesn't require specific interactions between lipids and sidechains in the protein. The presentation might be improved with a somewhat more circumspect and nuanced exposition of the new data and how it can be understood with earlier results.

There are several reasons why we do not think that the lipids in the C18/Ca2+ structure support the credit card mechanism, at least in the incarnation proposed for the TMEM16 scramblases.

1. In the credit card model, lipid headgroups enter and traverse the whole span of the groove (as described in multiple publications, i.e. Bethel and Grabe, PNAS, 2016; Jiang et al., Elife, 2018; Lee et al., Nat Comms, 2018; Kostriskii and Machtens, Nat Comms, 2021). The lipid densities near the groove suggest that P3 and P4 lipids are oriented with their heads facing the groove's exterior, not the interior. These heads are contiguous with other resolved lipids in the outer and inner leaflets, respectively. We added panels showing views of the pathway from the extracellular solution to better convey that the lipid heads do not enter the groove (see new Fig. 1F-G). We also added a statement on pg. 10 to clarify this important point.
2. In the present structures, which are consistent with earlier ones with lower resolution (Falzone et al., Elife, 2019; Kalienkova et al., Elife, 2019), residues in the extracellular vestibule do not interact with lipids (see new panels 1E-G). In contrast, the wide intracellular vestibule is embedded in the membrane. We agree with the reviewers that lipid headgroups can, and likely will, enter this wide vestibule during scrambling. We modified the text on pg. 12 to clearly state this point "The wide intracellular vestibule is embedded in the nanodisc membrane and, at the open pathway, the resolved P3 and P4 lipids have opposite orientations (Fig. 2A), suggesting scrambling might occur between them. In this case, the lipid headgroups would only need to move through the wide intracellular vestibule of the pathway below the T325-Y432 constriction rather than through the whole groove (Fig. 2A)."

These observations, together with the extensive mutagenesis data reported in Fig. 2 and 3, point to a mechanism that is different from the precisely coordinated credit-card mechanism that is the currently accepted paradigm for lipid scrambling.

Might the complex composition of native lipid membranes influence where and by what mechanism lipid movement between leaflets is catalysed by TMEM16 proteins?

The idea that the lipid composition might affect the mechanism of scrambling (i.e. through the groove vs out of the groove) is very interesting, and we are actively investigating it in the lab. However, it would be surprising if different lipids were scrambled by entirely different mechanisms.

2) The quality of lipid densities in cryo-EM structures is greatly affected by the number of particles used and the resolution obtained during refinement and it is therefore not surprising that the beautiful lipid densities observed here in the structure of afTMEM16 in lipid nanodiscs in the presence of calcium refined to 2.3 Å are not all observed in subsequent structures with lower resolution. This is true not only for the P lipids near the groove, but for those D lipids bound near the dimer interface, which is a stable region of the protein that does not change conformation. To be cautious, the authors should avoid resting any conclusions on the absence of lipid densities in the lower resolution structures. For example, on pg 15 the authors seem to be interpreting the absence of density for C22 lipids.

We agree with the reviewers on this point. However, at ~2.7 Å average resolution and with \>130,000 particles we would expect to see density for lipids near the pathway, if these were tightly bound. For example, in the mTMEM16F nanodisc structures from the Chen and Jan labs (Feng et al., Cell Reports, 2020), several lipid densities were identified near the closed pathway despite a substantially lower average resolution. However, we agree that we should not interpret this lack of signal and toned down our statement, "This suggests that the interactions of C22 lipids with the pathway helices are weaker than those of C18 lipids, possibly reflecting a higher energy cost associated with distorting these longer acyl chain lipids" to better indicate this is a possible explanation, rather than a definitive mechanistic interpretation.

3) The presentation of structural interactions between lipids and residues near the groove of the protein could be improved in the figures. A panel like Fig. 1J but for the groove would help, but it would be good to see expanded perspectives in the form of a supplementary figure where residues around the headgroup of the lipids are shown along with EM maps so the quality of the structural information for both lipids and side chains can be better appreciated. The preprint does have a lot of images of the lipids and the protein, but not in a way that enables the reader to quickly grasp the nature of interactions between side chains and lipid moieties for themselves, and we feel that close-ups of individual lipids as suggested above would help.

We thank the reviewers for this suggestion. We show density maps for the protein and lipids in Fig. 1C-E, and added close-up views of the densities near the groove in the new Fig. 1F-G to highlight the poses adopted by the lipids in this region. Figures showing both density and atomic models for the protein and lipids are very busy and difficult to discern; many of the lipids interact with multiple residues from different helices, with both their heads and tails. As such we could not find satisfactory views displaying both for the majority of the lipids.

It is also not clear what the authors mean by "lipid headgroup". Have the authors only considered interactions of the phospholipid phosphate group with protein residues? It would be helpful if the authors could clarify this in the manuscript and say whether other types of interactions were considered.

In our C18/Ca2+ map, we resolve a total of 16 lipids per monomer. Of these, we assigned 2 as PG lipids, because we could resolve the large PG headgroup (D4 and D5), shown in Fig. 1F-H and Supp. Fig 2. In all other cases, we truncated the lipids at the phosphate, as the density was insufficient to distinguish between a PC and a PG headgroup. This is now specified in the Fig. 1 legend. In our mutagenesis experiments (Fig. 2 and 3), we only targeted residues that were within interaction distance of the resolved portions of the headgroups, which is the phosphate in most cases. This is now clarified on page 11 "we investigated how mutating residues coordinating the resolved portions of the headgroups of P1-2 and P4-6 impacts scrambling."

It would also be nice to include a close-up view of D511A/E514A in 0.5 mM calcium with cryo-EM density to demonstrate the absence of bound calcium ions.

We thank the reviewers for this suggestion. We added a new panel in Supp. Fig. 10H showing a close-up of the cryoEM density of the mutant binding site.

4) The functional data in Fig 2, 3 and 4 are also not discussed in much detail and it would help if the authors could expand the presentation. Although scrambling in the presence of a very high concentration of calcium is not dramatically altered by any of the mutations, there is quite a lot going on in the absence of calcium and very little is said about these results. For example, differences in the scrambling rates can be observed with some mutants in the presence and absence of calcium in figures 2E and 3E, but statistical analysis would be required to know if the differences between mutants are significant. The differences in scrambling rates with different lipids are also not discussed (e.g. Fig. 4A) It would help if the authors could discuss what is the margin of error in the scrambling assay, and point to some concrete examples from their earlier work on this specific scramblase where mutants have a large impact on scrambling activity in their assay.

We agree with the reviewers that most mutants show some effects in 0 Ca2+. The effects are statistically significant for all but one mutant (2-tailed t-test, p\<0.005). However, the magnitude of the effects is relatively small (\<7-fold reductions in all cases). While our approach to quantify the scrambling rate constant captures well large changes, some of the assumptions underlying the analysis make it less well suited to quantify small effects. In past publications we used a 10-fold change as a cut-off threshold to consider an effect meaningful (Lee et al., Nat comms, 2018; Khelashvili, Falzone et al., Nat Comms, 2020). These limitations and rationale for choices are discussed in several of our past publications (Malvezzi et al., PNAS, 2018; Lee et al., Nat Comms, 2018; Falzone and Accardi, MiMB, 2020). We added statements indicating magnitude of the observed reduction for the mutants in the various conditions. We prefer to refrain from presenting statistical significance of these results as we do not want to convey the idea these effects are more meaningful than they might be.

Have the authors tried intermediate more physiologically relevant concentrations of calcium to see if the mutants have discernible effects under those conditions?

This is an excellent suggestion. However, in our experience the technical limitations of the experimental set-up and of the analysis render a precise quantification of small effects at intermediate Ca2+ concentrations not very reliable. For this reason, we did not pursue this further.

5) It is quite intriguing that the mutations in the subunit groove of afTMEM16 have little effect on scrambling activity. The authors propose that the groove-lining residues are not directly involved in lipid coordination even though their structure suggests that they do and there is a wealth of functional studies and MD simulations on various other TMEM16 homologs suggesting otherwise.

We are a bit confused by the reviewers' statement that our structure suggests that groove lining residues coordinate lipids. In our structures, the only two residues that directly line the open groove and coordinate lipids are T325 and Y432 (Fig. 2A). All other 23 residues tested either do not line the groove (9 residues mutated in Fig. 2) or do not interact with lipids (14 residues mutated in Fig. 3). The finding that mutating these residues has minor effects on scrambling suggests that interactions between lipids and these side chains is not required for scrambling.

We agree that the overall lack of effect of the mutants is surprising, especially in light of past work. However, none of the scrambling assays (in vitro or cell-based) can distinguish between mutations that affect permeation from those that affect gating. All that is measured is whether and -to a degree- how well lipids are transported. As such, we propose that at least some of the functional effects could have been misinterpreted. We are currently testing this hypothesis in the lab.

The discrepancy between our structural and functional results and the molecular mechanism emerging from MD simulations is more striking. Although some differences exist between the reports of different groups, the overall agreement among them is excellent. We were thus surprised that our data is so difficult to reconcile with their observations. Indeed, the extensive mutagenesis reported in Fig. 2 and 3 was performed to systematically test the unexpected inferences of our initial structural results (on the C18/Ca2+ structure). Our conclusions are also corroborated by the structures in different lipid compositions. In the discussion (pg. 21-22) we consider some of the possible sources for these discrepancies. For example, while in the MD simulations of nhTMEM16 the extracellular vestibule (i.e. E305, E310 and R425) is immersed in the groove, in our cryoEM maps we do not see evidence of lipids interacting with these residues (Fig. 1,2,3). Notably, a similar arrangement of the membrane-protein interface is seen in the Ca2+-bound open nhTMEM16 structure in nanodiscs (Kalienkova et al., Elife, 2019), indicating this issue is not specific to afTMEM16 or to the nanodisc used. We hypothesize this different membrane-protein interface is at the origin of the different proposed mechanisms. Another potentially relevant difference is that the tails of multiple lipids intercalate between helices forming the dimer cavity, some of which line the groove (Fig. 1). These lipids were not included in MD simulations as they were not previously resolved, and they could affect groove dynamics and, consequently, its interactions with the membrane. Other possibilities exist, but we believe they are less likely to be important (i.e. the limited nature of nanodiscs used for the cryoEM experiments could influence the protein-membrane interface, the mutations could have effects that are too subtle to measure in our assay). However, we think that enumerating all possibilities would lead to an overly lengthy discussion and require too much speculation.

We have revised the discussion of these important points in pg. 21-23 to better convey these uncertainties and added a statement (pg. 11) where we report the distance between the phosphate atom of the P3 lipid and E305 (13.7 Å), E310 (17.9 Å) and R425 (15.7 Å).

The authors' suggestion that mutations probably affect the equilibrium between open and closed conformations of the groove in other homologs but not in afTMEM16 is logical, however, there are some discrepancies. To name a few examples, if indeed this is the case, nhTMEM16 mutants with closed groove should still have significant basal scrambling, by extrapolation from afTMEM16 data. Yet, some of the nhTMEM16 mutants (E313/E318/R432 mutants) have no activity at all, or no basal scrambling activity (Y439A) (Lee et al, 2018). Would you expect that point mutations within the subunit groove remove the ability of the protein to deform the membrane in its closed conformation? Might the groove have intermediate conformations between closed and fully open where the mutants studied might have more impact in afTMEM16?

These are excellent ideas, and we are actively pursuing them in the lab. However, at the moment results are too preliminary to draw firm conclusions.

Further, mutating some of the residues on the scrambling domain of TMEM16 affected externalization of some lipid species, but not internalization etc. (Gyobu et al, 2017), which should not be the case if the interaction of the protein with the lipids is completely unnecessary for lipid scrambling.

This is a good point. However, mechanistic interpretation of results from cell-based scrambling assays is quite tricky, even more so than of the results from the in vitro measurements used in the present work. The presence of other lipid transporters and/or scramblases, or a multitude of other factors, could influence the results. For example, in cells scrambling by TMEM16F is delayed, it takes ~10 minutes after Ca2+ exposure to begin seeing PS externalization. In contrast, in in vitro measurements TMEM16F responds to Ca2+ nearly instantaneously, within the ~1 s mixing time of the cuvette (Alvadia et al., Elife, 2019). Thus, a direct comparison of the results obtained in cells and in vitro is not straightforward. More work is needed to investigate these important points.

While investigating this question further would require follow-up structural studies on other TMEM16 homologs and is outside of the scope of this study, we think that the manuscript would benefit from a more extensive discussion on contradicting results and alternative interpretations. The authors might want to consider the possibility that there may be substantial variations in how different scramblases function.

We agree that it is a priori possible that different TMEM16 proteins function according to different paradigms. However, we think this is an unlikely possibility. Despite differences in their gating behavior, most basic functional properties of TMEM16s are well conserved. Thus, fundamentally different mechanisms (i.e. through the groove or out of the groove) would have to result in similar functional phenotypes. We find the hypothesis that the basic scrambling mechanism is conserved among different TMEM16 homologues more plausible. While our results do not rule out that through the groove scrambling can occur, they suggest that it is not the main mechanism for afTMEM16, despite the fact that this protein adopts a very stable conformation with an open groove. Therefore, we consider the possibility of different mechanisms unlikely. This is mentioned on pg. 22 of the discussion.

afTMEM16 has high constitutive activity in the absence of calcium, while at least TMEM16F does not. Additionally, the extent to which scrambling is promoted by calcium varies, as mammalian scramblases might need other cellular factors to be activated. Also, the extent to which scramblases are seen to distort the membrane is highly variable, as again seen in TMEM16F structures. Might some of these differences imply that key aspects of the mechanism of scrambling (e.g. thinning of the membrane or whether lipids scramble inside or outside the groove) are not the same for all scramblases? This might be one way to organize the discussion to help reconcile some of the seemingly divergent findings in the field.

The reviewers raise an excellent point. Indeed, we find that for all TMEM16 homologues we have tested in the lab the degree of activity in 0 Ca2+ is highly dependent on the lipid composition. However, this does not appear to correlate with changes in conformation, as we report here for afTMEM16 and as reported by other groups for nhTMEM16 and TMEM16F.

6) The authors should correct the Ramachandran outliers in C18/calcium and C22/calcium structures.

We tried fixing the Ramachandran outliers, however this invariably led to worse fits of the atomic models with the density. Therefore, we believe it is appropriate to leave them as they are.

Additional suggestions for the authors to consider:

1) In several instances the authors conceptualize hypothetical mechanisms to set up experiments and frame their interpretations, which is not always the most straightforward way to communicate findings and what they reveal. The 'conveyor belt mechanism' introduced on page 10 is never fully defined in a way that helps the reader to understand what the functional effects of the mutants teach us. Might it be easier to set up the experiment by asking whether the interactions between sidechains that apparently interact with lipid headgroups in the structure play a critical role in scrambling, present the results and then conclude that they do not appear to? Collectively the functional effects of mutants do appear to suggest that specific side chain interactions are not critical for scrambling, but the conceptualized mechanism here makes the conclusions come across as unnecessarily forced.

We thank the reviewers for the suggestion. We agree that the conveyor belt mechanism is a bit of a strawman. However, it is a plausible mechanism based on the orientation of the lipids in the C18/Ca2+ map. The mutagenesis described in Fig. 2 was explicitly designed to test this possibility. Further, this allows us to draw a clear distinction between testing the roles of residues outside the groove and of side chains that directly line the groove.

The credit-card mechanism has been formally introduced and discussed in the field but has already been shot down in earlier work from the group and seems overly simplistic if we already know that scrambling can occur both inside and outside the groove from earlier studies. Just something for the authors to think about.

We do not believe our previous work (Malvezzi et al., PNAS, 2018) 'shot down' the credit-card model. While we proposed that the large, PEG-conjugated lipid headgroups traverse the membrane outside the groove, our model postulated that normal-sized headgroups were scrambled within the groove. Further, one of the recurring criticisms of that work, was that the path taken by the large PEG-conjugated lipids might not represent a physiologically relevant mechanism for normal lipids. Thus, the credit-card mechanism remained the dominant model to explain scrambling, as testified by many subsequent publications by multiple groups, including our own!

2) The uninitiated reader would greatly benefit from more of an introduction to the functional scrambling assay in the results and material and methods section so they can understand the results being presented. In the Material and methods, the authors mentioned: "All conditions were tested side by side with a control preparation", perhaps add here what exactly served as control –wild type protein in C18 lipids? It would be valuable to include information on the reconstitution efficiency between their preparations (WT in different lipid compositions and WT vs mutants). these if possible.

We thank the reviewers for this suggestion. We added a brief description of the assay in the Methods section and now specify that "All conditions were tested side by side with a control preparation of WT afTMEM16 reconstituted in C18 lipids."

3) Also, does the C18/calcium cryo-EM structure have sufficient resolution to distinguish between specific phospholipids (PG or PC) at the D1-D9 or P1-P7 positions? It would be particularly valuable if the authors could comment on whether PG or PC are observed in the D and P positions, or which lipids are lining the groove (P3-P6).

We could build 2 lipids as PG (D4 and D5), based on the presence of density that could accommodate the large PG headgroup. For other lipids, the density was too weak beyond the phosphate, and therefore we left them truncated. This is now stated in the Figure 1 legend.

4) While not essential, it would be interesting if the authors could perform the assay on the mutants with a more prominent effect in the absence of calcium (e.g. E310A, Y319A/F322A/K428A) with several additional calcium concentrations.

We thank the reviewers for this suggestion. However, as we noted above, given the relatively small effects and limitations of the assay, we do not believe we would be able to extract meaningful mechanistic information from these measurements in intermediate conditions.

5) The authors mentioned that the interaction of C22 lipids with the pathway helices is weaker than those of C18 lipids, which reflects the energy cost associated with distorting the longer lipids (page 15). However, they claimed that the interaction between the lipids and residues is not important for scrambling, which seems contradictory.

We apologize for the confusion. In our proposed model, the ability of afTMEM16 to thin the membrane is dictated by the interactions of the protein with the surrounding lipids. This is not only enabled by interactions between side chains and lipid headgroups, but also by interactions of the lipid tails interact with the protein (see for example the close-up panels in Supp. Fig. 2F-G and the text on pg. 11 "Rather, other factors, such as tail interactions with interhelical grooves, contribute to their association with afTMEM16 (Supp. Fig 2F-G) and stabilize the distorted membrane-protein interface that results in thinning at the pathway.")

(This is a response to peer review conducted by Biophysics Colab on version 1 of this preprint.)

That's a wide point beyond web3 -- to avoid the problems with big tech, we need to make software / products easier to create. Then there's little to gain by increasing scale beyond network effects (which is a separate topic web3 aims to solve).

I think we're already beginning to see this decentralization, if not in software then for YouTube & TikTok creators, indie makes etc in comparison to old media companies.

Reviewer #2 (Public Review):

Jepma et al. report an interesting manuscript studying how we learn from pain and its avoidance. The authors use an instrumental pain avoidance task where participants are required to choose between two stimuli, one of which is followed by painful thermal stimulation to the leg and the other is not. The probabilities of receiving pain drifted across trials using random walks. The authors combined this with pharmacological manipulation of the dopamine (via oral levodopa) or opioid (via oral naltrexone) systems and also with computational modelling of Q-learning rules and neuroimaging via fMRI. So, this is an ambitious and well conceived manuscript.

There are real strengths here. The manuscript is theoretically motivated, addresses a fundamental question about how we learn, and is generally well executed. The task is well controlled, the modelling choices seem appropriate, the imaging and its analyses are broad but well defended and choices in analysis strategies are well defined. The manuscript is well written. I did enjoy reading the manuscript.

The results have some interest. The modelling and neuroimaging data suggest important dissociations between learning about pain and learning about its absence - the modelling suggests faster learning rates for learning from pain than its avoidance. The imaging suggests that these two forms of learning are associated with different networks, with a known network linked to learning about pain but a novel network linked to learning about avoided pain.

These are worthwhile knowledge gains. The idea that different rate parameters govern learning about events that are present versus those that are absent is an old one. It is built into most error-correcting learning rules since Rescorla-Wagner and it makes sense. However, it was useful to see it supported here. The finding that different networks of brain regions were associated with the learning from pain versus avoided of pain was also interesting. The networks linked to the former made sense based on the literature. The networks linked to the latter were more novel and notably did not include classic 'relief' brain regions.

However, there were also important weaknesses here, at least on my readings.

I struggled as a reader to understand how the modelling actually related to the behavior and imaging. That is, there is a real disconnect in the manuscript for me between what is observed (behavior) what is inferred (modelling as well as it basis for correlations with fMRI data).

There were no differences in behavior reported between the two kinds of trials (learning from received pain versus avoided pain) effects, no effects of the drugs on behavioral performance, and no differential effect on learning from received pain versus avoided pain. I have no problems with reporting null effects, but here the reader is left wondering: if there are no behavioral differences reported, then why does the modelling predict that there should be? How accurate is the model given that it clearly predicts slower learning from avoided than received pain in the controls and faster learning from avoided pain under naltrexone and levodopa compared to control? In other words, what is it about the modelling that yields differences in learning rates between the two behavioral conditions and between the vehicle, levodopa, and naltrexone conditions when the behavioral data shown do not? Of course, it could be that the task was too easy - the modelling may be prescient and perhaps possible learning rate differences would be picked up under more difficult (more cues) and weaker probabilistic conditions. Perhaps there are behavioral data (reaction times?) not reported that do actually show differences in learning rate between learning from received pain versus avoided pain or show differences between the drug conditions?

I may have misunderstood all of this and am happy to be corrected. If not, think this issue needs to be addressed and would need new data that is hopefully already in hand to do convincingly (such as choice reaction times) to show some difference in behavior between learning from received pain versus avoided pain and/or some effects of the pharmacological manipulations on these.

In the absence of the data the manuscript seems to have three parts:

1. A more compelling set of findings reporting imaging differences between learning from received pain versus avoided pain that are interesting because they suggest a novel network of brain regions for the latter compared to the literature.<br> 2. A set of null findings that neither pharmacological manipulation affected behavior or these imaging findings.<br> 3. A less compelling set of findings that link the above to possible underlying differences in learning rate parameters.

The first could be of interest but the latter two need to be strengthened, in my opinion.

I had other minor points (e.g., consider the literature on opioid and dopamine receptor manipulations in the ventral striatum on aversive prediction errors because this suggests the opposite to the literature cited for the midbrain; is the word 'appetitive' in the title really appropriate given the findings in the manuscript), but these are less important than the above.

Author Response

Reviewer #1 (Public Review):

In this paper the authors use a conditional knockout strategy to assess the effects of deletion of the dominant oxygen-sensing hypoxia-inducible factor (HIF) hydroxylase enzyme, prolyl hydroxylase 2 (Phd2) restricted to the regulatory T cell (Treg) lineage. They use a well-established Foxp3-driven Cre recombinase allele. Phd2 is thus silenced in cells that have expressed or continue to express Foxp3 from the time this transcription factor, which is essential for Treg development and function, first occurs. They show that this approach leads to a change in Treg behaviour resulting in loss of some aspects of regulatory function and development of a Th1-like phenotype by the Foxp3 expressing cells. Effects are in general reversed when HIF-2 is silenced alongside Phd2, and may be amplified by simultaneous silencing of the HIF-1 isoform.

The findings overlap with those reported following generalised silencing of Phd2 and following adoptive transfer of Treg in which Phd2-silencing is induced (Yamamoto et al., 2019) and are broadly compatible with those reported following a similarly Treg-restricted knockout of the von Hippel-Lindau gene (the recognition component of the E2-ubiquitin ligase that targets HIF-alpha chains that have been modified by Phd2) (Lee et al., 2015) but the results reported also differ significantly from these earlier reports in a number of intriguing respects which I feel warrant further discussion and ultimately investigation.

The Introduction is in general informative and well written but it is a shame that it does not contain more discussion of the current state of knowledge of the interplay between HIF signalling and Treg function. This would provide a platform for a more detailed and scholarly discussion of the similarities and differences between this work and existing literature in the Discussion, where existing papers are currently described rather briefly. The introduction contains the statement 'Further complexity in this pathway has been provided by the identification of additional, non-HIF-related, PHD substrates, suggesting a role of proline hydroxylation in other settings requiring oxygen-dependent regulation', citing a single reference. This does not really represent the complex balance of arguments across the literature about non-HIF substrates for the HIF hydroxylase enzymes.

The conclusions of this paper are mostly well supported by data, but some aspects need to be clarified and extended.

We sincerely apologize for our apparent lack of recognition of previous work performed by other colleagues active in this field. We have now modified the Introduction section, to provide a better, yet concise, overview of the current knowledge of hypoxia signalling in regulatory T cell biology.

A central issue for any conditional knock-out strategy is whether the intended tissue restriction is successfully achieved. The authors acknowledge that some issues have been reported with the Cre-recombinase allele they use. They, however, show the expected restriction to cells of the Treg lineage in two of the lymphoid tissues under investigation (spleen and mesenteric lymph node - Supplementary figure 1b) but do not show similar results for other tissues. Some concerns arise because in Figure 8b YFP (which is expressed alongside the Cre-recombinase) is visible in what appears to be the endothelium of the spleen. Additionally, the spleen sections illustrated show convincing splenomegaly in the Phd2-deficient Treg mice but expansion of the red pulp appears to be at least as prominent as any changes that might have occurred in the white pulp. Furthermore, the gross changes in abdominal appearances described as a 'hemorrhagic abdomen' (Figure 1c) include a more plethoric abdominal wall, prominent intestinal blood vessels and a much darker, and perhaps enlarged, liver compared with the control animal. These appearances might result from increased angiogenesis and / or erythropoiesis, neither of which would be expected to result from Treg lineage restricted Phd2 knockout but are known to occur with Phd2 ablation in other tissues. If there is convincing evidence of haemorrhage it would be nice to see this more obviously displayed macro- or, perhaps better still, microscopically.

We thank the reviewer for this comment. We have now provided a better description of the haematological status of these mice, in which an elevated haematocrit and increased vascular permeability has been observed (now depicted in supplemental Figure 2). As suggested, we found indeed minimal, yet sizable expression of the Cre recombinase (as judged by YFP expression) in CD45-negative, non-lymphoid cells in all organs examined (as now depicted in supplemental Figure 9). Finally, none of the organs examined displayed an increased expression of erythropoietin (as judged by a sensitive qPCR assay, data not shown), a likely candidate for the haematological abnormalities observed in these mice. The mechanism underlying the apparent extramedullary erythropoiesis occurring in these mice remains therefore to be established. Noteworthy however, an additional experiment performed following a suggestion from one of the reviewers (see Figure 3 and our response 23), strongly suggests that PHD2 affects the Treg phenotype in a cell autonomous fashion. We do however acknowledge that the tissue abnormalities preclude any firm conclusion related to the positioning of Tregs within the spleen and have therefore deleted this section from the manuscript and adapted our conclusion consequently.

Given that the Cre-recombinase allele used is expressed through the endogenous Foxp3 locus which is located on the X-chromosome and thus subject to random inactivation in the cells of females it is important that the sex of animals used in the experiments is specified.

This has now been done in the Figure legends

Experiments show alterations in Phd2-deficient Treg mice compared with control mice in homeostatic proliferation in a lymphopenic environment (Figure 3), the induction of colitis by DSS colitis (Figure 4) and the response to Toxoplasma gondii infection (Figure 4). Given the time courses these effects are likely to be real but interpretation is complicated by the spontaneous effects on the colon of Phd2-deficient Treg mice reported in Figure 1d and e. Given the wide general importance of interferon-gamma in immune / inflammatory responses I am not sure how much weight to place on the observation that concurrent interferon-gamma knockout results in loss of the Phd2-deficient Treg mice pro-inflammatory phenotype (Figure S3). No differences are seen in an in vivo model in which inflammation is induced by injection of anti-CD3 antibodies (Figure S2).

Although the point is well taken, we felt it was important to perform a few experiments to illustrate the specificity of the inflammatory syndrome observed in these mice. We acknowledge the fact that the effect of concurrent loss of interferon-gamma on the phenotype of PHD2ΔTregs could have been anticipated. Additionnaly, we also think that the fact that these mice retain the same sensitivity to a “Th17-dominated” inflammatory response (also leading to a loss of weight) strengthens one of the messages of the manuscript, i.e. that loss of PHD2 expression affects Treg function in a selective, Th1-oriented fashion.

An important conceptual difference between the interpretation of results reported here and those reported by Yamamoto et al. is that the 'Phd2-deficient Treg' purified here do not show a change in regulatory function in vitro whereas those used by Yamamoto et al. failed to act normally as regulatory cells. It is unclear whether this is due to differences in the way proliferation was stimulated, the cell purification strategies used (YFP+ in the current work; CD4+;CD25+ in Yamamoto et al.), the silencing of Phd2 (by knockout throughout development here versus through an inducible-shRNA only in mature cells in Yamamoto et al.), some other feature of the experiments (e.g. the use of feeder cells) or whether a difference would be revealed by more extensive titration. The result reported here is somewhat surprising given the presence of a Th1-like immunophenotype in the cells used in these in vitro suppression assays, which at face value might mean that this immunophenotype is not responsible for changes in their regulatory capacity seen in vivo. This may be true, but it is at odds with Bayesian argumentation. It may be a coincidence, but both models in which control Treg and Phd2-deficient Treg behave similarly involve treatment with anti-CD3 antibodies, raising the possibility that these antibodies in some way nullify differences reported with other stimuli, rather than this necessarily being related to the hypothesised difference between Th1 and Th17 responses in the in vivo model.

We fully agree with the reviewer’s comment, and we were similarly worried that the differences reported in vivo vs in vitro were due to different agonists used. We however attempted to evaluate Treg function in vitro using alternative approaches, including an assay in which allogeneic antigen-presenting cells (including T-cell depleted spleen cells or highly purified dendritic cells) were used as agonists and Interferon-gamma secretion and proliferation as readouts. In another set of experiments, we used in vitro or in vivo derived Th1 cells instead of naïve T cells as responders. In all instances examined to date, PHD2-deficient Tregs displayed an adequate suppressive function in vitro (data not shown).

Data showing reversal of the Phd2-deficient Treg in vivo phenotype by knockout of HIF-2alpha, but not HIF-1alpha are convincing and support the data of Yamamoto et al. The observation that Treg-specific PHD2-HIF1α double knockout mice were born at sub-mendelian ratios, displayed a marked weight loss during adult life and reduced viability, indicative of a more pronounced pro-inflammatory status is reported but data is not shown. This is certainly of interest and will no doubt receive further attention. The data that Treg-selective HIF1α or HIF2α deficiency does not affect immune homeostasis in naive mice shown in Figure S4 is relevant and compelling. These results are discussed in the context of recent work published by Hsu et al., 2020 which is interesting. Taken together these data highlight the fact that results reported throughout this manuscript arise from a combination of developmental differences with those occurring in the adult animal.

We thank the reviewer for these positive comments

The transcriptomic data presented has not, to date, been made available to reviewers or the public. Importantly, it is reported to show a disconnection between changes in glycolytic gene expression pattern and the immune phenotype. Specifically, whilst loss of Phd2 expression in Treg is associated with alterations in their regulatory function and with induction of glycolytic genes, the change in function, but not the change in glycolytic gene expression, is reversed by simultaneous knockout of HIF-2alpha and conversely the gene expression pattern, but not the change in function, is reversed by simultaneous knockout of HIF-1alpha. This will be of great interest to those working on the hypothesis that the switch between oxidative phosphorylation and glycolysis underlies functional changes in T cells, particularly if the changes in glycolytic gene expression actually convert into changes in glycolytic flux (as observed following HIF-induction in other cell types).

The transcriptomic data are available to the public on GEO with the code: GSE184581

The authors propose that a change in CXCR3 expression resulting from a change in STAT1 phosphorylation (but not absolute levels of STAT1) consequent on Phd2- inactivation leads to mal-distribution of Treg (at least in the spleen), and that given the broadly paracrine action of Treg this feature alone might explain the loss of regulatory activity in vivo. This is an intriguing hypothesis based at least in part on associative data rather than a formal proof of causality. Changes in STAT1 phosphorylation following interferon-gamma stimulation are far from 'all-or-nothing' (at the timepoint illustrated many cells have normal pSTAT1 levels even though the mean fluorescence intensity is reduced). Results in Figure 7b show that changes in STAT1 phosphorylation are seen in conventional Foxp3 negative T cells; since Phd2 knockout is restricted to the Treg lineage this change is presumably indirect, raising the possibility that the change seen in Treg is also indirect, rather than truly cell autonomous. Changes in pSTAT1 are acknowledged to affect a huge number of genes / processes so picking any one as the total explanation for any change in behaviour may be an over simplification. The analysis of changes in Treg localisation in the spleen is potentially interesting and may reach the correct conclusion but the methodology used is not clearly explained and in particular it is not clear how splenomegaly / changes in gross splenic architecture have been taken into account.

We fully agree with the reviewer comments and have now deleted the final figure of our manuscript dealing with Treg positioning in the spleen. We indeed agree that due to the morphological changes in spleen size and architecture, more detailed work would be required to confirm our initial hypothesis. Unexpectedly, and thanks to a remark from another reviewer, we found that PHD2-deficient Tregs (which are present at high frequencies in the spleen of PHD2ΔTregs mice) are largely outcompeted both in heterozygous PHD-2fl/fl Cre+/- mice (see Figure 3) and upon equal transfer into WT mice of a 1:1 mix of wt and PHD-2-deficient Tregs, greatly complicating the study of the relative positioning of these cells within lymphoid organs. We do however stand by our previous conclusion suggesting that STAT1-signaling appears as affected in PHD2-deficient Tregs. This conclusion is not only supported by the reduced accumulation of pSTAT1 in these cells, as shown in Figure 8, but also by the bioinformatic analysis of transcriptomic data and the confirmation, at the protein level, of the reduced expression CXCR3 a well characterized STAT1-dependent chemokine receptors (as shown in Figure 8).

Overall, this work contains many interesting datasets which need to be taken into account as we build our understanding of the intersection between HIF-signalling and regulatory T cell function, particularly as pharmacological manipulation of HIF signalling may provide a route to immunomodulation through alterations in regulatory T cell function.

We thank again the reviewer for this positive appreciation of our work.

Author Response

Reviewer #1 (Public Review):

The key question addressed of this MEG study is whether speech is represented singly or multiplexed in the human brain in the linguistic hierarchy. The authors used state-of-the-art analyses (multivariate Temporal Response Functions) and probablilistic information-theoretic measures (entropy, surprisal) to test distinct contextual speech processing models at three hierarchical levels. The authors report evidence for the coexistence of local and global predictive speech processing in the linguistic hierarchy.

The work uses time resolved neuroimaging with state-of-the-art analyses and cognitive (here, linguistic) modeling. The study is very well conducted and draws from very different fields of knowledge in convincing ways. I see one limitation of the current study in that the authors focused on phase-locked responses, and I hope future work could extend to induced activity.

Overall, the flow in the MS could be streamlined. Some smoothing in the introduction would be helpful to extract the main key messages you wish to convey.

For instance, in the abstract:

-Can you explain the two views in a simpler way in the abstract and to a non-linguistic audience? Do you mean to say that classic psycholinguistic models tend to follow a strict hierarchically integration (analysis only) but an alternative model is hierarchically inferential (analysis by synthesis)?

-Indicate early on in abstract or intro where the audience is being led with a concise message on how you address the main question. For instance:

To contrast our working hypotheses A and B, we used a novel information-theoretic modeling approach and associated measures (entropy, surprisal), which make clear predictions on the latency of brain activity in responses to speech at three hierarchal contextual levels (sublexical, word and sentence).

We have revised the Abstract and Introduction to reduce the amount of terminology and add additional explanations. Wherever possible, we now use general terms (“bottom up”, “predictions”, “context”, …) instead of terms associated with specific theories. We hope we found a balance between improving accessibility and retaining the qualities seen by Reviewer 2, who thought the Introduction was clearly written and well connected to the psycholinguistics literature.

All the models we compare are compatible with an analysis by synthesis approach, as long as the generative models are understood to entail making probabilistic predictions about future input. The generative models in analysis by synthesis, then, are one way in which “to organize internal representations in such a way as to minimize the processing cost of future language input“ (Introduction, first paragraph). We have clarified this in the first paragraph of the Introduction.

• Why did the authors consider that the evoked response is the proper signal to assess as opposed to oscillatory (or non phase-locked) activity?

The primary reason for our choice of dependent measure is the prior research we based our design on, showing that the linguistic entropy and surprisal effects are measurable in phase-locked responses (Brodbeck et al., 2018; Donhauser and Baillet, 2020). We have made this more explicit in part of the Introduction where we introduce our approach (“To achieve this, we analyzed …”).

As to oscillatory dependent measures, we consider them an interesting but parallel research question. We are not aware of specific corresponding effects in non-phase locked activity. Accordingly, analyzing oscillatory responses without a clear prior hypothesis would require additional decisions, such as which bands to analyze, which would entail issues of multiple comparison. An additional caveat is that the temporal resolution of oscillatory activity is often lower than that of phase-locked activity, which might potentially make it harder to distinguish responses based on their latency as we did here, to test whether the latency of different context models differ.

• Parallel processing with different levels of context (hence temporal granularities) sounds compatible with temporal multiplexing of speech representation proposed by Giraud & Poeppel (2012) or do the authors consider it a separate issue?

We consider our investigation orthogonal to the model discussed by G&P (2012). G&P’s model is about the organization of acoustic information at different time-scales, and does not discuss the influence of linguistic constructs at the word level and above. On the other hand, the information-theoretic models that form the basis of our analysis track the linguistic information that can be extracted from the acoustic signal. The temporal scales invoked by G&P’s model are also different from the ones used here, defined based on acoustic vs. linguistic units. Thus, the kind of neural entrainment as a mechanism for speech processing hypothesized by G&P is fully compatible with our account, but not at all required by it.

Methods:

• Figure 2: please spell out TRFs and clarify the measured response

We have done both in the Figure legend.

• The sample size (N=12) is very low in today standards but the statistical granularity is that of the full MEG recording. Can a power estimate be provided or clear justification of reliability of statistical measures be described.

We appreciate and share the reviewers’ concern with statistical power and have made several modifications to better explain and rationalize our choices.

First, to contextualize our study: The sample size is similar to the most comparable published study, which had 11 participants (Donhauser and Baillet, 2020). Our own previous study (Brodbeck et al., 2018) had more participants (28) but only a fraction of the data per subject (8 minutes of speech in quiet, vs. 47 minutes in the present dataset). We added this consideration to the Methods/Participants section.

We also added a table with effect-sizes for all the main predictors to make that information more accessible (Table 1). This suggests that the most relevant effects have Cohen’s d > 1. With our sample size 12, we had 94% power to detect an effect with d = 1, and 99% power to detect an effect with d = 1.2. This post-hoc analysis suggests that our sample was adequately powered for the intended purpose.

Finally, all crucial model comparisons are accompanied by swarm-plots that show each subject as a separate dot, thus showing that these comparisons are highly reproducible across participants (note that there rarely are participants with model difference below 0, indicating that the effects are all seen in most subjects).

• The inclusion of a left-handed in speech studies in unusual, please comment on any difference (or lack thereof) for this participant and notably the lateralization tests.

We agree that this warrants further comment, in particular given our lateralization findings. We have made several changes to address this concern. At the same time we hope that the reviewers agree with us that, with proper care, inclusion of a left-handed participants is desirable (Willems et al., 2014), and indeed is becoming more mainstream, at least for studies of naturalistic language processing (e.g. Shain et al., 2020). First, we now draw attention to the presence of a left-hander where we introduce our sample (first paragraph of the Results section). Second, we repeated all tests of lateralization while excluding the left-hander. Because this did not change any of the conclusions, we decided to keep reporting results for the whole sample. However, third, we now mark the left-handed participant in all plots that include single-subject estimates and corresponding source data files. Overall, the left-hander indeed shows stronger right-lateralization than the average participant, but is by no means an outlier.

• The authors state that eyes were kept open or close. This is again unusual as we know that eye closure affects not only the degree of concentration/fatigue but directly impact alpha activity (which in turn affects evoked responses (1-40 Hz then 20 Hz) that are being estimated here). Please explain.

Previous comparable studies variably asked subjects to keep their eyes closed (e.g. Brodbeck et al., 2018) or open (e.g. Donhauser and Baillet, 2020). Both modes have advantages and disadvantages, none of which are prohibitive for our target analysis (ocular artifacts were removed with ICA and oscillatory alpha activity should, on average, be orthogonal to time-locked responses to the variables of interest). Importantly however, both modes have subjective disadvantages when enforced: deliberately keeping eyes open can lead to eye strain and excessive blinking, whereas closing eyes can exacerbate sleepiness. For this reason we wanted to allow subjects to self-regulate to optimize the performance on the aspects of the task that mattered – processing meaning in the audiobook. We extended the corresponding Methods section to explain this.

• It would be helpful to clarify the final temporal granularity of analysis. The TRFs time courses are said to be resampled to 1kHz (p22) but MEG time courses are said to be resampled at 100 Hz (p18).

Thanks for noting this. We clarified in the TRF time-course section: the deconvolution analysis was performed at 100 Hz, and TRFs were then resampled to 1 kHz for visualization and fine-grained peak analysis.

• The % of variance explained by acoustic attributes is 15 to 20 folds larger than the that explained by the linguistic models of interest. Can a SNR measure be evaluated on such observations?

We appreciate this concern, which is indeed reasonable. In order to better clarify this issue we have added a new paragraph, right after Table 1. In brief, since the statistical analysis looks for generality across subjects, the raw % explained values do not directly speak to the SNR or effect size. Rather, the SNR concerns how much variability is in this value across subjects. The individual subject values in Figure 3-B, and effect sizes now reported in Table 1, show that even though the % variability that is uniquely attributable to information-theoretic quantities is small, it is consistently larger than 0 across subjects.

Results and Figures:

• The current figures do not give enough credit to the depth of analysis being presented. I understand that this typical for such mTRFs approach but given the level of abstraction being evaluated in the linguistic inputs, it may be helpful to show an exemple of what to expect for low vs. high surprisal for instance from the modeling perspective and over time. For instance, could Figure 1 already illustrate disctinct predictions of the the local vs. global models?

Thank you for pointing out this gap. We have added two figures to make the results more approachable:

First, in Figure 3 we now show an example stimulus excerpt with all predictors we used. This makes the complete set of predictors quickly apparent without readers having to collect the information from the different places in the manuscript. It also gives a better sense of the detail that is modeled in the different stimulus representations. Second, we added Figure 6 to show example predictions from the different context models, and explain better how the mTRF approach can decompose brain responses into components related to different stimulus properties.

• Why are visual cortices highlighted in figures?

Those were darkened to indicate that they are excluded from the analysis. We have added a corresponding explanation to the legend of Figure 3.

• Figure 2 Fig 2A and B: can the authors quantitatively illustrate "5-gram generally leads to a reduction of word surprisal but its magnitude varies substantially between words" by simply showing the mean surprisal and its variance?

Added to the Figure legend.

Fig 2C: please explain the term "partial response"; please indicate for non M/EEGers what the arrow symbolizes.

Added to the Figure legend.

• Figure 3:

p8: the authors state controlling for the "acoustic features" but do not clearly describe how in the methods and this control comes as a (positive) surprise but still a bit unexpected at first read. Perhaps include the two acoustic features in Fig2C and provide a short couple sentences on how these could impair or confound mTRF performance.

We thank you for pointing out this lack of explanation. We have added a description of all the control predictors to the end of the Introduction, right after explaining the predictors of main interest. We have also added Figure 3 to give an example and make the nature of all the controls explicit.

Have the same analysis been conducted on a control region a priori not implicated in linguistic processing? This would be helpful to comfort the current results.

The analysis has been performed on the whole brain (excluding the insula and the occipital lobe). Figure 4 (previously Figure 3) shows that generally only regions in the temporal lobe exhibit significant contributions from the linguistic models (allowing for some dispersion associated with MEG source localization). Although this is not shown in the figure, regions further away from the significant region generally exhibit a decrease in prediction accuracy from adding linguistic predictors, as is commonly seen with cross-validation when models overfit to irrelevant predictors.

Fig 3B-C-E: please clearly indicate what single dot or "individual value" represents. Is this average over the full ROI? Was the orientation fixed? Can some measure of variability be provided?

Explanation of individual dots added to Figure 4-B legend (formerly 3-B). Fixed orientation added to the methods summary in the Figure 2-C legend. To provide more detailed statistics including a measure of variability we added Table 1.

Fig3E: make bigger / more readable (too many colors: significance bars could be black)

We have increased the size and made the significance bars black.

• Figure 4: having to go to the next Fig (Fig5) to understand the time windows is inconvenient and difficult to follow. Please, find a work around or combine the two figures. From which ROI are the times series extracted from?

