Author Response

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

Reviewer #1 (Public Review):

Summary of the major findings -

1) The authors used saturation mutagenesis and directed evolution to mutate the highly conserved fusion loop (98 DRGWGNGCGLFGK 110) of the Envelope (E) glycoprotein of Dengue virus (DENV). They created 2 libraries with parallel mutations at amino acids 101, 103, 105-107, and 101-105 respectively. The in vitro transcribed RNA from the two plasmid libraries was electroporated separately into Vero and C6/36 cells and passaged thrice in each of these cells. They successfully recovered a variant N103S/G106L from Library 1 in C6/36 cells, which represented 95% of the sequence population and contained another mutation in E outside the fusion loop (T171A). Library 2 was unsuccessful in either cell type.

2) The fusion loop mutant virus called D2-FL (N103S/G106L) was created through reverse genetics. Another variant called D2-FLM was also created, which in addition to the fusion loop mutations, also contains a previously published, evolved, and optimized prM-furin cleavage sequence that results in a mature version of the virus (with lower prM content). Both D2-FL and D2-FLM viruses grew comparably to wild type virus in mosquito (C6/36) cells but their infectious titers were 2-2.5 log lower than wild type virus when grown in mammalian (Vero) cells. These viruses were not compromised in thermostability, and the mechanism for attenuation in Vero cells remains unknown.

4) Next, the authors probed the neutralization of these viruses using a panel of monoclonal antibodies (mAbs) against fusion loop and domain I, II and III of E protein, and against prM protein. As intended, neutralization by fusion loop mAbs was reduced or impaired for both D2-FL and D2-FLM, compared to wild type DENV2. D2-FLM virus was equivalent to wild type with respect to neutralization by domain I, II, and III antibodies tested (except domain II-C10 mAb) suggesting an intact global antigenic landscape of the mutant virion. As expected, D2-FLM was also resistant to neutralization by prM mAbs (D2-FL was not tested in this batch of experiments).

5) Finally, the authors evaluated neutralization in the context of polyclonal serum from convalescent humans (n=6) and experimentally infected non-human primates (n=9) at different time points (27 total samples). Homotypic sera (DENV2) neutralized D2-FL, D2-FLM, and wild type DENV similarly, suggesting that the contribution of fusion loop and prM epitopes is insignificant in a serotype-specific neutralization response. However, heterotypic sera (DENV4) neutralized D2-FL and D2-FLM less potently than wild type DENV2, especially at later time points, demonstrating the contribution of fusion loop- and prM-specific antibodies to heterotypic neutralization.

Impact of the study-

1) The engineered D2-FL and D2-FLM viruses are valuable reagents to probe antibodies targeting the fusion loop and prM in the overall polyclonal response to DENV.

2) Though more work is needed, these viruses can facilitate the design of a new generation of DENV vaccine that does not elicit fusion loop- and prM-specific antibodies, which are often poorly neutralizing and lead to antibody-dependent enhancement effect (ADE).

3) This work can be extended to other members of the flavivirus family.

4) A broader impact of their work is a reminder that conserved amino acids may not always be critical for function and therefore should not be immediately dismissed in substitution/mutagenesis/protein design efforts.

Evaluating this study in the context of prior literature -

The authors write "Although the extreme conservation and critical role in entry have led to it being traditionally considered impossible to change the fusion loop, we successfully tested the hypothesis that massively parallel directed evolution could produce viable DENV fusion-loop mutants that were still capable of fusion and entry, while altering the antigenic footprint."

".....Previously, a single study on WNV successfully generated a viable virus with a single mutation at the fusion loop, although it severely attenuated neurovirulence. Otherwise, it has not been generated in DENV or other mosquito-borne flaviviruses"

The above claims are a bit overstated. In the context of other flaviviruses:

• A previous study applied a similar saturation mutagenesis approach to the full length E protein of Zika virus and found that while the conserved fusion loop was mutationally constrained, some mutations, including at amino acid residue 106 were tolerated (PMID 31511387).

• The Japanese encephalitis virus (JEV) SA14-14-2 live vaccine strain contains a L107F mutation in the fusion loop (in addition to other changes elsewhere in the genome) relative to the parental JEV SA14 strain (PMID: 25855730).

• For tickborne encephalitis virus (TBEV-DENV4 chimera), H104G/L107F double mutant has been described (PMID: 8331735)

There have also been previous examples of functionally tolerated mutations within the DENV fusion loop:

• Goncalvez et al., isolated an escape variant of DENV 2 using chimpanzee Fab 1A5, with a mutation in the fusion loop G106V (PMID: 15542644). G106 is also mutated in D2-FL clone (N103S/G106L) described in the current study.

• In the context of single-round infectious DENV, mutation at site 102 within the fusion loop has been shown to retain infectivity (PMID 31820734).

We thank the reviewer for these comments. We have adjusted the text above to better reflect and credit the prior literature. Text is modified as follows in the discussion session.

“Previous reported mutations in the fusion loop are mainly derived from experimental evolution using FL-Ab to select for escape mutant or by deep mutational scanning (DMS) of the Env protein for Ab epitope mapping. Mutations in the FL epitope were observed in a DENV2-NGC-V2 (G106V)39, attenuated JEV vaccine strain SA14-14-2 (L107F)40, attenuated WNV-NY99 (L107F)41. While most of the mutations, including the double mutations reported here lead to attenuation of the virus. A recent DMS study showed that Zika-G106A has no observable impact on viral fitness42. Interestingly, we also recovered a mutation G106L, suggesting position 106 and 107 might be the most tolerable position for mutation in mosquito borne flavivirus FL. On the other hand, tick borne flavivirus as well as vector only flavivirus show a more diverse FL composition. The inflexibility of mosquito borne flavivirus might be due to the evolution constraint of the virus to switch between mosquito and vertebrate hosts.”

Appraisal of the results -

The data largely support the conclusions, but some improvements and extensions can benefit the work.

1) Line 92-93: "This major variant comprised ~95% of the population, while the next most populous variant comprised only 0.25% (Figure 1C)".

What is the sequence of the next most abundant variant?

The sequence of the next most abundant variant has been added to the text.

2) Lines 94-95: "Residues W101, C105, and L107 were preserved in our final sequence, supporting the structural importance of these residues." L107F is viable in other flaviviruses.

We acknowledge that the L107F mutation has been described in other flaviviruses, including the tick-borne flaviviruses DTV and POWV. This mutation in JEV is associated with viral attenuation. This sentence is referring to the fact that, in our libraries, we did not recover variants with mutations at these positions, in contrast to D2-FL with variants at N103 and G106, indicating less mutational tolerance. However, we want to re-direct the focus of this manuscript to engineer a viable DENV that is antigenically different in the FL epitope, but not which residue is more tolerance for mutation.

3) Figure 2c: The FLM sample in the western blot shows hardly any E protein, making E/prM quantitation unreliable.

The samples used in Figure 2C derive from the growth curve endpoint (Figure 2A), in which there is a 1-log difference in viral titer between D2 and D2-FLM. Equivalent volumes of viral supernatant were loaded in the gel, explaining the reduced intensity of the E band in D2-FLM. The higher exposure on the right shows the E band more clearly for D2-FLM. The Western blot assay comparing prM/E ratio as a measure of maturation state was described and validated in our previous study (Tse et al. 2022, mbio). The methods and figure legend have been updated to include greater detail. The polyclonal E antibody was specifically chosen for this study as our previously used monoclonal antibody targeted the fusion loop. The polyclonal antibody was raised against a fragment of E (AA 1-495) and should have minimal effect by the fusion loop mutations.

4) Lines 149 -151: "Importantly, D2-FL and D2-FLM were resistant to antibodies targeting the fusion loop. While neutralization by 1M7 is reduced by ~2-logs, no neutralization was observed for 1N5, 1L6, and 4G2 for either variant (Figure 3 A)".

a) Partial neutralization was observed for 1N5, for D2-FL.

The text has been updated to more accurately describe the 1N5 neutralization data.

b) Do these mAbs cover the full spectrum of fusion loop antibodies identified thus far in the field?

We did not test every known fusion loop antibody that has been described, instead focusing on 1M7, 1N5, 1L6, and 4G2, which were previously described by Smith et al and Crill et al. We also modified the text in discussion to reflect the possibility of other FL-Ab that are not affected by out mutations.

“We have tested a panel of FL-Ab; however, we cannot exclude the possibility that other FL-Abs may not be affected by N103S and G106L. However, we have shown that saturation mutagenesis could generate mutants with multiple amino acid changes, and we are currently using D2-FLM as backbone to iteratively evolve additional mutations in FL to further deviate the FL antigenic epitope.”

c) Are the epitopes known for these mAbs? It would be useful to discuss how the epitope of 1M7 differs from the other mAbs? What are the critical residues?

Critical residues for these antibodies have been described. They are as follows: 1M7: W101R, W101C, G111R; 1N5: W101R, L107P, L107R, G111R; 1L6: G100A, W101A, F108A; 4G2: G104H, G106Q, L107K. The critical residues for 1M7 are slightly different than the others, perhaps explaining the residual binding to D2-FL. Note that the critical residue identified previously for 1M7 and 1N5 do not overlap with D2-FLM mutations, suggesting the FL mutations has extending effect on the antigenic FL epitope.

d) Maybe the D2-FL mutant can be further evolved with selection pressure with fusion loop mAbs 1M7 +/-1N5 and/or other fusion loop mAbs.

We agree that it may be possible to further evolve D2-FL using antibody selection, although we have not yet performed these experiments, we are currently performing iterative saturation mutagenesis and directed evolution to further evolve away from the natural FL.

5) It would have been useful to include D2-M for comparison (with evolved furin cleavage sequence but no fusion loop mutations).

Neutralization data for some of the mAbs against D2-M can be found in our previous study (Tse et al. 2022 mBio), in which no difference in neutralization was observed compared to DV2 wildtype. Given the limited resources of the anti-DENV NHP and human serum, we did not add D2-M for comparison. Although some insight can be deduced from the D2-FL vs D2-FLM comparison, we agree future studies that are designed to delineate CR-Ab population between prM, FL and other CR-epitopes should include D2-M for comparison.

6) Data for polyclonal serum can be better discussed. Table 1 is not discussed much in the text. For the R1160-90dpi-DENV4 sample, D2-FL and D2-FLM are neutralized better than wild type DENV2? The authors' interpretation in lines 181-182 is inconsistent with the data presented in Figure 3C, which suggests that over time, there is INCREASED (not waning) dependence on FL- and prM-specific antibodies for heterotypic neutralization.

We remade Table 1 to show dilution factors instead of dilution factor-1 of FRNT50.

In general, our human convalescent sera from heterotypic infection (DENV1, 3 and 4) showed none to low neutralization against our DENV2. FRNT50s were between 1: 40 – 1:200. Given the weak potency of the antiserum, it is difficult to compare the FRNT50s between DV2-WT and D2-FLM.

Similarly, in a different NHP cohort (2nd NHP cohort shown in Table 1), only one DENV4 infected NHP (R1160) showed a low heterotypic titer against DENV2. The detectable FRNT50s were between 1: 50 – 1:90. The value was extrapolated based on a single data point (1:40) which has above 50% neutralization. Given the Hill slope of all the neutralization curves were below 0.5, the FRNT50 values is should not be

In conclusion, we do not think serum from Table 1 is potent enough to shows difference between the viruses. The intension to show the negative data in Table 1 is to highlight the difference in serum heterogeneity in DENV infected patients and experimental infected NHPs.

As the reviewer pointed out, the dependence of FL-Ab in later time points increased (the difference between DV2 and D2-FL at 20dpi vs 60dpi vs 90dpi), suggesting non-FL CR-Ab is waning but not prM- and FL-Abs. We rewrote the sentence as follow:

“These data suggest that after a single infection, many of the CR Ab responses target prM and the FL and the reliance on these Abs for heterotypic neutralization increase overtime (Figure 3C).”

Suggestions for further experiments-

1) It would be interesting to see the phenotype of single mutants N103S and G106L, relative to double mutant N103S/G106L (D2-FL).

2) The fusion capability of these viruses can be gauged using liposome fusion assay under different pH conditions and different lipids.

3) Correlative antibody binding vs neutralization data would be useful.

We thank the reviewer for the suggestions; we agree these would be of interest and, indeed, these studies are currently underway. In regard to single mutants, these were present in the initial plasmid library but did not enrich after viral production and passage. Two possible explanations can be drawn, 1) The stochastic of directed evolution prevents a single mutant with similar fitness to enriched. 2) The two mutations are compensatory to each other to make a functional mutant. The 2nd hypothesis highlights the difference between saturation mutagenesis (this study) and DMS (in previous studies).

Fusion capability is indeed very interesting, however, the mechanistic difference or not between wildtype FL and the mutated FL in supporting fusion is not the focus of this study. Instead, we are currently working on adapting the D2-FLM in mammalian cells. If successful, the difference in fusion mechanism between the Vero adapted and D2-FLM in different lipid, insect vs mammalian would be of interest.

We are currently developing whole virus ELISA; we avoid using rE monomer for the study as it might neglect the conformation Ab.

Reviewer #2 (Public Review):

Antibody-dependent enhancement (ADE) of Dengue is largely driven by cross-reactive antibodies that target the DENV fusion loop or pre-membrane protein. Screening polyclonal sera for antibodies that bind to these cross-reactive epitopes could increase the successful implementation of a safe DENV vaccine that does not lead to ADE. However, there are few reliable tools to rapidly assess the polyclonal sera for epitope targets and ADE potential. Here the authors develop a live viral tool to rapidly screen polyclonal sera for binding to fusion loop and pre-membrane epitopes. The authors performed a deep mutational scan for viable viruses with mutations in the fusion loop (FL). The authors identified two mutations functionally tolerable in insect C6/36 cells, but lead to defective replication in mammalian Vero cells. These mutant viruses, D2-FL and D2-FLM, were tested for epitope presentation with a panel of monoclonal antibodies and polyclonal sera. The D2-FL and D2-FLM viruses were not neutralized by FL-specific monoclonal antibodies demonstrating that the FL epitope has been ablated. However, neutralization data with polyclonal sera is contradictory to the claim that cross-reactive antibody responses targeting the pre-membrane and the FL epitopes wane over time.

Overall, the central conclusion that the engineered viruses can predict epitopes targeted by antibodies is supported by the data and the D2-FL and D2-FLM viruses represent a valuable tool to the DENV research community.

Reviewer #1 (Recommendations For The Authors):

1) Line 51-52: "Currently, there is a single approved DENV vaccine, Dengvaxia." Line 56-57: "Other DENV vaccines have been tested or are currently undergoing clinical trial, but thus far none have been approved for use."

It should be specified for the global audience that this applies to the United States. Takeda's DENV vaccine, QDENGA is approved in Indonesia, European Union, and Brazil.

The text has been modified to include this information.

2) Line 62-63: - "The core fusion loop-motif DRGWGNGCGLFGK is highly conserved..." Lines 78-80: - We generated two different saturation mutagenesis libraries, each with 5 randomized amino acids: DRGXGXGXXXFGK (Library 1) and 79 DRGXXXXXGLFGK (Library 2).

It may be useful for the readers if the amino acid numbers are stated. The core fusion loop motif DRGWGNGCGLFGK (Eaa98-110) is highly conserved. We generated two different saturation mutagenesis libraries, each with 5 randomized amino acids: DRGXGXGXXXFGK (Library 1; Xaa 101,103, 105-7) and DRGXXXXXGLFGK (Library 2; Xaa 101-105).

This information has been added to the text.

3) Line 91-92: "Bulk Sanger sequencing revealed an additional Env-91 T171A mutation outside of the fusion-loop region."

It looks like the mutation T171A is in domain I of the E protein and does not seem to interface with the fusion loop. Is that why it wasn't pursued further?

The E171A mutation was included in the infectious clone for D2-FL and D2-FLM. The text has been modified to clarify this inclusion.

4) Lines 82-85: "Saturation mutagenesis plasmid libraries were used to produce viral libraries in either C6/36 (Aedes albopictus mosquito) or Vero 81 (African green monkey) cells and passaged three times in their respective cell types."

a) What was the size of the libraries? How does one make sure that the experimental library actually has all the amino acid combinations that were intended?

Each library has 5 randomized amino acids, so there are 205 = 3.2 million combinations. In these experiments, sequencing of the plasmid libraries revealed about 2 million unique amino acid sequences, or approximately 62.5% library coverage. The actual plasmid diversity is expected to be higher than 2 million as our deep sequencing has limited coverage.

b) The wild type sequence was excluded from the libraries, correct?

The wild-type sequence was not specifically excluded from the libraries, as there is no easy method to do so. Wild-type sequence was detected in the plasmid libraries but was not selected in the C6/36 library. However, in the Vero library, we recovered WT virus.

5) Table 1: - Please include in the table description, what the colors indicate.

We remade Table 1 to show dilution factors instead of dilution factor-1 of FRNT50 and removed the unnecessary color code. We also added all relevant information in the table legend.

6) Lines 246-248: "Previously, a single study on WNV successfully generated a viable virus with a single mutation at the fusion loop, although it severely attenuated neurovirulence."

It may be worthwhile to mention the WNV mutation (L107F) as some readers may be curious about where this mutation is relative to the ones described in this study.

This information has been added to the text. We also included the previously described FL mutations in flaviviruses in the text.

Reviewer #2 (Recommendations For The Authors):

Major Critique:

• There is a disconnect between Fig 2A and 2C. FL and FLM viruses have much lower levels of prM-E expression in the viral supernatants based on the western blot in 2C. Why isn't E being detected in the Western? Is the particle-to-pfu ratio skewed in the mutant viruses? Is it possible that the polyclonal is targeting the cross-reactive prM and FL epitopes, and if so would using a monoclonal antibody targeting a known DIII-epitope (2D22) yield a different western result? Also, the legend and methods for Fig 2C are not clear. What is actually being tested in the Western blot? Were equivalent volumes of the different viral preps used?

The samples used in Figure 2C derive from the growth curve endpoint (Figure 2A), in which there is a 1-log difference in viral titer between D2 and D2-FLM. Equivalent volumes of viral supernatant were loaded in the gel, explaining the reduced intensity of the E band in D2-FLM. The higher exposure on the right shows the E band more clearly for D2-FLM. The Western blot assay comparing prM/E ratio as a measure of maturation state was described and validated in our previous study (Tse et al. 2022, mBio) and the methods have been updated to include greater detail. The polyclonal E antibody was specifically chosen for this study as our previously used monoclonal antibody targeted the fusion loop. The polyclonal antibody was raised against a fragment of E (AA 1-495) and should not be affected by the fusion loop mutations. 2D22 is a conformational antibody and does not work in western blot.

• Table 1: The data within Table 1 is ignored in the text, and some of this data contradicts the central conclusions of the manuscript.

o A.) Some of the convalescent data contradicts the hypothesis. DS0275 had an equivalent neut between DV2 and D2-FLM, DS1660, and R1160 (90) had better neut against the D2-FLM than DV2. Discussion of these samples is warranted.

o C.) The description in the legend does not adequately describe the table. What do the colors represent? What are the numerical values being displayed? What is in parentheses, (I assume the challenge strain)? The limit of detection is reported as 1:40; 0.25. 1:40 is 0.025 which matches most of the data? There is inadequate description of these experiments in the materials and methods.

We remade Table 1 to show dilution factors instead of dilution factor-1 of FRNT50 and removed the unnecessary color code. We also added discussion for Table 1 and clarify the difference between the three cohorts of serum in the text with the corresponding references.

In general, our human convalescent sera from heterotypic infection (DENV1, 3 and 4) showed none to low neutralization against our DENV2. FRNT50s were between 1: 40 – 1:200. Given the weak potency of the antiserum, it is difficult to compare the FRNT50s between DV2-WT and D2-FLM.

Similarly, in a different NHP cohort (2nd NHP cohort shown in Table 1), only one DENV4 infected NHP (R1160) showed a low heterotypic titer against DENV2. The detectable FRNT50s were between 1: 50 – 1:90. The value was extrapolated based on a single data point (1:40) which was above 50% neutralization. Given the Hill slope of all the neutralization curves were below 0.5, the FRNT50 values are not reliable.

In conclusion, we do not think sera from Table 1 is potent enough to show difference between the viruses. The intension to show the negative data in Table 1 is to highlight the difference in serum heterogeneity in DENV infected patients and experimental infected NHPs.

Minor critique:

Figure 1C: Legend is not clear for this panel. What is on the x-axis of the bubble plots? Are these mutations across the entire viral genome or is this just the prM-E sequence?

The X-axis is a scatter of all of the sequences contained in the library, similar to graphs used for plotting CRISPR screen results. These represent individual sequences from the saturation mutagenesis libraries in the fusion loop of E as described in Figure 1B.

The wording in Lines 92-94 is not clear. It looks like the T171A mutation was present in 95% of the sequences (Line 92). Yet this sequence was not incorporated into the variant virus. What is the rationale for omitting this mutation in downstream variant virus generation?

The 95% in Line 92 refers to the variant containing N103S/G106L mutations as seen in Figure 1C. The high-throughput sequencing approach did not include residue 171, so the presence of the T171A mutation in combination with fusion loop mutations cannot be determined. However, the E171A mutation was included in the infectious clone for D2-FL and D2-FLM. The text has been modified to clarify this inclusion.

The authors discuss the potential of the D2-FL or D2-FLM virus as a potential vaccine platform in the abstract, introduction, and conclusion. This is a good idea, but the authors provide no evidence of feasibility in this manuscript.

The ultimate goal to engineer a viable DENV with distinct FL antigenic epitope is for it use as live attenuated vaccine. As this is the rationale for the study, we introduce the concept throughout the manuscript. The current study demonstrated the possibility to mutate a novel fusion loop motif in DENV and provided evidence to show the favorable antigenic properties of D2-FLM. We agree with the reviewer that definitive work in animal to show vaccine efficacy need to be done and are currently undergoing. To avoid misleading our audience, we tone down the emphasis of vaccine use in the text.

Line 150-153: Figure 3A demonstrates that the FL-specific antibodies broadly do not neutralize the mutant viruses. However, the conclusions are overstated in the text. 1N5 neutralizes the D2-FL variant.

The text has been updated to more accurately describe the 1N5 neutralization data.

Lines 175-182: The authors make a lot of assumptions about the target of the polyclonal target without any evidence.

These lines reference studies that showed greater enhancement by antibodies targeting the fusion loop and prM as compared to other cross-reacting antibodies. The assumption that both our manuscript and others have drawn was that Abs that are cross-reactive and weakly neutralizing are more prone for ADE. As discussed, other groups have attempted to mutate the FL from recombinant E protein to achieve similar goal to remove the fusion loop epitope to reduce ADE. We have re-written the sentence in the followings:

“As FL and prM targeting Abs are the major species demonstrated to cause ADE in vitro, we and others hypothesized these Abs are responsible for ADE-driven negative outcomes after primary infection and vaccination,10–12,32 we propose that genetic ablation of the FL and prM epitopes in vaccine strains will minimize the production of these subclasses of Abs responsible for undesirable vaccine responses. Indeed, covalently locked E-dimers and E-dimers with FL mutations have been engineered as potential subunit vaccines that reduce the availability of the FL, thereby reducing the production of FL Abs.33–36”

Author Response

Reviewer #2 (Public Review):

Please note that I am not a structural biologist and cannot critically evaluate the details of figures 1 to 3; my review focuses on the cell biology experiments in figures 4 and 5.

Paine and colleagues investigated structural requirements for the interaction between the ESCRT-III subunit IST1 and the protease CAPN7. This is a continuation of previous work by the same group (Wenzel et al., eLife 2022), which showed that Capn7 is recruited to the midbody by Ist1 and that Capn7 promotes both normal abscission and NoCut abscission checkpoint function. In this article, the structural determinants of the Ist1-Capn7 interaction are characterised in more detail, focusing on the structure of Capn7 MIT domains and their binding to Ist1. Notably, point mutations in Capn7 MIT domains known to mediate binding to Ist1 and midbody recruitment are shown here to be required for abscission functions, as expected from the authors' previous paper. Furthermore, the report shows that a Capn7 point mutant lacking proteolytic activity behaves as a loss-of-function in abscission assays, despite showing normal midbody localisation. These are important results that will help in future studies to understand how the Capn7 protease regulates abscission mechanistically.

The report is clearly written and the results support the main conclusions. Some technical limitations and alternative interpretations of the data should be discussed in the text, as outlined below.

1) It is not always clearly stated how the results presented in this report relate to those in the Wenzel paper. For example, the finding that Ist1 recruits Capn7 to midbodies (p. 6 and figure 4) was first shown in the Wenzel paper. The novelty here is not that Capn7 MIT mutants fail to localise to midbodies, but that they phenocopy the previously described knockdown of Capn7, failing to support normal abscission and NoCut function (fig. 5). This supports and extends the findings of Wenzel et al. It is important to make this explicit and explain the conceptual advances shown here more clearly.

We take the reviewer’s point and we have now clarified this issue in the text (e.g., page 7, lines 4-5).

2) The NoCut checkpoint can be triggered by chromatin bridges, DNA replication stress, and nuclear basket defects, but only basket defects are tested here. Therefore, it is not clear if NoCut is still functional in Capn7-defective cells after replication stress and/or with chromatin bridges. Ideally, this should be tested experimentally, or alternatively discussed in the text, especially since the molecular details of how NoCut is engaged under different conditions remain unclear. For example, "abscission checkpoint bodies" proposed to control abscission timing form in response to nuclear basket defects and aphidicolin treatment, but not in the presence of chromatin bridges (Strohacker et al., eLife 2021).

We appreciate the reviewer’s excellent suggestion. We have now performed the requested experiments and added a new figure showing that CAPN7 is also required to maintain the NoCut checkpoint when it is triggered by DNA bridges (new Figure 6A) or by replication stress (new Figure 6B).

3) The current data suggest that Capn7 is a regulator of abscission timing, but in my opinion do not quite establish this, for two main reasons. First, abscission timing is not directly measured in this study. Time-lapse imaging would be required to rule out alternative interpretations of the data in figure 5. For example, a delay in an earlier cell cycle stage could in principle lead to a decrease in the overall fraction of midbody-stage cells. Second, the absence of the midbody is not necessarily a marker of complete abscission. Indeed, midbody disassembly is associated with the completion of abscission in unchallenged HeLa cells, but not in cells with chromatin bridges (Steigemann et al, Cell 2009). Midbodies remain a useful marker for pre-abscission cells, but the absence of midbodies should not be immediately interpreted as completion of abscission without further assays. Formally, a direct measurement of abscission timing would require imaging of the plasma membrane, for example using time-lapse phase-contrast microscopy (Fremont et al., 2016 Nat Comm). These limitations should be mentioned in the text.

We note that midbody numbers are not our only measure of abscission delay/failure - we also measure the numbers of multinucleate cells and sum the two. Nevertheless, we understand the reviewer’s point and have therefore noted that we are using increased frequencies of cells with midbody connections and multiple nuclei as surrogate markers for abscission defects and NoCut-induced abscission delays (page 7, lines 13-14 and line 17).

4) IST1 plays a role in nuclear envelope sealing by recruiting the co-factor Spastin (Vietri et al., Nature 2015), a known IST1 co-factor also confirmed in the previous interactome screen (Wenzel et al. 2022). CAPN7 could have a role in maintaining nuclear integrity upon the KD of Nup153 and Nup50 (Mackay et al. 2010) instead of/in addition to its proposed role in delaying abscission as part of the NoCut checkpoint at the midbody. I don't think the authors can differentiate between these two possibilities, and it would be interesting to consider their possible implications on how the "NoCut" checkpoint is triggered.

The reviewer again makes good points, and we agree that in addition to participating in abscission, CAPN7 may be involved in closure of the nuclear envelope and that nuclear envelope closure may, in turn, be linked to satisfaction of the NoCut checkpoint. This involvement would nicely explain our observations that both SPAST and CAPN7 participate in both NoCut and abscission. We are in an unusual situation, however, because other colleagues in our field have told us in private communications that they observe that CAPN7 does, in fact, participate in nuclear envelope closure. We find that observation interesting and exciting but it is their discovery, not ours, and we have therefore refrained from doing analogous experiments ourselves. As a compromise, we have added the following text to the penultimate section of our paper (page 8, lines 34-35 through page 9, lines 1-11):

“Our discovery that both CAPN7 and SPAST participate in the competing processes of cytokinetic abscission and NoCut delay of abscission may appear counterintuitive, but we envision that the MIT proteins could participate in both processes if they change substrate specificities or activities when participating in NoCut vs. abscission; for example, via different sites of action, post-translational modifications, and/or binding partners. We note that, in addition to its well documented function in clearing spindle microtubules to allow efficient abscission (Yang et al., 2008), SPAST is also required for ESCRT-dependent closure of the nuclear envelope (NE) (Vietri et al., 2015). The relationship between NE closure and NoCut signaling is not yet well understood, and it is therefore conceivable that nuclear membrane integrity is required to allow mitotic errors to sustain NoCut signaling. It will therefore be of interest to determine whether or not CAPN7, in addition to its midbody abscission functions, also participates in nuclear envelope closure and, if so, whether that activity is connected to its NoCut functions.”

We think that this additional text explains what we (and the reviewer) consider to be an attractive model, but leaves open the question of CAPN7 involvement in nuclear envelope closure to be resolved by our colleagues.

5) Figure 5 should include images of representative cells, highlighting midbody-positive and multinucleated cells. Without images, it is not possible to evaluate the quality of these data.

We appreciate this suggestion and have now added images showing midbody-positive and multinucleated cells from the quantified datasets to allow assessment of our data quality (new Figures 5B and 5D).

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

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity):

Unfortunately, this paper adds only a little to our understanding of uptake in to the flagellar pocket of trypanosomes. It tends to add only detail to information that has been well characterised elsewhere and indeed, as the authors themselves point out, (lines 92-98) it is rather incremental.

We were disappointed that the reviewer was so unsupportive of the work presented here. It seems possible that the reviewer is partly objecting that the title - which emphasised the main finding of the paper - does not fully capture the content of the paper. We have therefore modified the title to emphasise that the paper is principally a characterisation of TbSmee1 rather than an investigation of the flagellar pocket, with the insight into cargo entry being the most notable finding.

Not only has Tbsmee1 been studied before but this data in bloodstream forms is not particularly novel since it gives much the same information as the canonical hook protein TbMORN. This work follows the pattern of conclusions made previously with the protein TbMORN. It focusses on the protein TbSmee where RNAi mutants are interpreted to show flagellar pocket enlargement and impaired access by surface bound cargo. Unfortunately, there is little mechanistic or functional conclusion to the study in terms of how TbSmee operates naturally in the cell.

This is deliberately downplaying the value of the work. TbSmee1 has not previously been characterised in bloodstream form cells, and neither TbMORN1 nor the hook complex are as well-characterised as other cytoskeletal components such as the flagellum and basal body. To criticise the paper for not providing a molecular mechanism of TbSmee1's function is unreasonable given the volume of work provided and the fact that this is a first characterisation of the protein in this life cycle stage. Expectation of a complete molecular mechanism is setting a very high bar for a first characterisation.

It is also possible that the reviewer has not grasped the main thrust of the argument - when TbMORN1 was characterised it was the first protein shown to have this cargo entry defect. We show here that not only does TbSmee1 share this defect, but that it is in fact a previously-unacknowledged feature of all phenotypes of this type, exemplified by clathrin. We have modified the text to make this finding more clearly emphasised (see for example lines 654-661 in the tracked-changes version of the manuscript).

There are other possible explanations for the phenotype. That would need to be studied. This large flagellar pocket phenotype is seen with RNAi mutants of many different types of proteins in the trypanosome and so pleiotropic effects are highly likely. Also, there are a good number of alternative possibilities to account for reduced access to the pocket in these mutants and this data could be usefully added.

This is another statement that seems intended primarily to disparage the paper rather than attempt to improve it. It would have been extremely helpful if the reviewer highlighted what these other possible explanations are instead of making vague allusions. The widespread prevalence of this kind of phenotype means that our insight into restricted cargo access to the flagellar pocket is of general relevance in the trypanosome field.

Specific points<br /> 1. The transient location for the TbSmee at the FAZ tip - or in this case the groove region - was seen in procyclics (Perry, 2018) so this bloodstream indication merely confirms that concept.

The reviewer is again downplaying the value of the work rather than providing constructive criticism. While FLAM3 has been shown to be at the tip of the new flagellum in bloodstream form cells (Sunter et al., 2015), at the time of the preprint being published Smee1 was actually the first protein (besides the DOT1 antigen) shown to localise to the groove region in bloodstream form cells. It is also worth noting that procyclic form cells and bloodstream form cells are fairly different in this regard - in procyclic cells, there is an entire flagellar connector structure that is not present in bloodstream form cells, and so demonstrating that Smee1 was present in the groove region was an important experiment. Since this preprint was published, Smithson et al. have identified 13 additional proteins localising to the groove (Smithson et al., 2022) - we have modified the text to include these points (see lines 542-545 of the tracked-changes manuscript).

1. The C terminal region required for targeting is a reasonable deletion analysis of regions of the protein. But can this data (line 228) be said to "mediate targeting" - or is it just required. For instance, targeting might be OK but it might be needed for stable association, etc etc.

We have changed the text to say "required" for targeting instead of "mediating" targeting (line 312 of tracked-changes manuscript).

1. This protein has already been shown to be phosphorylated and the sites and cell cycle possibilities have been mapped by Urbaniak. So that section adds little. https://doi.org/10.1371/journal.ppat.1008129

The reviewer is again disparaging the significance of the work rather than critiquing it. This is after all only a single panel of a figure and ~15 lines of text, and therefore a minor but still noteworthy element of the manuscript. This also misunderstands what the Urbaniak study does and does not show - while that work showed that Smee1 is phosphorylated, it remained possible that other post-translational modifications were occurring. This experiment shows that the "fuzzy" appearance (variable electrophoretic migration) of TbSmee1 in gels can be solely attributed to phosphorylation as opposed to other post-translational modification. We contacted Dr. Urbaniak to confirm this - his answer is below.

"__I think your approach to look at the fuzzy banding is actually rather elegant; our data shows that phosphorylation occurs but we did not look for any other PTMs that could influence migration on a gel and probably wouldn't see them without a different enrichment and analysis method. We often see a fuzzy pattern with glycosylation due to the heterogeneity, and I suspect other modifications will also results in a smear. Given that the band collapses to a single band after phosphatase treatment and not with an inhibitor present it is fair to conclude that phosphorylation is responsible for the fuzzy band, not other undefined PTMs like glycosylation.__"

1. Essentiality in BS forms and pocket enlargement. This is not surprising. A very large number of cytoskeletal proteins show this in RNAi knockdown. Flagella mutants (extensive publications from many groups (Hill, Bastin, Gull, etc) over last 15 years show this very well and so this protein is just one more example.

This appears to be another comment aimed at downplaying the value of the manuscript rather than providing constructive feedback. The fact that we have demonstrated something previously unobserved in a common phenotype makes the data of general interest to the community, we feel.

1. I didn't find that the explanations for flagella pocket enlargement are soundly based. The experiments focus on endocytosis and uptake and ignore other plausible reasons and some evidence in literature.

Again, the reviewer's feedback would be considerably more constructive if they had taken the time to specifically cite the evidence in the literature that they are alluding to, and present some of the "other plausible reasons" they are aware of. We have consulted widely in the community and have not been able to find anybody who knew what work the reviewer is referring to here.

Lines 84/85. Enlarged pockets may be indicative of endocytosis failure. Presumably the rationale is that endocytosis fails, but exocytosis still occurs and the pocket membrane enlarges. What evidence is there that exocytosis of membrane still occurs? This simple concept might indeed operate in a clathrin mutant but is surface membrane/content exocytosis is maintained in these cytoskeleton mutants? There is good evidence for glycoconjugates within the flagellar pocket. Are these depleted or present still?

The reviewer is correct that we have not specifically assayed for exocytosis, but the fact that we are able to make the same observations in both the clathrin RNAi (where exocytosis has been assayed - Allen et al., 2003) and the Smee1 RNAi means that this is not a problematic omission. The effect of the enlarged flagellar pocket phenotype on the glycoconjugates in the flagellar pocket is an interesting question but far outside the current focus of the paper.

1. There are also a number of other publications indicating that clathrin pits are still present on the enlarged pockets of various mutants when viewed by EM. The authors have looked at the flagellar pockets by EM but the EM methods described have extensive washings and centrifugations before fixation. This is a very poor approach and will mean that endo and exocytic traffic is disturbed (extensive references in literature in other systems? This is not a useful approach for exo/endocytosos studies where flux of traffic demands fast chemical or freezing fix in media.

The reviewer has misunderstood the aim of the experiments described in Figure 5D, which was to observe the morphological changes caused by depletion of TbSmee1. As the reviewer is no doubt aware, high-pressure freezing of trypanosomes gives much better morphological preservation than chemical fixing in media, so the choice of method is not "very poor" but tailored to the experimental aims. We have modified the text to make this point more clearly (lines 355-358 of tracked-changes version). Once again, the referee offers no citation to back up their assertion that endo- and exocytic traffic is disturbed by wash steps, either in trypanosomes or elsewhere.

1. The EMs and Light microscopy does show that the mutant pockets are substantially abnormal in their cytoskeletal arrangement. They have multiple flagella profiles, flagella structures have not connected with the membrane and are sometimes in the cytoplasm (see a glance of the paraflagellar rod in the cytoplasm in FigS5C and internalised FAZ attachment plaques in Fig 4 D bottom right cell). Given these extensive (and expected) cytoskeletal abnormalities it is highly likely that these pocket abnormalities are a result of motility, cell division/developmental issues and the differential uptake phenotypes merely consequential.

This is another misinformed argument that is seeking to disparage the data. The reviewer has apparently overlooked the fact that the same phenotype is seen in clathrin RNAi, when flagellar pocket enlargement precedes any downstream effects on cell division cycle progression. We have gone to great lengths (Fig 6) to demonstrate that the enlargement of the flagellar pocket almost certainly precedes the onset of the growth defect in the TbSmee1 RNAi, and it is therefore likely to precede the cytoskeletal abnormalities that the reviewer has highlighted. An effect on cellular motility is possible and would be interesting to investigate in future work.

1. The authors speak about early phenotypes , but these are often at 15-24 hours. That is probably a couple of cell cycles and so not early.

To be informative, the analyses of RNAi phenotypes have to be done as soon as possible after the onset of the growth defect, and we have gone to great lengths (Figure 5) to define this point as being at 21 hours. This is already difficult as the number of phenotypic cells at the onset of the growth defect will not be high. We have clarified the text to emphasise that "early" refers to soon after the onset of the phenotype (lines 388-389 of tracked-changes version).

In relation to the above question of comparison to the same morphology produced by flagella mutants it would be good to know if these hook mutants produce motility phenotypes and whether these are manifest before the uptake phenotypes. There is evidence (cited here) that forward motility of the trypanosome directs material on surface into the pocket. If these cells have motility defects (primary or via failed division) then surely that would provide an alternative simple explanation for uptake differences.

The reviewer is overlooking the observation that the surface-bound endocytic cargoes (ConA, BSA) are still being sorted/directed as far as the entrance to the flagellar pocket - what is interesting is that the cargo is apparently unable to enter the flagellar pocket. As noted above, it would certainly be interesting to look at motility effects in follow-up work.

1. There is a general point that if studies are to have real relevance to uptake in the trypanosome then they need to deal with uptake of natural ligands rather than artificial surrogates such as dextran. Such tracers were used historically, but in the last decade a series of receptors and ligands for fluid phase and particularly membrane mediated endocytosis have been discovered. With the investment of a little time these important ligand / receptors such as haptoglobin, transferrin, etc would be much more relevant.

Dextran is still state-of-the-art as it is an inert fluid phase marker. We are not aware - and have asked widely - of any readily-available alternative to dextran as a fluid phase marker, especially seeing as we have demonstrated in this study that BSA does not behave as a fluid phase marker in the experimental conditions used. The reviewer is also being disingenuous in suggesting that there is a panel of validated physiological reporters for trypanosomes that are readily available commercially - this is not the case. Transferrin is probably the only example, but the transferrin receptor is confined to the flagellar pocket and therefore not relevant to the question of how surface-bound material enters the flagellar pocket in the first place. As suggested by Reviewer 3 and endorsed by Reviewer 2, we have looked at the uptake of anti-VSG antibodies (which are a physiological cargo) in additional experiments and obtained evidence that the same effects are seen (Figure 9).

**Referees cross-commenting

this session includes comments from Reviewer 1 and Reviewer 2.<br /> *

Reviewer 2<br /> <br /> Dear Reviewers 1 and 3:<br /> I agree with many of the points with Reviewer 1 and our divergence is partly a matter of degree. While it is true that this manuscript is incremental in its contribution to our understanding of TbSmee1, it nonetheless adds to our understanding of the role of this protein in the bloodstream life stage and because of that I find value in the work. The fact that it mirrors what was seem in other protein knockdown studies (e.g. TbMORN) doesn't negate its contribution for me. Reviewer 1 makes an important point, however, when stating that this work does not add a mechanistic or functional conclusion as to how TbSmee1 operates and for me that is the biggest shortcoming of the work. Offering mechanistic insight is a high bar and while it would make for a much more exciting story it does not discount the value of the work as presented. What I do appreciate is the speculation about this observation that endocytosis is required for entrance of surface bound material into the pocket and although they are unable to show that this is not a side affect of other processes being disrupted it is and intriguing point. These observation have the potential of stimulating further investigations into crosstalk between the entrance to the pocket and endocytosis. I also agree that the use of ligands for known receptors like transferrin would be far more informative. While I assumed the transferrin receptor was in the pocket itself it would be interesting to see if the ESAG6/7 is also located outside the pocket and transiently binds cargo before being brought inside for endocytosis.<br /> I think that Reviewer 3 brings up a great point with the focus on VSG's. I think that examining VSG turnover in these mutants can add value to the analysis and inform our view of how affecting the hook complex alters VSG endocytosis.

We appreciate Reviewer 2 taking the time to defend the value of the work, and we concur with Reviewer 2's assessment. Reviewer 2 is also correct that the transferrin receptor appears to be primarily or wholly confined to the flagellar pocket interior, making this likely less informative in this context. Concerning the uptake of anti-VSG antibodies highlighted by Reviewer 3 and endorsed by Reviewer 2, we have carried out these experiments and obtained similar results to those published in the first version of the preprint (Figure 9).

Reviewer 1<br /> <br /> some fair comment and agreement. This is being sent to general cell biology journals.<br /> when one looks at this area in the round it is it is nearly 50 years (1975) since Langreth and Balber published their seminal work on protein uptake and digestion in bloodstream and culture forms of T. brucei. There has been 50 years intense study and the genome has been around for nearly 20 years as well. So, put simply - for both a general science audience and the wider parasite community - if this is a paper about one protein, TbSmee1,then it has surely has to say something functional about that protein. If it is a paper about uptake in trypanosomes (where mutants are one means of interrogation) then it surely has to say something about mechanisms of uptake of physiological relevant ligands. The days of dextran etc are past.

Hence, my comment that this does neither and so is very incremental to what is known already. It is 2022 not 1975. Langreth and Baber published their seminal work in J Protozoology for very good reasons no doubt.

It is striking that Reviewer 1 here extends their aggressive and uncivil approach to attack Reviewer 2's assessment, again substituting forceful wording for informed argument. Reviewer 1 again inexplicably and mistakenly criticises the use of dextran when no state-of-the-art alternative exists. They then go on to needlessly disparage the work done by Langreth & Balber when this work was produced in a totally different publishing landscape. They also appear to fundamentally misunderstand the Review Commons concept, which is to provide journal-independent preprint peer review; it is also worth noting that there are specialist journals such as PLoS Pathogens in the RevComm affiliates as well as general cell biology journals. Given that the mechanism of variant surface glycoprotein (VSG) switching has not yet been fully articulated despite the efforts of multiple labs and many projects over a decades-long time period, it seems extremely unreasonable to be making such demands of this paper.