We have combined the two figures to facilitate comparison, and have added a brief explanation of the ROI to the figure legend.

Reviewer #3 (Public Review):

This manuscript presents a neurophysiological investigation of the hierarchical nature of prediction in natural speech comprehension. The authors record MEG data to speech from an audiobook. And they model that MEG using a number of different speech representations in order to explore how context affects the encoding of that speech. In particular, they are interested in testing how the response to phoneme is affected by context at three different levels: sublexical how the probability of an upcoming phoneme is constrained by previous phonemes; word - how the probability of an upcoming phoneme is affected by its being part of an individual word; sentence - how the probability of an upcoming phoneme is affected by the longer-range context of the speech content. Moreover, the authors are interested in exploring how effects at these different levels might contribute - independently - to explaining the MEG data. In doing so, they argue for parallel contributions to predictive processing from both long-range context and more local context. The authors discuss how this has important implications for how we understand the computational principles underlying natural speech perception, and how it can potentially explain a number of interesting phenomena from the literature.

Overall, I thought this was a very well written and very interesting manuscript. I thought the authors did a really superb job, in general, of describing their questions against the previous literature, and of discussing their results in the context of that literature. I also thought, in general, that the methods and results were well explained. I have a few comments and queries for the authors too, however, most of which are relatively minor.

Main comments: 1) One concerns I had was about the fact that context effects are estimated using 5-gram, models. I appreciate the computational cost involved in modeling more context. But, at the same time, I worry a little that examining the previous 4 phonemes or (especially) words is simply not enough to capture longer-term dependencies that surely exist. The reason I am concerned about this is that the sentence level context you are incorporating here is surely suboptimal. As such, could it be the case that the more local models are performing as well as they are simply because the sentence level context has not been modeled as well as it should be? I appreciate the temporal and spatial patterns appear to differ for the sentence level relative to the other two, so that is good support for the idea that they are genuinely capturing different things. However, I think some discussion of the potential shortcomings of only including 4 tokens of context is worth adding. Particularly when you make strong claims like that on lines 252.

We strongly agree with the reviewer that the 5-gram model is not the ultimate model of human context representations. We have added a section to acknowledge this (Limitations of the sentence context model).

While we see much potential for future work to investigate context processing by using more advanced language models, a preliminary investigation suggests that it might not be trivial. We compared the ability of a pre-trained LSTM (Gulordava et al., 2018) to predict the brain response to words in our dataset with that of the 5-gram model. The LSTM performed substantially worse than the 5-gram model. An important difference between the two models is that our 5-gram model was trained on the Corpus of Contemporary American English (COCA), whereas the LSTM was trained on Wikipedia. COCA provides a large and highly realistic sample of English, whereas the language in Wikipedia might be a more idiosyncratic subsample. Thus, the LSTM might be worse just because it has been trained on a less representative sample of English. As an initial step we thus ought to train the LSTM on the superior COCA database, but this simple step alone would already be associated with a substantial computational cost, given the size of COCA at more than a billion words (we estimated 3 weeks on 32 GPUs in a computing cluster). Furthermore, while we acknowledge the limitations of the 5-gram model, we consider it very unlikely that its limitations are the reason that the more local models are performing well. In general, as more context is considered, the model’s predictions should become more different from the local model, i.e., a more sophisticated model should be less correlated with the local models, and should thus allow the local models to perform even better.

2) I found myself confused about what exactly was being modeled on my first reading of pages 4 through 7. I realized then that all of the models are based on estimating a probability distribution based on phonemes (stated on line 167). I think why I found it so confusing was that the previous section talked about using word forms and phonemes as units of representation (lines 118-119; Fig 2A), and I failed to grasp that, in fact, you were not going to be modeling surprisal or entropy at the word level, but always at the phoneme level (just with different context). Anyway, I just thought I would flag that as other readers might also find themselves thinking in one direction as they read pages 4 and 5, only to find themselves confused further down.

Thank you for pointing out this ambiguity; we now make it explicit that “all our predictors reflect information-theoretic quantities at the rate of phonemes” early on in the Expressing the use of context through information theory section.

3) I also thought some the formal explanations of surprisal and entropy on lines 610-617 would be valuable if added to the first paragraph on page 6, which, at the moment, is really quite abstract and not as digestible as it could be, particularly for entropy.

We appreciate that this needs to be much clearer for readers with different backgrounds. As suggested, we have added the formal definition to the Introduction, and we now also point readers explicitly to the Methods subsection that explains these definitions in more detail.

4) I like the analysis examining the possibility of tradeoffs between context models. I wonder might such tradeoffs exist as conversational environments vary - if the complexity of the speech varies and/or listening conditions vary might there be more reliance on local vs global context then. If that seems plausible, then it might be worth adding a caveat that you found no evidence for any tradeoff, but that your experiment was pretty homogenous in terms of speech content.

Thank you for this suggestion. We added this idea to the Discussion in the Implications for speech processing section.

I don't think it's any surprise that the US is a quite individualistic society in comparison to many other counties in the world. I personally don't feel too hopeful that the rhetoric that perpetuates individualism in our society will change, so I am curious to see what solutions may address these community inequalities/handicaps in education that we tend to neglect.

Author Response

Reviewer #2 (Public Review):

This paper combines neuroimaging, behavioral experiments, and computational modeling to argue that (a) there is a network of brain areas that represent physical stability, (b) these areas do so in a way that generalizes across many kinds of instability (e.g., not only a tower of blocks about to fall over, but also a person about to fall off a ladder), and (c) that this supports a simulation account of physical reasoning, rather than one based on feedforward processing; this last claim arises through a comparison of humans to CNNs, which do an OK job classifying physical instability but not in a way that transfers across these different stability classes. In my opinion, this is a lovely contribution to the literatures on both intuitive physical reasoning and (un)humanlike machine vision. At the same time, I wasn't sure that the broader conclusions followed from the data in the way the authors preferred, and I also had some concerns about some of the methodological choices made here.

1. The following framing puzzled me a bit, and even seemed to raise an unaddressed confound in the paper: "Here we investigate how the brain makes the most basic prediction about the physical world: whether the situation in front of us is stable, and hence likely to stay the same, or unstable, and hence likely to change in the immediate future".

Consider the following minor worry, which sets up a more major one: This framing, which connects 'stability' to 'change' and which continues throughout the paper, seems to equivocate on the notion of 'stability'. One meaning of 'stable' is, roughly, 'unchanging'. Another meaning is 'unlikely to fall over'. The above quotation, along with others like it, makes it seem like the authors are investigating the former, since that's the only meaning that makes this quotation make sense. But in fact the experiments are about the latter -- towers falling down, people falling off ladders, etc. But these aren't the same thing! So there's a bit of wordplay happening here, it seemed to me.

This sets up the more serious worry. As this framing reveals, unstable scenes (in the likely-to-fall-over sense) are, by their nature, scenes where something is likely to change. In that case, how do we know that the brain areas this project has identified aren't representing 'likeliness to change', rather than physical stability? There are, of course, many objects and scenes that might be highly likely to change without being at all physically unstable. Even the first example in the paper ("a dog about to give chase") is about likely changes without any physical instability. But isn't this a confound? All of the examples of physical instability explored here also involve likeliness to change! So these could be 'likely to change' brain areas, not 'physically unstable' brain areas. Right? Or if not, what am I missing?

The caption of Figure 1 seems to get at this a bit, but in a way I admit I just found a bit confusing. If authors do after all intend "physically unstable" to mean "likely to change", then many classes of scenarios that are unexplored here seem like they would be relevant: a line of sprinters about to dash off in a race, someone about to turn off all the lights in a home, a spectacular chemical reaction about to start, etc. But the authors don't intend those scenarios to fall under the current project, right?

The reviewer is correct that "stability" has (at least) these two different meanings, and also correct that we are investigating here the situation in which a configuration is not changing now but would be likely to change with just the slightest perturbation. Our hypothesis is that the “Physics Network” will be sensitive to the likelihood that a physical configuration will change for physical (not social) reasons. That is what our data show: we do not find the same univariate and multivariate effects for situations that are likely to change because of the behavior of an animal. This indicates that what we are decoding is not general ‘likeliness to change’ but rather physical instability in particular.

(Also: Is stability really 'the most basic prediction' we make about the world? Who is to say that stable vs. unstable is a more basic judgment than, say, present vs. absent, or expected vs. unexpected, or safe vs. unsafe, etc? I know this is mostly just trying to get the reader excited about the results, but I stumbled there.)

We have now modified the sentence to say: “…how the brain makes a fundamental prediction about the physical world: whether the situation in front of us is stable, and hence likely to stay the same, or unstable, and hence likely to change in the immediate future.”

1. Laying out these issues in terms of feedforward processing vs. simulation felt a bit misleading and/or unfair to those views, given the substance of what this paper is actually doing. In particular, the feedforward view ends up getting assimilated to "what CNNs do"; but these are completely different hypotheses (or at least can be). Note, for example, that many vision researchers who don't think CNNs are good models of human vision nevertheless do think that lots of what human vision does is feedforward; that view could only be coherent if there are kinds of feedforward processing that are un-CNN-like. It would be better not to conflate these two and just say that the pattern of results rules out CNN-like feedforward processing without ruling out feedforward processing in general.

This is a fair point, and we certainly agree that we cannot rule out all feedforward models. We have tried to be clear about this claim, e.g., here (in the Discussion: “Three lines of evidence from the present study indicate that pattern recognition alone – as instantiated in feedforward CNNs and the ventral visual pathway – is unlikely to explain physical inference in humans, at least for the case of physical stability."

3a. I wasn't sure how impressed to be by the fact that, say, 60% classification accuracy one class of stable/unstable scenes doesn't lead to above-chance performance on another class of stable/unstable scenes. Put differently, it seems that the CNNs simply didn't do a great job classifying physical stability in the first place; in that case, how general should we expect their representations to be anyway? Now, on one hand, I could see this worry only further supporting the authors' case, since you could think of this as all the more evidence that CNNs won't have representations of stability in them. But since (a) the claims the authors are making are about feedforward processing in principle, not just in one or two CNNs, and (b) the purpose of this paper is to explore the issue of generality per se, rather than just stability, this seems inadequate. It could be that a CNN that does achieve high accuracy on physical stability judgments (90%?) would actually show this kind of general transfer; but we don't know that from the data presented here, because it's possible that the lack of generality arises from poor performance to begin with.

You are correct in noting that CNNs don’t do a great job in classifying physical stability, which reinforces our point that pattern recognition systems are not very good at discerning physical stability. In fact, the classification accuracy that we have reported is close to the baseline performance in literature (Lerer et al 2016). Interestingly, training on the block tower dataset itself could only bring up the stability classification accuracy to 68.8% on the real-world block tower images. While this is true of the current best model of stability detection, we think that CNNs trained on large-scale datasets of stability under varying scenarios may in future be able to potentially generalize to other natural scenarios. However, to our knowledge no such datasets exist.

3b. I wasn't sure how to think about whether showing CNNs stable and unstable scenes is a fair test of their ability to represent physical stability. Do we know that stability is all that these images have in common? Maybe the CNN is doing a great job learning some other representation. This sort of thing comes up in some recent discussions of 'shortcuts' and/or the 'fairness' of comparisons between human and machine vision, including some recent theoretical papers (see author recommendations for specific suggestions here).

If our point were that CNNs do a great job at representing physical stability, we would indeed have to worry about low-level image confounds or “shortcuts” enabling this performance. But our point is that they do badly. If some of their already bad performance is due to image confounds/shortcuts then they are in fact doing even worse, and that only makes our point stronger.

4a. I didn't really follow this passage, which is relied on to interpret greater activity for unstable vs stable scenes: "we reasoned that if the candidate physics regions are engaged automatically in simulating what will happen next, they should show a higher mean response when viewing physically unstable scenes (because there is more to simulate) than stable scenes (where nothing is predicted to happen)." It seems true enough that, once one knows that a scene is stable, one doesn't then need a dynamically updated representation of its unfolding. But the question that this paper is about is how we determine, in the first place, that a scene is stable or not. The simulations at issue are simulations one runs before one knows their outcome, and so it wasn't clear at all to me that there is always more to simulate in an unstable scene. Stable scenes may well have a lot to simulate, even if we determine after those hefty simulations that the scene is stable after all. And of course unstable scenes might well have very little to simulate, if the scene is simple and the instability is straightforwardly evident. Can the authors say more about why it's easier to determine that a stable scene is stable than that an unstable scene is unstable? They may have a good answer! It would just be better to see it in the paper.

The idea here is that forward simulation happens in all cases but stops if no change has occurred since the last frame. That stopping, both represents the stability of the configuration and produces less activity. This idea is akin to the “sleep state” used for nonmoving objects in a physics engine: they do not need to be re-simulated or re-rendered if they have not moved since the last frame (Ullman et al, 2017 TICS).

4b. I was confused a bit by the Animals-People condition, and whether to think of it as a control condition or not. The image of it in Figure 1a makes it seem like it is meant to be interpreted along the usual "physical stability" lines, just like falling towers and people on ladders, and the caption seems to say this too; it also makes intuitive sense since the man in the boat looks like he'll fall if and when the alligator attacks. But then in the main text the authors predict that the representations of stability would not extend to the Animals-People condition, because they are just supposed to be about peril but not stability. Why not? And then the results themselves are equivocal, with some findings generalizing to Animals-People and some not. I don't have much more to say here other than that I found this hard to follow.

We used the Animals-People as a control for peril/instability that is not caused by the physical situation (but rather by another agent). Our hypothesis was that the “Physics Network” would hold information about physical stability, not just any kind of propensity for change for any reason. Hence, we predicted, that any brain region responding (only) to physical stability should not respond in a similar way to peril/non-peril conditions in the Animals-People scenario as they involve a more biological-agent driven interaction. That is what we found.

Reviewer #2 (Public Review):

This paper combines neuroimaging, behavioral experiments, and computational modeling to argue that (a) there is a network of brain areas that represent physical stability, (b) these areas do so in a way that generalizes across many kinds of instability (e.g., not only a tower of blocks about to fall over, but also a person about to fall off a ladder), and (c) that this supports a simulation account of physical reasoning, rather than one based on feedforward processing; this last claim arises through a comparison of humans to CNNs, which do an OK job classifying physical instability but not in a way that transfers across these different stability classes. In my opinion, this is a lovely contribution to the literatures on both intuitive physical reasoning and (un)humanlike machine vision. At the same time, I wasn't sure that the broader conclusions followed from the data in the way the authors preferred, and I also had some concerns about some of the methodological choices made here.

1. The following framing puzzled me a bit, and even seemed to raise an unaddressed confound in the paper: "Here we investigate how the brain makes the most basic prediction about the physical world: whether the situation in front of us is stable, and hence likely to stay the same, or unstable, and hence likely to change in the immediate future".

Consider the following minor worry, which sets up a more major one: This framing, which connects 'stability' to 'change' and which continues throughout the paper, seems to equivocate on the notion of 'stability'. One meaning of 'stable' is, roughly, 'unchanging'. Another meaning is 'unlikely to fall over'. The above quotation, along with others like it, makes it seem like the authors are investigating the former, since that's the only meaning that makes this quotation make sense. But in fact the experiments are about the latter -- towers falling down, people falling off ladders, etc. But these aren't the same thing! So there's a bit of wordplay happening here, it seemed to me.

This sets up the more serious worry. As this framing reveals, unstable scenes (in the likely-to-fall-over sense) are, by their nature, scenes where something is likely to change. In that case, how do we know that the brain areas this project has identified aren't representing 'likeliness to change', rather than physical stability? There are, of course, many objects and scenes that might be highly likely to change without being at all physically unstable. Even the first example in the paper ("a dog about to give chase") is about likely changes without any physical instability. But isn't this a confound? All of the examples of physical instability explored here also involve likeliness to change! So these could be 'likely to change' brain areas, not 'physically unstable' brain areas. Right? Or if not, what am I missing?

The caption of Figure 1 seems to get at this a bit, but in a way I admit I just found a bit confusing. If authors do after all intend "physically unstable" to mean "likely to change", then many classes of scenarios that are unexplored here seem like they would be relevant: a line of sprinters about to dash off in a race, someone about to turn off all the lights in a home, a spectacular chemical reaction about to start, etc. But the authors don't intend those scenarios to fall under the current project, right?

(Also: Is stability really 'the most basic prediction' we make about the world? Who is to say that stable vs. unstable is a more basic judgment than, say, present vs. absent, or expected vs. unexpected, or safe vs. unsafe, etc? I know this is mostly just trying to get the reader excited about the results, but I stumbled there.)

2. Laying out these issues in terms of feedforward processing vs. simulation felt a bit misleading and/or unfair to those views, given the substance of what this paper is actually doing. In particular, the feedforward view ends up getting assimilated to "what CNNs do"; but these are completely different hypotheses (or at least can be). Note, for example, that many vision researchers who don't think CNNs are good models of human vision nevertheless do think that lots of what human vision does is feedforward; that view could only be coherent if there are kinds of feedforward processing that are un-CNN-like. It would be better not to conflate these two and just say that the pattern of results rules out CNN-like feedforward processing without ruling out feedforward processing in general.

3a. I wasn't sure how impressed to be by the fact that, say, 60% classification accuracy one class of stable/unstable scenes doesn't lead to above-chance performance on another class of stable/unstable scenes. Put differently, it seems that the CNNs simply didn't do a great job classifying physical stability in the first place; in that case, how general should we expect their representations to be anyway? Now, on one hand, I could see this worry only further supporting the authors' case, since you could think of this as all the more evidence that CNNs won't have representations of stability in them. But since (a) the claims the authors are making are about feedforward processing in principle, not just in one or two CNNs, and (b) the purpose of this paper is to explore the issue of generality per se, rather than just stability, this seems inadequate. It could be that a CNN that does achieve high accuracy on physical stability judgments (90%?) would actually show this kind of general transfer; but we don't know that from the data presented here, because it's possible that the lack of generality arises from poor performance to begin with.

3b. I wasn't sure how to think about whether showing CNNs stable and unstable scenes is a fair test of their ability to represent physical stability. Do we know that stability is all that these images have in common? Maybe the CNN is doing a great job learning some other representation. This sort of thing comes up in some recent discussions of 'shortcuts' and/or the 'fairness' of comparisons between human and machine vision, including some recent theoretical papers (see author recommendations for specific suggestions here).

4a. I didn't really follow this passage, which is relied on to interpret greater activity for unstable vs stable scenes: "we reasoned that if the candidate physics regions are engaged automatically in simulating what will happen next, they should show a higher mean response when viewing physically unstable scenes (because there is more to simulate) than stable scenes (where nothing is predicted to happen)." It seems true enough that, once one knows that a scene is stable, one doesn't then need a dynamically updated representation of its unfolding. But the question that this paper is about is how we determine, in the first place, that a scene is stable or not. The simulations at issue are simulations one runs before one knows their outcome, and so it wasn't clear at all to me that there is always more to simulate in an unstable scene. Stable scenes may well have a lot to simulate, even if we determine after those hefty simulations that the scene is stable after all. And of course unstable scenes might well have very little to simulate, if the scene is simple and the instability is straightforwardly evident. Can the authors say more about why it's easier to determine that a stable scene is stable than that an unstable scene is unstable? They may have a good answer! It would just be better to see it in the paper.

4b. I was confused a bit by the Animals-People condition, and whether to think of it as a control condition or not. The image of it in Figure 1a makes it seem like it is meant to be interpreted along the usual "physical stability" lines, just like falling towers and people on ladders, and the caption seems to say this too; it also makes intuitive sense since the man in the boat looks like he'll fall if and when the alligator attacks. But then in the main text the authors predict that the representations of stability would not extend to the Animals-People condition, because they are just supposed to be about peril but not stability. Why not? And then the results themselves are equivocal, with some findings generalizing to Animals-People and some not. I don't have much more to say here other than that I found this hard to follow.

5. "Interestingness" ratings felt like a not-quite-adequate approach for evaluating how attention-grabbing the towers were. A Bach concerto is more interesting than a gunshot (and would be rated that way, I imagine), but the gunshot is surely more attention-grabbing. Why not use a measure like how much they distract from another task? That's the sort of thing I'd have expected, in any case.

Author Response

Reviewer #1 (Public Review):

In Wang et al., the authors investigate issues related to the relative proportion of flux for the enzymatic decarboxylation of pyruvate between PDH (pyruvate dehydrogenase) and PFOR (pyruvate-ferredoxin oxoreductase) in the model organism Synechococystis. The manuscript provides evidence that PDH becomes increasingly inactivated by a high ratio of NADH:NAD+ as well as evidence to suggest that PFOR is transcribed and remains intact under aerobic conditions. The authors put forward the theory that both PDH and PFOR are functionally active routes for pyruvate decarboxylation under aerobic conditions, whereas PFOR has previously been assumed to be inactive under growth conditions containing oxygen. This distinction is particularly highlighted by conditions where Synechocystis is grown photomixotrophically - and where the NADH:NAD+ pool may be relatively over-reduced because of two parallel inputs of reductant (water-splitting at PSII and catabolism of glucose). The authors examine growth under photoautotrophic and photomixotrophic conditions for a number of relevant mutants including members of the ferredoxin/flavodoxin family, PFOR, and NDH-1 complex subunits.

The theory put forward in this manuscript is of general interest regarding electron flux through the combined electron transport chain (photosynthetic + respiratory) of cyanobacteria. The authors further broaden the potential audience for the manuscript by elaborating on the potential significance of these results in the context of a switch from PFOR (ancestral) to PDH (oxygenic/modern).

Comments:

Generally, theories put forward in this manuscript are intriguing and have a number of potential implications for understanding electron flux and regulation of central metabolic processes in photosynthetic microorganisms. If these theories are supported and become more generally adopted, they would have significant impact on the understanding of the regulation of central carbon metabolism in cyanobacteria. That said (due in no small part to the complexity of some of these pathways), the evidence provided to support the hypotheses is indirect in many instances. In some cases, there is a pairing of indirect data with broad statements that can come across as over-reach. These problems can be somewhat exacerbated by an unclear organization at parts of the Discussion, a lack of succinctly defined claims, and numerous typographical considerations.

Thank you very much for this point. We now reorganized the discussion and overhauled it completely. It starts with aspects that are best supported by our data. We then added two sentences to stress that the following lines include hypothetical considerations that are meant as thought-provoking impulses. We hope that thereby over-reach is prevented.

Major considerations:

A major component of the proposed theories in this manuscript rest upon the assumption that PFOR is an active enzyme under highly aerobic conditions: this claim is never directly demonstrated.

This is true. We could show though that PFOR of Synechocystis is in constrast to most bacterial PFORs stable in the presence of oxygen. However, as stated likewise for the oxygen stable PFOR of the obligate aerobe Sulfolobus acidocaldarius (3), and PFOR from E. coli, which was recently shown to contribute to metabolism in the presence of oxygen in vivo (1) we as well had to remove oxygen for enzyme acitivty in vitro. This point is discussed frankly.

Indirect evidence of altered growth of pfor mutants, increased repression of PDH, and the higher NADH:NAD+ ratio under photomixotrophic conditions is in general alignment with this theory. However, while deletion of pfor does indeed result in altered growth dynamics in Synechocystis under periods of photomixotrophy, the alterations do not entirely align with the idea that this pathway is critical for rapid growth under aerobic conditions. For instance, pfor and most of the highlighted mutants (fdx 3, fdx 9, isiB) presented in Figure 3 show the greatest defects in their OD after reaching stationary phase (more rapid decline in OD on/after Day 6) relative to WT. This doesn't align as nicely with the highest NADH:NAD+ seen in Days 3-5 (which is also specifically called out: e.g., Line 146, Supplemental Figure S8).

We are very cautious to compare growth experiments day by day. This is due to the fact that the growth behaviour of WT and mutants differ between experiments. We therefore repeat these experiments in several independent experiments including at least three replicates and show the data of typical growth experiments. In the case of the shown growth behaviour of WT and pfor and the NADH/NAD+ ratios under photoautotrophic and photomixotrophic conditions shown in figure 1, NADH/NAD+ ratios were determined in exactly those cultures for which growth data are shown. It is therefore legitimate to directly compare these results day by day. However, we did not determine the NADH/NAD+ ratios of the cultures shown in Fig. 3. The rise in NADH might have started with a delay here.

In this context, the deletion of F-GOGAT is much more convincing in it's severity and timing, yet for this mutation to have a more severe phenotype is unexpected if PFOR is one of the primary/sole electron donors to the ferredoxin pool from glucose utilization as proposed (i.e., stated differently, F-GOGAT is only one of the enzymes downstream of ferrodoxin and might be expected to have a more subtle phenotype in comparison to the KO of PFOR if that is a primary source for electrons to ferredoxin under photoheterotrophic conditions).

F-GOGAT requires reduced ferredoxin which can be provided by PFOR and in addition also by PSI. As electrons from glucose oxidation can be fed via photosynthetic complex I into the PQ-pool they will eventually arrive at PSI (Fig. 3C) where ferredoxin can be reduced and transfer electrons to F-GOGAT. However, to get a truly complete picture of the situation several issues will have to be addressed in the future: we do not know which of the low abundant ferredoxins as well as high abundant ferredoxin 1 interact with PSI, F-GOGAT, PFOR and photosynthetic complex I. It would be furthermore helpful to know all midpoint potentials of the different ferredoxins. Without this information it might be too much to ask for a simple interpretation.

A central tenant of the argument put forward on the evolutionary importance of using either PFOR vs. PDH is the conservation of extra free energy by the former reaction. However, additional information on the ferredoxin paralog(s) that accept electrons from PFOR is necessary to evaluate these claims. Based on the data within these manuscripts, Fdx3, Fdx9, and IsiB have the strongest links to PFOR: though the authors do take care to never state directly that they have evidence that these are the acceptors in vivo. Given the variability in the midpoint potentials of different ferredoxins, some ferredoxin acceptors may better conserve the free energy in pyruvate, while others may actually be more 'wasteful' than NAD+ as the acceptor through PDH. Unfortunately, the midpoint potentials for Fdx3, Fdx9, and IsiB are unknown or not stated in this manuscript. It is therefore unclear what ferredoxin is being used as the reference point for conservation of Gibbs free energy in Figure 4C and referenced multiple times in the text.

We agree that it would be great if we already knew the redox potentials of all the ferredoxins involved. We are currently working on this issue. All that we know for now is that the redox potentials of ferredoxins lay between -240 mV to -680 mV whereas the redox potential is around -320 mV for NAD(P)H/NAD(P)+. Unpublished data that require further validation reveal that the redox potential of Fdx9 is definitely more negative than the redox potential of Fdx1 (-412 mV) in Synechocystis and is thereby clearly more negative that -320 mV. However, as these data require further validation, we did not name numbers. In addition, interaction studies on PFOR and low abundant ferredoxins are planed and preparations are in progress.

Finally, the measurements of NADH:NAD+ (most prominently used for measurements in Fig 1B) utilized kits that require multiple, long centrifugation steps in the dark prior to assaying this rapidly exchanging pool. While it appears that the authors were able to get reproducible results with these kits, it is difficult to interpret what the increase in relative NADH levels in glucose-fed cells means given that 10+ minutes of incubation in the dark and/or changing temperatures elapsed after the cyanobacteria were removed from the incubator before the NADH:NAD ratio was assessed. While it superficially makes logical sense that the cytosol would be over-reduced when illuminated and under glucose feeding relative to illumination alone, it shouldn't be assumed that these measurements are representative of this rapidly-exchanging pool under the steady-state growth conditions.

Thank you very much for raising this important point. We are very much aware of the difficulties to determine the redox state of NADH:NAD+ using these kits. However, there is no other method available that properly distinguishes NADH and NADPH. Furthermore, the centrifugation step was done at -9°C which should minimize metabolic reactions during this step. However, we now added in vivo measurements using the NAD(P)H-module available for the PAM and using the Dual-KLAS/NIR to determine the redox state of ferredoxin (newly added Fig. S4). Both methods show that NAD(P)H as well as ferredoxin are more strongly reduced under photomixotrphic conditions in comparison to photoautotrophic conditions and thus support our previous data.

Reviewer #2 (Public Review):

The observation that cyanobacteria can use two alternative pyruvate decarboxylating enzymes using either NAD+ or ferredoxin is an interesting and the work is useful contribution. The authors very nicely characterize the enzymatic properties of the two pyruvate metabolizing enzymes and also are able to connect the ideas of redox balance with a set of ferredoxins. Even though they are not able to definitively characterized the specific ferredoxin which interacts with the enzyme, the analysis is nicely conducted and it's clear that the suggestion they're making regarding the involvement of the minor ferredoxins is compelling. However, the work could be written in a way that might be more useful.

Specific comments:

Overall this is an interesting study, but the arguments could be sharpened and better connected with the literature. The introduction needs to be considerably revised in my opinion. It is not obvious whether it is even appropriate to discuss the enzymes as an aerobic enzymes or aerobic enzymes, since this concept is simplistic and perhaps, archaic. Indeed, placing the results of the present study in the context of "aerobic enzymes versus aerobic enzymes" is a bit of a 'strawman' argument. For example, the counter examples of O2-tolerant enzymes cited seem to suggest that PFORs have been capable of evolving into O2-tolerant enzymes quite readily and that two types of decarboxylase have evolved for quite different reasons than simple replacement for a new environment. Instead, I think a more current and general perspective relates more to the interpretation that the authors are already putting forth. Namely, the enzymes are utilized according to redox balance considerations rather than sensitivity to oxygen.

Therefore, I think the very long and pedantic introduction is useful for review, but only if it is shortened and also includes the alternative interpretation regarding adaptations to redox potential in the cytoplasm. My guess is that there are plenty of examples of redox balance function arguments in the literature to refer to in contrast to the evolutionary replacement argument used. Certainly, there are good examples regarding glucose toxicity in mutants of Synechocystis that can be considered.

Thank you very much for this point. The O2-tolerant PFORs mentioned were merely shown to be stable in the presence of oxygen in vitro which means that they can be isolated under anaerobic conditions. However, all enzymatic in vitro assays required anaerobic conditions. Only one PFOR was shown to be active in the presence of oxygen in vitro. Physiological studies on the importance of these enzymes under aerobic conditions in vivo are completely missing. However, animated by the requests of the reviewers we searched the literature intensively again and indeed found a recent report, which describes the involvement of PFOR in redox regulation in an aerobic culture of an E. coli mutant, in which glucose-6P dehydrogenase (ZWF) was down-regulated (1). We included this study both in our introduction and discussion. It very much supports our own findings, as the E. coli PFOR requires likewise anoxic conditions in in vitro enzyme tests. We agree that the idea that PDH complex and PFOR are exclusively regulated by oxygen availability might sound simplistic. However, we do not fully agree that this is a strawman argument as both enzyme systems are still mostly discussed as counterparts for either aerobic respiration (PDH complex) or anaerobic fermentation (PFOR)(4). To the best of our knowledge, the study that was included now and our own data, are the very first ones that put clearly forward the idea, that redox control governs the activity of these enzyme systems at the pyruvate node independent of oxygen. However, doubts about the rather simplistic distinction between aerobic versus anaerobic enzymes in general have indeed been expressed. Even though these studies in general lack physiological in vivo experiments. We therefore included this information in the introduction as well. (line 76: There are several reports on the aerobic expression of enzymes that are assigned to anaerobic metabolism in prokaryotes and eukaryotes and therefore challenge the simplistic distinction between aerobic versus anaerobic enzymes (5-7). Their physiological significance and regulation are only partly understood.) This did not result in a shortened introduction though as additional information was added. The new introduction thus includes alternative interpretations as requested and is therefore hopefully more balanced.

Given the interpretation that the alternative forms of the enzyme help cells adjust their redox balance to different conditions, such as photomixotrophic growth, the very nice enzymatic analysis and growth studies of the mutants work would be significantly strengthened by more direct physiological measurements that report intracellular redox states.

Thank you very much for this important point. Intracellular redox states were shown by measurements of the NAD+/NADP level (Figure 1B) and were now extended by new in vivo measurements that show that both the NAD(P)H and the ferredoxin pools are more reduced under photomixotrophic in contrast to photoautotrophic conditions (new Fig. S4).

Minor comments:

line 211: Perhaps, "..the deleted alleles failed to segregate, keeping some wild type copies."

This was changed to: the deleted alleles of fx2 (sll1382) and fx5 (slr0148) failed to segregate, keeping some wild type copies.

It would be interesting to characterize whether the observed distribution of PFOR correlates with specific physiological features. In other words, PFOR seems to become important upon the addition of an external carbon source in way that must integrate with autotrophic metabolism (i.e. mixotrophic growth) altering the balance of the oxidized and reduced form of redox cofactors--does the observed distribution correlate at least with the metabolic characteristics of the handful that have been studied in the lab?

Thank you very much for this suggestion. We checked the lists of cyanobacteria that either possess or do not possess a PFOR in order to search for shared known physiological features. However, the challenge is currently that the number of uncharacterized cyanobacteria in our list is too large. It is therefore impossible to find solid correlations. But we fully agree that it would be interesting to find these.

A more detailed set of calculations that help explain panel C in figure 4 need to be included to support the quoted values for redox potential in free energy. I assume these are standard values and and the specific superscripts and subscription associate with the ΔG nomenclature needs to be defined.

The calculations are shown in the materials and methods part. A respective notice (for calculations see materials and methods part) is now given in the legend of Fig. 4C. Information concerning the nomenclature is found in the cited literature in the materials and methods part as well.

Reviewer #3 (Public Review):

The manuscript by Wang et al. conclusively demonstrates that the cyanobacterium Synechocystis sp. PCC6803 prefers to use the ferredoxin-reducing enzyme PFOR over the NAD+-reducing PDH-pathway when grown under photomixotrophic conditions while the PDH-route is favored under photoautotrophic conditions. Both the potential physiological meaning of this switch and implications for the evolutionary history of the role of the respective enzymes and their pathways are discussed.

The main hypothesis of this work considers that PFOR-mediated decarboxylation of pyruvate replaces the PDH-based one when cells shift from photoautotrophic to photomixotrophic growth conditions. This hypothesis is assessed via the comparison of growth curves measured on a host of deletion mutants and via direct detection of expression levels of certain enzymes. The authors' hypothesis is robustly supported by the majority of the reported experiments and the reviewer is fully convinced by these data. However, I would hold that the data shown with respect to phosphorylation of PDH (Fig. S4) are unconvincing. I can't see a clear difference in growth-curves for the incriminated mutants deltaspkB and L which would convincingly exceed the variation observed for the entire dataset.

We agree that the data on the phosphorylation of the PDH complex including the kinase mutants are not very convincing. We were uncertain from the beginning on whether it would be a good idea to include these data sets and therefore discussed them very cautiously in the manuscript. Anyway, as the enzymatic tests with the E3 subunit of the PDH complex at different NADH concentrations show convincingly that high NADH levels have an inhibitory effect on the complex, we now decided to delete both data sets out of the manuscript, as they are not really required for the statement of the manuscript.

1) S. Li et al., Dynamic control over feedback regulatory mechanisms improves NADPH flux and xylitol biosynthesis in engineered E. coli. Metab Eng 64, 26-40 (2021).

2) T. Nakayama, S. Yonekura, S. Yonei, Q. M. Zhang-Akiyama, Escherichia coli pyruvate:flavodoxin oxidoreductase, YdbK - regulation of expression and biological roles in protection against oxidative stress. Genes Genet Syst 88, 175-188 (2013).

3) A. Witt, R. Pozzi, S. Diesch, O. Hädicke, H. Grammel, New light on ancient enzymes – in vitro CO2 Fixation by Pyruvate Synthase of Desulfovibrio africanus and Sulfolobus acidocaldarius. The FEBS Journal 286, 4494-4508 (2019).

4) M. Müller et al., Biochemistry and Evolution of Anaerobic Energy Metabolism in Eukaryotes. Microbiology and Molecular Biology Reviews 76, 444 (2012).

5) S. B. Gould et al., Adaptation to life on land at high O2 via transition from ferredoxin-to NADH-dependent redox balance. Proceedings of the Royal Society B: Biological Sciences 286, 20191491 (2019).

6) O. Schmitz, J. Gurke, H. Bothe, Molecular evidence for the aerobic expression of nifJ, encoding pyruvate : ferredoxin oxidoreductase, in cyanobacteria. FEMS Microbiol. Lett. 195, 97-102 (2001).

7) K. Gutekunst et al., LexA regulates the bidirectional hydrogenase in the cyanobacterium Synechocystis sp. PCC 6803 as a transcription activator. Molecular Microbiology 58, 810-823 (2005).

Author Response

Reviewer #1 (Public Review):

Strength: Excellent statistical methods are employed. Specimens collected from two centers are used.

Weakness: It is not clear what new knowledge this follow-up study bring to the audience. The critical biomarker, miR150 they propose for development of biodosimetry assay was already discovered. There are close to dozen publications showing the dose response of miR50, in mouse, rats, non-human primates and humans (including two research papers and and several reviews from authors). The dose response shown in 4b is not appreciable. Introduction and discussion talk about clinical utility for triage after nuclear disaster. Is analysis of miRNAs purified from exosome a viable approach for triage and clinical decision making? If so, please provide convincing argument showing practicality.

We appreciate that the reviewer and the editor believe that “excellent bioinformatics and biostatistical methods are employed”. We apologize for the confusion regarding miR-150 and its utility as a radiation exposure biomarker. Indeed we and others have shown the importance of miR-150 and other miRNAs in detecting radiation exposure in mice and macaques. We had inferred that the resulting evolutionarily conserved radiation-inducible microRNAs were very likely to translate well to humans due to the high conservation of their promoter regions and transcription factor binding sites. However, in this study validating microRNA-based test for radiation detection using actual samples , we demonstrate that while most of the predictions grounded in animal models held true, solely through the analysis of human data were we able to develop a model that reached clinically-useful performance. And most importantly there are key differences in humans suggesting that for clinical application the primary source of data has to be human. For example, a key miRNA for radiation detection noted in macaques – miR-133 – was absent in human patient sera. The miR-30 family, important for dose separation in mice was redundant in the human test. The results from animal studies of miR-150-5p are not directly translatable for the use in humans. In animals, particularly isogenic mice, miR-150-5p kinetics enable perfect separation of the irradiated from non-irradiated samples, even after low dose exposure. The dose response in humans, that have different genetic and clinical background, is much less appreciable and therefore a simple, single- or two-miRNA-based test is insufficient. To overcome this, we employed artificial neural networks reliant on the expression of 8 miRNAs and 2 normalizers, which assure robustness to differences in sample material content. Therefore, we are bringing significantly new knowledge to the field, and providing a template for how miRNA signatures derived from animal models need robust validation in human samples before we even conceive a human application. The analysis of miRNAs purified from exosomes constitutes an exploratory component of our work and is not part of the proposed diagnostic procedure for triage and clinical decision making. We introduced necessary changes to make the division between the main and exploratory parts of our work more evident (lines 116-127).

Major comments:

1. Longitudinal evaluation of specimens from human patients who received TBI is a plus. However, baseline readings in specimens collected from leukemia patients need to be compared with that in healthy humans. Why several specimens were excluded from analysis?

Since the irradiation of healthy humans would not be ethically acceptable, we cross-referenced the results from patients with leukemia with our earlier results of radiation-responsive miRNAs in healthy mice and non-human primates as a surrogate of healthy humans undergoing TBI. As outlined in the “Preprocessing of profiling data” section of Materials and Methods, we implemented quality control based on the number of detected miRNAs per sample. For the miRNA-seq based experiment, samples with less than 350 miRNAs with non-zero reads detected (4A and 7A in Figure 1 – supplementary figure 1) and respective paired samples were removed from the analysis. Additionally, sample DFCI.13A was an outlier in hierarchical clustering and in Principal Component Analysis (Figure 1 – supplementary figure 2) and therefore this sample, together with paired samples from other timepoints, were excluded from the analysis. We incorporated this information in the main part of the manuscript (lines 146-148).

1. Dose response noted is moderate. Biodosimetry refers retrospective evaluation of absorbed dose and the analysis should include validation using specimens of unknown exposure.

As outlined above, the moderate dose responsiveness of miRNAs used in our proposed signature is the primary reason why we believe that a simple diagnostic procedure based on a single miRNA, e.g. miR-150-5p, will not be feasible for use in humans. The final model was evaluated on an independent group of 12 patients with samples drawn under the same protocol (for which exposure and dose was unknown, to validate the model diagnostic accuracy).

1. Authors says that 1 Gy exposure in humans can cause ARS (paragraph 1, introduction). However their approach do not resolve dose under 4 Gy (around the LD50 value in humans).

The TBI protocol does not allow for irradiation with doses lower than 2Gy in a single fraction, which was the reason behind the definition of low-dose exposure group (2 or 4Gy) in our study. However, localized irradiation with higher doses provokes response reflected by changes in miRNA levels in serum (Malachowska et al. Int. J Radiation Oncol Biol Phys), suggesting that the irradiation signature are likely to hold true and identify individuals exposed to smaller doses.

Reviewer #2 (Public Review):

The study first compared the profiles of serum miRNA in patients before and after irradiation treatment. Then they selected 8 miRNA markers that showed significant changes in levels for further analysis. Then, they showed that the analysis of these markers by real-time PCR can differentiate the pre- and post-irradiation samples in 12 additional patients. The objective of the study is unclear.

We rephrased the appropriate sections of the manuscript accordingly to elucidate the objective of the study (lines 105-106 and 131-132).

The study only demonstrates that the 8 miRNA markers are useful to differentiate serum samples collected before and after irradiation. This information is not useful as the blood picture would be more accurate and cheap to accomplish this task.

The currently used diagnostic screening tests for radiation exposure, including time to onset of radiation sickness, kinetics of lymphocyte depletion and chromosomal abnormalities analysis, are time-consuming and do not allow definite conclusions, as outlined by the lack of FDA-approved biodosimeter. The nadirs of peripheral blood cell counts may reflect high dose exposure but do not allow for prediction of the eventual outcome. Moreover, as evidenced in our prior experimental studies, the dynamics of the blood cell counts are significantly slower than those of circulating miRNAs. For example, the differences in outcome, that is probability of survival of an animal after acute radiation exposure, is not evident by any blood counts or other measures for weeks after radiation, and is predicted by a blood based-microRNA signature with ~90% accuracy assessed 24 hours after radiation exposure (Acharya et al, Science Translational Medicine, 2015). Therefore, although we acknowledge that a blood cell count would be cheaper, we respectfully disagree that it would be more accurate in rapidly providing the necessary information to implement countermeasures safeguarding from the absorbed radiation dose. Furthermore, qPCR-based assays are also inexpensive and increasingly available, owing to the COVID-19 pandemic and the great need to expand PCR-based testing capabilities that it gave rise to. We acknowledge that this information was not presented in sufficient detail and we expanded relevant sections of the manuscript (lines 64-76, 401-402).

The authors also propose that these markers are useful for the identification of subjects exposed to irradiation. As this study has not addressed the specificity of these miRNA markers to irradiation, the claim of having a signature for radiation exposure is not justified.

We had shown in previous, experimental exposure studies (“Serum microRNAs are early indicators of survival after radiation-induced hematopoietic injury”, Science Translational Medicine, 2015 and “Evolutionarily conserved serum microRNAs predict radiation-induced fatality in nonhuman primates”, Science Translational Medicine, 2017), performed using animal models that miRNAs with radiation-dependent alterations of expression show association with bone marrow depletion, correlate with survival in amifostine rescue experiment, and that miRNA expression changes are supressed by the use of radiation-mitigating agents like gamma-3-tocotrienol. These arguments act in favour of specificity towards irradiation as the inciting stimulus of the expression patterns. The cross-referencing of results from animal studies and from our miRNA-seq experiment on human samples was aimed to account for this issue, as similar experiments on healthy humans would not be ethical, and to identify high-confidence miRNAs from which a signature could be built. We now added these explanations (lines 112-115, 164-167, 344-350).

Although patients with irrevocable damage of bone marrow due to other factors would be an interesting comparative group, we struggle to find an ethically acceptable scenario that would match the TBI in terms of the timeline and repeatability of the bone marrow depletion. A feasible alternative may be high dose chemotherapy conducted in preparation for bone marrow transplant, but the dynamics of that procedure are vastly different making the group more adequate for analyses of bone marrow regeneration rather than a control for TBI-initiated damage.

The key new experiments in this study are the profiling of the serum miRNA in the patients undergoing total body irradiation. The results on mouse model and macaques have been published previously. The consistency of the changes of the miRNA markers is not surprising.