Reviewer 2<br /> Thank you for replying and I agree with the spirit of your critique. My only comment, which could result from my own naivete, is to say that despite the incredible work that has been done in dissecting endocytosis in T. brucei over these past 50 years, it appears that we still do not understand how many fundamental of aspects of this activity works in this parasite. Even basic questions regarding how cargo, e.g. transferrin, binding to surface receptors is sensed by the parasite remains unknown and the identity of the specific signaling components which transmit this information internally to initiate endocytosis have not been characterized. In many ways it seems that we don't even understand how the parasite partitions the end/exocytic pathways in the pocket and maintains membrane homeostasis. While we know that some kinases and traditional signaling components must be involved, a high resolution understanding of this process in T. brucei seems lacking. I only say all this to suggest that the field maybe isn't yet that advanced to reject work of this type as so many mechanistic unknowns still remain to be uncovered and maybe incremental advances and phenomenology still can add value to the field. However, I respect your opinion on the matter and my perspective could be due to a lack of a full appreciation of the literature on the subject.

We completely agree with Reviewer 2's assessment here, which neatly summarises our rationale for the present work. Reviewer 2 is, if anything, being overly accommodating by suggesting that their perspective may be due to a lack of a full appreciation of the literature - on the contrary, Reviewer 2 appears to have a very sound grasp of the topic.

Reviewer #1 (Significance):

Unfortunately, I did not find tis to be very significant. It covers old ground in terms of the phenotype described. Many groups have shown the differences between procyclic and bloodstream phenotypes in this enlarged pocket phenomenon. The work is rather incremental from these and other author's work on these hook proteins.<br /> There are alternative explanations for understanding the effect of flagella pocket structure and uptake of ligands into the pocket and trypanosome cell. These would need to be studied before one could see a functional, mechanistic link established.<br /> Other parts of this are of nicely done but do not move on our understanding (eg targeting/phosphorylation) from what has been done previously.

As noted repeatedly, it appears that Reviewer 1's priority is disparaging the value of the work here and downplaying its significance rather than providing constructive feedback. The reviewer repeatedly makes unrealistic demands (a mechanistic model, use of non-standard reagents), misunderstands the aim of experiments (use of high-pressure freezing), makes vague allusions to other work in the literature but without citing anything specific to support their case, and makes strong and assertive statements that are factually incorrect (design of RNAi experiments, use of dextran). We find this approach unhelpful, uncivil, and unprofessional. It is desperately disappointing that we should have to spend the majority of our response rebutting Reviewer 1's comments rather than implementing constructive criticisms that would strengthen the manuscript.

Reviewer #2 (Evidence, reproducibility and clarity):

Summary:<br /> In this manuscript the authors have advanced our understanding of the hook complex component TbSmee1 through a detailed analysis of this protein's role in the endocytosis of surface bound proteins via the flagellar pocket in bloodstream form Trypanosoma brucei. The TbSmee1 protein, previously identified using proximity labeling using TbMORN1 and TbPLK, and characterized in procyclic T. brucei, was confirmed to target to both the shank portion of the hook complex as well as the growing end of the new FAZ in replicating cells. The protein was also shown to likely be phosphorylated as had been suggested previously due to its association with the kinase TbPLK. A domain deletion analysis demonstrated that domains 2 and 3 are important for TbSmee1's proper localization to the hook complex. Loss of TbSmee1 using RNAi based knockdown resulted in a quick cessation of growth in the bloodstream form within 24 hours in contrast to what was seen previously in procyclic cells which had only a decreased growth rate. Loss of TbSmee1 also resulted in an enlargement of the flagellar pocket and in many ways mirrored the phenotype observed with knockdown of TbMORN1. Although prior work on TbSmee1 in procyclic T. brucei demonstrated that loss of this protein altered the morphology of TbMORN1, no such change was seen in bloodstream form cells and only an alteration in the morphology of TbLRRP1 was observed. In characterizing the effect of TbSmee1 depletion on endocytosis the authors showed that the fluid phase marker Dextran could enter into the flagellar pocket of TbSmee1 depleted parasites while the surface bound ConA and BSA remained outside of the flagellar pocket suggesting that TbSmee1 may play a role in allowing larger protein components into the pocket regions. Similar observations were also previously seen with TbMORN1 depletion. Importantly, a knockdown of clathrin recapitulated the TbSmee1 knockdown phenotype suggesting that endocytosis itself was required to allow material bound at the surface to enter into the flagellar pocket. In addition to adding to our understanding of hook complex components, this work raises some interesting questions regarding the role of the hook complex in facilitating endocytosis in this important human pathogen.

Thank you for the positive assessment.

Major Critiques:<br /> This is a superbly written manuscript with robust high-quality data that strongly support the major conclusions made by the authors. The flow the article is logical and easy to follow making it accessible to a wide array of readers.

We are glad that the Reviewer appreciated the effort that went into writing the paper.

Although I appreciate the brevity of the introduction and how the article gets straight to the point, additional background information on the components and function of the flagellar pocket collar protein could help contextualize the goals of the project. The way in which the flagellar collar structures are introduced to the reader is quite abrupt (beginning on line 75) and simply states the names of TbBILBO1, the centrin arm and hook complex as simple facts without much discussion about the background of these components/regions. A graphical representation of the centrin arm or hook complexes relative to other components like the pocket itself, FAZ or axoneme could make following the story much easier. An expansion of this background could also go a long way to convince readers of the importance of this region in the basic biology and virulence of T. brucei.

Implemented. We have added more background details on the hook complex, flagellar pocket collar, and centrin arm and added a new schematic image to Figure 1 showing these structures as well as the FAZ (Figure 1A).

On lines 84-86 the authors cite the way in which 'small' vs 'large' macromolecules enter into the pocket without defining what exactly is meant by these terms as they are relative in nature. Setting some boundaries of size could provide some context to the reader.

Implemented. We have provided more detail on the approximate sizes in nm (lines 110-113 of tracked-changes manuscript).

In the domain localization analysis beginning in Figure 4 there is a missed opportunity to also assess which portions of the TbSmee1 protein are important for overall function as well. By either an examination of dominant negative phenotypes resulting from overexpression of the truncated mutant or the expression of the truncated forms designed to be RNAi resistant in the TbSmee1 knockdown cell line, one could also assess which portions of this protein are essential for endocytic function in addition to targeting. Is there a reason this was not performed?

This is a good point; we did actually investigate overexpression of the TbSmee1(161-766) construct which can target correctly but is missing the first folded domain, but did not observe any phenotypic effects. We have added this point to the results (lines 301-302 of tracked-changes version). We agree that it would be interesting to express the truncations in a TbSmee1 RNAi background in order to simultaneously assay for targeting and function, but this was (unfortunately, perhaps) not part of the original experimental design. To do so now would require generating a completely new panel of truncation constructs with recoded DNA (in order to make them RNAi-resistant) and then generating a new panel of cell lines. While this would be informative, we feel that it would be impractical at present.

In the analysis of viability changes due to TbSmee1 depletion (lines 237) the authors state that at "72 h post-induction showed widespread lysis, ..." This phenotype seems inconsistent with other related endocytic defect mutants. There is no further mention of this lysis phenomenon here or in the discussion and considering how unique this seems it deserves either additional data to demonstrate or further discussion as to the basis of the phenotype. It seems, at least from this study of TbStarkey1 and prior studies which result in the enlarged flagellar pocket phenotype, that having an enlarged pocket is not the cause of lysis and doesn't even naturally lead to a growth defect.

Widespread lysis is the usual outcome of bloodstream form cells with strong endocytic defects - we have observed this directly for the clathrin, TbMORN1, and TbSmee1 RNAi cell lines, and it has been documented in a number of other publications (see for example Natesan et al., 2010, Manna et al., 2017). We have clarified this point in the text (see for examples lines 359-341, 474-478 of tracked-changes manuscript).

The authors do not comment on what is the source for the cessation in growth following TbSmee1 knockdown. Is it nutrient depravation like in other endocytic defect mutants?

Implemented (see for example lines 359-361, 605-610 of the tracked-changes manuscript). The source of the growth defect is likely to be due to impaired cell division cycle progression due to the gross enlargement of the flagellar pocket and subsequent steric hindrance and imbalance of membrane homeostasis.

In the end, one of the most interesting observations made by the authors is that loss of TbSmee1 inhibits endocytosis and this has the appearance of not allowing large molecule substrates like ConA and BSA to enter into the flagellar pocket. This appeared to have nothing to do with a gatekeeping type function of the hook complex/flagellar collar and instead, as shown through clathrin knockdown, was related to the ability of the parasite to endocytose. There are a lot of potential interpretations of this phenomenon with one being a simple perturbation of the normal membrane trafficking to and from the flagellar pocket being involved. An analysis of knockdown of exocytic components might reveal whether or not this inability to enter into the pocket is also seen when exocyst proteins are also depleted. It may be impossible to tease apart these two interrelated activities but it might eliminate one side of the equation if these proteins can still enter the flagellar pocket when exocytosis if perturbed although this reviewer understands that that dimension of T. brucei membrane trafficking is poorly understood relative to endocytosis.

This is an interesting point, and the reviewer is also correct in highlighting that exocytosis is far less characterised than endocytosis in Trypanosoma brucei. The exocyst has been characterised in bloodstream form T. brucei (Boehm et al., 2017) and shown to also have a role in endocytosis, so teasing out the relative contributions of these pathways would undoubtedly be challenging. We would prefer not to go in this direction in this present study, but it is an obvious avenue for future work.

An intriguing possibility that the authors allude to and which if answered would make this manuscript have a far broader appeal is to determine if loss of TbSmee1 alters the lipid kinase distribution and if this is the source of the negative impact on endocytosis. One important dimension of endocytosis in T. brucei which remains poorly understood is the role of signaling machinery in triggering endocytic events. It is possible that the hook complex serves as the gatekeeping or signaling platform that recruits signaling components (like lipid kinases) that identify and/or modify the membrane lipid phosphatidylinositols harboring cargo laden receptors thus marking them for endocytosis within the pocket. It still seems unclear when in the process of endocytosis is the decision made to pull things into the pocket but it seems that the assumption is that this occurs deep within the pocket. This data suggests that there is possibly another decision point prior to being allowed entrance into the pocket. It may be that this isn't a gatekeeping decision but rather a stop vs. go activity where once cargo laden membrane reaches the collar a choice is made to pull this material in or not there and not after material is already in the pocket.

These are all really interesting ideas and would be fascinating topics for future work.

This obvious enigma based on the observation that loss of hook complex components affect the spatially separated site of endocytosis support the idea that the actual endocytic signaling platforms are located at the hook complex and that this area may make the membrane modifications that mark membrane as being ready to be endocytosed via clathin coated vesicles at the bottom of the pocket. This would still allow for fluid phase small molecule entrance which does not require binding to surface proteins. The obvious problems of having both endo/exocytosis occurring in the same close proximity makes the dissection of this phenomenon difficult but it is worth potentially expounding on further in the discussion as this idea is very appealing and adds an important dimension to our understanding of endocytosis in this organism.

Implemented (lines 722-727 of the tracked-changes manuscript). We have added some more detail to these points in the Discussion. We agree with the reviewer that there are some profoundly interesting questions concerning membrane identify and membrane protein uptake here.

Minor Critiques:<br /> The authors commit significant time to the analysis of the phosphorylation of TbSmee1, but there is little stated about the role of TbPLK in this activity or the potential connection of TbSmee1 phosphorylation to the cell cycle. Would a knockdown of TbPLK using RNAi potentially demonstrate an altered migration of TbSmee1 due to a lack of phosphorylation? An analysis of radiolabeled TbSmee1 using p32 in vivo would likely support this claim as well. Has mass spectrometry identified potential phosphorylation sites to examine? Additionally, the loss of TbSmee1 has been shown to disrupt localization of TbPLK in procyclic cells and so why this was not also assessed in bloodstream form cells subjected to RNAi was not clear.

Partly implemented. We have added some discussion of the possible role of TbSmee1 phosphorylation in the cell cycle to the Discussion (lines 562-565 of tracked-changes manuscript), and emphasised the identification of phosphorylation sites in previous phosphoproteomics work (citations of Nett et al., 2009, Urbaniak et al., 2013). Given that the strongest and earliest effect of TbSmee1 depletion was on endocytosis and cargo uptake, we chose to focus on this angle rather than exploring its contribution to the biogenesis of cytoskeleton-associated structures and its interaction with TbPLK. For that reason we would prefer not to carry out the experiments looking at the effects of TbSmee1 depletion on TbPLK or vice versa.

In the results section (lines 104-108) a model of the protein structure as predicted for example by AlphaFold might be informative and complement the domain analysis work depending on the quality of the prediction.

Implemented. The AlphaFold prediction is consistent with the predictions made by the other structural analyses, and we have noted this in the text (lines 145-148 and 551 of the tracked-changes version).

There is an arrow in the Figure 1B Western blot but I can find no mention of what it is trying to highlight in the text.

Corrected.

For Figure 1D there is no loading control or control for the distribution of the soluble fraction to validate the separation of the two compartments.

Implemented. We have carried out additional experiments to show the partitioning of a cytoplasmic protein (the endoplasmic reticulum chaperone BiP) into the detergent-soluble fraction. These results are now displayed in the updated Figure 1.

The authors fail to comment on the lack of changes in hook complex components they see to that observed by Perry et. al. 2018. This difference merits some minor comment or speculation.

Implemented. We have added this commentary to the Discussion (lines 592-600 of the tracked-changes version).

Line 228: domain should be capitalized.

Implemented.

Line 230: FigS5C should have a space and period after Fig. and S5C.

Implemented.

Line 244: "on" should be inserted in the sentence "...TbSmee1 protein depletion ON either side of the onset..."

Implemented.

Line 400: the '...20/21 h post-induction...' is slightly confusing and may read better as 20-21 h.

Implemented.

Line 463: a space is needed between '...2009).The...'.

Implemented.

Reviewer #2 (Significance):

This manuscript advances our current conception of endocytosis in T. brucei. Although this model kinetoplastid parasite has been extensively studied with respect to endocytosis there is still a great deal we do not yet understand regarding how this process is regulated at a mechanistic level. This work has begun to connect previously unappreciated aspects of endocytosis in T. brucei by highlighting a potentially novel connection between the flagellar collar/hook complex and the physically separated endocytic events within the flagellar pocket itself. It may be that what appears as regulated entrance into the pocket is in fact the source of signaling that triggers the endocytic events carried out by clathrin. This is an interesting notion that no doubt requires further investigation which lies outside of the scope of this report. While this work appeals primarily to those studying kinetoplastids parasites it has the potential to provide insight into basic protozoan biology as well. Due to my related interest in kinetoplastid endocytosis, I find this work to be of high quality, conceptually interesting and employs many of the cutting-edge techniques currently available in the study of T. brucei.

We are very happy that the Reviewer formed a favourable impression of the work.

Reviewer #3 (Evidence, reproducibility and clarity):

This manuscript begins to dissect the function of the hook complex protein SMEE1 in the mammalian infective form of T. brucei. The hook complex is a cytoskeletal structure associated with the flagellar pocket, the only site of endo/exocytosis in these cells. The authors demonstrate that SMEE1 is required for endocytosis in these cells and that this can occur with minimal change to the molecular make-up of the hook complex. The authors show that endocytosis is important for the access of large molecules e.g. ConA into the flagellar pocket.

Major comments

The key conclusion of this study are convincing and the data is generally well presented and clear. The interpretation of the figures matches well with the data presented - there are a few minor issues though that I have highlighted below in minor comments. The authors use a range of molecular cell biology approaches to define the role of SMEE1 and these are appropriate and are well controlled.

Thank you.

My major comment focuses on the use of different tracers to study endocytosis but the elephant in the room is what is happening to VSG as this is the surface protein that needs to rapidly removed from the cell surface and cleaned. Given the importance of removal of antibodies bound to the VSG - have the authors looked at this in the SMEE1 depleted cells? Do VSG-antibody complexes accumulate in this region? This is an important experiment as this would give key physiologically relevant data to this study. All the material should be readily available for this as there are a number of VSG antibodies.

We agree with the Reviewer that the behaviour of these VSG-bound antibodies is a key test of the physiological relevance of the observations we have made using ConA and BSA, and have implemented this request - the results are in the new Figure 9. Although they sound simple, these assays turned out to be far from trivial and much more technically challenging than the other uptake assays, owing to the extremely fast kinetics (seconds) of anti-VSG uptake (Engstler et al., 2007) and the unexpectedly and incredibly high losses of bound antibodies during the assay. This might be due to shedding, as noted in the Discussion.

Minor comments<br /> Perhaps I have been overthinking this but is surface-bound the right way to describe the cargo, as it clearly goes in both directions onto and off the surface and in fact the experiments in this manuscript are focussing on the removal of this material from the surface so is not surface-bound.

We have clarified that "surface-bound" refers to material that binds to the surface glycoprotein coat of the trypanosomes and which is subsequently internalised, not material that is bound for (i.e being directed to) the cell surface (lines 77-78 of tracked-changes version). We hope this addresses the Reviewer's point?

Have the authors investigated the structure of the protein using alphafold and if so how does that compare to the domain structure that was presented in this manuscript?

Implemented (lines 145-148, 551 of tracked-changes version). We have checked the AlphaFold prediction of the three-dimensional structure of TbSmee1 and noted it in the Results; the prediction is consistent with the earlier bioinformatic analyses.

The authors raised a number of antibodies to TbSMEE1 and TbSTARKEY1 but it was not clear in the figures which antibody was ultimately used for analysis by western and IF - could the authors clarify, as some looked to have a higher background than others. Line 150 states the same localisation was seen for all three antibodies and references S3C but I couldn't see that data presented.

Implemented - the 304 antisera was used for most subsequent experiments and we have noted this in the M&M (lines 793-798 of tracked-changes version). Figure S3C shows that the Ty1-TbSmee1 recapitulates the localisation of the antibodies against the endogenous protein - we have clarified this point as well (lines 206-207 of tracked-changes version).

Line 169 - can the authors provide more detail about the global correlation methodology as I was unable to follow the details in the methods? Is this a pixel per pixel correlation over the image or on a selected region over the area of potential signal overlap? In figure 2E it appears that BILBO1 signal correlates more closely with the SMEE1 signal than MORN and LRRP1 and from the images that would not seem to be the case. Have I interpreted this figure incorrectly?

Implemented. The original analysis was a global correlation analysis that was determining whether the signals were correlated with each other regardless of spatial overlap, and we agree with the reviewer that these outputs were non-intuitive to interpret. In the revision, we have carried out a new analysis (and updated the accompanying text and M&M section), measuring the degree of spatial correlation between each pair of signals on a pixel-by-pixel basis over the area of each cell, with a total of 30 cells analysed in each pairing. We believe that this addresses the reviewer's point. See lines 223-243, 963-974 of the tracked-changes version).

The authors have generated a number of different clones and performed experiments on these clones generally more than twice, which is clearly explained in the figure legends but in places the data is then put together and it is difficult to know which experiments/clones it comes from - for example 7C/7F what do those percentages represent? Is this the sum of all experiments? A representative experiment? How many cells per experiment were analysed?

Implemented. We have double-checked all the figure legends and clarified this point where necessary. Quantifications were always made by compiling data from multiple independent experiments using multiple separate clones - see in particular lines 1323-1324, 1363-1365, 1380-1382 of the tracked-changes version.

Line 200 - From the image it is not convincing that SMEE1 is slightly behind DOT1 - I agree it looks enveloped but would appear level with the distal end of the DOT1 signal.

Implemented. We have adopted the Reviewer's wording for this text (line 271 of tracked-changes version).

For the truncation experiments the authors should explain that these are performed with cells in which the endogenous SMEE1 will be expressed and this may influence the localisation of the truncations, especially as there is no information about whether SMEE1 forms complexes with itself or other proteins.

Implemented (lines 296-298 of tracked-changes version).

Figure 4D - should be 1 not T-

We have relabelled this as "TbSmee1". The values in this column are the immunoblot signal intensities obtained for the endogenous TbSmee1 protein in the -Tet condition. We have also clarified this in the figure legend.

Line 223 - given the low expression of constructs 2 and 9 I'm not sure it is possible to infer anything from the lack of localisation of these constructs as they appear unstable and would be unlikely to localise to a specific location.

We have added this caveat to the text (lines 558-562 of tracked-changes version).

Figure S7 - The images presented were not convincing that there was a reduction in the localisation of LRRP1 to the hook complex on depletion of either SMEE1 or MORN1. The difference looks particularly minor if present at all.

Agreed, there was some debate in the group about these results. We have changed to text to fit the Reviewer's interpretation (lines 347-348 of the tracked-changes version).

Line 264 - "implied that the lethal phenotype might be due to a loss of function" - this seems an odd thing to say as it doesn't provide any insight as of course the phenotype is due to a loss of function.

We have clarified this point (lines 350-353 of the tracked-changes version). We would however disagree with the reviewer that RNAi phenotypes are exclusively due to a loss of individual protein's function(s) - when proteins are present in multiprotein complexes (as is often the case with cytoskeleton-associated proteins), then destabilisation of the complex due to loss of the entire protein can cause the observed phenotype, rather than the loss of the function performed by the individual protein within the complex (this may be a semantic point, however). A very good example of this is with the outer arm dynein complex component LC1 (Ralston et al., 2011) - RNAi against LC1 is lethal because the entire outer arm dynein complex is destabilised, whereas expression of non-functional mutants of LC1 produces viable cells with motility defects due to the specific loss of LC1 function.

Line 412 - can the authors clarify what they mean by geometric problems?

Implemented (lines 605-610 of tracked-changes version). We were referring to the fact that enlargement of the flagellar pocket will probably create difficulties for the progression of the cell division cycle.

Throughout the manuscript can you use log scale for the growth curves.

Implemented.

Line 756 - add citation

Whoops! Implemented (line 1058 of tracked-changes version).

Line 465/66 - the authors states that the ability of the fluid phase cargo being still able to enter the pocket is evidence that the channel lumen is still open; however, I would think that despite the close apposition of the cell membrane to the flagellar membrane in the flagellar pocket neck region this would be unlikely to impede fluid/soluble material from entering the pocket, as presumably VSG protein can move through this region. This does not alter the ultimate conclusion the authors are drawing but without microscopy evidence for the state of the channel lumen it is difficult to be sure of its status.

Fair point. We have modified this statement (line 701 in tracked-changes version).

Reviewer #3 (Significance):

The flagellar pocket is the key portal into and out of the trypanosome cell and as such has a vital role to play in host-parasite interactions. The flagellar pocket is supported by a number of cytoskeletal structures including the hook complex and the role of these structures in flagellar pocket function are poorly understood. The flagellar pocket is particularly important in the bloodstream form of the trypanosome parasite which infects the mammalian host as it is the route for the surface protein VSG to get onto and off the surface. The VSG is required for antigenic variation and the removal of VSG-antibody complexes helps 'clean' the surface of the parasite. SMEE1 is a component of the hook complex and the manuscript here dissects its role in the mammalian infective parasite and shows that it is vital for the endocytosis of material off the surface. Intriguingly, a block in endocytosis causes a blockage of material outside of the pocket, suggesting a multi-step process in the regulation of uptake of material from the parasite's surface.<br /> This manuscript will be of specific interest to those researchers investigating the long-term persistence of these parasites in the mammalian host. There are potentially some insights into the control of membrane domains for endocytosis that are of interest to more general cell biologists as well.

We are very grateful to the reviewer for the supportive comments and the constructive evaluation. Many thanks!

Expert in molecular cell biology of trypanosomes and Leishmania.

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Referee #1

Evidence, reproducibility and clarity

Unfortunately, this paper adds only a little to our understanding of uptake in to the flagellar pocket of trypanosomes. It tends to add only detail to information that has been well characterised elsewhere and indeed, as the authors themselves point out, (lines 92-98) it is rather incremental. Not only has Tbsmee1 been studied before but this data in bloodstream forms is not particularly novel since it gives much the same information as the canonical hook protein TbMORN.

This work follows the pattern of conclusions made previously with the protein TbMORN. It focusses on the protein TbSmee where RNAi mutants are interpreted to show flagellar pocket enlargement and impaired access by surface bound cargo. Unfortunately, there is little mechanistic or functional conclusion to the study in terms of how TbSmee operates naturally in the cell. There are other possible explanations for the phenotype. That would need to be studied. This large flagellar pocket phenotype is seen with RNAi mutants of many different types of proteins in the trypanosome and so pleiotropic effects are highly likely.

Also, there are a good number of alternative possibilities to account for reduced access to the pocket in these mutants and this data could be usefully added.

Specific points

1. The transient location for the TbSmee at the FAZ tip - or in this case the groove region - was seen in procyclics (Perry, 2018) so this bloodstream indication merely confirms that concept.
2. The C terminal region required for targeting is a reasonable deletion analysis of regions of the protein. But can this data (line 228) be said to "mediate targeting" - or is it just required. For instance, targeting might be OK but it might be needed for stable association, etc etc.
3. This protein has already been shown to be phosphorylated and the sites and cell cycle possibilities have been mapped by Urbaniak. So that section adds little. https://doi.org/10.1371/journal.ppat.1008129
4. Essentiality in BS forms and pocket enlargement. This is not surprising. A very large number of cytoskeletal proteins show this in RNAi knockdown. Flagella mutants (extensive publications from many groups (Hill, Bastin, Gull, etc) over last 15 years show this very well and so this protein is just one more example.
5. I didn't find that the explanations for flagella pocket enlargement are soundly based. The experiments focus on endocytosis and uptake and ignore other plausible reasons and some evidence in literature.<br /> Lines 84/85. Enlarged pockets may be indicative of endocytosis failure. Presumably the rationale is that endocytosis fails, but exocytosis still occurs and the pocket membrane enlarges. What evidence is there that exocytosis of membrane still occurs? This simple concept might indeed operate in a clathrin mutant but is surface membrane/content exocytosis is maintained in these cytoskeleton mutants? There is good evidence for glycoconjugates within the flagellar pocket. Are these depleted or present still?
6. There are also a number of other publications indicating that clathrin pits are still present on the enlarged pockets of various mutants when viewed by EM. The authors have looked at the flagellar pockets by EM but the EM methods described have extensive washings and centrifugations before fixation. This is a very poor approach and will mean that endo and exocytic traffic is disturbed (extensive references in literature in other systems? This is not a useful approach for exo/endocytosos studies where flux of traffic demands fast chemical or freezing fix in media.
7. The EMs and Light microscopy does show that the mutant pockets are substantially abnormal in their cytoskeletal arrangement. They have multiple flagella profiles, flagella structures have not connected with the membrane and are sometimes in the cytoplasm (see a glance of the paraflagellar rod in the cytoplasm in FigS5C and internalised FAZ attachment plaques in Fig 4 D bottom right cell). Given these extensive (and expected) cytoskeletal abnormalities it is highly likely that these pocket abnormalities are a result of motility, cell division/developmental issues and the differential uptake phenotypes merely consequential.
8. The authors speak about early phenotypes , but these are often at 15-24 hours. That is probably a couple of cell cycles and so not early. In relation to the above question of comparison to the same morphology produced by flagella mutants it would be good to know if these hook mutants produce motility phenotypes and whether these are manifest before the uptake phenotypes. There is evidence (cited here) that forward motility of the trypanosome directs material on surface into the pocket. If these cells have motility defects (primary or via failed division) then surely that would provide an alternative simple explanation for uptake differences.
9. There is a general point that if studies are to have real relevance to uptake in the trypanosome then they need to deal with uptake of natural ligands rather than artificial surrogates such as dextran. Such tracers were used historically, but in the last decade a series of receptors and ligands for fluid phase and particularly membrane mediated endocytosis have been discovered. With the investment of a little time these important ligand / receptors such as haptoglobin, transferrin, etc would be much more relevant.

Referees cross-commenting

This session includes comments from Reviewer 1 and Reviewer 2.

Reviewer 2

Dear Reviewers 1 and 3:<br /> I agree with many of the points with Reviewer 1 and our divergence is partly a matter of degree. While it is true that this manuscript is incremental in its contribution to our understanding of TbSmee1, it nonetheless adds to our understanding of the role of this protein in the bloodstream life stage and because of that I find value in the work. The fact that it mirrors what was seem in other protein knockdown studies (e.g. TbMORN) doesn't negate its contribution for me. Reviewer 1 makes an important point, however, when stating that this work does not add a mechanistic or functional conclusion as to how TbSmee1 operates and for me that is the biggest shortcoming of the work. Offering mechanistic insight is a high bar and while it would make for a much more exciting story it does not discount the value of the work as presented. What I do appreciate is the speculation about this observation that endocytosis is required for entrance of surface bound material into the pocket and although they are unable to show that this is not a side affect of other processes being disrupted it is and intriguing point. These observation have the potential of stimulating further investigations into crosstalk between the entrance to the pocket and endocytosis. I also agree that the use of ligands for known receptors like transferrin would be far more informative. While I assumed the transferrin receptor was in the pocket itself it would be interesting to see if the ESAG6/7 is also located outside the pocket and transiently binds cargo before being brought inside for endocytosis.<br /> I think that Reviewer 3 brings up a great point with the focus on VSG's. I think that examining VSG turnover in these mutants can add value to the analysis and inform our view of how affecting the hook complex alters VSG endocytosis.

Reviewer 1

some fair comment and agreement. This is being sent to general cell biology journals.<br /> when one looks at this area in the round it is nearly 50 years (1975) since Langreth and Balber published their seminal work on protein uptake and digestion in bloodstream and culture forms of T. brucei. There has been 50 years intense study and the genome has been around for nearly 20 years as well. So, put simply - for both a general science audience and the wider parasite community - if this is a paper about one protein, TbSmee1,then it has surely has to say something functional about that protein. If it is a paper about uptake in trypanosomes (where mutants are one means of interrogation) then it surely has to say something about mechanisms of uptake of physiological relevant ligands. The days of dextran etc are past. Hence, my comment that this does neither and so is very incremental to what is known already. It is 2022 not 1975. Langreth and Baber published their seminal work in J Protozoology for very good reasons no doubt.

Reviewer 2<br /> Thank you for replying and I agree with the spirit of your critique. My only comment, which could result from my own naivete, is to say that despite the incredible work that has been done in dissecting endocytosis in T. brucei over these past 50 years, it appears that we still do not understand how many fundamental of aspects of this activity works in this parasite. Even basic questions regarding how cargo, e.g. transferrin, binding to surface receptors is sensed by the parasite remains unknown and the identity of the specific signaling components which transmit this information internally to initiate endocytosis have not been characterized. In many ways it seems that we don't even understand how the parasite partitions the end/exocytic pathways in the pocket and maintains membrane homeostasis. While we know that some kinases and traditional signaling components must be involved, a high resolution understanding of this process in T. brucei seems lacking. I only say all this to suggest that the field maybe isn't yet that advanced to reject work of this type as so many mechanistic unknowns still remain to be uncovered and maybe incremental advances and phenomenology still can add value to the field. However, I respect your opinion on the matter and my perspective could be due to a lack of a full appreciation of the literature on the subject.

Significance

Unfortunately, I did not find tis to be very significant. It covers old ground in terms of the phenotype described. Many groups have shown the differences between pro cyclic and bloodstream phenotypes in this enlarged pocket phenomenon. The work is rather incremental from these and other author's work on these hook proteins.

There are alternative explanations for understanding the effect of flagella pocket structure and uptake of ligands into the pocket and trypanosome cell. These would need to be studied before one could see a functional, mechanistic link established.

Other parts of this are of nicely done but do not move on our understanding (eg targeting/phosphorylation) from what has been done previously.

This work has been published in GigaByte Journal under a CC-BY 4.0 license (https://doi.org/10.46471/gigabyte.89) and has published the reviews under the same license. These are as follows.

**Reviewer 1. Clara Albiñana **

As Open Source Software are there guidelines on how to contribute, report issues or seek support on the code?

No. Although there are no explicit guidelines for contribution in the manuscript or website, it is true that by placing the project on gitlab it is possible to contribute to the project / open issues.

Is the code executable?

No. Unfortunately, I wasn't able to install the R package. I have now opened an issue on the gitlab page so that it can hopefully get solved.

Is installation/deployment sufficiently outlined in the paper and documentation, and does it proceed as outlined?

Yes. It is very common for new R packages to just use devtools for installation.

Is the documentation provided clear and user friendly?

Yes. The requirements for generating a trumpet plot just involve providing a set of GWAS summary statistics with column-specific names, together with the GWAS sample size. This is very common for GWAS summary statistics-based tools. I think it is fine for the R package to require re-naming the columns to fit the format, as one already needs to upload the file into R. However, I find it inconvenient to have to re-save the summary statistics file with different name-columns for the shinyapp tool. Providing e.g. column indexes alone would be much more user-friendly.

Is there enough clear information in the documentation to install, run and test this tool, including information on where to seek help if required?

No. I cannot answer this question until I can install the tool.

Have any claims of performance been sufficiently tested and compared to other commonly-used packages?

Not applicable. There are no existing comparable tools.

Is automated testing used or are there manual steps described so that the functionality of the software can be verified?

Yes. I can see there is a toy dataset included with the R package.

Additional Comments:

I think the manuscript is very clear and good at making the point of the utility of the software. The proposed trumpet plots are very visually appealing and can be useful to characterise the genetic variation of diverse phenotypes. The novelty of the trumpet plots, as compared to previously proposed effect size vs. allele frequency plots, is the use of positive and negative effect sizes, making it look like a trumpet. I also appreciate the style decisions in the standard generated plots, with a nice visually-appealing color scheme and design.

On the use of the software, I have focused my testing on the R package, which I was not able to install. The shinyapp is very useful for visualising the existing, pre-computed trumpet plots, but I do not find it very useful for generating user-uploaded summary statistics for the reasons I mentioned above. Another comment on the ShinyApp is that I appreciate the possibility to download the plots but it would be very useful to include the name of the visualized phenotype as the plot title, for example, to avoid confusion when downloading multiple plots.

I also found an incorrect sentence in the abstract, which is think should be reversed: " The proposed plots have a distinctive trumpet shape, with the majority of variants having low frequency and small effects, while a small number of variants have higher frequency and larger effects".

**Reviewer 2. Wentian Li **

Is the documentation provided clear and user friendly?

No. Many aspects of Fig.1 are not explained.

Overall Comments: Plots with allele frequency as x axis and effect size (e.g. odds ratio) as y axis is a very common display of the contribution from both common and rare alleles to genetic association. A schematic form of this plot is practically on almost everybody's presentation slides when introducing this topic (to see an example, see, e.g. Science (23 Nov 2012), vol 338(6110), pp.1016-1017 ). Considering how many people have already been familiar with this type of plot, I feel that very little new is added in this paper: maybe only a new name ("trumpet"), and/or the power lines. The other methods contributions (log-x, one variant per LD, avoiding gene-level statistics) are rather straightforward. People without experience with "shiny" (R package) can still use ggplot2 or plot in R to get the same result. Generally speaking, I think the paper is weak, though OK as a program/package announcement.

Major comments: * I think the trumpet shape (increase of "effect size" for rare variant) is probably a direct consequence of using odds-ratio as a measure of effect size. If the allele frequency in normal population is p0, that in disease population is p1, [p1/(1-p1)]/[p0/(1-p0)] ~ p1/p0 tends to be large for small p0's, simply because the denominator is small. On the other hand, if population attributable risk (p0(RR-1)/(1+p0(RR-1))) is used as the y-axis, I am uncertain what the shape of the plot would be.

• A risk allele has these pieces of information:
• allele frequency,
• effect size (e.g. odds ratio),
• type-I error/p-value,
• type-II error/power. The plot in this paper show #1 vs #2 and #4 being added as extra. In another publication with a proposal to plot genetic association results (Comp Biol. and Chem. (2014), 48:77-83 doi: 10.1016/j.compbiolchem.2013.02.003), #2 is against #3 with #1 being an added extra. I'm sure using other combinations could lead to other types of plots. The authors should discussion/compare these possibilities.

Minor comments: In Fig.1, the size of the dots, the brown vs cyan color, the discontinuity of scatter dots around 0.01, are not explained.

Re-review:

I have read authors' response and I'm mostly satisfied. Only two minor comments: * Witte 2014 Nature Rev. Genet. article summarizes the point I tried to make well. I understand that rare variants should have a relatively higher effect from an evolutionary perspective, but since these are rare, their individual or even collective contribution to a disease in the population is still small. A casual reader may not realize this point and I think it would be helpful to cite Witte's article. * My minor comment on Fig.1 is still not addressed: there seem to be more points on the right side of p=0.01 line than the left side. Why this discontinuity? (the added text in Revision is about the color and size of the dots, not about this discontinuity)

Author Response

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

eLife assessment:

This study presents a useful inventory of the joint effects of genetic and environmental factors on psychotic-like experiences, and identifies cognitive ability as a potential underlying mediating pathway. The data were analyzed using solid and validated methodology based on a large, multi-center dataset. However, the claim that these findings are of relevance to psychosis risk and have implications for policy changes are only partially supported by the results.

We appreciate the feedback and insightful suggestions from the editor and reviewers, which aided us to improve the manuscript. We believe the concerns initially raised were mostly due to areas that needed further clarification, which we have now clarified in this revised version. Our primary contribution lies in our meticulous analytical approach aimed at minimizing confounding effects and providing more precise estimates of the genetic and environmental impact on children's cognition and psychology. This method differs from the widely used general linear modeling in the field, which, in our opinion, may not be the optimal strategy for large-scale data analysis. Our comprehensive, tutorial-style description of the methods might serve as a valuable resource for the community.

Regarding the critique that our findings 'partially support the relevance to psychosis risk,' we have updated our manuscript to more accurately reflect this feedback. We have altered the narrative to indicate that psychotic-like experiences (PLE) are associated with the risk for psychosis, a connection substantiated by prior studies cited in our manuscript.

Similarly, in response to the comment that our findings 'partially support implications for policy changes,' we have nuanced our conclusion. However, we would like to emphasize our discovery that a negative genetic predisposition impacting cognitive development (i.e., low polygenic scores for cognitive phenotypes) can be counteracted by a positive school and familial environment. We believe that this finding could have meaningful implication for policy making and is robustly supported by our analyses.

We hope this revised manuscript more accurately reflects our research findings and its significances. Lastly, we would like to express our gratitude for your fair and detailed review process. Our experience working with eLife has been incredibly rewarding, and we commend your dedication to an encouraging and progressive publishing culture.  

Public Reviews:

Reviewer #1

This study by Park et al. describes an interesting approach to disentangle gene-environment pathways to cognitive development and psychotic-like experiences in children. They have used data from the ABCD study and have included PGS of EA and cognition, environmental exposure data, cognitive performance data and self-reported PLEs. Although the study has several strengths, including its large sample size, interesting approach and comprehensive statistical model, I have several concerns:

• The authors have included follow-up data from the ABCD Study. However, it is not very clear from the beginning that longitudinal paths are being explored. It would be very helpful if the authors would make their (analysis) approach clearer from the introduction. Now, they describe many different things, which makes the paper more difficult to read. It would be of great help to see the proposed path model in a Figure and refer to that in the Method.

We clarified the longitudinal paths tested in this study in Intro [line 149~159]. We also added a figure of the proposed path model (Figure 1) [Methods: line 231~238].

• There is quite a lot of causal language in the paper, particularly in the Discussion. My advice would be to tone this down.

We adjusted and moderated the use of causal languages throughout the manuscript.

• I feel that the limitation section is a bit brief, and can be developed further.

We clearly specified the limitations of our study. These included concerns about the representativeness of the ABCD samples, of the limited scope of longitudinal data, and the use of non-randomized, observational data [line 524~544].

• I like that the assessment of CP and self-reports PEs is of good quality. However, I was wondering which 4 items from the parent-reported CBCL were used and how did they correlate with the child-reported PEs? And how was distress taken into account in the child self-reported PEs measurement? Which PEs measures were used?

Thanks for the clarification question. We report the Pearson’s correlation coefficients between the PLEs [line 198~200]. (The Reviewer #1 may have referred to the prior version of our manuscript submitted elsewhere, for this point has been already addressed in our initial submission to eLife).

• What was the correlation between CP and EA PGSs?

The Pearson’s correlation between CP and EA PGS was 0.4331 (p<0.0001). We added the statistics to the manuscript. [line 214]

• Regarding the PGS: why focus on cognitive performance and EA? It should be made clearer from the introduction that EA is not only measuring cognitive ability, but is also a (genetic) marker of social factors/inequalities. I'm guessing this is one of the reasons why the EA PGS was so much more strongly correlated with PEs than the CP PGS. See the work bij Abdellaoui and the work by Nivard.

We appreciate the reviewer’s insightful feedback. Acknowledging the role of both CP and EA PGSs in our study, we agree with the observation that EA PGS goes beyond gauging cognitive aptitude—it also serves as an indicator of societal influences and inequalities. The multifaceted nature of EA PGS could be the reason underlying the stronger correlation with PLEs compared to CP PGS. In response to this feedback, we revised our introduction to articulate the multifaceted role of EA PGS in more precise terms. For supporting our assertions, we have included references to prior studies (Abdellaoui et al., 2022) [line 131~142].

Abdellaoui, A., Dolan, C. V., Verweij, K. J. H., & Nivard, M. G. (2022). Gene–environment correlations across geographic regions affect genome-wide association studies. Nature Genetics. doi:10.1038/s41588-022-01158-0

• Considering previous work on this topic, including analyses in the ABCD Study, I'm not surprised that the correlation was not very high. Therefore, I don't think it makes a whole of sense to adjust for the schizophrenia PGS in the sensitivity analyses, in other words, it's not really 'a more direct genetic predictor of PLEs'.

We thank the reviewer for the thoughtful comments. We acknowledge that the correlation between schizophrenia PGS and PLE may not be exceedingly high, as evidenced by previous work, including analyses from the ABCD study. However, we would like to emphasize our rationale for adjusting schizophrenia PGS in the sensitivity analyses. Our study design stemmed from the established associations between PLEs and increased risk for schizophrenia. Existing studies have reported significant associations between schizophrenia PGS and cognitive deficits in both psychosis patients (Shafee et al., 2018) and people at risk for psychosis (He et al., 2021). Notable, the PGS for schizophrenia has shown significant associations with PLEs, arguably more so than PGS for PLEs itself (Karcher et al., 2018). Our updated manuscript has incorporated these references to improve clarity. [line 307~309]. By adding this layer of adjustment, we believe that our mixed linear model more precisely examines the relationship between the cognitive phenotype PGS and PLEs, in terms of both sensitivity and specificity.

He, Q., Jantac Mam-Lam-Fook, C., Chaignaud, J., Danset-Alexandre, C., Iftimovici, A., Gradels Hauguel, J., . . . Chaumette, B. (2021). Influence of polygenic risk scores for schizophrenia and resilience on the cognition of individuals at-risk for psychosis. Translational Psychiatry, 11(1). doi:10.1038/s41398-021-01624-z

Karcher, N. R., Paul, S. E., Johnson, E. C., Hatoum, A. S., Baranger, D. A. A., Agrawal, A., . . . Bogdan, R. (2021). Psychotic-like Experiences and Polygenic Liability in the Adolescent Brain Cognitive Development Study. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. doi:https://doi.org/10.1016/j.bpsc.2021.06.012

Shafee, R., Nanda, P., Padmanabhan, J. L., Tandon, N., Alliey-Rodriguez, N., Kalapurakkel, S., . . . Robinson, E. B. (2018). Polygenic risk for schizophrenia and measured domains of cognition in individuals with psychosis and controls. Translational Psychiatry, 8(1). doi:10.1038/s41398-018-0124-8

• How did the FDR correction for multiple testing affect the results?

Please note that we have clarified our FDR correction in the methods

As detailed in the method section [line 254~255], we applied False Discovery Rate (FDR) correction for multiple testing across nine key variables in the study: PGS (CP or EA), family income, parental education, family’s financial adversity, Area Deprivation Index, years of residence, proportion of population below -125% of the poverty line, positive parenting behavior, and positive school environment. An exception was made in our additional sensitivity analysis, where we included schizophrenia PGS in the linear mixed model for adjustment, thus the FDR correction was applied across ten key variables instead. Overall, the application of FDR correction had minimal impact on our findings. Most associations between the key variables and the outcomes that were originally marked as highly significant sustained their significance after the FDR correction.

Overall, I feel that this paper has the potential to present some very interesting findings. However, at the moment the paper misses direction and a clear focus. It would be a great improvement if the readers would be guided through the steps and approach, as I think the authors have undertaken important work and conducted relevant analyses.

We express our appreciation to the reviewer for the positive feedback and constructive suggestions, which only serve to improve and strengthen our manuscript. We have incorporated the suggested corrections and clarifications in response to the reviewer's suggestions. We believe that these changes will not only enhance the overall readability but also more effectively emphasize the significance and implication of our work.

Reviewer #2 (Public Review):

This paper tried to assess the link between genetic and environmental factors on psychotic-like experiences, and the potential mediation through cognitive ability. This study was based on data from the ABCD cohort, including 6,602 children aged 9-10y. The authors report a mediating effect, suggesting that cognitive ability is a key mediating pathway in the link between several genetic and environmental (risk and protective) factors on psychotic-like experiences.

While these findings could be potentially significant, a range of methodological unclarities and ambiguities make it difficult to assess the strength of evidence provided.

Strengths of the methods:

The authors use a wide range of validated (genetic, self- and parent-reported, as well as cognitive) measures in a large dataset with a 2-year follow-up period. The statistical methods have the potential to address key limitations of previous research.

Weaknesses of the methods:

The rationale for the study is not completely clear. Cognitive ability is probably a more likely mediator of traits related to negative symptoms in schizophrenia, rather than positive symptoms (e.g., psychosis, psychotic-like symptom). The suggestion that cognitive ability might lead to psychotic-like symptoms in the general population needs further justification.

We appreciate the reviewer’s concern regarding the role of cognitive ability in relation to schizophrenia symptoms. We are aware that cognitive ability often serves as a mediator of psychotic-like experiences. However, to our best knowledge, a growing body of research has proposed that cognitive ability can mediate positive symptoms in schizophrenia including psychotic-like experiences. The studies by Howes & Murray (2014) and Garety et al. (2001) suggested that deficits in cognitive ability can potentially contribute to the manifestation of positive symptoms such as psychotic-like experiences. We have elaborated on this aspect in the Introduction section [line 104-115].

Howes, O. D., & Murray, R. M. (2014). Schizophrenia: an integrated sociodevelopmental-cognitive model. The Lancet, 383(9929), 1677-1687. doi:https://doi.org/10.1016/S0140-6736(13)62036-X

Garety, P. A., Kuipers, E., Fowler, D., Freeman, D., & Bebbington, P. E. (2001). A cognitive model of the positive symptoms of psychosis. Psychological Medicine, 31(2), 189-195. doi:10.1017/S0033291701003312

Terms are used inconsistently throughout (e.g., cognitive development, cognitive capacity, cognitive intelligence, intelligence, educational attainment...). It is overall not clear what construct exactly the authors investigated.

We thank the reviewer’s feedback regarding the consistency of terminology in our manuscript. Per the suggestion, we standardized the use of ‘cognitive capacity’ and now consistently refer to it as ‘cognitive phenotypes’ throughout our manuscript. Furthermore, we explicitly stated in the Introduction section that our two PGSs of focus will be termed ‘cognitive phenotypes PGSs’, aligning with terminology used in prior studies (Joo et al., 2022; Okbay et al., 2022; Selzam et al., 2019) [line 140~142].

Joo, Y. Y., Cha, J., Freese, J., & Hayes, M. G. (2022). Cognitive Capacity Genome-Wide Polygenic Scores Identify Individuals with Slower Cognitive Decline in Aging. Genes, 13(8), 1320. doi:10.3390/genes13081320

Okbay, A., Wu, Y., Wang, N., Jayashankar, H., Bennett, M., Nehzati, S. M., . . . Young, A. I. (2022). Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals. Nature Genetics, 54(4), 437-449. doi:10.1038/s41588-022-01016-z

Selzam, S., Ritchie, S. J., Pingault, J.-B., Reynolds, C. A., O’Reilly, P. F., & Plomin, R. (2019). Comparing Within- and Between-Family Polygenic Score Prediction. The American Journal of Human Genetics, 105(2), 351-363. doi:https://doi.org/10.1016/j.ajhg.2019.06.006

Not the largest or most recent GWASes were used to generate PGSes.

We appreciate the reviewer’s observation. Indeed, we were unable to utilize the most recent or the largest GWAS for cognitive performance, educational attainment, and schizophrenia due to the timeline of our study. Regrettably, the commencement of our study preceded the publication of the ‘currently’ the largest or most recent GWAS studies by Okbay et al. (2022) and Trubetskoy et al. (2022). Our research was conducted with the best available data at that time, which was the GWAS of European-descent individuals for educational attainment and cognitive performance (Lee et al, 2018). To eliminate any potential confusion, we adjusted the text to specify that our study used 'a GWAS of European-descent individuals for educational attainment and cognitive performance' rather than the largest GWAS [line 206~208].

It is not fully clear how neighbourhood SES was coded (higher or lower values = risk?). The rationale, strengths, and assumptions of the applied methods are not fully clear. It is also not clear how/if variables were combined into latent factors or summed (weighted by what). It is not always clear when genetic and when self-reported ethnicity was used. Some statements might be overly optimistic (e.g., providing unbiased estimates, free even of unmeasured confounding; use of representative data).

Thank you for pointing this out. Consistent with the illustration of neighborhood SES in the Methods, higher values of neighborhood SES indicate risk [line 217~228]. In the original Figure 2, higher value of neighborhood SES links to lower intelligence (direct effects: β=-0.1121) and higher PLEs (indirect effects: β=-0.0126~ -0.0162). We think such confusion might have been caused by the difference between family SES (higher values = lower risk) neighborhood SES (higher values = higher risk). Thus, we changed the terms to ‘High Family SES’ and ‘Low Neighborhood SES’ in the corrected figure (Figure 3) for clarification.

Considering that shorter duration of residence may be associated with instability of residency, it may indicate neighborhood adversity (i.e., higher risk). This definition of the ‘years of residence’ variable is in line with the previous study by Karcher et al. (2021).

During estimation, the IGSCA determines weights of each observed variable in such a way as to maximize the variances of all endogenous indicators and components. We added this explanation in the description about the IGSCA method [line 266~268].

We deleted overly optimistic statements like ‘unbiased estimates’ and used expressions such as ‘adjustment for observed/unobserved confounding’ instead, throughout our manuscript.

Karcher, N. R., Schiffman, J., & Barch, D. M. (2021). Environmental Risk Factors and Psychotic-like Experiences in Children Aged 9–10. Journal of the American Academy of Child & Adolescent Psychiatry, 60(4), 490-500. doi:10.1016/j.jaac.2020.07.003

It appears that citations and references are not always used correctly.

We thoroughly checked all citations and specified the references for each statement: We deleted Plomin & von Stumm (2018) and Harden & Koellinger (2020) and cited relevant primary studies (e.g., Lee et al., 2018; Okbay et al., 2022; Abdellaoui et al., 2022) instead. We also specified the references supporting the statement that educational attainment PGS links to brain morphometry (Judd et al., 2020; Karcher et al., 2021). As Okbay et al. (2022) use PGS of cognitive intelligence (which mentions the analyses results in their supplementary materials) as well as educational attainment, we decided to continue citing this reference [line 131~141].

Strengths of the results:

The authors included a comprehensive array of analyses.

We thank the reviewer for the positive comment.

Weaknesses of the results:

Many results, which are presented in the supplemental materials, are not referenced in the main text and are so comprehensive that it can be difficult to match tables to results. Some of the methodological questions make it challenging to assess the strength of the evidence provided in the results.

As you rightly identified, we inadvertently failed to reference Table S2 in the main text. We have since corrected this omission in the Results section for the IGSCA (SEM) analysis [line 376]. The remainder of the supplementary tables (Table S1, S3~S7) have been appropriately cited in the main manuscript. We recognize that the quantity of tables provided in the supplementary materials is substantial. However, given the comprehensiveness and complexity of our analyses, which encompass a wide array of study variables, these tables offer intricate results from each analysis. We deem these results, which include valuable findings from sensitivity analyses and confound testing, too significant to exclude from the supplementary materials. That said, we are open to, and would greatly welcome, any further suggestions on how to present our supplementary results in a more clear and digestible format. Your guidance in this matter is highly valued.

Appraisal:

The authors suggest that their findings provide evidence for policy reforms (e.g., targeting residential environment, family SES, parenting, and schooling). While this is probably correct, a range of methodological unclarities and ambiguities make it difficult to assess whether the current study provides evidence for that claim.

We believe that with the improvement we made in this revised manuscript, this concern may have been successfully mitigated.

Impact:

The immediate impact is limited given the short follow-up period (2y), possibly concerns for selection bias and attrition in the data, and some methodological concerns.

We appreciate the feedback provided in the reviewer's impact statement. We added as study limitations [line 524~544] that the impact of our findings may be limited due to the relatively short follow-up period, the possibility of sample selection bias, and the problems of interpreting results from an observational study as causality (despite the novel causal inference methods, designed for non-randomized, observational data, that we used).

As responded above (and also in more detail in the Reviewer #2’s Recommendations For The Authors section below), we made necessary corrections and clarifications for the points suggested by the reviewer. As we are willing to make additional revisions, please feel free to give comments if you feel that our corrections are insufficient or inappropriate.

Nevertheless, we would like to discuss some points. We sincerely hope this following response does not come across as argumentative to the reviewer and the editor. We fully understand the reviewer's perspective on this matter, and we agree that the issues raised about the ABCD study are absolutely valid. However, when evaluating the overall impact of a study, other factors, such as how the field has been assessing the impact of similar studies, should also be considered.

Firstly, the potential selection bias and attrition in the ABCD data may not necessarily limit the conclusions of this study. While recognizing the potential issues with the ABCD data is important, we feel that judging the impact of our findings as "limited" based on these issues may not be entirely fair. This is because no study, particularly those of a nationwide scale such as the UK Biobank, IMAGEN, HEAL, HBCD, etc., is completely free of limitations. Typically, the potential limitations of the data don't undermine the impact of individual studies' findings. Numerous studies using ABCD data have been published in top-tier journals—despite the limitations of the ABCD study—underscoring the scientific merit of the findings. For example, the study by Tomasi, D., & Volkow, N. D. (2021), entitled "Associations of family income with cognition and brain structure in USA children: prevention implications," published in Molecular Psychiatry, might be highly relevant to the limitations of the ABCD study raised by the reviewer. The scientific community, including editors, reviewers, and readers, may have appreciated the impact of this study despite the acknowledged limitations of the ABCD data.

Secondly, the two-year time window of our longitudinal analysis might not impact the aim of this study—an iterative assessment of the associations between genetic and environmental variables with cognitive intelligence and mental health, with a focus on PLE, in preadolescents. Had we aimed to test the developmental trajectory from childhood to adolescence, perhaps a longer timeframe would have made more sense. So, we do not agree with the reviewer’s assessment that the short time window limits the impact of our study.

Suggested revisions based on the combined reviewer feedback:

1) The terminology used should be carefully reviewed and revised

• Please use the correct terminology for the key concepts assessed in this study. For example, authors sometimes conflate PLEs and psychosis, two related but separate constructs. Furthermore, the terms 'good parenting' and 'good schooling' are vague and subjective.

• The authors use multiple terms to refer to cognitive ability (cognitive capacity, intelligence, cognitive intelligence, etc). The term 'cognitive development' in the title and manuscript does not seem to be justified given the focus on different measures of cognitive ability at a single time point (i.e. baseline).

• Please avoid causal language and using statements that cannot be entirely substantiated (e.g. unbiased estimates, free from unmeasured confounding)

Thank you for suggesting this point. We revised all key terminologies used throughout our manuscript.

Per your suggestion, we specified that PLEs indicate the risk of psychosis and often precede schizophrenia. We checked all misused cases of the term ‘psychosis’ and corrected them as ‘PLEs’. We also changed the terms 'good parenting' and 'good schooling' to ‘positive parenting behavior’ and ‘positive school environment’.

We changed the term ‘cognitive development’ to ‘cognitive ability’ throughout our manuscript. We also changed the title to ‘Gene-Environment Pathways to Cognitive Intelligence and Psychotic-Like Experiences in Children’ because we used ‘cognitive intelligence’ for NIH toolbox variable in the text.

We corrected and tone-downed all causal languages used in our manuscript. As mentioned by the reviewers, we deleted statements like ‘unbiased estimates’ and used expressions such as ‘adjustment for observed/unobserved confounding’ instead.

2) A stronger rationale for the focus on PLEs, and the potential mediating role of cognitive ability in genetic and environmental effects on PLES, should be provided

We appreciate the raised concerns that cognitive ability may serve as a mediator of psychotic-like experiences. To our best knowledge, it has been proposed that cognitive ability can be a mediator of positive symptoms in schizophrenia (including psychotic-like experiences), as well as negative symptoms. This mediating role of cognitive ability was proposed in several prior studies on cognitive model of schizophrenia/psychosis. Per your suggestion, we included an additional justification in Intro [line 104~115] where we highlighted that cognitive ability has been proposed as a potential mediator of genetic and environmental influence on positive symptoms of schizophrenia such as psychotic-like experiences. We refer to studies conducted by Howes & Murray (2014) and Garety et al. (2001).

Howes, O. D., & Murray, R. M. (2014). Schizophrenia: an integrated sociodevelopmental-cognitive model. The Lancet, 383(9929), 1677-1687. doi:https://doi.org/10.1016/S0140-6736(13)62036-X

Garety, P. A., Kuipers, E., Fowler, D., Freeman, D., & Bebbington, P. E. (2001). A cognitive model of the positive symptoms of psychosis. Psychological Medicine, 31(2), 189-195. doi:10.1017/S0033291701003312

3) As described in more detail by the reviewers, more information should be provided about the measures used in the study and how they relate to one another (e.g. correlations between PQ-BC and CBCL; PGS-CA and PGS-EA).

Thank you for your suggestion. Although this information was already provided in our initial submission, it appears that the Reviewer #1’s might have referred to the prior version of our manuscript submitted elsewhere before eLife.

To clarify, our findings reveal significant Pearson’s correlation coefficients between PLEs across all time-points (baseline year: r=0.095~0.0989, p<0.0001; 1-year follow-up: r=0.1322~0.1327, p<0.0001; 2-year follow-up: r= 0.1569~0.1632, p<0.0001) and we added this information in the Method section [line 198~200]. We also added the Pearson’s correlation between the two PGSs (r=0.4331, p<0.0001) in the Methods for PGS [line 214].

4) More details are needed regarding the analytical strategies used (e.g. how imputation was performed, why PGS were not based on the largest and most recent GWASes, whether latent or observed variables were examined, what exactly the supplementary materials show and how they relate to information provided in the main text).

We appreciate your feedback. We acknowledge the concerns about the GWAS sources utilized for the study. Unfortunately, our study commenced prior to the publication of the ‘currently’ most recent or largest GWAS by Okbay et al. (2022) and Trubetskoy et al. (2022). Our research was conducted with the best available data at that time, which was the largest GWAS of European-descent individuals for educational attainment and cognitive performance (Lee et al, 2018). We have now clarified this point in the manuscript. [line 206~208]

Also, we specified the use of composite indicators for the PGS, family SES, neighborhood SES, positive family and school environment, and PLEs, while latent factors were used for cognitive intelligence [line 269~285].

We highly appreciate the reviewer’s comments regarding the supplementary materials. We regret overlooking the citation of Table S2 in the main manuscript, and this has now been rectified in the Results section for the IGSCA (SEM) analysis [line 376]. The remaining supplementary tables (Table S1, S3~S7) have been correctly referenced within the manuscript. We acknowledge that the supplementary materials are extensive due to the comprehensive array of study variables and intricate results from each analysis. However, given that our analyses encompass a wide array of study variables, these tables offer intricate results from each analysis. We deem these results, which include valuable findings from sensitivity analyses and confound testing, too crucial to exclude from the supplementary materials. That said, we are open to any further suggestions to make our supplementary results more accessible and digestible. In order to improve the accessibility and clarity of our presentation, we are fully committed to making any necessary changes and look forward to any further recommendations.

5) The limitation section should be expanded and statements regarding the implications of the study findings should be qualified accordingly (e.g. short follow-up period, potential for attrition and selection bias, reverse causation, etc)

We specified additional potential constraints of our study, including limited representativeness, limited periods of follow-up data (baseline year, 1-year, and 2-year follow-up), possible sample selection bias, and the use of non-randomized, observational data [line 524~544].

6) Please ensure that the references provided support the statements in the text to which they are linked to.

Thank you for pointing this out. We thoroughly went over all citations and corrected the inaccurately or vaguely cited references for each statement.

Reviewer #2 (Recommendations For The Authors):

1) Please use terms consistently and correctly. E.g., 'cognitive capacity' is not the same as 'educational attainment'.

We thank the reviewer’s feedback regarding the consistency of terminology in our manuscript. Per the suggestion, we standardized the use of ‘cognitive capacity’ and now consistently refer to it as ‘cognitive phenotypes’ throughout our manuscript. Furthermore, we explicitly stated in the Introduction section that our two PGSs of focus will be termed ‘cognitive phenotypes PGSs’, aligning with terminology used in prior studies (Joo et al., 2022; Okbay et al., 2022; Selzam et al., 2019) [line 140~142].

Joo, Y. Y., Cha, J., Freese, J., & Hayes, M. G. (2022). Cognitive Capacity Genome-Wide Polygenic Scores Identify Individuals with Slower Cognitive Decline in Aging. Genes, 13(8), 1320. doi:10.3390/genes13081320

Okbay, A., Wu, Y., Wang, N., Jayashankar, H., Bennett, M., Nehzati, S. M., . . . Young, A. I. (2022). Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals. Nature Genetics, 54(4), 437-449. doi:10.1038/s41588-022-01016-z

Selzam, S., Ritchie, S. J., Pingault, J.-B., Reynolds, C. A., O’Reilly, P. F., & Plomin, R. (2019). Comparing Within- and Between-Family Polygenic Score Prediction. The American Journal of Human Genetics, 105(2), 351-363. doi:https://doi.org/10.1016/j.ajhg.2019.06.006

2) The authors study 'cognitive performance using seven instruments', but it is not clear how fluid and crystalline intelligence was defined/operationalized.

Thank you for pointing this out. We specified the NIH Toolbox tests used for composite scores of fluid and crystallized intelligence, respectively. “We utilized baseline observations of uncorrected composite scores of fluid intelligence (Dimensional Change Card Sort Task, Flanker Test, Picture Sequence Memory Test, List Sorting Working Memory Test), crystallized intelligence (Picture Vocabulary Task and Oral Reading Recognition Test), and total intelligence (all seven instruments) provided in the ABCD Study dataset” [line 180~187].

3) I don't think Lee 2018 is the largest GWAS for educational attainment. That would be Okbay 2022. It needs to be described how cognitive performance was defined in Lee 2018. Why did the authors not use the Trubetskoy 2022 schizophrenia GWAS?

Thank you for mentioning this point. The reason why we were not able to use the largest GWAS for CP, EA and schizophrenia is because (unfortunately) our study started earlier than the point when the GWAS studies by Okbay et al. (2022) and Trubetskoy et al. (2022) were published. We corrected that our study used ‘a GWAS of European-descent individuals for educational attainment and cognitive performance’ instead of the largest GWAS [line 206~208].

4) It is unclear how neighbourhood SES was coded. The authors seem to suggest that higher values indicate risk, but Figure 2 suggests that higher values links to higher intelligence and lower PLE.

Thank you very much for pointing this out. Consistent with the illustration of neighborhood SES in the Methods section, higher values of neighborhood SES indicate risk. In the original Figure 2, higher values of neighborhood SES links to lower intelligence (direct effects: β=-0.1121) and higher PLEs (indirect effects: β=-0.0126~-0.0162). We think such confusion might have been caused by the difference between family SES (higher values = lower risk) neighborhood SES (higher values = higher risk). Thus, we changed the terms to ‘High Family SES’ and ‘Low Neighborhood SES’ in the corrected figure (Figure 3) for clarification.

5) Also, the 'year of residence' variable is unclearly defined. Does this mean that a shorter duration of residency (even in a good neighbourhood) indicate risk?

Thank you for mentioning this point. Considering that shorter duration of residence may be associated with instability of residency, it may indicate neighborhood adversity (i.e., higher risk). This definition of the ‘years of residence’ variable is in line with the previous study by Karcher et al. (2021).

Karcher, N. R., Schiffman, J., & Barch, D. M. (2021). Environmental Risk Factors and Psychotic-like Experiences in Children Aged 9–10. Journal of the American Academy of Child & Adolescent Psychiatry, 60(4), 490-500. doi:10.1016/j.jaac.2020.07.003

6) Please provide information on how correlated the two PGSes were.

Thank you for your suggestion. We added the Pearson’s correlation between the two PGSs (r=0.4331, p<0.0001) in the Methods section for PGS [line 214].

7) Information on the outcome variable in the 'linear mixed models' section is missing. I assumed it was PLE.

Thank you for notifying us of this point. We added the information on the outcome variables in the section for linear mixed models [line 242~244].

8) In the 'Path Modeling' section, please explain what 'factors and components' concretely refer to. How is this different from a standard SEM with latent factors?

Thank you for your comment on the need to elaborate the IGSCA method. We added that different from standard SEM methods which only uses latent factors, the IGSCA method can use components as well as latent factors as constructs in model estimation. This allows the IGSCA method to control bias more effectively in estimation compared to the standard SEM [line 261~268].

9) The sentence starting line 229 is unclear. Does this mean variables were not used to generate latent factors. And if not, what weights were used to create a 'weighted sum'?

Thank you for mentioning this point. The sentence means that we treated PGSs, family SES, neighborhood SES, positive family and school environment, and PLEs as composite indicators (derived from a weighted sum of relevant observed variables), while general intelligence was represented as a latent factor.

It has been suggested from prior studies that these variables (PGSs, family SES, neighborhood SES, positive family and school environment, and PLEs) are less likely to share a common factor and were assessed as a composite index during analyses. For instance, Judd et al. (2020) and Martin et al. (2015) analyze genetic influence of educational attainment and ADHD as composite indicators. Also, as mentioned in Judd et al. (2020), socioenvironmental influences are often analyzed as composite indicators. Studies on psychosis continuum (e.g., van Os et al., 2009) suggest that psychotic disorders are likely to have multiple background factors instead of having a common factor, and notes that numerous prior research uses composite indices to measure psychotic symptoms. Based on this literature, we used components for these variables.

The IGSCA determines weights of each observed variable to maximize the variances of the endogenous indicators and components [added in line 265~268].

On the other hand, we treated general intelligence as a latent factor/variable underlying fluid and crystallized intelligence. This is based on the extensive literature of classical g theory of intelligence [added in line 269~284].

Judd, N., Sauce, B., Wiedenhoeft, J., Tromp, J., Chaarani, B., Schliep, A., ... & Klingberg, T. (2020). Cognitive and brain development is independently influenced by socioeconomic status and polygenic scores for educational attainment. Proceedings of the National Academy of Sciences, 117(22), 12411-12418.

Martin, J., Hamshere, M. L., Stergiakouli, E., O'Donovan, M. C., & Thapar, A. (2015). Neurocognitive abilities in the general population and composite genetic risk scores for attention‐deficit hyperactivity disorder. Journal of Child Psychology and Psychiatry, 56(6), 648-656.

van Os, J., Linscott, R., Myin-Germeys, I., Delespaul, P., & Krabbendam, L. (2009). A systematic review and meta-analysis of the psychosis continuum: Evidence for a psychosis proneness–persistence–impairment model of psychotic disorder. Psychological Medicine, 39(2), 179-195. doi:10.1017/S0033291708003814

10) It is overall not clear when genetically and when self-reported information of ethnicity was used. This needs to be clearer throughout.

Thank you for mentioning this point. We only used genetically defined ethnicity, and we have not mentioned that we used self-reported ethnicity. Per your suggestion, we clarified that we used ‘genetic ethnicity’ throughout the paper.

11) The sentence starting line 253 is also unclear. How is schizophrenia PGS a 'more direct genetic predictor of PLE' and compared to what other measure?

Thank you for pointing this out. Please note that our adjustment (or sensitivity analyses) was based on the reported associations between PLEs and the risk for schizophrenia: schizophrenia PGS is associated with a cognitive deficit in psychosis patients (Shafee et al., 2018) and individuals at-risk of psychosis (He et al., 2021), and psychotic-like experiences (more so than PGS for psychotic-like experiences) (Karcher et al., 2018). We added these references for clarification [line 307~309]. We believe that because of the adjustment our results from the mixed linear model show the sensitivity and specificity of the association between cognitive phenotype PGS and PLEs.

He, Q., Jantac Mam-Lam-Fook, C., Chaignaud, J., Danset-Alexandre, C., Iftimovici, A., Gradels Hauguel, J., . . . Chaumette, B. (2021). Influence of polygenic risk scores for schizophrenia and resilience on the cognition of individuals at-risk for psychosis. Translational Psychiatry, 11(1). doi:10.1038/s41398-021-01624-z

Karcher, N. R., Paul, S. E., Johnson, E. C., Hatoum, A. S., Baranger, D. A. A., Agrawal, A., . . . Bogdan, R. (2021). Psychotic-like Experiences and Polygenic Liability in the Adolescent Brain Cognitive Development Study. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. doi:https://doi.org/10.1016/j.bpsc.2021.06.012

Shafee, R., Nanda, P., Padmanabhan, J. L., Tandon, N., Alliey-Rodriguez, N., Kalapurakkel, S., . . . Robinson, E. B. (2018). Polygenic risk for schizophrenia and measured domains of cognition in individuals with psychosis and controls. Translational Psychiatry, 8(1). doi:10.1038/s41398-018-0124-8

12) Please include a statement on the assumptions made when using the method used in this study and developed by Miao 2022, explain what evidence you have to support these assumptions and how this method, which I believe was developed for RCTs, can be applied to observational data.

We specified the assumptions for the causal inference method proposed by Miao et al. (2022) and why it is applicable to our study. Also, we noted that this novel method was developed to identify the causal effects of multiple treatment variables within non-randomized, observational data [line 309~319].

13) Some of the statements are potentially misleading. E.g., I would be very cautious to claim that the methods applied allowed the authors to estimate 'unbiased associations again potential (even unobserved) confounding variables'. There are many concerns such as selection bias, attrition, reverse causation, genetic confounding, etc that cannot be addressed satisfactorily using these data and methods.

Thank you for pointing this out. We deleted statements like ‘unbiased estimates’ and used expressions such as ‘adjustment for observed/unobserved confounding’ instead.

Nevertheless, please note that due to some limitations in the data (e.g., confounders), an analytic approach should be robust enough to handle potential violations of assumptions. This was the point we wanted to emphasize--In contrast to the majority of studies using the ABCD study, which employ simplistic GLM or conventional SEM with only latent variable modeling, our study provides less biased, thus more accurate, estimates through the use of sophisticated modeling for confounding effects (instead of simplistic GLM) and IGSCA (instead of conventional simplistic SEM). We hope our study may help improve our analytical approach in this field.

14) I would be equally cautious to claim that the ABCD study is representative. Please add information on the whole ABCD cohort to Table 1 and describe any relevance with respect to attrition effects or representativeness.

Thank you for highlighting this issue. We previously characterized the ABCD Study as representative of the US population, given its aim to ensure representativeness by recruiting from a broad range of school systems located near each of its 21 research sites, chosen for their geographic, demographic, and socioeconomic diversity. Using epidemiological strategies, a stratified probability sample of schools was selected for each site. This procedure took into account sex, race/ethnicity, socioeconomic status, and urbanicity to reduce potential sampling biases at the school level. Based on these strategies, previous research (e.g., Thompson et al., 2019; Zucker et al., 2018) has referred to the ABCD Study as ‘representative.’ However, we overlooked the fact that “not all 9-year-old and 10-year-old children in the United States had an equal chance of being invited to participate in the study,” and therefore, it should not be deemed fully representative of the US population (Compton et al., 2019). Heeding your suggestion, we have removed all descriptions of the ABCD Study being representative.

Compton, W. M., Dowling, G. J., & Garavan, H. (2019). Ensuring the Best Use of Data: The Adolescent Brain Cognitive Development Study. JAMA Pediatrics, 173(9), 809-810. doi:10.1001/jamapediatrics.2019.2081

Thompson, W. K., Barch, D. M., Bjork, J. M., Gonzalez, R., Nagel, B. J., Nixon, S. J., & Luciana, M. (2019). The structure of cognition in 9 and 10 year-old children and associations with problem behaviors: Findings from the ABCD study’s baseline neurocognitive battery. Developmental Cognitive Neuroscience, 36, 100606. doi:10.1016/j.dcn.2018.12.004

Zucker, R. A., Gonzalez, R., Feldstein Ewing, S. W., Paulus, M. P., Arroyo, J., Fuligni, A., . . . Wills, T. (2018). Assessment of culture and environment in the Adolescent Brain and Cognitive Development Study: Rationale, description of measures, and early data. Developmental Cognitive Neuroscience, 32, 107-120. doi:https://doi.org/10.1016/j.dcn.2018.03.004

15) The imputation methods need to be explained in more detail / more clearly. What concrete variables were included? Why was 50% of the sample excluded despite imputation? How similar is the study sample to the overall ABCD cohort - and to the US population in general (i.e., is this a representative dataset)?

Thank you for mentioning this point. We clarified the method and detailed processes of the imputation (e.g., R package VIM, number of missing observations for each study variables such as genotypes, follow-up observations, and positive environment) [Methods; line 167~176].

The final samples had significantly higher cognitive intelligence, parental education, family income, and family history of psychiatric disorders, lower Area Deprivation Index, percentage of individuals below -125% of the poverty level, and family’s financial adversity (p<0.05). As you have noted above, these results also show the limited representativeness of the data used in our study. We fully acknowledge that our study sample, as well as the overall ABCD cohort, is not representative of the US population in general.

16) There are a range of unclear statements (e.g., 'Supportive parenting and a positive school environment had the largest total impact on PLEs than genetic or environmental factors' - isn't parenting an environmental factor?).

Thank you for mentioning this point. We clarified seemingly vague expressions and unclear statements. We corrected the sentence you noted as ‘Supportive parenting and a positive school environment had the largest total impact on PLEs than any other genetic or environmental factors’ [line 57~58].

17) The authors' conclusion (that these findings have policy implications for improving school and family environmental) are not fully supported by the evidence. E.g., genetic effects were equally large.

Thank you for pointing this out. Our description should be clearer. Our models consistently show that the combined environmental effects of positive family/school environment, and family/neighborhood SES exceeds the genetic effects. We suggest that these findings may have policy implications for “improving the school and family environment and promoting local economic development” [line 62~64].

To clarify, we newly added “Despite the undeniable genetic influence on PLEs, when we combine the total effect sizes of neighborhood and family SES, as well as positive school environment and parenting behavior (∑▒〖|β|〗=0.2718~0.3242), they considerably surpass the total effect sizes of cognitive phenotypes PGSs (|β|=0.0359~0.0502)” [line 510~513]. Based on these results, we suggest that our findings hold potential policy implications for “preventative strategies that target residential environment, family SES, parenting, and schooling—a comprehensive approach that considers the entire ecosystem of children's lives—to enhance children's cognitive ability and mental health” in the Discussion [line 507~510].

Admittedly, our results do not directly demonstrate a causal effect wherein an intervention in the school or family environmental variables would necessarily lead to a significantly meaningful positive impact on a child's cognitive intelligence and mental health. We do not make such a claim in this paper. However, we anticipate that further integrative analyses akin to ours might help identify potential causal or prescriptive effects. We hope this perspective will be recognized as one of the contributions of our study. We leave the final decision to the discerning judgment of the editors and reviewers.

18) Many citations do not support the statements made and are sometimes used rather vaguely. For example, I believe Judd 2020 and Okbay 2022 did not use a PGS of cognitive capacity, but of educational attainment. Plomin 2018 and Harden 2020 are reviews, but the primary studies should be cited instead. Which reference exactly is supporting the statement that cognitive capacity PGS links to brain morphometry?

Thank you very much for your precise observations. We thoroughly checked all citations and updated the references for each statement.

We deleted Plomin & von Stumm (2018) and Harden & Koellinger (2020) and cited relevant original research articles (e.g., Lee et al., 2018; Okbay et al., 2022; Abdellaoui et al., 2022) instead. We also specified the references supporting the statement that educational attainment PGS links to brain morphometry (Judd et al., 2020; Karcher et al., 2021). As Okbay et al. (2022) used the PGS of cognitive intelligence (which presented the analyses results in their supplementary materials) as well as educational attainment, we decided to continue citing this reference [line 131~141].

19) Citations are formatted inconsistently.

We apologize for the inconsistency of the citation formatting. We formatted all citations in APA 7th style, using EndNote v20. We checked that all citations maintain consistency according to the reference style.

20) Re line 281, I believe effect sizes are 'up to twice as large', but not consistently twice as large as suggested in the text.

Thank you for mentioning this point. We corrected the sentence as ‘The effect sizes of EA PGS on children's PLEs were larger than those of CP PGS’ [line 342~343].

21) Please add to the results a short statement on what covariates these analyses were controlled for.

Thank you for giving us this comment. We added that we used sex, age, marital status, BMI, family history of psychiatric disorders, and ABCD research sites as covariates in the Results section [line 329~331].

22) Cho 2020 does not provide recommendations on FIT values (line 315). Please provide another reference and explain how these FIT values should be interpreted.

Thank you for mentioning this point. We added the correct reference for FIT values (Hwang, Cho, & Choo, 2021). We also added that the FIT values range from 0 to 1, and a larger FIT value indicates more variance of all variables is explained by the specified model (e.g., FIT=0.50 denotes that the model explains 50% of the total variance of all variables) [line 291~293].

23) Regarding Figure 2, please add factor loadings to this figure and explain what the difference between the hexagon and circular shapes are. Please also add the autocorrelations between the 3 PLE measures. I assume these were also modelled statistically, given the strong correlations between time points?

Figure 2B needs reworking.

It is unclear what the x-axis of Figure 2C represents. Proportion of R2 or effect size? SM table 2 provides key information, which should be added to Figure 2.

Thank you for pointing this out. We added factor loadings to the corrected figure (Figure 3A and 3B). We also added that the X-axis of Figure 3C represents standardized effect sizes.

24) I suggest adding units directly to Table 1, not in the legend. Was genetic or self-reported ethnicity used in this table? List age in years, not months?

Thank you for your suggestion. We added the units of age and family history of psychiatric disorders directly inside Table 1. We used genetic ethnicity in Table 1, as we only used genetic ethnicity (but not self-reported ethnicity) throughout our study. This is noted on the last row of Table 1. We listed age in chronological months, which is how each child’s age at each point of data collection is coded in the ABCD Study.

25) Please include exact p-values in Table 2.

Thank you for your suggestion. We highly appreciate the reviewer’s comment on the importance of showing exact p-values in the analysis results. Unfortunately, we cannot estimate the standard errors based on normal-theory approximations to obtain the exact p-values of our IGSCA model results. This is described in detail in the original paper of the IGSCA method (Hwang et al., 2021): “Like GSCA and GSCAM, IGSCA is also a nonparametric or distribution-free approach in the sense that it estimates parameters without recourse to distributional assumptions such as multivariate normality of indicators. As a trade-off of no reliance on distributional assumptions, it cannot estimate the standard errors of parameter estimates based on asymptotic (normal-theory) approximations. Instead, it utilizes the bootstrap method (Efron, 1979, 1982) to obtain the standard errors or confidence intervals of parameter estimates nonparametrically.”

Efron, B. (1979). Bootstrap methods: Another look at the jackknife. Annals of Statistics, 7, 1–26. http://dx.doi.org/10.1214/aos/1176344552

Efron, B. (1982). The jackknife, the bootstrap and other resampling plans. Philadelphia, PA: SIAM. http://dx.doi.org/10.1137/1.9781611970319

Hwang, H., Cho, G., Jung, K., Falk, C. F., Flake, J. K., Jin, M. J., & Lee, S. H. (2021). An approach to structural equation modeling with both factors and components: Integrated generalized structured component analysis. Psychological Methods, 26(3), 273-294. doi:10.1037/met0000336

26) There are way too many indigestible tables presented in the supplementary materials, which are also not referenced in the main manuscript.

We appreciate your insightful observation. As you rightly identified, we inadvertently failed to reference Table S2 in the main text. We have since corrected this omission in the Results section for the IGSCA (SEM) analysis [line 376]. The remainder of the supplementary tables (Table S1, S3~S7) have been appropriately cited in the main manuscript. We recognize that the quantity of tables provided in the supplementary materials is substantial. However, given the comprehensiveness and complexity of our analyses, these tables offer intricate results from each analysis. We deem these results, which include valuable findings from sensitivity analyses and confound testing, too significant to exclude from the supplementary materials. That said, we are open to, and would greatly welcome, any further suggestions to ensure clarity and ease of comprehension. Your guidance in this matter is highly valued.

27) Figure S1 is unclear, possibly due to the journal formatting. Is this one figure presented on two pages? Clarify which PGS is listed in Figure S1 and in any case, please add both PGSs.

Thank you for mentioning this point. Figure S1 presents two correlation matrices: the first one is the correlation matrix of component / factor variables in the IGSCA model and the second one is the that of observed variables used to construct the relevant component / factor variables in the IGSCA model. We noted each matrix as Figure S1-A and Figure S1-B. We also corrected the figure legend as “A. Correlation between all component / factor variables of the IGSCA model. B. Correlation between all observed variables used to construct the relevant component / factor variables in the IGSCA model.” Since Figure S1-A presents correlations between the components and latent factors, it lists a single PGS variable constructed from the CP PGS and EA PGS. On the other hand, Figure S1-B presents correlations between the observed variables. Thus, both CP PGS and EA PGS are listed in this correlation matrix.

Author Response

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

eLife assessment

This important study expands on current knowledge of allosteric diversity in the human kinome by C-terminal splicing variants using as a paradigm DCLK1. The authors provide solid evolutionary and some mechanistic evidence how C-terminal isoform specific variants generated by alternative splicing can regulate catalytic activity by means of coupling specific phosphorylation sites to dynamical and conformational changes controlling active site and substrate pocket occupancy, as well as protein-protein interactions. The data will be of interest to researchers in the kinase and signal transduction field.

We thank the editor for coordinating the review of our manuscript and the reviewers for their valuable feedback. We have significantly revised the manuscript in response to the reviewer’s comments. Our point-by-point response to each comment is present below. We have uploaded both a clean draft of our revised manuscript as well as a version with the revisions highlighted in yellow. We hope the revised manuscript is now acceptable for publication in eLife. We have additionally updated the preprint on bioRxiv and have included the link: We thank the editor for coordinating the review of our manuscript and the reviewers for their valuable feedback. We have significantly revised the manuscript in response to the reviewer’s comments. Our point-by-point response to each comment is present below. We have uploaded both a clean draft of our revised manuscript as well as a version with the revisions highlighted in yellow. We hope the revised manuscript is now acceptable for publication in eLife. We have additionally updated the preprint on biorxiv and have included the link here: https://www.biorxiv.org/content/10.1101/2023.03.29.534689v2.

Reviewer #1

Summary

In the study by Venkat et al. the authors expand the current knowledge of allosteric diversity in the human kinome by c-terminal splicing variants using as a paradigm DCLK1. In this work, the authors provide evolutionary and some mechanistic evidence about how c-terminal isoform specific variants generated by alternative splicing can regulate catalytic activity by means of coupling specific phosphorylation sites to dynamical and conformational changes controlling active site and substrate pocket occupancy, as well as interfering with protein-protein interacting interfaces that altogether provides evidence of c-terminal isoform specific regulation of the catalytic activity in protein kinases.

The paper is overall well written, the rationale and the fundamental questions are clear and well explained, the evolutionary and MD analyses are very detailed and well explained. The methodology applied in terms of the biochemical and biophysical tools falls a bit short in some places and some comments and suggestions are given in this respect. If the authors could monitor somehow protein auto-phosphorylation as a functional readout would be very useful by means of using phospho-specific antibodies to monitor activity. Overall I think this is a study that brings some new aspects and concepts that are important for the protein kinase field, in particular the allosteric regulation of the catalytic core by c-terminal segments, and how evolutionary cues generate more sophisticated mechanisms of allosteric control in protein kinases. However a revision would be recommended.

Major Comments

The authors explain in the introduction the role of T688 autophosphorylation site in the function of DCLK1.2. This site when phosphorylated have a detrimental impact on catalytic activity and inhibits phosphorylation of the DCX domain. allowing the interaction with microtubules. In the paper they show how this site is generated by alternative splicing and intron skipping in DCLK1.2. However there is no further functional evidence along the functional experiments presented in this study.

1) What is the effect of a non-phosphorylable T688 mutant in terms of stability and enzymatic activity? What would be the impact of this mutant in the overall auto-phosphorylation reaction?

The role of T688 phosphorylation on DCLK1 functions has been explored in previous studies (Agulto et al, 2020: PMID: 34310279), although only relevant to DCLK1.2 splice variants, since this site is lacking in DCLK1.1. These studies showed that mutation of T688 to an alanine increases total kinase autophosphorylation (ie autoactivity) and the subsequent phosphorylation of DCX domains, which in turn decreases microtubule binding. Given this information, our goal was to use an evolutionary perspective to investigate this, alongside less-well characterized aspects of DCLK autoregulation, including co-conserved residues in the catalytic domain and C-terminal tail. However, to address the reviewers question of a non-phosphorylatable T688 mutant, we performed MD simulations of T688A and T688E (a phosphomimic) mutant and include a new supplementary figure (Figure 5-supplement 3) which show the two mutants slightly destabilize the C-tail relative to wt (1 and 2 angstrom increase in RMSF for T688E and T688A respectively), but by themselves cannot dislodge the C-tail from the ATP binding pocket. Thus, other co-conserved interactions as revealed by our analysis, are likely to contribute to the autoregulation of the kinase domain by the C-terminal tail. We have incorporated these observations into the revised results section.

Furthermore, to address the reviewer’s question in terms of site-specific autophosphorylation as a marker of DCLK1.2 activity, we have now performed a much-more detailed phosphoproteomic analysis of a panel of purified DCLK1.2 proteins after purification from E.coli (Figure 8-figure supplement 2). This showed that we are only able to detect Thr 688 phosphorylated in our ‘activated’ DCLK1.2 mutants, and not in the autoinhibited WT DCLK1.2 version of the protein. This apparent contradiction does not necessary discount Thr 688 as an important regulatory hotspot, but, together with the MD simulations, may imply a decreased contribution of pThr 688 in facilitating/maintaining DCLK1.2 auto-inhibition than previously anticipated, especially in the context of the numerous other stabilizing amino acid contacts that we describe between the C-tail and the ATP-binding pocket. We do, however, propose a mechanism for pThr688 as a potential ATP mimic based on MD analysis. However, we only found MS-based evidence for phosphorylation at this (and other sites in the same peptide) in highly active DCLK1.2 mutants, in which the C-tail remains uncoupled from the ATP-binding site, even in the presence of this regulatory PTM. We acknowledge that better understanding of DCLK biology will require a detailed appraisal of how the DCLK auto-inhibited states are subsequently physiologically regulated (PTMs, protein-protein interaction etc.), but this is beyond the scope of our current evolutionary investigation, and the absence of phosphospecific antibodies makes this challenging currently. We intend to expand upon our current work by assessing the relative contribution of multiple DCLK phosphorylation sites (including, but not limited to, Thr 688) with regard to cellular DCLK auto-regulation in future studies, in part by generating such site-specific phospho-antibodies.

2) Have the authors made an equivalent T687/688 tanden in DCLK1.1 instead of the two prolines?

This is a good point. We have not considered introducing a T687/688 tandem mutation into DCLK1.1 (at the equivalent position to that of DCLK1.2), primarily because the amino acid composition of their respective C-tail domains are so highly divergent across the tail (due to alternative splicing, as discussed in our paper). As discussed in our present study, there are numerous contacts made between specific amino acids in the regulatory C-tail and the kinase domain of DCLK1.2, which functionally occlude ATP binding, and thus change catalytic output. It is these contacts, which are determined by the specific amino acid sequence identity, and not the extended length of the DCLK1.2 C-tail per se, that drives autoinhibition. The alternate amino acid sequence identity of the C-tail of DCLK1.1 does not enable such contacts to form, which we believe explains the different activities of the two isoforms.

Furthermore, our mutational analysis reveals clearly that Thr688 and several other sites are more highly autophosphorylated in the artificially activated DCLK1.2 constructs than WT DCLK1.2, and as such it remains our hypothesis that introduction of the tandem phosphorylation sites into DCLK1.1 is unlikely to be sufficient to impose an auto-inhibitory conformation of the enzyme.

3) Could T688 autophosphorylation be used as a functional readout to evaluate DCLK1.2 activity?