The consistency of the radiation-inducible miRNAs between mice, non-human primates and humans was expected, given the high conservation of their promoter regions and transcription factor binding sites, as we showed previously (Fendler et al., 2017). This step was important to assure that the miRNA level changes observed in humans result from radiation exposure, as this could not be determined directly, as mentioned in the response to previous remark. However, the creation of the clinically-applicable test would not be possible without a true study in humans presented in the manuscript. Notably, miRNAs crucial for the radiation exposure models in our macaque model (miR-133b) was surprisingly absent in human sera, and the miR-30 family, important for dose separation in mice was redundant in the human test. This serves as a cautionary tale for “translational” studies without true validation in humans and underlines the importance of our findings in terms of the first human-specific and adequately validated diagnostic and prognostic test for radiation exposure.

Reviewer #3 (Public Review):

1. Appropriate bioinformatics discussions and functional pathway analysis are necessary for the key differentially expressed miRNAs that have been screened out. It is boring to only discuss the differences of miRNA data.

We appreciate the suggestion to back the results of differential miRNA expression with a more in-depth bioinformatic discussion. We discussed the results of functional enrichment analysis, presented in Fig. 3C, in more detail, and appended the bioinformatic analysis (lines 218-222, 360-364, 546-549). A graph of miRNA-gene interactions, created using miRTargetLink 2.0 for miRNAs differentially expressed in exosomes after high dose irradiation has been added as figure supplement 1 to Figure 3.

1. In page 5, "We used logistic regression to create such a model in the low-dose setting (N=22 sample pairs). The resulting classifier was based on the expression of miR-150-5p, miR-126-5p and miR-375" , Why the three miRNAs in the low-dose radiation group were selected for modeling instead of the seven overlapping miRNAs in the high and low dose radiation group to classificate the irradiated- and non-irradiated samples ? Please explain in detail.

The expression of miR-150-5p, miR-126-6p and miR-375 was used in our previous animal studies to determine radiation exposure and we used similar approach at this stage of the project to evaluate whether their expression measured using RNA sequencing in human sera can reliably distinguish between the irradiated and non-irradiated samples. We acknowledge that it is not clearly stated. The primary purpose of this analysis was to visually present similarities in radiation-inducible miRNA expression changes across species, and the logistic regression model in question was not used any further. Following the Reviewer suggestion, we built a model using the seven miRNAs overlapping in the high and low dose radiation comparisons to classify the irradiated- and non-irradiated samples, obtaining AUC of 0.95 (95%CI: 0.89-1.0); however, we believe adding this information to the main part of the manuscript is not necessary.

1. In page 5, "Therefore, the expression of miR-126-5p, miR-150-5p and miR-375 enabled efficient classification of the irradiated- and non-irradiated samples in both settings (Fig. S6C)";

In page 6, "Interestingly, a set of 3 miRNAs quantified by qPCR in all of our previous experiments clearly visually distinguished irradiated from non-irradiated samples in the human analysis (Fig. 5A)",

Which three of miRNAs，miR-150-5p，miR-375，miR-126-5p mentioned before or miR-150-5p，miR-375，miR-215-5p？Please clarify clearly.

Thank you for the suggestion. We rephrased this fragment (lines 289-290).

1. In page 4, "Since miRNA-containing exosomes.......high dose irradiation", Do you think that the differently expression of serum miRNAs partly results from exosomes? Low dose irradiation is also able to change exosomal miRNA profile，why only high dose irradiation is taken into account in paper while low dose irradiation is not？

We believe that serum miRNA expression results in part from exosomes and, as an exploratory component of our work, aimed to verify whether the magnitude of changes in exosomal miRNA expression exceeded that in serum, improving the potential biomarker specificity to the extent that would justify the development of an arguably more complex and labour-intensive test utilizing exosome isolation. The sequencing of exosomal miRNA content was therefore performed as an exploratory analysis only after high radiation exposure. However, the lower amount of exosomal miRNA than obtained through the total miRNA extraction protocol offsets any benefit stemming from higher cellular specificity of the former, and, based on the results that were comparable with those obtained from sera, decided to not explore this concept further. We added this explanation to our manuscript as this issue was not clarified previously (lines 116-127 and 339-343).

1. Are there any miRNAs that can clearly distinguish between high and low dose groups? If so, please clarify them in text.

We now clarified this issue in discussion (lines 415-417).

1. In page 7,"Importantly, similarities were observed in the level of both individual miRNAs and miRNA families", What part of result Comes to this conclusion？Please explain clearly.

When describing similarities between human and animal studies, we refer to our previous work describing radiation-responsive miRNAs in mice and non-human primates. These similarities (and differences) are described in detail in Table 1. We added relevant references to Table 1 and to the cited sentence (line 352).

1. In page 7, "We found that the most common putative tissue sources for differentially expressed miRNAs were hematopoietic and endothelial cells", Which part of result shows this sentence? Please point it out.

This statement is not validated in our work explicitly but based on the results from references: Ludwig et al., 2016, de Rie et al., 2017 and Landgraf et al., 2007. Since Ludwig et al., de Rie et al. and Landgraf et al. generated excellent data of miRNA expression across human and mouse tissues and cell types that showed overlapping results for the miRNAs of interest, as detailed in Table 1, we did not perform additional confirmatory experiments.

1. Were the patients suffering from cancer or other diseases? How to ensure that the differential expression of miRNA was caused by radiation exposure rather than their own disease? Please explain.

As described above, initial experimental studies performed in animal models (mouse and macaque) in preparation for this study showed the specificity of miRNA (including ones in the signature) towards radiation exposure in different animal models. This was evidenced on multiple layers of validation and rescue experiments. Admittedly, a demonstration that additional diseases with a phenotype similarity with ARS affect study performance is an interesting concept, but it would be extremely unlikely to impair the performance of the test in an individual after radiation exposure. Namely, even if the examined patient has a hematologic malignancy or myelofibrosis potentially affecting the performance of the test, identification of such individuals as potentially irradiated would lead to them being followed-up adequately. Failure of the test to detect radiation exposure will likely not be severe risk, since such individuals will already be severely ill and under proper care with regular monitoring of bone marrow function. We are aware that some unforeseen and not discussed clinical factors may affect some facets of the test but the built-in robustness derived from having multiple miRNAs mitigates the risk of non-specificity.

What is interesting is the reasoning we often come up with viewing ourselves is often negative as we seem to like to often question how others think that you look good while you may end up looking at yourself negatively.

• I THINK SO
• DIFFERENT zotero items for
• arxiv
• • different item for each version!!!
• doi publisher
• Each item with its PDF!!!
• DIFFERENT Citations!!!

System design details

Author Response

Reviewer #1 (Public Review):

In the present work Valperga and de Bono performed a forward genetic screen to identify candidate genes that would fulfill two criteria when mutant: 1) enhance an escape response to high ambient oxygen but 2) without modifications in the respective oxygen sensing neurons. They found that qui-1 mutants meet these criteria. qui-1 is known to act in the nociceptive neurons ASH and ADL (among others). The authors show that in qui-1 mutants ADL neurons are defective in normal chemo-sensation and upregulate neuropeptide secretion. This is associated with increased gene expression of neurosecretion components in ADL, among them two GPCR receptors (npr-22 and tkr-1); mutants in these receptors partially phenocopy the neurosecretion phenotype. The authors suggest an intriguing model in which ADL, upon loss of its normal sensory properties, relays peptidergic input from oxygen sensory circuits to peptidergic output towards yet unidentified downstream circuitry. This novel mechanism of sensory cross modality expands on on previous work on cross modality in C. elegans, where until now only one example been demonstrated, and where a different mechanisms than in the present study was described (Rabinowitch 2016). These findings could serve as generalizable models for other systems where cross-modal plasticity has been observed. Although many conclusions in this work are substantiated by cell specific rescue of qui-1 in ADL others are made based on correlated observations only. The study therefore would benefit from additional experiments that demonstrate a causal link between elevated neurosecretion in ADL and the associated changes in behavior. This could be achieved by ADL cell ablation experiments and specific interference with ADL neurosecretion.

We thank the reviewer for this analysis of our work. We sought to address points raised in this summary using her/his suggestions.

Reviewer #2 (Public Review):

Loss of one sensory modality is often compensated with an increase in another sensory modality. Valperga and de Bono identify a possibly conserved mechanism that appears to heighten the worm's sensitivity to O2 while dampening other sensory responses. The mechanism that they discover suggests that increased neuropeptide secretion could be responsible for the overcompensation for a loss of a sense. The combined data based on forward genetic screening and behavioral analysis, imaging and genomics are convincing and interesting.

1. I very much enjoyed reading a manuscript that uses 'good old' forward genetics to make an interesting discovery!

2. The paper is well written and very easy to follow. The data quality and their display in the figures are very convincing, too.

3. The proposed mechanism of using enhanced neuropeptide secretions for compensating the loss of one sensory modality with an increase of function of another is novel and could indeed be conserved.

We are grateful to the reviewer for the encouraging review of our work.

Reviewer #3 (Public Review):

The work by Valperga and de Bono aims to uncover molecular components of cross-modal plasticity, a system-wide form of neuronal remodeling that responds to sensory loss by altering the performance of remaining sensory modalities. The study focuses on the interplay between oxygen-sensing and pheromone detection in C. elegans. The data presented are mostly convincing and revealing. However, the message and the overall context within which the findings are framed are problematic.

The authors rightly assert that the molecular processes underlying cross-modal plasticity are not fully understood. However, they emphasize that the important challenge is to reveal genetic lesions that result in sensory loss and drive cross-modal plasticity. I find this to be over-specific and imprecise. There are many possible causes for sensory loss, some are genetic, some are non-genetic (e.g., certain diseases and injuries). In any case, the causes for sensory loss are usually independent of the processes that give rise to cross-modal plasticity. The genetics behind cross-modal plasticity enables the response to sensory loss, it does not cause the sensory loss. Genetic lesions to genes involved in cross-modal plasticity disrupt cross-modal plasticity, they don't induce it. Curiously, the authors sought to find single genes whose removal is simultaneously associated with both the loss of a sensory modality and the enhancement of another. This was done using a forward genetic screen for C. elegans mutants displaying enhanced oxygen sensation.

We thank our reviewer for her/his thoughtful comments. We have revised our introduction to take account of her/his comments, and to remove the misleading statements s/he highlights.

The analysis was further complicated by the fact that the screen was performed on strains whose oxygen sensitivity is already modified due to dysregulated activity in the RMG hub-and-spoke neural circuit, which integrates diverse sensory signals to control locomotion. Mutagenesis was performed on either the N2 strain, exhibiting RMG suppression, and thus decreased oxygen sensitivity, or flp-21 mutants, displaying excessive RMG activation, and increased oxygen sensitivity.

We chose two genetic backgrounds for our mutant screens that attenuate the output of the RMG hub interneurons. Both backgrounds include a gain-of-function allele of the neuropeptide receptor NPR-1 that inhibits RMG output. The NPR-1 receptor has multiple peptide ligands, so in the second screen we reduced NPR-1 inhibitory signalling by deleting one these ligands, FLP-21. Neither of the two strains we used, N2 or flp-21, show appreciable O2 responses on food, and do not aggregate or accumulate on thicker parts of the food lawn, facilitating our screen (See Figure 1B).

The screen yielded a gene, qui-1, whose dysfunction led to enhanced oxygen sensing (it is unclear if this is in the N2 or flp-21 background). The authors found that increased neuropeptide release from the pheromone-sensing neuron ADL underlies the increase in oxygen sensitivity. Furthermore, the qui-1 mutation was shown to diminish ADL pheromone responses. Therefore, a very particular genetic coupling between loss of pheromone sensation and enhanced oxygen sensitivity was revealed.

We have indicated the parental origin of the qui-1 mutant in the revised manuscript.

To generalize this finding, several additional mutant genes (not from the screen) were examined, including genes from the BBS family as well as wrt-6 and fig-1. They too displayed enhanced oxygen sensing linked to increased ADL neuropeptide secretion. However, their effects on ADL pheromone sensation were not reported. The main conclusion I draw from these findings is that the ADL neurons are able to modulate oxygen sensitivity by relaying information about oxygen levels from the RMG circuit to locomotor circuits via neuropeptide secretion. It is not at all clear that loss of pheromone sensation in the qui-1 case is the cause for increased neuropeptide release, or whether it is just one out of the many outcomes of mutating this gene. A much cleaner and more revealing experiment could have been, for example, to examine worms lacking the functional pheromone receptor OCR-2 in ADL. In fact, unlike qui-1 mutants who showed diminished oxygen responses in ADL, previous work from the de Bono group (Fenk and de Bono 2017) demonstrated that ADL O2 response are normal in ocr-2 mutants, indicating a profound difference between loss of pheromone sensitivity due to receptor dysfunction (ocr-2) and the unknown and broad effects of qui-1.

We thanks the reviewer for this important suggestion. We have sought to test our model with a functional experiment that selectively disrupts sensory input into the ADL neurons. To achieve this, we decided to knock down a protein required for intraflagellar transport, OSM-6, rather than the OCR-2 TRP channel subunit. OCR-2 mediates not only pheromone responses in ADL, but also O2-escape behavior (de Bono et al., 2002). This may reflect a broader role for OCR-2 in ADL than sensory transduction. Disrupting OSM-6 truncates sensory cilia and severely compromises many chemosensory responses, but only weakly reduces aggregation and O2 responses.

To target OSM-6 degradation specifically to the ADL neurons we knocked in DNA encoding an Auxin Inducible Degron (AID) into the osm-6 locus, and expressed TIR1 in ADL to achieve cell-specificity. TIR1 is required for AID. We have added the new data to Figure 4F–G and Figure 4 – figure supplement 2. We show that expressing TIR1 in ADL disrupts OSM-6::AID function both in the presence and absence of Auxin. This agrees with recent work that tested the efficiency and specificity of the AID system (Hills-Muckey et al., 2021). A partial OSM-6::AID reduction in ADL recapitulates many of the phenotypes of qui-1 mutants, including increased neurosecretion from ADL, heightened ADL responses to O2 inputs and a small but significant enhancement of the O2-escape response. We think these new data support our interpretation that a change in ADL’s sensory properties leads to heightened response of ADL neurons to O2 inputs, a phenotype observed in qui-1 and multiple other sensory defective mutants and a hallmark of cross-modal plasticity. However, the effects of knocking down osm-6 on ADL function also appear to be complex, as the stronger osm-6 knockdown achieved by adding auxin to the osm-6::AID knockin animals expressing TIR1 in ADL, unexpectedly gives weaker phenotypes than when auxin is absent.

In fact, it would be interesting if the authors could explain or speculate how qui-1 eliminates ADL O2 responses, and how neuropeptide signaling from the RMG circuit via the NPR-22 neuropeptide receptor bypasses this lack of response and drives enhanced neuropeptide secretion in ADL, as they report.

We can only speculate why O2-evoked responses in ADL disappear in qui-1 mutants. One possibility is that ADL becomes less excitable due to the reconfigured gene expression associated with loss of qui-1 in ADL. This model would predict that selectively knocking down qui-1 in ADL would confer the same Ca2+ response phenotype. Blocking ADL neurosecretion with TeTx in qui-1 mutants would test if the increased ADL neurosecretion we describe feeds back to reduce the O2-evoked Ca2+ response in ADL. An alternative hypothesis is that the effect of disrupting qui-1 is non-cell-autonomous, altering excitatory or inhibitory input to ADL from other qui-1 expressing neurons. We have not tested if neurosecretion from other qui-1-expressing neurons is altered in qui-1 mutants.

Strikingly, while disrupting qui-1 leads to loss of a measurable O2-evoked Ca2+ response in ADL, these neurons display elevated O2-evoked neurosecretion in qui-1 mutants. This implies that some O2-evoked Ca2+ responses are retained in ADL’s axons in qui-1 mutants. It also suggests that other second messengers upregulate neurosecretion. Elevating cAMP, for example, can promote dense-core vesicle release more efficiently than increasing Ca2+ levels (Costa et al., 2017). Altered G-protein coupled receptor signalling could lead to elevated cAMP levels and increased neurosecretion in qui-1 mutants. It is worth noting that in N2 controls, ADL does not display O2-evoked neurosecretion despite showing measurable Ca2+ responses.

The work includes a transcriptomic analysis comparing ADL-specific gene expression between wild type and the qui-1 mutant. Unlike other experiments in the study, in which the specific effects of mutations were confirmed through rescue experiments and the use of additional alleles, thus eliminating potential confounds with background mutations, the transcriptomic experiment did not apply such controls. Therefore, it is hard to conclude whether the reported changes in transcription are due solely to the qui-1 mutation or to other unrelated genetic modifications in the mutant strain.

We worried about unspecific effects of background mutations both on the ADL transcriptome and on other qui-1 related phenotypes. We regret we did not explicitly address this point in our initial submission. To remove background mutations, mutants isolated in our screen, including qui-1, were backcrossed with the N2 laboratory strain a minimum of four times. These qui-1 animals were further crossed into a 5 times outcrossed line that expresses the fluorescent protein mKate specifically in ADL, to generate the strains from which we sorted ADL neurons by FACS. Mutant and transgenic strains were outcrossed using the N2 laboratory strain. We explain this in the Methods section of the revised manuscript.

The extensive outcrossing make us confident that the large majority of differentially regulated genes between wild type and qui-1 samples in ADL are due to the absence of qui-1. Supporting this, both mutations in neuropeptide receptors identified by our profiling, npr-22 and tkr-1, suppress ADL’s elevated neurosecretion. Nevertheless, we have added a note to explicitly bring up the concern raised by our reviewers, that some transcriptional differences could be the result of background mutations.

Overall, except for where mentioned, the data presented are solid and consistent. However, the conclusion that the study reveals a molecular pathway for cross-modal plasticity is less convincing. The chain of events does not include some form of sensory loss, leading to subsequent, independent neural plasticity, as expected for cross-modal plasticity. Rather, a very broad genetic switch is described that can simultaneously change receptor abundance and neuropeptide release. Thus, an equally interesting and more coherent framing of the data could be that the study uncovered a genetic regulator, yet to be fully characterized, of oxygen-dependent behavior in a non-oxygen sensing neuron, adding to previous literature on neural circuit cross-talk.

We are grateful to the reviewer for her/his thorough and critical analysis of our work, which has prompted us to perform additional experiments and helped us revise our manuscript. These additional data clarify our final interpretation of the data regarding cross-modal plasticity.

SciScore for 10.1101/2021.12.23.21268325: (What is this?)

Please note, not all rigor criteria are appropriate for all manuscripts.

Table 1: Rigor

Table 2: Resources

Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

Limitations: Despite best efforts, our recruitment strategy may have missed relevant voices, including those who are not computer literate. Our data must be interpreted with this in mind. Conclusions: In conclusion, the majority of young people described and concluded that for themselves, the benefits of vaccination did not outweigh the perceived risks to themselves. They did not consider themselves to be at risk of becoming seriously ill from COVID-19 and did not think that the vaccination was capable of protecting those around them. This, combined with concerns about the safety of the vaccine, resulted in reluctance to be vaccinated at present. Perceptions of risks and benefits were influenced by participants’ age and health status, trust in government, understanding of science, and pre-existing ideas and expectations. Participants were unsure who they could and could not trust and were resistant to attempts that were viewed as coercive. In order to promote uptake, public health campaigns should focus on the provision of information from trusted sources that carefully explains the benefits of vaccination and addresses safety concerns more effectively. To overcome inertia in people with low levels of motivation to be vaccinated appointments must be easily accessible (both in terms of location and timing). Research now needs to identify how to communicate risks (from COVID-19 and vaccination) and benefits (for the individual and population) so that people can make informed pe...

Results from TrialIdentifier: No clinical trial numbers were referenced.

Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

Results from JetFighter: We did not find any issues relating to colormaps.

• Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
• Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
• No protocol registration statement was detected.

Results from scite Reference Check: We found no unreliable references.

About SciScore

SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

The final piece of writing is a critical reflection about your work that uses the ideas and texts in the course to support, and highlight, your ideas.

This piece will also be published in SCALAR for future use; that is, the final piece should say something about how you've encountered the material in the course so as to instruct future users/readers. Your writing—your readings of the texts; your telling of your experience with ideas—will be great guides for students.

Think broadly, first. Ruminate on the following and record it for yourselves somewhere (I use a black notebook for this and write longhand; no technology, other than a Sharpie, for thinking—that works best for me):

Explain and describe what the texts help you see and understand, even if this means further confusion, or the creation of more questions that are yet unanswerable for you. Here, begin to not rely on invisibility and slow violence; think beyond these very large themes.

How have these texts helped you delve deeper into the questions of environmental justice—and expanding the meaning, on confusing it, making it, perhaps, more nuanced?

How does environmental justice affect your view of what you need to examine about your goals going forward?

This preamble, the questions, should be seen as lofty goals to guide your thinking and your writing. More specific "how-to" is below.

The GOAL of this piece is to describe, discuss, and even argue ideas that will flow smoothly into an answer to the following question: Knowing what you know now, how are you going to approach the rest of your life?

This question doesn't have a definitive answer; it's about perspective, point of view, attitude. It's also about responsibility — the ability to respond: where will you find the space(s) necessary to give yourself enough time to respond to what comes your way—unexpectedly? how do you do this? how will your education help, with examples, referring to texts, in this course and others you've encountered, that have affected the way you think? after summarizing the texts in this course, which singular text, which one of these, is something you know you'll take with you, meaning you know that it has affected you and the ideas found in this text are important guides? how does this text help you see yourself better?

I taught an FYS back in the fall of 2015 and the class had a similar assignment. Students asked that I too write the assignment and provide a model. You guys didn't take this course, but I'm sharing with you what I wrote (since published) (Links to an external site.) so that you can see a model for the work I'm asking you to do. Notice how I contextualize the texts, give the reading of each I need for my argument/description, and use this to describe a native characteristic of American culture. I'm not asking that you be as lengthy. I'm not expecting this sort of reading of American culture; these courses are different. I'm basically wanting to know what it is you see now that the course is over, or nearly over. This model (linked) is simply a sketch for you, and an outline that allows you to see a way into the work, and a way through—a way to organize.

I want you to be creative about your approach. You can tell a story and use the texts, for instance. You can use your experiences as a way through this and use the texts. And so on ...

I have created a SCALAR PAGE (Links to an external site.) for each of you.

I want you to consider following these guidelines for writing:

Go back to your mapping exercise: How did your plan turn out? Where are you now? [this is something we will have already spoken about in our f2f meetings, so you want to have notes from that]. This shouldn't be written, When I look at my mapping...or I said in my mapping that ... Rather, it should be something along the lines of, My writing interests in this course suggest (ideas + support from essays) ... or A central focus of my essays (or thinking) has been ... (examples)...or Engaging the texts in this course, I started to think about ... (examples) ... I thought ... and now I'm thinking that ... (examples)  — This section should be short (no more than a tight paragraph) and strategically placed.
As preparation for writing, without looking at the texts, just referring to their titles for inspiration, see what you recall: write out a paragraph or so about each text encountered in the course—this is for your own use and a way to organize before writing; this is done to determine what you recall, which is important and what you should focus on because that's instinct talking; eventually open the texts to make sure you have examples for citing [any material from outside the syllabus you wish to cite is fine, too, especially since I've sent you a lot of reading from the popular media].
Find a central idea or theme you want to explore. Set it down somewhere so you can see it and read it back to yourself. Yes, there will be the tendency to speak about invisibility and slow violence, I get that; however, these should be ideas that help illustrate a central idea or theme that's your very own and based on what your reading of the courses' texts tells you about the nature of society, as it is now, the challenges we face, and, definitely, where you're situated, in the texts and the challenges we face. Thus, invisibility and slow violence should not be the central ideas/themes of your work, rather instruments/conditions/truths you found along the way and you're using these to pry open a deeper, richer understanding of your relationship to these ideas and environmental justice.
Write a draft and start sharing it with your group. Likewise, you want to make sure that you and I sit with your piece, letting me comment on it before it's due  (even numerous times) so that we have the piece you want. You definitely want to conference with me about your piece so I can help you get as deep as possible into the subject—in other words: making sure each of you writes something you're really moved by and proud of.
Since this is on SCALAR, make sure you have relevant images, links, where appropriate and necessary, and any other media (clips, sound, etc), you may wish to insert creatively to lift your piece.

Author Response

Reviewer #1 (Public Review):

There are very few studies on the spatial integration of color signals of V1 receptive fields, which is a striking gap in knowledge given the importance of color to primate vision and the powerfulness that spatial analysis of luminance contrast integration has proven for understanding how V1 works. This paper helps fill this major gap in knowledge. The main take home is that double opponent cells and simple cells are more likely to be linear in how they integrate signals across their receptive fields than a sample of non-double-opponent/non-simple cells. This conclusion is consistent with the limited data presently in the literature, and I wonder if further analysis of the rich dataset could uncover some deeper insights.

We thank the reviewer for highlighting the gap in knowledge that our study helps to fill and for the excellent suggestions for ways to improve the manuscript. In response to both reviewers, we have conducted new analyses that uncover deeper insights into signal integration in V1. These new analyses have been incorporated into the revised manuscript.

Reviewer #2 (Public Review):

De and Horwitz deploy a focussed technique for testing the linearity of spatial summation for V1 neurons with spatial opponency, with the emphasis being on the properties of cells that encode chromatic information in a spatially opponent manner - so called double opponent cells. The technique isolates non-linearities of summation from non-linearities that occur after summation, by using an adaptive procedure to home in on stimulus contrasts in different color directions that produce a pre-defined criterion response. The authors conclude that many (but not all) double opponent cells embody linear spatial summation, and discuss implications for our understanding of the cortical circuitry that mediates color vision. The data appear carefully collected and generally well-analyzed. There are some points, elaborated in broad strokes below, where I think the paper would benefit from further elaboration of the data and its implications, and the paper would also benefit from some revisions to improve clarity.

How are results affected by the cell classification criteria? The authors apply criteria to sort cells into four classes: simple, double opponent, NSNDO, and those not studied further. Response properties are then studied as a function of cell class. Criteria for classification include presence/absence of spatial opponency revealed by the pixel white noise measurements and the adequacy of a linear STA to describe the hyperpixel white noise data. I think more work is needed to clarify for the reader the extent to which these criteria, in and of themselves, affect the results for each class studied. In particular, if a linear STA describes the hyperpixel white noise data, shouldn't we then expect to find linear summation in the spatial receptive field in that same hyperpixel white noise data? I understand, as the authors point out, that the Phase 3 measurements could reveal failures of spatial summation not seen in the hyperpixel white noise data. But I'm a bit perplexed by the outliers in the NLI indices in Figure 3D. What properties of these cells allow a linear 6D STA to handle the hyperpixel white noise data well, but cause them to summate over space non-linearly for that same hyperpixel white noise data? In terms of the new information provided by the Phase 3 measurements, I wasn't able to get a sense of how much harder these stimuli were driving the cells than the Phase 2 measurements. It seemed like this was the intent of Figure 2 - Figure Supplement 1 and Figure 3 - Figure Supplment 1, but those two figures in the end didn't provide this information in a manner I could digest. Absent this, it was hard to tell how much more we are learning from the Phase 3 data. Could the higher NLI's here than in Phase 2 be a consequence of some stimuli but not others driving the neuron into saturation? And although the authors write on page 15 "Nevertheless, we found that nonlinearities detected in Phase 2 of our experiment were a good indicator of nonlinearity over the greater stimulus duration and range of contrasts in Phase 3, principally for the NSNDO cells (Figure 3E)", those correlations look very weak to me. I was left hoping for a better understanding the commonalities and differences in the data between Phases 2 and 3. I'm also not sure of the reliability of the measured NLI's for each cell with each method. Can anything more be provided about that? I note here that I did study the section of the discussion that nominally addresses some if these issues, and that my comments above remain after that study.

The Reviewer brings up several important points that are addressed individually below.

The revised manuscript is more explicit about the role of the cell classification criteria on the results. Particular emphasis is placed on the role of the spike-triggered covariance criterion in enriching the pools of simple cells and DO cells with neurons that are approximately linear.

We agree with the Reviewer that, if a linear STA describes the hyperpixel white noise data well, we expect to find linear summation in the spatial receptive field in that same hyperpixel white noise data analyzed in other ways. A critical question is “does the STA describe the white noise data well?”. We address this question in two ways in this report: with an analysis of (the statistical significance of) the first principal component of the hyperpixel spike-triggering stimuli (PC1) and with a comparison of GLM and GQM fits to the hyperpixel white noise data (the white noise NLI). These analyses are related but are sensitive to different types of departure from linearity.

Consider a neuron whose output is the product of two half-wave rectified linear subunits (see Figure 2 – Figure Supplement 5). Such a neuron would have a large white noise NLI due to the non-linear interaction between the subfields, but it would lack a significant PC1, because the nonlinearity tightens the distribution of excitatory stimuli, and the PC1 is the dimension along which the stimulus distribution is widest. In principle, such a nonlinearity would manifest in the smallest principal component, but in practice, small PCs often resemble the STA, which complicates their interpretation.

Conversely, a neuron can have a significant PC1 but a small NLI. For example, consider a neuron that has a half-wave rectified response to modulations of one color channel but a full-wave rectified response to another. Such a neuron will have a significant PC1 due to the full-wave rectification, but an NLI near zero, because this nonlinearity is hidden once the stimuli are projected onto the STA (recall that the white noise NLI is computed from a pair of 1-D projections not the original 6-D representation). Code simulating these hypothetical neurons (used to produce Figure 2 – Figure Supplement 5) is available at GitHub (https://github.com/horwitzlab/Chromatic_spatial_contrast).

The original submission lacked documentation of the difference in firing rates produced during Phases 2 and 3. We have added a new supplementary figure that quantifies this difference (see Figure 2 – Figure Supplement 2). Figure 2 – Figure Supplement 1 illustrates the range of inputs provided in Phases 2 & 3. This has been clarified in the revised text.

Please note that the data shown in Figure 3D are isoresponse NLIs (that is, NLIs computed from responses recorded during Phase 3 of the experiment) not white noise NLIs (NLIs computed from the hyperpixel white noise shown during Phase 2 of the experiment). This has been clarified in the revised text.

We agree that the correlation between the white noise NLI and isoresponse NLI measurements is weak. A full treatment of the differences in neural responses to the stimuli presented in Phase 2 & 3 is beyond the scope of this study. Nevertheless, we can think of several reasons that some neurons may have appeared more nonlinear in Phase 3 than they did in Phase 2. The first is, as suggested above, Phase 3 stimuli had higher contrast than Phase 2 stimuli, and are more likely to have engaged nonlinear gain control mechanisms upstream or within V1. Second, the linear and nonlinear models in Phase 2 had 3 and 6 parameters, respectively, but 2 and 5 in Phase 3, and this may affect the ratio of prediction errors. Third, nonstationary responses are expected to affect isoresponse NLIs more severely than white noise NLIs, because of the sequential way that isoresponse points were measured in Phase 3.

Assessing the reliability of NLIs within cells is challenging because of the crossvalidation that is built into the definition. To address this comment, we used a jackknife procedure that quantifies the spread of NLIs computed from each of the data partitions used in the cross-validation.

Implications of the results for models. As the authors summarize in their introduction, the motivation for testing the linearity of spatial summation is that the results can guide how we formulate response models for V1 chromatically sensitive cells. More discussion of this would be helpful. As an example, could cells with the nonlinear spatial filtering as shown in Figure 1C be classified as DO, making them relevant to the focussed tests applied in this paper? Or are they necessarily NSNDO? More generally, can the authors spend a little time discussing what classes of response models they would pursue for DO cells that do/don't show linear spatial summation, and for NSNDO cells that do/don't show linear spatial summation. Such discussion would tie the results of the primary data back to the motivating question in a more satisfactory manner, I think. Such discussion could also be used as a vehicle to discuss what the authors think about the DO cells that fail to show linear spatial summation and the NSNDO cells that do, something I found under-treated in the results. As with the comment above, I did read the sections of the paper that speak to this question, but still find it that it would benefit from going deeper.

Inspired by this comment, we have added a new section to the Results that considers response models for neurons that do not show linear spatial summation. Specifically, we test the model illustrated in Figure 1C and reject it for many neurons. Figure 1C depicts a neuron that integrates inputs linearly within each subfield but nonlinearly across subfields. Within each RF subfield, therefore, this neuron conforms to a linear-nonlinear cascade model. Critically, during Phase 2 of the experiment, the stimulation at one RF subfield can be considered as an additive noise with respect to the signal generated by the other RF subfield. This is because the influences of the two RF subfields combine additively (under the model) and the modulations of the two hyperpixels are independent.

To test this model, we compared GLM and GQM fits as we did in the analysis of the white noise NLI. The regressors in this analysis were the modulations of the three color channels from a single subfield. These GLMs fit the data systematically worse than GQMs as assessed by cross-validated prediction error. This result indicates that the nonlinearity of the NSNDO cells is unlikely to be a result of nonlinear combination of inputs from two linear RF subfields, as postulated by the model in Figure 1C. Instead, for many NSNDO neurons the nonlinearity appears to arise from nonlinear combinations of signals within individual subfields. We mention in the Discussion that linear DO cells may lie on a continuum with some NSNDO cells.

Color properties of subfields. The study measures detailed properties of cells that show at least two distinct subfields in the initial pixel white noise analysis. The paper focuses on whether signals from such subfields are combined linearly before any downstream linearities. However, there is another feature of the data that seems central to understanding these cells, and that is what the chromatic properties of these subfields are, and how strong in the data the constraint that the chromatic properties of the two separate subfields be complementary is. It is stated in passing (page 7) that "the two sides of the hyper pixel STA were complementary or nearly so", but it would be nice to see this treated in more detail and also to understand whether there are differences in the distribution of the chromatic properties of the two sides between the DO and NSNDO cells, and between cells with low and high non-linearity indices.

We have added new section on the chromatic properties of the subfields of the neurons we studied (Figure 2 – Figure Supplement 3).

Author Response

Reviewer #1 (Public Review):

Summary:

In this work, the authors develop a tool for personalising prostate cancer treatment using a Boolean model. The model is extremely complex and describes the regulation of invasion, migration, cell cycle, apoptosis, androgen and growth factors signalling in prostate cancer using 133 nodes (genes and our metrics) and 449 edges (regulation pathways. Using their model, they were able to grade the effect of combined treatments for each of the 488 patients for already-developed drugs and find several genes suitable for intervention in most of the 488 patients. The predications from their model could help develop a patient-tailored treatment that could boost success of pancreatic cancer treatments in clinical practice.

Strengths:

The authors clearly achieved their aims of predicative prostate cancer modelling and have added value to the field of prostate cancer personalisation.

Calibrating and then validating predications of a model, as this work does, is a fundamental part of systems biology and mathematical modelling. By using a cell line to investigate predictions that AKT is the top hit for prostate cancer, validates the utility of their model and also shines a light on how useful models like this can be in oncology. The methodology in this paper provides a guide for future modelling work in this area.

Providing a detailed Supplementary Information and additional links to the code and fundamental modelling platform publications, helps to provide readers with a tool that may be applied in other settings. However, while this is a strength of the publication, the model is extremely complex and relies heavily on readers spending time comprehending pre-published work and doesn't provide a single contained body of work.

The methodology they are presenting could have significant impact on the field of cancer treatment, but would need to be testing clinically to validate that personalising treatment in this manner does improve outcomes.

We thank the reviewer for these comments.

Weaknesses:

While it is a strength of this work that such a detailed, and complex model is developed for prostate cancer, and that the code is provided, the weakness of this work is that the model is not easily accessible, and a lot of the techniques used in model development feel brushed over. The work relies heavily on other works and does not provide detailed descriptions of the underlying algorithm, requiring readers to absorb knowledge from our places. This could be a challenge if an experimentalist wishing to implement this methodology in a different cancer treatment.

We have summarised the main techniques on which this work relies upon in a dedicated section in the Supplementary Material (Appendix file) by describing small introductions to Boolean modelling, MaBoSS stochastic approach to Boolean models, and PROFILE methods.

We have also provided the codes to reproduce the figures and the analyses. We tried to comment on the code files (e.g., Jupyter notebook) as much as possible to facilitate their use in different contexts.

The protein/genes in the model are not presented in a way that it can be easily validated as such, the complexity of such a Boolean model comes into question.

We have listed all the proteins/genes of the model in SuppFile 1 with references for all the interactions of the network.

For transparency, we have also described in the Appendix how we used information from all the different sources to construct the model in the section "Prior knowledge network construction".

How sure are we in the model predications and are there are any potential weaknesses to modelling the network in such an extensive manner? For such a model like this, it is crucial to demonstrate its sensitivity to initial conditions and node additions/removals so some work could be done to demonstrate this so that the readers have an idea of how many over/under predications there might be in the model.

For the sensitivity to initial conditions, we have tested some of them on the generic model in the Jupyter notebook (provided in the supplementary files) but have not done it systematically. The table of all the stable states can be computed exactly as it is done in the notebook (2460 fixpoints are found), and the simulations of MaBoSS clearly show that the proportions of some solutions (probability of model states) change depending on which input is ON. We have tested some conditions: all inputs random, all inputs at 0, growth factors ON (EGF, FGF, Androgen, and Nutrients ON), death signals ON (Carcinogen, Androgen, Acidosis, Hypoxia and TNFalpha ON) leading to very different outputs (Figure 3 for LNCaP and S22 for all 8 prostate cell lines). In fact, the MaBoSS simulation with all inputs random shows the existence of all possible, stable states as it explores the whole state transition graph: for all nodes, 50% of the trajectories will start at 0, and 50% will start at 1. Similarly, we tested the effect of some mutations on the generic model (e.g. mutation of p53, which reduces the probability to reach apoptosis). The aim of these simulations was to test the overall coherence in the model behaviour vs biological evidence as a first validation.

As for automatic removal and addition of new nodes to assess the importance of each of them, we would recommend against it. Indeed, the model was built from the knowledge extracted from the literature, from databases (cf. Omnipath), discussions with experts, and results from data analyses. Removing nodes would mean that some nodes are considered less important, and adding new nodes would mean that some new findings were found that would justify a new addition.

In addition, in this work, we need to balance the robustness of the model with the flexibility of being used to cover the different cell line personalisations. Thus, we do not want a highly robust wild type model that has extremely robust, few stable states but is unable to capture the different cell lines specifics. Nevertheless, we have partially covered this with our "High-Throughput mutant analysis of the LNCaP model" section in Appendix file (Section 6.1), where we study all the perturbations on one node and combinations of two nodes, let them be knock-outs (where a node is forced to be 0 throughout the simulation) or overexpression (forced to be 1). By using this analysis, we wanted to identify the fragility points of the mutants' models, but we did not perform this test to have a thorough robustness analysis. In any case, we found varying effects of these perturbations on the phenotype scores, and double perturbations having a greater effect than single ones.

Finally, we have performed a perturbation on the stability of the logical rules. We have changed one and two logical gates from each logical rule of the LNCaP model and studied the effects on the phenotype scores. In short, we have changed an AND in OR and vice versa in each logical rule (level 1 with 372 simulations) or twice in the same rule (level 2 with 1263 simulations).

Overall, we see that all of the most probable phenotypes are very robust to this kind of perturbation. Even the less stable phenotype, Invasion-Migration-Proliferation, only has ~3% of either level 1 or 2 perturbations that reduce this phenotype's probability to zero (Appendix File, Figure S30). Most of these perturbations were focused on HIF1, AR_ERG and p53 nodes (Appendix File, Figure S31).

We added a sentence in the Methods section to explain this: "In addition, we found that the LNCaP model is very robust against perturbations of its logical rules, by systematically changing an AND for an OR gate or vice versa in all of its logical rules (Appendix File, Section 6.2, Figure S30 and S31)." and added Section 6.2 to the Appendix file titled "Robustness analysis of the logical model".

As they test so many drugs and combination regimes it is also hard to extract information about which key drugs should be repurposed. It could be useful to the readers to have this spotlighted more in the model so that it is easily discernable.

The complete study on the inhibition of all nodes of the LNCaP model can be found in the supplemental information (SuppFile 6 and Appendix file, Section "High-Throughput mutant analysis of the LNCaP model").

Because of the size of the model, we chose to filter the full list of nodes with the list of existing drugs and their targets. Thus, Table 1 gathers the drugs we discuss in this article along with the node that they target. We also studied a selection of combinations of drugs, as depicted in Section "Experimental validation of drugs in LNCaP" of Results. In that section, we focused on the combinations that reduced Proliferation and/or increased Apoptosis. For completeness sake, we provide all the combinations of all the drugs from Table 1 in Appendix File, Figures S34 and S35, and their Bliss score in Appendix File, Figures S36 and S37. Furthermore, the code to reproduce these in our GitHub repository: https://github.com/ArnauMontagud/PROFILE_v2/blob/main/Gradient%20inhibition%20of%20nodes/data_analysis.R

We could have identified the nodes from Table 1 on the figure of the network (main text Figure 1), but we decided against it because the figure is already hard to read, and colours were added to specify the signalling pathways that are included.

Suggestions:

Another way to validate the cohort level predications could have been to examine the efficacy of the predicted personalised protocols, or sensitive parts of the Boolean network, in a new prostate cancer patient cohort. Do we see the same sensitive pathways if we examine a different cohort of prostate cancer patients?

We thank the reviewer for this suggestion. Indeed we are working on using this pipeline in other cancers and in other studies.

One of the topics that we think can facilitate the use of this methodology is on optimising its runtime and portability. Thus, we are currently working on having a containerised, HPC semi-automatic workflow to reduce the time and optimise the efforts to get results using (almost) any published model and (almost) any omics data.

In terms of the reproducibility of the results and as we say in the discussion section of the main text, there is a kind of effect size on this type of study. You may find that for a specific patient, their conclusions are not in line with what is expected, but when you analyse at the level of groups of patients, these outliers dampen off.

Reviewer #2 (Public Review):

Montagud et al. present a very successful experiment - modeling feedback loop: the authors develop a Boolean model of the major signaling pathways deregulated in prostate cancer, use molecular data from patient samples to personalise this model, use drug response of cell lines to validate the model, predict 15 actionable interventions based on the model, and test nine of these interventions, confirming four.

The premise of the work is well-supported by prior work by the team and the wider community. The methods are sound, well integrated and thoroughly documented, with one notable omission. The process through which the logic functions of the nodes were determined/decided is not described. The Appendix file indicates "The model is completed by logical rules (or functions), which assign a target value to each node for each regulator level combination.". The interested reader would want to know what information is used and what considerations are the basis of these assignments, and what would change if an assignment were different.

The manuscript makes a number of testable predictions of actionable single and combinatorial therapeutic interventions for prostate cancer. Equally important, the combination of information and methodologies used in this paper offers a roadmap for future development of predictive and personalised models. Such models are much needed in precision oncology.

We thank the reviewer for these encouraging comments.

Reviewer #3 (Public Review):

This paper tries to establish a model for drug (and combination) selection for individual prostate cancer patient based on a prior signal network knowledge base and genomic/transcriptomic profiling data. This is of great clinical potential. However, whether this approach could be robustly applied in clinic is not validated. Limited validation using cell line is provided. Most tumors have complex structure including tumor cells and surrounding microenvironment. The model is mainly built from onco-signaling pathways. The contribution of microenvironment including immunity is unclear.

The focus of this model is intracellular only. We explored the interplay between signaling pathways that may be linked to tumorigenesis. We only consider the microenvironment effect as indirect and in no way comprehensive. For instance, we have not considered any immune cells or the effect of the metabolism.

Nevertheless, we are building on top of this work a multiscale model where we can include different cell types, such as immune cells, and drug-related pharmacodynamics.

Author Response:

Reviewer #2:

In this study, Russell et al. combined T cell receptor (TCR) repertoire sequencing data with SNP array genotype data to infer genetic polymorphisms which impact upon the process of TCR generation. Using these data, the authors looked for loci with polymorphisms which associate with different V(D)J recombination probabilities, i.e. sites in the genome which impact upon the chances of TCRs with different properties being produced when they change.

Beyond the expected sites in the TCR and MHC loci, the authors observed strong associations with distant sites. One was with DCLRE1C, which encodes Artemis, the endonuclease responsible for cutting the TCR loci during recombination, while the second was DNTT, the site encoding the enzyme Tdt, which is responsible for addition of nucleotides to cut V(D)J during recombination. This is the first time that such SNP associations have been described to my knowledge, and yet make perfect sense: DCLRE1C variations were associated with the amount of trimming V and J genes underwent during recombination, while DNTT polymorphisms associated with the number of inserted nucleotides. The authors also report, after assigning donors an associated ancestry based on clustering of their genotype data, that certain inferred ancestries associate with different TCR repertoire properties. In this analysis 'Asian-associated' TCR repertoires had fewer non-templated nucleotide insertions, along with a corresponding greater incidence of the DNTT polymorphisms associated with differences in insertions, relative to other groups.