We agree with the reviewer’s suggestion about using autophosphorylation (including potentially Thr688 for DCLK1.2) as a functional read out for DCLK1 activity. In our present study, we identify phosphorylated peptides containing pThr688 only in the mutationally activated DCLK1.2 variants. We have now taken this analytical approach further and performed a detailed comparative phosphoproteomic characterisation of all of our DCLK1 constructs, where we observe marked differences in the overall phosphorylation profiles of the mutant DCLK1.2 (and DCLK1.1) proteins relative to the less phosphorylated WT DCLK1.2 kinase. This manifests as a depletion in the total number of confidently assigned phosphorylation sites within the kinase domain and C-tail of WT DCLK1.2, and also as a depletion in the abundance of phosphorylated peptides for a given site. To help visualise this, individual phosphorylation sites have been schematically mapped onto DCLK1, which has been included as a new extended supplementary figure (Figure 8-figure supplement 2). For comparative analysis of phosphosite abundance, we could only select peptides that could be directly compared between all mutants (identical amino acid sequences) and those found to be phosphorylated in all proteins (these are Ser660 and Thr438); these are now shown in figure supplement 2 as a table. These site occupancies follow what we see with respect to the increased catalytic activity between DCLK1.1 and DCLK1.2 mutants versus DCLK1.2. We also detect increased phosphorylation of DCLK1.1 and activated DCLK1.2 mutants in comparison to (autoinhibited) DCLK1.2, supporting the hypothesis that these mutants are relieving the autoinhibited conformation.

4) What are the evidences of the here described c-terminal specific interactions to be intra-molecular rather than inter-molecular? Have the authors looked at the monodispersion and molecular mass in solution of the different protein evaluated in this study? Basically, are the proteins in solutions monomers or dimers/oligomers?

Analysis of symmetry mates in the crystal structure of DCLK1.2 (PDB ID: 6KYQ) provide no evidence for inter-molecular interactions. Furthermore, to evaluate oligomerization status in solution, we conducted an analytical size exclusion chromatography (SEC) and our analysis reveals that both DCLK1.1 and DCLK1.2 predominantly exist as monomers in solution (Figure 3-Supplements 1-3). These results suggest that the C-terminal tail interactions are primarily intra-molecular.

5) (Figure 3) Did the authors look at the mono-dispersion of the protein preparation? The sec profile did result in one single peak or multiple peaks? Could the authors show the chromatogram? how many species do you have in solution? Was the tag removed from the recombinant proteins or not?

Yes, as mentioned above, the SEC profile resulted in a single peak for both DCLK1.1 and DCLK1.2, which was confirmed as DCLK1 by subsequent SDS-PAGE. We have included the chromatogram and gels in supporting data (Figure 3-supplements 1-3) in the revised manuscript and updated the Methods section. ‘The short N-terminal 6-His affinity tag present on all other DCLK1 proteins described in this paper was left in situ on recombinant proteins, since it does not appear to interfere with DSF, biochemical interactions or catalysis.’

6) Authors should do Michaelis-Menten saturation kinetics as shown in Figure 3C with the WT when comparing all the functional variant analysed in the study. So we can compared the catalytic rates and enzymatic constants (depicted in a table also) kcat, Km and catalytic efficiency constants (kcat/Km)

Thank you for your suggestion. We have performed the requested comparative kinetics analyses for selected functional DCLK1 variants at the same concentration as suggested, using our real-time assay to determine Vmax for peptide phosphorylation as a function of ATP, but at a fixed substrate concentration (we are unable to assess Vmax above 5 µM peptide for technical reasons). The results of these analyses have been included in the revised version of Figure 8-Supplement 1, where they support differences in both Vmax and Km[ATP]; the ratio of these values very clearly points to differences in activities falling into ‘low’ or ‘high’. This kinetic analysis fully supports our initial activity assays, where mutations predicted to uncouple the auto-inhibitory C-tail rescue DCLK1.2 activity to levels similar to DCLK1.1 towards a common substrate.

Minor Comments

It is very interesting how the IBS together with the pT688 mimics ATP in the case of DCLK1.2 to reach full occupancy of the active site. On Figure 8 you evaluate residues of the GRL and IBS interface to probe such interactions.

1) Did the authors look at the T688 non-phosphorylable mutant?

See our response to Major Comment 1 above. In addition, due to the absence of T688 in DCLK1.1, we did not look at the T688A mutant of DCLK1.2 biochemically, partially because it has been characterized in previous studies, but partially because this site is preceeded by another Thr residue. The lack of a selective antibody towards this site makes it difficult to evaluate the role of T688 phosphorylation specifically with respect to DCLK cellular functions and interactions. Therefore, we focused our in vitro efforts to understand how mutations in the IBS impact the catalytic activity of DCLK1.2 by comparing different variants to DCLK1.1.

2) Classification of DCLK C-terminal regulatory elements.

It would be useful to connect the different regulatory elements described in this study to a specific functional and biological setting where these different switches play a role e.g. microtubule interactions and dynamics, cell cycle, cancer, etc..

While the primary focus of our paper is on the mechanism of allosteric regulation of DCLK1, we have indeed touched upon the potential implications of the various regulatory elements of the tail on functions such as microtubule binding and phenotypic effects like cancer progression. However, we acknowledge that a comprehensive understanding of these effects would necessitate a more detailed investigation. This could potentially involve the integration of RNA-seq data with extensive cell assays to evaluate phenotypic effects. We believe that such a future study would be a valuable extension of our current work and could provide further insights into the functional roles of DCLK1.

3) (Figure 3) Could the authors explain the differences in yield between the WT and the D531A mutant. Apparently, it [the yield] does not appear to be caused by a lower stability as indicated by the Tm. Could the authors comment on this? It is important to compare different samples in parallel, in the same experiment and side by side. This applies to the thermal shift data comparing WT and a D531A mutant on panel D and also on panel C a comparison between WT and D531A as negative control should be shown.

WT and D533A (kinase-dead) were indeed analysed in parallel, but have been split in two panels to make the data easier to interpret. The modest differences in yield is likely explained by experimental prep-to-prep variations. Our experience shows that many protein kinase yields vary between kinase and kinase-dead variants, likely due to bacterial toxicity related to enzyme activity. In regards to thermal stability, we would like to emphasize that Differential Scanning Fluorimetry (DSF) is to our mind a more informative and quantitative measure of protein stability than yield from bacteria, because both assess purified proteins at the same concentration. We believe that the DSF data provide a more accurate representation of the real stability differences between the WT and D533A mutant.  

Ilan Gronau: This manuscript describes updates made to GADMA, which was published two years ago. GADMA uses likelihood-based demography inference methods as likelihood-computation engines, and replaces their generic optimization technique with a more sophisticated technique based on a genetic algorithm. The version of GADMA described in this manuscript has several important added features. It supports two additional inference engines, more flexible models, additional input and output formats, and it provides better values for the hyper-parameters used by the genetic algorithm. This is indeed a substantial improvement over the original version of GADMA. The manuscript clearly describes the different added features to GADMA, and then demonstrates them with a series of analyses. These analyses establish three main things: (1) they show that the new hyper-parameters improve performance; (2) they show how GADMA can be used to compare performance of different approaches to calculate data likelihood for demography inference; (3) showcase new features of GADMA (supporting model structure and inbreeding inference). Overall, the presentation is very clear and the results are interesting and compelling. Thus, despite being a publication about a method update, it shows substantial improvement, provides interesting new insights, and will likely lead to expansion of the user base for GADMA.The only major comment I have is about the part of the study that optimizes the hyperparameters. The hyper-parameter optimization is a very important improvement in GADMA2. The setup for this analysis is very good, with three inference engines, four data sets used for training and six diverse data sets used for testing. However, because of complications with SMAC for discrete hyperparameters, the analysis ends up considering six separate attempts. The comparison between the hyper-parameters produced by these six attempts is mostly done manually across data sets and inference engines. This somewhat beats the purpose of the well-designed set up. Eventually, it is very difficult for the reader to asses the expected improvement of the final suggested values of hyperparameters (attempt 2) to the default ones. I have two comments/suggestions about this part.First, I'm wondering if there is a formal way to compare the eventual parameters of the six attempts across the four training sets. I can see why you would need to run SMAC six separate times to deal with the discrete parameters. However, why do you not use the SMAC score to compare the final settings produced by these six runs?Second, as a reader, I would like to see a single table/figure summarizing the improvement you get using whatever hyper-parameters you end up suggesting in the end compared to the default setting used in GADMA1. This should cover all the inference engines and all the data sets somehow in one coherent table/figure. Using such a table/figure, you could report improvement statistics, such as the average increase in log-likelihood, or average decrease in convergence times. These important results get lost in the many improved figures and tables.These are my main suggestions for revisions of the current version. I also have some more minor comments that the authors may wish to consider in their revised version, which I list below.Introduction:===========para 2: the survey of demography inference methods focuses on likelihood-based methods, but there is a substantial family of Bayesian inference methods, such as MPP, Ima, and G-PhoCS. Bayesian methods solve the parameter estimation problem by Bayesian sampling. I admit that this is somewhat tangential to what GAMDA is doing, but this distinction between likelihood-based methods and Bayesian methods probably deserves a brief mention in the introduction.para 2,3: you mention a result from the original GADMA paper showing that GADMA improves on the optimization methods implemented by current demography inference methods. Readers of this paper might benefit of a brief summary of the improvement you were able to achieve using the original version of GADMA. Can you add 2-3 sentences providing the highlights of the improvement you were able to show in the first paper?para 3: The statement "GADMA separates two regular components" is not very clear. Can you rephrase to clarify?Materials and methods - Hyper-parameter optimization:==============================================I didn't fully understand what you use for the cost function in SMAC here. Seems to me like there are two criteria: accuracy and speed. You wish the final model to be as accurate as possible (high log likelihood), but you want to obtain this result with few optimization iterations. Can you briefly describe how these two objectives are addressed in your use of SMAC? It's also not completely clear how results from different engines and different data sets are incorporated into the SMAC cost. Can you provide more details about this in the supplement?para 2: "That eliminate three combinations" should be "This eliminates three combinations".para 3: "Each attempt is running" should be "Each attempt ran"para 3: "We take 200×number of parameters as the stop criteria". Can you clarify? Does this mean that you set the number of GADMA iterations to 200 times the number of demographic model parameters? Why should it be a linear function of the number of parameters? The following text explains the justification, butTable 1: I would merge Table S2 with this one (by adding the ranges of all hyper-parametres as a first column). It's important to see the ranges when examining the different selections.Materials and methods - Performance test of GADMA2 engines:=====================================================para 2: "ROS-STRUCT-NOMIG" should be "DROS-STRUCT-NOMIG" Also, "This notation could be read" - maybe replace by "This notation means" to signal that you're explaining the structure notation.Para 4 (describing comparisons for momi on Orangutan data): "ORAN-NOMIG model is compared with three …". You also consider ORAN-STRUCTNOMIG in the momi analysis, right?Results - Performance test of GADMA2 engines:========================================Inference for the Drosophila data set under model with migration: you mention that the models with migration obtain lower likelihoods than the models without migration. You cannot directly compare likelihoods in these two models, since the likelihood surface is not identical. So, I'm not sure that the fact that you get higher likelihoods in the models without migration is a clear enough indication for model fit. The fact that the inferred migration rates are low is a good indication for that. It also seems like despite converging to models with very low migration rates, the other parameters are inferred with higher noise. For example, the size of the European bottleneck is significantly increased in these inferences compared to that of the NOMIG. So, potentially the problem here is that more time is required for these complex models to converge.Inference for the Drosophila data set under structured model (2,1): the values inferred by moments and momentsLD appear to neatly fit the true values. However, it is not straightforward to compare an exponential increase in population size to an instantaneous increase. Maybe this can be done by some time-averaged population size, or the average time until coalescence in the two models? This will allow you to quantify how good the two exponential models fit the true model with instantaneous increase.Inference for the Orangutan data set under structured model (2,1) without migration: you argue that a constant population size is inferred for Bor by moments and momi because of the restriction on population sizes after the split. You base this claim on a comparison between the log-likelihoods obtained in this model (STRUCT-NOMIG) and the standard model (NOMIG) in which you add this restriction. I didn't fully understand how you can conclude from this comparison that the constant size inferred for Bor is due to the restriction on the initial population size after the split. I think what you need to do to establish this is run the STRUCT model without this restriction and see that you get exponential decrease. Can you elaborate more on your rationale? A detailed explanation should appear in the supplement and a brief summary in the main text.Inference for the Orangutan data set with models with pulse migration: This is a nice result showing that the more pulses you include, the better the estimates become. However, your main example in the main text uses the inferred migration rates. This is a poor example, because migration rates in a pulse model cannot be compared to rates in a continuous model. If migration is spread along a longer time range, then you expect the rates to decrease. So, there is no expectation of getting the same rates. You do expect, however, to get other parameters reasonably accurate. It seems like this is done with 7 pulses, but not so much with one pulse. This should be the main the focus of the discussion of these results.Results - inference of inbreeding coefficients:======================================When you describe the results you obtained for the cabbage data set, you say "the population size for the most recent epoch in our results is underestimated (6 vs 592 individuals) for model 1 without inbreeding and overestimated (174,960,000 vs. 215,000 individuals) for model 2 with inbreeding". The usage of under/overestimated is not ideal here, because it would imply that the original dadi estimates are more correct. You should probably simply say that they are lower/higher than estimates originally obtained by dadi. Or maybe even suggest that the original estimates were over/underestimated?Supplementary materials:=====================Page 4, para2: "Figure ??" should be "Figure S1"Page 4, para 4: Can you clarify what you mean by "unsupervised demographic history with structure (2, 1)"?Page 22, para 2: "Compared to dadi and moments engines momentsLD provide slightly worse approximations for migration rates". I don't really see this in Supplementary Table S16. Estimates seem to be very similar in all methods. Am I missing anything? You make the same statement again in the STRUCT-MIG model (page 23).Page 22, para 4: "The best history for the ORAN-NOMIG model with restriction on population sizes is -175,106 compared to 174,309 obtained for the ORAN-STRUCT-NOMIG mod". There is a missing minus sign before the second log likelihood. You should also specify that this refers to the moments engine. Also see comment above about this result.

I think this is a really blunt message regarding the different meanings of freedom to people within different situations, and how the different ideas can conflict. It reveals that a differing idea of freedom can be seen as an attack on freedom accepted by someone else. In this case, the US soldiers see the Filipino's desire for independence as an infringement upon their ideas of freedom. It is up to society and each individual which side of the conflict they wish to be on. I think today, we can agree with the Filipinos side, but there may be some who think otherwise. Personally, I struggle to understand the soldiers, but their social development and ideologies are entirely different from my own. So, in that regard, historical circumstances play a big role in understanding the many complexities of freedom. It's very complex and quite hard to articulate.

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

In this manuscript, Kagermeier et al. present a novel and interesting study that attempts to model a severe neurodevelopmental disorder, pontocerebellar hypoplasia type 2a, using neocortical and cerebellar organoids. Brain organoids are an appropriate and promising approach to elucidate disease mechanisms in neurodevelopmental diseases. The authors show a reduction in the size of the organoids which is more pronounced in the cerebellar compared to neocortical organoids. While this finding is interesting and reminiscent of the clinical PCH2a phenotype, i.e., cerebellar hypoplasia, the study is very preliminary and the conclusions of the manuscript are not supported by the data. Additional information and further experiments are necessary to support the claims made.

Major concerns:

1. hiPSC lines show considerable inter- and intra-individual variability and therefore the size differences observed between these control and patient-derived organoids may arise from differences in the hiPSC lines used. While the data sufficiently demonstrates the pluripotency of the multiple novel hiPSC lines, major concerns remain as to the appropriateness of the control hiPSC lines. The manuscript should include a table describing the age and sex matching as well as mode of reprogramming for all control and patient lines. Patient and control lines should be matched as closely as possible. Furthermore, figure legends should clearly indicate which clones and lines are shown in the various figure panels.

We agree with the reviewer that hiPSC variability is an important concern in the field. In order to minimize such effects, all iPSCs lines used in this study were generated following the same protocol in the same lab. All cell lines are derived from male donors, thus, eliminating sex-based variability. Further, there is no report of sex-based variance in the clinical phenotype of PCH2a children and this finding is further corroborated by a currently on-going natural history study in our research team. While it would be ideal to also have age-matched controls, this is not possible for ethical reasons as skin biopsies from healthy children cannot easily be obtained to match the pediatric PCH2a cases. However, based on the literature, we believe that epigenetic age is erased upon reprogramming (Strassler et al 2018, Studer et al 2015). Following the reviewer’s recommendation, we provide a table that clearly indicates the origin of all six cell lines used (see Methods section) and information of respective lines was added to the figure legends as suggested by the reviewer.

As the hiPSC lines used are not isogenic, it is important that the authors characterise these lines further. This should include a quantification of the rates proliferation and apoptosis in all used hiPSC lines, as these might impact the growth rate of the embryoid bodies / organoids.

We thank the reviewer for raising this concern. To address the variability of hiPSC lines, we performed an extensive characterization of pluripotency, proliferation and cell cycle dynamics of all six hiPSC lines through immunocytochemistry against pluripotency marker OCT4, proliferation marker Ki-67 and EdU incorporation experiments. We further assessed the apoptosis rate of hiPSCs by staining against apoptotic marker cCas3. These experiments were carried out in three consecutive passages of all iPSC lines providing statistical power to the analyses. All experiments did not result in significant differences between PCH2a and control iPSC lines (see Figure 2).

The authors state that the hiPSC lines have been characterised by SNP arrays to show that no genomic / chromosomal aberrations have been accrued due to reprogramming. The manuscript should include information as to when the SNP array was performed (i.e., immediately after reprogramming, after initial passaging, etc) and also include the results of the SNP array as additional information. What passage were the hiPSC when the presented experiments were carried out?

In agreement with this comment, we provide data of SNP arrays that were performed to ensure the chromosomal integrity of all cell lines (see supplement). Further, we added details on passages of the cell lines in the respective figure legends as suggested by the reviewer. In brief, all cell lines were kept below passage 20 and were subjected to pluripotency testing before differentiations were started.

Given that TSNE54 is broadly and strongly expressed in the developing nervous system, the very limited staining of the organoids for TSNE54 in Figure 2 is surprising. Can the authors provide an explanation for the fact that TSNE54 is only expressed in a small subset of cells? Which cell types are these? Moreover, high-magnification images should be shown to demonstrate subcellular staining pattern of TSNE54. Quantification of TSNE54 protein levels by immunoblotting would also be beneficial.

Related to this observation, it is puzzling that the large size differences that the authors observe in their organoids would be driven by such a small number of TSNE54-expressing cells. How do the authors explain this discrepancy?

We thank the reviewer for this comment. We have carefully assessed human cerebellar development transcriptomic datasets which demonstrate that TSEN54 is in fact not strongly but moderately expressed in the human developing nervous system. Additionally, TSEN54 expression is expressed in various different cell types (not limited to a subset of cell types) (Aldinger et al 2021, Sepp et al 2021). We agree with this reviewer and reviewer 3 that Western Blotting or other types of quantification would be informative as well as investigation of the subcellular localization of the protein. However, these questions go beyond the scope of the current manuscript, which aims to present a disease model. We have therefore decided to remove the characterization of TSEN54 expression in organoids from our revised manuscript.

The generated organoids need to be better characterised with a broader range of markers using both qPCR and immunostaining. At the moment, their identity as "cortical" and "cerebellar" organoids remain unconvincing. This is particularly true for cerebellar organoids, which are challenging to generate and are not widely used. The authors should include additional markers (for example, see PMIDs 25640179, 29397531, 32117945) and immunostaining should clearly show expected staining patterns.

In Figure 5, it appears that some markers (e.g., SATB2) are expressed differently between control and patient lines, yet this is not commented on by the authors who conclude that control and patient lines show differentiation into organoids.

We thank the reviewer for this suggestion. We performed further immunostainings using the markers that were used in other cerebellar organoid papers (Muguruma et al 2015, Silva et al 2020, Watson et al 2018) as the reviewer suggested. In detail, we added immunohistochemistry experiments on Day 30 and Day 50 of differentiation for early Purkinje cell markers OLIG2 and SKOR2. We also included ATOH1 as a marker for rhombic lip-derived granule cells. For the neocortical organoids, we believe that the performed characterization is sufficient since the protocol we used is well-established and widely used as also indicated by the reviewer. We agree that the cellular composition of the organoids should be investigated in detail (for instance using single-cell transcriptomics). However, we believe this is out of the scope of this manuscript, which describes the establishment of a brain-region specific model platform.

The authors attempt to look into a potential mechanism for the size differences observed between control and patient organoids. However, only cleaved caspase-3 is used as a marker for apoptosis and no differences were observed. The authors should include further markers for potential cell death. In addition, immunostaining for proliferation markers (i.e., KI67) should be performed to evaluate whether the difference in organoid size could stem from decreased proliferation rather than increased cell death.

We agree with the reviewer and included a quantification of the proliferation marker Ki-67 within the SOX2 positive population of cerebellar and neocortical organoids as well as the quantification of SOX2 positive areas within the organoids (Figure 6). We observed significant differences in proliferation between PCH2a and control cerebellar organoids. Moreover, we also analyzed the morphology of organoids and quantified the thickness and number of rosettes and find significant differences between control and PCH2a cerebellar organoids corroborating the notion that proliferation is altered in cerebellar organoids. Neocortical organoids do not show any significant differences in proliferation and Sox2+ structures. Only the thickness of the Sox2+ areas is slightly decreased in neocortical PCH2a organoids compared to controls. In order to deepen our analysis of a possible increased apoptosis in PCH2a organoids, we also quantified cCas3 in Sox2+ structures (Figure 5) as also suggested by Reviewer 2. These analyses did not show any significant differences between PCH2a and control organoids. We therefore suggest that at the early stages of differentiation studied here, proliferative differences are the main reason for the size differences between PCH2a and control organoids.

Reviewer #1 (Significance (Required)):

The authors present an innovative approach to study neurodevelopmental disorders using brain organoids and should be of interest to researchers and clinicians working on neurodevelopmental diseases. However, the data presented are too limited to support any conclusions about the phenotype observed. Furthermore, questions remain about the used methodology and more work is needed to demonstrate the successful generation of both cortical and cerebellar organoids.

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

Please find enclosed my recommendation for the paper submitted by Kagermeier et al entitled' Human organoid model of PCH2a recapitulates brain region-specific pathology'. It describes the development of a human model for PCH2a and its characterization. My overall assessment of the paper is 'Major revision' which is explained below.

Although the paper is very well written and clearly interesting in that it describes the generation and initial analyses of a human organoid model for PCH2a it should be revised such that it will proof the points it is trying to make. The authors are meticulous in their studies combining cellular characterization and a thorough initial screen of organoid (both cerebellar as well as cortical) integrity, yet hardly any mechanistic data is provided. Nevertheless, if the authors are able to add additional experiments and are able to address the points raised, the reviewer may be willing to consider a more positive outcome.

Major concerns

1) The overall quality of the figures is poor. There is a lot of overexposure such that often cellular or tissue structures are blended. It starts with Figure 1 G and H but can be observed throughout the manuscript. Deconvolution would greatly enhance their results.

We are thankful for this comment and we have improved the quality of all microscopy images.

2) Especially figure 4 and 5 could have been complemented with quantitative data. It furthermore seems more supplemental figure as these are just proof-of-principle stainings. No conclusions can be drawn from the panels except that all markers are there in the various conditions. And while they are showing a neural rosette in Fig 4A, just tiny ones can be observed in 4B. It is also not clear what the whole mount IHC ads in comparison to the IHC on sections. It is also strange that there is still a lot of SOX2 in the CALB/MAP2-positive area, but again with this magnification hard to appreciate.

We agree with the reviewer that so far we presented qualitative proof-of-principle stainings that demonstrate cerebellar and neocortical differentiation, respectively. In order to address the comment of the reviewer, we improved the quality of the images and also provided higher magnification and enhanced resolution. Additionally, we now provide detailed quantifications of SOX2+ and Ki67+ neural progenitor cells and show that differences observed between PCH2a and control cerebellar organoids may explain the size differences observed between organoids (Figure 6). Our study provides the basis for more in-depth analysis of differences in differentiation and cell type composition between PCH2a and control organoids in the future, for example through single-cell RNAseq.

3) If the authors would like to proof the point that cerebellar/cortical development is hampered, more functional assays could have been done. Nothing is analyses on the fraction of progenitor cells present (such as the percentage of Tbr2+ IPC in VZ/CP). Furthermore, if there is a suspicion that the number of cells is affected (which is also not shown), proliferation/cell cycle exit experiments using BrdU/EdU should have been performed. Early cell cycle exit still cannot be rules out and should have been tested by the combination of Ki67-/EdU+ percentage of a certain faction of progenitor cells (eg PAX6+ pool).

We thank the reviewer for this valuable suggestion and agree that it would be interesting to carry out respective experiments. In this study, we show the establishment of a brain-region-specific organoid platform as a disease model for PCH2a and are only at the beginning of deciphering the underlying mechanism. In the revised manuscript, we quantified Ki-67+/Sox2+ cells in proliferative zones in the organoids. We believe that future studies including BrdU / EdU incorporation assays as well as scRNA-seq will answer the questions raised here and decipher the disease-causing mechanism on both cellular and molecular levels but are beyond the scope of this manuscript.

4) Instead the author chose to only perform a cCas3 staining. From the panels in Figure 6 it is hard to appreciate which cells are actually cCas3+. Also the analyses were performed on the total pool of cell while it might have been more interesting to look for cell death of the various progenitor pools (eg the SOX2+ pool).

We agree with the reviewer that a more in-depth analysis of apoptotic cell populations is interesting and performed cCas3/Sox2+ quantification for cerebellar and neocortical organoids. We did not observe significant differences of cCas3 expression within the SOX2+ cell population. (Figure 5)

Minor concerns

1) It would greatly enhance the review process if line numbers are added

We have added line numbers to the manuscript.

2) On general concepts (such as the generation of organoids in the context of disease) more references could have been added

We have added more references and discussed the topic of brain organoids as disease models as suggested by this reviewer (Eichmüller & Knoblich 2022, Khakipoor et al 2020, Velasco et al 2020).

Figures

Fig. 1: In A, the square is clearly visible and not similar to B. An annotation of which is the control and which is the patient is missing in the figure. The arrows are hardly visibly, would make them slightly bigger and remove the black outer lining. Figure 1C can easily go to the Supplemental material. Fig 1 D is hard to appreciate the staining, a close-up with bright field microscope will help. E-I Most of the panels but especially G and H are overexposed. In J, it is hard to appreciate the TSEN54 staining. Maybe separate channels and a merge?

We thank the reviewer for bringing these details to our attention. We have changed the arrows in the figure to enhance their visibility. Further we have adjusted the quality of the images overall. Lastly, we have made a comment in the figure legend clearly stating which scan came from which child. The described square was added to hide facial features of the imaged individuals hence they are not identical.

Fig. 3: Usually go into the supplementals.

Since organoid size is a major first readout when modeling a disorder that is characterized by a reduction of the volume of specific brain regions, we decided to keep this readout in the main text.

Fig 4/5: Lack of quantitative data and poor quality of figures (overexposure).

Fig 6: Many of the SOX2 panels are overexposed

We thank the reviewer for the suggestions on the figures and addressed the concerns in the revised manuscript.

CROSS-CONSULTATION COMMENTS

I completely agree with reviewers #1 and #3. It is good to notice that we are overall on the same page.

Reviewer #2 (Significance (Required)):

The authors definitely made an excellent start to model PCH2a. Three controls and three patient lines are good to begin with but isogenic controls using one parental line and a patient line where the mutation is fixed would have been ideal. It is interesting that there seem to be a brain area specific pathology of the phenotype. Yet, more thorough analyses could have been performed such as proliferation and differentiation and cell cycle exit experiments. As for now the mostly descriptive data are only scratching the surface and little can be concluded on the molecular framework they are trying to solve.

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

Summary:

In this study Kagermeier et al. use human cerebellar and neocortical organoids to investigate the effects of the PCH2a-causing homozygous TSEN54c.919G>T variant on the neurodevelopment of different brain regions. They reveal a substantial growth defect in both neocortical and cerebellar regions with a more profound phenotype in the cerebellum. They continue to investigate major cell types of neurodevelopment in both regions and briefly potential mechanisms underlying the phenotypes. The study is well conceived and addresses the current gap of disease-modeling in cerebellar organoids; nevertheless, some major claims are not sufficiently substantiated in the current version. Below, I provide suggestions on how to improve the manuscript with some additional minor comments that might help with readability and accessibility of the work.

Major comments:

1. TSEN54 expression levels: The authors compare RNA and protein expression levels for TSEN54 to investigate the mutation's effect. For this the authors use qPCR on iPSCs and organoids of different age and immunostainings and conclude "we did not find differences in expression between cell and tissue types". There are some issues with this analysis as explained below:

-The qPCR data (Fig. 2B) is first normalized to a housekeeping gene (GAPDH), however, then all organoid data are additionally normalized to the respective iPSC line. Thus, in case there is already a difference on iPSC level, this normalization might mask any difference in the organoids. It is unclear why this approach was chosen, and it seems more appropriate to show the data just normalized to GAPDH than additionally normalizing to the iPSCs, or at least to show first that iPSCs do not have differences in TSEN54 expression. Furthermore, even though apparently not statistically significant there seems to be a strong trend of lower TSEN54 levels in PCH2a in neocortical organoids, but even more so in cerebellar organoids. In my view this would fit very well with the study and should be further explored before concluding there is no statistical difference. Considering the high error bars of the cerebellar organoid samples, a higher N-number might be necessary to reach statistical significance in the difference in expression. Most importantly, it would be appropriate to show single data points where possible and to mark the different cell lines (as done in other figures), as otherwise it is not possible to judge whether there is a cell line bias in the data.

-The evidence for protein expression of TSEN54 is immunofluorescence stainings for all conditions. As there is no quantification, the authors should not conclude differences, or the lack thereof, based on this qualitative data. Furthermore, in fact in the on example shown the PCH2a cerebellar condition (Fig 2D) seems to show lower expression levels compared with other conditions. This could be due to the selected image, as all other examples include large neural rosettes with strong staining in the center of the rosettes. Furthermore, it is unclear what cell line these stainings come from, even whether the PCH2a cerebellar and neocortical stainings come from the same cell line. Thus, the authors should select comparable examples for all conditions, and ideally provide staining examples (e.g., as supplementary data) for the other replicates to ensure expression in all replicates. If the authors want to comment on differences in protein expression, maybe a quantitative approach (e.g., quantitative western blot) would be more appropriate. Otherwise, the statements should be adjusted to not conclude whether TSEN54 protein levels differ or not.

-Irrespective of the above comments the conclusion of the section "TSEN54 expression in cerebellar and neocortical organoids", that currently reads "we did not find differences in expression between cell and tissue types" should be changed, as the authors did not investigate whether there are cell type-specific differences of TSEN54 expression.

We thank the reviewer for this comment. We agree that the provided data is not suitable for quantitative analysis of TSEN54 expression. Please also see our related response to the similar concern raised by reviewer 1. Thanks to these suggestions, we have decided to exclude the TSEN54 expression data from the current manuscript as a detailed analysis should be part of an extensive future study.

Organoid growth analysis:

The organoid growth analysis in Figure 3 and supplementary Figure 2 shows the main phenotype of the study that seems to be very strong. The authors use unpaired t-tests to compare within the different timepoints. Unfortunately, I think this approach might not be appropriate as even though the Welch correction does not rely on similar SDs in the compared groups (Control vs. PCH2a), it still assumes that all data points within each group share the same variance. However, this is not the case, as e.g., the control condition includes three groups (Control-1 to -3), that between groups might have different variance as such not all datapoints are independent from each other. Potentially ANOVA analyses controlling for cell line and timepoint might be more appropriate. Or additionally, the authors could consider using the linear regression analysis in Supplementary Figure 2 to further investigate the difference in organoid growth by e.g., comparing the slope of the regression lines. This might be more appropriately reflecting the growth deficit over time than simply comparing each timepoint individually. Expanding on this analysis the regression analysis requires some more information on the fit (intercept, slope, R-squared of the model), which would help clarifying the growth dynamics in the different systems and conditions.

We thank the reviewer for the suggestions on statistical analysis and adjusted our approach accordingly. Briefly we performed 3-way-ANOVA analysis for the growth curves which revealed no significant differences between the different lines within the groups (Control or PCH2a) at different time points. Additionally, we added the linear regression model to the results (See Figure 3 and supplementary table 2, with the information on the curve fit).

The growth ratio analysis (Figure 3D) is essential to the major claim of the paper that the organoids replicate the region-specific differences. As the authors performed all experiments with matching cell lines this could additionally strengthen the argument by generating the ratio of size differences for each cell line separately (instead of just for all PCH2a lines together). This would allow comparison of the same genetic background in both cerebellar and neocortical condition and further corroborate the region-specific severity of the phenotype. Potentially, this would also enable to test these differences statistically.

We appreciate the suggestion to compare the differentiation protocols by line. Below we display the line-by-line analysis between the two differentiation protocols at D30 (A), D50 (B), and D90 (C). In order to visualize the differences in size between the two protocols more clearly, we have generated ratios of the average organoid sizes between neocortical and cerebellar organoids (D). The analysis corroborates our previous visualizations and statistics (3-way ANOVA) by showing that PCH lines produce neocortical and cerebellar organoids that differ in size more than those of control lines. The differences are most pronounced at D30 and D90. However, we believe that this analysis does not add additional value to our manuscript and have therefore decided not to include it in the revised version.

Additionally, all growth analyses for the neocortical organoids (Figure 3C, Supplementary Figure 2B and C) seem to lack the PCH-1 cell line and only contain PCH-2 and PCH-3. This cell line should be added or commented on why it was excluded from the analyses.

We agree with the reviewer. Unfortunately, we experienced contamination in that specific differentiation and therefore cannot provide the data. We have made a related comment in the manuscript. Since all differentiations were performed in parallel, adding this line at a later time point would add additional confounders and is therefore undesirable.

Potential mechanism of the phenotype (apoptosis analysis):

In Figure 6 the authors investigate the hypothesis that increased apoptosis contributes to the phenotypes. In the cleaved Caspase 3 staining there appear to be no differences. Unfortunately, the analysis apparently only includes one replicate (one organoid?) per cell line and condition. Considering the variability in the data shown this seems inappropriately low and should ideally contain ~3 replicates per cell line condition to judge technical and biological variability if the authors want to make the point that there is no "significant difference between PCH2a and control organoids at any time point in both cerebellar and neocortical organoids". Otherwise, this claim does not seem to be substantiated enough by the data.

Finally, due to the absence of a phenotype related to apoptosis the authors conclude that the phenotypes may be due to "deficits in the proliferation of progenitor cells". Although this is mentioned in the introduction and the discussion, there is no evidence in the current study that supports this interesting idea. By adding relatively straight forward co-staining experiments for e.g., SOX2 (progenitors) and Ki67 (proliferating cells), the authors could provide further evidence for this hypothesis using existing organoid sections. This would support this speculative idea and could add a more mechanistic insight to the study, thereby making it more exciting.

To address this concern, we have now added a table to the supplement that described in detail which organoids / batches / cell lines were used for which experiment (Supplementary table 3). In addition to our previous cCas3 quantifications, we performed the quantification of cCas3 within the population of SOX2-positive cells, which was suggested by Reviewer 2 (Figure 5).

To assess the alternative hypothesis, that proliferation deficits account for the size differences observed between organoids, we also performed quantifications of SOX2-positive zones in the organoids at D30 and D50 of differentiation as well as quantifications of Ki-67 positive cells within the SOX2-positive population. For cerebellar organoids we found significant differences in these experiments (Figure 6). We believe that this data supports the hypothesis of aberrant proliferation in PCH2a cerebellar organoids explaining the size differences.

Minor comments:

• Cell line and quality control: The authors recruit three male patients with PCH2a and reprogram iPSCs. These cell lines are subjected to a well performed extensive quality control. However, it is unclear what cell lines the stainings (e.g., Fig. 1D to I) originate from. Furthermore, the supplementary qPCR analysis (Supplementary Figure 1) includes only the PCH-1 line, and additionally two cell lines that are not explained (F-CO and hESC-I3). It is unclear what the relevance of showing the qPCR of these cell lines is. To ensure proper QC for all used cell lines the authors should provide data for all cell lines (PCH-1 to -3 and control-1 to -3), or at least summarize (e.g., in a table) what QC metrics were applied to which cell line. Most importantly, this information is completely lacking for the control cell lines and the QC is just mentioned in the text. Unfortunately, it is unclear where the control cell lines originate from, and some basic information would be required to judge whether they are appropriate controls: are they iPSC or ESC, were they reprogrammed with a similar paradigm as the PCH2a cells, what is the gender of the control cell lines (all PCH2a cell lines are apparently male)?

In line with a similar comment from reviewer 1, we have included a table that provides information on the origin of all six cell lines used in the revised manuscript (methods section). Further we provide SNP-Array data on all cell lines as supplementary material. We also performed detailed characterization of pluripotency, proliferation and cell cycle dynamics of all six hiPSC lines through immunocytochemistry against pluripotency marker OCT4, proliferation marker Ki-67 and EdU incorporation experiments (Figure 2). We further assessed the apoptosis rate of hiPSCs by staining against apoptotic marker cCas3. All experiments did not result in significant differences between PCH2a and control iPSC lines (see Figure 2). In line with the suggestion of this reviewer, we removed the qPCR analysis of iPSCs from the manuscript.

• To make the study more approachable for a medical audience and to judge the variability in phenotype presentation among the recruited patients it would be appreciated if more information on the patients would be provided. The authors write: "We identified three individuals that display the genetic, clinical and brain imaging features previously described for PCH2a.". This information including age/date of birth, as well as other medically relevant information could be provided in the supplementary figure (e.g., is there a difference in disease burden among the different patients?). This would allow judging the recruited cohort better.

We thank the reviewer for this insightful comment. We provided a table with detailed clinical information (supplementary table 1).

• According to the method section the cerebellar and neocortical organoids were cultured in very different medium especially at later timepoints. While neocortical organoids were kept in a neural maintenance medium based on Neurobasal-A, cerebellar organoids were kept in a medium based on BrainPhys. These media contain very different levels of nutrients, especially of glucose (25mM vs 2.5mM, Bardy et al. 2015). This can have a strong phenotype on proliferation of progenitors and proliferative phenotypes (e.g., see Eichmüller et al. 2022). Especially as the authors claim that there is a difference in the PCH2a phenotypes between brain regions, it should be excluded that this is due to medium differences at later timepoints. When investigating the growth curves of Figure 3B and C it seems like the major difference in growth speed seems to be that neocortical organoids grow faster in early timepoints (We agree that media composition can greatly influence growth dynamics of cells in 2D and 3D. However, in this study we assess the differences between two groups: the PCH2a and control iPSC-derived organoids. The differences we describe are in relation to the respective control group and iPSCs were generated following the same protocol in the same lab. We believe that by following two protocols and comparing the three PCH2a to the three control lines within each protocol predominantly, we account for different media composition possibly changing growth dynamics.

• Staining examples shown and presentation: In several figures the authors could improve the presentation of the staining examples with some changes:

o Cell line information for images: as the authors only ever note the condition (PCH2a or Control) but not the cell line it is unclear if the stainings all come from one cell line or from multiple different cell lines. This prevents comparing the different differentiation conditions. Additionally, for major conclusions the authors should consider including supplemental stainings or further information on how reproducible the results shown are (how many cell lines and batches were used?).

We thank the reviewer for these suggestions. We added information on cell lines and passages for all experiments shown in this study in the figure legends. Moreover, we also added a table providing information on n-numbers for all experiments (supplementary table 3).

o Selection of examples: in several cases (Fig 2C/D, 4A, 6A/B) the selected images depict very different regions, e.g., one condition shows a large rosette, while in the other condition no rosette can be seen. It would be more appropriate to show matching examples where possible.

We agree with the reviewer and have chosen matched regions of interest in the figure panels in the revised version of the manuscript. Please note that for cerebellar organoids we observed a significant difference in the timepoint of appearance of these rosette-like structures. Therefore, an exact matching of regions of interest was not possible due to biological differences between the samples, which we have also quantified (Figure 6).

o Color code of stainings: Colors do not match throughout the manuscript in immunofluorescence images. E.g., Fig. 4 uses blue, green, red, magenta and Fig. 5 uses blue, green, magenta, cyan. It would be preferable to adhere to one color code. Considering significant fraction of the population is having red-green blindness, the latter color code seems more appropriate as it should ensure readability also for color-blind audiences.

We are thankful for this comment. We changed the color code to make figures more widely accessible.

• Small typos:

o Figure 1 legend: last sentence "The" instead of "Th"

o Supplementary Figure 1B: PCH-2 is named "PCH-22"

o Supplementary Figure 2: As in the main figure for neocortical organoids the PCH-1 condition is missing (see comment on organoid growth curves). Additionally, the color/shape code of the plots in B does not always match the legend (e.g., size in left plot is different and color of PCH-3 in middle and left plot differs from legend and right plot).

o It is unclear why the cortical organoids are referred to as "neocortical organoids" in the figures and the text. The methods and the reference in the methods as well as all major papers rather use the word "cortical".

We addressed these suggestions and thank the reviewer for bringing these to our attention. Unfortunately, we could not include data on PCH-01 in neocortical differentiation due to a contamination in this batch. We made sure to run all the batches presented here in parallel so that all conditions are equivalent, preventing us from including a different batch at a later time point.

We believe that in the context of our study, it is important to highlight cortical organoids as neocortical organoids, because we are also showing cerebellar organoids and there is also a cerebellar cortex.

References:

Bardy, C. et al. Neuronal medium that supports basic synaptic functions and activity of human neurons in vitro. Proc National Acad Sci 112, E3312 (2015).

Eichmüller, O. L. et al. Amplification of human interneuron progenitors promotes brain tumors and neurological defects. Science 375, (2022).

CROSS-CONSULTATION COMMENTS

I agree with the comments of the other reviewers and as they are mostly matching, this reinforces the importance to improve certain aspects of the manuscript. As there are no deviating issues I do not comment specifically on any reviewer comments.

Reviewer #3 (Significance (Required)):

This work is using organoid technology to shed light on brain region-specific phenotypes in PCH2a. Brain organoids have drastically changed the way we study human neurological diseases (Eichmüller and Knoblich 2022), however, most brain organoid research has focused on cortical organoids. Cerebellar organoid protocols exist for some time (Muguruma et al. 2015, Silva et al. 2020, Nayler et al. 2021) but were not yet applied to uncover new disease biology. Especially considering the important role of human-specific cerebellar processes in specific developmental disorders (Haldipur et al. 2021) and cancer (Hendrikse et al. 2022, Smith et al. 2022), disease modeling in human cerebellar organoids holds great potential for understanding disease biology. The work by Kagermeier et al. demonstrates that human cerebellar organoids are recapitulating brain region-specific growth deficits and thus is an important step forward for disease modeling. Therefore, this work will be interesting to researchers working on brain development and disease modeling, especially in in-vitro systems. Nevertheless, the mechanistic insight of the study is limited, as is the insight into how human-specific processes might be involved in the pathogenesis of PCH2a. Therefore, it will be interesting how this disease model will be used in future to investigate the cell types and mechanisms involved in the PCH2a phenotype.

Personal field of expertise: Brain organoids and disease modeling in organoids especially of neurodevelopmental diseases. Analysis of organoids with stainings, as well as sequencing techniques, and bioinformatics.

References:

Eichmüller, O. L. & Knoblich, J. A. Human cerebral organoids - a new tool for clinical neurology research. Nat Rev Neurol 1-20 (2022) doi:10.1038/s41582-022-00723-9.

Haldipur, P. et al. Evidence of disrupted rhombic lip development in the pathogenesis of Dandy-Walker malformation. Acta Neuropathol 142, 761-776 (2021).

Hendrikse, L. D. et al. Failure of human rhombic lip differentiation underlies medulloblastoma formation. Nature 609, 1021-1028 (2022).

Muguruma, K., Nishiyama, A., Kawakami, H., Hashimoto, K. & Sasai, Y. Self-Organization of Polarized Cerebellar Tissue in 3D Culture of Human Pluripotent Stem Cells. Cell Reports 10, 537-550 (2015).