Strengths:

This manuscript is exceedingly well written. Both the TCR biology and the statistical considerations of the genetic analyses are extremely complex topics, mired in arcane terminology, which often end up somewhat impenetrable to non-expert readers. However both have been introduced and explained with admirable clarity throughout, including the caveats and implications of analyses that would not be intuitive to many readers not already expert in both fields.

As best I can determine, the analyses themselves are also extremely rigorous, with each step carefully taken and justified in the text, involving numerous corrections at multiple scales (e.g. for TCR productivity, TCR gene usage, specific TRDB2 genotype, population substructure, and more). The major findings have also been validated in a completely separate cohort, using a different analysis pipeline. While the authors point out that such genome-wide association efforts looking at TCR gene expression have been undertaken before, the major innovation presented here lies in applying those data to investigating specific V(D)J recombination probabilities. Thus the findings are novel, and the conclusions well supported by the data.

The data visualisation have all been plotted in a sensible and easily interpretable manner. The majority of data themselves are all already publicly available, having been published in prior studies. The TCRseq data for the validation code has been assigned a BioProject accession, which I presume will go live at the time of publication. The code is also appropriately hosted on Github, and are mostly adequately commented and documented enough so as to be repeatable.

Thank you!

Limitations:

There are very few if any obvious technical limitations or weaknesses that I can see that are not intrinsic to the data themselves. While the authors do mention these limitations, I wonder if they should be devoted some more attention somewhere in the text of the manuscript; relatively few researchers are expert in both TCR biology and the technicalities of genome-wide association studies, so I think more explicit consideration of these issues would be helpful.

We have expanded the section containing limitations of our approach within the discussion section. We hope this addition clarifies the intrinsic limitations of the data used here.

In particular, I think the difficulty of studying these loci with standard techniques could be underlined, along with what implications that might have for this study. The highly repetitive nature of the TCR loci can certainly make any analysis looking at short sequences problematic, which has implications for both the TCRseq and genotyping aspects of this study. Combined with the fact that most studies focus on certain populations, polymorphisms in the TCR loci are very likely being relatively undersampled by the field (a hypothesis supported by the ongoing discovery of novel exonic polymorphisms in TCRseq data itself, e.g. as demonstrated in this pre-print by Omer et al. (https://doi.org/10.1101/2021.05.17.444409). The consequences of SNP polymorphism coverage in SNP arrays has already been considered for IgH (https://doi.org/10.1038/gene.2012.12): while this is an admittedly more polymorphic locus, the underlying causes of these issues are mostly all true of the TCR loci as well. Similarly, while the authors do appropriately point out that issues with V(D)J gene assignment could infer biases it may be worth noting that the TCRseq technology used to produce their main dataset uses relatively short read sequencing, that is unable to distinguish a substantial fraction of even known TCR gene- and allele-level diversity (see Fig. 1C of the Omer et al. pre-print). Thus there may be a whole dimension of TCR polymorphism that is not well captured by either platform.

This is a great suggestion and we have added a section within the discussion to mention these limitations and their implications for both the SNP array and TCR repertoire sequencing data used here.

Overall, I think this is an extremely considered and digestible study, which will be of great interest across and beyond the field. As the wider community comes to grips with how best to incorporate TCR and BCR polymorphisms into their analyses of the adaptive immune loci themselves (and how this might impact upon recombination, expression, and downstream immune functions) this serves as a timely reminder that we should not forget the polymorphisms elsewhere in the genome that might also be relevant.

Thank you!

Reviewer #3:

In this manuscript, Russel et al propose an inference method to link genetic variations with TCR repertoire feature variations, based on observations from previous studies showing similarities at various level of the repertoire in monozygotic twins. To that end, they used a unique publically available dataset, which combines TCRb immunosequencing data as well as whole genome SNPs data. The method is elegant and sheds light on the importance of combining different type of data to better understand the complexity of TCR repertoire generation and selection. However, unfortunately, while their discovery data set provide some associations between SNPs and TCR repertoire features, they were almost unable to recapitulate the results with their validation dataset. The main reasons could be that the donor demographics are highly divergent between the two cohorts (81% Caucasian in the discovery vs. mainly Hispanic in the validation), the immunosequencing data were generated using RNA based method for the validation while the discovery dataset was obtained from gDNA templates and finally the SNPs array were discordant between the two datasets. Nonetheless, the approach and the study deserve attention and might be improved by additional experiments or analyses and by providing additional information.

Thank you for your review. We would like to emphasize that the validation results reported here are as good as one might expect given the small sample size of the validation cohort (94 individuals) and the discordance between the discovery and validation SNP sets. The overlap between the discovery cohort and the validation cohort SNP sets consisted of just two significant SNPs, one within the gene encoding the Artemis protein (DCLRE1C) and the other within the gene encoding the TdT protein (DNTT). This DCLRE1C SNP (rs12768894, c.728A>G) was strongly associated with the extent of V-gene and J-gene trimming in the discovery cohort, and we were able to successfully validate this finding within the validation cohort. Specifically, this DCLRE1C SNP was significantly associated with the extent of J-gene trimming in productive TCRalpha and TCRbeta chains and V-gene trimming of both productive and non-productive TCRalpha and TCRbeta chains within the validation cohort. The overlapping SNP within the DNTT locus (rs3762093) was only weakly associated with the extent of N-insertion within the discovery cohort, and as such, it was not surprising that this SNP only reached statistical significance for one of the N-insertion types (productive TCRalpha rearrangements; note that due to the lack of the D gene, N-insertion annotations are likely less noisy on the TCRalpha locus). Despite our inability to replicate all N-insertion associations, we noted that the model coefficients for rs3762093 genotype were in the same direction (i.e., the minor allele was associated with fewer N-insertions) for all N-insertion and productivity types within the TCRbeta chains for both cohorts.

Reviewer #2 (Public Review): 

In this study, Russell et al. combined T cell receptor (TCR) repertoire sequencing data with SNP array genotype data to infer genetic polymorphisms which impact upon the process of TCR generation. Using these data, the authors looked for loci with polymorphisms which associate with different V(D)J recombination probabilities, i.e. sites in the genome which impact upon the chances of TCRs with different properties being produced when they change. 

Beyond the expected sites in the TCR and MHC loci, the authors observed strong associations with distant sites. One was with DCLRE1C, which encodes Artemis, the endonuclease responsible for cutting the TCR loci during recombination, while the second was DNTT, the site encoding the enzyme Tdt, which is responsible for addition of nucleotides to cut V(D)J during recombination. This is the first time that such SNP associations have been described to my knowledge, and yet make perfect sense: DCLRE1C variations were associated with the amount of trimming V and J genes underwent during recombination, while DNTT polymorphisms associated with the number of inserted nucleotides. The authors also report, after assigning donors an associated ancestry based on clustering of their genotype data, that certain inferred ancestries associate with different TCR repertoire properties. In this analysis 'Asian-associated' TCR repertoires had fewer non-templated nucleotide insertions, along with a corresponding greater incidence of the DNTT polymorphisms associated with differences in insertions, relative to other groups. 

Strengths: 

This manuscript is exceedingly well written. Both the TCR biology and the statistical considerations of the genetic analyses are extremely complex topics, mired in arcane terminology, which often end up somewhat impenetrable to non-expert readers. However both have been introduced and explained with admirable clarity throughout, including the caveats and implications of analyses that would not be intuitive to many readers not already expert in both fields. 

As best I can determine, the analyses themselves are also extremely rigorous, with each step carefully taken and justified in the text, involving numerous corrections at multiple scales (e.g. for TCR productivity, TCR gene usage, specific TRDB2 genotype, population substructure, and more). The major findings have also been validated in a completely separate cohort, using a different analysis pipeline. While the authors point out that such genome-wide association efforts looking at TCR gene expression have been undertaken before, the major innovation presented here lies in applying those data to investigating specific V(D)J recombination probabilities. Thus the findings are novel, and the conclusions well supported by the data. 

The data visualisation have all been plotted in a sensible and easily interpretable manner. The majority of data themselves are all already publicly available, having been published in prior studies. The TCRseq data for the validation code has been assigned a BioProject accession, which I presume will go live at the time of publication. The code is also appropriately hosted on Github, and are mostly adequately commented and documented enough so as to be repeatable. 

Limitations: 

There are very few if any obvious technical limitations or weaknesses that I can see that are not intrinsic to the data themselves. While the authors do mention these limitations, I wonder if they should be devoted some more attention somewhere in the text of the manuscript; relatively few researchers are expert in both TCR biology and the technicalities of genome-wide association studies, so I think more explicit consideration of these issues would be helpful. 

In particular, I think the difficulty of studying these loci with standard techniques could be underlined, along with what implications that might have for this study. The highly repetitive nature of the TCR loci can certainly make any analysis looking at short sequences problematic, which has implications for both the TCRseq and genotyping aspects of this study. Combined with the fact that most studies focus on certain populations, polymorphisms in the TCR loci are very likely being relatively undersampled by the field (a hypothesis supported by the ongoing discovery of novel exonic polymorphisms in TCRseq data itself, e.g. as demonstrated in this pre-print by Omer et al. https://doi.org/10.1101/2021.05.17.444409). The consequences of SNP polymorphism coverage in SNP arrays has already been considered for IgH (https://doi.org/10.1038/gene.2012.12): while this is an admittedly more polymorphic locus, the underlying causes of these issues are mostly all true of the TCR loci as well. Similarly, while the authors do appropriately point out that issues with V(D)J gene assignment could infer biases it may be worth noting that the TCRseq technology used to produce their main dataset uses relatively short read sequencing, that is unable to distinguish a substantial fraction of even known TCR gene- and allele-level diversity (see Fig. 1C of the Omer et al. pre-print). Thus there may be a whole dimension of TCR polymorphism that is not well captured by either platform. 

Overall, I think this is an extremely considered and digestible study, which will be of great interest across and beyond the field. As the wider community comes to grips with how best to incorporate TCR and BCR polymorphisms into their analyses of the adaptive immune loci themselves (and how this might impact upon recombination, expression, and downstream immune functions) this serves as a timely reminder that we should not forget the polymorphisms elsewhere in the genome that might also be relevant.

Author Response

Reviewer #1 (Public Review):

The recordings done by the authors are impressive and rare, and I appreciate the efforts of the authors to bridge very different types of signals that are generally recorded in different paradigms. However, the analysis at many places is quite nuanced and high-level, making it difficult to directly compare these findings with previous results. I think several additional analyses are needed to properly place these findings with previous results.

1. Effects of attention in V4 generally start earlier (~100 ms). It is unclear why no effect is observed during earlier time periods in these data. To make better comparison with previous studies (such as Nandy et al., 2017), the authors should show the average PSTHs in supragranular, granular and infragranular layers during both target-out versus target-in conditions. Interestingly, Nandy and colleagues found largest changes in firing rates in the granular layer. To better understand the ERP outside the cortex, the authors should also show the average LFPs in the three layers, for target-in and target-out conditions. It is surprising that MI analysis reveals no significant information about the target in granular layer - given that some attentional effects are seen in upstream areas such as V1 and V2.

We have created a new figure showing multiunit activity and LFP across the layers in both attention conditions. It is included here for convenience. Accompanying text has been added to the Results and Discussion sections to address the reviewers’ comments.

The timing of differentiation between attended and unattended in the population spiking activity is evident in both MUA and LFP. We note that the largest magnitude difference in population spiking between attention conditions was observed in the middle layers, consistent with Nandy et al., 2017. We wish to highlight two observations.

First, with respect to the timing of attentional modulation, it should be noted that the attention task used in our study (pop-out visual search) is different from that used by Nandy et al., 2017, Neuron (cued change detection). The timing of “effects of attention” vary according to stimulus properties and task demands (the number of publications demonstrating this is too long to list). Hence, we do not expect equivalence between the times we measure and times Nandy et al. measure. Nonetheless we are happy to include the requested supplementary figure with that caveat in mind.

Second, with respect to the surprising observation of a relationship between activity in the granular layer and the extracortical signal, we think it is important to remember that these information theoretic analyses are not simply correlational. That is, attentional modulation might be observed in both signals, but if the covariation of these signals trial-to-trial does not exist, then we would not expect a relationship in the mutual information analysis.

1. Eye position analysis: my understanding is that the animals could make a saccade as soon as the arrays were displayed. Given that the main effect of attention is observed after ~150-200 ms, the potential effect of saccade preparation could be important. There could also be small eye movements before the saccade. Given that the RFs were quite fovial for one monkey and not too far from the fixation window, and the effect of attention appears to be quite late, detailed analysis of eye position and microsaccades is needed to rule out the possibility of differences in eye movements between target in and target-out conditions influencing the results. A timeline and some analysis of eye movement patterns would be appropriate. The authors should also clearly mention the mean and SD of the saccade onset.

The reviewer makes a valuable observation. Saccades will influence the electrical signals, something we are quite familiar with (e.g., Godlove et al., 2011, J Neurophysiol). In an effort to combat this, we have two points worth noting. First, as was the case in the initial submission (which remains the same in the revision), we have clipped signals on a trial-by-trial basis prior to eye movements. By doing so, we cannot have an influence of the motor-related polarization of the task-demanded eye movement on the data.

Second, we have prepared a microsaccade analysis – and accompanying newly added supplementary figure included here for convenience – to determine whether they might be driving the results. To do this, we identified trials where microsaccades occurred using a well-regarded microsaccade detection algorithm (Otero-Millan et al., 2014, J Vis). We then reperformed the information theoretic analysis across sessions after removing trials where microsaccades were detected. Briefly, we found that the information theoretic relationship persists in the absence of trials where microsaccades occurred. We believe this serves as evidence that microsaccades are not responsible for the information theoretic findings.

To address the reviewer’s last point, we have included response time data (defined as the saccade onset latency) in the Results.

1. Attention studies typically keep the stimulus in the RF the same to tease out the effect of attention from stimulus selectivity. Ideally, the comparison should be between the two green (or red) in RF conditions as shown in Figure 4A. However, these results are shown only after pooling across all color selective columns. This comparison should be shown from Figure 2 itself (i.e., Figure 2C should have green in the RF and red target outside).

We have clarified prior to Figure 4 that we used a all trials including both colors in each of the attention conditions. That is, while the cartoon in Figure 2 shows only green-attended and red-unattended conditions, green-unattended and red-attended conditions were also included in this analysis. As the proportion of red-target and green-target trials was matched, this first analysis was designed in such a way that the influence of stimulus color should be minimized, yet all trials could still contribute to the calculation. We have included a new supplementary figure (included here for convenience) which is what we believe the reviewer requests. In this addition, we perform the information theoretic computation on only stimulus matched conditions. Briefly, we find that this approach does not seem to alter the temporal profile of information theoretic findings.

1. Information has been well characterized in a large number of previous studies (generally yielding values between a few bits/s, see for example, Reich et. al, 2001, JNP). Here, the absolute value of mutual information seems rather low. This may be due to the way the information is computed. A discussion about these reasons would be useful for scientists interested in information-theoretic measures.

We agree that the exact magnitude of our information theoretic analyses in curious. And while these methods have been widely characterized – they have not been characterized, to our knowledge, in relating intracortical laminar currents to extracortical field potentials. As such, we do not have a strong prior as to what we should expect magnitude-wise. We have expanded the discussion to note this observation and provide potential reasons as to why this might be the case. The conclusion being that further application of these methods to these datatypes is necessary to really gain a fuller sense of what should and shouldn’t be expected.

1. Dependence on feature preference: The effect of spatial and feature attention is well studied. A multiplicative gain model of spatial attention would predict a larger increase in firing rates )and perhaps other signals such as CSD) for preferred versus non-preferred signals. Feature similarity gain model would predict the red preferring columns to increase their activity and green preferring columns to reduce their activity when the animal is attending to the feature red, irrespective of which stimulus is in the receptive field. Here, the task is a pop-out task which likely has both a spatial and feature attention component. The authors should discuss their findings in these contexts. Further, the authors should discuss whether their findings could just be a reflection of the magnitude of the change (which could be larger for preferred versus non-preferred stimulus). The information-theoretic measure should ideally not depend on the absolute magnitude, but these quantities often get biased in non-trivial ways based on the magnitude. Does information transmission depend on the magnitudes of firing rates/CSDs?

The relationship of these findings to the specificities of attentional mechanisms and models is indeed intriguing. As the reviewer suggested, this task likely engages both spatial and feature attention – however, the design was not such that they can be disentangled wholly. We have added text to the Discussion to reflect this consideration. As for the potential influence of response magnitude changes on the information theoretic analyses – the exact parameters were chosen to mitigate concerns about magnitude. That is, we chose a uniform count binning procedure on the data which eliminates potential issues such as outliers driving relationships as well as the changes in variability associated with increases in magnitude. Moreover, the uniform count binning procedure results with states rather than magnitudes which again mitigates response-magnitude-driven effects.

1. For columns that were not feature selective, is there an effect of attention? Does the magnitude of N2pc change depend on color selectivity? I think that should be the case based on Figure 4H and 4I, but a plot and/or some quantification would be useful.

These questions have been addressed in a newly added supplementary figure as well as quantification in the Results. Briefly, we did find an effect of attention non-selective columns. Also, we found the magnitude of N2pc did not depend on color-selectivity of the intracortical recording. The results were reported as:

“We also tested whether feature selective columns, on average, transmitted more information than their non-feature-selective counterparts. We found that feature selective columns, in all laminar compartments, transmitted significantly more information (Figure 4I) (two-sample t test: L2/3, p = 0.044; L4, p = 0.023; L5/6, p = 0.009). As such, we wanted to determine if this was due to a lack of attentional modulation in the non-selective columns. This was not the case, we observed that non-selective columns were modulated with attention. Attentional modulation was observed in both the CSD in L2/3 and L5/6 (one-sample t test: L2/3: t(64) = -6.01, p = 9.8e-8; L4: t(64) = -0.18, p = 0.86; L5/6: t(64) = 5.24, p = 1.9e-6) as well as across all layers in the population spiking activity (one-sample t test: L2/3: t(64) = 8.00, p = 3.7e-11; L4: t(64) = 9.66, p = 4.1e-14; L5/6: t(64) = 7.58, p = 1.8e-10) during the N2pc interval (averaged 150-190 ms following array onset) (Figure S6).

Importantly, we tested whether the N2pc varied across sessions with or without color-selective columns sampled. We found no difference between N2pc polarization (150-190 ms after the array) between sessions with (n = 17) or without (n = 13) sampling of color selective columns (two sample t test: t(28) = -0.75, p = 0.46). This invariance is expected because extracortical EEG spatially integrates signals from multiple cortical columns.”

Reviewer #2 (Public Review):

Scalp ERPs are widely used in human neuroscience research to understand basic mechanisms of neural and cognitive function and to understand the nature of neurological and psychiatric research. However, this research is hampered by a surprising lack of research in animal models exploring the neural mechanisms that produce specific ERP components.

Previous research by this research group identified a potential monkey homologue of the N2pc component, a neural correlate of the focusing of attention onto visual objects embedded in arrays of distractors. The present study took a giant leap forward by recording extracellular potentials from densely spaced arrays of electrodes (.1 mm spacing) on probes that extended perpendicular to the cortical surface. These electrode arrays made it possible to simultaneously record voltages throughout the different layers of a cortical column and convert these voltages into current source density (CSD, which isolates local synaptic current flow and minimize volume-conducted activity from other brain regions). In addition, simultaneously recorded voltage from an electrode just above the cortical surface was used as a proxy for scalp potentials. Scalp ERP recordings were also obtained from separate monkeys to measure the actual scalp ERPs and verify that an N2pc-like ERP was elicited by the task (a simple visual search task in which the monkey made an eye movement to the location of a color popout item).

Very clear CSD was observed in V4 in both supragranular and infragranular layers that was stronger when attention was directed to the contralateral visual field than when attention was directed to the ipsilateral visual field, which is the hallmark of the N2pc component. Little or no such activity was observed in the granular layer (the primary recipient of feedforward projections). In addition, the effects were observed primarily when the column was selective for the target's color. An information theory analysis showed that these intracortical current flows contained significant information about the voltage measured on the cortical surface and the location of the target object.

All of these results were clear and convincing. Moreover, the laminar and columnar analyses provide interesting new evidence about attention-related neural activity independent of any considerations about ERPs. The most challenging aspect of the study is to provide a solid link from the intracortical activity to the voltage on the cortical surface, and then to the monkey scalp ERPs, and finally to human ERPs. Toward that end, the present study relied entirely on correlational evidence, rather than experimental manipulations. That's quite appropriate for a first step, but it must be considered an important limitation on the conclusions that can be drawn. It would be wonderful if future research took the next step of providing experimental evidence.

We appreciate the reviewer noting that this manuscript is a valuable step in linking attention-associated electrophysiological signals across species. We also recognize that there is much work to be done in this domain. As requested, we have added to the Discussion the limitation of this type of study as well as what should be considered valuable next steps in this program of research.

There are also some troubling aspects of the existing evidence. The scalp ERP effect in this study and the prior work from this groups is a positive voltage over the contralateral hemisphere, whereas in humans the voltage is negative. This may well reflect the orientation of the relevant cortical surface in monkeys versus humans. However, the voltage on the cortical surface in the present study was negative contralateral to the target, not positive. Unless this opposite voltage on the cortical surface relative to the scalp reflects something about the reference site for the cortical surface electrode, then this makes it difficult to link the intracortical effects and cortical surface effects to the scalp ERP effects. Also, the CSD was negative in the upper layers and positive in the lower layers, again suggesting that the voltage should be negative contralateral to the target on the surface. Ironically, this polarity is what would be expected from the human brain, where a contralateral negativity is observed. The oddity seems to be the contralateral positivity in the monkey scalp data. Also, the cortical surface voltage exhibits a polarity reversal at approximately 180 ms, which is not seen in the intracortical CSD.

One possible explanation for the discrepancy is that the scalp voltage likely comes from multiple brain areas besides V4. If, for example, areas on the ventral surface of the occipital and temporal lobes produce stronger scalp voltages than V4 under the present conditions, the opposite orientation of these areas relative to the cortical surface would be expected to produce a positive voltage at the scalp electrodes.

The manuscript notes that multiple areas probably contribute to the scalp ERPs and argues that the pattern of intracortical CSD results obtained in V4 will likely generalize to those areas. That seems quite plausible. Moreover, the results are interesting independent of their link to scalp ERPs. Thus, the present results are important even if the scalp polarity issue cannot be definitively resolved at this time.

We thank the reviewer for expressing that the results are important whether this polarity difference can be resolved. This is an interesting observation and quite important to consider carefully. First, it is worth reiterating that the referencing setup in our ‘10/20’ monkeys was different than that for the monkeys where intracranial recordings took place. Specifically, the 10/20 recordings were more similar to our previous reports of monkey EEG (e.g., Woodman et al., 2007, PNAS; Cohen et al., 2009, J Neurophysiol; Purcell et al., 2013, J Neurophysiol). Recordings from these monkeys used either a frontal EEG electrode (approximately FpFz) or linked ears for referencing. These yielded the positive-going N2pc and contrast the negative-going N2pc found in humans. The V4 laminar recordings – and their accompanying extracortical signal – used a different referencing setup that we believe is the most likely candidate for the observed difference. Specifically, these recordings used a tied ground-reference setup which incorporated the support rod of the linear multielectrode array. This support rod extended into the brain meaning we had a neural tissue grounded signal and that the reference spanned the neural generator. Therefore, if we are not measuring both sides of the electric field across the generator equally, we might observe an inverted signal. Unfortunately, we cannot observe the 10/20 EEG distribution with an intracranial reference. Ideally, this could be resolved by an experiment where referencing setups are tested before and after performing craniotomy with a series of reference locations used to understand where exactly this flipping of polarization takes place. We have added this consideration to the Discussion and more thoroughly detailed the referencing setups in the Methods.

There are also some significant concerns about the filters. The high-pass cutoff was high enough that it could have produced artifactual opposite polarity deflections in the data. If causal filters were applied (e.g., in hardware during the recordings), these artifactual deflections would have been after rather than before the initial deflection, possibly explaining the polarity reversal at 180 ms. If noncausal filters were applied in software, this would be a larger problem and could produce artifacts at both the beginning and end of the waveform. Moreover, the filters were different for the CSD data and the extracortical voltages, which is somewhat problematic for the information theoretic comparisons of these two data sources (but is likely to reduce rather than inflate the effects).

In revisiting the description of the recording system and filters, we see how some information was conveyed poorly. The language describing the recording in the original submission suggested that online filters were applied to the data as it was being recorded. This was not the case. We have changed that language so that it reads as the data was being collected at a sampling frequency sufficient to observe data between 0.1 Hz and 12 kHz rather than the data being filtered between 0.1 Hz and 12 kHz. Also, it appears that the description of the processing sequence regarding CSD was ambiguous in the original submission. The CSD underwent the same offline, bandpass filtering procedure (1-100 Hz) as the extracortical signal. We have clarified the Methods accordingly.

Reviewer #3 (Public Review):

In this study, Westerberg et al., investigate the cortical origins of the N2pc, an ERP for selective attention. By using a combination of indefinite inverse models of cranial EEG and translaminar electrophysiology, the authors demonstrate that dipoles in V4 are the source of the N2pc.

The study is well conducted and the manuscript is well written.

We are pleased that the reviewer recognized the contribution of our efforts.

I have a few comments about the CSD, RF alignment profiles, and LFP based analyses:

(A) The method section states correctly that "current sinks following visual stimulation first appear in the granular input layer of the cortex, then ascend and descend to extra granular compartments". However in the example CSDs shown in Fig 2, Fig 3, Fig S3 there is no visible current sink in the infra-granular layers. Instead, the identified infra-granular layers show a prolonged current source (e.g. Fig S5B,C), which is unexpected.

We have clarified the Methods to reflect the observations of our data and why they may differ from previous reports. We believe the discrepancy is likely due to the stimulus conditions used to evoke the CSD profile. Specifically, the descending infragranular sink in visual cortical columns has most commonly been described when CSD was computed while monkeys view briefly presented flashes or stimuli (e.g., Schroeder et al., 1998, Cereb Cortex). However, our study uses task evoked CSD to perform the alignment. Importantly, this means there is a persistent stimulus in the receptive field. We believe this persistent stimulus, rather than a flashed stimulus, leads to a persistent, strong sink in the superficial layers of cortex which would mask any current sink present in the infragranular layers (Mitzdorf, 1985, Physiol Rev). This is an observation we made in previous reports (Task evoked CSD: Westerberg et al., 2019, J Neurophysiol vs. Flash evoked CSD: Maier et al., 2010, Front Syst Neurosci), albeit in V1 instead of V4. Given the latency offset between putative granular and supragranular sinks, that we observe receptive fields below the putative granular input sink, and the demonstrable multiunit activation as indicated by the newly included Figure S2, we have no reservations in our assessment of the position of the electrode relative to the layers across sessions.

(B) The example RF profile shown in Fig S5A, although aligned, looks a little strange in that the RFs taper off rapidly in the infra-granular layer. Is this the best representative example? It will be important to see other examples of RF alignment.

The attenuation observed in the lower layers is largely due to overall decreased gamma power in the lower layers of cortex as compared to upper and middle layers (Maier et al., 2010, Front Syst Neurosci). At the reviewer’s request, we have added an additional panel to the noted supplementary figure which shows additional laminar receptive field profiles using the evoked LFP so that they are more directly comparable to those shown in Nandy et al., 2017, Neuron.

(C) The study used LFP power in the gamma range to compute the response ratio between red and green stimuli. LFPs measured across the cortical depth are highly correlated, and so would gamma power estimated from the LFPs. Given this, how meaningful is the laminar analysis shown in Fig 4B? How confidently can it be established that the LFP derived gamma power estimates have laminar specificity?

An astute observation – there are two aspects to consider. The existence of color-feature columns has been well-documented in V4 (e.g., Zeki, 1973, Brain Res; Zeki, 1980, Nature; Tootell et al., 2004, Cereb Cortex; Conway and Tsao, 2009, PNAS; Kotake et al., 2009, J Neurophysiol; Westerberg et al., 2021, PNAS). This manuscript did not need the evaluation of interlaminar differences in color selectivity to address the question at hand – the top of Figure 4B only serves as a step to the bottom of Figure 4B which provides the measurements used for the subsequent analyses. Thus, the estimation of color selectivity from gamma was sufficient to capture a general sense of the color selectivity of the column. Second, we recently published a manuscript which directly addresses the laminar specificity of gamma with respect to feature selectivity. Westerberg et al., 2021, PNAS uses a spatially localized form of gamma to evaluate color-feature selectivity along V4 columns. In that manuscript, we find a high degree of consistency along the layers of cortex using the gamma signal. Notably, we compared the gamma signal to the population spiking and found a high degree of coherence between selectivity in those two measures as a function of cortical depth. Given the secondary nature of the interlaminar feature selectivity to this submitted manuscript and the detailed report of laminar feature selectivity using the same dataset in another manuscript, we are inclined to leave the analysis reported here as is with adjustments to the text that note these considerations now included in the Results.

The irony is that this is, itself, somewhat a conspiracy theory.

Though, I think a nuanced understanding may be closer:

• The real purpose is not to influence people to believe anything. It's money. It's ad spend and data collection to sell. We need to demonstrate to advertisers that their ads are actually getting seen. The more they get seen, the more money we make. And, the more time is spent on the service, the more data we have to sell... which is as valuable as the add spend.
• Companies jigger algorithms to maximize time spent on the service.
• As the Bible is clear, the heart of man is wicked, and the kinds of things that maximize time spent are themselves attitudes of evil, malice, wickedness, and hatred, and the list of things Paul repeatedly tells us to avoid. Go figure.
• So, people feel the platforms are basically like smoking, and yet, they can't stop.

Author Response:

Reviewer #1:

This manuscript by Silver, et al., details work investigating the relationship between season of conception and DNA methylation differences at sites across the genome, measured by widely-used arrays, in two cohorts of children using Fourier regression. They find that season of conception is associated with persistent methylation differences at several hundred CpG sites, and that these CpG are enriched for properties, compared to sets of control sites, that suggest that methylation at these sites is influenced very early in development/during conception and that these sites are positioned in genomic regions relevant for gene activation and regulation. Additional analyses investigated the effects of genetic variation of these sites, and found no evidence for single nucleotide polymorphisms nor child sex confounding the associations between season of conception and DNA methylation. As the number of sites measures by these arrays are a very small amount of total sites across the genome, the authors suggest that these findings indicate there may be many more sensitive methylation 'hotspots' in the genome that are not captured by these arrays but could impact on health/development.

The key strengths of this manuscript include the use of two cohorts of children at different ages, providing evidence that these effects of season of conception appear to attenuate by 8-9 years of age; and comparison with control sites and additional analyses investigating confounding to build the evidence for these relationships reflecting true, biological associations rather than statistical artefacts or the result of confounding.

However, the conclusions around the potential functional importance of these methylation differences are limited by a lack of evidence for a relationship between methylation of these season-of-conception-associated sites and child growth/development, so while this manuscript builds compelling evidence for the effects of season of conception on methylation, it's functional relevance is unclear. Additionally, there are some choices made in the analyses where the rationale for those choices should be made more clear, such as the use of CpG sites above or below a certain estimated effect size for different analyses.

Overall, the approach taken here to demonstrate different levels of evidence for true relationships between early development exposures and differences in DNA methylation is a compelling one, and the manuscript delivers clear evidence for its primary conclusions.

We are currently researching links between several SoC-CpGs and health-related outcomes including measures of growth, and we have prepared/submitted other papers with different groups of authors (e.g. the EMPHASIS team) relating to other phenotypes. We consider a detailed analysis of links between SoC-CpGs and diverse outcome measures in Gambian children to be beyond the scope of the current study and would argue that such an analysis would dilute the central focus of this paper that is already long and complex. We do already refer to two existing studies linking Gambian SoC or nutrition-associated CpGs to health outcomes in non-Gambians (child & adult obesity/POMC, Kuhnen et al Cell Metab 2016; cancer/VTRNA2-1, Silver et al, Gen Biol 2015) in the current manuscript. The VTRNA2-1 locus does not overlap any SoC-CpGs and we already speculate that this may be due to SoC effect attenuation, since the previous association was observed in younger (3-9mth) infants. We have additionally referenced a recently published paper linking another SoC-associated locus to thyroid volume and function in Gambian children (Candler et al Sci Adv 2021) and highlighted that neither this nor the POMC locus overlap the array background analysed in this study. Finally we had already included an analysis of overlaps between SoC-CpGs and traits in published EWAS and GWAS catalogues.

Regarding our use of different SoC amplitude thresholds for one analysis, our original motivation for analysing all 768 ‘SoC-associated CpGs’ with FDR<5% in the ENID 2yr analysis, including those with amplitude < 4%, was to explore the degree to which the strength / amplitude of SoC effects could be explained by proximity to ERV1 over the wider range of amplitudes represented by the larger set of loci. However we agree that this approach is open to question and have removed this analysis (previous Fig. 6B and Supp. Fig. 11, and text in section headed ‘Enrichment of transposable elements and transcription factors associated with genomic imprinting’). We have also removed the definition of ‘SoC- associated CpGs’ (which included CpGs with SoC amplitude < 4%) from Table 2 and Methods to aid clarity and avoid confusion.

Reviewer #2:

This is a very interesting manuscript, which will be of interest for a broader readership. The authors have analysed an unique cohort, which is of importance to understand the impact of environmental factors on DNA methylation.

The performed analysis is well balanced, and the conclusions are justified by the presented data. It is a strength of this study, that results from the initial ENID study have been re-evaluated in the EMPHASIS study. Unfortunately, DNA methylation has been analysed using HM450 and EPIC arrays. Both methods are providing only a limited view on methylome-wide DNA methylation.

Another limitation (as already addressed by the authors) is the lack of longitudinal samples. This would potentially have helped to gain further knowledge about the identified attenuation of DNA methylation levels at SoC associated CpGs.

Finally, I am not entirely sure, that one confounding factor has been completely ruled out: It is known, that blood composition may cause methylation variability. In general, the authors addressed this point and analysed blood compositions (supplementary Figure 16) of both cohorts. Here, no marked seasonal differences between and within both cohorts have been identified. However, the participants of the EMPHASIS cohort have a very similar age (8-9 years). For this reason, I am wondering if methylation variability/ differences and in addition the attenuation of methylation levels might be influenced by the younger age of ENID participants compared to EMPHASIS study individuals.

We agree that the necessary restriction of our analysis to data derived from Illumina 450k and EPIC arrays means that we can only obtain a limited view of DNAm loci associated with Gambian season of conception. We expect that there will be many more such hotspots across the human methylome. We have commented on this in the Discussion.

Regarding the lack of longitudinal data to confirm the potential attenuation of SoC effects with age observed between unrelated cohorts, we are pleased to report that we have now acquired an additional EPIC array dataset covering a subset of n=138 individuals from the ENID cohort included in the main analysis. This subset had methylation measured in blood at age 5-7yrs enabling us to conduct an investigation of longitudinal methylation changes in these individuals. This analysis strongly supports the circumstantial evidence of SoC effect attenuation with age suggested by our previous comparison of the independent ENID (2yr) and EMPHASIS (7-9yr) cohorts, with:

a) strong correlation of conception date methylation maximum between age 2yr and 5- 7yrs at SoC-CpGs in these 138 individuals (Figs. 3A, 4A); and

b) evidence of SoC effect size attenuation at the majority of SoC-CpGs (Fig. 3B; Wilcoxon signed rank sum p=10-12).

We note that this additional longitudinal dataset has a different confounding structure with respect to biological and technical covariates (Supp Tables 15-17) and date of sample collection (Supp. Fig. 1B), lending strong support to our previous two-cohort cross-sectional analysis.

Regarding the potential for confounding by differences in blood cell composition, we have performed an additional sensitivity analysis with Houseman estimated blood cell counts added directly to the linear regression model for the ENID cohort (see ST1s). 518 out of the 520 estimated Fourier regression coefficients from the main analysis (1 pair of sine and cosine terms for each of the 259 SoC-CpGs) fall within the 95% confidence interval obtained in the Houseman-adjusted analysis, confirming that cell composition effects did not unduly influence SoC effect estimates in the original analysis. We have added a brief note on this and the other sensitivity analyses (batch, cell composition and village effects) in Results to the manuscript, with more details in Methods.

If the reviewer is referring to the possibility that the SoC effect attenuation with age could be driven by different cell composition effects in the older cohort, we think that the replication of the timing of SoC effects across the 3 datasets analysed (including the additional longitudinal data; Fig. 4A), all of which have different confounding structures with respect to season of sample collection (Fig. 2A; Supp Fig. 1B), together with additional evidence of SoC effect attenuation with age in the longitudinal analysis (Fig. 3B) support this being a genuine age attenuation effect.

Reviewer #3:

Silver et al. Investigate the influence of seasonal variation (nutrition, infection, environment) on blood DNA methylation in two cohorts of children (233 [2y] and 289 [8y-9y]) from the same sustenance farming communities in rural Gambia. One cohort (450K,233) was extensively studied before in multiple publications, the second dataset (850k,289) is unpublished. Using cosinor modeling they find 768 CpGs with a significant seasonal pattern(SoC-CpG, FDR<0.05) in the probes that overlap between the 450k and 850k arrays. Look-up of these 768 SoC-CpGs in the second sample showed 61 SoC-CpGs with FDR 0.05 (no mention is made if the direction of effect is consistent, but we assume it is so).

In fact we did report that the ‘direction’ of the effect (conception date at methylation maximum) is highly consistent with increased DNAm in conceptions at the peak of the rainy season across the two cohorts at the 61 SoC-CpGs with FDR<0.05 – see Fig. 2C.

The authors notice that most SoCs seem to be attenuated in the 8-9y sample. Then the authors select out of the 768 SoC-CpG the FDR<0.05 and >=4% seasonal amplitude in this discovery sample: 257 which they bring further in (enrichment) analyses. It is unclear if all 257 are (nominally) significant in the replication sample.

We did not check this because of evidence that, despite strong replication of effect direction (Fig. 4A), the amplitude of the SoC effect attenuates with age (Fig. 2E). This means that it would not be surprising if one or more SoC-CpGs failed to achieve nominal significance in the older cohort. This is now strongly supported by our additional analysis of longitudinal data confirming SoC effect attenuation with age and consistency of SoC effect direction (Figs. 3B and 4A).

These SoC-CpGs are enriched for imprinted and oocyte germline loci. Roughly 10% of SoC-CpGs overlap with so-called meta-stable epialleles (MEs), on which the authors have published greatly. This is a large fold enrichment, and subsequently the main focus of the Results and Discussion. Indeed, it skews the Discussion heavily and one wonders what could have been found in the other 90%?

Our strategy throughout the Results and Discussion was to focus on characteristics including metastability, parent of origin-specific methylation, histone modifications and gametic and early embryo methylation patterns that suggest a link to establishment of methylation states in the early embryo at SoC-CpGs. For these analyses all SoC-CpGs were considered at every stage and metastability was not the primary focus. However, as the reviewer suggests, we do repeatedly point out that many of the above contextual characteristics that are associated with SoC-CpGs have also been associated with metastability which we consider to be worthy of note, in part because it suggests that many SoC-CpGs may in fact be MEs, despite not having been previously identified as such. We have further cause to believe this could be the case because of i) the typically small sample size of multi-germ layer/tissue datasets used to screen for MEs, meaning that published screens for human MEs are likely to be underpowered and will hence fail to capture most MEs; and ii) the evidence that we present suggesting that environmentally-driven inter-individual variation at loci exhibiting ME-like properties may diminish with age, again suggesting that ME screens, which largely analyse adult tissues, will miss metastable loci present in infancy and early childhood.

We had already made the point ii) above in the Discussion. However, given the reviewer’s concerns we have added an additional comment on point i).

The Discussion is heavily geared to interpretation within their MEs focus and does little to discuss study weaknesses and strengths, to which the tail of the Results suggest there are multiple. For at the end of the Results and in the Methods we find additional sensitivity analyses and discussion points on a very strong enrichment for CpGs with a mean difference in methylation between the sexes (>1/3 of the 257), adjustments for genetic confounding and a high inflation factor in the discovery cohort.

We have added an additional comment on the need for further functional analysis in cell and/or animal models at the end of our discussion on possible mechanisms underpinning the observed strong enrichment for sex effects at loci associated with periconceptional environment. We have performed an additional analysis of SoC effects on global methylation using predicted LINE1 and Alu element methylation to address the issue of genomic inflation in the discovery cohort (Methods ‘Inflation of test statistics’ and additional Supp. Fig. 14). We have commented on the potential for residual genetic confounding and the limitation of a lack of genetic data in the discovery cohort in the Discussion. We have also provided an additional comment on the potential influence of unmeasured inter-relatedness in our study population.

Indeed, despite the strong and good flow of the Result section and the impressive (albeit somewhat one-side) look-up of SoC-CpGs in published datasets; the tail and Methods section leaves this reader with a strong suspicion of possible methodological issues on the measurement level already identified prior.

The authors reports that the discovery cohort is biased in the collection of conception months (figure 2A), has a strong inflation of 1.3 (no QQ-plot is shown to assess bias in addition to inflation), no adjustment for genetic background could be made (which is false, as the 450k array contains several dedicated SNP probes, even hundreds when extracted with the omicsPrint package) and > 1/3 of SoC-CpGs is a sex CpG. For the latter observation the authors regressed out sex and repeated the analysis, noting no difference. However, regressing out sex does not help if sex is heavily correlated with confounding biological/sampling/technical covariates.

The authors reason that the inflation is nothing to worry about citing single cohort studies on global effects on DNAm of methyl donors. Global DNAm is indeed often association with methyl donor intake but generally these studies investigate ALU or SINES repetitive elements and the PACE consortium reported only modest effects on select 450K array loci for prenatal folate supplementation, showing that their reasoning might hold on the ME loci (in/close to repetitive elements) but not the genome-wide analysis per se.

The authors should convince the reader that their (discovery) data is valid. The data they do show in Supplemental tables 16 and 17 show that after functional normalization a strong effect of batches remains, while from my own experience these are normally nicely mitigated via functional normalization. Normally only strong cell type correlations remain in the first PCAs of the normalized data. But for ENID we see a remainder of sentrix row, often the strongest batch effect, and slide and plate remaining. Also, the biological, season and cohort specific variables are not noted here. We just must assume that the blank correction for the first 6 PCAs, rather than the actual adjustment for the measured batch/confounding effects, does not remove (or over adjusts) for biological/study design (village, genetic ancestry) effects. In addition to these observations figure 2C seems to indicate that the controls CpGs (elegantly selected by the authors) also show seasonal variation, just not as much as the SoC-CpGs. This leaves the reader to wonder: is there bias in their sample randomization across plates, rows and slides? This feeling is amplified by the fact that almost all SoC-CpGs seem to show an increase in DNAm in jul-aug (Suppl Fig. S5 and Figure 1B). [An observation that is not given enough prominence in the Results]. Which might or might not hint to a correlation with a batch effect (like sentrix row?).

Our addition of a third longitudinal dataset with a very different confounding structure provides strong reassurance of the robustness of the reported SoC effects. However we recognise many of the concerns raised by the review and have therefore substantially extended our analysis of potential confounders in our analysis, including additional sensitivity analyses (see Supplementary Tables ST1p-1s).

In our extended analysis of possible confounding of technical and biological covariates by SoC, we note that the majority of batch and biological covariates are categorical so that it was not possible to report correlation rho’s. We have instead reported p-values for corresponding association tests – see Supplementary Tables for further details of tests that were carried out. Also note that for simplicity season of conception is modelled as a binary variable (Dry: Jan-Jun; Rainy: July-Dec). We consider this to be a valid approximation to the main cosinor (Fourier) regression analysis since this showed a clear relationship between DNAm and dichotomised (Dry/Rainy) season of conception (Figs 2D & 4A). Note that we have not included month of collection as this completely confounds season of conception in the main ENID (2yr) analysis and cannot confound the EMPHASIS (7-9yr) analysis, as discussed in the manuscript (Fig. 2A). This is a key reason why we compared SoC effects across these two cohorts. Note that the month of collection also cannot confound the ENID 5-7yr (longitudinal) analysis as all samples are collected in the rainy season (additional Supp. Fig. 1B).

The covariate correlation analysis confirms:

• No correlation between SoC and all considered batch and biological covariates including principal components across all three analysed datasets (Supp Table, ST1p- 1r).