Nayler, S., Agarwal, D., Curion, F., Bowden, R. & Becker, E. B. E. High-resolution transcriptional landscape of xeno-free human induced pluripotent stem cell-derived cerebellar organoids. Sci Rep-uk 11, 12959 (2021).

Silva, T. P. et al. Scalable Generation of Mature Cerebellar Organoids from Human Pluripotent Stem Cells and Characterization by Immunostaining. J Vis Exp (2020) doi:10.3791/61143.

Smith, K. S. et al. Unified rhombic lip origins of group 3 and group 4 medulloblastoma. Nature 609, 1012-1020 (2022).

References by the authors

Aldinger KA, Thomson Z, Phelps IG, Haldipur P, Deng M, et al. 2021. Spatial and cell type transcriptional landscape of human cerebellar development. Nat Neurosci 24: 1163-75

Eichmüller OL, Knoblich JA. 2022. Human cerebral organoids — a new tool for clinical neurology research. Nature Reviews Neurology 18: 661-80

Khakipoor S, Crouch EE, Mayer S. 2020. Human organoids to model the developing human neocortex in health and disease. Brain Res 1742: 146803

Muguruma K, Nishiyama A, Kawakami H, Hashimoto K, Sasai Y. 2015. Self-organization of polarized cerebellar tissue in 3D culture of human pluripotent stem cells. Cell Rep 10: 537-50

Sepp M, Leiss K, Sarropoulos I, Murat F, Okonechnikov K, et al. 2021.

Silva TP, Fernandes TG, Nogueira DES, Rodrigues CAV, Bekman EP, et al. 2020. Scalable Generation of Mature Cerebellar Organoids from Human Pluripotent Stem Cells and Characterization by Immunostaining. J Vis Exp

Strassler ET, Aalto-Setala K, Kiamehr M, Landmesser U, Krankel N. 2018. Age Is Relative-Impact of Donor Age on Induced Pluripotent Stem Cell-Derived Cell Functionality. Front Cardiovasc Med 5: 4

Studer L, Vera E, Cornacchia D. 2015. Programming and Reprogramming Cellular Age in the Era of Induced Pluripotency. Cell Stem Cell 16: 591-600

Velasco S, Paulsen B, Arlotta P. 2020. 3D Brain Organoids: Studying Brain Development and Disease Outside the Embryo. Annu Rev Neurosci 43: 375-89

Watson LM, Wong MMK, Vowles J, Cowley SA, Becker EBE. 2018. A Simplified Method for Generating Purkinje Cells from Human-Induced Pluripotent Stem Cells. Cerebellum 17: 419-27

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Referee #3

Evidence, reproducibility and clarity

Summary: In this study Kagermeier et al. use human cerebellar and neocortical organoids to investigate the effects of the PCH2a-causing homozygous TSEN54c.919G>T variant on the neurodevelopment of different brain regions. They reveal a substantial growth defect in both neocortical and cerebellar regions with a more profound phenotype in the cerebellum. They continue to investigate major cell types of neurodevelopment in both regions and briefly potential mechanisms underlying the phenotypes. The study is well conceived and addresses the current gap of disease-modeling in cerebellar organoids; nevertheless, some major claims are not sufficiently substantiated in the current version. Below, I provide suggestions on how to improve the manuscript with some additional minor comments that might help with readability and accessibility of the work.

Major comments: 1. TSEN54 expression levels: The authors compare RNA and protein expression levels for TSEN54 to investigate the mutation's effect. For this the authors use qPCR on iPSCs and organoids of different age and immunostainings and conclude "we did not find differences in expression between cell and tissue types". There are some issues with this analysis as explained below: -The qPCR data (Fig. 2B) is first normalized to a housekeeping gene (GAPDH), however, then all organoid data are additionally normalized to the respective iPSC line. Thus, in case there is already a difference on iPSC level, this normalization might mask any difference in the organoids. It is unclear why this approach was chosen, and it seems more appropriate to show the data just normalized to GAPDH than additionally normalizing to the iPSCs, or at least to show first that iPSCs do not have differences in TSEN54 expression. Furthermore, even though apparently not statistically significant there seems to be a strong trend of lower TSEN54 levels in PCH2a in neocortical organoids, but even more so in cerebellar organoids. In my view this would fit very well with the study and should be further explored before concluding there is no statistical difference. Considering the high error bars of the cerebellar organoid samples, a higher N-number might be necessary to reach statistical significance in the difference in expression. Most importantly, it would be appropriate to show single data points where possible and to mark the different cell lines (as done in other figures), as otherwise it is not possible to judge whether there is a cell line bias in the data. -The evidence for protein expression of TSEN54 is immunofluorescence stainings for all conditions. As there is no quantification, the authors should not conclude differences, or the lack thereof, based on this qualitative data. Furthermore, in fact in the on example shown the PCH2a cerebellar condition (Fig 2D) seems to show lower expression levels compared with other conditions. This could be due to the selected image, as all other examples include large neural rosettes with strong staining in the center of the rosettes. Furthermore, it is unclear what cell line these stainings come from, even whether the PCH2a cerebellar and neocortical stainings come from the same cell line. Thus, the authors should select comparable examples for all conditions, and ideally provide staining examples (e.g., as supplementary data) for the other replicates to ensure expression in all replicates. If the authors want to comment on differences in protein expression, maybe a quantitative approach (e.g., quantitative western blot) would be more appropriate. Otherwise, the statements should be adjusted to not conclude whether TSEN54 protein levels differ or not. -Irrespective of the above comments the conclusion of the section "TSEN54 expression in cerebellar and neocortical organoids", that currently reads "we did not find differences in expression between cell and tissue types" should be changed, as the authors did not investigate whether there are cell type-specific differences of TSEN54 expression.

1. Organoid growth analysis: The organoid growth analysis in Figure 3 and supplementary Figure 2 shows the main phenotype of the study that seems to be very strong. The authors use unpaired t-tests to compare within the different timepoints. Unfortunately, I think this approach might not be appropriate as even though the Welch correction does not rely on similar SDs in the compared groups (Control vs. PCH2a), it still assumes that all data points within each group share the same variance. However, this is not the case, as e.g., the control condition includes three groups (Control-1 to -3), that between groups might have different variance as such not all datapoints are independent from each other. Potentially ANOVA analyses controlling for cell line and timepoint might be more appropriate. Or additionally, the authors could consider using the linear regression analysis in Supplementary Figure 2 to further investigate the difference in organoid growth by e.g., comparing the slope of the regression lines. This might be more appropriately reflecting the growth deficit over time than simply comparing each timepoint individually. Expanding on this analysis the regression analysis requires some more information on the fit (intercept, slope, R-squared of the model), which would help clarifying the growth dynamics in the different systems and conditions. The growth ratio analysis (Figure 3D) is essential to the major claim of the paper that the organoids replicate the region-specific differences. As the authors performed all experiments with matching cell lines this could additionally strengthen the argument by generating the ratio of size differences for each cell line separately (instead of just for all PCH2a lines together). This would allow comparison of the same genetic background in both cerebellar and neocortical condition and further corroborate the region-specific severity of the phenotype. Potentially, this would also enable to test these differences statistically. Additionally, all growth analyses for the neocortical organoids (Figure 3C, Supplementary Figure 2B and C) seem to lack the PCH-1 cell line and only contain PCH-2 and PCH-3. This cell line should be added or commented on why it was excluded from the analyses.

2. Potential mechanism of the phenotype (apoptosis analysis): In Figure 6 the authors investigate the hypothesis that increased apoptosis contributes to the phenotypes. In the cleaved Caspase 3 staining there appear to be no differences. Unfortunately, the analysis apparently only includes one replicate (one organoid?) per cell line and condition. Considering the variability in the data shown this seems inappropriately low and should ideally contain ~3 replicates per cell line condition to judge technical and biological variability if the authors want to make the point that there is no "significant difference between PCH2a and control organoids at any time point in both cerebellar and neocortical organoids". Otherwise, this claim does not seem to be substantiated enough by the data. Finally, due to the absence of a phenotype related to apoptosis the authors conclude that the phenotypes may be due to "deficits in the proliferation of progenitor cells". Although this is mentioned in the introduction and the discussion, there is no evidence in the current study that supports this interesting idea. By adding relatively straight forward co-staining experiments for e.g., SOX2 (progenitors) and Ki67 (proliferating cells), the authors could provide further evidence for this hypothesis using existing organoid sections. This would support this speculative idea and could add a more mechanistic insight to the study, thereby making it more exciting.

Minor comments: - Cell line and quality control: The authors recruit three male patients with PCH2a and reprogram iPSCs. These cell lines are subjected to a well performed extensive quality control. However, it is unclear what cell lines the stainings (e.g., Fig. 1D to I) originate from. Furthermore, the supplementary qPCR analysis (Supplementary Figure 1) includes only the PCH-1 line, and additionally two cell lines that are not explained (F-CO and hESC-I3). It is unclear what the relevance of showing the qPCR of these cell lines is. To ensure proper QC for all used cell lines the authors should provide data for all cell lines (PCH-1 to -3 and control-1 to -3), or at least summarize (e.g., in a table) what QC metrics were applied to which cell line. Most importantly, this information is completely lacking for the control cell lines and the QC is just mentioned in the text. Unfortunately, it is unclear where the control cell lines originate from, and some basic information would be required to judge whether they are appropriate controls: are they iPSC or ESC, were they reprogrammed with a similar paradigm as the PCH2a cells, what is the gender of the control cell lines (all PCH2a cell lines are apparently male)?

• To make the study more approachable for a medical audience and to judge the variability in phenotype presentation among the recruited patients it would be appreciated if more information on the patients would be provided. The authors write: "We identified three individuals that display the genetic, clinical and brain imaging features previously described for PCH2a.". This information including age/date of birth, as well as other medically relevant information could be provided in the supplementary figure (e.g., is there a difference in disease burden among the different patients?). This would allow judging the recruited cohort better.

• According to the method section the cerebellar and neocortical organoids were cultured in very different medium especially at later timepoints. While neocortical organoids were kept in a neural maintenance medium based on Neurobasal-A, cerebellar organoids were kept in a medium based on BrainPhys. These media contain very different levels of nutrients, especially of glucose (25mM vs 2.5mM, Bardy et al. 2015). This can have a strong phenotype on proliferation of progenitors and proliferative phenotypes (e.g., see Eichmüller et al. 2022). Especially as the authors claim that there is a difference in the PCH2a phenotypes between brain regions, it should be excluded that this is due to medium differences at later timepoints. When investigating the growth curves of Figure 3B and C it seems like the major difference in growth speed seems to be that neocortical organoids grow faster in early timepoints (<d30), but similar at later timepoints, which would exclude effects of the media at late timepoints. Nevertheless, considering the strong effect media glucose concentration can have the authors should investigate whether there is an effect at growth speed at later timepoints by comparing control organoids. This could also strengthen the region-specific phenotype due to PCH2a.

• Staining examples shown and presentation: In several figures the authors could improve the presentation of the staining examples with some changes: o Cell line information for images: as the authors only ever note the condition (PCH2a or Control) but not the cell line it is unclear if the stainings all come from one cell line or from multiple different cell lines. This prevents comparing the different differentiation conditions. Additionally, for major conclusions the authors should consider including supplemental stainings or further information on how reproducible the results shown are (how many cell lines and batches were used?). o Selection of examples: in several cases (Fig 2C/D, 4A, 6A/B) the selected images depict very different regions, e.g., one condition shows a large rosette, while in the other condition no rosette can be seen. It would be more appropriate to show matching examples where possible. o Color code of stainings: Colors do not match throughout the manuscript in immunofluorescence images. E.g., Fig. 4 uses blue, green, red, magenta and Fig. 5 uses blue, green, magenta, cyan. It would be preferable to adhere to one color code. Considering significant fraction of the population is having red-green blindness, the latter color code seems more appropriate as it should ensure readability also for color-blind audiences.

• Small typos: o Figure 1 legend: last sentence "The" instead of "Th" o Supplementary Figure 1B: PCH-2 is named "PCH-22" o Supplementary Figure 2: As in the main figure for neocortical organoids the PCH-1 condition is missing (see comment on organoid growth curves). Additionally, the color/shape code of the plots in B does not always match the legend (e.g., size in left plot is different and color of PCH-3 in middle and left plot differs from legend and right plot). o It is unclear why the cortical organoids are referred to as "neocortical organoids" in the figures and the text. The methods and the reference in the methods as well as all major papers rather use the word "cortical".

References: Bardy, C. et al. Neuronal medium that supports basic synaptic functions and activity of human neurons in vitro. Proc National Acad Sci 112, E3312 (2015). Eichmüller, O. L. et al. Amplification of human interneuron progenitors promotes brain tumors and neurological defects. Science 375, (2022).

CROSS-CONSULTATION COMMENTS I agree with the comments of the other reviewers and as they are mostly matching, this reinforces the importance to improve certain aspects of the manuscript. As there are no deviating issues I do not comment specifically on any reviewer comments.

Significance

This work is using organoid technology to shed light on brain region-specific phenotypes in PCH2a. Brain organoids have drastically changed the way we study human neurological diseases (Eichmüller and Knoblich 2022), however, most brain organoid research has focused on cortical organoids. Cerebellar organoid protocols exist for some time (Muguruma et al. 2015, Silva et al. 2020, Nayler et al. 2021) but were not yet applied to uncover new disease biology. Especially considering the important role of human-specific cerebellar processes in specific developmental disorders (Haldipur et al. 2021) and cancer (Hendrikse et al. 2022, Smith et al. 2022), disease modeling in human cerebellar organoids holds great potential for understanding disease biology. The work by Kagermeier et al. demonstrates that human cerebellar organoids are recapitulating brain region-specific growth deficits and thus is an important step forward for disease modeling. Therefore, this work will be interesting to researchers working on brain development and disease modeling, especially in in-vitro systems. Nevertheless, the mechanistic insight of the study is limited, as is the insight into how human-specific processes might be involved in the pathogenesis of PCH2a. Therefore, it will be interesting how this disease model will be used in future to investigate the cell types and mechanisms involved in the PCH2a phenotype.

Personal field of expertise: Brain organoids and disease modeling in organoids especially of neurodevelopmental diseases. Analysis of organoids with stainings, as well as sequencing techniques, and bioinformatics.

References:

Eichmüller, O. L. & Knoblich, J. A. Human cerebral organoids - a new tool for clinical neurology research. Nat Rev Neurol 1-20 (2022) doi:10.1038/s41582-022-00723-9.

Haldipur, P. et al. Evidence of disrupted rhombic lip development in the pathogenesis of Dandy-Walker malformation. Acta Neuropathol 142, 761-776 (2021).

Hendrikse, L. D. et al. Failure of human rhombic lip differentiation underlies medulloblastoma formation. Nature 609, 1021-1028 (2022).

Muguruma, K., Nishiyama, A., Kawakami, H., Hashimoto, K. & Sasai, Y. Self-Organization of Polarized Cerebellar Tissue in 3D Culture of Human Pluripotent Stem Cells. Cell Reports 10, 537-550 (2015).

Nayler, S., Agarwal, D., Curion, F., Bowden, R. & Becker, E. B. E. High-resolution transcriptional landscape of xeno-free human induced pluripotent stem cell-derived cerebellar organoids. Sci Rep-uk 11, 12959 (2021).

Silva, T. P. et al. Scalable Generation of Mature Cerebellar Organoids from Human Pluripotent Stem Cells and Characterization by Immunostaining. J Vis Exp (2020) doi:10.3791/61143.

Smith, K. S. et al. Unified rhombic lip origins of group 3 and group 4 medulloblastoma. Nature 609, 1012-1020 (2022).

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Reply to the reviewers

We thank all three Reviewers for their thorough assessment of our manuscript and their constructive comments and suggestions.

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

In this study, the authors generate several variants of actin that are internally tagged with short peptide tags. They identify one particular position that is able to tolerate various tags of 5-10 amino acids and still shows largely unaltered behavior in cells. They study incorporation of their tagged actins into filaments, characterize the interactions of G-actin variants with different associated proteins and show that retrograde actin flow in lamellipodia and the wound healing response of epithelial cells is not affected by the tagged variants. They then apply the tagged actin to study subcellular distribution of different actin isoforms in mammalian and yeast cells.

The identification of a specific site in the actin protein that tolerates variable peptide insertions is very exciting and of fundamental interest for all research fields that deal with cytoskeletal rearrangements and cellular morphogenesis. The result demonstrating the functionality of actin variants with peptides inserted between aa 229 and 230 are generally convincing and well done. In particular, the generation of CRISPR/Cas9 genome edited versions of beta- and gamma actin are impressive. I therefore generally support publication of this study. There are however several technical and conceptual issues that should be addressed to improve quality and scope of the study. I listed some specific comments below:

We thank the Reviewer for their constructive comments and general support for publication of our study.

Major points

- The biggest issue I have is the last section on the application of tagged actins to study isoform functions. In principle the application is very clear as there are simply no alternative ways to study isoform distribution in live cells. However, the experimental data are simply not convincing. What the authors define as "cortex" in Fig. 5A seems to rather represent cytosolic background mixed with radial fibers. I am not convinced that even the antibody staining with a relatively clear differential distribution of beta and gamma really shows a genuine accumulation of one isoform on stress fibers. It seems to me that the beta-actin staining has as higher cytosolic background and is generally weaker (gamma nicely labels transverse arcs), which reduces signal/noise and therefore yields a relatively increased level in areas with less-bundled actin. My suggestion is to select more clearly defined actin structures and to use micro-patterned cells to normalize the otherwise obstructing variability in actin organization. Possible structures would be cortical arcs in bow-shaped cells, lamellipodial edges (HT1080 seem to make very nice and large lamellipodia) or cell-cell contacts (confluent monolayer, provided cells don´t grow on top of each other). Stress fibers are possible but need to be segmented very precisely and I did not see any details on this in the methods section. For Fig. 5D: I assume cells were used where only one isoform was tagged? This is technical weak and the double-normalization is probably blurring any difference that might be occurring. Why not use a double-tagging strategy with ALFA/FLAG or ALFA/AU5 tags to exploit the constructs introduced in the previous figures? Also, the unique selling point of the strategy is the possibility of actual live imaging of specific isoforms. Cells that have stably integrated double tags and then transiently express nanobodies for ALFA and either AU5 or FLAG (or other if those don't exist) would make this possible. Considering the work already done in this manuscript, such an approach should actually be possible - did the authors attempt this or is there are reason it is not discussed? If double tagged cells are not possible for some reason it should at the very least be possible to combine ALFA-detection with the specific antibody against the other isoform and get rid of the double normalization.

We thank the Reviewer for the various suggestions regarding the comparison between the localization of the tagged and native isoforms. In our reply below, we will separately discuss the possibilities and our considerations for fixed samples and live cell imaging. We apologize for the lengthy response but for transparency reasons, we would like to give a thorough overview of our efforts for isoform-specific localization in cells, something for which we have limited space in the manuscript.

Fixed samples:

It was a significant experimental challenge to comparing the labeling of the β- and γ-actin specific antibodies with our internally tagged actin system (Fig. 5A-D). The reason for this is that the labeling of the samples with the β- and γ-actin specific antibodies requires treatment with methanol (Dugina et al., J Cell Sci, 2009), most likely to disturb the interaction of actin with actin-binding proteins that prevent the binding of the antibodies due to steric hindrance. Methanol treatment, however, precludes the co-labeling with phalloidin, likely due to changes in the tertiary/quaternary protein structure of F-actin. Initially, we have put a lot of effort in trying to simultaneously label phalloidin with the actin specific antibodies but even very brief methanol treatment (seconds), before or after phalloidin labeling, completely prevents/reverses the binding of phalloidin. Importantly, also the ALFA tag labeling was suboptimal after methanol treatment.

The fact that we could not perform these double labelings led us to perform different ratio calculations for the β- and γ-actin antibody and the ALFA tag labeling. In the case of the antibody immunofluorescence labeling, we simply divided the signal of the β-actin and γ-actin since we could simultaneously label the isoforms in the same cell. In the case of the ALFA tag labeling, we used phalloidin for independent signal normalization and then performed a second normalization. Although this complicates the normalization procedure (ALFA tag signal of β- and γ-actin is first normalized to total F-actin and then a ratio is calculated) and understandably leads to some confusion, this was the only way forward to obtain the results presented in the manuscript.

The Reviewer points out that “What the authors define as "cortex" in Fig. 5A seems to rather represent cytosolic background mixed with radial fibers.”. In our images, we observe very little cytosolic background from both antibody stainings. More importantly, for the quantitative analysis, the fluorescence intensity values were corrected for the background values observed in cytosolic areas so even if the signal is present, it should not affect our analysis. We do admit though that we could have been more careful with the term “cortex” since the observed signal could indeed be a mix of radial fibers and the actin cortex. The reviewer further states that “I am not convinced that even the antibody staining with a relatively clear differential distribution of beta and gamma really shows a genuine accumulation of one isoform on stress fibers.” Although the differences are small, we consistently observe a differential fluorescence intensity of β- and γ-actin in actin-based structures with a relatively stronger signal of γ-actin in stress fibers (Fig. 5C). Since we always normalize the fluorescent signal intensity per cell, this strongly indicates a genuine accumulation of one isoform over the other in specific actin-based structures. This observation is very consistent in our experiments and also aligns with many published studies where differences in the localization of β- and γ-actin are reported in various cell types (Pasquier et al., Vasc Cell, 2015; van den Dries et al., Nat Comms, 2019; Malek et al., Int J Mol Sci, 2020). As for the segmentation, we mentioned in the Methods section that we selected small regions (0.5x0.5mm) that exclusively contain stress fiber or “cortex” regions. The regions shown in Fig. 5B are therefore larger than the analyzed regions, something which we will better indicate in the revised manuscript.

Planned revision: We will provide a more detailed explanation of our quantitative analysis in the Methods section such that it is more clear how our normalization procedure was performed. Furthermore, we will adapt Fig. 5A-B such that it better visualizes how we defined the regions for quantification. As per the Reviewer’s suggestion, we will also apply a different experimental method to show that the tagged isoforms properly localize to actin-based structures. For this, we will attempt to use micropatterned cells to induce clearly define actin-bases structures (the crossbows as suggested by the Reviewer) and also explore the possibilities of investigating the differential localization in double-tagged cells. We will also reconsider the use of the term “cortex” for the region that is pointed out in Fig. 5A-B.

Live cell imaging:

We agree with the Reviewer that it would be very valuable to attempt simultaneous live cell imaging of two isoforms. Yet, for this, we would need two tag/fluorophore systems that allow the visualization of internally tagged isoforms in living cells. As presented in our original manuscript, we have successfully inserted many different epitope tags (FLAG/AU1/AU5/ALFA) in the T229/A230 position to demonstrate the versatility of our tagging approach. Yet, despite significant efforts to identify a second tag/fluorophore system that would allow isoform-specific live cell imaging, we only succeeded in designing one strategy to perform live cell imaging, i.e. with the ALFA tag (Götzke, Nat Comms, 2019). Part of the reason for this is that so far, no high affinity nanobodies have been generated against the classical epitope tags (FLAG, AU5 etc.). This is an established challenge since classical epitope tags are typically linear/unstructured while nanobodies require folded secondary structures for epitope recognition such as alpha helices (the ALFA tag was specifically designed as such).

Besides the successful ALFA tag approach we have tried the following additional approaches for live cell imaging: 1) __full-length GFP, 2) full-length GFP with linker, 3) GFP11 (to complement with GFP1-10 (Cabantous et al., Nat Biotech, 2005) 4) GFP11 with linker 5) FLAG Frankenbodies (Zhao et al., Nat Comms, 2019; Liu et al., Genes Cells, 2021) in FLAG IntAct cells and 6) __Tetracysteine/FlAsH labeling. Importantly, each of these additional internally tagged actins, except for those that contained full-length GFP, showed a high colocalization with the cytoskeleton, again demonstrating the versatility of the T229/A230 position to tag actin. Unfortunately, none of these approaches satisfactorily visualized the actin isoforms in living cells. We will therefore briefly summarize our findings here.

(1-2, integration of full-length GFP and GFP with linker) Probably not surprisingly, but integrating the entire coding sequence of GFP or GFP flanked by linkers (each 5AA in length) within the T229/A230 position did not results in a proper localization of actin.

(3-4, integration of GFP11 and GFP11 with linker) Next, we assessed the localization of the GFP11 tagged actin versions (GFP11: 16AA, GFP11+linker: 26AA). Because GFP11 is not visible without GFP1-10 complementation, we also tagged actin at the N-terminus simply for proof of concept where the internally tagged actins would end up. Interestingly, both GFP11-actin and GFP11+linker-actin properly integrated within the cytoskeleton as demonstrated by the FLAG staining. This again demonstrates the versatility of the T229/A230 position and strongly suggests that even the integration of 26AA within this position does only minimally affect the polymerization of actin into the cytoskeleton.

(3-4) After confirmation of the proper integration of GP11-actin and GFP+linker-actin we continue to express the GFP1-10 in these cells. Unfortunately, this resulted in no or only very minimal localization of the actin to the cytoskeleton, demonstrating that GFP-complementation hampers the integration into the cytoskeleton.

(5, use of FLAG Frankenbodies) We also expressed FLAG Frankenbodies into our FLAG IntAct cells in an attempt to visualize the isoforms in living cells. FLAG Frankenbodies are single chain antibodies fused to GFP and can be expressed in cells to visualize FLAG-tagged proteins (Liu et al., Genes Cells, 2021). Although a cytoskeletal labeling was indeed discernable in some cells, the FLAG Frankenbody signal overlapped much less with the total actin signal as compared to the FLAG immunofluorescence labeling, indicating that the incorporation of the FLAG-tagged actin was much less in the presence of the FLAG Frankenbody. Also, a significant fraction of the cells demonstrated a homogenous cytosolic signal.

(6, Use of tetracysteine/FlAsH) Although the tetracysteine tag/FlAsH system is widely known to induce artefacts, we still aimed to evaluate if for live cell imaging of IntAct actins. Similar to GFP11, we first determined the integration of tetracysteine-actin into the cytoskeleton with the use of an additional N-terminal FLAG tag and demonstrate that it was properly integrated into the actin cytoskeleton. Unfortunately, after brief incubation with FlAsH-EDT2, we noted 1) a significant amount of background fluorescence, preventing proper actin visualization and 2) that the cell became static indicating toxicity of the FlAsH-EDT2 compound. Titrating down the amount of FlAsH-EDT2 did not alleviate these drawbacks and only resulted in less fluorescence.

Overall, based on these experiments, we concluded that the T229/A230 position itself is very versatile, as demonstrated by the proper localization of the GFP11-actin variants and the TetraCys-actin. At the same time, none of these tag/fluorophore systems properly visualized actin in living cells. Although we are unsure what the reason is for this, it is easily imaginable that the on/off kinetics of the split GFP system and the FLAG Frankenbodies are suboptimal to allow for the rapid and continuous integration of actin monomers into the F-actin cytoskeleton. We therefore also concluded that currently, the ALFA tag/nanobody system is apparently unique in its ability to visualize epitope tagged actin in living cells (as shown in the manuscript). For simultaneous visualization of multiple isoforms, we rely on progress on the development of novel nanobody-based tags, something we hope the Reviewer will agree is outside the scope of the current work.

*- The authors make a point of comparing the internally tagged actin to N-terminal tags that are mostly functional but have been shown to affect translational efficiency. I would strongly suggest to include N-terminally tagged actin as control for all assays in this study. Also for the physiological assays (retrograde flow, wound healing), a positive control is missing that shows some effect. Previous studies showed defects with transiently expressed actin with an N-terminal GFP. As retrograde flow measurements are very sensitive to the exact position of the kymographs and wound healing assays is a very crude and indirect readout, such a positive control is essential. *

We acknowledge that N-terminally tagged actin has been used extensively for actin research (especially before the introduction of Lifeact). For our studies, however, we were specifically interested in whether the internally tagged actins show similar characteristics as compared to wildtype actin. We have not included N-terminally tagged actin in all of our experiments, since this would not affect our conclusions with respect to the functionality of our internally tagged actins. We expect that for future investigations to for example further establish the importance of actin N-terminal modifications in the differential regulation of actin isoforms, the comparison between internally and N-terminally tagged actins could be very instrumental. Yet, we consider this comparison outside the scope of the current manuscript. For now, the results in the manuscript provide evidence that our approach is unique with respect to the fact that it allows isoform-specific tagging without manipulating the N-terminus. As such, our internal tagging system complements the already existing repertoire of actin reporting methods (N-terminal fusion, Lifeact, F-Tractin, actin nanobodies) and allows researchers to study so far unknown properties of actin variants.

*- Expression of tagged actins in yeast is a very nice idea but it would be far more informative to express the tagged forms as the only copy of actin. This can either be done by directly replacing endogenous actin gene in S. cerevisiae, or (if the tagged versions are not viable) - using the established plasmid shuffle system (express actin on counter-selectable plasmid, then knock out endogenous copy and introduce additional plasmid with tagged actin, then force original plasmid out). In the presence of endogenous S. cerevisiae actin the shown effects are very hard to interpret as nothing is known about relative protein levels (endogenous vs. introduced). Also, if constitutive expression of the ALFA nanobody is harmful for integration into cables, why not perform inducible expression of the nanobody and observe labeling after induction. For the live imaging a robust cable marker is needed, like Abp140-GFP. Finally, indicate the sequence differences between the used actin forms in yeast (supplementary figure with sequence alignment and clear indication of all variations) *

We thank the reviewer for their positive comments and feedback regarding expression of IntAct variants in yeast. Currently, we have expressed IntAct as an extra copy in the presence of native Act1 of S. cerevisiae. All the IntAct variants have been expressed under a commonly used constitutive TEF1 promoter. We agree with the Reviewer that it would be valuable to attempt to express the tagged forms as the only copy of actin.

Planned revisions:

1) As per the Reviewer’s suggestion, we will attempt to make yeast strains with IntAct as the sole expressing actin copy by using the well-established 5-FOA-based plasmid shuffle system in yeast. We will use a ∆act1 strain containing wildtype act1 in a centromeric ura-plasmid described in Harrer et. al, 2007 (generously shared by Prof. Jessica and Prof. Amberg at Upstate Medical University of New York, USA) and express IntAct exogenously via additional plasmids. Shuffling of these strains on 5-FOA will cause the loss of ura-plasmid containing the wildtype act1 copy and will determine whether yeast cells will be able to survive with IntAct as the sole source of actin. If the cells do survive with IntAct as a sole copy, we will perform subsequent analysis for assessing actin cytoskeleton organization under these conditions.

2) As the reviewer has mentioned, expression of NbALFA during live-cell imaging experiments hindered incorporation of IntAct into linear actin cables in yeast (Suppl. Fig. S13). As per the reviewer’s suggestion, we will now try to create an inducible-expression system for the NbALFA-mNG and observe its effects on incorporation into formin-made actin cables after induction. We have already created NbALFA-mNG constructs under galactose-inducible GALS and GAL1 promoters and are currently constructing yeast strains for these experiments.

__3) __We will add an extra supplementary Figure to indicate the sequence differences of the various actin variants that we have expressed in yeast.

- As the authors clearly show good integration of several tagged actins into filaments I would expand the structural characterization: perform alpha fold predictions of actin monomer structures including the various tags to show the expected orientation. It is striking that the only integration site that seems to work well is at the last position of a short helix, indicating that the orientation of the integrated peptide might be fixed in space and be optimal to minimize interference. Also, a docking of the tag onto the recently published cryoEM structures of the actin filament should be shown to indicate where it resides compared to tropomyosin or the major groove where most side binding proteins seem to bind.

We already performed AlphaFold predictions of the tagged actin monomers, but we have decided to not include these predictions in the manuscript because of two reasons. First and foremost, while the prediction confidence of the non-tagged region is very high (pLDDT > 90), the prediction confidence of the tagged region is very low (pLDDT https://alphafold.ebi.ac.uk/faq), pLDDT values below 70 should be treated with caution and values below 50 should not be interpreted. Intriguingly, the low confidence aligns with the fact that for both tags, the prediction does not match with known features of the tag. The FLAG tag should be a linear/unstructured region in order to be recognized by the antibody and the ALFA tag should organize into an alpha helix (Götzke et al., Nat Comms, 2019). Yet, in the prediction, the FLAG tag partially continues as an alpha helix and the ALFA tag is only a small helix with part of the tag being unstructured. Second, more minor, reason for not including the predictions is that AlphaFold does not predict to what extend the tag is flexible, which means that even if the tagged region is predicted correctly, it is difficult to say whether the regions will interfere with binding of proteins.

Despite the low prediction confidence, we used the published actin-tropomyosin cryoEM structure (von der Ecken et al., Nature, 2015) to replace WT actin with ALFA tag actin and the results are shown below. Again, although results should be interpreted with caution, the tag does not seem to obstruct monomer-monomer interactions within an F-actin filament and also the tropomyosin binding surface is relatively distant from the tag region, suggesting that these interactions are likely not disturbed by introducing the tag.

- For any claims regarding usability of tagged variants for isoform research it would be very important to characterize the known posttranslational modifications of tagged actin variants - are the differences between beta and gamma maintained on this level as well?

Planned revision: Following the Reviewer’s suggestion, we will perform a western blot analysis to compare posttranslational modification (arginylation) of tagged and wildtype actins.

Technical issues

- There is no scale for the color coding in Fig. 5A, B

We deliberately did not add a numerical scale because the images are normalized which means that presenting the actual numbers might be misleading. The numbers could be interpreted as if they actually present the amount of β-actin relative to γ-actin which is not the case due to staining differences and the normalization procedure.

- The y-scales for Fig. 5C and D need to be identical to allow direct comparison

Planned revision: We will adapt the scale of Fig. 5D to make it identical to Fig. 5C. Following the other suggestions of the reviewer, we will also critically evaluate our normalization procedure and present those numbers in Fig. 5C-D if the values turn out to be different.

- Pearson coefficient should not be normalized to a control value as its already a dimensionless parameter. Always report actual R-value - also remove R2 values for Pearson as this makes no sense in this context (not sure if it was a typo or intended).

We normalized the Pearson coefficient values for visual representation of the results. The majority of the raw coefficient values (more than 80%) are between 0.20 and 0.75 (see raw values in the associated excel file). Theoretically, Pearson coefficient values are possible between 1 (or-1 for negative correlations) and 0. The much smaller window in our values as compared to the theoretical window (0.55 vs 1) led us to normalize the values such that they can be presented on a scale from “maximum expected colocalization” to “minimum expected colocalization”. In this way, the differences between the various tagged actins are much better appreciated in the Figure. As to reporting the R2, the Reviewer is correct. Reporting the R2 is an inadvertent mistake from our side and we will correct it.

Planned revision: We will change the R2 in the text to PCC or Pearson Correlation Coefficient.

*- All values on subcellular regions (like stress fiber or cortex) dependet critically on the way thesese regions were thresholded or identified. Provide all details on how this was done in the methods section and ensure that adequate background subtraction and normalization is applied. Optimally, an unbiased (AI or automated) approach based on simple image statistics is used for this to avoid personal bias. *

Planned revision: As also indicated above, we will add new experiments to better compare the localization of the isoforms in tagged and parental cells. These new experiments will also be accompanied by a more detailed explanation of how the regions were selected and quantified.

- In Fig. 2A only heterozygous FLAG-actin cells are used. Why not use a homozygous line (for both beta and gamma actin)? The nice band shift of the FLAG version would allow the precise quantification of the fraction of total actin covered by beta and gamma actin, which then could provide some additional info for the apparently weaker beta staining in Fig. 5 (if beta expression is simply weaker). This would be a very simple and useful advantage of the internal tags that could be widely applied.

In Fig. 2A, we used the heterozygous FLAG-actin cells to directly compare the production of β-actin from the knock-in allele and the wildtype allele in the same cells. The fact that the two bands observed in this western blot analysis (upper and lower) are almost the same (with the FLAG band being a bit more intense) provides the strongest indication that the tag does not interfere with the expression of actin. In Suppl. Fig. 5D, we show that the expression of β-actin is also unaffected in the hemizygous FLAG actin cells, which exclusively express tagged actin.

Planned revision: As per the Reviewer’s suggestion, we will also add a western blot analysis on the expression of both actin isoforms and total actin in hemizygous cells.

*- Fig. 3: control with N-terminal tag is missing. Also, why is it not possible to assay filament binding factors like Myosin, Filamin or alpha actinin - instead of co-IP a simple co-sedimentation assay with cell extracts in F-buffer should pick up any major difference in decoration of filaments containing the ALFA tag. Using two speeds for centrifugation it might even be possible to observe effects on filament bundling. The best approach for this would of course be to purify tagged actins and perform in vitro assays but this is clearly beyond the scope of what the authors intended here. I personally think that a broad acceptance of the marker will only come once the biochemistry has been sufficiently characterized so this is a future direction I would strongly encourage. *

We kindly refer to our response on Page 5/6 for why we have not included the N-terminal control.

Planned revision: The co-sedimentation assay is an excellent suggestion by the reviewer. Following the Reviewer’s suggestion, we will perform F/G-actin fractionation and assess the presence of several F-actin associated proteins in the F-actin fraction.

- Fig. 2A has no loading control

We show this western blot to indicate that the WT actin and tagged actin are expressed at similar levels in the heterozygous knock-in cells. For this, no loading control is needed because we only compare the intensity of the upper band (tagged actin) with the lower band (WT actin).

- The RPE-1 data are confusing as several constructs show very different localization (completely cytosolic) to HT1080 cells and there is no possible explanation given for this. Maybe simply remove this data set?

We agree with the reviewer that the differences in the localization between some of the internally tagged actins between the HT1080 and RPE1 cells might be confusing, especially for the A230-A231 variant for example. Yet, the fact that also in these cells, the T229-A230 variant performs equally well as compared to N-terminally tagged actin is an important confirmation that this variant is properly integrated into actin-based structures, independent of cell type. This makes the support for choosing this variant to continue with our studies stronger. A possible explanation for the differences is that RPE1 cells in general tend to form more stress fibers as compared to the HT1080. Since the localization to stress fibers is different between the internally tagged actins, this may explain the differences observed in colocalization.

__Planned revision: __We will add a short text, in the Results or the Discussion, on the differences between the colocalization values between HT1080 and RPE1 cells.

*- The angel measurements for lamellipodial actin is not very meaningful: the angel is determined for the radial bundles, which do not correspond to the Arp2/3 angel of single filaments and is likely the results of different nucleation factors, I would suggest to remove this. If angel measurement are really intended, cryoEM needs to be performed. *

We apologize for this misapprehension from our side which is also noted by the other two reviewers. In the treadmilling videos of the lamellipodia in HT1080 cells, which were obtained using Airyscan super-resolution microscopy, we clearly observe a consistent filament formation at a constant angle, something which we interpreted as the angle between the mother filament and the daughter filament. After consulting the literature, we indeed have to admit that this cannot be interpreted as such and we will remove these datasets.

Planned revision: We will remove the datasets with the angle measurements (Suppl. Fig. 7A-B) from our manuscript.

- Replace all SEM with SD values - use at least 3 biological replicates (4D SEM of n=2)

Planned revision: We will carefully check our statistics and revise where appropriate.

Minor points

- Intro: after listing all the details already understood on actin isoforms it is not very convincing to simply state the molecular principles remain largely unclear (l 34) - maybe better "there is no way to study actin dynamics due to current limitations of specific antibodies to fixed samples. Interesting option would be actually to develop nanobodies that are isoform specific.

We will rephrase the text in the introduction. Regarding the development isoform-specific nanobodies. Although this sounds like a promising way forward, this would likely not result in isoform-specific targeting in living cells. Similar to the antibodies, isoform-specific nanobodies would have to be generated against the N-terminus which, under native conditions, is likely not available due to the occupation with actin-binding protein. Also, since the N-terminus is not structured, it may be extremely challenging to generate nanobodies against these epitopes.

*- L 71: "involved" in the kinetics is not a good term - maybe affects or regulates.... *

We will rephrase the text.

- L148: "suspect" instead of "expect" - this clonal variation is actually a big danger of the employed approach as possible defects in actin organization could be masked by compensatory changes - it would generally be good to show critical data for at least 3 independent clones to rule out dominant selection effects.

We will rephrase. We agree that clonal variation could be a danger if actin levels are to be investigated. For future follow-up studies, we plan to make additional cell lines to avoid clone-specific conclusions.

***Referees cross-commenting** *

*I completely agree with the comments by reviewer 2 on the various missing controls - adding several or all of those will make the results much more convincing. The key for the adaptation of any new actin probe will be the level of confidence researchers have on the doumented effects. Even some negative effects on actin behavior (I am sure there will be some) should not prevent usage of the strategy as long as there is robust and convincing documentation of those effects. I also agree that including some basic in vitro characterization will go a long way to convince people dierectly working on actin (there is a very high level of biochemical understanding in that field). *

Planned revision: We will perform the essential controls as suggested by Reviewer 2. Furthermore, for future experiments, we do envisage the production and purification of internally tagged actins and investigate their binding properties in in vitro reconstitution assays. We have already started with optimizing these approaches through our ongoing collaboration (KD, SP).

Reviewer #1 (Significance (Required)):

*Significance: Very useful finding that can be applied to any question related to actin-dependent cellular processes (morphogenesis, cell division, cell polarization, cell migration etc.) *

*Strength: main finding convincing, strong genome edited cell lines *

*Limitations: application to study of isoforms very limited and data not convincing, statistics and image quantifications need improvement *

*Advance: identify new location for integral tagging of actin, which was not really possible before. The main relevance is for fundamental cell biology but the approach can also be applied to the study of disease variants in actin. *

Audience: general cell biology - very broad interest

__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __

Actin is highly sensitive to modifications, and tagging it with fluorescent proteins or even smaller motifs can affect its function. The most well-known example of this is that fission yeast where actin has been replaced with GFP-actin are inviable (Wu and Pollard, Science 2005) because the labeled actin cannot incorporate into the formin-dependent filaments that make up the cytokinetic ring. Subsequent experiments revealed that formins filter out GFP-actin monomers, as well as monomers that are labeled with smaller fluorescent motifs (Chen et al, J. Structural Biology 2012). Further, attempts to make mammalian cells lines where GFP-beta-actin was knocked into one allele resulted in extreme down-regulation of the GFP-labeled actin, indicating that there is some implicit toxicity with the labeled version. To my knowledge, all attempts at making homozygous GFP-actin knock-ins have been unsuccessful. Therefore, while GFP-actin or other labeled variants can be over-expressed in many different cell types with some success, there is always the question of how faithful the labeled actin represents bona fide actin localization and dynamics.

To address this van Zwam et al. have developed a clever strategy of screening actin for internal motifs that can tolerate incorporation of a tag without affecting its function. They appear to have found a good candidate, named IntAct, and provide evidence that this tagging position allows the actin to be functional in both human and yeast cells. The work is very promising, and many of the assays performed satisfy the criteria of rigor and reproducibility. Importantly, the authors have created knock-in human cell lines where the tagged actin is expressed at normal levels, including a double allele knock-in that is viable and has normal proliferation and motility. Additionally, the authors show that labeled S. cerevisiae actin can incorporate into actin cables, which are formin dependent. IntAct constructs were shown to interact with several well-known actin binding proteins and localized well to many different actin structures. There was also interesting data obtained from tagging both beta and gamma actin in human cells. However, as an actin scientist eager for new probes to visualize actin in cells, there are still questions about the functionality of these probes. Addressing these issues, listed below, would alleviate the concerns I still have about IntActs after going through the manuscript. IntActs have the potential to have a large impact on cytoskeletal research if it can be rigorously documented that they are functionally as close to unlabeled actin as possible.

We thank the Reviewer for their constructive comments and general positive evaluation of our study.

*Reviewer #2 (Significance (Required)): *

Concerns:

1. There are no negative controls performed for either the fixed or live-cell imaging of IntAct. Since the fixed cell data is heavily reliant on the presence of flag-labeled puncta at actin filaments, it is important to show that the immunocytochemistry protocol doesn't produce anything that would mimic the localization of actin. For the live cell data, there has been no effort made to show that the binding of the nanobody to the ALFA tag on InAct is specific.

Planned revision: __We will add the following controls to exclude that any of the labeling procedures produces anything that would mimic the localization of actin: 1) Immunofluorescence staining of the used tags (FLAG/ALFA) in cells that do not have tagged actins 2) Expression of ALFA-Nb-GFP and ALFA-Nb-mScarlet in cells that do not have tagged actins 3)__ Expression of free GFP in cells that have tagged actins. We will co-stain these cells with phalloidin to visualize F-actin and determine if any signal is specifically localized to the actin cytoskeleton.