• No correlation between sex and all considered batch and biological covariates; weak correlations with PC4 and PC3 in EMPHASIS and ENID 5-7yr datasets respectively (ST1q,1r); note also that the sex sensitivity analysis previously reported in the manuscript used methylation values that were pre-adjusted for sex using a regression model that included sex as the only adjustment covariate, alleviating concerns that there may be residual confounding due to strong correlations between technical/biological/sampling covariates and sex. We have added some additional comments on this to Results.

• Expected strong correlations between SoC, month of conception and month of birth in all datasets (ST1p-1r).

• Functional Normalisation (FN) removed most but not all of the effects of technical batch effects (sample plate, slide etc) from the DNAm array data used in the main ENID analysis (ST1p).

• Samples are not perfectly randomised across 450k sample plate (month of birth [mob] and conception [moc]) and slide (mob and village) for the ENID 2yr cohort (ST1p).

The last point raises the possibility of potential residual confounding due to array batch effects in the ENID analysis. We checked for this in two ways. First, we performed sensitivity analyses with batch and village ID variables included directly in the linear regression models, in addition to the PCs that served as proxies for batch variables in our original analysis. This suggested no residual confounding due to array batch or village ID effects (ST1s: ‘batch adjusted model’ and ‘village adjusted model’). Second, we confirmed that neither mob, moc nor village ID were associated with batch or any other covariates in the EMPHASIS or new ENID 5-7yr analyses (ST1q, ST1r). The tight correspondence of date of methylation maximum across all three datasets (cross-cohort and longitudinal analyses) (Figs. 2C, 3A and 4A) with different confounding structures (ST1p-1r) strongly suggests that the reported SoC associations are not driven by residual confounding.

In summary, this analysis provides strong reassurance that our main analysis is not confounded by residual associations with technical and/or biological covariates considered in this analysis, and that the observed enrichment for previously identified sex-associations amongst SoC-CpGs is not driven by residual confounding due to sex.

We have made multiple amendments to the manuscript to incorporate the longitudinal analysis; in the Introduction (lines 58-9); in the first section of Results; and we have made particular reference to the alignment of SoC effects across 3 datasets with different confounding structures. We have also amended several figure captions to distinguish the ENID 2yr and 5-7yr datasets and added the longitudinal dataset to Methods and to the study design schematic (revised Fig. 1), and visualised key results from this additional analysis in Figs. 3 and 4A. Finally we have added additional text on the sensitivity analyses in the main text and in Methods.

Author Response:

Reviewer #2 (Public Review):

The authors try to identify ATR-mediated phosphorylation sites in male meiosis of mice and performed phosphoproteomics using two distinct mouse models. The paper focuses on important topics in the field. Since ATR has key functions in meiosis, successful identification of ATR-mediated phosphorylation sites would have a profound impact.

The study has certain technical issues in experimental design and data interpretations.

The rationale as to why they used Rad1-cKO was not well described. According to the co-submitted manuscript, Rad1-cKO spermatocytes experience meiotic arrest, and the cellular composition is totally different between controls and Rad1-cKO testes. The "RAD1-dependent" phenotype may simply reflect the difference in cellular composition in testis. With this criterion, any phosphorylation sites present after the mid-pachytene stage in normal spermatogenesis can be categorized as "RAD1-dependent".

We have altered the figure and text in the manuscript to more clearly explain the rationale for using Rad1-cKO and combining the generated data with the data from the rapid 4 hour ATRi treatment. Importantly, we now consider the phosphorylation sites impaired after a quick 4 hour treatment with ATRi (New Supplementary File 1), which is expected to be too quick to induce an appreciable pachytene arrest. Therefore, the final ATR-dependent and RAD1-dependent dataset is unlikely to include phosphorylation sites that are only shown as being depleted due to a persistent mid-pachytene arrest (these sites should appear as RAD1-dependent and ATR-independent).

There are two different experiments for ATR inhibitor (ATRi)-treated mice (2 pairs after 2.5-3 days of treatment, and 2 pairs 4 hours after a single dose). However, these results are not distinguished in the analysis, and there is no evaluation of testicular morphology after ATRi treatment.

We addressed the point of separating the data from 4 hour and 2-3 days of treatment. We also have now also addressed testicular morphology after 4 hour ATRi treatment and did not observe any defect (new Figure 5-figure supplement 3A-B).

Finally, the authors showed ATR-dependent localization of SETX and RANBP3 and discussed interesting data. However, it has not been determined whether these localization changes were due to the functions of identified phosphorylation sites or some other mechanisms.

We agree with the reviewer that it would be very interesting to address the role of specific phosphorylation sites in SETX and RANBP3. However, we feel this would require significantly additional effort and time, which would not be realistic in the current manuscript, and is beyond the scope of this resource paper.

Reviewer #3 (Public Review):

In this study, Sims et al. perform a phosphoproteomic analysis of the ATR signaling pathway in mouse testis. By studying the different phosphorylated peptides found in testis samples from ATR inhibited mice and from mutant mice for the member of the ATR-activating 9-1-1 complex, RAD1, authors defined a comprehensive map of the ATR signaling pathway in the mouse testis. In general, the methodological approach performed is appropriate to accomplish the desired goal and the results obtained are well explained and properly discussed. The conclusions raised by the authors are supported by the results obtained and the manuscript reads easily. Thus, overall the manuscript is of high quality. Furthermore, the information provided in this study is novel since to my knowledge this is the first attempt to characterize the ATR signaling pathway in the testis. In my opinion, these data will be very relevant to better understand the role of the ATR in mouse spermatogenesis, and in meiosis in particular, in the future.

Thank you, we appreciate the positive remarks.

Nonetheless, I have a few major concerns about this manuscript. Firstly, I think an important part of the description of the results is placed in a related preprint by the authors (Pereira et al. https://www.biorxiv.org/content/10.1101/2021.04.09.439198v1). In my opinion, this manuscript lacks a more detailed analysis of the ATR signaling on DNA repair and chromosome axis structure, which are fundamental to understand the meiotic prophase. Secondly, the manuscript falls short of providing novel insights about ATR roles during the meiotic prophase. As ATR function on the meiotic prophase has been extensively studied, the ATR phosphoproteome should provide either some clues about possible novel functions ATR may do during the meiotic prophase or spermatogenesis, or provide a mechanistic explanation of how ATR performs its meiotic functions (e.g., meiotic sex chromosome inactivation or meiotic recombination). The final section of the results is an attempt at doing sol, but to me, the data provided only suppose a small incremental advance in our knowledge of how ATR promotes MSCI. I would have liked the authors to expand this section to prove the utility of the data.

We agree with the reviewer that it would be very interesting to address more details of the roles of ATR in meiosis and the underlying molecular mechanisms. However, we feel this would require significantly additional effort and time, which would not be realistic in the current manuscript, and is beyond the scope of this resource paper. We note that the revised version of the manuscript now reports the exciting finding that ATR is important for the proper localization of CDK2 in meiotic spreads. While the details and mechanisms remain unknown, we believe this finding, together with other reported findings in this resource paper, open new directions to study meiotic ATR signaling.

Author Response:

Evaluation Summary:

Are enzymes found in organisms that optimally grow at colder temperatures are more active than the same enzymes found in organisms that optimally grow at warmer temperatures? Here, an assessment of the catalytic constants for approximately 2200 enzymes (obtained from the BRENDA database) showed no correlation between the relative catalytic activity and the optimum growth temperature. Further support for this conclusion was obtained from the measurement of the catalytic constant from a selection of ketosteroid isomerases from organisms that optimally grow between 15 and 46 degrees centigrade. These are interesting results, although the significance with respect to earlier studies has not been clearly explained.

We have made the relationship between previous work and our work more explicit. Earlier studies have used a limited number of specific cases to compare enzyme rates from different organisms (for example, n = 28, Figure 1C, Figure 1D). In this work, we performed a systematic analysis of 2223 enzyme reactions, reducing confirmation bias, and we have clarified this point. Prior work developed physical models about enzyme catalysis but were based on data that do not appear to be representative.

Reviewer #2 (Public Review):

The authors are trying to understand how enzymes evolve to best enable organisms to adjust to changes in the temperature of their environment. The paper reports an analysis of 2223 values of kcat from the BRENDA database, for 815 organisms with known optimal growth temperatures, and for which there are at least two variants per reaction. This analysis fails to show the expected preference for values of [(kcat)cold/(kcat)warm] > 1 observed in earlier studies.

This is a useful attempt to use one large databases to gain insight into how enzymes evolve to enable organisms to adapt to changes in temperature. They have done a good job in curating the BRENDA database to identify data that meets their criteria for analysis.

There are deficiencies that should be corrected.

(1) The first concerns the reported values of [(kcat)cold/kcat)warm]. Figure 1D shows "Rate comparisons of warm-adapted and cold-adapted enzyme variants made at identical temperatures." I think that it is important that these kinetic parameters be reported for catalysis at a common temperature, but it is not clear to me that is the case for the author's analysis. For example, they write beginning on line 234 that "The rate ratio kcold/kwarm per reaction was determined by dividing rate of the enzyme from the organism with the minimum TGrowth by the rate of the enzyme from organism with the maximum TGrowth." My reading of this sentence is that these rate constants kcat [not rates] were determined individually at the organisms optimal growth temperatures, and not at identical temperatures as reported in Figure 1D. This will complicate the author's interpretation of the two sets of results.

Analysis of kinetic parameters at a common temperature supports the conclusions of this work.

(2) The author's fail to present a clear physical model to use in analyzing these results.

For example, they write on line 35 that: "According to the rate compensation model of temperature adaptation, this challenge is met by cold-adapted enzyme variants providing more rate enhancement than the corresponding warm-adapted variants (Figure 1A)"

I cannot recall hearing the term rate compensation model, but am familiar with discussions on the differences in properties of enzymes isolated from organisms that have adapted to warm and cold environments. The term cold adapted enzymes is not appropriate, because it is the organism not the enzyme, that adapts to the change to a cold environment. This is accomplished through the natural selection of enzymes with kinetic parameters, stability, etc. that optimize the organisms chances of survival in a cold climate. The kinetic parameters for essentially all enzymes will decrease with decreasing temperature. The most highly evolved metabolic enzymes have kinetic parameters kcat/Km close to the diffusion controlled limit, because this optimizes energy production from metabolism. A decrease in temperature will cause the values of kcat and therefore kcat/Km for these enzymes to decrease, to the detriment of the organism. This may be overcome by selection of enzymes with values of kcat/Km close to that observed for the parent [unevolved] organism. The result is that larger kinetic parameters kcat, for catalysis at a common temperature, will be observed for enzymes isolated from the cold-adapted, compared to the unevolved parent organism. This simple application of Darwin's principals of natural selection is strongly supported by the data reported in Figure 1D.

The reviewer presents a model that presumes that there would be greater selection to optimize energy production. This is also the model supported by the prior data (Figure 1D).

However, the more extensive data in our work do not support the model that the reviewer notes and that has been widely accepted in the literature –this is the central conclusion of this work and we have attempted to clarify this, as noted above. The strict Darwinian interpretation for our observations is that there is not a strong selection for enzyme rates to be maximized, as described in the Discussion.

An alternative model, consistent with the data we present, is that there are different selective pressures on enzymes than rate maximization. We note that it is possible that different metabolic strategies may be more advantageous at different life stages or in different communities (see Wortel et al., 2018, now cited in our main text). These models can be tested experimentally –e.g., by examining how variations of a weak-link enzyme fare over time under different growth conditions. There is much more to be learned from linking the properties of enzymes to evolution, and we expect the relationship between fundamental rate constants and selection to be complex, fascinating and important.

We use the term rate compensation to refer to the phenomenon and not the physical explanation; there is no need for a physical explanation of a phenomenon in the absence of evidence for the phenomenon itself. We have clarified that we have introduced this term in the Introduction: According to what we term the rate compensation model of temperature adaptation, this challenge has been suggested to be met by cold-adapted enzyme variants providing more rate enhancement than the corresponding warm-adapted variants (Figure 1A).

We use the term “cold-adapted” in agreement with literature usage: from an organism that is cold adapted. We have clarified this language usage: We use the term “cold-adapted variant” to refer to an enzyme from an organism annotated with lower TGrowth values.

Finally, “cold-adapted” is not synonymous with “having faster enzymes”, which is often how it is used in the literature and how it is implied in the reviewer’s model.

(3) The paper alludes to, but does not clearly explain extensions of these ideas that are based on one model for how enzymes work. Enzymes often undergo large conformational changes during their catalytic cycle, and so must have sufficient flexibility for these changes to occur with rate constants that support catalysis. This predicts that the enhancement for catalysis observed for enzymes from cold-adapted organisms, might best be achieved through mutations that favor an increase in protein flexibility. There will also be natural selection of enzymes for thermophilic organisms that optimize the organisms chances of survival in a hot climate, where heat denaturation of the protein catalyst is minimized through the selection of stiffer protein catalysts. This analysis predicts a decrease in enzyme flexibility with increasing preferred growth temperature, that might give rise to an increase in protein stability with increasing optimal growth temperature.

We agree that there are many fascinating aspects of temperature adaptation at the level of individual enzymes, their mechanisms, and their particular rate-limiting steps that remain to be explored. These were not the subject of our study. The goal of our manuscript was to test the previously presented rate compensation model of enzyme cold adaptation.

(4) The authors should consider the possibility that the pressure to compensate for the cold-induced decrease in kcat for enzymes from cold-adapted organism will be strongest for highly evolved metabolic enzymes with values of kcat/Km close to the diffusion controlled limit. In cases where the enzyme starts out as less than perfect, an organism adapting to the cold might derive smaller, or even negligible advantages, from natural-selection of enzymes with enhanced kinetic parameters. For example, the organism might also minimize the effect of this change in kinetic parameter, by an adjustment or diversion of flux through the networks of metabolic pathways in which the enzyme functions. One possible explanation for the weak correlation observed between kcat and Tgrowth for ketosteroid isomerase is that the organisms studied gain little from optimization of the activity of this enzyme in cold-adapted organisms. One risk in the use of the larger BRENDA database may be the failure to account for differences in the pressure for enzymes to evolve to enable organisms adapt to cold environments.

We considered these and additional models. For example, interestingly, the opposite of what the reviewer proposed has been suggested in the literature –that the slowest enzymes (“least perfect”) are under the heaviest selection pressure for optimization (see Noda-Garcia et al., 2018). Although our data indicates that temperature exerts a weaker force on enzyme activity than previously proposed, it is indeed possible that subgroups of enzymes do indeed adapt to temperature through changes in activity. Deciphering this and other pressures is an important future challenge. We did not parse the data in this report out of concerns for “p-hacking” or multiple hypothesis testing.

Reviewer #3 (Public Review):

Enzyme catalysis underlies all living processes. Understanding the effects of temperature on enzymes is important in understanding how they are adapted to particular environmental conditions, and also relates to the response of organisms and even ecosystems to changes in temperature. The essential question is: what determines optimal growth rates of organisms, and the optimal temperature of other biological processes? Two potentially important factors are enzyme stability and catalytic activity.

This manuscript collates data from previous investigations and presents new results on KSI variants, aiming to look at the interesting question of what factors are important in relating enzyme activity and stability to optimum growth temperatures of organisms. It presents a useful survey of published data, particularly focusing on the enzyme ketosteroid isomerase (KSI) for which new resluts for a number of variants are presented, building on nice recent work by this group. The main finding in this manuscript is that enzyme optimum temperatures do not correlate well with enzyme activity. This has been found also previously. The manuscript provides quite an extensive analysis and is consistent with previous results and findings. There is useful information in this manuscript, and the compilation of data will be useful to the community, but some crucial aspects and recent relevant work are not covered, and the discussion is limited. The analysis does not identify any relevant determinant of optimum temperature, and the focus on a single temperature in each case may be misleading.

We do not agree that our analysis is “misleading.” We would characterize the prior analysis based on a small number of examples that were not randomly selected as potentially misleading. In contrast, we tested the prior conclusions with all relevant data that are available. We also highlight the power of collecting more data by further reporting the rate enhancement of 20 enzyme variants in depth. Temperature compensation through activity may still occur in specific settings, as we have noted in the Discussion.

We agree with Reviewer #3 about the vast potential to use temperature dependencies to relate to evolutionary pressures and adaptations from molecules to organisms. This is a prime area for future investigation.

Previous analyses have shown that optimum rates of enzymes do not correlate with optimal growth temperatures (e.g. Elias et al (2014) Trends in Biochemical Sciences 39, 299; Peterson (2004) Journal of Biological Chemistry 279, 20717; Thomas & Scopes (1998) Biochemical Journal 330, 1087; Lee et al (2007) FASEB Journal 21, 1934). This is particularly notable for psychrophilic (cold adapted) enzymes, but is also apparent from the fact that enzymes from the same organism often have quite different optimum temperatures. The data collected in the current manuscript are consistent with previous analyses and so are usefully confirming of this. The authors note that optimal growth temperatures may not correlate with activity for a number of reasons, including that the individual enzyme rate may not be under evolutionary pressure. Also, obviously, as noted by the authors, factors other than temperature are also important in enzyme evolution.

We agree that it is obvious that factors other than temperature are important in evolution, but here we address whether the adaptation to temperature is accompanied by a common response. As noted, more catalysis for organisms at lower temperature was concluded previously and (as noted by Reviewer #2) is expected. However, this conclusion, upon further analysis (carried out herein) appears not to hold. Thus, even when organisms are adapting to temperature, other factors appear to be dominant. This was not previously known. The analyses the reviewer notes refer to thermal parameters derived from the temperature dependence of the rate constant for a given enzyme as a function of temperature, rather than what is addressed herein –the relative rate constant for enzymes from organisms with different growth temperatures.

There is somewhat better correlation of enzyme stability with optimum growth temperatures, but it is not strong. Therefore, other factors must be important in determining optimum growth temperatures. The authors briefly mention some possibilities. One factor is that a given enzyme may not be a bottleneck in a metabolic pathway. It is not clear that KSI is in fact a metabolic limiter. Also, for many metabolic pathways, it may be essential to consider the kinetics of the pathway as a whole, which may not be determined by a single enzyme. Directly relevant here is the recent proposal of the 'inflection point hypothesis', which provides an explanation of these observations (Prentice et al. Biochemistry (2020) 59, 3562), which the authors do not mention, and may not be aware of. This hypothesis proposes that, rather than alignment of optimum temperatures or stabilities, rather the inflection points of enzymes in a metabolic pathways are aligned at the mean environmental temperature for the organism. This has the effect of coordinating relative enzyme rates and preventing metabolic disruption as temperature fluctuates. Also relevant here is that the response of metabolic pathways in general is not determined solely by a single enzyme. Prentice et al. show that, in general, the temperature-dependent properties of each enzyme in the pathway is important in determining the temperature dependence of the whole pathway.

We thank Reviewer #3 for bringing this work to our attention and we have included it in the revised manuscript. This paper points out additional complexities regarding metabolic coordination of relative enzyme rates, enhancing points made in the Discussion.

It is certainly important to understand what molecular features determine the temperature dependence of enzyme activity and its relationship to stability. Some previous proposals are mentioned in the manuscript. One important factor at the molecular level, mentioned by the authors, is work of Åqvist, Brandsval and coworkers, who have convincingly shown that activation entropy and enthalpy differ significantly between psychrophilic enzymes and their mesophilic and thermophilic counterparts. For small soluble enzymes, this is particularly due to changes at the enzyme surface, which may also affect stability. As mentioned by the authors, there have been many proposals over the years that suggest a relationship between stability and activity, though there is not a simple general relationship.

The cited study is based on molecular dynamics simulations and underlying potentials which can provide models to be tested via experiment. Our analyses relate to this model in that they suggest that rate compensation (to temperature) is not general and so a universal linkage of temperature, flexibility and catalysis is not expected.

Also directly relevant for the discussion here is what factors limit enzyme activity as temperature increases. The traditional view is that loss of activity is due to protein unfolding at high temperatures (the poor correlation of stability with growth temperatures found here indicates that this cannot be a general explanation). There is increasing evidence that this simple picture is wrong (see e.g. Daniel & Danson. (2010) Trends in Biochemical Sciences 35, 584). This behavior may be accounted for by conformational (e.g. two state) effects as proposed by Danson et al, distinct from the 'flexibility' proposals mentioned in the supporting information here. The introduction of the manuscript here states that "reaction rates are reduced at lower temperatures" , which might naively seem obvious but actually is not universally true, many reactions do not display simple Arrhenius-type behavior (see e.g. Kohen and Truhlar PNAS 2001 98 848). Many enzymes show a temperature of optimum activity, i.e. activity drops above the optimum temperature but before unfolding occurs. As the authors note, Arcus et al. show that this can be accounted for by an activation heat capacity, significantly larger in psychrophiles. Signatures of this behavior are apparent at the large scale (e.g. Schipper et al Global Change Biol. 2014 20 3578; Alster et al (2016) Front. Microbiol. 7:1821) and it appears to be generally important.

We also are enthralled by the many proposals put forward for the physical and thermodynamic behavior of enzymes and we look forward to rigorous tests of the predictions of these models. Like Reviewer #3, we expect that there are many different features and properties of enzymes to discover!

Biophysics Colab

Consolidated peer review report (30 November 2021)

GENERAL ASSESSMENT

The TMEM16 family of membrane proteins have been shown to function as calcium-activated chloride channels and lipid scramblases. In recent years, X-ray and cryo-EM structures have been solved for TMEM16 proteins in ligand-free and ligand-bound conformations, providing valuable structural information on their functional duality and activation mechanisms. It is largely accepted that the catalytic site (termed subunit groove or cavity) is mostly shielded from the membrane in the ligand-free TMEM16 scramblases. Calcium binding induces a conformational rearrangement of the cavity-lining helices, opening the groove to the surrounding membrane. Since the groove is hydrophilic, it was proposed that it serves as a permeation pathway for lipid headgroups while the hydrophobic lipid tails remain embedded into the hydrophobic membrane core, which has been termed the "credit card" mechanism of lipid scrambling. Additionally, structures of several TMEM16 homologs in lipid nanodiscs revealed that these proteins deform the lipid bilayer in the vicinity of the subunit cavity by bending and thinning the membrane, irrespective of the presence of the activating ligand calcium. Functional experiments also suggested that lipids can be scrambled outside of the open subunit cavity and that local protein-induced membrane deformation is critical for lipid scrambling.

In the present study, Falzone and colleagues further address the mechanisms of lipid scrambling using single particle cryo-EM and liposome-based functional assays. Firstly, the authors solved the structure of a calcium-bound fungal homolog, afTMEM16, in nanodiscs with a lipid composition where the protein is maximally active. Although similar structures were obtained before, this new structure has the highest resolution thus far, representing > 1 Å improvement! The structure is beautiful and is a major achievement, which enabled the authors to resolve individual lipids and their interaction with the protein around the subunit cavity, whereas in previous structures unresolved non-protein densities were observed passing through the groove. The authors also solved a number of structures with and without calcium in lipid compositions that promote (thinner lipid bilayers) or suppress (thicker lipid bilayers) scrambling. The authors show that afTMEM16 can scramble lipids while the subunit groove remains closed, a phenomenon that is further enhanced in thinner membranes, whereas in thicker membranes scrambling is suppressed even though the groove is open. We particularly appreciated how different software packages and processing strategies were used to rigorously identify structural heterogeneity in their cryo-EM data. Remarkably, mutations of residues lining the subunit cavity and interacting with lipids do not appear to have dramatic effects on scrambling rates, which suggests that lipids do not need to interact with the protein to be scrambled. Thus, the overall conclusion of the study is that membrane thinning by TMEM16 scramblases in their calcium-free conformation is enough to induce lipid scrambling, and that the groove opening induced by calcium binding further enhances membrane deformation, promoting faster scrambling. By contrast, in thicker membranes the protein fails to sufficiently deform the bilayer and scrambling is suppressed, even when the subunit groove is open. The present study provides unprecedented structural information on the interaction of lipids with afTMEM16 and new evidence that lipids can be scrambled outside of the groove.

The findings and conclusions presented here help to explain why TMEM16 scramblases can transport lipids with headgroups much bigger than the dimensions of the subunit cavity and why structures of some of the other scramblases (opsins, Xkrs and mammalian homolog TMEM16F) lack the obvious hydrophilic groove seen in fungal TMEM16 scramblases. Overall, this is a well-rounded study with an exceptional amount of high-quality cryo-EM data and functional experiments supporting the conclusions.

RECOMMENDATIONS

Revisions essential for endorsement:

1) The resolved lipids binding within the groove in the first structure might be seen by some as supporting the credit card mechanism as it definitively demonstrates that lipids reside within the groove. While the authors provide evidence that lipids can permeate outside the groove in this and earlier work, as far as we can tell, none of that would preclude permeation through the groove if it doesn't require specific interactions between lipids and sidechains in the protein. The presentation might be improved with a somewhat more circumspect and nuanced exposition of the new data and how it can be understood with earlier results. Might the complex composition of native lipid membranes influence where and by what mechanism lipid movement between leaflets is catalysed by TMEM16 proteins?

2) The quality of lipid densities in cryo-EM structures is greatly affected by the number of particles used and the resolution obtained during refinement and it is therefore not surprising that the beautiful lipid densities observed here in the structure of afTMEM16 in lipid nanodiscs in the presence of calcium refined to 2.3 Å are not all observed in subsequent structures with lower resolution. This is true not only for the P lipids near the groove, but for those D lipids bound near the dimer interface, which is a stable region of the protein that does not change conformation. To be cautious, the authors should avoid resting any conclusions on the absence of lipid densities in the lower resolution structures. For example, on pg 15 the authors seem to be interpreting the absence of density for C22 lipids.

3) The presentation of structural interactions between lipids and residues near the groove of the protein could be improved in the figures. A panel like Fig. 1J but for the groove would help, but it would be good to see expanded perspectives in the form of a supplementary figure where residues around the headgroup of the lipids are shown along with EM maps so the quality of the structural information for both lipids and side chains can be better appreciated. The preprint does have a lot of images of the lipids and the protein, but not in a way that enables the reader to quickly grasp the nature of interactions between side chains and lipid moieties for themselves, and we feel that close-ups of individual lipids as suggested above would help. It is also not clear what the authors mean by "lipid headgroup". Have the authors only considered interactions of the phospholipid phosphate group with protein residues? It would be helpful if the authors could clarify this in the manuscript and say whether other types of interactions were considered. It would also be nice to include a close-up view of D511A/E514A in 0.5 mM calcium with cryo-EM density to demonstrate the absence of bound calcium ions.

4) The functional data in Fig 2, 3 and 4 are also not discussed in much detail and it would help if the authors could expand the presentation. Although scrambling in the presence of a very high concentration of calcium is not dramatically altered by any of the mutations, there is quite a lot going on in the absence of calcium and very little is said about these results. For example, differences in the scrambling rates can be observed with some mutants in the presence and absence of calcium in figures 2E and 3E, but statistical analysis would be required to know if the differences between mutants are significant. The differences in scrambling rates with different lipids are also not discussed (e.g. Fig. 4A) It would help if the authors could discuss what is the margin of error in the scrambling assay, and point to some concrete examples from their earlier work on this specific scramblase where mutants have a large impact on scrambling activity in their assay. Have the authors tried intermediate more physiologically relevant concentrations of calcium to see if the mutants have discernible effects under those conditions?

5) It is quite intriguing that the mutations in the subunit groove of afTMEM16 have little effect on scrambling activity. The authors propose that the groove-lining residues are not directly involved in lipid coordination even though their structure suggests that they do and there is a wealth of functional studies and MD simulations on various other TMEM16 homologs suggesting otherwise. The authors' suggestion that mutations probably affect the equilibrium between open and closed conformations of the groove in other homologs but not in afTMEM16 is logical, however, there are some discrepancies. To name a few examples, if indeed this is the case, nhTMEM16 mutants with closed groove should still have significant basal scrambling, by extrapolation from afTMEM16 data. Yet, some of the nhTMEM16 mutants (E313/E318/R432 mutants) have no activity at all, or no basal scrambling activity (Y439A) (Lee et al, 2018). Would you expect that point mutations within the subunit groove remove the ability of the protein to deform the membrane in its closed conformation? Might the groove have intermediate conformations between closed and fully open where the mutants studied might have more impact in afTMEM16? Further, mutating some of the residues on the scrambling domain of TMEM16 affected externalization of some lipid species, but not internalization etc. (Gyobu et al, 2017), which should not be the case if the interaction of the protein with the lipids is completely unnecessary for lipid scrambling. While investigating this question further would require follow-up structural studies on other TMEM16 homologs and is outside of the scope of this study, we think that the manuscript would benefit from a more extensive discussion on contradicting results and alternative interpretations. The authors might want to consider the possibility that there may be substantial variations in how different scramblases function. afTMEM16 has high constitutive activity in the absence of calcium, while at least TMEM16F does not. Additionally, the extent to which scrambling is promoted by calcium varies, as mammalian scramblases might need other cellular factors to be activated. Also, the extent to which scramblases are seen to distort the membrane is highly variable, as again seen in TMEM16F structures. Might some of these differences imply that key aspects of the mechanism of scrambling (e.g. thinning of the membrane or whether lipids scramble inside or outside the groove) are not the same for all scramblases? This might be one way to organize the discussion to help reconcile some of the seemingly divergent findings in the field.

6) The authors should correct the Ramachandran outliers in C18/calcium and C22/calcium structures.

Additional suggestions for the authors to consider:

1) In several instances the authors conceptualize hypothetical mechanisms to set up experiments and frame their interpretations, which is not always the most straightforward way to communicate findings and what they reveal. The 'conveyor belt mechanism' introduced on page 10 is never fully defined in a way that helps the reader to understand what the functional effects of the mutants teach us. Might it be easier to set up the experiment by asking whether the interactions between sidechains that apparently interact with lipid headgroups in the structure play a critical role in scrambling, present the results and then conclude that they do not appear to? Collectively the functional effects of mutants do appear to suggest that specific side chain interactions are not critical for scrambling, but the conceptualized mechanism here makes the conclusions come across as unnecessarily forced. The credit-card mechanism has been formally introduced and discussed in the field but has already been shot down in earlier work from the group and seems overly simplistic if we already know that scrambling can occur both inside and outside the groove from earlier studies. Just something for the authors to think about.

2) The uninitiated reader would greatly benefit from more of an introduction to the functional scrambling assay in the results and material and methods section so they can understand the results being presented. In the Material and methods, the authors mentioned: "All conditions were tested side by side with a control preparation", perhaps add here what exactly served as control – wild type protein in C18 lipids? It would be valuable to include information on the reconstitution efficiency between their preparations (WT in different lipid compositions and WT vs mutants). these if possible.

3) Also, does the C18/calcium cryo-EM structure have sufficient resolution to distinguish between specific phospholipids (PG or PC) at the D1-D9 or P1-P7 positions? It would be particularly valuable if the authors could comment on whether PG or PC are observed in the D and P positions, or which lipids are lining the groove (P3-P6).

4) While not essential, it would be interesting if the authors could perform the assay on the mutants with a more prominent effect in the absence of calcium (e.g. E310A, Y319A/F322A/K428A) with several additional calcium concentrations.

5) The authors mentioned that the interaction of C22 lipids with the pathway helices is weaker than those of C18 lipids, which reflects the energy cost associated with distorting the longer lipids (page 15). However, they claimed that the interaction between the lipids and residues is not important for scrambling, which seems contradictory.

REVIEWING TEAM

Reviewed by:

Angela Ballesteros, Research Fellow (K.J. Swartz lab, NINDS, USA): structural biology (X-ray crystallography), membrane protein function, lipid scrambling, cell biology, fluorescence microscopy

Valeria Kalienkova, Postdoctoral Fellow (C. Paulino lab, University of Groningen, The Netherlands): membrane structural biology (X-ray crystallography and cryo-EM), membrane transport and lipid scrambling

Kenton J. Swartz, Senior Investigator, NINDS, USA: ion channel structure and mechanisms, chemical biology and biophysics, electrophysiology and fluorescence spectroscopy

Curated by:

Kenton J. Swartz, Senior Investigator, NINDS, USA

(This consolidated report is a result of peer review conducted by Biophysics Colab on version 1 of this preprint. Minor corrections and presentational issues have been omitted for brevity.)

SciScore for 10.1101/2021.12.10.21267582: (What is this?)

Please note, not all rigor criteria are appropriate for all manuscripts.

Table 1: Rigor

Table 2: Resources

No key resources detected.

Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

As mentioned, this study has limitations, first it used descriptive statistical methods, was small in size and secondly it did not use placebo for control and was not blinded. Nevertheless, the design was still considered valid to provide essential evidence for the preventive use of Echinacea during the COVID-19 pandemic for the following reasons: a first parameter was defined as incidence of (viral) RTIs, for which sample size calculation found sufficient statistical power of >80% for 120 included subjects. The lack of blinding/placebo might be considered a methodological weakness, but it can be assumed that the placebo effect/knowledge of therapy have only limited effects on detection of viral pathogens in NP/OP samples and blood serum. We therefore think that the study design was suitable to address the research question on antiviral effects of Echinaforce in vivo.

Results from TrialIdentifier: We found the following clinical trial numbers in your paper:<br><table><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Identifier</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Status</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Title</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT05002179</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Completed</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Echinaforce Study to Investigate Explorative Pharmacology an…</td></tr></table>

Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

Results from JetFighter: We did not find any issues relating to colormaps.

• Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
• Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
• Thank you for including a protocol registration statement.

Results from scite Reference Check: We found no unreliable references.

About SciScore

SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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

Learn more at Review Commons

Reply to the reviewers

Response to reviewers

Reviewer #1

I believe that this is a very sound and authoritative study. The analysis of all data seems appropriate and robust, and many connections between the data (and subsets of data) and their possible interpretations have been considered. In fact, in the massive Results section, some interpretations are supported by cited references (this is not meant as a critique). However, I wonder about the length of the Results section, and the balance between it and the relatively short Discussion section. It is difficult for me to nail down any part of Results that might be shortened, as I could not find clear redundancies. I also think that the level of speculation is absolutely warranted, and I did not find excessive claims being made to this or that end. Rather, I suggest to broaden the perspective somewhat (in their Discussion; see below under Significance), which might allow people with a less mechanistic perspective to grasp the potential relevance of this work for non-model plant systems studied mostly by evolutionary geneticists.

Response: We thank the reviewer for their kind remarks. We have spent a very large amount of time trying to streamline the results section and we are not sure if it would be possible to shorten it any further without removing critical details.

We appreciate the reviewer’s comment to add more detail to the discussion to make it more appealing to evolutionary geneticists and we have added the following lines to the discussion section: “The WISO or “weak inbreeder/strong outcrosser” model (Brandvain & Haig, 2005) emerges from the dynamics of parental conflict and parent-of-origin effects. Under this model, a parent from populations with higher levels of outcrossing is exposed to higher levels of conflict and can thus dominate the programming of maternal resource allocation in a cross with an individual from a population with lower levels of outcrossing. Such a phenomenon has been observed in numerous clades including Dalechampia, Arabidopsis, Capsella and Leavenworthia (Brandvain & Haig, 2018; İltaş et al., 2021; Lafon-Placette et al., 2018; Raunsgard et al., 2018). Intriguingly, loss of function phenotypes in the RdDM pathway are more severe in recently outcrossing species than in A.thaliana (Grover et al., 2018; Wang et al., 2020) and suggests that RNA Pol IV functions are more elaborate and important in these species. This raises the possibility that the role for RNA Pol IV and RdDM in parental conflict that we describe in A.thaliana here is likely heightened in and mediates the elevated level of parental conflict in species that are currently or have been recently outcrossing.”

One aspect that might warrant more scrutiny is the mapping of sRNA reads to the reference genome. I found the short section of this (M&M section, page 20, lines 23-25) to be too brief. It is not clear to me which of ShortStack's v3 weighting scheme the authors used, which is relevant for multi-mapping reads (see NR Johnson et al. 2016, G3). In addition, it is not mentioned whether zero mismatches were allowed. Perhaps this is described in more detail in Erdmann et al. (2017), but even if so, it deserves to be clarified here.

Response: Small RNA reads were aligned after allowing two mismatches. This was indicated in the bowtie command (‘bowtie -v 2’ where v 2 indicates two mis-matches). We have added text to expand on the meaning of the commands.

We have also expanded the commands used for ShortStack. We used the “Placement guided by uniquely mapping reads (-u)” option to divide the multi-mapping reads.

The manuscript is well-written and concise, despite the length of the Results section. The verbal clarity and absence of typos or grammatical issues is superb. I did find some of the Figures to be somewhat "un-intuitive", in the sense that it takes acute concentration for an outsider (of sorts) to gather and interpret the underlying data. This is probably due to the many cross-comparisons of differences between two genotypes on one axis and those of a different pair of genotypes on the other axis. I am not sure how this issue can be ameliorated (nor whether this is really necessary); however, from a technical point of view, all Figures and Suppl. Figures are really well-done.

Response: We thank the reviewer for their kind remarks. We have strived to make the figures easier to understand but we are aware that the figures do require a lot of concentration. We haven’t found an easy way to fix this. We thank the reviewer for patiently going through the figures.

The list of references seems adequate in terms of citing relevant (both older and very recent) publications. However, almost all cited papers concern Arabidopsis or other model species; I suggest to consider adding a few relevant studies on non-Brassicaceae (whether considered model taxa or not), in conjunction with my suggestion (in Significance) to potentially broaden the scope by searching for natural phenomena that also involve parent-of-origin effects on endosperm/seed development. Curiously, many of the references are "incomplete" in the sense of stopping with the journal's name, then stating the doi, i.e. they lack volume numbers and page/article numbers. This should be harmonized throughout.

Response: We have added references to non-Brassicaceae species and have also fixed the references.

Reviewer #2: This manuscript provides evidence that a loss of either the maternal or paternal copy of NRPD1 have different, and sometime opposite, effects on the accumulation of small RNAs and on expression of a subset of genes, with a loss of the maternal copy having more substantial effects. The manuscript is well written, and the conclusions, as far as they go, are justified by the data, which are effectively presented. The overall effect is subtle but informative and according to the authors support a parental conflict model for imprinting. The experiments failed to find a smoking gun in the form of a mechanism to explain how or why the maternal and paternal alleles have different effects and the explanation for a lack of clear phenotypic differences was reasonable, but untested. I would have like to see it tested by looking in a plant species that is outcrossing and highly polymorphic. However, I do appreciate that the observation that the male and female alleles can have distinct effect when mutant is an important clue. My specific comments below may reflect confusion on my part, rather than real issues. If that is that I hope that confusion can aid in clarifying what are in places quite subtle points.

Response: We thank the reviewer for their comments. We agree that it would be potentially informative to do similar experiments in an outcrossing species but that this is beyond the scope of this manuscript. Additionally, loss of NRPD1 or other components of the RdDM pathway has dramatic effects on gametogenesis in some examined outcrossing species(Grover et al., 2018; Wang et al., 2020), which could prevent the detection of subtle parent-of-origin effects on seed development.

Page 6, last paragraph: "Because the endosperm is triploid, in these comparisons there are 3 (wild-type), 2 (pat nrpd1+/-), 1 (mat nrpd1+/-) and 0 (nrpd1-/-) functional NRPD1 alleles in the endosperm. However, NRPD1 is a paternally expressed imprinted gene in wild-type Ler x Col endosperm and the single paternal allele contributes 62% of the NRPD1 transcript whereas 38% comes from the two maternal alleles (Pignatta et al., 2014). Consistent with paternal allele bias in NPRD1 expression, mRNA-Seq data shows that NRPD1 is expressed at 42% of wild- type levels in pat nrpd1+/- and at 91% of wild-type levels in mat nrpd1+/- (Supplementary Table 6)". I would think this would really complicate the analysis. Should all of the dosage values include NPRD1 imprinting values? That is to say, expressed in terms of expression values? This is also a bit confusing. The maternal copies together express 38% of the transcript, so why isn't the mat nrpd1 at 68%, rather than 91%? In any event, given this imprinting and differences in dosage of the male and female it appears that two variables, parental origin and expression levels are being compared. Since 91% is awfully close to 100%, are the mat pat comparisons really just comparing low with nearly normal expression of NRPD1? And actually, given that, the outsized effect of the mat nrpd1 +/- is even more striking.

Response: We included the details of dosage rather than imprinting values because the potential for buffering of expression upon loss of one allele could not be discounted. Indeed, we do find that the endosperm transcriptome buffers against the loss of the maternal or paternal alleles (Supplementary Table 6). The reviewer is correct in pointing out that the outsized effect of mat nrpd1+/- on gene expression is even more striking, and strongly supports our view that these effects are parental rather than endospermic.

To reduce confusion in this section, we removed the details about 38% maternal allele transcripts obtained from our previous study, and instead report only the observed values from this study (which are also consistent with the previously reported paternally-biased expression of NRPD1 in endosperm).

Page 4, Line 16. I'm afraid it's still a bit difficult to understand what was being compared what in this section. Please clarify.

Response: The authors in this previously published study compared sRNAs obtained from wild-type whole seeds (which consists of three different tissues, including endosperm) with mutant endosperm. We are pointing out that the difference in tissue composition makes the effect of nrpd1 mutation hard to disentangle from the tissue differences between the two genotypes.

Page 5, Line 5. I'm sure this is fine, but it's not entirely clear what is from the previously published paper and what is reanalysis here. All the crosses and measurements were made then, but not organized in this way?

Response: This data was indeed previously published. In that analysis, we had pooled results from different crosses and calculated significance between genotypes using chi-square tests. During a later study (Satyaki and Gehring, 2019), we realized that we were losing information by ignoring the seed abortion values per cross. So, a reanalysis of that data on a cross by cross basis allowed us to find strong evidence for maternal and paternal effects.

Page 6, Line 26. This is an excellent dosage series, but it's complicated by imprinting. So it's not 3, 2, 1, 0 effective copies. If we set the paternal copy at ~1 and each maternal at ~0.1, then it's 1.2 (wild type), 0.20 (pat nrpd1+/-), 1 (mat nrpd1+/-), and 0 (nrpd1-/-).

Response: At the genomic DNA level, its 3, 2,1 and 0 doses. The reviewer’s comment on the transcriptional dose is not clear to us. Based on measured gene expression levels, relative wild-type NRPD1 transcriptional dose =1, pat nrpd1+/- is 0.42, and mat nrpd1+/- is 0.91.

Page 6, line 31. Is the main thing we are comparing the difference between expression at 42% verses 91% of wild type?

Response: We are using the small RNA-seq data alongside the mRNA-seq data to argue that loss of mat and pat nrpd1+/- have no impact on overall Pol IV activity in endosperm (as measured by small RNA production). A nrpd1 heterozygous endosperm has almost the same small RNA profile as a wild-type endosperm. Thus any effects seen in the endosperm, including the effects on mRNA expression described later in the manuscript, are likely parental rather than zygotic endospermic effects.

Page 7, line 11. So, the overall effect in either direction on smRNA gene targets was really quite small, and I'm guessing the effect on gene expression was even smaller.

Response: The effects of loss of maternal or paternal Pol IV on sRNAs was indeed small (Fig. 1/Fig. S3). Effect of loss of maternal Pol IV on gene expression was substantially large and distinct from the relatively small impacts observed upon loss of paternal Pol IV (Fig. 3) This observation supports the view that Pol IV mediates parent-of-origin effects on gene expression.

Page 7, line 17. I take it that it is this difference, rather than the overall numbers that is of interest.

Response: Correct. The lack of a relationship between sRNAs impacted upon loss of mat and pat nrpd1 is additionally suggestive of parent-of-origin effects

Page 9, line 2. Really interesting, since one might expect that these are methylated loci that would be expected to be fed into any existing embryo maintenance methylation pathway. Surprising that they are maintained independently.

Response: It is indeed surprising that Pol IV activity in parents can have different impacts on sRNAs in the endosperm. It should be noted though, that as described in Erdmann et al 2017 and in this paper later on, many endosperm sRNA loci are in fact not associated with endosperm DNA methylation. In addition, sRNA loci that are dependent on paternal Pol IV activity are more likely to be associated with DNA methylation than are sRNA loci associated with maternal Pol IV activity. These points have been described in Figure S8.

Page 9, line 22. Proportion of total imprinted genes? Did the mutant obviate/enhance the imprinting?

Response: We have modified the manuscript to describe effects on imprinted genes: “ The expression of imprinted genes is known to be regulated epigenetically in endosperm. In mat nrpd1+/- imprinted genes were more likely to be mis-regulated than expected by chance (hypergeometric test p-15) – 15 out of 43 paternally expressed and 45 out of 128 maternally expressed imprinted genes were mis-regulated in mat nrpd1+/- while two maternally expressed imprinted genes but no paternally expressed imprinted genes were mis-regulated in pat nrpd1+/- (Table S6).” We have also added a new supplementary figure (Fig. S6) that describes the impacts of NRPD1 loss of imprinted gene expression.