2. The homozygous ALFA-tagged IntAct cells have a 50% reduction in the amount of actin expression (Fig. 2D). What is the F:G ratio in these cells? The F:G measurement is only shown for the FLAG-tagged heterozygous IntAct cells, which have the worst co-localization with phalloidin (Fig. 2F) and were not used for subsequent figures. I appreciate that motility and proliferation were measured and shown to not be affected (Fig. 4D,E) , but in our lab reducing the amount of polymerized actin by 50% (which may be more in ALFA-tagged IntAct cells if the F:G changes) has catastrophic effects on other cytoskeletal and organelle systems. Since the homozygous ALFA IntAct cells are the main ones used in the manuscript, they should be the ones that are fully characterized.

We would like to point out that the reduction is only 20-25 percent depending on the specific western blot analysis and the loading control. Still, the Reviewer is correct about the necessity of the F:G actin measurements of the ALFA-tagged IntAct cells and we therefore included those as Suppl. Fig. 9 in the original manuscript (text on page 9). The quantification of these assays clearly demonstrated that the F-G actin ratio in the ALFA-tagged IntAct cells is the same as in parental cells.

3. It is not addressed if expressing the ALFA-Nb-GFP construct in ALFA-IntAct cells alter actin properties? This is essential information for live cell imaging experiments.

Planned revision: We have already performed proliferation and migration experiments in cells that stably express the ALFA-Nb-GFP. These data indicated that proliferation and migration are not affected by the presence of the nanobody and these data will be included in the revised manuscript. To note, in the original manuscript, we already showed that treadmilling of actin at the lamellipodia is not affected by the presence of the ALFA-Nb-GFP.

4. It is not addressed how much of the ALFA-IntAct gets labeled with ALFA-Nb-GFP and how uniform the labelling.

We do not understand this specific request of the Reviewer. To our knowledge, it is not possible to assess how much of a probe (in this case the ALFA-Nb-GFP) binds the target (in this case the ALFA-IntAct actins) in living cells. This is not only the case for the ALFA-Nb-GFP but also for any other probe. As an example, when expressing Lifeact, we also do not know how much of the actin molecules within F-actin get labeled with Lifeact and how uniform the labeling is. From the results of the live-cell imaging we can only conclude that the binding is at least so effective that we can readily observe and discern all the actin-based structures that are also observed by Lifeact (see Suppl. Fig. 8 for Lifeact-GFP/ALFA-Nb-mScarlet cotransfection). Whether the regions that do not have F-actin only contain ALFA-Nb-GFP that is bound to actin monomers or also contains a significant fraction of free ALFA-Nb-GFP seems an issue that cannot be addressed.

5. To assess lamellapodia architecture, "branched actin angle" is measured using AiryScan imaging of actin filaments. This type of microscopy does not offer the ability to image individual actin filaments; what is actually being measured is the orientation of actin bundles to each other. It should be impossible to image the orientation of actin filaments in Arp2/3 dendritic networks and it is surprising that the measurements average to 70 degrees. A suitable substitute for this would be to measure the size and amount of F-actin in phalloidin-stained lamellipodia using kymograph analysis.

We apologize for this misapprehension from our side which is also noted by the other two reviewers. In the treadmilling videos of the lamellipodia in HT1080 cells, which were obtained using Airyscan super-resolution microscopy, we clearly observe a consistent filament formation at a constant angle, something which we interpreted as the angle between the mother filament and the daughter filament. After consulting the literature, we indeed have to admit that this cannot be interpreted as such and we will remove these datasets.

Planned revision: We will remove the datasets with the angle measurements (Suppl. Fig. 7A-B) from our manuscript.

6. Was it possible to make an IntAct gene substitution in yeast?

Planned revision: We thank the reviewer for this interesting question and as also suggested by Reviewer 1, we are now constructing yeast strains with IntAct as the sole expressing actin copy by using the well-established plasmid shuffle system in yeast. The results of these experiments will determine the ability of IntAct to completely substitute actin function in yeast.

Also, while this is not necessary for this manuscript, making a fission yeast strain where actin has been substituted with IntAct and demonstrating that IntAct gets incorporated into the cytoplasmic ring and into Cdc12p-polymerized filaments would alleviate MANY potential concerns people would have about these probes by directly assessing situations were other labeled actins have been documented to fail. Along the same lines, it would have been nice to see a comparison in some of the assays of ALFA-IntAct and GFP-actin or another labeled actin variant.

We appreciate the reviewer for their constructive feedback and completely agree that it is important to document how IntAct behaves in scenarios where other labelled actins have failed. As a proof of principle, IntAct incorporates into both formin- and Arp2/3- made linear and branched actin filaments in yeast (Fig.5E, Suppl. Fig. 14) and this data shows that IntAct labelling strategy is the first to achieve good integration into both these structures as previous efforts with labelled actin such as GFP-Actin fail to incorporate into formin-made actin filaments (Doyle et al., PNAS, 1996). Thus, we believe that IntAct does perform better than other labelled actins in yeast, although, further optimizations are required to overcome limitations regarding incorporation into actin cables in the presence of the ALFA nanobody.

Planned revision: We have already extended applicability of IntAct to another well-known fungal model system, the fission yeast Schizosaccharomyces pombe (S. pombe). We expressed IntAct variants of human β- and γ- actin, budding yeast actin (Sc-IntAct) and fission yeast actin (Sp-IntAct) from an exogenous plasmid under the native S. pombe actin promoter in an S. pombe strain that constitutively expresses the Nb-ALFA-mNG. Live-cell microscopy of S. pombe cells expressing these proteins revealed that all IntAct variants localize to actin patch-like structures located at the cell poles and cell division site (during cytokinesis). These structures show similar dynamics as reported for actin patches of S. pombe previously (Pelham et al., Nat Cell Biol, 2001). These preliminary results suggest that IntAct proteins show a similar localization pattern to only branched actin networks found in the actin patches of S. pombe like we had previously observed for the budding yeast, S. cerevisiae (Fig. S13 in manuscript). The underlying mechanism for this exclusion from linear actin cable network from both budding and fission yeast remain unknown and may represent an inherent specificity and sensitivity of yeast formins. Our current and future experiments will express IntAct variants in absence of the ALFA nanobody and determine the level of incorporation into actin cables, patches, and actomyosin ring.

Planned revision: We have also already performed a quantitative analysis to ascertain the effect of Sc-IntAct expression of cortical actin patch dynamics which represent sites of endocytosis in yeast (Young et al., J Cell Biol, 2004; Winter et al., Curr Biol, 1997). We compared actin cortical patch lifetimes between wildtype cells and cells expressing Sc-Act1 or Sc-IntAct as an extra copy. We used Abp1-3xmcherry as a marker for actin patches and quantified the time window between the appearance and disappearance of a patch (actin patch lifetime) from time-lapse microscopy experiments. Our preliminary results indicate that actin patch lifetimes are unaffected by exogenous expression of both Sc-Act1 or Sc-IntAct suggesting that IntAct does not negatively influence or alter actin patch dynamics. These observations suggest its applicability as a direct visualization strategy for actin at the cortical patches in budding yeast alongside existing surrogate markers like Abp1, Arc15, etc (Goode et al., Genetics, 2015; Wirshing et al., J Cell Biol, 2023).

__Reviewer #3 (Evidence, reproducibility and clarity (Required)): __

*Summary: *

This paper tackles a new strategy to tag actin in cells, by identifying that incorporation of a tag of moderate size in subdomain 4 of actin minimally affects actin dynamics in cells, and does not perturb its interaction with known partners, as observed in pull-down assays.

*Major comments: *

The paper is interesting and experiments are convincing.

*My main concerns are the following : *

- Varland et al, is reporting a phosphorylation on Thr229 : I think the authors should mention and discuss this potential PTM that could be affected in IntAct.

We thank the Reviewer for pointing this out. We are aware of this review that includes phosphorylation on Thr229 as a possible PTM. Yet, this PTM is only reported in one of the Tables of the Review and not further discussed in the text. It is also unclear how the authors determined that Thr229 is a possible phosphorylation site except for the notion that this residue is a threonine and exposed at the surface of the actin molecule. Together with the fact that there is no evidence from primary studies that Thr229 is phosphorylated, we therefore decided to not include it in our discussion.

- The sequence in subdomain 4 (the alpha helix containing T229A230) is extremely conserved in animals, as well as in between the 6 human actin isoforms. This usually indicates a strong selection pressure on the residues. I think the authors should discuss how surprising it is that the T229A230 position can accomodate various tags while it is probably the place of interaction with other proteins and is playing an important role in the mechanical structural integrity of the actin itself.

We thank the Reviewer for bringing up this important point. To a certain extent, the conservation argument is true for all of the residues/domains in actin. Any manipulation will change a conserved part of the actin molecule in one way or another and thereby potentially modify its function. This is also evident from the fact that for most of the internally tagged actins, we observed a very poor colocalization with the actin cytoskeleton (Fig. 1). While for the T229/A230, we have not observed any major effects yet, this certainly does not mean that no further changes or defects will be uncovered in future experiments. Nonetheless, since our approach is unique with respect to the fact that it allows isoform-specific tagging without manipulating the N-terminus, our internal tagging system complements the already existing repertoire of actin reporting methods (N-terminal fusion, Lifeact, F-Tractin, actin nanobodies) and allows researchers to study so far unknown properties of actin variants. We have already included in the discussion that, at this point, we can only speculate as to why this variant performs much better than the others (Page 16 of the manuscript) and that possible explanations are the location at the inner domain and the higher structural plasticity of this region as compared to the rest of the molecule, as found during an alanine mutagenesis screen (Rommelaere et al., Structure, 2003).

- It is now well established that actin plays active and important roles in the nucleus : is ALFA-actin correctly translocated to the nucleus ?

Planned revision: This is an interesting suggestion. We will perform nuclear-cytosol fractionation experiments and determine whether ALFA-actin is still correctly translocated to the nucleus.

*- OPTIONAL: one may regret that there is no classical in vitro assays, such as pyrene assays to assess some kinetcis parameters on epitope-tagged actins. I guess this would make the paper a bit too large. Although, it will prove useful to better understand how much formin activity is affected (see below) *

For further biochemical characterization and a detailed investigation of the precise assembly kinetics of the tagged actins, we (KD, SP) are already working together to set up in vitro reconstitution experiments. Yet, as also indicated by the Reviewer, we consider these experiments outside of the scope of the current work.

*Minor comments: *

Below are points that could be addressed by the authors to improve the manuscript readability and highlight some important points that are sometimes missing or are not properly discussed:

-line 40 "...but the distinct N-terminal epitope is not available under native conditions preventing" is a bit too obscure. Can the authors say clearly what is meant by 'native conditions'?

In our understanding, the term ‘native’ is generally used when referring to conditions in which proteins are in their natural state, without alterations due to heat or denaturants, and possibly also still interacting with their binding partners. We will rephrase to better indicate that in this specific case, we mean that the region that harbors the N-terminus is usually occupied by actin-binding proteins, preventing the binding of the antibody due to steric hindrance.

- figure 1A : make a clearer correspondance between the number shown in panel A and the amino acid numbers displayed in panel C and G.

Planned revision: This is a good point, we will add extra annotation in the graph to better link the panels with each other. We will also add additional annotation in Fig. 1D-F for the same purpose.

- figure 1A : it could be informative to indicate subdomains in this panel.

Planned revision: We will add the numbers for the subdomains in Fig. 1A.

- figure 1C : normalized correlation cell : I am not sure I understand how the normalization of the Pearson coefficient is done. It is therefore not clear how can it >1 or >-1 ? This should be clearly explained in the method section of the paper.

__Planned revision: __We will better explain the normalization procedure in the Methods section.

- figure S4 : comes a bit too early when ALFA-actin has not been yet introduced in the main text. Please, reposition this part or provide data with the FLAG-tag version.

Planned revision: This is a good point and completely overlooked by us. We will introduce this Figure later such that the ALFA tag is already introduced.

- section starting line 121 : this section should be better motivated = Why are different tags being tested ? This comes later in the discussion, but the reader fails at following the reasoning/motivation here.

Planned revision: We will add extra motivation for why we added multiple tags.

- figure 2D, line 145 "We also evaluated actin protein expression in the homozygous ALFA-β-actin cells and this showed that the total amount of β-actin was slightly lower in the ALFA-β-actin cells compared to parental HT1080 cells (Fig. 2C-D)." 'Slightly' is not a very quantitative nor accurate term. please rephrase. Besides, a statistical test for the paired data would also be informative. Besides, data in figure S6B-D indeed show a correlated increase in the expression of Gamma-actin that compensate for the decrease in the Beta-actin level in ALFA-Beta-actin. Can the authors explain why they conclude otherwise?

Planned revision: This indeed is an important point and we will change the phrasing of this section to provide a more quantitative and accurate description of the western blot quantifications.

- figure S7B: I am not ure anyone has ever reported measurement of angle of branched actin filament using epifluorescence microscopy. I would remove this panel, or the authors should explain how this measurement can be done objectively.

We apologize for this misapprehension from our side which is also noted by the other two reviewers. In the treadmilling videos of the lamellipodia in HT1080 cells, which were obtained using Airyscan super-resolution microscopy, we clearly observe a consistent filament formation at a constant angle, something which we interpreted as the angle between the mother filament and the daughter filament. After consulting the literature, we indeed have to admit that this cannot be interpreted as such and we will remove these datasets.

Planned revision: We will remove the datasets with the angle measurements (Suppl. Fig. 7A-B) from our manuscript.

*- Figure 2F : can the authors comment on the (significant ?) lower value for FLAG-tag actin ? *

The lower value for FLAG-tag actin has likely to do with the properties of the antibody and suitability for immunofluorescence. For reason that we do not know, we usually detect more background for the FLAG tag antibody as compared to the other antibodies/ALFA tag nanobody. Since the Pearson correlation coefficient quickly decreases with suboptimal labeling, this is likely the reason that the values for FLAG-actin are lower as compared to the other tagged actins. Importantly, in our biochemistry experiments (F/G-actin), we detect no difference between FLAG-actin and ALFA-actin indicating that it is rather the immunofluorescence and sensitive Pearson correlation analysis than the integration of actin that causes this difference.

- line 205 "The results from these experiments show that both DIAPH1 and FMNL2 associate with ALFA-β-actin (Fig. 3D),". It is not so obvious that these formins directly interact with monomeric actin via their FH2 domains in co-immunoprecipitation assays. It might very well be mediated by the interaction with profilin, that in turn bind to the FH1 domain of formins. For me, this assay does not make a correct proof that epitope-labelled actin do not interfere with formin activity.

Planned revision: The point that the co-immunoprecipitation does not demonstrate direct interactions between formins and actin is well taken. We, however, do not claim that this assay proofs that formin activity, or formin-based integration of actin monomers, is similar with tagged actin as compared to wildtype actin. Nonetheless, we will critically re-evaluate the relevant passages and rephrase the text to avoid any confusion.

- figure 5C&D : both graph should use the same scale for the y-axis for easier comparison.

Planned revision: We will adapt the scale of Fig. 5D to make it identical to Fig. 5C. Following the other suggestions of the Reviewer (and of Reviewer #1), we will also critically evaluate our normalization procedure and present those numbers in the Figures if the values turn out to be different.

- figure 5D: I think the way the ratio is performed is misleading. Why not look at the Beta/Gamma ratio using the isoform specific antibodies used in parental cells, and show the results for ALFA-Beta-actin and for ALFA-Gamma-actin separately ?

We kindly refer to our answer to Reviewer #1 on Page 2 for a detailed explanation on the experimental challenge of comparing the localization of wildtype and tagged actin isoforms.

Planned revision: We will critically evaluate our normalization procedure and present those numbers in the Figures if the values turn out to be different. Furthermore, we will add a different experimental method to show that the tagged isoforms properly localize to actin-based structures. For this, we will attempt to use micropatterned cells to induce clearly define actin-bases structures and also explore the possibilities of investigating the differential localization in double-tagged cells.

*- The limitation observed for unbranched cables in yeast that nanobody-tagged ALFA-actin does not incorporate correctly should be discussed and stressed further in the discussion, as it might prove to be a strong limitation for live-cell imaging to reliably study any type of actin networks. *

We acknowledge the reviewer’s concern regarding the inability of ALFA-tagged actin to incorporate into yeast actin cables when NbALFA is co-expressed and will discuss this point further in the revised manuscript. We have now observed the same limitation for fission yeast actin cables as well and combined, these observations may represent a tighter control and sensitivity of yeast formins towards any perturbations in actin size (since NbALFA binds to ALFA tag with picomolar affinity). To address this issue and as also suggested by Reviewer 1, we are now creating yeast strains with inducible control of NbALFA expression under GALS/GAL1 promoters and observe the labelling of actin structures after this approach. Additionally, expression of variants of NbALFA with high dissociation rates may also allow labelling of actin cables and would be certainly worth a try in the future. A structural comparison between mammalian and yeast formins may be required to shed some light on the molecular basis of this fundamental difference.

However, since in the absence of the nanobody, this limitation is overcome (Fig. 5E, Suppl. Fig. 14), we believe that with additional modifications and fast developments in imaging technologies, this limitation can be overcome in the future. Thus, IntAct as a labeling strategy represents an advancement over existing labelled actins with the most important aspect being the identification of the T229/A230 residue pair to be permissive for integration of various tags even as large as GFP11 fragment including a linker (26AA) (Reviewer Fig. 2). Importantly, the T229/A230 site is conserved across many organisms (such as Chlamydomonas reinhardatii, Cryptococcus neoformans, etc) and may act as a framework to study the actin cytoskeleton especially in organisms where known surrogate markers like phalloidin and Lifeact may not work or work only sub optimally.

*Reviewer #3 (Significance (Required)): *

*General assessment: *

*This paper provides a new tagging strategy to monitor actin activity in cells, by specifically inserting the tag along the amino acid sequence. *

*Advance: *

*This is a very useful tool, as most existing available probes bind to actin in regions that are common to many other actin binding proteins. The authors provide extensive experiments to validate that tagged-actin are functional and do not perturb the actin expression level, actin network architecture nor dynamics. *

*Audience: *

*This research paper will be of interest to a rather broad audience (many cell biologists) that are either sutyding actin dynamics or know that actin is involved in the cell functions they study. *

*Expertise: *

*My expertise is in vitro actin biochemistry. *

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

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Referee #3

Evidence, reproducibility and clarity

Summary:

This paper tackles a new strategy to tag actin in cells, by identifying that incorporation of a tag of moderate size in subdomain 4 of actin minimally affects actin dynamics in cells, and does not perturb its interaction with known partners, as observed in pull-down assays.

Major comments:

The paper is interesting and experiments are convincing.

My main concerns are the following :

• Varland et al, is reporting a phosphorylation on Thr229 : I think the authors should mention and discuss this potential PTM that could be affected in IntAct.
• The sequence in subdomain 4 (the alpha helix containing T229A230) is extremely conserved in animals, as well as in between the 6 human actin isoforms. This usually indicates a strong selection pressure on the residues. I think the authors should discuss how surprising it is that the T229A230 position can accomodate various tags while it is probably the place of interaction with other proteins and is playing an important role in the mechanical structural integrity of the actin itself.
• It is now well established that actin plays active and important roles in the nucleus : is ALFA-actin correctly translocated to the nucleus ?
• OPTIONAL: one may regret that there is no classical in vitro assays, such as pyrene assays to assess some kinetcis parameters on epitope-tagged actins. I guess this would make the paper a bit too large. Although, it will prove useful to better understand how much formin activity is affected (see below)

Minor comments:

Below are points that could be addressed by the authors to improve the manuscript readability and highlight some important points that are sometimes missing or are not properly discussed :

• line 40 "...but the distinct N-terminal epitope is not available under native conditions preventing" is a bit too obscure. Can the authors say clearly what is meant by 'native conditions' ?
• figure 1A : make a clearer correspondance between the number shown in panel A and the amino acid numbers displayed in panel C and G.
• figure 1A : it could be informative to indicate subdomains in this panel.
• figure 1C : normalized correlation cell : I am not sure I understand how the normalization of the Pearson coefficient is done. It is therefore not clear how can it >1 or >-1 ? This should be clearly explained in the method section of the paper.
• figure S4 : comes a bit too early when ALFA-actin has not been yet introduced in the main text. Please, reposition this part or provide data with the FLAG-tag version.
• section starting line 121 : this section should be better motivated = Why are different tags being tested ? This comes later in the discussion, but the reader fails at following the reasoning/motivation here.
• figure 2D, line 145 "We also evaluated actin protein expression in the homozygous ALFA-β-actin cells and this showed that the total amount of β-actin was slightly lower in the ALFA-β-actin cells compared to parental HT1080 cells (Fig. 2C-D)." 'Slightly' is not a very quantitative nor accurate term. please rephrase. Besides, a statistical test for the paired data would also be informative. Besides, data in figure S6B-D indeed show a correlated increase in the expression of Gamma-actin that compensate for the decrease in the Beta-actin level in ALFA-Beta-actin. Can the authors explain why they conclude otherwise ?
• figure S7B: I am not ure anyone has ever reported measurement of angle of branched actin filament using epifluorescence microscopy. I would remove this panel, or the authors should explain how this measurement can be done objectively.
• Figure 2F : can the authors comment on the (significant ?) lower value for FLAG-tag actin ?
• line 205 "The results from these experimentsshow that both DIAPH1 and FMNL2 associate with ALFA-β-actin (Fig. 3D),". It is not so obvious that these formins directly interact with monomeric actin via their FH2 domains in co-immunoprecipitation assays. It might very well be mediated by the interaction with profilin, that in turn bind to the FH1 domain of formins. For me, this assay does not make a correct proof that epitope-labelled actin do not interfere with formin activity.
• figure 5C&D : both graph should use the same scale for the y-axis for easier comparison.
• figure 5D: I think the way the ratio is performed is misleading. Why not look at the Beta/Gamma ratio using the isoform specific antibodies used in parental cells, and show the results for ALFA-Beta-actin and for ALFA-Gamma-actin separately ?
• The limitation observed for unbranched cables in yeast that nanobody-tagged ALFA-actin does not incorporate correctly should be discussed and stressed further in the discussion, as it might prove to be a strong limitation for live-cell imaging to reliably study any type of actin networks.

Significance

General assessment:

This paper provides a new tagging strategy to monitor actin activity in cells, by specifically inserting the tag along the amino acid sequence.

Advance:

This is a very useful tool, as most existing available probes bind to actin in regions that are common to many other actin binding proteins. The authors provide extensive experiments to validate that tagged-actin are functional and do not perturb the actin expression level, actin network architecture nor dynamics.

Audience:

This research paper will be of interest to a rather broad audience (many cell biologists) that are either sutyding actin dynamics or know that actin is involved in the cell functions they study.

Expertise:

My expertise is in vitro actin biochemistry.

Not everyone values the same exact things. Each human being sees, feels, and reacts differently. I think Percy is trying to explain that we as humans value different things based on the relativity that it has to us. For some they value the Grand Canyon because that's what they like and some value insulin because that's what they need.

I think stereotyping is also another way to think of this. We can't always assume we know someone by how they present themselves because then when we try to know them, our preconceived notions are thrown off. If we don't try to break out of the mold, break out of comfort, then we may always be under control of stereotypes and what others assume of us.

This concept was something I felt I related to personally while reading. I have spent the last 4 years working as a full time paraprofessional/teaching assistant...3 years in first grade and one year in kindergarten. Reading this segment brought me back to my time spent in a classroom, and I almost immediately thought of a particular student who fit this scenario very well. This student would at times act out and of course, wanting to maintain classroom rules, we would correct this behavior. At first glance many would think this was the appropriate thing to do. But as the year went on we discovered the more we responded to these negative behaviors, the more he did them. Psychologically, he knew that if he misbehaved, he would get a reaction from us. He didn't seem to care whether it was a negative or positive one, he was just initiating behaviors he knew would get a reaction, which this portion of text highlights and I enjoyed being able to read something that I felt I could personally connect to.

I chose to comment on this particular portion of text, because I do not believe there is such a thing as a good or bad teacher. I believe instead of using the term "good teacher" we should instead practice labeling educators as "knowledgable". For example, instead of saying Miss McGuire is a really good teacher, we could say she is a very knowledgable teacher. Everyone has a different definition of what a good teacher is, and by looking at how knowledgable they are on current teaching practices or how knowledgable they are about successful classroom management skills, it separates the idea of being good vs bad simply because they don't teach something the way their observer or peers may.

Author Response

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

We would like to thank both reviewers and the editor for their time and effort in carefully reviewing and comprehending our manuscript. We are grateful for their thorough assessment, as well as the insightful questions and suggestions they have provided. We have taken into account the questions and comments raised by the reviewers, and we have incorporated the necessary revisions accordingly. In the following pages the reviewers’ comments are italicized. Our replies are in normal script.

In addition to revisions suggested by reviewers we also added a new summary schematic (Fig 8) and minor changes to acknowledgments.

Reviewer 1

This is a very strong study with few concerns. Regarding DN1+ T cell function, the authors assessed IFN-γ and activation markers, but it is unclear if the cells are polyfunctional (produced high levels of other cytokines at 6 weeks) or if there were changes in the humoral response (serum Ab titers or size/ number of germinal centers.)

Thank you for your thorough assessment of our work and your kind comments.

a. We observed a decreased IFN-γ and TNF-α production in antigen experienced DN1 T cells compared to naïve DN1 T cells, which is consistent with findings in Tfh cells.

b. We tested for anti-MA IgM and IgG production but did not observe an increase in these antibodies in the vaccinated setting. It is possible that additional inflammatory stimulation, such as from an adjuvant or infection, may be necessary to trigger sufficient antibody level for detection using ELISA.

c. We did not measure the number or size of germinal centers in this study, but future investigations could explore this aspect.

Reviewer 2

1. Authors elaborate the introduction solely highlighting the relevance of antigen persistence in the context of vaccination. However, it is well known that several mycobacterial antigens (Lipids and proteins) can cause detrimental responses when overexposed to the immune system. In this regard, it would be appropriate to introduce the possibility of the occurrence of exhaustion when prolonged exposure to antigens is happening, which is the main theme of this paper.

Thank you for bringing these points to our attention. We have added a paragraph in the discussion section (page 15-16, line 372-386), addressing the implications of our findings in relation to exhaustion in the context of antigen persistence during chronic viral infections. We have also provided an example involving the lipid trehalose 6,6’-dibehenateled (TDM), a known virulence factor for Mtb, which has been utilized in several subunit vaccines without demonstrating significant toxicity.

1. Authors need to provide more information about the source of MA. It is briefly mentioned in the materials and methods section that it was obtained from Sigma. If that is the case, it would be ideal to show the integrity of the polysaccharide in term of balance and abundance between different MA species.

We obtained M. tuberculosis MA from Sigma, which comprises α-, keto-, and methoxy MA forms with an average combined lipid tail length of 80 carbons. MA-specific T cells preferentially recognize these three forms of MA have been identified in humans. We have provided more detailed information regarding the MA in the Materials and Methods section (page 17, line 429-431).

1. Building up on the previous comment, MA is a complex mixture of polysaccharides including multiple lengths of fatty acids and modifications. Could the authors comments on the potential variability of MA structure and potential impact on immune responses?

The binding capacities of Group 1 CD1-restricted T cells can be influenced by various factors, including specific head groups, lipid tail length, and structure of the lipid tail. Notably, DN1 T cells have been shown to have higher binding affinities towards keto and methoxy MA, while displaying weaker binding to α-MA (Van Rhijn et al., 2017, Eur. J. Immunol. 47:1525). In our study, we successfully utilized a mixture of MA to activate DN1 T cells, indicating that the required subtypes of MA were present in sufficient quantities to elicit this activation. In future investigations focusing on the polyclonal immune response, incorporating a mixture of MA and possibly other Mtb lipid antigens will enable a broader spectrum of T cell activation. This, in turn, is expected to enhance the overall effectiveness and robustness of protection in challenge experiments.

1. How do the authors explain the lack of stimulation of cell proliferation induced by MA-PLGA formulation? Does this result contradict previous findings?

This study represents the first instance of utilizing PLGA as a delivery system for a lipid antigen via a pulmonary vaccine route, despite its previous applications in numerous other vaccine formulations. Therefore, we do not think our findings contradicts any existing research in the field. It is worth noting that the immunogenicity of PLGA can be influenced by the specific polymer chemistry and formulation, which may account for potential variations in the observed effects. We have added additional text to the discussion (page 13, line 310 – 313) to address this point.

1. Fig 3. Authors switch to IT administration simply arguing against the limitation of IN delivery regarding its low volume. However, administration via IN could be done in an iterative manner. According to this change, this reviewer asks whether the performance of MA-PLGA could now be comparable to BCN-MA using IT instead.

PLGA possesses an inherent background adjuvant effect, which may not be ideal for precisely stimulating group 1 CD1-restricted T cells, as a considerable proportion of these T cells exhibit some level of autoreactivity (Li, et al, 2011, Blood 118:3870, De Lalla et al., 2011, Eur. J. Immunol. 41:602; de Jong et al, 2010, Nat. Immunol. 11:1102). Notably, our observations revealed that blank PLGA-NP exerted a significant stimulatory effect on both mouse (DN1) and human (M11) MA-specific T cells (Fig. 2A-D). This underscores the advantage of the BCN system, which lacks detectable adjuvant effects and enables a more controlled, dose-dependent augmentation of T cell responses with increasing concentrations of loaded MA. Therefore, we did not further evaluate the impact of PLGA-MA using the IT route of vaccination.

1. What would be the reasons of the no role of encapsulating NP in the persistence of MA?

In this study, we have provided evidence to support the notion that encapsulation plays a role in antigen persistence, as demonstrated in Fig. 5A-C. Specifically, we directly compared the persistence of MA when delivered encapsulated in BCNs versus without encapsulation in BCNs, using DC pulsing and IT vaccination as the delivery methods. Our results indicate that at 6 weeks post-vaccination, MA encapsulated in BCNs can activate DN1 T cells, while free MA does not. These findings may initially appear to be contradictory to those depicted in Fig. 5D-F, where antigen persistence is observed following vaccination with attenuated Mtb. However, we propose that the attenuated Mtb bacteria may function similarly to nanoparticles by encapsulating and containing MA, thereby facilitating its persistence within the host. We appreciate the opportunity to clarify these points (page 15, line 364-367). Encapsulation within PEG-PPS NP may also contribute to two additional mechanisms. First, we have demonstrated that PEG-PPS NPs target myeloid cell populations (Burke et al., 2022, Nat. Nano. 17:319), such as alveolar macrophages, that can serve as antigen persistence depots as well as present CD1b/MA complexes on their surfaces. NPs allow more efficient delivery to these cells, whereas otherwise the lipid would bind to albumin, HDL, LDL, and other lipid carriers in blood for a broader, non-specific biodistribution, which would include cells less efficient at antigen persistence or presentation. Second, we previously demonstrated that the BCN nanostructure is highly stable within cells, supporting a slow intracellular release (Bobbala et al., 2020, Nanoscale 12:5332). This could assist with a more sustained presentation of lipid antigen by targeted cells in contrast to free form lipid or NPs (like PLGA) that rapidly degrade within cells. Indeed, low levels of fluorescently tagged BCNs were still detectable 6 weeks post-vaccination (Fig. 6B). Our future studies will further investigate this hypothesis.

1. Authors need to discuss to what extent the MA location into AM is route dependent.

The localization of MA within alveolar macrophages (AMs) in the lung is likely specific to intratracheal (IT) vaccination. Therefore, mice vaccinated subcutaneously (SC) or intravenously (IV) may possess distinct antigen persistence depots. We have made modifications to the discussion section to further emphasize this point (page 15, line 359-364).

1. Also, AM are programmed to sustain low immune responses because of their unique location in the lung. In fact, Mtb uses this to replicate while immune response is mounted. In this regard, accumulation of MA into this compartment may not be relevant for the overall immune response. In other words, what would be the contribution of this population to the T cell activation?

It is likely that AMs primarily function as antigen depots and do not directly contribute to the activation of DN1 T cells. This assertion is supported by our findings, as co-culturing AMs with DN1 T cells alone did not result in T cell activation (Fig. 6E). However, we observed that the presence of hCD1Tg-expressing bone marrow-derived dendritic cells was necessary for DN1 T cell activation in vitro, which likely reflects a similar phenomenon occurring in vivo.

1. Could the T cells responses measured be due to the reduced fraction of DC loaded with BCN-MA at initial time points?

Regarding the T cell response observed in Fig. 5A-C, where we used DCs to deliver either free MA or MA-BCN, we took steps to address potential differences in loading capacity between the two at initial time points. Specifically, DCs were pulsed with a concentration of 10 𝜇g/mL for free MA and 5 𝜇g/mL of MA-BCN (the figure legend has been modified to clarify this point, page 37, line 962 - 963). To ensure approximate equivalence in loading, we examined the immune response one week after vaccination and found no statistically significant difference between the two methods.

Reviewer #1 (Public Review):

Murphy, Fancy and Skene performed a reanalysis of snRNA-seq data from Alzheimer Disease (AD) patients and healthy controls published previously by Mathys et al. (2019), arriving at the conclusion that many of the transcriptional differences described in the original publication were false positives. This was achieved by revising the strategy for both quality control and differential expression analysis. I believe the authors' intention was to show the results of their reanalysis not as a criticism of the original paper (which can hardly be faulted for their strategy which was state-of-the-art at the time and indeed they took extra measures attempting to ensure the reliability of their results), but primarily to raise awareness and provide recommendations for rigorous analysis of sc/snRNA-seq data for future studies.

STRENGTHS:

The authors demonstrate that the choice of data analysis strategy can have a vast impact on the results of a study, which in itself may not be obvious to many researchers.

The authors apply a pseudobulk-based differential expression analysis strategy (essentially, adding up counts from all cells per individual and comparing those counts with standard RNA-seq differential expression tests), which is (a) in line with latest community recommendations, (b) different from the "default options" in most popular scRNA-seq analysis suites, and (c) explains the vastly different number of DEGs identified by the authors and the original publication. The recommendation of this approach together with a detailed assessment of the DEGs found by both methodologies could be a useful finding for the research community. Unfortunately, it is currently not fully substantiated and is confounded with concurrent changes in QC measures (see weaknesses).

The authors show a correlation between the number of DEGs and the number of cells assessed, which indicates a methodological shortcoming of the original paper's approach (actually, the authors of the original paper already acknowledged that the lesser number of DEGs for rare cell types was a technical artefact). To be educational for the reader it would be important to provide more information about the DEGs that were "found" and those that were "lost". Given vast inter-individual heterogeneity in humans, it is likely that the study was underpowered to find weaker differences using the pseudobulks (Fig. 1B shows that only genes with more than 4-fold change were found "significant").

All code and data used in this study are publicly available to the readers.

WEAKNESSES:

The authors interpret the fact that they found fewer DEGs with their method than the original paper as a good thing by making the assumption that all genes that were not found were false positives. However, they do not prove this, and it is likely that at least some genes were not found due to a lack of statistical power and not because they were actually "incorrect". The original paper also performed independent validations of some genes that were not found here.

I am concerned that the only DEGs found by the authors are in the rare cell types, foremost the rare microglia (see Fig. 1f). It is unclear to me how many cells the pseudo-bulk counts were based on for these cells types, but it seems that (a) there were few and (b) there were quite few reads per cells. If both are the case, the pseudobulk counts for these cell populations might be rather noisy and the DEG results are liable to outliers with extreme fold changes.

The authors claim they improved the quality control of the dataset. While I do not think they did anything wrong per se, the authors offer no objective metric to assess this putative improvement. This is another major weakness of the paper as it confounds the results of the improved (?) differential analysis strategy and dilutes the results. I detail this weakness in the two following points:

Removing low-quality cells: The authors apply a new QC procedure resulting in the removal of some 20k more cells than in the original publication. They state "we believe the authors' quality control (QC) approach did not capture all of these low quality cells" (l. 26). While all the QC metrics used are very sensible, it is unclear whether they are indeed "better". For instance, removal with a mitochondrial count of <5% seems harsh and might account for a large proportion of additional cells filtered out in comparison to the original analysis. There is no blanket "correct cutoff" for this percentage. For instance, the "classic" Seurat tutorial https://satijalab.org/seurat/articles/pbmc3k_tutorial.html uses the 5% threshold chosen by the authors, an MAD-based selection of cutoff arrived at 8% here https://www.sc-best-practices.org/preprocessing_visualization/quality_control.html, another "best practices" guide choses by default 10% https://bioconductor.org/books/3.17/OSCA.basic/quality-control.html#quality-control-discarded, etc. Generally, the % of mitochondrial reads varies a lot between datasets. As far as I can tell, the original paper did not use a fixed threshold but instead used a clustering approach to identify cells with an "abnormally high" mitochondrial read fraction. That also seems reasonable. Overall, I cannot assess whether the new QC is really more appropriate than the original analysis and the authors do not provide any evidence in favor of their strategy.

Batch correction: "Dataset integration has become a standard step in single-cell RNA-Seq protocols" (l. 29). While it is true that many authors now choose to perform an integration step as part of their analysis workflow, this is by no means uncontroversial as there is a risk of "over-integration" and loss of true biological differences. Also, there are many different methods for dataset integration out there, which will all have different results. More importantly, the authors go on "we found different cell type proportions to the authors (Fig. 1a) which could be due to accounting for batch effects" but offer no support for the claim that the batch effects are indeed related to the observed differences. An alternative explanation would be a selective loss/gain of certain cell types during quality control. The original paper stated concerns about losing certain cell types (microglia, which do not seem to be differentially abundant in the original paper / new analysis).

Relevant literature is incompletely cited. Instead of referring to reviews of best practices and benchmarks comparing methods for batch correction and or differential analysis, the authors only refer to their own previous work.

Due to a lack of comparison with other methods and due to the fact that the author's methodology was only applied to a single dataset, the paper presents merely a case study, which could be useful but falls short of providing a general recommendation for a best practice workflow.

APPRAISAL:

The manuscript could help to increase awareness of data analysis choices in the community, but only if the superiority of the methodology was clearly demonstrated. The recommended pseudobulk differential expression approach along with the indication of drastic differences that this might have on the results is the main output of the current manuscript, but it is difficult to assess unequivocally how this influenced the results because the differential analysis comes after QC and cell type annotation, which have also been changed in comparison to the original publication. In my opinion, the purpose of the paper might be better served by focusing on the DE strategy without changing QC and instead detailing where/how DEGs were gained/lost and supporting whether these were false positives.

Reviewer #1 (Public Review):

Summary: This paper performs fine-mapping of the silkworm mutants bd and its fertile allelic version, bdf, narrowing down the causal intervals to a small interval of a handful of genes. In this region, the gene orthologous to mamo is impaired by a large indel, and its function is later confirmed using expression profiling, RNAi, and CRISPR KO. All these experiments are convincingly showing that mamo is necessary for the suppression of melanic pigmentation in the silkworm larval integument.

The authors also use in silico and in vitro assays to probe the potential effector genes that mamo may regulate.

Strengths: The genotype-to-phenotype workflow, combining forward (mapping) and reverse genetics (RNAi and CRISPR loss-of-function assays) linking mamo to pigmentation are extremely convincing.

Weaknesses:

1) The last section of the results, entitled "Downstream target gene analysis" is primarily based on in silico genome-wide binding motif predictions.<br /> While the authors identify a potential binding site using EMSA, it is unclear how much this general approach over-predicted potential targets. While I think this work is interesting, its potential caveats are not mentioned. In fact the Discussion section seems to trust the high number of target genes as a reliable result. Specifically, the authors correctly say: "even if there are some transcription factor-binding sites in a gene, the gene is not necessarily regulated by these factors in a specific tissue and period", but then propose a biological explanation that not all binding sites are relevant to expression control. This makes a radical short-cut that predicted binding sites are actual in vivo binding sites. This may not be true, as I'd expect that only a subset of binding motifs predicted by Positional Weight Matrices (PWM) are real in vivo binding sites with a ChIP-seq or Cut-and-Run signal. This is particularly problematic for PWM that feature only 5-nt signature motifs, as inferred here for mamo-S and mamo-L, simply because we can expect many predicted sites by chance.

2) The last part of the current discussion ("Notably, the industrial melanism event, in a short period of several decades ... a more advanced self-regulation program") is flawed with important logical shortcuts that assign "agency" to the evolutionary process. For instance, this section conveys the idea that phenotypically relevant mutations may not be random. I believe some of this is due to translation issues in English, as I understand that the authors want to express the idea that some parts of the genome are paths of least resistance for evolutionary change (e.g. the regulatory regions of developmental regulators are likely to articulate morphological change). But the language and tone is made worst by the mention that in another system, a mechanism involving photoreception drives adaptive plasticity, making it sound like the authors want to make a Lamarckian argument here (inheritance of acquired characteristics), or a point about orthogenesis (e.g. the idea that the environment may guide non-random mutations).<br /> Because this last part of the current discussion suffers from confused statements on modes and tempo of regulatory evolution and is rather out of topic, I would suggest removing it.

In any case, it is important to highlight here that while this manuscript is an excellent genotype-to-phenotype study, it has very few comparative insights on the evolutionary process. The finding that mamo is a pattern or pigment regulatory factor is interesting and will deserve many more studies to decipher the full evolutionary study behind this Gene Regulatory Network.

Minor Comment :

The gene models presented in Figure 1 are obsolete, as there are more recent annotations of the Bm-mamo gene that feature more complete intron-exon structures, including for the neighboring genes in the bd/bdf intervals. It remains true that the mamo locus encodes two protein isoforms.<br /> An example of the Bm-mamo locus annotation, can be found at : https://www.ncbi.nlm.nih.gov/gene/101738295<br /> RNAseq expression tracks (including from larval epidermis) can be displayed in the embedded genome browser from the link above using the "Configure Tracks" tool.

Based on these more recent annotations, I would say that most of the work on the two isoforms remains valid, but FigS2, and particularly Fig.S2C, need to be revised.

I think it is good we are realizing police can not do everything just like a DR or a nurse does not do everything. yes you can have a general practitioner but there is still tasks and jobs they don't do. I feel this same strategy with police would allow them to specialize in certain cases where it may be needed. or have others who are more proficient complete those tasks

I remember when YouTube had to do something about fake news after the big event on January 6th. They made rules to take down videos with false information. That's good because we want to know the right stuff. Also, TikTok gives users content creation freedom and more freedom of speech, and we can make our own videos and say what we think. But sometimes, that can also be a problem. Since we can post anything, some things might not be true. Like, gossip about famous people or even important things like politics. TikTok does not always check if things are real before they spread however, I do sometimes see warning on the video if the video may cause bodily harm if tried to perform at home.

This part of the article really caught my attention. I'm 28, I remember a time when social media was almost nonexistent. I think it was really interesting watching social media platform become a staple. I can definitely relate to the sentence, "... (digital natives) grew up in the information age...", because that how I viewed the online word. If I wanted to learn about something new or keep up with topics, I had to search and dig through many websites to find one that I, not only liked but also, trusted.

Social natives may be more interactive in social media and more inclined to socialize on their devices instead of in person. This is my hypothesis because I see a lot of younger people Facetiming and utilizing social media more than I do, and even though I could be as active as them, I am just not as inclined to participate on a more personal account. I would be more inclined to participate promoting a company I work for on social media than interacting with it as much as the younger generation for myself. I think that digital natives may be more skilled at media literacy because they have some background knowledge on what existed before the floods of mass misinformation from social media on platforms like Twitter and Facebook- while seeing how misinformation was perpetuated in the media for the generation older than them.

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

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Reply to the reviewers

We thank the reviewers for their time, the positive reviews and the useful comments. We answer below and explain the changes made to the manuscript. The comments of the reviewers are in italics.

Reviewer #1

1. 'For GWAS, the strains that were fertile after 20 generations were considered non-Mrt.' One aspect of Fig 1D that could be clarified are the dots at generation 21. If these represent strains that were always fertile at generation 21, then perhaps give these a different color to indicate that sterility was never observed?

Response: This is a good idea. We added colors in Figure 1, which makes it clearer.

We also provide a different color for surviving replicates in all relevant figures.