Page 9, line 27. How could 2) occur in the homozygous mutant?

Response: Loss of NRPD1 may impact gene expression in both parents. When the nrpd1-/- mutant endosperm is investigated, we are also examining the consequences of the inheritance of these disrupted gene expression states. We refer to this as epistatic interactions of mat and pat nrpd1.

Page 10, line 9. Interesting!

Response: We strongly agree!

Page 10, line 11. Is this 2.7 versus 2.18 significant because it's statistically significant, or because it's conceptually significant?

Response: We are pointing out that the 2.7-fold value is quite similar to the predicted value of 2.18-fold, which is arrived at by simply summing the effects of mat nrpd1 and pat nrpd1. This is a conceptually significant point.

Are the examples in 3D representative, or the most convincing examples? And a big difference in ROS1 is of some concern, since that may well be expected to affect imprinting indirectly. I know I'm being picky here, but the pattern is so intriguing I'd be worried about confirmation bias.

Response: The examples in 3D are representative for those genes with significant changes in expression in both mat and pat nrpd1, and other genes also behave similarly. The antagonistic effect described for 3D can also be observed as a much broader trend affecting hundreds of genes to varying extents in Fig 3C and 3E-H. The concern about ROS1 is not clear to us but we agree that an effect of ROS1 may be one way that NRPD1 controls gene expression.

Page 10, line 18. Ok, but 0.123 is a pretty subtle negative correlation. Although I do appreciate that it clearly is not a positive correlation. If I'm understanding correctly, this was the "aha" moment, because it's exactly what one might expect of NRPD1 from the mother and father or working at cross purposes. But the numbers are getting awfully small here.

Response: It is unclear how to calibrate our expectations of effect sizes considering that our study is the first (to our knowledge) to make such a measurement involving gene expression in parental conflict. A review of the few empirical examples of parental conflict’s impact on seeds shows that parental conflict may drive small changes in seed size (Brandvain and Haig, 2018).

The evolution of quantitative traits maybe driven by selection for large effects at a small number of loci and/or by selection of small effects at a large number of loci. In a similar vein, parental conflict can impact seed phenotypes either via large effects at a few loci or via small effects at a large number of loci. Our analysis described in Fig 3D-H can fit either possibility. Large effects can be found at a few loci such as SUC2 and PICC (Fig. 3D). Smaller antagonistic effects can be found at hundreds of loci as shown in Figure 5A. The negative correlation described in this figure can be observed even upon dropping the genes that show a statistically significant differential expression in both mat and pat nrpd1+/- (slope after dropping genes significantly mis-regulated in both mat and pat nrpd1+/- is -0.126). In summary, a correlation of -0.123 strongly supports the existence of a widespread antagonistic regulatory effect.

Page 10, line 29. The point simply being that that other phenomenon is also significant even if the differences are that large?

Response: We are pointing out that the magnitude of the effects we see are similar to that observed for phenomenon such as dosage compensation.

Page 12. So, there is no effect on cleavage and no obvious effect on flanking siRNA clusters. The suspense is building...

Page 12, line 24. And not in potential regulatory regions? CNSs?

Response: We did not identify a significant enrichment for differentially methylated regions in regulatory regions. We used the relative distance function in bedtools (https://bedtools.readthedocs.io/en/latest/content/tools/reldist.html) to calculate the relationship between the genomic location of DMRs and genomic location of a differentially expressed gene. This analysis was chosen as it does not make a priori assumptions about the size of the regulatory region of a gene. A broad association between DMRs and differentially expressed genes would be indicated by a frequency far greater than 0.02. We show the results of this analysis in Fig. S8F; we find no evidence for significant enrichment of DMRs in the regulatory regions of differentially expressed genes.

Page 12, line 28. I guess it depend on whether or not the changes are in regulatory sequences no immediately apparent as part of the gene, doesn't it?

Response: We examined DNA methylation over genes here because in endosperm, unlike in other tissues, many small RNAs are genic. Moreover, DNA methylation within the gene may control transcript abundance (Eimer et al., 2018; Klosinska et al., 2016). We have also examined regulatory regions adjacent to genes in Fig S8F and found no effect.

Line 13, line 2. Not sure it's that important, but couldn't you chop all of these genes in half and see if they are no longer significant collectively?

Response: We do not think that this will provide a useful insight.

Page 14, line 15. I'm afraid I'm getting confused here with the terms cis and trans here. Just to be clear, cis means a direct effect of small RNAs that are dependent on NRPD1 on a gene and trans means anything else? But in this context, it's not clear that is what is meant. Do you mean that gene expression is determined and preset in the gametophyte? What are the levels of expression of NRPD1 in the two gametophytes?

Response: The reviewer’s interpretation of cis and trans is correct. However, the cis imprints may be preset in gametophytes or in the sporophytic tissues that surround or give rise to the gametophyte. Pol IV is known to be active either in gametophyte or in related sporophytic tissues in both the mother and the father(Kirkbride et al., 2019; Long et al., 2021; Olmedo-Monfil et al., 2010).

Page 14, line 19. Prior to fertilization?

Response: Yes, that is the idea. As described in the manuscript, Pol IV activity in either the parental sporophyte or gametophyte prior to fertilization could impact gene expression in the endosperm after fertilization.

Page 14, line 27. Do you mean driven by, or just associated with?

Response: In response to the comment, we have replaced the phrase “driven by” with “due to” for increased clarity. In wild-type, DOG1 is predominantly expressed from the paternal allele. In mat nrpd1+/-, the paternal allele is somewhat upregulated but the maternal allele, which is almost silent in wild-type, is highly expressed in mat nrpd1+/-.

Page 15, line 26. And this is really the issue. The primary conclusion, backed up by the lack (I'm assuming) of phenotypic differences between mat NRPD1 -/+ and pat NRPD1 +/- suggests that the observed differences in expression are not particularly important, unless the exceptional cases are informative.

Response: We are not sure whether the reviewer means “issue” in a negative, neutral, or positive light. Seed phenotypes are often subtle and we have not examined phenotypic differences in sufficient detail to comment.

Page 15, line 12. Yes, but I'm not at all clear what the mechanism for this is.

Response: We have tested and falsified multiple hypotheses to explain how Pol IV can regulate gene expression in endosperm. Considering the complex genetics and the difficulty of isolating endosperm, we have concluded that this is a matter for a future study. The point of this study is the discovery of Pol IV’s parental effects.

Page 15, line 23. Since this is a very small subset of genes, are these genes that you might expect to play a role in parental conflict?

Response: The functions of most genes in endosperm remain unknown. However, some have a likely role in conflict. SUC2 is antagonistically regulated by parental Pol IV (Fig. 3D). SUC2 transports sucrose, the key form of carbon imported into seeds from the mother (Sauer & Stolz, 1994).

Page 15, line 33. Indeed, these could be the informative exceptions.

Response: We believe the reviewer means that the identify of strongly antagonistically regulated genes may be informative in terms of thinking about these results in the context of parental genetic conflict, which we agree with.

Page 15, line 29. Hardly surprising, given that the paternal copy of NRPD1 is expressed at a higher level than the maternal copies, is it?

Response: It is actually somewhat surprising since we show in Fig. 2 that the sRNA production in mat and pat nrpd1+/- are comparable to that of wild-type. The higher contribution of NRPD1 from the paternal copy does not really explain the methylation differences

Page 16, line 1. So this is what you mean by in cis. Presetting?

Response: The reviewer’s previous interpretation of cis (acting directly at a target gene) is correct. However, the cis imprints may be preset in gametophyte or in the sporophytic tissues that surround or give rise to the gametophyte. Pol IV is known to be active in gametophytes and in related sporophytic tissues in both the mother and the father.

These are intriguing results that would benefit from a test of the hypothesis by comparing these result with those obtained in an outcrossing plant species.

Response: We agree that it would interesting and informative to perform similar experiments in an outcrossing species. However, loss of NRPD1 or other components of the the RdDM pathway have dramatic effects on gametogenesis in outcrossing species (Grover et al., 2018; Wang et al., 2020), preventing the detection of subtle parent-of-origin effects on seed development. Additionally, this would be a separate study.

Reviewer #3

We thank the reviewer for their comments.

• Expression of NRPD1 was 42% of WT in paternal nrpd1 and 91% of WT in maternal nrpd1, yet throughout the paper the effect of maternal nrpd1 was far stronger than paternal nrpd1. The authors may also want to confirm that protein levels follow the same pattern, in case protein degradation or post-transcriptional regulation may play a role.

Response: We show in Fig. 2 that sRNA production in mat and pat nrpd1+/- are similar to wild-type endosperm. This strongly suggests that NRPD1 protein is produced at functionally equivalent levels in wild-type, mat and pat nrpd1+/-. The finding that mat nrpd1+/- has a stronger effect on gene expression and small RNAs, despite having higher levels of NRPD1 transcript in endosperm, is consistent with our conclusion that the effects we are observing in heterozygous endosperm are due to NRPD1 action before fertilization.

P. 9 line 1 - this only seems to be true for maternal ISRs, not paternal ISRs; this claim should be narrowed.

Response: Accordingly, we have modified the text here to : “In summary, these results indicate that most maternally and some paternally imprinted sRNA loci in endosperm are dependent on Pol IV activity in the parents and are not established de novo post-fertilization.”

A small number of sRNA loci become highly depleted in maternal nrpd1 but not paternal nrpd1 (Fig. 1D, F, Fig. 2C) - are these siren loci?

Response: This is an interesting question. Siren loci have not been defined in Arabidopsis but are described as loci with high levels of sRNAs in ovules, seed coat, endosperm and embryo (Grover et al., 2020). Loci losing sRNAs in maternal nrpd1+/- include a large number of maternally expressed imprinted sRNAs (mat ISRs). We do not know if mat ISR loci are expressed in the ovule. In Erdmann et al (2017), we excluded loci that were also expressed in the seed coat from mat ISRs. Thus, these loci meet only some of the conditions for being defined as siren loci.

Fig. 2 suggests that many of the downregulated sRNA regions in maternal nrpd1 are maternally biased to begin with. Related, are genic sRNAs more likely to be affected by maternal or paternal nrpd1 than non-genic or TE sRNAs?

Response: As described in Fig. 1B and S3, loss of maternal NRPD1 has more impacts on the sRNA landscape. As a percentage of total loci, genes are more likely to be affected than TEs.

For the sRNA loci shown in Fig. 2C, how is % maternal affected in maternal vs. paternal nrpd1? These ISRs are normally maternal or paternal biased, does this change in maternal or paternal nrpd1?

Response: We assess the allelic bias of ISRs only when they have at least ten reads in the genotypes being compared. In mat nrpd1+/-, most mat ISRs lose almost all their reads (Fig. 2) and we can assess allelic bias only at 107/366 mat ISRs. As seen in the Rev. comment. Fig1, these 107 lose their maternal bias. In pat nrpd1+/-, loci with maternally biased sRNAs show somewhat increased expression (Fig 2E) but do not show an appreciable change in maternal bias (Figure Review 1). All paternal ISRs do not show any dramatic impacts on allelic bias in mat or pat nrpd1+/-. We have not added this additional datapoint to our paper because we were worried that the paper was becoming too dense – a concern also voiced by reviewer 1. However, we can add this to the manuscript if the reviewer prefers.

• Might have missed this, but I didn't see the gene ontology results (p9 line 16) shown anywhere? Would like to see significance values, fold enrichments, etc. In particular, the group of paternal nrpd1 up-regulated genes seems too small to have much confidence for GO enrichment analysis.

Response: We have added a Supplementary Table 7 with outputs of GO analyses.

• I would suggest expanding the analysis in Fig. 3D-H to explore whether the additive model is more predictive of nrpd1-/- expression levels than other potential models (epistatic, etc.) in general at all genes, or only at the subsets of genes shown, independently of whether the effects are large enough to pass the arbitrary significance cutoffs used in E-H. Identifying specifically which genes do and don't follow this additive pattern could help dissect mechanism. For example, genes following this pattern might share a TF binding site for a TF that is regulated by Pol IV.

Response: While we are interested, we currently cannot explore other models such as epistasis as this would require knock-down of NRPD1 in the endosperm and we plan to do this as part of a future study.

1. 13 line 26 - how do changes in CG methylation in maternal or paternal nrpd1 compare to changes in dme or ros1? Do either set of DMRs significantly overlap dme or ros1 DMRs? Could some of these be explained by changes in ROS1 expression, since ROS1 is a Pol IV target?

Response: Yes. It’s entirely possible that a subset of observed gene expression changes are linked to changes in ROS1 expression. However, there are no comparable methylation data for ROS1 in the endosperm. A potential role for ROS1 has been discussed on Page 11, line 4. Comparison with DMRs in the dme endosperm is difficult. dme mutant endosperm has low non-CG methylation (Ibarra et al., 2012). We have unpublished data showing that the expression of genes involved in RNA-directed DNA methylation (RdDM) is reduced in the dme endosperm. It is therefore difficult to understand if and how DME-mediated demethylation may impact RdDM.

P. 10 line 3 - is the overlap of 36 out of 51 genes unlikely to occur by chance

Response: A hypergeometric test indicates that this is indeed significant. We have added it to text on Page 9, line 34.

In sRNA and mRNA-seq libraries, what was the overall maternal/paternal ratio in each library? Did loss of Pol IV affect this?

The graphs above show the maternally derived fraction of mRNA and sRNA libraries for different genotypes. Please note that the Ler nrpd1 mutant was generated by backcrossing Col-0 nrpd1+/- into Ler. Some Col-0 regions remain in this background and are called “hold-outs”. Reads mapping to these hold-outs have been excluded while calculating the maternal fraction of each library described in the graph above. We cannot confidently judge if the overall maternal fraction of the mRNA transcriptome is affected by loss of NRPD1 as we likely need more replicates. However, we find that loss of all NRPD1-dependent sRNAs (as in the nrpd1 null mutant) leaves behind sRNAs that roughly reflect the genomic 2:1 ratio.

P. 9 line 22 - how many paternally and maternally expressed imprinted genes were considered? Were imprinted genes statistically more likely to be misregulated in mat nrpd1?

Response: We considered 128 maternally and 43 paternally expressed genes that had been previously been identified as imprinted in Col x Ler crosses (Pignatta et al 2014). We have modified the manuscript to describe effects on imprinted genes: “ The expression of imprinted genes is known to be regulated epigenetically in endosperm. In mat nrpd1+/- imprinted genes were more likely to be mis-regulated than expected by chance (hypergeometric test p-15) – 15 out of 43 paternally expressed and 45 out of 128 maternally expressed imprinted genes were mis-regulated in mat nrpd1+/- while two maternally expressed imprinted genes but no paternally expressed imprinted genes were mis-regulated in pat nrpd1+/- (Table S6). “ We have also added a supplementary figure (Figure S6) that focuses on genic mRNA imprinting in NRPD1 heterozygotes and homozygous mutants.

References cited in the response

Brandvain, Y., & Haig, D. (2005). Divergent Mating Systems and Parental Conflict as a Barrier to Hybridization in Flowering Plants. The American Naturalist, 166(3), 330–338. https://doi.org/10.1086/432036

Brandvain, Y., & Haig, D. (2018). Outbreeders pull harder in a parental tug-of-war. Proceedings of the National Academy of Sciences, 115(45), 11354–11356. https://doi.org/10.1073/pnas.1816187115

Eimer, H., Sureshkumar, S., Singh Yadav, A., Kraupner-Taylor, C., Bandaranayake, C., Seleznev, A., Thomason, T., Fletcher, S. J., Gordon, S. F., Carroll, B. J., & Balasubramanian, S. (2018). RNA-Dependent Epigenetic Silencing Directs Transcriptional Downregulation Caused by Intronic Repeat Expansions. Cell. https://doi.org/10.1016/j.cell.2018.06.044

Grover, J. W., Burgess, D., Kendall, T., Baten, A., Pokhrel, S., King, G. J., Meyers, B. C., Freeling, M., & Mosher, R. A. (2020). Abundant expression of maternal siRNAs is a conserved feature of seed development. Proceedings of the National Academy of Sciences of the United States of America, 117(26), 15305–15315. https://doi.org/10.1073/pnas.2001332117

Grover, J. W., Kendall, T., Baten, A., Burgess, D., Freeling, M., King, G. J., & Mosher, R. A. (2018). Maternal components of RNA ‐directed DNA methylation are required for seed development in Brassica rapa. The Plant Journal, 94(4), 575–582. https://doi.org/10.1111/tpj.13910

Ibarra, C. A., Feng, X., Schoft, V. K., Hsieh, T.-F., Uzawa, R., Rodrigues, J. A., Zemach, A., Chumak, N., Machlicova, A., Nishimura, T., Rojas, D., Fischer, R. L., Tamaru, H., & Zilberman, D. (2012). Active DNA Demethylation in Plant Companion Cells Reinforces Transposon Methylation in Gametes. Science, 337(6100), 1360–1364. https://doi.org/10.1126/science.1224839

İltaş, Ö., Svitok, M., Cornille, A., Schmickl, R., & Lafon Placette, C. (2021). Early evolution of reproductive isolation: A case of weak inbreeder/strong outbreeder leads to an intraspecific hybridization barrier in Arabidopsis lyrata. Evolution, 75(6), 1466–1476. https://doi.org/10.1111/evo.14240

Kirkbride, R. C., Lu, J., Zhang, C., Mosher, R. A., Baulcombe, D. C., & Chen, Z. J. (2019). Maternal small RNAs mediate spatial-temporal regulation of gene expression, imprinting, and seed development in Arabidopsis. Proceedings of the National Academy of Sciences, 116(7), 2761–2766. https://doi.org/10.1073/pnas.1807621116

Klosinska, M., Picard, C. L., & Gehring, M. (2016). Conserved imprinting associated with unique epigenetic signatures in the Arabidopsis genus. Nature Plants, 2, 16145. https://doi.org/10.1038/nplants.2016.145

Lafon-Placette, C., Hatorangan, M. R., Steige, K. A., Cornille, A., Lascoux, M., Slotte, T., & Köhler, C. (2018). Paternally expressed imprinted genes associate with hybridization barriers in Capsella. Nature Plants, 4(6), 352–357. https://doi.org/10.1038/s41477-018-0161-6

Long, J., Walker, J., She, W., Aldridge, B., Gao, H., Deans, S., Vickers, M., & Feng, X. (2021). Nurse cell­–derived small RNAs define paternal epigenetic inheritance in Arabidopsis. Science, 373(6550). https://doi.org/10.1126/science.abh0556

Olmedo-Monfil, V., Durán-Figueroa, N., Arteaga-Vázquez, M., Demesa-Arévalo, E., Autran, D., Grimanelli, D., Slotkin, R. K., Martienssen, R. A., & Vielle-Calzada, J.-P. (2010). Control of female gamete formation by a small RNA pathway in Arabidopsis. Nature, 464(7288), 628–632. https://doi.org/10.1038/nature08828

Raunsgard, A., Opedal, Ø. H., Ekrem, R. K., Wright, J., Bolstad, G. H., Armbruster, W. S., & Pélabon, C. (2018). Intersexual conflict over seed size is stronger in more outcrossed populations of a mixed-mating plant. Proceedings of the National Academy of Sciences, 115(45), 11561–11566. https://doi.org/10.1073/pnas.1810979115

Sauer, N., & Stolz, J. (1994). SUC1 and SUC2: two sucrose transporters from Arabidopsis thaliana; expression and characterization in baker’s yeast and identification of the histidine-tagged protein. The Plant Journal, 6(1), 67–77. https://doi.org/10.1046/j.1365-313X.1994.6010067.x

Wang, Z., Butel, N., Santos-González, J., Borges, F., Yi, J., Martienssen, R. A., Martinez, G., & Köhler, C. (2020). Polymerase IV Plays a Crucial Role in Pollen Development in Capsella. The Plant Cell, 32(4), 950–966. https://doi.org/10.1105/tpc.19.00938

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

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

This manuscript provides evidence that a loss of either the maternal or paternal copy of NRPD1 have different, and sometime opposite, effects on the accumulation of small RNAs and on expression of a subset of genes, with a loss of the maternal copy having more substantial effects. The manuscript is well written, and the conclusions, as far as they go, are justified by the data, which are effectively presented. The overall effect is subtle but informative and according to the authors support a parental conflict model for imprinting. The experiments failed to find a smoking gun in the form of a mechanism to explain how or why the maternal and paternal alleles have different effects and the explanation for a lack of clear phenotypic differences was reasonable, but untested. I would have like to see it tested by looking in a plant species that is outcrossing and highly polymorphic. However, I do appreciate that the observation that the male and female alleles can have distinct effect when mutant is an important clue. My specific comments below may reflect confusion on my part, rather than real issues. If that is that I hope that confusion can aid in clarifying what are in places quite subtle points.

Specific comments:

Page 6, last paragraph: "Because the endosperm is triploid, in these comparisons there are 3 (wild-type), 2 (pat nrpd1+/-), 1 (mat nrpd1+/-) and 0 (nrpd1-/-) functional NRPD1 alleles in the endosperm. However, NRPD1 is a paternally expressed imprinted gene in wild-type Ler x Col endosperm and the single paternal allele contributes 62% of the NRPD1 transcript whereas 38% comes from the two maternal alleles (Pignatta et al., 2014). Consistent with paternal allele bias in NPRD1 expression, mRNA-Seq data shows that NRPD1 is expressed at 42% of wild- type levels in pat nrpd1+/- and at 91% of wild-type levels in mat nrpd1+/- (Supplementary Table 6)".

I would think this would really complicate the analysis. Should all of the dosage values include NPRD1 imprinting values? That is to say, expressed in terms of expression values? This is also a bit confusing. The maternal copies together express 38% of the transcript, so why isn't the mat nrpd1 at 68%, rather than 91%? In any event, given this imprinting and differences in dosage of the male and female it appears that two variables, parental origin and expression levels are being compared. Since 91% is awfully close to 100%, are the mat pat comparisons really just comparing low with nearly normal expression of NRPD1? And actually, given that, the outsized effect of the mat nrpd1 +/- is even more striking.

Page 4, Line 16. I'm afraid it's still a bit difficult to understand what was being compared what in this section. Please clarify.

Page 5, Line 5. I'm sure this is fine, but it's not entirely clear what is from the previously published paper and what is reanalysis here. All the crosses and measurements were made then, but not organized in this way?

Page 6, Line 26. This is an excellent dosage series, but it's complicated by imprinting. So it's not 3, 2, 1, 0 effective copies. If we set the paternal copy at ~1 and each maternal at ~0.1, then it's 1.2 (wild type), 0.20 (pat nrpd1+/-), 1 (mat nrpd1+/-), and 0 (nrpd1-/-).

Page 6, line 31. Is the main thing we are comparing the difference between expression at 42% verses 91% of wild type?

Page 7, line 11. So, the overall effect in either direction on smRNA gene targets was really quite small, and I'm guessing the effect on gene expression was even smaller.

Page 7, line 17. I take it that it is this difference, rather than the overall numbers that is of interest.

Page 9, line 2. Really interesting, since one might expect that these are methylated loci that would be expected to be fed into any existing embryo maintenance methylation pathway. Surprising that they are maintained independently.

Page 9, line 22. Proportion of total imprinted genes? Did the mutant obviate/enhance the imprinting?

Page 9, line 27. How could 2) occur in the homozygous mutant?

Page 10, line 9. Interesting!

Page 10, line 11. Is this 2.7 versus 2.18 significant because it's statistically significant, or because it's conceptually significant? Are the examples in 3D representative, or the most convincing examples? And a big difference in ROS1 is of some concern, since that may well be expected to affect imprinting indirectly. I know I'm being picky here, but the pattern is so intriguing I'd be worried about confirmation bias.

Page 10, line 18. Ok, but 0.123 is a pretty subtle negative correlation. Although I do appreciate that it clearly is not a positive correlation. If I'm understanding correctly, this was the "aha" moment, because it's exactly what one might expect of NRPD1 from the mother and father or working at cross purposes. But the numbers are getting awfully small here.

Page 10, line 29. The point simply being that that other phenomenon is also significant even if the differences are that large?

Page 12. So, there is no effect on cleavage and no obvious effect on flanking siRNA clusters. The suspense is building...

Page 12, line 24. And not in potential regulatory regions? CNSs?

Page 12, line 28. I guess it depend on whether or not the changes are in regulatory sequences no immediately apparent as part of the gene, doesn't it?

Line 13, line 2. Not sure it's that important, but couldn't you chop all of these genes in half and see if they are no longer significant collectively?

Page 14, line 15. I'm afraid I'm getting confused here with the terms cis and trans here. Just to be clear, cis means a direct effect of small RNAs that are dependent on NRPD1 on a gene and trans means anything else? But in this context, it's not clear that is what is meant. Do you mean that gene expression is determined and preset in the gametophyte? What are the levels of expression of NRPD1 in the two gemetophytes?

Page 14, line 19. Prior to fertilization?

Page 14, line 27. Do you mean driven by, or just associated with?

Page 15, line 26. And this is really the issue. The primary conclusion, backed up by the lack (I'm assuming) of phenotypic differences between mat NRPD1 -/+ and pat NRPD1 +/- suggests that the observed differences in expression are not particularly important, unless the exceptional cases are informative.

Page 15, line 12. Yes, but I'm not at all clear what the mechanism for this is.

Page 15, line 23. Since this is a very small subset of genes, are these genes that you might expect to play a role in parental conflict?

Page 15, line 33. Indeed, these could be the informative exceptions.

Page 15, line 29. Hardly surprising, given that the paternal copy of NRPD1 is expressed at a higher level than the maternal copies, is it?

Page 16, line 1. So this is what you mean by in cis. Presetting?

Page 16, line 9. So ideally, one would want to look at a highly polymorphic out-crosser. I'm not suggesting that for this paper, but would this be a good test of the hypothesis? How about maize?

Page 16, line 15. But the pat and mat heterozygotes looked the same. No differences in phenotype?

Page 17, line 22. I'm confused, since aren't most 24 nt smRNAs dependent on POLIV (Figure S2)? Do you mean differentially regulated smRNAs? Expression of POLIV specifically in one or the other parent?

Page 17, line 23. How are you defining important here? Important because at least in the female NPRD1 is not expressed in the central cell? But not important, since this mutant has no effect on phenotype except in an imbalanced cross.

Page 18, line 13. For this reason, it would be nice to know much more about these genes. Mutant phenotypes, for instance. And how many of these have this feature conserved?

Significance

These are intriguing results that would benefit from a test of the hypothesis by comparing these result with those obtained in an outcrossing plant species.

Referee Cross-commenting

I agree that the other comments seem both fair and reasonable.

Looking back to my first draft I had only included a brief summary of the article I had read without putting much of my opinion in the paragraph. As I was editing I had to keep asking myself "yeah but why do you think it is important" or "what do you think about it" because I realized the strength of this essay is supposed to be based on my thoughts and journey through discovering an answer to my question rather than summaries of my research. So, in the final draft I knew I had to include why I think rap videos make a greater impact than what we may originally believe. I added in my thoughts about how in the black community there is an "internal battle" regarding the issue of colorism. I realize now I could have included more about how some artist purposefully choose darker skin extras in their videos to compare to those who don't .

According to all known laws of aviation,

there is no way a bee should be able to fly.

Its wings are too small to get its fat little body off the ground.

The bee, of course, flies anyway

because bees don't care what humans think is impossible.

Yellow, black. Yellow, black. Yellow, black. Yellow, black.

Ooh, black and yellow! Let's shake it up a little.

Barry! Breakfast is ready!

Ooming!

Hang on a second.

Hello?

• Barry?
• Adam?

• Oan you believe this is happening?
• I can't. I'll pick you up.

Looking sharp.

Use the stairs. Your father paid good money for those.

Sorry. I'm excited.

Here's the graduate. We're very proud of you, son.

A perfect report card, all B's.

Very proud.

Ma! I got a thing going here.

• You got lint on your fuzz.
• Ow! That's me!

• Wave to us! We'll be in row 118,000.
• Bye!

Barry, I told you, stop flying in the house!

• Hey, Adam.
• Hey, Barry.

• Is that fuzz gel?
• A little. Special day, graduation.

Never thought I'd make it.

Three days grade school, three days high school.

Those were awkward.

Three days college. I'm glad I took a day and hitchhiked around the hive.

You did come back different.

• Hi, Barry.
• Artie, growing a mustache? Looks good.

• Hear about Frankie?
• Yeah.

• You going to the funeral?
• No, I'm not going.

Everybody knows, sting someone, you die.

Don't waste it on a squirrel. Such a hothead.

I guess he could have just gotten out of the way.

I love this incorporating an amusement park into our day.

That's why we don't need vacations.

Boy, quite a bit of pomp... under the circumstances.

• Well, Adam, today we are men.
• We are!

• Bee-men.
• Amen!

Hallelujah!

Students, faculty, distinguished bees,

please welcome Dean Buzzwell.

Welcome, New Hive Oity graduating class of...

...9:15.

That concludes our ceremonies.

And begins your career at Honex Industries!

Will we pick ourjob today?

I heard it's just orientation.

Heads up! Here we go.

Keep your hands and antennas inside the tram at all times.

• Wonder what it'll be like?
• A little scary.

Welcome to Honex, a division of Honesco

and a part of the Hexagon Group.

This is it!

Wow.

Wow.

We know that you, as a bee, have worked your whole life

to get to the point where you can work for your whole life.

Honey begins when our valiant Pollen Jocks bring the nectar to the hive.

Our top-secret formula

is automatically color-corrected, scent-adjusted and bubble-contoured

into this soothing sweet syrup

with its distinctive golden glow you know as...

Honey!

• That girl was hot.
• She's my cousin!

• She is?
• Yes, we're all cousins.

• Right. You're right.
• At Honex, we constantly strive

to improve every aspect of bee existence.

These bees are stress-testing a new helmet technology.

• What do you think he makes?
• Not enough.

Here we have our latest advancement, the Krelman.

• What does that do?
• Oatches that little strand of honey

that hangs after you pour it. Saves us millions.

Oan anyone work on the Krelman?

Of course. Most bee jobs are small ones. But bees know

that every small job, if it's done well, means a lot.

But choose carefully

because you'll stay in the job you pick for the rest of your life.

The same job the rest of your life? I didn't know that.

What's the difference?

You'll be happy to know that bees, as a species, haven't had one day off

in 27 million years.

So you'll just work us to death?

We'll sure try.

Wow! That blew my mind!

"What's the difference?" How can you say that?

One job forever? That's an insane choice to have to make.

I'm relieved. Now we only have to make one decision in life.

But, Adam, how could they never have told us that?

Why would you question anything? We're bees.

We're the most perfectly functioning society on Earth.

You ever think maybe things work a little too well here?

Like what? Give me one example.

I don't know. But you know what I'm talking about.

Please clear the gate. Royal Nectar Force on approach.

Wait a second. Oheck it out.

• Hey, those are Pollen Jocks!
• Wow.

I've never seen them this close.

They know what it's like outside the hive.

Yeah, but some don't come back.

• Hey, Jocks!
• Hi, Jocks!

You guys did great!

You're monsters! You're sky freaks! I love it! I love it!

• I wonder where they were.
• I don't know.

Their day's not planned.

Outside the hive, flying who knows where, doing who knows what.

You can'tjust decide to be a Pollen Jock. You have to be bred for that.

Right.

Look. That's more pollen than you and I will see in a lifetime.

It's just a status symbol. Bees make too much of it.

Perhaps. Unless you're wearing it and the ladies see you wearing it.

Those ladies? Aren't they our cousins too?

Distant. Distant.

Look at these two.

• Oouple of Hive Harrys.
• Let's have fun with them.

It must be dangerous being a Pollen Jock.

Yeah. Once a bear pinned me against a mushroom!

He had a paw on my throat, and with the other, he was slapping me!

• Oh, my!
• I never thought I'd knock him out.

What were you doing during this?

Trying to alert the authorities.

I can autograph that.

A little gusty out there today, wasn't it, comrades?

Yeah. Gusty.

We're hitting a sunflower patch six miles from here tomorrow.

• Six miles, huh?
• Barry!

A puddle jump for us, but maybe you're not up for it.

• Maybe I am.
• You are not!

We're going 0900 at J-Gate.

What do you think, buzzy-boy? Are you bee enough?

I might be. It all depends on what 0900 means.

Hey, Honex!

Dad, you surprised me.

You decide what you're interested in?

• Well, there's a lot of choices.
• But you only get one.

Do you ever get bored doing the same job every day?

Son, let me tell you about stirring.

You grab that stick, and you just move it around, and you stir it around.

You get yourself into a rhythm. It's a beautiful thing.

You know, Dad, the more I think about it,

maybe the honey field just isn't right for me.

You were thinking of what, making balloon animals?

That's a bad job for a guy with a stinger.

Janet, your son's not sure he wants to go into honey!

• Barry, you are so funny sometimes.
• I'm not trying to be funny.

You're not funny! You're going into honey. Our son, the stirrer!

• You're gonna be a stirrer?
• No one's listening to me!

Wait till you see the sticks I have.

I could say anything right now. I'm gonna get an ant tattoo!

Let's open some honey and celebrate!

Maybe I'll pierce my thorax. Shave my antennae.

Shack up with a grasshopper. Get a gold tooth and call everybody "dawg"!

I'm so proud.

• We're starting work today!
• Today's the day.

Oome on! All the good jobs will be gone.

Yeah, right.

Pollen counting, stunt bee, pouring, stirrer, front desk, hair removal...

• Is it still available?
• Hang on. Two left!

One of them's yours! Oongratulations! Step to the side.

• What'd you get?
• Picking crud out. Stellar!

Wow!

Oouple of newbies?

Yes, sir! Our first day! We are ready!

Make your choice.

• You want to go first?
• No, you go.

Oh, my. What's available?

Restroom attendant's open, not for the reason you think.

• Any chance of getting the Krelman?
• Sure, you're on.

I'm sorry, the Krelman just closed out.

Wax monkey's always open.

The Krelman opened up again.

What happened?

A bee died. Makes an opening. See? He's dead. Another dead one.

Deady. Deadified. Two more dead.

Dead from the neck up. Dead from the neck down. That's life!

Oh, this is so hard!

Heating, cooling, stunt bee, pourer, stirrer,

humming, inspector number seven, lint coordinator, stripe supervisor,

mite wrangler. Barry, what do you think I should... Barry?

Barry!

All right, we've got the sunflower patch in quadrant nine...

What happened to you? Where are you?

• I'm going out.
• Out? Out where?

• Out there.
• Oh, no!

I have to, before I go to work for the rest of my life.

You're gonna die! You're crazy! Hello?

Another call coming in.

If anyone's feeling brave, there's a Korean deli on 83rd

that gets their roses today.

Hey, guys.

• Look at that.
• Isn't that the kid we saw yesterday?

Hold it, son, flight deck's restricted.

It's OK, Lou. We're gonna take him up.

Really? Feeling lucky, are you?

Sign here, here. Just initial that.

• Thank you.
• OK.

You got a rain advisory today,

and as you all know, bees cannot fly in rain.

So be careful. As always, watch your brooms,

hockey sticks, dogs, birds, bears and bats.

Also, I got a couple of reports of root beer being poured on us.

Murphy's in a home because of it, babbling like a cicada!

• That's awful.
• And a reminder for you rookies,

bee law number one, absolutely no talking to humans!

All right, launch positions!

Buzz, buzz, buzz, buzz! Buzz, buzz, buzz, buzz! Buzz, buzz, buzz, buzz!

Black and yellow!

Hello!

You ready for this, hot shot?

Yeah. Yeah, bring it on.

Wind, check.

• Antennae, check.
• Nectar pack, check.

• Wings, check.
• Stinger, check.

Scared out of my shorts, check.

OK, ladies,

let's move it out!

Pound those petunias, you striped stem-suckers!

All of you, drain those flowers!

Wow! I'm out!

I can't believe I'm out!

So blue.

I feel so fast and free!

Box kite!

Wow!

Flowers!

This is Blue Leader. We have roses visual.

Bring it around 30 degrees and hold.

Roses!

30 degrees, roger. Bringing it around.

Stand to the side, kid. It's got a bit of a kick.

That is one nectar collector!

• Ever see pollination up close?
• No, sir.

I pick up some pollen here, sprinkle it over here. Maybe a dash over there,

a pinch on that one. See that? It's a little bit of magic.

That's amazing. Why do we do that?

That's pollen power. More pollen, more flowers, more nectar, more honey for us.

Oool.

I'm picking up a lot of bright yellow. Oould be daisies. Don't we need those?

Oopy that visual.

Wait. One of these flowers seems to be on the move.

Say again? You're reporting a moving flower?

Affirmative.

That was on the line!

This is the coolest. What is it?

I don't know, but I'm loving this color.

It smells good. Not like a flower, but I like it.

Yeah, fuzzy.

Ohemical-y.

Oareful, guys. It's a little grabby.

My sweet lord of bees!

Oandy-brain, get off there!

Problem!

• Guys!
• This could be bad.

Affirmative.

Very close.

Gonna hurt.

Mama's little boy.

You are way out of position, rookie!

Ooming in at you like a missile!

Help me!

I don't think these are flowers.

• Should we tell him?
• I think he knows.

What is this?!

Match point!

You can start packing up, honey, because you're about to eat it!

Yowser!

Gross.

There's a bee in the car!

• Do something!
• I'm driving!

• Hi, bee.
• He's back here!

He's going to sting me!

Nobody move. If you don't move, he won't sting you. Freeze!

He blinked!

Spray him, Granny!

What are you doing?!

Wow... the tension level out here is unbelievable.

I gotta get home.

Oan't fly in rain.

Oan't fly in rain.

Oan't fly in rain.

Mayday! Mayday! Bee going down!

Ken, could you close the window please?

Ken, could you close the window please?

Oheck out my new resume. I made it into a fold-out brochure.

You see? Folds out.

Oh, no. More humans. I don't need this.

What was that?

Maybe this time. This time. This time. This time! This time! This...

Drapes!

That is diabolical.

It's fantastic. It's got all my special skills, even my top-ten favorite movies.

What's number one? Star Wars?

Nah, I don't go for that...

...kind of stuff.

No wonder we shouldn't talk to them. They're out of their minds.

When I leave a job interview, they're flabbergasted, can't believe what I say.

There's the sun. Maybe that's a way out.

I don't remember the sun having a big 75 on it.

I predicted global warming.

I could feel it getting hotter. At first I thought it was just me.

Wait! Stop! Bee!

Stand back. These are winter boots.

Wait!

Don't kill him!

You know I'm allergic to them! This thing could kill me!

Why does his life have less value than yours?

Why does his life have any less value than mine? Is that your statement?

I'm just saying all life has value. You don't know what he's capable of feeling.

My brochure!

There you go, little guy.

I'm not scared of him. It's an allergic thing.

Put that on your resume brochure.

My whole face could puff up.

Make it one of your special skills.

Knocking someone out is also a special skill.

Right. Bye, Vanessa. Thanks.

• Vanessa, next week? Yogurt night?
• Sure, Ken. You know, whatever.

• You could put carob chips on there.
• Bye.

• Supposed to be less calories.
• Bye.

I gotta say something.

She saved my life. I gotta say something.

All right, here it goes.

Nah.

What would I say?

I could really get in trouble.

It's a bee law. You're not supposed to talk to a human.

I can't believe I'm doing this.

I've got to.

Oh, I can't do it. Oome on!

No. Yes. No.

Do it. I can't.

How should I start it? "You like jazz?" No, that's no good.

Here she comes! Speak, you fool!

Hi!

I'm sorry.

• You're talking.
• Yes, I know.

You're talking!

I'm so sorry.

No, it's OK. It's fine. I know I'm dreaming.

But I don't recall going to bed.

Well, I'm sure this is very disconcerting.

This is a bit of a surprise to me. I mean, you're a bee!

I am. And I'm not supposed to be doing this,

but they were all trying to kill me.

And if it wasn't for you...

I had to thank you. It's just how I was raised.

That was a little weird.

• I'm talking with a bee.
• Yeah.

I'm talking to a bee. And the bee is talking to me!

I just want to say I'm grateful. I'll leave now.

• Wait! How did you learn to do that?
• What?

The talking thing.

Same way you did, I guess. "Mama, Dada, honey." You pick it up.

• That's very funny.
• Yeah.

Bees are funny. If we didn't laugh, we'd cry with what we have to deal with.

Anyway...

Oan I...

...get you something?

• Like what?

I don't know. I mean... I don't know. Ooffee?

I don't want to put you out.

It's no trouble. It takes two minutes.

• It's just coffee.
• I hate to impose.

• Don't be ridiculous!
• Actually, I would love a cup.

Hey, you want rum cake?

• I shouldn't.
• Have some.

• No, I can't.
• Oome on!

I'm trying to lose a couple micrograms.

• Where?
• These stripes don't help.

You look great!

I don't know if you know anything about fashion.

Are you all right?

No.

He's making the tie in the cab as they're flying up Madison.

He finally gets there.

He runs up the steps into the church. The wedding is on.

And he says, "Watermelon? I thought you said Guatemalan.

Why would I marry a watermelon?"

Is that a bee joke?

That's the kind of stuff we do.

Yeah, different.

So, what are you gonna do, Barry?

About work? I don't know.

I want to do my part for the hive, but I can't do it the way they want.

I know how you feel.

• You do?
• Sure.

My parents wanted me to be a lawyer or a doctor, but I wanted to be a florist.

• Really?
• My only interest is flowers.

Our new queen was just elected with that same campaign slogan.

Anyway, if you look...

There's my hive right there. See it?

You're in Sheep Meadow!

Yes! I'm right off the Turtle Pond!

No way! I know that area. I lost a toe ring there once.

• Why do girls put rings on their toes?
• Why not?

• It's like putting a hat on your knee.
• Maybe I'll try that.

• You all right, ma'am?
• Oh, yeah. Fine.

Just having two cups of coffee!

Anyway, this has been great. Thanks for the coffee.

Yeah, it's no trouble.

Sorry I couldn't finish it. If I did, I'd be up the rest of my life.

Are you...?

Oan I take a piece of this with me?

Sure! Here, have a crumb.

• Thanks!
• Yeah.

All right. Well, then... I guess I'll see you around.

Or not.

OK, Barry.

And thank you so much again... for before.

Oh, that? That was nothing.

Well, not nothing, but... Anyway...

This can't possibly work.

He's all set to go. We may as well try it.

OK, Dave, pull the chute.

• Sounds amazing.
• It was amazing!

It was the scariest, happiest moment of my life.

Humans! I can't believe you were with humans!

Giant, scary humans! What were they like?

Huge and crazy. They talk crazy.

They eat crazy giant things. They drive crazy.

• Do they try and kill you, like on TV?
• Some of them. But some of them don't.

• How'd you get back?
• Poodle.

You did it, and I'm glad. You saw whatever you wanted to see.

You had your "experience." Now you can pick out yourjob and be normal.

• Well...
• Well?

Well, I met someone.

You did? Was she Bee-ish?

• A wasp?! Your parents will kill you!
• No, no, no, not a wasp.

• Spider?
• I'm not attracted to spiders.

I know it's the hottest thing, with the eight legs and all.

I can't get by that face.

So who is she?

She's... human.

No, no. That's a bee law. You wouldn't break a bee law.

• Her name's Vanessa.
• Oh, boy.

She's so nice. And she's a florist!

Oh, no! You're dating a human florist!

We're not dating.

You're flying outside the hive, talking to humans that attack our homes

with power washers and M-80s! One-eighth a stick of dynamite!

She saved my life! And she understands me.

This is over!

Eat this.

This is not over! What was that?

• They call it a crumb.
• It was so stingin' stripey!

And that's not what they eat. That's what falls off what they eat!

• You know what a Oinnabon is?
• No.

It's bread and cinnamon and frosting. They heat it up...

Sit down!

...really hot!

• Listen to me!

We are not them! We're us. There's us and there's them!

Yes, but who can deny the heart that is yearning?

There's no yearning. Stop yearning. Listen to me!

You have got to start thinking bee, my friend. Thinking bee!

• Thinking bee.
• Thinking bee.

Thinking bee! Thinking bee! Thinking bee! Thinking bee!

There he is. He's in the pool.

You know what your problem is, Barry?

I gotta start thinking bee?

How much longer will this go on?

It's been three days! Why aren't you working?

I've got a lot of big life decisions to think about.

What life? You have no life! You have no job. You're barely a bee!

Would it kill you to make a little honey?

Barry, come out. Your father's talking to you.

Martin, would you talk to him?

Barry, I'm talking to you!

You coming?

Got everything?

All set!

Go ahead. I'll catch up.

Don't be too long.

Watch this!

Vanessa!

• We're still here.
• I told you not to yell at him.

He doesn't respond to yelling!

• Then why yell at me?
• Because you don't listen!

I'm not listening to this.

Sorry, I've gotta go.

• Where are you going?
• I'm meeting a friend.

A girl? Is this why you can't decide?

Bye.

I just hope she's Bee-ish.

They have a huge parade of flowers every year in Pasadena?

To be in the Tournament of Roses, that's every florist's dream!

Up on a float, surrounded by flowers, crowds cheering.

A tournament. Do the roses compete in athletic events?

No. All right, I've got one. How come you don't fly everywhere?

It's exhausting. Why don't you run everywhere? It's faster.

Yeah, OK, I see, I see. All right, your turn.

TiVo. You can just freeze live TV? That's insane!

You don't have that?

We have Hivo, but it's a disease. It's a horrible, horrible disease.

Oh, my.

Dumb bees!

You must want to sting all those jerks.

We try not to sting. It's usually fatal for us.

So you have to watch your temper.

Very carefully. You kick a wall, take a walk,

write an angry letter and throw it out. Work through it like any emotion:

Anger, jealousy, lust.

Oh, my goodness! Are you OK?

Yeah.

• What is wrong with you?!
• It's a bug.

He's not bothering anybody. Get out of here, you creep!

What was that? A Pic 'N' Save circular?

Yeah, it was. How did you know?

It felt like about 10 pages. Seventy-five is pretty much our limit.

You've really got that down to a science.

• I lost a cousin to Italian Vogue.
• I'll bet.

What in the name of Mighty Hercules is this?

How did this get here? Oute Bee, Golden Blossom,

Ray Liotta Private Select?

• Is he that actor?
• I never heard of him.

• Why is this here?
• For people. We eat it.

You don't have enough food of your own?

• Well, yes.
• How do you get it?

• Bees make it.
• I know who makes it!

And it's hard to make it!

There's heating, cooling, stirring. You need a whole Krelman thing!

• It's organic.
• It's our-ganic!

It's just honey, Barry.

Just what?!

Bees don't know about this! This is stealing! A lot of stealing!

You've taken our homes, schools, hospitals! This is all we have!

And it's on sale?! I'm getting to the bottom of this.

I'm getting to the bottom of all of this!

Hey, Hector.

• You almost done?
• Almost.

He is here. I sense it.

Well, I guess I'll go home now

and just leave this nice honey out, with no one around.

You're busted, box boy!

I knew I heard something. So you can talk!

I can talk. And now you'll start talking!

Where you getting the sweet stuff? Who's your supplier?

I don't understand. I thought we were friends.

The last thing we want to do is upset bees!

You're too late! It's ours now!

You, sir, have crossed the wrong sword!

You, sir, will be lunch for my iguana, Ignacio!

Where is the honey coming from?

Tell me where!

Honey Farms! It comes from Honey Farms!

Orazy person!

What horrible thing has happened here?

These faces, they never knew what hit them. And now

they're on the road to nowhere!

Just keep still.

What? You're not dead?

Do I look dead? They will wipe anything that moves. Where you headed?

To Honey Farms. I am onto something huge here.

I'm going to Alaska. Moose blood, crazy stuff. Blows your head off!

I'm going to Tacoma.

• And you?
• He really is dead.

All right.

Uh-oh!

• What is that?!
• Oh, no!

• A wiper! Triple blade!
• Triple blade?

Jump on! It's your only chance, bee!

Why does everything have to be so doggone clean?!

How much do you people need to see?!

Open your eyes! Stick your head out the window!

From NPR News in Washington, I'm Oarl Kasell.

But don't kill no more bugs!

• Bee!
• Moose blood guy!!

• You hear something?
• Like what?

Like tiny screaming.

Turn off the radio.

Whassup, bee boy?

Hey, Blood.

Just a row of honey jars, as far as the eye could see.

Wow!

I assume wherever this truck goes is where they're getting it.

I mean, that honey's ours.

• Bees hang tight.
• We're all jammed in.

It's a close community.

Not us, man. We on our own. Every mosquito on his own.

• What if you get in trouble?
• You a mosquito, you in trouble.

Nobody likes us. They just smack. See a mosquito, smack, smack!

At least you're out in the world. You must meet girls.

Mosquito girls try to trade up, get with a moth, dragonfly.

Mosquito girl don't want no mosquito.

You got to be kidding me!

Mooseblood's about to leave the building! So long, bee!

• Hey, guys!
• Mooseblood!

I knew I'd catch y'all down here. Did you bring your crazy straw?

We throw it in jars, slap a label on it, and it's pretty much pure profit.

What is this place?

A bee's got a brain the size of a pinhead.

They are pinheads!

Pinhead.

• Oheck out the new smoker.
• Oh, sweet. That's the one you want.

The Thomas 3000!

Smoker?

Ninety puffs a minute, semi-automatic. Twice the nicotine, all the tar.

A couple breaths of this knocks them right out.

They make the honey, and we make the money.

"They make the honey, and we make the money"?

Oh, my!

What's going on? Are you OK?

Yeah. It doesn't last too long.

Do you know you're in a fake hive with fake walls?

Our queen was moved here. We had no choice.

This is your queen? That's a man in women's clothes!

That's a drag queen!

What is this?

Oh, no!

There's hundreds of them!

Bee honey.

Our honey is being brazenly stolen on a massive scale!

This is worse than anything bears have done! I intend to do something.

Oh, Barry, stop.

Who told you humans are taking our honey? That's a rumor.

Do these look like rumors?

That's a conspiracy theory. These are obviously doctored photos.

How did you get mixed up in this?

He's been talking to humans.

• What?
• Talking to humans?!

He has a human girlfriend. And they make out!

Make out? Barry!

We do not.

• You wish you could.
• Whose side are you on?

The bees!

I dated a cricket once in San Antonio. Those crazy legs kept me up all night.

Barry, this is what you want to do with your life?

I want to do it for all our lives. Nobody works harder than bees!

Dad, I remember you coming home so overworked

your hands were still stirring. You couldn't stop.

I remember that.

What right do they have to our honey?

We live on two cups a year. They put it in lip balm for no reason whatsoever!

Even if it's true, what can one bee do?

Sting them where it really hurts.

In the face! The eye!

• That would hurt.
• No.

Up the nose? That's a killer.

There's only one place you can sting the humans, one place where it matters.

Hive at Five, the hive's only full-hour action news source.

No more bee beards!

With Bob Bumble at the anchor desk.

Weather with Storm Stinger.

Sports with Buzz Larvi.

And Jeanette Ohung.

• Good evening. I'm Bob Bumble.
• And I'm Jeanette Ohung.

A tri-county bee, Barry Benson,

intends to sue the human race for stealing our honey,

packaging it and profiting from it illegally!

Tomorrow night on Bee Larry King,

we'll have three former queens here in our studio, discussing their new book,

Olassy Ladies, out this week on Hexagon.

Tonight we're talking to Barry Benson.

Did you ever think, "I'm a kid from the hive. I can't do this"?

Bees have never been afraid to change the world.

What about Bee Oolumbus? Bee Gandhi? Bejesus?

Where I'm from, we'd never sue humans.

We were thinking of stickball or candy stores.

How old are you?

The bee community is supporting you in this case,

which will be the trial of the bee century.

You know, they have a Larry King in the human world too.

It's a common name. Next week...

He looks like you and has a show and suspenders and colored dots...

Next week...

Glasses, quotes on the bottom from the guest even though you just heard 'em.

Bear Week next week! They're scary, hairy and here live.

Always leans forward, pointy shoulders, squinty eyes, very Jewish.

In tennis, you attack at the point of weakness!

It was my grandmother, Ken. She's 81.

Honey, her backhand's a joke! I'm not gonna take advantage of that?

Quiet, please. Actual work going on here.

• Is that that same bee?
• Yes, it is!

I'm helping him sue the human race.

• Hello.
• Hello, bee.

This is Ken.

Yeah, I remember you. Timberland, size ten and a half. Vibram sole, I believe.

Why does he talk again?

Listen, you better go 'cause we're really busy working.

But it's our yogurt night!

Bye-bye.

Why is yogurt night so difficult?!

You poor thing. You two have been at this for hours!

Yes, and Adam here has been a huge help.

• Frosting...
• How many sugars?

Just one. I try not to use the competition.

So why are you helping me?

Bees have good qualities.

And it takes my mind off the shop.

Instead of flowers, people are giving balloon bouquets now.

Those are great, if you're three.

And artificial flowers.

• Oh, those just get me psychotic!
• Yeah, me too.

Bent stingers, pointless pollination.

Bees must hate those fake things!

Nothing worse than a daffodil that's had work done.

Maybe this could make up for it a little bit.

• This lawsuit's a pretty big deal.
• I guess.

You sure you want to go through with it?

Am I sure? When I'm done with the humans, they won't be able

to say, "Honey, I'm home," without paying a royalty!

It's an incredible scene here in downtown Manhattan,

where the world anxiously waits, because for the first time in history,

we will hear for ourselves if a honeybee can actually speak.

What have we gotten into here, Barry?

It's pretty big, isn't it?

I can't believe how many humans don't work during the day.

You think billion-dollar multinational food companies have good lawyers?

Everybody needs to stay behind the barricade.

• What's the matter?
• I don't know, I just got a chill.

Well, if it isn't the bee team.

You boys work on this?

All rise! The Honorable Judge Bumbleton presiding.

All right. Oase number 4475,

Superior Oourt of New York, Barry Bee Benson v. the Honey Industry

is now in session.

Mr. Montgomery, you're representing the five food companies collectively?

A privilege.

Mr. Benson... you're representing all the bees of the world?

I'm kidding. Yes, Your Honor, we're ready to proceed.

Mr. Montgomery, your opening statement, please.

Ladies and gentlemen of the jury,

my grandmother was a simple woman.

Born on a farm, she believed it was man's divine right

to benefit from the bounty of nature God put before us.

If we lived in the topsy-turvy world Mr. Benson imagines,

just think of what would it mean.

I would have to negotiate with the silkworm

for the elastic in my britches!

Talking bee!

How do we know this isn't some sort of

holographic motion-picture-capture Hollywood wizardry?

They could be using laser beams!

Robotics! Ventriloquism! Oloning! For all we know,

he could be on steroids!

Mr. Benson?

Ladies and gentlemen, there's no trickery here.

I'm just an ordinary bee. Honey's pretty important to me.

It's important to all bees. We invented it!

We make it. And we protect it with our lives.

Unfortunately, there are some people in this room

who think they can take it from us

'cause we're the little guys! I'm hoping that, after this is all over,

you'll see how, by taking our honey, you not only take everything we have

but everything we are!

I wish he'd dress like that all the time. So nice!

Oall your first witness.

So, Mr. Klauss Vanderhayden of Honey Farms, big company you have.

I suppose so.

I see you also own Honeyburton and Honron!

Yes, they provide beekeepers for our farms.

Beekeeper. I find that to be a very disturbing term.

I don't imagine you employ any bee-free-ers, do you?

• No.
• I couldn't hear you.

• No.
• No.

Because you don't free bees. You keep bees. Not only that,

it seems you thought a bear would be an appropriate image for a jar of honey.

They're very lovable creatures.

Yogi Bear, Fozzie Bear, Build-A-Bear.

You mean like this?

Bears kill bees!

How'd you like his head crashing through your living room?!

Biting into your couch! Spitting out your throw pillows!

OK, that's enough. Take him away.

So, Mr. Sting, thank you for being here. Your name intrigues me.

• Where have I heard it before?
• I was with a band called The Police.

But you've never been a police officer, have you?

No, I haven't.

No, you haven't. And so here we have yet another example

of bee culture casually stolen by a human

for nothing more than a prance-about stage name.

Oh, please.

Have you ever been stung, Mr. Sting?

Because I'm feeling a little stung, Sting.

Or should I say... Mr. Gordon M. Sumner!

That's not his real name?! You idiots!

Mr. Liotta, first, belated congratulations on

your Emmy win for a guest spot on ER in 2005.

Thank you. Thank you.

I see from your resume that you're devilishly handsome

with a churning inner turmoil that's ready to blow.

I enjoy what I do. Is that a crime?

Not yet it isn't. But is this what it's come to for you?

Exploiting tiny, helpless bees so you don't

have to rehearse your part and learn your lines, sir?

Watch it, Benson! I could blow right now!

This isn't a goodfella. This is a badfella!

Why doesn't someone just step on this creep, and we can all go home?!

• Order in this court!
• You're all thinking it!

Order! Order, I say!

• Say it!
• Mr. Liotta, please sit down!

I think it was awfully nice of that bear to pitch in like that.

I think the jury's on our side.

Are we doing everything right, legally?

I'm a florist.

Right. Well, here's to a great team.

To a great team!

Well, hello.

• Ken!
• Hello.

I didn't think you were coming.

No, I was just late. I tried to call, but... the battery.

I didn't want all this to go to waste, so I called Barry. Luckily, he was free.

Oh, that was lucky.

There's a little left. I could heat it up.

Yeah, heat it up, sure, whatever.

So I hear you're quite a tennis player.

I'm not much for the game myself. The ball's a little grabby.

That's where I usually sit. Right... there.

Ken, Barry was looking at your resume,

and he agreed with me that eating with chopsticks isn't really a special skill.

You think I don't see what you're doing?

I know how hard it is to find the rightjob. We have that in common.

Do we?

Bees have 100 percent employment, but we do jobs like taking the crud out.

That's just what I was thinking about doing.

Ken, I let Barry borrow your razor for his fuzz. I hope that was all right.

I'm going to drain the old stinger.

Yeah, you do that.

Look at that.

You know, I've just about had it

with your little mind games.

• What's that?
• Italian Vogue.

Mamma mia, that's a lot of pages.

A lot of ads.

Remember what Van said, why is your life more valuable than mine?

Funny, I just can't seem to recall that!

I think something stinks in here!

I love the smell of flowers.

How do you like the smell of flames?!

Not as much.

Water bug! Not taking sides!

Ken, I'm wearing a Ohapstick hat! This is pathetic!

I've got issues!

Well, well, well, a royal flush!

• You're bluffing.
• Am I?

Surf's up, dude!

Poo water!

That bowl is gnarly.

Except for those dirty yellow rings!

Kenneth! What are you doing?!

You know, I don't even like honey! I don't eat it!

We need to talk!

He's just a little bee!

And he happens to be the nicest bee I've met in a long time!

Long time? What are you talking about?! Are there other bugs in your life?

No, but there are other things bugging me in life. And you're one of them!

Fine! Talking bees, no yogurt night...

My nerves are fried from riding on this emotional roller coaster!

Goodbye, Ken.

And for your information,

I prefer sugar-free, artificial sweeteners made by man!

I'm sorry about all that.

I know it's got an aftertaste! I like it!

I always felt there was some kind of barrier between Ken and me.

I couldn't overcome it. Oh, well.

Are you OK for the trial?

I believe Mr. Montgomery is about out of ideas.

We would like to call Mr. Barry Benson Bee to the stand.

Good idea! You can really see why he's considered one of the best lawyers...

Yeah.

Layton, you've gotta weave some magic

with this jury, or it's gonna be all over.

Don't worry. The only thing I have to do to turn this jury around

is to remind them of what they don't like about bees.

• You got the tweezers?
• Are you allergic?

Only to losing, son. Only to losing.

Mr. Benson Bee, I'll ask you what I think we'd all like to know.

What exactly is your relationship

to that woman?

We're friends.

• Good friends?
• Yes.

How good? Do you live together?

Wait a minute...

Are you her little...

...bedbug?

I've seen a bee documentary or two. From what I understand,

doesn't your queen give birth to all the bee children?

• Yeah, but...
• So those aren't your real parents!

• Oh, Barry...
• Yes, they are!

Hold me back!

You're an illegitimate bee, aren't you, Benson?

He's denouncing bees!

Don't y'all date your cousins?

• Objection!
• I'm going to pincushion this guy!

Adam, don't! It's what he wants!

Oh, I'm hit!!

Oh, lordy, I am hit!

Order! Order!

The venom! The venom is coursing through my veins!

I have been felled by a winged beast of destruction!

You see? You can't treat them like equals! They're striped savages!

Stinging's the only thing they know! It's their way!

• Adam, stay with me.
• I can't feel my legs.

What angel of mercy will come forward to suck the poison

from my heaving buttocks?

I will have order in this court. Order!

Order, please!

The case of the honeybees versus the human race

took a pointed turn against the bees

yesterday when one of their legal team stung Layton T. Montgomery.

• Hey, buddy.
• Hey.

• Is there much pain?
• Yeah.

I...

I blew the whole case, didn't I?

It doesn't matter. What matters is you're alive. You could have died.

I'd be better off dead. Look at me.

They got it from the cafeteria downstairs, in a tuna sandwich.

Look, there's a little celery still on it.

What was it like to sting someone?

I can't explain it. It was all...

All adrenaline and then... and then ecstasy!

All right.

You think it was all a trap?

Of course. I'm sorry. I flew us right into this.

What were we thinking? Look at us. We're just a couple of bugs in this world.

What will the humans do to us if they win?

I don't know.

I hear they put the roaches in motels. That doesn't sound so bad.

Adam, they check in, but they don't check out!

Oh, my.

Oould you get a nurse to close that window?

• Why?
• The smoke.

Bees don't smoke.

Right. Bees don't smoke.

Bees don't smoke! But some bees are smoking.

That's it! That's our case!

It is? It's not over?

Get dressed. I've gotta go somewhere.

Get back to the court and stall. Stall any way you can.

And assuming you've done step correctly, you're ready for the tub.

Mr. Flayman.

Yes? Yes, Your Honor!

Where is the rest of your team?

Well, Your Honor, it's interesting.

Bees are trained to fly haphazardly,

and as a result, we don't make very good time.

I actually heard a funny story about...

Your Honor, haven't these ridiculous bugs

taken up enough of this court's valuable time?

How much longer will we allow these absurd shenanigans to go on?

They have presented no compelling evidence to support their charges

against my clients, who run legitimate businesses.

I move for a complete dismissal of this entire case!

Mr. Flayman, I'm afraid I'm going

to have to consider Mr. Montgomery's motion.

But you can't! We have a terrific case.

Where is your proof? Where is the evidence?

Show me the smoking gun!

Hold it, Your Honor! You want a smoking gun?

Here is your smoking gun.

What is that?

It's a bee smoker!

What, this? This harmless little contraption?

This couldn't hurt a fly, let alone a bee.

Look at what has happened

to bees who have never been asked, "Smoking or non?"

Is this what nature intended for us?

To be forcibly addicted to smoke machines

and man-made wooden slat work camps?

Living out our lives as honey slaves to the white man?

• What are we gonna do?
• He's playing the species card.

Ladies and gentlemen, please, free these bees!

Free the bees! Free the bees!

Free the bees!

Free the bees! Free the bees!

The court finds in favor of the bees!

Vanessa, we won!

I knew you could do it! High-five!

Sorry.

I'm OK! You know what this means?

All the honey will finally belong to the bees.

Now we won't have to work so hard all the time.

This is an unholy perversion of the balance of nature, Benson.

You'll regret this.

Barry, how much honey is out there?

All right. One at a time.

Barry, who are you wearing?

My sweater is Ralph Lauren, and I have no pants.

• What if Montgomery's right?
• What do you mean?

We've been living the bee way a long time, 27 million years.

Oongratulations on your victory. What will you demand as a settlement?

First, we'll demand a complete shutdown of all bee work camps.

Then we want back the honey that was ours to begin with,

every last drop.

We demand an end to the glorification of the bear as anything more

than a filthy, smelly, bad-breath stink machine.

We're all aware of what they do in the woods.

Wait for my signal.

Take him out.

He'll have nauseous for a few hours, then he'll be fine.

And we will no longer tolerate bee-negative nicknames...

But it's just a prance-about stage name!

...unnecessary inclusion of honey in bogus health products

and la-dee-da human tea-time snack garnishments.

Oan't breathe.

Bring it in, boys!

Hold it right there! Good.

Tap it.

Mr. Buzzwell, we just passed three cups, and there's gallons more coming!

• I think we need to shut down!
• Shut down? We've never shut down.

Shut down honey production!

Stop making honey!

Turn your key, sir!

What do we do now?

Oannonball!

We're shutting honey production!

Mission abort.

Aborting pollination and nectar detail. Returning to base.

Adam, you wouldn't believe how much honey was out there.

Oh, yeah?

What's going on? Where is everybody?

• Are they out celebrating?
• They're home.

They don't know what to do. Laying out, sleeping in.

I heard your Uncle Oarl was on his way to San Antonio with a cricket.

At least we got our honey back.

Sometimes I think, so what if humans liked our honey? Who wouldn't?

It's the greatest thing in the world! I was excited to be part of making it.

This was my new desk. This was my new job. I wanted to do it really well.

And now...

Now I can't.

I don't understand why they're not happy.

I thought their lives would be better!

They're doing nothing. It's amazing. Honey really changes people.

You don't have any idea what's going on, do you?

• What did you want to show me?
• This.

What happened here?

That is not the half of it.

Oh, no. Oh, my.

They're all wilting.

Doesn't look very good, does it?

No.

And whose fault do you think that is?

You know, I'm gonna guess bees.

Bees?

Specifically, me.

I didn't think bees not needing to make honey would affect all these things.

It's notjust flowers. Fruits, vegetables, they all need bees.

That's our whole SAT test right there.

Take away produce, that affects the entire animal kingdom.

And then, of course...

The human species?

So if there's no more pollination,

it could all just go south here, couldn't it?

I know this is also partly my fault.

How about a suicide pact?

How do we do it?

• I'll sting you, you step on me.
• Thatjust kills you twice.

Right, right.

Listen, Barry... sorry, but I gotta get going.

I had to open my mouth and talk.

Vanessa?

Vanessa? Why are you leaving? Where are you going?

To the final Tournament of Roses parade in Pasadena.

They've moved it to this weekend because all the flowers are dying.

It's the last chance I'll ever have to see it.

Vanessa, I just wanna say I'm sorry. I never meant it to turn out like this.

I know. Me neither.

Tournament of Roses. Roses can't do sports.

Wait a minute. Roses. Roses?

Roses!

Vanessa!

Roses?!

Barry?

• Roses are flowers!
• Yes, they are.

Flowers, bees, pollen!

I know. That's why this is the last parade.

Maybe not. Oould you ask him to slow down?

Oould you slow down?

Barry!

OK, I made a huge mistake. This is a total disaster, all my fault.

Yes, it kind of is.

I've ruined the planet. I wanted to help you

with the flower shop. I've made it worse.

Actually, it's completely closed down.

I thought maybe you were remodeling.

But I have another idea, and it's greater than my previous ideas combined.

I don't want to hear it!

All right, they have the roses, the roses have the pollen.

I know every bee, plant and flower bud in this park.

All we gotta do is get what they've got back here with what we've got.

• Bees.
• Park.

• Pollen!
• Flowers.

• Repollination!
• Across the nation!

Tournament of Roses, Pasadena, Oalifornia.

They've got nothing but flowers, floats and cotton candy.

Security will be tight.

I have an idea.

Vanessa Bloome, FTD.

Official floral business. It's real.

Sorry, ma'am. Nice brooch.

Thank you. It was a gift.

Once inside, we just pick the right float.

How about The Princess and the Pea?

I could be the princess, and you could be the pea!

Yes, I got it.

• Where should I sit?
• What are you?

• I believe I'm the pea.
• The pea?

It goes under the mattresses.

• Not in this fairy tale, sweetheart.
• I'm getting the marshal.

You do that! This whole parade is a fiasco!

Let's see what this baby'll do.

Hey, what are you doing?!

Then all we do is blend in with traffic...

...without arousing suspicion.

Once at the airport, there's no stopping us.

Stop! Security.

• You and your insect pack your float?
• Yes.

Has it been in your possession the entire time?

Would you remove your shoes?

• Remove your stinger.
• It's part of me.

I know. Just having some fun. Enjoy your flight.

Then if we're lucky, we'll have just enough pollen to do the job.

Oan you believe how lucky we are? We have just enough pollen to do the job!

I think this is gonna work.

It's got to work.

Attention, passengers, this is Oaptain Scott.

We have a bit of bad weather in New York.

It looks like we'll experience a couple hours delay.

Barry, these are cut flowers with no water. They'll never make it.

I gotta get up there and talk to them.

Be careful.

Oan I get help with the Sky Mall magazine?

I'd like to order the talking inflatable nose and ear hair trimmer.

Oaptain, I'm in a real situation.

• What'd you say, Hal?
• Nothing.

Bee!

Don't freak out! My entire species...

What are you doing?

• Wait a minute! I'm an attorney!
• Who's an attorney?

Don't move.

Oh, Barry.

Good afternoon, passengers. This is your captain.

Would a Miss Vanessa Bloome in 24B please report to the cockpit?

And please hurry!

What happened here?

There was a DustBuster, a toupee, a life raft exploded.

One's bald, one's in a boat, they're both unconscious!

• Is that another bee joke?
• No!

No one's flying the plane!

This is JFK control tower, Flight 356. What's your status?

This is Vanessa Bloome. I'm a florist from New York.

Where's the pilot?

He's unconscious, and so is the copilot.

Not good. Does anyone onboard have flight experience?

As a matter of fact, there is.

• Who's that?
• Barry Benson.

From the honey trial?! Oh, great.

Vanessa, this is nothing more than a big metal bee.

It's got giant wings, huge engines.

I can't fly a plane.

• Why not? Isn't John Travolta a pilot?
• Yes.

How hard could it be?

Wait, Barry! We're headed into some lightning.

This is Bob Bumble. We have some late-breaking news from JFK Airport,

where a suspenseful scene is developing.

Barry Benson, fresh from his legal victory...

That's Barry!

...is attempting to land a plane, loaded with people, flowers

and an incapacitated flight crew.

Flowers?!

We have a storm in the area and two individuals at the controls

with absolutely no flight experience.

Just a minute. There's a bee on that plane.

I'm quite familiar with Mr. Benson and his no-account compadres.

They've done enough damage.

But isn't he your only hope?

Technically, a bee shouldn't be able to fly at all.

Their wings are too small...

Haven't we heard this a million times?

"The surface area of the wings and body mass make no sense."

• Get this on the air!
• Got it.

• Stand by.
• We're going live.

The way we work may be a mystery to you.

Making honey takes a lot of bees doing a lot of small jobs.

But let me tell you about a small job.

If you do it well, it makes a big difference.

More than we realized. To us, to everyone.

That's why I want to get bees back to working together.

That's the bee way! We're not made of Jell-O.

We get behind a fellow.

• Black and yellow!
• Hello!

Left, right, down, hover.

• Hover?
• Forget hover.

This isn't so hard. Beep-beep! Beep-beep!

Barry, what happened?!

Wait, I think we were on autopilot the whole time.

• That may have been helping me.
• And now we're not!

So it turns out I cannot fly a plane.

All of you, let's get behind this fellow! Move it out!

Move out!

Our only chance is if I do what I'd do, you copy me with the wings of the plane!

Don't have to yell.

I'm not yelling! We're in a lot of trouble.

It's very hard to concentrate with that panicky tone in your voice!

It's not a tone. I'm panicking!

I can't do this!

Vanessa, pull yourself together. You have to snap out of it!

You snap out of it.

You snap out of it.

• You snap out of it!
• You snap out of it!

• You snap out of it!
• You snap out of it!

• You snap out of it!
• You snap out of it!

• Hold it!
• Why? Oome on, it's my turn.

How is the plane flying?

I don't know.

Hello?

Benson, got any flowers for a happy occasion in there?

The Pollen Jocks!

They do get behind a fellow.

• Black and yellow.
• Hello.

All right, let's drop this tin can on the blacktop.

Where? I can't see anything. Oan you?

No, nothing. It's all cloudy.

Oome on. You got to think bee, Barry.

• Thinking bee.
• Thinking bee.

Thinking bee! Thinking bee! Thinking bee!

Wait a minute. I think I'm feeling something.

• What?
• I don't know. It's strong, pulling me.

Like a 27-million-year-old instinct.

Bring the nose down.

Thinking bee! Thinking bee! Thinking bee!

• What in the world is on the tarmac?
• Get some lights on that!

Thinking bee! Thinking bee! Thinking bee!

• Vanessa, aim for the flower.
• OK.

Out the engines. We're going in on bee power. Ready, boys?

Affirmative!

Good. Good. Easy, now. That's it.

Land on that flower!

Ready? Full reverse!

Spin it around!

• Not that flower! The other one!
• Which one?

• That flower.
• I'm aiming at the flower!

That's a fat guy in a flowered shirt. I mean the giant pulsating flower

made of millions of bees!

Pull forward. Nose down. Tail up.

Rotate around it.

• This is insane, Barry!
• This's the only way I know how to fly.

Am I koo-koo-kachoo, or is this plane flying in an insect-like pattern?

Get your nose in there. Don't be afraid. Smell it. Full reverse!

Just drop it. Be a part of it.

Aim for the center!

Now drop it in! Drop it in, woman!

Oome on, already.

Barry, we did it! You taught me how to fly!

• Yes. No high-five!
• Right.

Barry, it worked! Did you see the giant flower?

What giant flower? Where? Of course I saw the flower! That was genius!

• Thank you.
• But we're not done yet.

Listen, everyone!

This runway is covered with the last pollen

from the last flowers available anywhere on Earth.

That means this is our last chance.

We're the only ones who make honey, pollinate flowers and dress like this.

If we're gonna survive as a species, this is our moment! What do you say?

Are we going to be bees, orjust Museum of Natural History keychains?

We're bees!

Keychain!

Then follow me! Except Keychain.

Hold on, Barry. Here.

You've earned this.

Yeah!

I'm a Pollen Jock! And it's a perfect fit. All I gotta do are the sleeves.

Oh, yeah.

That's our Barry.

Mom! The bees are back!

If anybody needs to make a call, now's the time.

I got a feeling we'll be working late tonight!

Here's your change. Have a great afternoon! Oan I help who's next?

Would you like some honey with that? It is bee-approved. Don't forget these.

Milk, cream, cheese, it's all me. And I don't see a nickel!

Sometimes I just feel like a piece of meat!

I had no idea.

Barry, I'm sorry. Have you got a moment?

Would you excuse me? My mosquito associate will help you.

Sorry I'm late.

He's a lawyer too?

I was already a blood-sucking parasite. All I needed was a briefcase.

Have a great afternoon!

Barry, I just got this huge tulip order, and I can't get them anywhere.

No problem, Vannie. Just leave it to me.

You're a lifesaver, Barry. Oan I help who's next?

All right, scramble, jocks! It's time to fly.

Thank you, Barry!

That bee is living my life!

Let it go, Kenny.

• When will this nightmare end?!
• Let it all go.

• Beautiful day to fly.
• Sure is.

Between you and me, I was dying to get out of that office.

You have got to start thinking bee, my friend.

• Thinking bee!
• Me?

Hold it. Let's just stop for a second. Hold it.

I'm sorry. I'm sorry, everyone. Oan we stop here?

I'm not making a major life decision during a production number!

All right. Take ten, everybody. Wrap it up, guys.

I had virtually no rehearsal for that.

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

Learn more at Review Commons

Reply to the reviewers

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

**Summary**

The authors have performed highly quantitative analyses of GPCR signaling to reveal heterogenous ERK and Akt activation patterns by using kinase translocation reporters. Using a massive number of single-cell imaging data, the authors show heterogeneous responses to GPCR agonists in the absence or presence of inhibitors. By cluster analysis, the responses of ERK and Akt were classified into eight and three patterns. This paper is clearly written with sufficient information for the reproducibility. However, the conclusion may not be necessarily supported by the provided data as described below.

**Major comments:**

This work has been well done in an organized way and adds new insight into the regulation of protein kinases by GPCRs. The conclusion will be of great interest in the field of single-cell signal dynamics and quantitative biology. On a bit negative note, considering the complexity of the downstream of GPCRs, some of the conclusions may need revision. *

We thank the reviewer for the evaluation and for raising a number of comments that have helped us to strengthen the manuscript and that will be addressed below.

1. The conclusion of the title that "Heterogeneity and dynamics of ERK/Akt activation by GPCR depend on the activated heterotrimeric G proteins," may not be supported by the data. The authors compared just one pair each of GPCR and ligand. The heterogeneity may come from the nature of the ligand or the characteristics of the single clone chosen for this study. The title may suggest that the heterogeneity depends only on the G-protein (although that is not what the title says). Instead, we mean that G-proteins play a role in the heterogeneity, as we infer from the experiments with the G-protein inhibitors. If the reviewer feels strongly about this, we are open to changing the title, for instance to:

“Kinase translocation reporters reveal the single cell heterogeneity and dynamics of ERK and Akt activation by G protein-coupled receptors”

• The obvious question is that why the authors did not analyze the correlation between ERK and Akt activity more extensively. Cell Profiler will be able to extract multiple cellular features. Linking the heterogeneous signals to cellular features will benefit readers in the broad cell biology field. If the authors wish to write another paper with that data, it should be at least discussed. *

We agree that we can add more information on the correlation between ERK and Akt activity and we have added a plot that shows the co-incidence of the ERK and Akt clusters. This is now panel C of figure 8. We have no wish of writing another paper and we have made the data and code available, so anyone can do a more detailed analysis if desired.

We appreciate the suggestion to correlate activities with cellular features, such as cell area and shape. However, in our analysis we use nuclear fluorescence to segment the nuclear and cytoplasmic fluorescence (as generally done in studies that use KTRs). Therefore, the information on cellular features is not readily available. Such analysis would require a marker for the cytoplasm or membrane (or yet another image analysis procedure).

Another apparent flaw of this work is that YM was not challenged to UK-stimulated cells. The authors probably assumed lack of effect. Nevertheless, I believe it is required to show. Or, remove the PTx data from the Histamine-stimulated cell data.

We agree that this is valuable data to include. Unfortunately, this experiment was done in a slightly different condition than the other experiments (different spacing of the time intervals) and we initially skipped the data for these reasons. After careful examination of the data, we have decided to include these data (added to figures 3 & 5).

We note that we still miss the data from the YM+PTx data for UK and we have currently no way to carry out these experiments (mainly due to lack of funding). In our opinion, the absence of this data is not critical for the interpretation of the results. We prefer to show the YM+PTx data for the other two conditions.

The most interesting response is that of S1P. ERK is biphasically activated. Combined inhibition of Gq and Gi failed to suppress ERK activity. It may be discussed why the biphasic activation pattern was not identified by the classification.

We think that the biphasic activation pattern is reflected by cluster 7 and 8 and we now mention this in the text: “The biphasic ERK activation pattern, which is specific for stimulation with S1P are reflected by cluster 7 and 8.”

For clarity, we now added the dynamics for each cluster to figure 9.

*The authors argue that the brightness of the KTR reporter was not correlated with the dynamic range of ERK or Akt reporter (Supplementary Figure 3), but it is not clear. I had an impression that ERK-KTR brightness (Supplementary Figure 3A) has a slightly negative correlation with "maximum change in CN ratio" (Supplementary Figure 3B) (e.g., A6>B3>B5 in brightness and A6

We thank the reviewer for the suggestion and have now added this data to supplemental figure 3 as panel C.

The authors have shown cluster analyses for the temporal patterns in kinase activations. However, the only difference of cluster 3 and 5 (Figure 7) seem to be amplitude. The authors have also shown the amplitude is dependent on the dose of the activators, which together makes it difficult to see the biological meaning of discriminating the two patterns in comparing different agonists, e.g., Histamine, UK, and S1P. The authors should discuss their views on how the clustering analyses will benefit biological interpretations together with possible limitations.

This is a valid point, and it is a consequence of clustering method. We have added text to the discussion to explain our view: “The clustering is a powerful method for the detection of patterns and simplification of large amounts of data. Yet, it should be realized that clustering is mathematical procedure that is not necessarily reflecting the biological processes. One example is the graded response of ERK and Akt activities to ligands, whereas cells are grouped in weak, middle and strong responders. This may be solved by developing and using clustering methods that take the underlying biological processes into account.”

Considering the importance of the content, the supplemental note 2 may be included in the main text.

We appreciate this suggestion, and we have incorporated supplemental note 2 in the main text.

\*Minor comments:**

1. The authors should clarify the cell type they used (HeLa cells) in the main text and figure legends. *

This information is now indicated in the first paragraph of the results section and in the legend of figure1.

Supplementary note1: The data-not-shown data (no correlation of KTR expression and its response to serum) should be very informative for the readers. The data should be shown as an independent supplementary figure.

This relates to major point 5 and we agree that this is valuable. The data of the expression and the maximum response has been added to supplementary figure 3 as panel C.

Supplementary Figure S2: The authors should clarify this image processing is about background subtraction. Also, the authors should clearly note "rolling ball with a radius of 70 pixels" is about an ImageJ function, "Subtract Background".

We added text to highlight that the processing is a background subtraction and noise reduction. We added text to explain it is a FIJI function.

• 1. Supplementary Figure S5: Figure labels are "A, A, B, B" not "A, B, C, D". Also the top two figures are lacking Y axis labels. *

Thanks for pointing this out. We the labels are corrected.

Page6 (top): The authors should mention the description is about Supplementary Figure S5 (UK) and Supplementary Figure S6 (S1P).

This is an accidental omission, it is corrected.

Figure 3: the figures are lacking x-axis labels (probably uM, nM and pM from left).

Well spotted, this is fixed by adding the units to the labels for each ligand.

Values in tables: The significant figure must be 2, at best. This should be consistent throughout the text. For example, "The EC50 values for histamine, S1P and UK were respectively 0.3 μM, 63.7 nM and 2.5 pM." This is somewhat awkward.

This has been fixed in the text and in the table.

Page 7, the first paragraph: No comments on S1P!

We added our observation that: “The response to S1P is hardly affected by YM, but the amplitude is reduced by PTx.”

Fig. 3: 100 mM must read as 100 micromolar.

We do not understand this comment, but the units of figure 3 are now corrected (see also point 6).

• Fig. 9: Concentration unit is missing.*

Thanks for pointing this out, units are added.

• Page 11, line 4: EKR should read as ERK. *

Fixed

• Page 13: "So far, only a couple of studies looked into kinase activation by GPCRs and these studies used overexpressed receptors [32,33]." Please describe precisely. Protein kinase activation by GPCR has been studied more than 20 years. Why are these two recent papers cited here? *

We updated the text to explain that: “So far, only a couple of studies looked into kinase activation by GPCRs in single cells with KTRs and these studies used overexpressed receptors”.

"This is in marked contrast to other fluorescent biosensors that typically require an overexpressed receptor for robust responses [34]." Following words should be included in the end: "in our hands".

We’ve included the suggested line.

• "Histamine is reported to predominantly activate Gq in HeLa cells [36] and UK activates Gi [37]." Describe the name of receptors for the better understanding. *

We added names: “Histamine is reported to predominantly activate Gq in HeLa cells by the histamine H1 receptor [36] and UK activates Gi by α2-adrenergic receptors [37]”

• "S1P can activate a number of different GPCRs, all known to be expressed by HeLa cells [24]." Why is this paper chosen? The authors can easily find RNA-Seq data, if they wish to see the expression level. The cited paper did not scrutinize the S1P receptors expressed in HeLa cells. *

The S1PR levels are scrutinized in the cited paper, but it is ‘hidden’ in the supplemental figure S4A. We will clarify this and explicitly mention this supplemental figure: “The situation for S1P is different. S1P can activate a number of different GPCRs, all known to be expressed by HeLa cells as shown in the supplemental figure S4A of [24]”

*Reviewer #1 (Significance (Required)):

The authors used biosensors for ERK and Akt to examine the kinetics of activation by GPCR ligands. Technical advancement is in the massive analysis method and cluster analysis. This is an important direction for the quantitative biology. GPCR signaling is complex because of multiple receptors coupled with different G proteins. The simple ones such as histamine receptor and alpha2-adrenergic receptor can be easily analyzed as shown in this study. However, there are many S1P receptors, which make the interpretation difficult. If the authors could have shown interesting proposal on this data, the paper may interest many researchers in the field of cell biology and systems biology.

Expertise: Cell biology, signal transduction of protein kinases, fluorescence microscopy.

**Referee Cross-commenting**

1. I agree with the other two reviewers in that immunoblotting data is required to show the efficiency of P2A cleavage.
2. All reviewers think it looks strange that the authors did not show UK + YM data.

3. Showing the dynamic range of the biosensors will reinforce the data as Reviewer #3 states. ERK-KTR is quite sensitive and can be easily saturated. Ideally, the ratio of pERK vs ERK can be quantified by the different mobility in SDS-PAGE. But, I do not know how we can do it for Akt.

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

   **Summary**

   In this paper Chavez-Abiega and colleagues investigate the dynamics of ERK and Akt activity downstream of several G protein-couples receptors (GPCRs). Using drugs to block specific G-proteins, they probe the activation of ERK/Akt by different heterotrimeric G proteins with fluorescent biosensors at the single cell resolution. Main finding is that ERK/AKT can be activated by different G-proteins, depending on the receptor coupling to the G-protein subclass, and that the ERK/AKT dynamics for S1P are specifically heterogeneous. Moreover, it seems that the AKT signaling response is very similar to ERK after GPCR stimulation.

   **Major points:**

   1) For this paper, the authors produced a new construct to express simultaneously the nuclear marker, the Akt and the ERK biosensors. The tree parts are connected by P2A peptides that determine their separation. Although, the biosensors are based on existing ones, the connection between them by P2A might create artifacts if the separation of the two parts is incomplete. For that, important controls are missing, such as treatment with an ERK and an Akt inhibitor. If the two parts are well separated the inhibitors should block the cytosol translocation of one of the two components and not of the other. This control is also important to check if in HeLa cells the Akt biosensors is not phosphorylated by ERK as well, as described in other reports. Alternatively, P2A separation can be quantified on a protein blot. *

We agree that it is important to establish that the P2A sequence results in separation of the reporters. There are several observations that support our notion that the separation is efficient. First, we have been using the 2A-like sequences for over a decade in HeLa cells (first paper: doi:10.1038/nmeth.1415) and we have never encountered situations where the cleavage was problematic. Second, the distribution in signal of the nuclear Scarlet probe differs substantially from that of the mTurquoise2 and the mNeonGreen probe. Third, the dynamics of the ERK-KTR and Akt-KTR are different. Fourth, we have included new data with an ERK inhibitor, showing that the Akt-KTR responds independently of the ERK-KTR (figure S5). We have also added text to explain this: “Next, we examined the effect of the MEK inhibitor PD 0325901. Pre-incubation with the inhibitor for 20 minutes blocked the response of the ERK-KTR to FBS, but not that of Akt-KTR (Supplemental Figure S5). This supports previous observations [14] [15] that the P2A effectively separates the different components, since the Akt-KTR and ERK-KTR show independent relocation patterns.”

This latter point is also supported by the co-incidence plot of the ERK versus Akt clusters (figure 8C) showing that the probes act independently (which is the main reason for using this strategy).

Although any of the aforementioned points cannot exclude that a small fraction of the probe remains fused, we think that this potential issue is far outweighed by the benefits of the use of 2A peptides.

2) The description of ERK and Akt should be reported in a more uniform way, such as using the same representations for both (e.g. the equivalent of figure 2 for Akt is missing) or the same number of clusters.

We choose to concentrate first on ERK activity, that is why a similar plot for Akt activation is not shown. However, the Akt responses are detailed in figure 4 and supplemental figures S5 and S7.

For the cluster analysis, we looked into the optimal number of clusters (as explained in Supplemental note S2). This number differs for ERK and Akt, since the complexity of the responses is different. We move supplemental note 2 to the main text, which also clarifies the different number of clusters that we used for the analysis.

3) Figure 3 & Figure 5: It seems that the YM and YM+PTx data for the UK 14304 data is missing. This would be an interesting addition to the manuscript, and it is easy to add. A similar analysis for the Akt sensor is missing in figure 3 and should be added for consistency. Figure 4 shows data for Akt, but as timeseries and only for Histamine. See point 2, it would benefit the reader greatly if ERK and AKT are presented in a more uniform and complete fashion throughout the manuscript.

We agree that it is valuable to add data for UK with YM. This data has been added, see also reply to reviewer 1, major point 3

As for the Akt data, the response was largely similar albeit with less complexity and a lower amplitude. This is the reason to focus on ERK and this is explained in the discussion: “Therefore, the measurement of Akt does not add information. Moreover, the Akt response had a relatively poor amplitude.”

4) In the results text of figure 4, the authors state that "...as shown in Figure 4C-D, which is in line with the effect of histamine on ERK.". It is unclear what the authors mean with this statement, the effects of single/double inhibition of Histamine stimulation on ERK are not quantified or discussed. Both responses can be quantified more carefully and compared.