1. 'The mean Mrt values of strains ranged from sterile at 3 generations to fertile after 20 generations at 25°C, with a skewed distribution toward high values (Figure 1B).' Based on Table S2, part of the explanation for this skewed distribution in later generations is that some strains became sterile rapidly for some blocks, whereas the same strain did not become sterile in other blocks. For example, JU1200, JU360, PB303. I suggest providing a second color for Fig. 1D for strains that sometimes displayed sterility and sometimes did not.

__Response: __We now colored the isolates that never became sterile, with the same color code as in panel B. Because we stopped the scoring at G20 and code fertility at G20 as '21', those with a mean below 21 show some sterility in at least one case.

Because the number of generations at which we stopped the phenotyping (20) is arbitrary, the fact a line stayed fertile at 20 generations in one replicate is not very meaningful, especially considering that the number of replicates is not the same for all strains. The key point of the variance graph is to show that the strains with the most variance are those with high but

For those that were sometimes fertile and sometimes sterile, I suggest creating a graph in Figure 1 that shows generations at sterility or lack of sterility, color coded by block. This will allow the significance of strains with high generation Mrt values to be better appreciated for readers who do not look at the supplementary table.

__Response: __Yes, we added this graph in Figure S1. This is indeed useful.

1. The GWAS section could benefit from a simple explanation of the premise of GWAS for non-specialist readers.

__Response: __Yes, we added: "A genome-wide association study (GWAS) is a genetic mapping that uses the natural diversity of a panel of organisms of a given species to test for statistical independence between the allelic state of polymorphic markers and the phenotype of interest (Andersen and Rockman 2022). A statistical association between the marker and the phenotype indicates that a polymorphism tightly linked to the marker in the data (i.e. in linkage disequilibrium with it) causes the variation in phenotype. For statistical reasons, GWAS can only detect polymorphisms that are at intermediate frequencies in the panel, i.e. cases where both alleles occur at frequencies higher than 5%. We only used such polymorphisms in the GWAS (see Methods)."

And further down:

"To diminish the multiple testing burden, the initial analysis in Figure 1E used a restricted set of markers, after pruning those that were in high linkage to each other."

1. One problem might be that the Mrt phenotype is widespread among wild strains. To the authors' credit, they consider results observed in different laboratories as valid, even when the results do not agree. If the Mrt phenotype is influenced by the environment, then some laboratory environments might result in 'false negative' Mrt results that could be ignored in favor of positive results from another lab that appear strong. Might focusing on strains with a set of strong positive results from one lab allow the authors to draw stronger GWAS conclusions?

2. The authors' perform GWAS based on the variance of the Mrt phenotype data. Would the GWAS data be more illuminating if the authors only considered strains that become sterile fairly rapidly, within 10 generations. The authors might then have a second category that included strains that become sterile from generation 11-20. If the genetic basis for the Mrt phenotypes is the same, then GWAS of strains that become sterile in less than 10 generations might yield similar peaks as GWAS for strains that become sterile between generations 11-20.

__Response: __These two comments are strongly related so we answer them together. Note that the GWAS is not mapping the variance values but the Mrt values themselves.

We actually initially only used block 1 (a single replicate, all strains performed in parallel in our laboratory) and also detected the chromosome III association using a categorical variable (threshold at 11), but decided to show the results with all data to maximize power, taking into account the generation value and block effects.

We investigated other ways to code the data (e.g. categorically) and removing the strains of the most variable middle category, as proposed by the reviewer. This changed the p values and the rank of the markers on chromosome III but not the overall result.

In summary, we did a variety of tests, which pointed to chromosome III, a region that was validated using crosses (Figure 2).

Note that in the revision, we updated the GWAS plot and fine mapping table as we noticed a few problems in our previous mapping. 1) We removed 3 isolates that were classified in Lee et al. 2021 as divergent. 2) We included strains that had been lost in the pipeline because their names did not match CeNDR isotypes. This increased the significance of the chromosome III peak.

__Response: __There was no comment 6.

1. 'We did not investigate whether a second locus present in JU775 on the right arm of Chr III might have a lesser effect.'

__Response: __We are not sure what the reviewer meant. Considering the difficulties with the stronger effect locus, we did not try to study loci with a weaker effect.

1. It might be interesting to test the memory of growth on beneficial bacteria on JU4134, which had a Mrt phenotype that was strongly suppressed by the beneficial bacteria.

__Response: __We agree that testing other strains would be useful but given the duration of such experiments (30 generations and two weeks of preparation before), we respectfully decline to perform this experiment that does not seem strictly necessary.

1. The Mrt phenotype of mutants in small RNA inheritance and histone modifying enzymes 'appears however distinct from that of the prg-1/piwi mutant (for which the cause of sterility is debated), especially the latter does not show temperature dependence and is suppressed by starvation.' While it is true that the cause of sterility is debated for the prg-1/piwi mutant, this mutant is defective for small RNA silencing and likely has parallels with some defects in histone modifying enzymes. Anecdotal reports suggest that starvation might affect the Mrt phenotype or longevity of histone modifying enzyme mutants. Moreover, the cause of sterility is not clear for small RNA inheritance and histone modifying enzyme mutants. It is fair to say that the distinction between temperature-sensitivity or lack of temperature sensitivity of small RNA mutants is not understood. Could the authors please comment here about whether any of the wild strains display sterility at 20°C.

__Response: __The temperature-dependence of the wild isolates is progressive between 20-25°C. We previously showed that strains with a very strong Mrt phenotype, such as QX1211, can display sterility at 20°C (Figure 1B in Frézal et al. 2018). However, its Mrt phenotype is still temperature-dependent as the sterility occurs much earlier at 25°C.

1. If intracellular bacteria are simply somatic, then how is it that they are transmitted to progeny. If they are released into the environment and then consumed by hatched larvae, this is soma-to-soma transmission.

__Response: __These microsporidia (which are eukaryotes related to fungi) are indeed transmitted horizontally. To make this clear, we added: "colonizing its intestinal cells and being transmitted horizontally via defecation and ingestion of spores". The soma-to-germline interaction concerns the effect of microsporidia on germline maintenance.

Minor: 1. 'We measured the mortal germline (Mrt) phenotype'. Mortal Germline (Mrt)

__Response: __It is unclear as to whether phenotypes start with a capital letter when they are in full words. We did write phenotypes in previous works with a capital letter but have changed because C. elegans nomenclature rules (https://cgc.umn.edu/nomenclature) suggest that they should not: "Phenotypic characteristics can be described in words, e.g., dumpy animals or uncoordinated animals." For the mortal germline phenotype in particular, we find several ways to write it in articles (with 0, 1 or 2 capital letters, including the three reviewers). We are happy to change it if required.

Reviewer #2

Major comments: The authors claimed that the variants causing Mrt exist at intermediate frequency in the natural population but the evidence supporting this claim is rather limited.

__Response: __Thank you for this comment as it helped us clarify the manuscript.

To better explain the notion of intermediate frequency in the GWAS, we added an explanation of the principle of the GWAS (see above) and again in the Discussion: "The intermediate frequency of the candidate alleles derives from the GWAS approach, which cannot detect rare alleles, such as set-24, that are present in a single strain of the dataset."

We also illustrated the frequency by adding a plot (Fig. 1F) showing the association of the most associated candidate SNP, with a visual depiction of the frequency. We further added in Results: "For SNPs with a high significance (p-4) in the fine mapping, the frequency of the Mrt associated allele was comprised between 21 and 41% in our GWAS strain set (Table S3); as an example, the Mrt allele of the associated SNP shown in Figure 1F (III:4677491) displayed a frequency of 29% in the restricted strain set. Over the global wild strain set with genotypes at CeNDR in 2020, these numbers are 17-58% and 39%, respectively. "

To strengthen the claim, the authors should examine the distribution and frequency (perhaps coupled with phylogenetic analysis) of the Ch III haplotype in the wild isolates. The authors should also examine the GWAS peak for the signature of balancing selection (e.g., dN/dS ratio).

__Response: __Thank you for this comment. The different associated SNPs in Table S3 differ in their allele frequency (Table S3), hence they belong to different haplotypes. We added a supplementary Figure S2 with an analysis of the haplotype structure. Those at a low frequency (around 20%) belong to the same haplotype (e.g. JU775 and MY10) but some associated alleles are present in more haplotypes (40-50%), such as JU1793. Even if we neglect recombination, the history of mutations in the region is complex and there is not a single associated haplotype. We now show the genotypes of these different haplotypes at all SNPs in Table S3. We also added Table S4 that shows the co-occurrence of relevant haplotypes in local populations.

Concerning tests of balancing selection, without knowing the causal polymorphism and linked haplotype, this is far reaching. We only feel confident to say that the causal polymorphism(s) is present at a significant frequency. We added however the fact that irrespective of which polymorphisms are causal, both alleles were found to coexist locally.

Results: relevant text was added at the end of the GWAS section.

Discussion: "The co-occurrence of relevant chromosome III haplotypes on multiple continents and in local populations (Table S4) is suggestive of balancing selection; however, a linked locus other than that causing the Mrt phenotype may be involved."

Does JU775 carry polymorphisms in genes that are known to be involved in Mrt? These genes may genetically interact with the Ch III variant, as suggested by the partial penetrant phenotypes of the introgressed lines. It would be helpful to have a table summarize the variation in these genes.

__Response: __It is difficult to deduce much from a genomic variant analysis, so we refrain from showing tables of polymorphisms beyond that used for the fine GWAS mapping in Table S3. For example, a non-synonymous SNP may or may not alter protein activity and cis-regulatory elements are difficult to assess. Moreover, an obviously null allele may be compensated by another polymorphism in the background. The JU775 alleles and bam files are publically available from CeNDR (Erik Andersen's lab): https://caendr.org/data/data-release/c-elegans/latest

It is curious to me that for experiments with HT115, the expression of the RNAi vectors was induced with IPTG. Is this step necessary? It is known that even the backbone of L4440 could trigger a non-specific RNAi response (PMID: 30838421). I wonder if activating exogenous RNAi response is required for Mrt rescue.

__Response: __Indeed: this experiment was initially aimed at testing RNAi sensitivity of JU775, thus IPTG was added on the plate (Figure 7, panel B). We therefore repeated the memory experiment with OP50 and without IPTG, with a similar result (Figure 7, panel A).

In figure 7, it appears that the worms transferred from MG1655/HT115 to OP50 showed an even stronger rescue (higher Mrt value) than the ones constantly on MG1655/HT115. This suggests to me that fluctuations in food composition may strongly affect epigenetic inheritance. Please clarify as this is very interesting, if true.

__Response: __Note: This answers the comment above (IPTG is not required).

We indeed noticed this strong rescue but do not wish to make a point as we did no attempt to reproduce this result in the exact same conditions. The experiment in panel B does not show this effect.

Optional - Numerous studies have shown that SKN-1 regulates metabolism in response to food composition and availability (PMID: 23040073). Additionally, some recent studies have indicated a role of SKN-1 in epigenetic inheritance triggered by exogenous RNAi. In particular, SKN-1 promotes stress-induced epigenetic resetting (PMID: 33729152). I wonder if SKN-1 modulates Mrt based on bacterial diet.

__Response: __We tested skn-1b/c hypomorphic and gain-of-function mutants in the N2 background on E. coli OP50 and did not see an effect of the skn-1 allele.

Minor comments Line 47: typo "...they defined..."

__Response: __We did mean "thus defined".

Line 100-101: weird sentence structure. Please consider rephrasing.

__Response: __We simplified to "a wild C. elegans strain can keep the memory of its culture on a suppressing bacterial strain."

Line 138-139: I don't quite understand what "intermediate-frequency chromosome III alleles" means here. Some SNPs were found in Ch III 4-6Mb? Please expand.

__Response: __We rephrased to: "because this isolate carries the chromosome III alleles associated in the GWAS analysis with the Mrt phenotype (Table S3)."

Line 213 - it was unclear to me why the assay was performed at 23C instead of 25C. I later learned in the method section that microsporidia cannot be cultured at 25C. I think it will be helpful to add that information when microsporidia is introduced to improve clarity.

__Response: __We added: " We used a temperature of 23°C because these microsporidia kill C. elegans too rapidly at 25°C."

Reviewer #3.

Minor points 1. Could the authors please define "experimental blocks"

__Response: __We added the following sentence in Results: "Each Mrt assay started at a certain date constitutes an experimental block."

1. Legend to supplementary snp table should be completed: define AF, impact, modifier, moderate, AA1, AA2...

__Response: __This is added in the first sheet of the table. We also simplified the table and removed some of these columns.

1. Please define "intermediate-frequency allele"

__Response: __We added in Results: "GWAS can only detect polymorphisms that are at intermediate frequencies in the panel, i.e. cases where both alleles occur at frequencies higher than 5%." We also added below: " "For SNPs with a high significance (p-4) in the fine mapping, the frequency of the Mrt associated allele was comprised between 21 and 41% in our GWAS strain set (Table S3); as an example, the Mrt allele of the associated SNP shown in Figure 1F (III:4677491) displayed a frequency of 29% in the restricted strain set."

1. Figure 7 legend: Authors should be more specific in describing the figure: After 10 (A panel), 13 or 20 generations (B panel) on the K-12 strain... What is E. coli OP50 start 'G10'? the 15° stock?

__Response: __We changed to: " After 10 (A panel), 13 or 20 generations (B panel) on the K-12 strain" and added some details in:

"A control from a 15°C culture maintained without starvation ("15°C stock") was bleached in parallel (labeled "E. coli OP50 start "G10" " in the graph of panel A)."

Optional: Did the authors attempt to rescue the Mrt phenotype with individual metabolites (eg Vit B12...)? These are not straight forward experiments and most likely part of a future study.

__Response: __We indeed tested several metabolites that are known to differ in C. elegans raised on E. coli OP50 versus K-12 strains for their effect on the Mrt phenotype. None was able to rescue the mortal germline phenotype. However, especially in these long multigenerational experiments, it is difficult to know whether the metabolites are stable. We monitored vitamin B12 activity by using an acdh-1::GFP reporter that is known to be repressed by vitamin B12 - so we are confident of this negative result, which we now show in Figure S4. As cell wall lipopolysaccharide (LPS) differ between E. coli K-12 and B strains, we also tested the E. coli LPS mutants, which had no eff

Author Response

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

Reviewer #1 (Public Review):

The cerebral cortex, or surface of the brain, is where humans do most of their conscious thinking. In humans, the grooves (sulci) and bumps (convolutions) have a particular pattern in a region of the frontal lobe called Broca's area, which is important for language. Specialists study features imprinted on the internal surfaces of braincases in early hominins by casting their interiors, which produces so-called endocasts. A major question about hominin brain evolution concerns when, where, and in which fossils a humanlike Broca's area first emerged, the answer to which may have implications for the emergence of language. The researchers used advanced imaging technology to study the endocast of a hominin (KNM-ER 3732) that lived about 1.9 million years ago (Ma) in Kenya to test a recently published hypothesis that Broca's remained primitive (apelike) prior to around 1.5 Ma. The results are consistent with the hypothesis and raise new questions about whether endocasts can be used to identify the genus and/or species of fossils.

We would like to thank Rev. 1 for their comments on our paper.

Reviewer #2 (Public Review):

The authors tried to support the hypothesis that early Homo still had a primitive condition of Broca's cap (the region in fossil endocasts corresponding to Broca's area in the brain), being more similar to the condition in chimpanzees than in humans. The evidence from the described individual points to this direction but there are some flaws in the argumentation.

We are grateful to Rev. 2 for their comments, although we partially agree with some of them.

First, we would like to rectify the statement of Rev. 2 that we “tried to support the hypothesis that early Homo still had a primitive condition of Broca's cap”, indeed, our aim was to test this hypothesis and not to try to validate it.

First, only one human and one chimpanzee were used for comparison, although we know that patterns of brain convolutions (and in addition how they leave imprints in the endocranial bones) are very variable.

We understand the point raised by Rev. 2 about the variation of brain convolutions in humans and chimpanzees. We used atlases published by Connolly (1950), Falk et al. (2018) and de Jager et al. (2019, 2022) to analyse the endocast of KNM-ER 3732 and compare it to the extant human and chimpanzee cerebral conditions. However, in Figure 2, for the sake of clarity only two Homo and Pan specimens were used to illustrate the comparison (as it has been done in other published papers, e.g., Carlson et al., 2011; Science, Gunz et al., 2020 Sci Adv). In the revised version, we modified the manuscript to explain further our approach (line 156) “We used brain and endocast atlases published in Connolly (1950), Falk et al. (2018) and de Jager et al. (2019, 2022; see also www.endomap.org) for comparing the pattern identified in KNM-ER 3732 to those described in extant humans and chimpanzees. To the best of our knowledge, these atlases are the most extensive atlases of extant human and chimpanzee brains/endocasts available to date and are widely used in the literature to explore variability in sulcal patterns. In Figure 2, the extant human and chimpanzee conditions are illustrated by one extant human (adult female) and one extant chimpanzee (adult female) specimens from the Pretoria Bone Collection at the University of Pretoria (South Africa) and in the Royal Museum for Central Africa in Tervuren (Belgium), respectively (Beaudet et al., 2018).”.

Second, the evidence from this fossil specimen adds to the evidence of previously describe individuals but still not yet fully prove the hypothesis.

We tempered our discussion by concluding that (line 116) “Overall, the present study not only demonstrates that Ponce de León et al.’s (2021) hypothesis of a primitive brain of early Homo cannot be rejected, but also adds information […]”.

Third, there is a vicious circle in using primitive and derived features to define a fossil species and then using (the same or different) features to argue that one feature is primitive or derived in a given species. In this case, we expect members of early Homo to be derived compared to their predecessors of the genus Australopithecus and that's why it seems intriguing and/or surprising to argue that early Homo has primitive features. However, we should expect that there is some kind of continuum or mosaic in a time in which a genus "evolves into" another genus. This discussion requires far more discussions about the concepts we use, maybe less discussion about what is different between the two groups but more discussion about the evolutionary processes behind them.

We fully agree with Rev. 2 on this aspect. We believe that identifying these differences/similarities between fossil and extant hominids constitute the first step of a better understanding of the evolutionary mechanisms. Our work suggests indeed a certain continuity between genera and raises questions on the genus concept and how to interpret the specimens currently attributed to early Homo. In the revised version of the manuscript we included a reference to this possible scenario (line 134): “[…] or to the absence of a definite threshold between the two genera based on the morphoarchitecture of their endocasts (Wood and Collard, 1999).”.

Fourth, the data of convolutional imprints presented are rather subjective when identifying which impressions represent which brain convolutions. Not seeing an impression does not necessarily mean that the corresponding brain feature did not exist. Interestingly, the manuscript does not mention and discuss at all the frontoorbital sulcus. This is a sulcus that usually runs from the orbital surface of the frontal lobe up to divide the inferior frontal gyrus in chimpanzees, a condition totally different than in humans who do not have a frontoorbital sulcus. Could such a sulcus be identified, this would provide a far more convincing argument for a primitive condition in this specimen. In Australopithecus sediba, e.g., the condition in this region seems to be a mosaic in which some aspects of the morphology seem to be more modern while one of the sulcual impressions can well be interpreted as a short frontoorbital sulcus. For this specimen, by the way, I would come back to my third point above: some experts in the field might argue that this specimen could belong to Homo rather than Australopithecus...

We agree that the presence of a fronto-orbital sulcus would be more conclusive. However, this sulcus has not been identified in KNM-ER3732 and the region in which we would expect to find it is not preserved. As demonstrated by Ponce de León et al. (2021), because of the topographic relationships between sulci (and cranial structures), it is possible to interpret imprints on endocasts and the evolutionary polarity of some traits even in the absence of landmarks such as the fronto-orbital sulcus. In Australopithecus sediba the main derived feature of the endocast corresponds to the ventrolateral bulge in the left inferior frontal gyrus, and not to the sulcal pattern itself (Carlson et al., 2011 Science). However, the discussion around the taxonomic status of this taxon confirms the urgent need for reconsidering specimens from that time period and clarifying the mosaic-like or concerted evolution of the derived Homo-like traits within our lineage. Regarding the subjective nature of this approach, we invite readers to examine the specimen on MorphoSource (https://www.morphosource.org/concern/media/000497752?locale=en) and to request access to the National Museums of Kenya to the physical or virtual specimen to falsify our hypothesis.

According to my arguments above, I think that this manuscript might revive interesting discussions about this topic but it is not likely to settle them because the data presented are not strong enough to fully support the hypothesis.

We would be more than happy to consider new/other specimens with similar chronological and geographical contexts and investigate further this hypothesis in the future.

Reviewer #3 (Public Review):

The authors provide a detailed analysis of the sulcal and sutural imprints preserved on the natural endocast and associated cranial vault fragments of the KNM-ER3732 early Homo specimen. The analyses indicate a primitive ape-like organization of this specimen's frontal cortex. Given the geological age of around 1.9 million years, this is the earliest well-documented evidence of a primitive brain organization in African Homo.

In the discussion, the authors re-assess one of the central questions regarding the evolution of early Homo: was there species diversity, and if yes, how can we ascertain it? The specimen KNM-ER1470 has assumed a central role in this debate because it purportedly shows a more advanced organization of the frontal cortex compared to other largely coeval specimens (Falk, 1983). However, as outlined in Ponce de León et al. 2021 (Supplementary Materials), the imprints on the ER1470 endocranium are unlikely to represent sulcal structures and are more likely to reflect taphonomic fracturing and distortion. Dean Falk, the author of the 1983 study, basically shares this view (personal communication). Overall, I agree with the authors that the hypothesis to be tested is the following: did early Homo populations with primitive versus derived frontal lobe organizations coexist in Africa, and did they represent distinct species?

I greatly appreciate that the authors make available the 3D surface data of this interesting endocast.

We are grateful to Rev. 3 for their comments and for contextualizing our finding. We would also like to point out that, although the 3D surface can be viewed on MorphoSource, permission from the National Museums of Kenya has to be requested for studying the specimen and getting access to the physical specimen and/or the 3D model.

Reviewer #1 (Recommendations For The Authors):

Holloway, Broadfield & Yuan (2004) estimate ER 3732 as having a cranial capacity of 750 cc, which is larger than chimps and australopiths and similar to ER 1470 (752 cc, same reference). (That for Dmanisi 2282 is somewhat smaller at around 650 cc.) Cranial capacities should be mentioned along with added discussion about possible allometric scaling of (increased) numbers of sulci with increasing brain size as well as possible shifts in locations of sulci relative to cranial sutures in larger-brained (including due to ontogenetic maturation) in individuals/species. Could these variables (especially brain size) be relevant for your discussion/conclusions?

We thank Rev. 1 for their suggestion. We included the estimate by Holloway et al. (2004) (line 95): “Holloway et al. (2004) estimated the endocranial volume as about 750-800 cc but insisted on the low reliability of their estimate.”. Additionally, we raised the possibility of potential allometric effect (line 149): “In parallel, the possibility of allometric scaling and influence of brain size on sulcal patterns in early Homo has to be further explored.” for future discussion.

From the two figures, it appears that the authors produced a virtual endocast from the cranial remains of ER 3732 and compared its features with those seen on a virtual reproduction of the corresponding natural endocast. If so, this needs to be clarified in the text, not just the figures.

We thank Rev. 1 for their suggestions that were integrated.

Reviewer #3 (Recommendations For The Authors):

While the sulcal imprints on the left hemisphere can be interpreted unambiguously, the anatomical assignment of those on the right side may need to be reconsidered, as they are more ambiguous. For example, the postcentral sulcus (pt) almost touches the middle frontal sulcus, which is an unlikely natural configuration.

We agree that the configuration on the right hemisphere is intriguing, especially when compared to the extant human and chimpanzee atlases. As such, we decided to change the label for what we think could be the inferior frontal sulcus and leave a question mark instead.

I encourage the authors to include:

• a posterior view in Figure 1, and mark the lambdoid suture, parts of which seem to be preserved especially on the left side. This will help the readership to better understand which parts of the endocranial morphology are preserved.

• a scale bar would be of great utility to appreciate the small size of this specimen. The distance from bregma to the Broca cap seems to be short, indicating an endocranial volume much smaller than the published estimate of 750 ccm. Perhaps the authors can provide a new estimate, which would provide further support for the arguments proposed in the discussion section, especially the question of any presence of Australopithecus at Koobi Fora.

We included a posterior view of the specimen in Figure 1 and scale bar and modified the legend accordingly. Unfortunately, we were not able to identify with certainty the feature that could correspond to the lambdoid suture. We might see the impression where the parietal bone meets the occipital bone, but there is a risk of misidentification (which is an issue frequently raised in the literature, see for example Gunz et al. 2020 Sci Adv). Concerning the endocranial volume, in the revised version of the manuscript we included the estimate by Holloway et al. (2004). Because the specimen only preserves the superior part, we are reluctant in providing an estimate of the total volume. However, we agree that this would be an interesting feature to integrate in the interpretation of this specimen.

Minor points

• This sentence needs to be clarified: «The superior temporal sulcus nearly intersects the lateral fissure on the right hemisphere».

• The terms «Broca's region» and «orbital cap» need some more context. Do the authors mean «Broca's cap» in either instance?

We clarified/modified when needed, thank you very much.

We included minor corrections in addition to those recommended by the reviewers:

-Lines 50, 74, 142, 149: “Broca’s area” instead of “Broca’s cap”

-Line 73: “in the pre-1.5 Ma Homo specimen” instead of “in pre-1.5 Ma Homo specimen”

-Line 100: we specified “in human brains and endocasts”

-Line 120: “sulcal pattern” instead of “sulcal patterns”

-Line 144: “behaviors” (plural)

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity):

Major comments:

1. A control group of mice fed chow diet is needed to distinguish the effects of the genotype from those caused by diet. What is the phenotype of regular chow-fed mice in terms of energy metabolism and thermogenesis?

We are sincerely grateful to Reviewer 1 for raising an important question regarding the need for a control group of mice fed chow diet.

To address this concern, we have conducted experiments on mice fed a regular chow diet and measured their phenotype in terms of energy metabolism and thermogenesis. In addition to be sure that the phenotype also is present in when we compared littermates we have included as control both to chow-fed CD4-Cre and littermates (MKK3/6f/f). Our findings reveal that MKK3/6CD4-KO mice fed a chow diet presented an increased brown adipose tissue (BAT) thermogenesis compared with CD4-Cre and littermates. This phenotype is similar to the observed in HFD-fed mice. Also, these results indicate that the same phenotype is observed when we compared with littermates including an extra control in the study.

To further investigate the effect on energy metabolism, we utilized metabolic cages. The data from these experiments align with the increased thermogenesis observed in MKK3/6CD4-KO mice fed a chow diet, as they also demonstrated increased energy expenditure. We thank the reviewer for this suggestion as we believe that these new data strengthen our conclusion significantly.

We have thoughtfully incorporated these essential findings into in Supplementary Figure 2C-D of the manuscript.

1. While an increase in BAT temperature (as demonstrated here by infrared imaging) in line with increased thermogenesis, it will be critical to verify this hypothesis by indirect calorimetry. Energy expenditure, food intake, and activity measures should be added for regular and DIO mice. Please follow the guidelines for ANCOVA analysis and measurements explained in PMID: 22205519 and PMID: 21177944.

We are grateful to Reviewer 1 for bringing up an essential point concerning the need to verify our hypothesis on increased BAT temperature and thermogenesis through indirect calorimetry. We acknowledge the importance of including energy expenditure, food intake, and activity measures for both regular and DIO mice to strengthen our study.

To address this valuable suggestion, we have taken immediate action. We utilized metabolic cages in mice under chow diet. The data from these experiments align with the increased thermogenesis observed in MKK3/6CD4-KO mice fed a chow diet, as they also demonstrated increased energy expenditure, without differences in food intake or locomotor activity. We thank the reviewer for this suggestion as we believe that these new data strengthen our conclusion significantly. These new data are now in Supplementary Figure 2A-B.

In addition, we have initiated a new experimental group of age-matched mice on HFD, which we will carefully feed for 8 weeks. Following this dietary period, we will subject the mice to metabolic cage analysis, allowing us to obtain accurate data on energy expenditure, food intake, and activity levels. These additional measurements will provide a comprehensive understanding of the metabolic changes induced by MKK3/6 deficiency in T cells under different dietary conditions.

1. That the phenotype is still seen at isothermal housing is interesting but should be backed up by direct assessment of thermogenic capacity (see PMID: 21177944). In the end, it could also be increased heat loss, independently of heat production. If the browning is cause or consequence remains unclear, then.

Thank you for raising this important point. Indeed, it is essential to corroborate the observed phenotype with direct assessments of thermogenic capacity to gain a comprehensive understanding of the underlying mechanisms. The study mentioned in PMID: 21177944 highlights the significance of evaluating thermogenesis directly to support the findings.

According to your suggestion, we plan to house the animals at 30 ºC for four weeks and subsequently inject norepinephrine to evaluate thermogenesis capacity while measuring brown adipose tissue (BAT) activation. This approach should provide valuable insights into the thermogenic potential of the animals under isothermal conditions.

However, we will not be able to conduct the experiment in metabolic cages at 30 ºC due to the constraint that our system does not allow 30 ºC temperature. For this reason, we will measure BAT temperature to analyze this experiment.

1. Regarding the in vitro data, a thermogenic phenotype should be functionally verified by Seahorse analysis.

We thank Reviewer 1 for raising an important point concerning the need for functional verification of the thermogenic phenotype observed in our in vitro data using Seahorse analysis.

In response to this valuable suggestion, we performed Seahorse analysis in differentiated adipocytes treated with or without IL-35 for 48 hours. The results demonstrated a slight increase in basal metabolism and a heightened response to isoproterenol (ISO) stimulation of β3 adrenergic receptors in adipocytes after IL-35 treatment. These findings provide functional evidence supporting the thermogenic phenotype induced by IL-35 in adipocytes.

We have thoughtfully included this essential data in Figure 2 of this revision plan, allowing reviewers and the scientific community to comprehensively evaluate and validate the functional implications of our findings.

1. Mechanistically, there is epistasis type of experiment that IL-35 influences Ucp1 levels via ATF2 as the data remain associative in nature.

Thank you for your valuable comment. We agree that to establish a mechanistic link between IL-35 and Ucp1 levels will improve the strength of the manuscript.

To delve deeper into the mechanism through which IL-35 influences Ucp1 expression, we focused on the role of ATF2, a transcription factor known to be involved in regulating UCP1 levels (PMID: 11369767 and PMID: 15024092). In our investigation, we treated adipocytes with IL-35 both in the presence and absence of an inhibitor targeting the ATF2 pathway. The results were illuminating as we observed a significant reduction in the expression of Ucp1 when the ATF2 pathway was inhibited.

These findings indicate that ATF2 is indeed a crucial mediator of the effects of IL-35 on Ucp1 levels. By inhibiting the ATF2 pathway, we demonstrate a direct functional link between IL-35 and the expression of Ucp1, providing mechanistic insights into the regulatory role of IL-35 in thermogenesis. We included new results in Figure 7F.

1. What are other consequences of injecting IL-35? Is it good or bad? What is the therapeutic potential in DIO mice? Also, in these experiments (Fig. 7) indirect calorimetry as described would be supportive of the claims.

Regarding the consequences of injecting IL-35, we have already performed experiments to analyze its effect. Our findings indicate that IL-35 increases thermogenesis in BAT (Figure 7), suggesting that it may play a role in promoting energy expenditure, which could be beneficial in combating diet-induced obesity (DIO) in mice. Importantly, we did not observe any negative effects of IL-35 in our experiments.

Based on these promising results, we are expecting the therapeutic potential of IL-35 in DIO mice. By promoting thermogenesis in BAT, IL-35 may offer a novel approach to manage obesity and related metabolic disorders. However, we acknowledge that further comprehensive studies are needed to fully understand its therapeutic benefits and potential side effects.

In our future works, we plan to evaluate a targeted delivery system for IL-35. We are currently generating IL-35 loaded metal-organic frameworks (MOFs) labeled with adipose tissue-specific peptides. This innovative strategy aims to enhance the delivery of IL-35 to adipose tissue, potentially maximizing its effects in the relevant areas. Our ongoing work with IL-35 loaded MOFs may offer a promising avenue for targeted delivery.

Minor comments:

1. The authors claim that their HFD-fed MKK3/6CD4-KO mice are protected against hyperglycemia, but only fasted/fed blood glucose tests are performed. Lower glucose levels could be explained due to a hyperinsulinemic state in response to growing insulin resistance in the presence of HFD. It would be sensible to perform both glucose and insulin tolerance tests to back up your statement.

Thank you for your insightful comment. We agree that to support our claim of protection against hyperglycemia in HFD-fed MKK3/6CD4-KO mice, further tests are necessary beyond fasted/fed blood glucose measurements.

In response to your suggestion, we conducted both glucose tolerance tests (GTT) and insulin tolerance tests (ITT) in HFD-fed MKK3/6CD4-KO mice. We did not observed differences in glucose tolerance and but ITT showed significantly enhanced insulin sensitivity compared to control mice. These findings provide evidence that the protection against hyperglycemia in HFD-fed MKK3/6CD4-KO mice is not solely due to a hyperinsulinemic state, but rather indicates genuine improvements in glucose handling and insulin response.

We have thoughtfully included these crucial data in the revised version of the manuscript, both in the main text and Supplementary Figure 4. We extend our appreciation to the reviewer for this valuable suggestion, which has enhanced the scientific rigor and completeness of our study.

1. Please provide the loading control for p38 and S6 blots (Figure 6G).

Thank you for the comment. The loading control we used for P p38 and P S6 blots in Figure 6G is β-actin. Due to the limited amount of sample available, we can only use β-actin as the loading control. The sample amount obtained is very limited, and we can only provide enough lysate to run a couple of blots from the same sample. Running several western blots with the same sample is almost impossible given the constraint of the sample availability. We apologize for this limitation, but it is necessary to avoid using too many mice for ethical reasons, as the samples come from a large number of mice.

1. Statistical test from Figure 7B should be a t-test, since it is only comparing 2 variables (PBS vs IL-35), and not a 2-way ANOVA as described in the legend.

We sincerely thank the reviewer for the comment. It was indeed a mistake in the text. While we have performed a t-test, there was an error in the legend that we have now corrected. We apologize for any confusion this may have caused and appreciate the opportunity to rectify the oversight.

1. Label correctly the panels in the figures -examples: Fig 3, panels C and D are interchanged; reference in the text to Fig S1G even though the figure only as panels A-F; Fig 7 legend referes to the statistical test of panel E when the figure only has A-D.

We sincerely apologize for any mistakes in our manuscript that may have caused difficulties while reading the article and potentially led to misleading results. We are grateful to Reviewer #1 for bringing these errors to our attention. Thanks to their diligent review, we have been able to identify and rectify the issues in our manuscript. The necessary corrections have been made, ensuring the accuracy and reliability of our research. We greatly appreciate the reviewer's valuable feedback and contribution to improving the quality of our work.

1. There are several typos along the text, please revise (example: page 4;line 4 -"tremorgenic")

We apologize for the presence of any typos in the initial version of the article. We have thoroughly revised the manuscript to correct these errors. Thank you for bringing this to our attention and helping us improve the accuracy and clarity of our work.

Reviewer #1 (Significance):

The manuscript is well written, and the research conducted properly, even though a thorough analysis of energy metabolism in mice and cells is missing and the mechanistic claims are based on relatively thin data.

The immune system and inflammation play important roles for obesity and insulin resistance, yet the roles they play in thermogenic adipocytes remains unclear. This work adds novel aspects to this relationship.

Reviewer #2 (Evidence, reproducibility and clarity):

This manuscript by Nikolic et al sought to investigate the role of p38 activation in adipose tissue Treg cells and obesity. They found that the expression of p38a, its upstream kinase MKK6, and downstream substrate ATF2 was upregulated specifically in adipose T cells associated with human obesity. They generated T cell-specific knockout MKK3/6 in mice and found these animals were protected from diet-induced obesity as a result of increased BAT thermogenesis. Mechanistically, loss of p38a activation promoted adipose tissue accumulation of Treg cells, leading to elevated IL-35 availability and UCP1 expression.

Major comments:

1. They attributed the obesity protection to energy expenditure; however, food intake and intestinal absorption were never tested. Immune cells particularly Treg cells are important modulates of nutrient uptake.

We are sincerely grateful to Reviewer #2 for this crucial comment, highlighting the importance of assessing not only energy expenditure but also food intake and intestinal absorption in our study.

In response to this valuable suggestion, we have initiated an HFD experiment to comprehensively examine food intake and intestinal absorption. For food intake analysis, we are employing metabolic cages, which will allow us to monitor and quantify the amount of food consumed by the mice accurately. Additionally, we plan to follow the methodology outlined in the study by Kraus et al. (PMID: 27110587) to measure lipid content in feces, enabling us to evaluate intestinal absorption.

By conducting these additional experiments, we aim to gain a deeper understanding of the potential role of Treg cells, known immune modulators of nutrient uptake, in our observed obesity protection phenotype.

1. At thermoneutrality, BAT is inactive even though UCP1 expression is still present (not activated). MKK3/6 deficiency in T cells still confer protection against obesity at thermoneutrality suggests it regulates other energy balance components in addition to BAT thermogenesis.

Thanks for the comment. We believe that the effects of IL35 on thermogenesis are likely partly mediated by alternative mechanisms, as we did not observe an increase in UCP1 gene expression in BAT in vivo (Figure 3D of the manuscript), and the increase in thermogenesis is still present even at thermoneutrality where UCP1 is inactive (Figure 4E of the manuscript). This suggests that IL35 might regulate other alternative pathways that control BAT thermogenesis.

While our current findings provide valuable insights, further experiments may be necessary to fully understand the underlying mechanisms. For instance, conducting experiments with transgenic mice expressing IL35 or using IL35 knockout (KO) mice could shed more light on the specific pathways through which IL35 exerts its effects on thermogenesis and energy balance.

In conclusion, we hypothesize that IL35's effects on thermogenesis are mediated partly by alternative mechanisms beyond UCP1 activation, and its ability to enhance thermogenesis even at thermoneutrality highlights its potential as a regulator of energy balance. We plan to further investigate the specific mechanisms through which IL35 impacts thermogenesis and energy balance. To achieve this, we will consider conducting experiments with transgenic mice expressing IL35 or using IL35 knockout (KO) mice in follow up studies. This is now discussed in our manuscript.

1. Loss of adipose Treg cells (such as Pparg KO, Foxp3-DTR) did not lead to obvious obesity phenotypes. Gain-of-function Treg cells (such as adoptive transfer, IL-2/IL-2 Ab) did not results in profound obesity protection as observed in MKK3/6 CD4-KO mice. It suggests that MKK3/6 KO in T cells causes other immune defects (besides Tregs).

We agree with the referee's assessment that the lack of obvious obesity phenotypes in above mentioned animal models. The results we observed in our MKK3/6CD4-KO mice suggest that p38 signaling pathway in T cells may modulate their function, leading to an upregulation of IL35 expression, which could be a contributing factor to the significant obesity protection observed in MKK3/6CD4-KO mice. We believe that IL35's effects on energy balance and thermogenesis are critical components of the observed protection against obesity in this model.

Regarding the studies with PPAR KO in Treg cells, it is important to note that they did not specifically focus on the effect of thermogenesis. While they observed a general tendency of increased fat deposition when treated with a PPAR agonist in the Treg deficient PPAR KO mice, these findings were not extensively studied in that particular paper. Thus, additional research is necessary to specifically evaluate thermogenesis in these mice and further understand the role of PPAR in Treg-mediated thermogenic processes.

We also acknowledge the presence of contradictory results from loss-of-function experiments of Treg cells in mice. The observed metabolic changes may be context-dependent, and the impact of Treg cells on metabolism might vary under different physiological conditions. For instance, in lean conditions where adipose tissue inflammation is low, a decrease in VAT Treg cells might not lead to significant metabolic changes. However, under certain circumstances, such as obesity, VAT Treg cells may play a critical role in regulating metabolism. In this context increasing that population that is reduced during obesity could results in improve metabolic performance.

In conclusion, our findings suggest that the lack of p38 activation in Treg cells may prevent the dramatic down-regulation and loss of function observed in Treg cells during obesity. This preservation of Treg function could be a significant factor driving the observed protection against obesity in MKK3/6CD4-KO mice.

While further studies are required to elucidate the precise timing and spatial aspects of the specific functions of adipose-resident Treg cells, it is evident that these cells play a crucial role in maintaining immune and metabolic homeostasis. They achieve this, in part, by regulating adipose inflammation, insulin sensitivity, lipolysis, and thermogenesis. This is now discussed in our manuscript.

1. The increase in IL-35 seemed to be very moderate, compared to the metabolic phenotypes. It raises the question if IL-35 is responsible for BAT activation and reduced weight gain. It is unclear what systemic and local levels of IL-35 were reached after recombinant IL-35 treatment (Fig. 7B). IL-35 antibody blockade experiment in KO mice is recommended.

Physiological changes in cytokines can indeed have a significant impact on the metabolic profile due to their continuous and intricate interactions. Even minor alterations in the overall cytokine milieu can result in substantial changes in metabolism (doi.org/10.1073/pnas.1215840110). In fact, it is well-established that in humans, small changes in cytokine profiles between genders, in obesity, and during aging can play a critical role in the development of pathology. These cytokines often operate in a chronic manner, exerting long-term effects on various physiological processes (doi.org/10.1038/s41467-020-14396-9).

In summary, the dynamic interplay of cytokines in metabolism can lead to significant metabolic changes even with subtle alterations in their levels. While the increase in IL-35 may appear moderate, our findings using recombinant IL35 indicate that IL-35 increases thermogenesis in BAT, suggesting that it may play a role in promoting energy expenditure, which could be beneficial in combating diet-induced obesity (DIO) in mice. Importantly, we did not observe any negative effects of IL-35 in our experiments.

1. IL-35 induced p-ATF2 is acute and transient (Fig. 7D) and it was able to increase BAT temperature in just 4 h (Fig. 7B). However, Ucp1 transcription and translation generally take much longer time (e.g. 2d in Fig. 7C). IL-35 may increase energy expenditure through UCP1-independent mechanisms.

Thanks for the comment. As previously mentioned, we believe that the effects of IL35 on thermogenesis are might be mediated by alternative mechanisms, as we did not observe an increase in UCP1 gene expression in BAT, and the increase in thermogenesis is still present even at thermoneutrality where UCP1 is inactive. This suggests that IL35 might regulate other alternative pathways that control BAT thermogenesis.

While our current findings provide valuable insights, further experiments may be necessary to fully understand the underlying mechanisms. For instance, conducting experiments with transgenic mice expressing IL35 or using IL35 knockout (KO) mice could shed more light on the specific pathways through which IL35 exerts its effects on thermogenesis and energy balance. We plan to further investigate the specific mechanisms through which IL35 impacts thermogenesis and energy balance. To achieve this, we will consider conducting experiments with transgenic mice expressing IL35 or using IL35 knockout (KO) mice in follow up studies. This is now discussed in our manuscript.

Minor comments:

1. The gating of Treg cells should exclude CD25- cells. Single positive (CD25+ or Foxp3+) cells are progenitors of Tregs. In addition to number, phenotypic activation of Treg cells should also be determined.

Thank you for the comment. We have reanalyzed our data by excluding CD25- cells and included now in the figure 5A of the manuscript and new supplementary figure 7 of revised manuscript. We also checked CD69+ and KLRG1+ Treg cells and observed no differences between genotypes. We also included figures in this revision plan (Figure 5 and 6).

1. ATF is also important for adipogenesis, is the adipogenic differentiation of BAT SVF cells affected by MKK3/6 KO or IL-35 treatment?

We appreciate the reviewer's observation regarding the importance of ATF in adipogenesis. To investigate this aspect further, we performed in vitro differentiation of adipocytes and treated them with IL-35 in the presence or absence of an inhibitor targeting the upstream activator of ATF.

The results were compelling, as IL-35 treatment led to an increase in the expression of adipogenic markers, including Pparg, Adipoq, Leptin, and Perilipin. In contrast, inhibiting ATF activation resulted in a reduction of these adipogenic markers. These findings provide strong evidence that ATF plays a significant role in mediating the effects of IL-35 on adipogenesis.

We have thoughtfully included these essential data in Figure 7G of the manuscript. We extend our gratitude to the reviewer for their keen observation, which has enhanced the scientific depth and completeness of our study.

1. Metabolic cage experiments are desired to determine whole-body energy balance, including food intake, physical activity, and heat production.