We agree that this is poorly formulated, and we rephrase it to make it clearer: “Inhibition of Gq (figure 4C) decreases the maximum activity up to ~70%, and simultaneous inhibition of Gq and Gi causes a decrease of the responses up to ~90%, as shown in Figure 4D. These Akt amplitudes and effects of inhibitors are largely similar to those observed for ERK.”

5) This paper would benefit from a mechanistic investigation. For instance, the authors could investigate the pathways that lead to the generation of the pulse of ERK and Akt. These (preliminary) results presented call for deeper investigation into the signaling pathway from Gai and Gaq to ERK and AKT, and the authors are in a great position to probe this. One simple approach is to explore the upstream pathway, such as the MAPK cascade, PI3K, RTKs by means of inhibitors.

We agree that there is much that can be done with the KTR technology. To this end, we deposit the probe and make all our data analysis methods available. We hope that others will benefit from our efforts and use the tools for mechanistic studies. 6) Since different G-proteins seem to elicit similar responses on ERK and especially for Akt, it is likely a B-arrestin / beta-gamma subunit mediated mechanism? It would be interesting to hear what the authors think of this, did they investigate/consider this possibility? E.g. Perhaps blocking RTK signaling / B-arrestin signaling would reduce heterogeneity?

We appreciate this suggestion and have added a statement to the discussion: “Based on our data, we cannot exclude that beta-arrestin or RTKs play a role in the activation of ERK and Akt. To study the role of non-classical routes to ERK activation, inhibitor studies, or probes that interrogate these processes would be useful.”

7) The authors should take a serious effort to summarize the data in the figures better. Many plots that can be merged/presented in a more concise way, which would improve the readability of the manuscript greatly.

We will take care to improve the data visualization during the revision. We will address any specific points that are raised.

\*Minor points:**

1) The authors should spell out in the legend of each figure if they are representing the absolute C/N or the normalized C/N *

Thanks for pointing this out. We added this information to the legends and it is also written in the materials and methods: "data was normalized by subtracting the average of two time points prior to stimulation (usually the 5th and 6th time point) from every data point."

2) In Figure 2 the authors should show the control with no stimulus. Also would be informative to inform the reader about the stimulation protocol used, or indicate the stimulation time and length in the figure.

We have added the no stimulus control and added the information to the legend.

3) Figure 3: This figure would benefit from a different presentation of the data, it is currently confusing. E.g. Average curves per drug condition in a single graph would present the point the authors make more clear and concise, and this single cell overview can be moved to supplements.

Our main focus is on single cell analysis and we think that the current plots convey the message in a clear and transparent fashion. It is in line with the recently proposed idea of “superplot” (https://doi.org/10.1083/jcb.202001064). We also provide scripts and data, enabling anyone to replot the data if that is desired.

4) Figure 4 legend states "CN ERK" and "ERK C/N", but is depicting only Akt responses? Only in 4c the axes are labeled, this together is very confusing.

Thanks for pointing this out. This is corrected

*5) Figure 5 is missing the controls with ERK and Akt inhibitors, to show the loss of correlation between the AUC of the two

*We have included data with a MEK inhibitor (new supplemental figure S5) to demonstrate the specificity of the probe and it also demonstrates that Akt can be independently activated

6) Figure 6, the presumed lack of correlation between baseline activity and response should be confirmed statistically.

We have improved the presentation of figure 6. We now show only the maximal response and how this varies between conditions. It is evident from the graphical representation that the curves are similar for the different start ratios. We feel that the use of statistics is not necessary here.

7) It seems that in S1P treated cells there is a second oscillation in ERK activity well visible in figure 2 and also in S10. Could the authors comment on that?

We add text to the discussion to address this: “We observed that activation of endogenous S1P receptors resulted in a strong, but highly heterogeneous ERK-KTR response, with two peaks in a population of cells.” and “When PTx is present, the biphasic response is abolished and the first peak of activation is reduced, suggesting that the initial response is due to Gi signaling.”

*8) In the abstract it is unclear what authors mean with "UK".

*Changed to brimonidine

9) Figure 9, it would be helpful to visually repeat the typical curve of the different clusters here, to guide the reader.

This is a good suggestion and we have added the typical curves for the different clusters to the plot.

10) The observed heterogeneity in responses might be related to different cell cycle stages, did the authors investigated/consider this possibility (e.g. with a cell cycle biosensor)?

This is a very valid comment. We do consider its importance, but we did not investigate the effects of cell cycle.

*Reviewer #2 (Significance (Required)):

The paper describes with high accuracy the dynamics of ERK and Akt biosensors downstream of several GPCRs.

However, it feels like this is a preliminary report that leaves many important questions still open. It does not provide mechanistic insight and doesn't fully exploit the potential of single-cell technologies. The authors have the tools to investigate several important questions that are left open in the manuscript (e.g. connection Gaq/Gai to ERK/AKT, B-arrestin/betagamma involvement). Moreover, some important controls are missing. The authors should also consider the data presentation in the figures, to improve readability and interpretation of the manuscript.

Properly revised, would be of interest for a broad audience in cell biology, specifically GPCR and RTK signaling fields.

Expertise in cell biology, gpcr and rtk signaling, fluorescent biosensors.

**Referee Cross-commenting**

I agree with the assessments by the other reviewers.

Indeed showing the dynamic range of the biosensors, as Reviewer #3 states, would strengthen the manuscript and put the S1P response heterogeneity in context.

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

This manuscript uses a live-cell biosensor approach to examine the activity kinetics of the ERK and Akt kinases in response to different GPCR ligands. The paper provides a detailed description of the development of a HeLa reporter cell line that expresses both Akt and ERK biosensors, along with a nuclear marker for use in cell tracking. The authors then catalog the individual responses from thousands of cells to three GPCR ligands. Individual cells show strong correlation in stimulated ERK and Akt activity. Using inhibitors for Gq and Gi proteins, it is shown that ERK and Akt activities are dependent on different G proteins. The authors also show that the heterogeneous responses within each population can be decomposed into several clusters representing similar dynamic behaviors; the frequencies of these clusters increase or decrease depending on treatments.

Overall, this is a well documented extension of an existing biosensor approach to examine GPCR signaling, and the approach is clearly described. There are however, some control experiments that are essential to support the conclusions.

**Major comments:**

1. The maximal responses of ERK and Akt biosensors in the selected cell clone are not adequately shown. Although FBS responsiveness is used as a validation and selection criterion, it would be much more informative to show the distribution of single-cell responses for defined activators of ERK and Akt, such as EGF and IGF-1, respectively. Without seeing the variability in these responses, it is difficult to put the heterogeneity observed in GPCR responses into context. *

The FBS is used as a (crude) way to examine responsiveness of the clones. We understand that treatment of the cells with growth factors would add more data and therefore more information to the manuscript. However, the main aim of the study is to examine whether KTR technology can be used to study endogenous GPCR signaling. It is clear that the answer is positive. Next, we asked whether we could detect differences for different GPCRs and that was the focus of this study. It is unclear how studies with EGF would add new information to our observations.

It is not clear whether the basal activity for the biosensors represents actual activity or simply the measurement floor. This should be established by using saturating treatment inhibitors for ERK and Akt to determine the biosensor readings in the absence of any activity. Ideally, an approach such as the one shown by Ponsioen et al. (PMID: 33795873) should be used to determine the dynamic range of the sensors.

We studied the basal levels and the effect of serum. We found that the basal levels are reduced by replacing the growth medium with serum free medium. The reduction in C/N ratio reaches a plateau after ~ 2hours of replacing the medium. This data is added as supplemental figure S4. Therefore, we have performed all experiments 2 hours after replacing the growth medium with serum free imaging medium.

Because the biosensors are separated by self-cleaving peptides, there is the potential that incomplete cleavage could complicate the results. Cleavage efficiency should be assessed by western blot or an equivalent method.

We agree that it is important to establish that the P2A sequence results in separation of the reporters. There are several observations that support our notion that the separation is efficient. First, we have been using the 2A-like sequences for over a decade in HeLa cells (first paper: doi:10.1038/nmeth.1415) and we have never encountered situations where the cleavage was problematic. Second, the distribution in signal of the nuclear Scarlet probe differs substantially from that of the mTurquoise2 and mNeonGreen probe. Third, the dynamics of the ERK-KTR and Akt-KTR are different. Fourth, we have included new data with an ERK inhibitor, showing that the Akt-KTR responds independently of the ERK-KTR (figure S5). We have also added text to explain this: “Next, we examined the effect of the MEK inhibitor PD 0325901. Pre-incubation with the inhibitor for 20 minutes blocked the response of the ERK-KTR to FBS, but not that of Akt-KTR (Supplemental Figure S5). This supports previous observations [14] [15] that the P2A effectively separates the different components, since the Akt-KTR and ERK-KTR show independent relocation patterns.”

This latter point is also supported by the co-incidence plot of the ERK versus Akt clusters (figure 8C) showing that the probes act independently (which is the main reason for using this strategy).

Although any of the aforementioned points cannot exclude that a small fraction of the probe remains fused, we think that this potential issue is far outweighed by the benefits of the use of 2A peptides.

Ideally, an alternate method such as immunofluorescence for phosphorylated ERK/Akt or their substrates could be used in a subset of the conditions to validate the heterogeneity observed by the biosensors.

We thank the reviewer for this suggestion. Since we see a lot of variability in the dynamics, which cannot be addressed by immunofluorescence, we do not think this will experiment be valuable. Of note, GPCR activity is known to induce ERK activity in a dose-dependent manner on a population level as determined with immunolabeling methods and that is what we observe with the ERK KTR as well.

\*Minor comments:**

1. In the introduction, more rationale and background could be provided for the examination of GPCR-stimulated ERK and Akt activity. There is not much information provided on why this is an interesting question. Other than the involvement of beta arrestin and RTK transactivation, which are mentioned, what mechanisms are known to be involved? Also, the importance of ERK and Akt in cancer is brought up, but it is not made clear how this approach or results would connect specifically to a cancer model. *

We think that the connections between heterotrimeric G-proteins and kinase activity are not well established. Except for the classical Gq -> PKC -> ERK pathway, not so much is known and we add this to the discussion: “The classic downstream effector of Gq is PKC, which can activate ERK. On the other hand, it is not so clear how Gq would affect Akt. The molecular network that connects the activity of Gi with kinases also not so clear.”

*It would be helpful to provide some explanation for why the UK+YM and UK+YM+PTx data are not shown in figure 3

*

We agree that this is valuable data to include. Unfortunately, this experiment was done in a slightly different condition than the other experiments (different spacing of the time intervals) and we initially skipped the data for these reasons. After careful examination of the data, we have decided to include these data (added to figures 3 & 5).

We note that we still miss the data from the YM+PTx data for UK and we have currently no way to carry out these experiments (mainly due to lack of funding). We prefer to show the YM+PTx data for the other two conditions.

• In the Abstract figure, it is not clear which samples "Inhibitor" and "Agonist" are referring to. **

  *

Thanks for this comment. We will remove the visual abstract when the preprint is submitted to a journal.

* Reviewer #3 (Significance (Required)):

While similar reporter approaches have been used in a number of papers to examine growth factor signaling dynamics of ERK and Akt, this manuscript is the first I have seen to examine the responses of these kinases to different GPCR ligands. In doing so, it adds significantly to the growing body of literature on single-cell signaling responses. The mechanisms of ERK and Akt activation by GPCRs remain somewhat ambiguous, and the data reported here will be helpful in refining models for this signal transduction process. The findings that the GPCR ligands examined show different G protein dependencies than anticipated is an interesting facet, as is the observation that, while ERK and Akt are generally correlated, inhibition of Gi preferentially blocks S1P-induced ERK activity more so than Akt activity. However, the main findings of heterogeneity in signaling, and the observation of clusters that describe the different dynamic behaviors present within a population, are highly consistent with what has been shown in other systems. Overall, this study is a useful confirmation that GPCR signaling to ERK and Akt follows a similar pattern to other forms of stimulation.

**Referee Cross-commenting**

Regarding the dynamic range, I don't think it is necessary to do a western blot (though this would be nice) - I think it would be sufficient to show maximal activation using EGF/IGF and full suppression using MEK/ERK and Akt inhibitors. I also agree that all the points raised by the other reviewers. In particular, a deeper exploration and better visualization of the relationship between ERK and Akt would be very useful, as noted by both Reviewers #1 and #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 #1

Evidence, reproducibility and clarity

Summary

The authors have performed highly quantitative analyses of GPCR signaling to reveal heterogenous ERK and Akt activation patterns by using kinase translocation reporters. Using a massive number of single-cell imaging data, the authors show heterogeneous responses to GPCR agonists in the absence or presence of inhibitors. By cluster analysis, the responses of ERK and Akt were classified into eight and three patterns. This paper is clearly written with sufficient information for the reproducibility. However, the conclusion may not be necessarily supported by the provided data as described below.

Major comments:

This work has been well done in an organized way and adds new insight into the regulation of protein kinases by GPCRs. The conclusion will be of great interest in the field of single-cell signal dynamics and quantitative biology. On a bit negative note, considering the complexity of the downstream of GPCRs, some of the conclusions may need revision.

1. The conclusion of the title that "Heterogeneity and dynamics of ERK/Akt activation by GPCR depend on the activated heterotrimeric G proteins," may not be supported by the data. The authors compared just one pair each of GPCR and ligand. The heterogeneity may come from the nature of the ligand or the characteristics of the single clone chosen for this study.
2. The obvious question is that why the authors did not analyze the correlation between ERK and Akt activity more extensively. Cell Profiler will be able to extract multiple cellular features. Linking the heterogeneous signals to cellular features will benefit readers in the broad cell biology field. If the authors wish to write another paper with that data, it should be at least discussed.
3. Another apparent flaw of this work is that YM was not challenged to UK-stimulated cells. The authors probably assumed lack of effect. Nevertheless, I believe it is required to show. Or, remove the PTx data from the Histamine-stimulated cell data.
4. The most interesting response is that of S1P. ERK is biphasically activated. Combined inhibition of Gq and Gi failed to suppress ERK activity. It may be discussed why the biphasic activation pattern was not identified by the classification.
5. The authors argue that the brightness of the KTR reporter was not correlated with the dynamic range of ERK or Akt reporter (Supplementary Figure 3), but it is not clear. I had an impression that ERK-KTR brightness (Supplementary Figure 3A) has a slightly negative correlation with "maximum change in CN ratio" (Supplementary Figure 3B) (e.g., A6>B3>B5 in brightness and A6<B3<B5 in maximum change in CN ratio). The authors should show dot plots of average fluorescence vs. the maximum change in CN ratio.
6. The authors have shown cluster analyses for the temporal patterns in kinase activations. However, the only difference of cluster 3 and 5 (Figure 7) seem to be amplitude. The authors have also shown the amplitude is dependent on the dose of the activators, which together makes it difficult to see the biological meaning of discriminating the two patterns in comparing different agonists, e.g., Histamine, UK, and S1P. The authors should discuss their views on how the clustering analyses will benefit biological interpretations together with possible limitations.
7. Considering the importance of the content, the supplemental note 2 may be included in the main text.

Minor comments:

1. The authors should clarify the cell type they used (HeLa cells) in the main text and figure legends.
2. Supplementary note1: The data-not-shown data (no correlation of KTR expression and its response to serum) should be very informative for the readers. The data should be shown as an independent supplementary figure.
3. Supplementary Figure S2: The authors should clarify this image processing is about background subtraction. Also, the authors should clearly note "rolling ball with a radius of 70 pixels" is about an ImageJ function, "Subtract Background".
4. Supplementary Figure S5: Figure labels are "A, A, B, B" not "A, B, C, D". Also the top two figures are lacking Y axis labels.
5. Page6 (top): The authors should mention the description is about Supplementary Figure S5 (UK) and Supplementary Figure S6 (S1P).
6. Figure 3: the figures are lacking x-axis labels (probably uM, nM and pM from left).
7. Values in tables: The significant figure must be 2, at best. This should be consistent throughout the text. For example, "The EC50 values for histamine, S1P and UK were respectively 0.3 μM, 63.7 nM and 2.5 pM." This is somewhat awkward.
8. Page 7, the first paragraph: No comments on S1P!
9. Fig. 3: 100 mM must read as 100 micromolar.
10. Fig. 9: Concentration unit is missing.
11. Page 11, line 4: EKR should read as ERK.
12. Page 13: "So far, only a couple of studies looked into kinase activation by GPCRs and these studies used overexpressed receptors [32,33]." Please describe precisely. Protein kinase activation by GPCR has been studied more than 20 years. Why are these two recent papers cited here?
13. "This is in marked contrast to other fluorescent biosensors that typically require an overexpressed receptor for robust responses [34]." Following words should be included in the end: "in our hands".
14. "Histamine is reported to predominantly activate Gq in HeLa cells [36] and UK activates Gi [37]." Describe the name of receptors for the better understanding.
15. "S1P can activate a number of different GPCRs, all known to be expressed by HeLa cells [24]." Why is this paper chosen? The authors can easily find RNA-Seq data, if they wish to see the expression level. The cited paper did not scrutinize the S1P receptors expressed in HeLa cells.

Significance

The authors used biosensors for ERK and Akt to examine the kinetics of activation by GPCR ligands. Technical advancement is in the massive analysis method and cluster analysis. This is an important direction for the quantitative biology. GPCR signaling is complex because of multiple receptors coupled with different G proteins. The simple ones such as histamine receptor and alpha2-adrenergic receptor can be easily analyzed as shown in this study. However, there are many S1P receptors, which make the interpretation difficult. If the authors could have shown interesting proposal on this data, the paper may interest many researchers in the field of cell biology and systems biology.

Expertise: Cell biology, signal transduction of protein kinases, fluorescence microscopy.

Referee Cross-commenting

1. I agree with the other two reviewers in that immunoblotting data is required to show the efficiency of P2A cleavage.
2. All reviewers think it looks strange that the authors did not show UK + YM data.
3. Showing the dynamic range of the biosensors will reinforce the data as Reviewer #3 states. ERK-KTR is quite sensitive and can be easily saturated. Ideally, the ratio of pERK vs ERK can be quantified by the different mobility in SDS-PAGE. But, I do not know how we can do it for Akt.

There is an interesting analogy here worth pursuing:

This idea and its structure have lots of similarities to those of growth and evolution in Werner R. Loewenstein's The Touchstone of Life: Molecular Information, Cell Communication, and the Foundations of Life. What if we reframe RNA or mitochondria in the role of the filing cabinet? What emergent properties occur in these processes? What do these processes have in common?

I need at least some shorthand idea or word for talking about the circular evolving processes of life in Loewenstein's book. Maybe evolution spirals?

Think inputs and outputs.

Author Response:

Reviewer #2 (Public Review):

Oberle et al. provide a detailed analysis of how descending projections from the auditory cortex interact with ascending auditory projections on neurons in the shell region of the inferior colliculus on a cellular basis. Using optogenetic activation of auditory cortical neurons or projections and electrical stimulation of fibres in combination with whole-cell patch clamp recordings in vivo and in vitro, they show that most neurons in the shell region of the inferior colliculus receive several monosynaptic cortical inputs. In vitro, these descending synapses show sublinear summation with a major tonic component for prolonged stimuli. Both in vivo and in vivo experiments support the idea that descending cortical inputs and ascending inputs from the central inferior colliculus temporally overlap and both activate NMDA and non-NMDA receptors. This cooperativity of inputs leads to supra-linear summation and boosting of the response.

Strengths:

• The manuscript provides a first detailed analysis of a loop between the cortex and midbrain. It elegantly combines in vivo and in vitro electrophysiological techniques to study this network on a cellular/synaptic level.

• These experiments thoroughly characterize the nature of cortical and midbrain excitatory inputs onto shell IC neurons and elucidate how they integrate the ascending and descending inputs on a cellular level.

Weaknesses:

• A major weakness of this study is that they do not directly show that ascending and descending inputs to the IC shell neurons actually coincide, but only imply that this should be the case, considering different latency measurements. Latencies that are measured in the anesthetized preparation may change in the awake behaving animals which may change the timing of the respective inputs.

We rectify this issue in our revision with new data showing that the latency of sound-evoked activity in the superficial IC is similar in anesthetized and awake mice. We acknowledge that the conduction velocity of descending axons may differ between anesthetized and awake state. However, existing data show that conduction velocities of cortical axons increase in the alert brain compared to non-alert conditions (Stoelzel et al., 2017). Taken together, we would expect an increased temporal coincidence of ascending and descending signals in awake compared to anesthetized animals, which all available evidence suggests would enhance NMDAR-dependent non-linearities such as those we described (Gasparini et al., 2004; Gasparini and Magee, 2006; Losonczy and Magee, 2006; Takahashi and Magee, 2009; Branco et al., 2010; Branco and Häusser, 2011). We now revise our Results to highlight that our latency measurements in anesthetized mice represent the upper bound for the arrival of auditory cortical EPSPs.

In addition, the authors do not show to what extent coincidence of ascending and descending inputs to shell IC neurons is maintained for longer and more complex sounds as compared to click stimuli.

Previous work shows that auditory cortico-collicular neurons sustain firing during long, complex sounds (Williamson and Polley, 2019), and our data show that descending transmission is maintained for extended periods of corticofugal activity both in vitro and in vivo (Figure 4E-H). Thus, we would expect temporal overlap of ascending and descending inputs to occur under these conditions as well. We agree that Reviewer #2 touches upon an important knowledge gap. However, we believe that a full investigation of which sounds do and do not engage descending modulation merits a separate, in-depth study.

• The manuscript does not address the question of whether the different neuron types that they encounter in the shell region based on the firing pattern to current injections, vary in their input latencies, their number and distribution of NMDA receptors or their integrative properties. This may have some additional effect on how these neurons process ascending and descending information.

We agree that correlating intrinsic and synaptic properties could reveal something interesting. However, our initial analyses (Figure 3) did not show any striking correlation between membrane biophysics and the half-width or amplitude of descending EPSPs. As such, we had no a priori basis to hypothesize that synaptic integration differs systematically with measurable membrane properties, and the low-throughput of dual pathway stimulation experiments (Figures 6 and 8) precluded collecting a large dataset needed to convincingly determine if any synaptic non-linearity does or does not meaningfully correlate with the cellular biophysics.

We acknowledge this limitation of our study in our revised Discussion. Future studies, perhaps leveraging cell-type specific markers for different IC neurons (Goyer et al., 2019; Naumov et al., 2019; Silveira et al., 2020; Kreeger et al., 2021) will be required to clarify this issue.

• The authors have not demonstrated that silencing of descending inputs from the AC affects IC shell activity.

We did not initially perform this experiment given the extensive literature establishing that silencing auditory cortex modifies the magnitude, timing, and/or selectivity of IC neuron sound responses (Yan and Suga, 1999; Nwabueze-Ogbo et al., 2002; Popelár et al., 2003; Nakamoto et al., 2008, 2010; Anderson and Malmierca, 2013; Popelář et al., 2016; Weible et al., 2020). Indeed, these classic results were a major motivation for us to focus on the cellular mechanisms that support corticofugal transmission. We thus reasoned that a cortical inactivation experiment would be largely confirmatory of prior knowledge, and limited in its potential for mechanistic interpretation given the known caveats of cortical loss-of-function manipulations (Li et al., 2019; Andrei et al., 2021; Slonina et al., 2021). However, we acknowledge that such an experiment is useful to frame our cellular-level findings in a broader, systems-level context. As such, we address Reviewer #2’s concern in our revision with a new experiment demonstrating that auditory cortical silencing indeed affects sound-evoked activity in the IC of awake mice.

Reviewer #3 (Public Review):

Overall, this manuscript is generally nicely written and well-illustrated. I don´t really have any major issues. I like the manuscript but I have a few comments and some issues that need to be addressed.

My main concern is that the authors claim several times that the projections to the central nucleus of IC are weak and they neglect their potential functional role. I think this is a little bit unfortunate. It is true that the large AC projection primarily targets the cortical regions or shell of IC, but it is beyond doubt that it also targets the central nucleus (e.g. Saldaña's studies) . We cannot know whether it is a weak projection or not without central nucleus recordings. Admittedly, these experiments would be challenging, so I would ask the authors to tone down a bit these comments throughout the ms. Also, the reason for the 'weak' projection to the central nucleus may be due to the size and location of the injections made in the auditory cortex. Thus, I would like to see the injections site of Chronos if possible. Likewise, fig 1B is too small and of low quality (at least in my pdf file for review) to appreciate details of labeling. I would suggest that the authors make a separate figure showing the injection site in the AC and larger and clearer labeling in the IC.

We agree that in vitro recordings from the central IC in adult mice are quite challenging. As suggested we have toned down claims of the “weak” projection to central IC and provide micrographs of Chronos injection sites. However, we concur that this is an important point. Thus, we include a new transsynaptic tracing experiment showing the somata of presumptive postsynaptic targets of auditory cortex neurons in the IC. Although the data show that the majority of cortico-recipient IC neurons are located in the shell regions, a few central IC neurons are indeed clearly labeled. Future studies will be required to test the extent and potency of this direct auditory cortex->central IC projection, and to compare the synaptic properties with our results in the shell IC.

Also I wonder if the title of the manuscript should refer to the non-lemniscal IC as most of the data is related to this area.

We have changed the title of the paper to Synaptic Mechanisms of Top-Down Control in the Non-Lemniscal Inferior Colliculus.

While the dogma is that the descending projections are glutamatergic, the authors may care to consider a recently published paper https://www.frontiersin.org/articles/10.3389/fncir.2021.714780/full, which challenges this view by showing that inhibitory long-range VIP-GABAergic neurons target the IC. It would be interesting if the authors could comment on how this projection may have influenced the results of the present study.

We thank Reviewer #3 for pointing out this new study which does indeed relate to our work. However, we don’t think direct GABAergic projections contributed much, if at all to our results. Indeed, the experiments of Figure 5A did not reveal any inhibitory postsynaptic potentials following bath application of NBQX as one might expect from direct stimulation of VIP-GABA axons (these experiments were performed without SR95531 in the bath). Rather, it may be that the VIP-GABA synapses have low release probability, transmit mainly via non-synaptic diffusion (e.g., spillover), or may primarily release the neuropeptide VIP which would be difficult to detect via whole-cell patch-clamp electrophysiology. We now address the work of Bertero et al. in the Discussion section.

References

Anderson LA, Malmierca MS (2013) The effect of auditory cortex deactivation on stimulus-specific adaptation in the inferior colliculus of the rat. Eur J Neurosci 37:52–62.

Andrei AR, Debes S, Chelaru M, Liu X, Rodarte E, Spudich JL, Janz R, Dragoi V (2021) Heterogeneous side effects of cortical inactivation in behaving animals. eLife 10:e66400.

Branco T, Clark BA, Häusser M (2010) Dendritic discrimination of temporal input sequences in cortical neurons. Science 329:1671–1675.

Branco T, Häusser M (2011) Synaptic integration gradients in single cortical pyramidal cell dendrites. Neuron 69:885–892.

Gasparini S, Magee JC (2006) State-dependent dendritic computation in hippocampal CA1 pyramidal neurons. J Neurosci Off J Soc Neurosci 26:2088–2100.

Gasparini S, Migliore M, Magee JC (2004) On the initiation and propagation of dendritic spikes in CA1 pyramidal neurons. J Neurosci Off J Soc Neurosci 24:11046–11056.

Goyer D, Silveira MA, George AP, Beebe NL, Edelbrock RM, Malinski PT, Schofield BR, Roberts MT (2019) A novel class of inferior colliculus principal neurons labeled in vasoactive intestinal peptide-Cre mice. eLife 8:e43770.

Kreeger LJ, Connelly CJ, Mehta P, Zemelman BV, Golding NL (2021) Excitatory cholecystokinin neurons of the midbrain integrate diverse temporal responses and drive auditory thalamic subdomains. Proc Natl Acad Sci U S A 118:e2007724118.

Li N, Chen S, Guo ZV, Chen H, Huo Y, Inagaki HK, Chen G, Davis C, Hansel D, Guo C, Svoboda K (2019) Spatiotemporal constraints on optogenetic inactivation in cortical circuits. eLife 8:e48622.

Losonczy A, Magee JC (2006) Integrative properties of radial oblique dendrites in hippocampal CA1 pyramidal neurons. Neuron 50:291–307.

Nakamoto KT, Jones SJ, Palmer AR (2008) Descending projections from auditory cortex modulate sensitivity in the midbrain to cues for spatial position. J Neurophysiol 99:2347–2356.

Nakamoto KT, Shackleton TM, Palmer AR (2010) Responses in the inferior colliculus of the guinea pig to concurrent harmonic series and the effect of inactivation of descending controls. J Neurophysiol 103:2050–2061.

Naumov V, Heyd J, de Arnal F, Koch U (2019) Analysis of excitatory and inhibitory neuron types in the inferior colliculus based on Ih properties. J Neurophysiol 121:2126–2139.

Nwabueze-Ogbo FC, Popelár J, Syka J (2002) Changes in the acoustically evoked activity in the inferior colliculus of the rat after functional ablation of the auditory cortex. Physiol Res 51 Suppl 1:S95–S104.

Popelár J, Nwabueze-Ogbo FC, Syka J (2003) Changes in neuronal activity of the inferior colliculus in rat after temporal inactivation of the auditory cortex. Physiol Res 52:615–628.

Popelář J, Šuta D, Lindovský J, Bureš Z, Pysanenko K, Chumak T, Syka J (2016) Cooling of the auditory cortex modifies neuronal activity in the inferior colliculus in rats. Hear Res 332:7–16.

Silveira MA, Anair JD, Beebe NL, Mirjalili P, Schofield BR, Roberts MT (2020) Neuropeptide Y Expression Defines a Novel Class of GABAergic Projection Neuron in the Inferior Colliculus. J Neurosci 40:4685–4699.

Slonina ZA, Poole KC, Bizley JK (2021) What can we learn from inactivation studies? Lessons from auditory cortex. Trends Neurosci:S0166-2236(21)00203-4.

Stoelzel CR, Bereshpolova Y, Alonso J-M, Swadlow HA (2017) Axonal Conduction Delays, Brain State, and Corticogeniculate Communication. J Neurosci Off J Soc Neurosci 37:6342–6358.

Takahashi H, Magee JC (2009) Pathway interactions and synaptic plasticity in the dendritic tuft regions of CA1 pyramidal neurons. Neuron 62:102–111.

Weible AP, Yavorska I, Wehr M (2020) A Cortico-Collicular Amplification Mechanism for Gap Detection. Cereb Cortex N Y N 1991 30:3590–3607.

Williamson RS, Polley DB (2019) Parallel pathways for sound processing and functional connectivity among layer 5 and 6 auditory corticofugal neurons. eLife 8:e42974.

Yan J, Suga N (1999) Corticofugal Amplification of Facilitative Auditory Responses of Subcortical Combination-Sensitive Neurons in the Mustached Bat. J Neurophysiol 81:817–824.

Reviewer #3 (Public Review):

Overall, this manuscript is generally nicely written and well-illustrated. I don´t really have any major issues. I like the manuscript but I have a few comments and some issues that need to be addressed.

My main concern is that the authors claim several times that the projections to the central nucleus of IC are weak and they neglect their potential functional role. I think this is a little bit unfortunate. It is true that the large AC projection primarily targets the cortical regions or shell of IC, but it is beyond doubt that it also targets the central nucleus (e.g. Saldaña's studies) . We cannot know whether it is a weak projection or not without central nucleus recordings. Admittedly, these experiments would be challenging, so I would ask the authors to tone down a bit these comments throughout the ms. Also, the reason for the 'weak' projection to the central nucleus may be due to the size and location of the injections made in the auditory cortex. Thus, I would like to see the injections site of Chronos if possible. Likewise, fig 1B is too small and of low quality (at least in my pdf file for review) to appreciate details of labeling. I would suggest that the authors make a separate figure showing the injection site in the AC and larger and clearer labeling in the IC.<br> Also I wonder if the title of the manuscript should refer to the non-lemniscal IC as most of the data is related to this area.<br> While the dogma is that the descending projections are glutamatergic, the authors may care to consider a recently published paper<br> https://www.frontiersin.org/articles/10.3389/fncir.2021.714780/full, which challenges this view by showing that inhibitory long-range VIP-GABAergic neurons target the IC. It would be interesting if the authors could comment on how this projection may have influenced the results of the present study.

Reviewer #1 (Public Review):

This paper reports features of the development (and subsequent loss) of the egg tooth of the short-beaked echidna (T. aculeatus) at the histological level. Based on these features, the authors then consider the homology of the egg tooth/caruncle of the echidna with those of avian and non-avian reptiles. The authors report that while the echidna egg tooth is first apparent as a Shh-expression epithelial placode, the tooth then takes shape by evagination, rather than invagination, of that placode. This is reminiscent of the first teeth of some reptiles. The authors also find that the echidna egg tooth is anchored directly to the bone of the premaxilla (again, reminiscent of the mechanism of attachment of some reptilian teeth, and unlike the thecodonty seen in mammalian teeth). The caruncle also forms near the premaxillary bone and is associated with a prematurely differentiated and cornified epithelium. Finally, the authors find that the egg tooth is lost via a combination of resorption (by multinucleated TRAP-positive clast cells) and by cell death within the egg tooth pulp, and that the caruncle is lost at some undetermined point between 11- and 50-days post-hatching. Taken together, these findings indicate that the only tooth (albeit a transient one) in the otherwise edentulate echidna more closely resembles the teeth of reptiles than those of eutherian mammals, indicative of remarkable conservation of dental features in monotremes and reptiles from the last common ancestor of amniotes.

Strengths

We commend the authors on acquiring a unique and impressive series of embryonic and post-embryonic echidna specimens, and on making the most of these precious specimens by sequentially imaging them for microCT, followed by processing for paraffin histochemistry and/or immunofluorescence. The quality of the histology and image data presented here is high, and the authors effectively use their various data types (CT and section) in combination to provide good and clear anatomical context for their observations. This histochemical stainings presented here are very clear, and easily allows the reader to distinguish tissue types and connectively between elements (e.g., between the dentine of the egg tooth and the premaxilla, and between the os caruncle and the premaxilla).

Furthermore, by framing their work in a comparative context, the authors can propose homologies between the egg tooth of the echidna and the first forming teeth of some lizards and crocodilians. Monotremes possess a fascinating melange of anatomical features classically regarded as "mammalian" or "reptilian", but these are extremely difficult to study developmentally. This work is a significant contribution in this regard and highlights the importance of monotreme developmental data when reconstructing the nature of the last common ancestor of amniotes.

Weaknesses

The introduction of the paper is a bit too long (and, at times, unfocused). Given the succinct nature of the results, the paper would benefit from a more focused and streamlined introduction.

While the embryonic samples studied here are understandably limited (and sample sizes necessarily small), there are nevertheless claims made here that are not fully supported by the figures. In most instances, this is a case of a lack of high-magnification panels in the plates illustrating, for example, the features of the odontoblast layer, the ameloblast-like cells at the tip of the tooth, etc. These features are discussed, but not shown.

The story around the caruncle isn't fully developed. It is introduced as though there has been some debate about whether the element forms as a distinct condensation from the premaxilla, but then this is not revisited. Also, the rationale for the choice of molecular markers used to characterise the epithelial component of the caruncle isn't entirely clear. The authors state that Loricrin is a marker of "terminal differentiation" - but does this mean that the loricrin-expressing epithelium adjacent to the caruncle skeleton is just farther along in its development relative to adjacent epidermis? Or is loricrin a specific marker of "cornified epithelia"? And if the latter, has loricrin expression been examined in the developing caruncles of avian or non-avian reptiles?

Finally, the evolutionary synthesis presented here seems reasonable with respect to the egg tooth but remains a bit less clear with respect to the caruncle. The authors conclude that the os caruncle may be a novelty of monotremes, but that the epithelial caruncle may be homologous between monotremes and reptiles - but then suggest that the last common ancestor of amniotes had both structures? It is difficult to follow this logic. I think that that paper would benefit from a more nuanced "final model" or hypothesis of homology of egg teeth and caruncles across amniotes.

Author Response:

Reviewer #3 (Public Review):

In this manuscript the authors make several conclusions, according to the abstract:

1 - LTG activity is essential by contributing to a process independent of PG recycling.

2 - LTGs are important because of their catalytic activity rather than because of a protein-protein interaction.

3 - LTG mutants are hypersusceptible to production of periplasmic polymers.

4 - LTGs prevent toxic periplasmic crowding and their function is temporally separate from PG synthesis.

The authors perform a series of genetic experiments that lead to their conclusions. Their first conclusion is well supported by data showing that a PG recycling mutant does not have the same defects as their LTG mutant.

Their second conclusion needs more justification/explanation. They show a catalytic mutant of RlpA is unable to sustain growth as the only LTG in the cell. However, I am confused by their wording around RlpA in general. In the text they note that their delta_7 mutant, which encodes RlpA, 'has no highly active LTGs' (lines 130-131). Does that imply that RlpA is not an LTG? In the discussion they note that E.coli RlpA has no LTG activity. Is this enzyme known to have LTG activity in V.cholerae? One important control would be to show that the catalytically inactive protein is stable (i.e. that the defect is not due to protein misfolding). This could be supported by looking at protein stability via Western or even quantifying the fluorescence data in Figure S3b.

Alignment of VcRlpA with P. aeruginosa RlpA, which has been demonstrated in vivo and in vitro to be an active LTG, suggests VcRlpA retains the active site residues required for PG cleavage. This, as well as the inability of a VcRlpA^D145A mutant (based on the alignment with catalytically inactive EcRlpA) to rescue native RlpA depletion from the ∆LTG mutants suggests that VcRlpA is an active LTG and that this activity is required in the absence of all other annotated V. cholerae LTGs. We agree that “no highly active LTGs” is confusing and we have changed the text to simply describe the ∆7 LTG mutant as being significantly depleted in LTG activity as measured by anhMurNAc abundance in the sacculus. Lastly, we have conducted Western Blots demonstrating in the revised manuscript that our catalytic site mutant is indeed produced and stable (Figure S3).

Their third conclusion also needs more support. The authors do a series of experiments showing that delta7 is more susceptible to SacB. What are the data that show sacB produces large polysaccharides molecules in the periplasm rather than (or in addition to) the cytoplasm? This would be important to show as these data are the main test of the authors model.

In native B. subtilis as well as in E. coli, SacB has a canonical Sec signal peptide which is annotated as being cleaved after residue Ala29 (Uniprot G3CAF6_BACIU) to be released extracellularly. A reference (Pereira, et al, 2001) has been added in support of SacB functioning extracellularly and not in the cytoplasm of its native host, B. subtilis.

The authors have other data that all argue for their model that LTG deficient strains have an excess of periplasmic crowding. The suppressor of delta_opgH is intriguing, but does not restore the morphological defects in delta_7, suggesting that the increase in length during prolonged growth may not be caused by periplasmic crowding, or at least is not alleviated by deletion of OpgH. What then does the deletion of OpgH suppress? Here, I was confused by the experiments in low salt. The authors write that the cells lyse (line 222) but this is not shown anywhere. Growing the cells continually in low salt may not be the hypoosmotic challenge the authors presume. A challenge typically implies an acute change in osmolarity, rather than a prolonged exposure, which may allow cells to adapt.

We do not fully understand the role of OpgH, but here is our working model: LTGs have at least two essential functions – 1) PG release and 2) mitigating periplasmic crowding, either or both of which can become more important based on osmotic conditions. Since MltG seems to be the main PG release factor (at least based on E. coli), which can be partially supplanted by collective action of other LTGs, the ∆7 suffers from both PG release defects and periplasmic crowding defects, perhaps more so in an osmotically challenging low salt medium. The evidence for lysis is that at high inoculum (10^-2) the ∆7 LTG mutant does grow for a short time, but then we observe a drop in OD_600, indicative of lysis. According to our model, ∆6, on the other hand, which still has MltG, likely suffers only (or mostly) from a periplasmic crowding defect. Deleting periplasmic glucans only mitigates periplasmic crowding (and probably only partially), which does not help the more defective ∆7, which additionally suffers from lack of the postulated second activity.

The reviewers raise an interesting point regarding the word “challenge”. We indeed specifically make the point that this is not an acute challenge, but rather accumulating damage during prolonged growth, even in salt-free LB. We have thus removed the word “challenge” from the revised manuscript. Importantly, we only use the ∆opgH suppression phenotype as one of many puzzle pieces for our conclusion. The key assay is the direct demonstration of periplasmic soluble PG strands accumulating in both WT and, to a higher degree, the ∆6 LTG mutant (Fig. 6).

I was also highly confused by the antibiotic + BADA staining experiments. Do the authors stain the cells, treat, and then visualize? Are they then studying the fate of old PG? How does BADA get incorporated into PG in V.cholerae? Is it through LDT activity or some other way? Without more explanation, it is hard to interpret the results.

BADA does get incorporated through either LDT or PG synthesis activity in V. cholerae, but for these experiments, the specific incorporation pathway is inconsequential, since we only focus on the end product (stained PG). We think that what we visualize is not the fate of old PG (otherwise we would see similar strong stains with Fosfomycin, which inhibits cell wall synthesis upstream of PG strand generation by PBPs/SEDS), but rather visualizes the generation of long, uncrosslinked PG strands due to the inhibition of PBP transpeptidase activity. We have added more explanations of this assay to the revised manuscript.

The last conclusion is not supported by data. There are no data showing that LTG activity is temporally separate from PG synthesis.

We would like to point out that this is not framed as a conclusion per se, but rather a plausible speculation. Our data showing soluble strand accumulation in the WT strongly suggest that LTGs do not work in perfect harmony with synthesis, but rather degrade strands AFTER they accumulate (i.e., temporally separate). We further believe that complementation with a heterologous enzyme (MltE), which does not have a homolog in V. cholerae strongly argues that LTGs and PG synthesis do not have to associate through protein-protein interactions. All this adds to an emerging model that PG synthesis and LTG-mediated degradation are not as tightly co-ordinated as one might assume.

Author Response:

Reviewer #1:

Authors introduce a deep learning-based toolbox (ELEPHANT) to provide ease in annotation and tracking for 3D cells across time. The study takes two datasets (CE and PH) to demonstrate the performance of their method and compare it with two existing 3D cell tracking methods on segmentation and accuracy metrics. 3D U-Nets are shown to be performing well in segmentation tasks in recent years, authors also utilize 3D U-Net for segmenting cells as well as linking the nuclei across time through optical flow. The variation in selected datasets is shown to be in the shape, size and intensity of cells. Beyond segmentation, authors also demonstrate the performance of ELEPHANT in exploring the tracking results with and without optical flow and regenerating their fate maps. A complete server-based implementation is provided with detailed codebase and docker images to implement and utilize ELEPHANT.

Strengths:

The paper is technically sound with detailed explanation of each methodological step and results. 3D U-Nets are optimized for the segmentation task in hand with large training sessions, efficiency of the pipeline is nicely demonstrated which serves this as a useful toolbox for real-time annotation and prediction of cell structures. The detailed implementation on a local and remote server is presented which is a need while handling and analyzing large scale bio-imaging datasets. Beyond smoothing, SSIM-based loss is effectively applied to make the model robust against intensity and structural variations which definitely helps in generalized performance of the segmentation and tracking pipeline.

Segmentation results are validated on a large set of nuclei and links which is helpful to understand the limitation of the models. The advantage of using optical flow-based linking is clearly shown on top of using nearest neighbors. Spatio-temporal distribution of cells on a given data guides the users in using the framework for several biological applications such as tracking the lineage of newly born cells - a hard task in stem cell engineering.

A detailed implementation on both remote and server as well as open-source codebase on Github is well provided for the scientific community which will help the users to easily use ELEPHANT for specific datasets. Although CE and PH datasets are used to demonstrate the performance, however, similar implementation can also be performed on neuronal datasets that would be of much use in exploring neurogenesis.

Weaknesses:

Authors use ellipse-like shapes to annotate the data, however, many cells are not elliptic or circular in shape but consist of varying morphology. If the annotation module is equipped with drawing free annotations then it will be better useful to capture the diverse shapes of cells in both training and validation. This also limits the scope of the study to be used only for cells' datasets that are circular/elliptical in shape.

ELEPHANT can be used to track nuclei or cells of diverse shapes. Tracking is based on reliable detection of nuclei/cells but does not require precise segmentation of their shapes. We have now added results showing that ellipsoid approximations are sufficient for detection and cell tracking, even when tracking cells with complex and variable shapes (figure 3).

As we now explain in the manuscript (page 4), we use ellipsoids for annotation because they are essential for rapid and efficient training and predictions, which are the backbone of interactive deep learning. In practice, using ellipsoids also reduces the amount of work required for annotating the data compared with precise drawing of cell outlines. Post-processing can be appended to our workflow if a user needs to extract the precise morphology of cells.