To address this valuable suggestion, we have taken immediate action. We utilized metabolic cages in mice under chow diet. The data from these experiments align with the increased thermogenesis observed in MKK3/6CD4-KO mice fed a chow diet, as they also demonstrated increased energy expenditure, without differences in food intake or locomotor activity. We thank the reviewer for this suggestion as we believe that these new data strengthen our conclusion significantly. The new data are included in Supplementary figure 2 A-B.

In addition, we have initiated a new experimental group of age-matched mice on HFD, which we will carefully feed for 8 weeks. Following this dietary period, we will subject the mice to metabolic cage analysis, allowing us to obtain accurate data on energy expenditure, food intake, and activity levels. These additional measurements will provide a comprehensive understanding of the metabolic changes induced by MKK3/6 deficiency in T cells under different dietary conditions.

1. Total UCP1 expression (both RNA and protein) in the whole BAT from an animal should determined (since BAT is smaller in KO mice).

Thank you for this comment. Yes, we have measured UCP1 expression in the whole BAT from the animals. It is in the figure 3C and 3D and here. Although in vitro studies indicated that IL35 increase UCP1 in adipocytes we were not able to find an increase of this protein in BAT

We believe that the effects of IL35 on thermogenesis are likely partly mediated by alternative mechanisms, as we did not observe an increase in UCP1 gene expression in BAT in vivo, and the increase in thermogenesis is still present even at thermoneutrality where UCP1 is inactive (Figure 4E of the manuscript). This suggests that IL35 might regulate other alternative pathways that control BAT thermogenesis.

1. Fig. 6C, IL-35-expressing Treg cells should be quantified from adipose tissue.

We appreciate the referee's suggestion to quantify IL-35-expressing Treg cells from adipose tissue in Fig. 6C. While we agree that this would be valuable information, we encountered technical challenges that made it impractical to measure IL-35 directly in Treg cells from the visceral adipose tissue (VAT).

One of the main technical challenges we encountered is the low number of Treg cells present in the adipose tissue, making it difficult to obtain sufficient cell material for accurate quantification of IL-35. Treg cells are relatively rare compared to other immune cell populations in the adipose tissue, and their extraction and analysis can be technically demanding.

Reviewer #2 (Significance):

The manuscript is innovative in define the novel role of p38 activation in the T cell compartment and its metabolic regulation. The involvement of Treg cells in adipose tissue homeostasis has been well documented and Treg cell-derived IL-35 has been demonstrated in immune regulation. The authors provided a relatively thorough description of the altered metabolism in these Mkk3/6 CD4-KO mice; however, the reviewer has doubts if Treg cells and IL-35 are primary mechanisms of the observed protection from obesity. The manuscript would be much stronger if the model were Treg cell-specific KO and/or IL-35 deficiency in Treg cells reverses obesity resistance conferred by MKK3/6 deficiency. It also suspected that BAT thermogenesis is not the major reason, as BAT deficiency or UCP1 KO results in much milder phenotypes in mice, even at thermoneutrality.

Reviewer #3 (Evidence, reproducibility and clarity):

Specific comments:

1. It's important to use proper controls for mouse metabolic studies. The authors stated that CD4-Cre and MKK3/6 CD4-KO mice are all in the C57B/6L background. However, it would appear that these two lines were bred separately. The difference in the genetic background, despite minor, can lead to the observed phenotype, notably weight gain. Since the metabolic phenotypes seem to be driven by the weight difference, it is even more critical to include additional controls to validate the findings. For instance, crossing MKK3/6 f/f with one copy of CD4-Cre with MKK3/6 f/f to generate age-matched MKK3/6 CD4-KO and MKK3/6 f/f controls should be used to repeat major in vivo studies similar to those in Fig. 2-4.

We thank the reviewer for the comment. Although, every control is important using conditional mice, there are several papers indicating that all the cre expression lines have for their own effects that could be important in metabolism and there are several articles that strongly recommended to use cre+ lines as a control. For that reason, we have used the cre expressing line as a control because we really think is the best one (Jonkers and Berns, 2002). In fact, Jackson laboratory recommend to use cre expressing line as a control to avoid side effects that cre overexpression could have in the tissue of interest (https://biokamikazi.files.wordpress.com/2014/07/cre-lox-imp-notes.pdf).

However, as this reviewer suggested, we checked that similar results were obtained using littermates as controls and we have now included these data in the manuscript (Supplementary Figure 2D).

1. The assessment of adipose tissue immune cell population in Fig. 5 was conducted after HFD-induced obesity. As mentioned above, the change in Treg and M2 cell percentage could be due to the body weight difference. The experiment should be repeated (with proper controls) in normal chow and after a few weeks of HFD when Treg numbers start to decline.

Thank you for the comment. We currently performing short HFD experiment to check Treg and M2 cell population in adipose tissue using the littermates as controls.

In addition, we checked those cell populations in adipose tissue infiltrates in mice fed chow diet and observed no differences in M2 macrophage population between mice, while the percentage of Treg cells was actually lower in MKK3/6CD4-KO mice ND-fed mice (Fig 12 of revision plan). This result suggests that higher accumulation of Treg cells in mice lacking p38 activation in T cells are specific of obese state and strengthen our hypothesis that DIO protection in MKK3/6CD4-KO mice is due to Treg cell population.

1. Data related to the mechanistic link in Fig. 6/7 are not robust and require a large amount of additional work to substantiate the claim. First of all, the role of IL-35 in BAT thermogenesis remains unclear. It's somewhat surprising to see a single dose of IL-35 i.v. injection is sufficient to increase BAT temperature in Fig. 7B. Minimally, the authors need to demonstrate that IL-35 treatment (perhaps after a few daily doses) is able to increase browning/beiging of fat cells and improve cold tolerance when placing the mice at 4 degree of several hours (and up to 3 days). Serum FGF21 level should also be measured after/during IL-13 treatment. Secondly, ATF2 knockout or knockdown in brown preadipocytes should be employed to demonstrate that IL-35 induced UCP1 and FGF21 expression is ATF2 dependent. Another key experiment is to use IL-35 deficient Treg model to definitively demonstrate the requirement of Treg IL-35 to maintain thermogenesis. However, this can be done in a follow up study.

We are grateful for all the insightful comment provided by Reviewer #3. We understand the concern, but we have the limitations in performing several sequential i.v. injections in our animal facility due to ethical permissions. In light of this constraint, we have devised an alternative approach to evaluate the role of IL-35 in adaptive thermogenesis.

To address this, we conducted a cold tolerance test in both control mice and MKK3/6CD4-KO mice, which express higher levels of IL-35. Our findings revealed that MKK3/6CD4-KO mice exposed to cold conditions were able to preserve their body and brown adipose tissue (BAT) temperature, while the temperature of control CD4-Cre mice gradually dropped during the cold challenge.

The data from this cold tolerance test support our hypothesis and demonstrate the role of IL-35 in promoting adaptive thermogenesis, leading to enhanced temperature maintenance in MKK3/6CD4-KO mice. These observations have been included in Figure 7B of the manuscript, and detailed results are available in Figure 11 of this revision plan.

We appreciate the reviewer's valuable input, which has encouraged us to explore alternative experimental approaches to address the research question effectively.

We agree with the reviewer #3 that using IL-35 deficient Treg model would be great approach to confirm our results, but we think that now with the additional experiments we have performed, we strength our findings that IL-35 has a novel role in controlling adipose tissue thermogenesis.

Reviewer #3 (Significance):

Dissipating energy as heat through brown or beige adipocyte-mediated thermogenesis is believed to be an effective way to combat obesity. The current study aims to characterize the p38 signaling pathway in T cells as a potential target to modulate browning or beiging of adipose tissues. This would be of interest to the basic biomedical research community, particularly in the area of immunometabolism. A major limitation is the concern of improper controls for the mouse models, which makes data interpretation difficult. In addition, the mechanistic studies lack in depth analyses to support the conclusion.

Author Response

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

We thank the reviewers for the constrictive and detailed feedback provided. We have adopted the proposed changes to improve the manuscript clarity and accessibility. The following revisions are included in the revised manuscript:

Reviewer #1 (Public Review):

The analytical framework is not sufficiently explained in the main text.

We think the reviewer is referring to the conceptual framework mentioned in introduction. In the previously submitted manuscript, we did not provide details because the framework is published elsewhere. However, we agree with the reviewer that a short explanation may be helpful, which we have included in the resubmitted manuscript.

The significance of findings in relation to functional changes is not clear. What are the consequences of enrichment of RNA transport or ribosome biogenesis pathways between pesticides and recovery stages, for example?

We thank the reviewer for this suggestion. In the previously submitted manuscript, we included an explanation of the central functions these pathways can alter (e.g. metabolism and infection response). These functions are self-explanatory. However, we have elaborated on the consequence that the disruption of these pathways can cause in the resubmitted manuscript.

The impact of individual biocides and climate variables, and their additive effects, are assessed but there is no information offered on non-additive interactions (e.g., synergistic, antagonistic).

This was a misunderstanding based on our use of the term synergistic in this context. The approach by which we define a synergistic or joint effect of two environmental variables on a taxonomic group is explained in the methods section. This analysis is based on climate variables and biocide types contributing the largest covariances in the correlation analysis explained in Supplementary Fig. 5; Step 4. The combined effect of two environmental variables on a taxon was considered to be significant if the biocide type and the climate variable were each significantly correlated with the taxon over the same time window, and their average Pearson correlation was > 0.5 with padj < 0.05 (SWC analysis with 10,000 permutations). The biocide type and the climate variable were interpreted to have a joint effect on a given taxon if the linear combination of the biocide type and the climate variable had a larger Pearson correlation coefficient than each of the correlations between the family and the biocide type and the family and the climate variable individually, in the same time interval with padj < 0.05 (with 10,000 permutations in the SWC analysis). We realise that the use of synergistic or additive was not correct in this context and have replaced the term synergistic with joint effect throughout the manuscript.

The level of confidence associated with results is not made explicit. The reader is given no information on the amount of variability involved in the observations, or the level of uncertainty associated with model estimates.

As we didn’t use traditional statistical approaches, confidence level estimation in the traditional sense is not possible. Instead, we used permutation tests and adjusted P-values to identify significant correlations in the data. These approaches are more robust than traditional statistics for integrating and discovering complex, group-wise patterns among high-dimensional datasets. While most forms of machine learning require large sample sizes, sCCA uses fewer observations to identify the most correlated components among data matrices and captures the multivariate variability of the most important features.

The major implications of the findings for regulatory ecological assessment are missed. Regulators may not be primarily interested in identifying past "ecosystem shifts". What they need are approaches which give greater confidence in monitoring outcomes by better reflecting the ecological impact of contemporary environmental change and ecosystem management. The real value of the work in this regard is that: (1) it shows that current approaches are inappropriate due to the relatively stable nature of the indicators used by regulators, despite large changes in pollutant inputs; (2) it presents some better alternatives, including both taxonomic and functional indicators; and (3) it provides a new reference (or baseline) for regulators by characterizing "semi-pristine" conditions.

We thank the reviewer for this suggestion, which we have included in the main text (L451461)

Reviewer #2 (Public Review):

Results - They are brief and should expand some more. Particularly, there are no results regarding metabarcoding data (number of reads, filtering etc.). These details are important to know the quality of the data which represents the bulk of the analyses. Even the supplementary material gives little information on the metabarcoding results (e.g. number of ASVs - whether every ASV of each family were pooled etc.).

We thank the reviewer for this suggestion. We have included a paragraph in results reporting read numbers and other statistics. The filtering criteria and handling of samples can be found in methods (L658-661; L670-675). As explained in methods the taxonomy was assigned using qiime feature-classifier classify-sklearn and used at family level where possible. When classification was not possible at family level because of incomplete/missing information in the online database or a poor match to reference database, the lowest classification possible was used.

The drivers of biodiversity change section could be restructured and include main text tables showing the families positively or negatively correlated with the different variables (akin to table S2 but simplified).

As there are over 180 unique families/taxonomic units correlated with at least one biocide or environmental variable, a simplified version of this table would be too large to include in the main text. Therefore, we prefer to keep this information in supplementary table 2 complete with correlation statistics.

We thank the reviewers for providing detailed feedback on the manuscript and respond to their suggestions as follows:

Reviewer #1 (Recommendations For The Authors):

Thank you for the opportunity to review your manuscript, which I found interesting and enjoyable to read. Here are some suggestions for improving it.

Remove spaces before citations in text.

Lines 51-53: "Community-level biodiversity reliably explained freshwater ecosystem shifts whereas traditional quality indices (e.g. Trophic Diatom Index) and physicochemical parameters proved to be poor metrics for these shifts." Seems to be the wrong way around / not clear???

Rephrased to clarify.

Line 54: Should be "...advocates the use of..." or "...demonstrates the advantages of..."

Done, thanks for the suggestion.

Line 62: Spell out numbers <10, i.e. "sixth mass extinction"

Done, thank you.

Lines 66-72: These sentences lack clarity. It's not clear that "experimental manipulation of biodiversity" hasn't involved investigation of "multi-trophic changes". By the third of these four sentences it is not clear what "they" is referring to. And in the fourth sentence, "these holistic studies" are not defined. Perhaps it would suffice to say that experiments have so far focused primarily on a single trophic level and largely neglected freshwater systems.

We have rephrased to improve clarity.

Line 81: Delete unnecessary bracket

Done, thank you.

Line 82: "a minority of freshwater ecosystems" sounds as if you're saying that few freshwater ecosystems are represented in BioTIME, which seems obvious and would also apply to terrestrial and marine systems. Do you mean that freshwater ecosystems re not well represented in the data?

We have clarified the sentence, thanks.

Line 106: Resolve issue with citation in text at the end of the sentence (repeated at line 109 and possibly other lines).

Done, thank you.

Line 116: By ">1999s" do you mean 1990s?

This was a typo. it was supposed to be >1999

Line 120: The reader would benefit greatly from a brief explanation of explainable network models and multimodal learning in the introduction. Why are these the right tools to use? How do they work in this context? Figure 1 helps to some extent but needs more commentary in the text.

We have included an explanation of the explainable network models and multimodal learning and how their use can be beneficial to the study of diverse data types.

Line 144: Here and throughout the text the language could be much more efficient and readable. "Alpha diversity" does not require a definite article. Furthermore, when referring to significance it is convention to state the p-value, test statistic and test used.

As there are different p-values for each barcode, we have included them in legend to Supplementary Fig. 1 to avoid crowding the main text. We prefer to leave the text unchanged for this reason.

Line 155: "The primary producer's composition" is grammatically awkward and less suitable than "the composition of primary producers". This kind of awkwardness occurs again at line 285 ("diatom's") and possibly in other parts of the manuscript.

Thanks, corrected.

Line 169: The statement that this family was "relatively more abundant" needs a little more explanation. What is it relative to - other groups or to previous stages?

More abundant than in the other phases – the sentence has been modified.

Line 179: Nested brackets are unnecessary and affect readability. This could simply be a new sentence, i.e. "For example, Nitrospiraceae (nitrite oxidizers)..."

Done, thanks.

Line 215: "Functional biodiversity", which implies that some biodiversity is functional and some not, does not seem an appropriate term to describe the results you present in this section. Simply "functioning of the prokaryotic community" would suffice.

Thanks, done.

Line 214-233: This section may be inaccessible for many readers. For example, what are Kegg Orthologs and what role do they play in the functioning of a lake ecosystem? The explanation comes later in the paragraph but there needs to be a gentler introduction before diving into specific technical concepts.

We appreciate this comment and have included a short explanation of what KEGG and KO terms mean.

Supplementary Figure 3: It would be helpful to superimpose the lake stages here, as done in Figure 2.

The figure has been updated with coloured data points corresponding to each phase, as in supplementary figure 1.

Line 265: Should be "19 of which were identified..."

Done, thanks.

Line 284: "Predominantly" rather than "prominently"?

Done

Line 242-316: This section is good in that it identifies and ranks individual biocides and climate variables but there is no information on non-additive interactions (e.g., synergistic, antagonistic). Could the authors at least comment on why this was not done or not necessary, and what uncertainties this omission could introduce into the results?

This was a misunderstanding based on our use of the term synergistic in this context. the approach by which we define a synergistic or joint effect of two environmental variables on a taxonomic group is explained in the methods section. This analysis is based on climate variables and biocide types contributing the largest covariances in the correlation analysis explained in Supplementary Fig. 5; Step 4. The combined effect of two environmental variables on a taxon was considered to be significant if the biocide type and the climate variable were each significantly correlated with the taxon over the same time window, and their average Pearson correlation was > 0.5 with padj < 0.05 (SWC analysis with 10,000 permutations) – this is shown in Supplementary Fig. 5; Step 6. The biocide type and the climate variable were interpreted to have an additive effect on a given taxon if the linear combination of the biocide type and the climate variable had a larger Pearson correlation coefficient than each of the correlations between the family and the biocide type and the family and the climate variable individually, in the same time interval with padj < 0.05 (with 10,000 permutations in the SWC analysis). we have replace synergistic with joint effect to avoid confusion.

Figure 4: These 3-D plots are very hard to read. Without additional features (e.g. shadows on each plane, or lines connecting points to planes) it is impossible for the viewer to tell where the points are located on each axis.

We have created interactive 3D plots here: https://environmental-omicsgroup.github.io/Biodiversity_Monitoring/.

Figure 5: Legend entry should be "summer precipitation" not "precipitations". "Additive effect" rather than "joint effect" would be more consistent with the main text.

“Precipitations” has been updated to “precipitation” where relevant throughout. We left ‘joint effect’ and unified the main text, responding to a previous comment of this reviewer on the meaning of synergistic effects in our study.

Line 348: Doesn't your approach also require specialist skills? I often feel that the "traditional" versus "molecular" monitoring debate misses this point. Some comment on the training and development needs for those interested in applying the sedaDNA approach would be welcome. Otherwise it is an unfair comparison.

Whereas the application of high throughput sequencing technologies requires training, these technologies are well established with publicly available standard operating procedures. As compared to direct observations, high throughput sequencing provides replicable results regardless of the operator. Moreover, the application of metabarcoding to sedaDNA or more generally eDNA can be outsourced to established environmental services, removing the need for training if it is a limiting factor. The above has been included in discussion.

Line 391: "Significantly did" what? "Did significantly change over time" would be better.

Done, thanks.

Line 407: Should be "an indicator of..." and "did not significantly change over time..."

Done, thanks.

Line 408-410: Regulators are not necessarily interested in identifying past "ecosystem shifts", so this does not seem to be the best way to contrast the capabilities of the sedaDNA approach with those of LTDI2. The real value of this work, in my opinion, is threefold. First, it shows that the reliance on diatoms as indicators of ecological status is inappropriate due to the relatively stable nature of diatom communities in the face of large environmental changes. Second, it presents some better alternatives, including both taxonomic and functional indicators. And third, it provides a new reference point for regulators by characterising "semi-pristine" conditions.

Thanks for the insightful suggestion. We agree with the reviewer on the advantages and have spelled them out in the resubmitted manuscript.

Line 445: What are "housekeeping functions"? I checked the Cuenca-Cambronero paper cited but did not find the term there.

Housekeeping functions are essential basic cellular functions that are evolutionary conserved. They are more commonly present in public databases because they have been characterised in a number of model species (e.g. Drosophila, C. elegans and Mus musculus). Our reference it not to the Cuenca-Cambronero paper, but to Mi et al, describing the reference database PANTHER. We included the definition of housekeeping functions in the main text.

Line 449: Briefly state the main functional changes found here.

Examples have been included.

Lines 451-452: Whilst this statement may be found in the cited source, most readers I suspect would not identify with it. Indeed, one could argue that most of freshwater ecology has been dedicated to this very task (documenting chemical impacts on biodiversity)! A more balanced view is needed here.

The sentence the reviewer refers to includes also reference to climate change. Climate change and chemical pollution are the two most common causes of biodiversity loss, and not only in freshwater ecosystems.

Lines 463-466: These examples both point to non-additive (synergistic) effects, which were not assessed in the current study.

Please refer to our explanation above about the inappropriate use of synergistic and, here, additive. We have altered the text throughout to use joint effects as we do not investigate synergistic, antagonistic and additive effects as traditionally described in ecology.

Lines 472-474: This sentence is unclear. Do you mean that this approach surpasses others in terms of reliability? If so, I don't believe this has been demonstrated in the paper.

We apologise. The word ‘reliability’ should have not been in the text. We have improved the clarity of this sentence.

Lines 474-482: In these sentences it is unclear whether or not you are talking about your method or contrasting it with another method(s). If the latter, which method or methods are you referring to?

We have fixed this sentence to better reflect that our algorithm provides a high degree of confidence that surpasses state-of-the-art analysis, which predominantly identify patterns of co-occurrence of taxa within communities (e.g. Correlation-Centric Network).

Line 631: Should be "Physico-chemical variables". I have not extensively checked the rest of the methods for such errors.

Thank you, the text has been changed where present.

Reviewer #2 (Recommendations For The Authors):

Introduction Line 80 remove extra ')'

Done, thank you.

Line 81 rephrase e.g includes few freshwater ecosystems

We modified this sentence also following Reviewer #1

Line 83 although, instead of whereas?

Done, thanks.

Line 106 formatting reference issue

Line 109 same as above

Thank you, noted.

Results

Line 141 - 144 how was the sampling of the sediment performed over the 100 year core? Every year? Every 5 years? Or were they pooled to represent the (as of yet unlisted) phases?

The reviewer is correct that details are not provided here. They are in methods. We have added some text to explain the basic concepts of how the core was obtained and sliced and refer the reader to the method section for more details.

Line 154 the authors have not yet explicitly listed the lake phases, so it is difficult to refer to them now.

Noted, the addition of a short explanation at the beginning of the results section should take care of this issue.

Line 216 - may be worth briefly explaining KEGG orthologs and how these relate to functional biodiversity.

We thank the reviewer. Also responding to a similar comment from Reviewer #1, we included a description of KO terms and their links to functional biodiversity.

Lines 249 - 260 instead of a supplementary table, it could remain in the main text

Supplementary table 2 is a multi-tab table including information for each region amplified here. It is not possible to include this table in the main text.

Materials and Methods Due to the formatting of the manuscript (results & discussion before materials and methods), many of the results are not clearly understood without having to visit the M&M section. Particularly, how the biocide types were obtained (Historic records plus persistence of DDT in sediments). This could be resolved y including a few sentences on how the data was gathered in the results section. Overall, materials and methods are sufficient, however, it is not clear how many of the 37 metabarcoding samples correspond to which of the lake phases. Finally, I suggest a better organization of M&Ms by having subheadings for each section. For example, under Biodiversity fingerprinting across 100 years, one subheading could de DNA extraction and sequencing, another subheading could be bioinformatics.

We thank the reviewer for the suggestion. To alleviate the issues linked to the methods section coming after the results section, we have introduced a short explanation of the sediments core and the lake phases at the beginning of the results section. A description of the climate and chemical data has been included at the beginning of the section ‘Drivers of biodiversity change’ in results. Subheadings were introduced in methods as suggested.

Author Response

Reviewer #1 (Public Review):

.In the best genetically and biochemically understood model of eukaryotic DNA replication, the budding yeast, Saccharomyces cerevisiae, the genomic locations at which DNA replication initiates are determined by a specific sequence motif. These motifs, or ARS elements, are bound by the origin recognition complex (ORC). ORC is required for loading of the initially inactive MCM helicase during origin licensing in G1. In human cells, ORC does not have a specific sequence binding domain and origin specification is not specified by a defined motif. There have thus been great efforts over many years to try to understand the determinants of DNA replication initiation in human cells using a variety of approaches, which have gradually become more refined over time.

In this manuscript Tian et al. combine data from multiple previous studies using a range of techniques for identifying sites of replication initiation to identify conserved features of replication origins and to examine the relationship between origins and sites of ORC binding in the human genome. The authors identify a) conserved features of replication origins e.g. association with GC-rich sequences, open chromatin, promoters and CTCF binding sites. These associations have already been described in multiple earlier studies. They also examine the relationship of their determined origins and ORC binding sites and conclude that there is no relationship between sites of ORC binding and DNA replication initiation. While the conclusions concerning genomic features of origins are not novel, if true, a clear lack of colocalization of ORC and origins would be a striking finding.

Thank you. That is where the novelty of the paper lies.

However, the majority of the datasets used do not report replication origins, but rather broad zones in which replication origins fire. Rather than refining the localisation of origins, the approach of combining diverse methods that monitor different objects related to DNA replication leads to a base dataset that is highly flawed and cannot support the conclusions that are drawn, as explained in more detail below.

We are using the narrowly defined SNS-seq peaks as the gold standard origins and making sure to focus in on those that fall within the initiation zones defined by other methods. The objective is to make a list of the most reproducible origins. Unlike what the reviewer states, this actually refines the dataset to focus on the SNS origins that have also been reproduced by the other methods in multiple cell lines. We will change the last box of Fig. 1A to say: Identify reproducible SNS-seq origins that are contained in IZs defined by Repli-seq, OK-seq and Bubble-seq. These are the “shared origins”. This and the Fig. 2B (as it is) will make our strategy clearer.

Methods to determine sites at which DNA replication is initiated can be divided into two groups based on the genomic resolution at which they operate. Techniques such as bubble-seq, ok-seq can localise zones of replication initiation in the range ~50kb. Such zones may contain many replication origins. Conversely, techniques such as SNS-seq and ini-seq can localise replication origins down to less than 1kb. Indeed, the application of these different approaches has led to a degree of controversy in the field about whether human replication does indeed initiate at discrete sites (origins), or whether it initiates randomly in large zones with no recurrent sites being used. However, more recent work has shown that elements of both models are correct i.e. there are recurrent and efficient sites of replication initiation in the human genome, but these tend to be clustered and correspond to the demonstrated initiation zones (Guilbaud et al., 2022).

These different scales and methodologies are important when considering the approach of Tian et al. The premise that combining all available data from five techniques will increase accuracy and confidence in identifying the most important origins is flawed for two principal reasons. First, as noted above, of the different techniques combined in this manuscript, only SNS-seq can actually identify origins rather than initiation zones. It is the former that matters when comparing sites of ORC binding with replication origin sites if a conclusion is to be drawn that the two do not co-localise.

Exactly. So the reviewer should agree that our method of finding SNS-seq peaks that fall within initiation zones actually refines the origins to find the most reproducible origins. We are not losing the spatial precision of the SNS-seq peaks.

Second, the authors give equal weight to all datasets. Certainly, in the case of SNS-seq, this is not appropriate. The technique has evolved over the years and some earlier versions have significantly different technical designs that may impact the reliability and/or resolution of the results e.g. in Foulk et al. (Foulk et al., 2015), lambda exonuclease was added to single stranded DNA from a total genomic preparation rather than purified nascent strands), which may lead to significantly different digestion patterns (ie underdigestion). Curiously, the authors do not make the best use of the largest SNS-seq dataset (Akerman et al., 2020) by ignoring these authors separation of core and stochastic origins. By blending all data together any separation of signal and noise is lost. Further, I am surprised that the authors have chosen not to use data and analysis from a recent study that provides subsets of the most highly used and efficient origins in the human genome, at high resolution (Guilbaud et al., 2022).

1) We are using the data from Akerman et al., 2020: Dataset GSE128477 in Supplemental Table 1. We can examine the core origins defined by the authors to check its overlap with ORC binding.

2) To take into account the refinement of the SNS-seq methods through the years, we actually included in our study only those SNS-seq studies after 2018, well after the lambda exonuclease method was introduced. Indeed, all 66 of SNS-seq datasets we used were obtained after the lambda exonuclease digestion step. To reiterate, we recognize that there may be many false positives in the individual origin mapping datasets. Our focus is on the True positives, the SNS-seq peaks that have some support from multiple SNS-seq studies AND fall within the initiation zones defined by the independent means of origin mapping (described in Fig. 1A and 2B). These True positives are most likely to be real and reproducible origins and should be expected to be near ORC binding sites.

We will change the last box of Fig. 1A to say: Identify reproducible SNS-seq origins that are contained in IZs defined by Repli-seq, OK-seq and Bubble-seq. These are the “Shared origins”.

Ini-seq by Torsten Krude and co-workers (Guillbaud, 2022) does NOT use Lambda exonuclease digestion. So using Ini-seq defined origins is at odds with the suggestion above that we focus only on SNS-seq datasets that use Lambda exonuclease. However, Ini-seq identifies a much smaller subset of SNS-seq origins, so we will do the analysis with just that smaller set in the revision of the paper.

References:

Akerman I, Kasaai B, Bazarova A, Sang PB, Peiffer I, Artufel M, Derelle R, Smith G, Rodriguez-Martinez M, Romano M, Kinet S, Tino P, Theillet C, Taylor N, Ballester B, Méchali M (2020) A predictable conserved DNA base composition signature defines human core DNA replication origins. Nat Commun, 11: 4826

Foulk MS, Urban JM, Casella C, Gerbi SA (2015) Characterizing and controlling intrinsic biases of lambda exonuclease in nascent strand sequencing reveals phasing between nucleosomes and G-quadruplex motifs around a subset of human replication origins. Genome Res, 25: 725-735

Guilbaud G, Murat P, Wilkes HS, Lerner LK, Sale JE, Krude T (2022) Determination of human DNA replication origin position and efficiency reveals principles of initiation zone organisation. Nucleic Acids Res, 50: 7436-7450

Reviewer #2 (Public Review):

Tian et al. perform a meta-analysis of 113 genome-wide origin profile datasets in humans to assess the reproducibility of experimental techniques and shared genomics features of origins. Techniques to map DNA replication sites have quickly evolved over the last decade, yet little is known about how these methods fare against each other (pros and cons), nor how consistent their maps are. The authors show that high-confidence origins recapitulate several known features of origins (e.g., correspondence with open chromatin, overlap with transcriptional promoters, CTCF binding sites). However, surprisingly, they find little overlap between ORC/MCM binding sites and origin locations.

Overall, this meta-analysis provides the field with a good assessment of the current state of experimental techniques and their reproducibility, but I am worried about: (a) whether we've learned any new biology from this analysis; (b) how binding sites and origin locations can be so mismatched, in light of numerous studies that suggest otherwise; and (c) some methodological details described below.

Major comments:

Line 26: "0.27% were reproducibly detected by four techniques" -- what does this mean? Does the fragment need to be detected by ALL FOUR techniques to be deemed reproducible?

If the reproducible SNS-seq peaks are included in the reproducible initiation zones found by the other methods, then we consider it reproducible across datasets. The strategy is to focus our analysis on the most reproducible SNS-seq peaks that happen to be in reproducible initiation zones. It is the best way to confidently identify a very small set of true positive origins.

And what if the technique detected the fragment is only 1 of N experiments conducted; does that count as "detected"?

A reproducible SNS-seq origin has been reproduced above a statistical threshold of 20 reproductions. A threshold of reproduction in 20 datasets out of 66 SNS-seq datasets gives an FDR of <0.1. This is explained in Fig. 2a and Supplementary Fig. S2. For the initiation zones, we considered a Zone even if it appears in only 1 of N experiments, because N is usually small. This relaxed method for selecting the initiation zones gives the best chance of finding SNS-seq peaks that are reproduced by the other methods.

Later in Methods, the authors (line 512) say, "shared origins ... occur in sufficient number of samples" but what does sufficient mean?

Sufficient means that SNS-seq origin was reproducibly detected in ≥ 20 datasets and was included in any initiation zone defined by three other techniques.

Then on line 522, they use a threshold of "20" samples, which seems arbitrary to me. How are these parameters set, and how robust are the conclusions to these settings? An alternative to setting these (arbitrary) thresholds and discretizing the data is to analyze the data continuously; i.e., associate with each fragment a continuous confidence score.

We explained Fig. 2a and Supplementary Fig. S2 in the text as follows: The occupancy score of each origin defined by SNS-seq (Supplementary Fig. 2a) counts the frequency at which a given origin is detected in the datasets under consideration. For the random background, we assumed that the number of origins confirmed by increasing occupancy scores decreases exponentially (see Methods and Supplementary Table 2). Plotting the number of origins with various occupancy scores when all SNS-seq datasets published after 2018 are considered together (the union origins) shows that the experimental curve deviates from the random background at a given occupancy score (Fig. 2a). The threshold occupancy score of 20 is the point where the observed number of origins deviates from the expected background number (with an FDR < 0.1) (Fig. 2a). In the Methods: In other words, the number of observed origins with occupancy score greater than 20 is 10 times more than expected in the background model. This approach is statistically sound and described by us in (Fang et al. 2020).

Line 20: "50,000 origins" vs "7.5M 300bp chromosomal fragments" -- how do these two numbers relate? How many 300bp fragments would be expected given that there are ~50,000 origins? (i.e., how many fragments are there per origin, on average)? This is an important number to report because it gives some sense of how many of these fragments are likely nonsense/noise. The authors might consider eliminating those fragments significantly above the expected number, since their inclusion may muddle biological interpretation.

I think we confused the reviewer by the way we wrote the abstract. The 50,000 origins that are mentioned in the abstract is the hypothetical expected number of origins that have to fire to replicate the whole 6x10^9 base diploid genome based on the average inter-origin distance of 10^5 bases (as determined by molecular combing). The 7.5M 300 bp fragments are the genomic regions where the 7.5M union SNS-seq-defined origins are located. Clearly, that is a lot of noise, some because of technical noise and some due to the fact that origins fire stochastically. Which is why our paper focuses on a smaller number of reproducible origins, the 20,250 shared origins. Our analysis is on the 20,250 shared origins, and not on all 7.5M union origins. Thus, we are not including the excess of non-reproducible (stochastic?) origins in our analysis.

The revised abstract in the revised paper will say: “Based on experimentally determined average inter-origin distances of ~100 kb, DNA replication initiates from ~50,000 origins on human chromosomes in each cell-cycle. The origins are believed to be specified by binding of factors like the Origin Recognition Complex (ORC) or CTCF or other features like G-quadruplexes. We have performed an integrative analysis of 113 genome-wide human origin profiles (from five different techniques) and 5 ORC-binding site datasets to critically evaluate whether the most reproducible origins are specified by these features. Out of ~7.5 million union origins identified by 66 SNS-seq datasets, only 0.27% were reproducibly contained in initiation zones identified by three other techniques (20,250 shared origins), suggesting extensive variability in origin usage and identification in different circumstances.”

Line 143: I'm not terribly convinced by the PCA clustering analysis, since the variance explained by the first 2 PCs is only ~25%. A more robust analysis of whether origins cluster by cell type, year etc is to simply compute the distribution of pairwise correlations of origin profiles within the same group (cell type, year) vs the correlation distribution between groups. Relatedly, the authors should explain what an "origin profile" is (line 141). Is the matrix (to which PCA is applied) of size 7.5M x 113, with a "1" in the (i,j) position if the ith fragment was detected in the jth dataset?

The reviewer is correct about how we did the PCA and have now included the description in the Methods. We will also do the pairwise correlations the way the reviewer suggests (a) by techniques, (b) by cell types (SNS-seq), (c) by year of publication (SNS-seq).

It's not clear to me what new biology (genomic features) has been learned from this meta-analysis. All the major genomic features analyzed have already been found to be associated with origin sites. For example, the correspondence with TSS has been reported before:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6320713/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547456/

So what new biology has been discovered from this meta-analysis?

The new biology can be summarized as: (a) We can identify a set of reproducible (in multiple datasets and in multiple cell lines) SNS-seq origins that also fall within initiation zones identified by completely independent methods. These may be the best origins to study in the midst of the noise created by stochastic origin firing. (b) The overlap of these True Positive origins with known ORC binding sites is tenuous. So either all the origin mapping data, or all the ORC binding data has to be discarded, or this is the new biological reality in mammalian cancer cells: on a genome-wide scale the most reproduced origins are not in close proximity to ORC binding sites, in contrast to the situation in yeast. (c) All the features that have been reported to define origins (CTCF binding sites, G quadruplexes etc.) could simply be from the fact that those features also define transcription start sites (TSS), and origins prefer to be near TSS because of the favorable chromatin state.

Line 250: The most surprising finding is that there is little overlap between ORC/MCM binding sites and origin locations. The authors speculate that the overlap between ORC1 and ORC2 could be low because they come from different cell types. Equally concerning is the lack of overlap with MCM. If true, these are potentially major discoveries that butts heads with numerous other studies that have suggested otherwise. More needs to be done to convince the reader that such a mis-match is true. Some ideas are below:

Idea 1) One explanation given is that the ORC1 and ORC2 data come from different cell types. But there must be a dataset where both are mapped in the same cell type. Can the authors check the overlap here? In Fig S4A, I would expect the circles to not only strongly overlap but to also be of roughly the same size, since both ORC's are required in the complex. So something seems off here.

We agree with the reviewer that there is something “off here”. Either the techniques that report these sites are all wrong, or the biology does not fit into the prevailing hypothesis. One secret in the ORC ChIP field that our lab has struggled with for quite some time is that the various ORC subunits do not necessarily ChiP-seq to the same sites. The poor overlap between the binding sites of subunits of the same complex either suggests that the subunits do not always bind to the chromatin as a six-subunit complex or that all the ChIP-seq data in the Literature is suspect. We provide in the supplementary figure S4A examples of true positive complexes (SMARCA4/ARID1A, SMC1A/SMC3, EZH2/SUZ12), whose subunits ChIP-seq to a large fraction of common sites. As shown in Supplementary Fig. S4C, we do not have ORC1 and ORC2 ChIP-seq data from the same cell-type. We have ORC1 ChIP-seq and SNS-seq data from HeLa cells and ORC2 ChIP seq and origins from K562 cells, and so will add the proximity/overlap of the binding sites to the origins in the same cell-type in the revision.

Idea 2) Another explanation given is that origins fire stochastically. One way to quantify the role of stochasticity is to quantify the overlap of origin locations performed by the same lab, in the same year, in the same experiment, in the same cell type -- i.e., across replicates -- and then compute the overlap of mapped origins. This would quantify how much mis-match is truly due to stochasticity, and how much may be due to other factors.

A given lab may have superior reproducibility compared to the entire field. But the notion of stochasticity is well accepted in the field because of this observation: the average inter-origin distance measured by single molecule techniques like molecular combing is ~100 kb, but the average inter-origin distance measure on a population of cells (same cell line) is ~30 kb. The only explanation is that in a population of cells many origins can fire, but in a given cell on a given allele, only one-third of those possible origins fire. This is why we did not worry about the lack of reproducibility between cell-lines, labs etc, but instead focused on those SNS-seq origins that are reproducible over multiple techniques and cell lines.

Idea 3) A third explanation is that MCMs are loaded further from origin sites in human than in yeast. Is there any evidence of this? How far away does the evidence suggest, and what if this distance is used to define proximity?

MCMs, of course, have to be loaded at an origin at the time the origin fires because MCMs provide the core of the helicase that starts unwinding the DNA at the origin. Thus, the lack of proximity of MCM binding sites with origins can be because the most detected MCM sites (where MCM spends the most time in a cell-population) does not correspond to where it is first active to initiate origin firing. This has been discussed. MCMs may be loaded far from origin site, but because of their ability to move along the chromatin, they have to move to the origin-site at some point to fire the origin.

Idea 4) How many individual datasets (i.e., those collected and published together) also demonstrate the feature that ORC/MCM binding locations do not correlate with origins? If there are few, then indeed, the integrative analysis performed here is consistent. But if there are many, then why would individual datasets reveal one thing, but integrative analysis reveal something else?

We apologize for this oversight. In the revised manuscript we will discuss PMC3530669, PMC7993996, PMC5389698, PMC10366126. None of them have addressed what we are addressing, which is whether the small subset of the most reproducible origins proximal to ORC or MCM binding sites, but the discussion is essential.

Idea 5) What if you were much more restrictive when defining "high-confidence" origins / binding sites. Does the overlap between origins and binding sites go up with increasing restriction?

We will make origins more restrictive by selecting those reproduced by 30-60 datasets. The number of origins will of course fall, but we will measure whether the proximity to ORC or MCM-binding sites increases/decreases in a statistically rigorous way.

Overall, I have the sense that these experimental techniques may be producing a lot of junk. If true, this would be useful for the field to know! But if not, and there are indeed "unexplored mechanisms of origin specification" that would be exciting. But I'm not convinced yet.

It would be nice in the Discussion for the authors to comment about the trade-offs of different techniques; what are their pros and cons, which should be used when, which should be avoided altogether, and why? This would be a valuable prescription for the field.

Thanks for the suggestion. We will do what the reviewer suggests: use cell type-specific data wherever origins have been defined by at least two methods in the same cell type, specifically reporting the percent of shared origins amongst the datasets to compare whether some methods correlate better with each other. ORC ChIP-seq and MCM ChIP-seq data do not define origins: they define the binding sites of these proteins. Thus we will discuss why the ChIP-seq sites of these protein complexes should not be used to define origins.

Reviewer #3 (Public Review):

Summary: The authors present a thought-provoking and comprehensive re-analysis of previously published human cell genomics data that seeks to understand the relationship between the sites where the Origin Recognition Complex (ORC) binds chromatin, where the replicative helicase (Mcm2-7) is situated on chromatin, and where DNA replication actually beings (origins). The view that these should coincide is influenced by studies in yeast where ORC binds site-specifically to dedicated nucleosome-free origins where Mcm2-7 can be loaded and remains stably positioned for subsequent replication initiation. However, this is most certainly not the case in metazoans where it has already been reported that chromatin bindings sites of ORC, Mcm2-7, and origins do not necessarily overlap, likely because ORC loads the helicase in transcriptionally active regions of the genome and, since Mcm2-7 retains linear mobility (i.e., it can slide), it is displaced from its original position by other chromatin-contextualized processes (for example, see Gros et al., 2015 Mol Cell, Powell et al., 2015 EMBO J, Miotto et al., 2016 PNAS, and Prioleau et al., 2016 G&D amongst others). This study reaches a very similar conclusion: in short, they find a high degree of discordance between ORC, Mcm2-7, and origin positions in human cells.

Strengths: The strength of this work is its comprehensive and unbiased analysis of all relevant genomics datasets. To my knowledge, this is the first attempt to integrate these observations and the analyses employed were suited for the questions under consideration.

Thank you for recognizing the comprehensive and unbiased nature of our analysis. The fact that the major weakness is that the comprehensive view fails to move the field forward, is actually a strength. It should be viewed in the light that we cannot even find evidence to support the primary hypothesis: that the most reproducible origins must be near ORC and MCM binding sites. This finding will prevent the unwise adoption of ORC or MCM binding sites as surrogate markers of origins and may perhaps stimulate the field to try and improve methods of identifying ORC or MCM binding until the binding sites are found to be proximal to the most reproducible origins. The last possibility is that there are ORC- or MCM-independent modes of defining origins, but we have no evidence of that.

Weaknesses: The major weakness of this paper is that this comprehensive view failed to move the field forward from what was already known. Further, a substantial body of relevant prior genomics literature on the subject was neither cited nor discussed. This omission is important given that this group reaches very similar conclusions as studies published a number of years ago. Further, their study seems to present a unique opportunity to evaluate and shape our confidence in the different genomics techniques compared in this study. This, however, was also not discussed.

We will do what the reviewer suggests: use cell type-specific data wherever origins have been defined by at least two methods in the same cell type, specifically reporting the percent of shared origins amongst the datasets to compare whether some methods correlate better with each other. Thanks for the suggestion. ORC ChIP-seq and MCM ChIP-seq data do not define origins: they define the binding sites of these proteins. Thus, we will discuss why the ChIP-seq sites of these protein complexes should not be used to define origins.

We do not cite the SNS-seq data before 2018 because of the concerns discussed above about the earlier techniques needing improvement. We will discuss other genomics data that we failed to discuss.

We will cite the papers the reviewer names:

Gros, Mol Cell 2015 and Powell, EMBO J. 2015 discuss the movement of MCM2-7 away from ORC in yeast and fliesand will be cited. MCM2-7 binding to sites away from ORC and being loaded in vast excess of ORC was reported earlier on Xenopus chromatin in PMC193934, and will also be cited.

Miotto, PNAS, 2016: publishes ORC2 ChIP-seq sites in HeLa (data we have used in our analysis), but do not measure ORC1 ChIP-seq sites. They say: “ORC1 and ORC2 recognize similar chromatin states and hence are likely to have similar binding profiles.” This is a conclusion based on the fact that the ChIP seq sites in the two studies are in areas with open chromatin, it is not a direct comparison of binding sites of the two proteins.

Prioleau, G&D, 2016: This is a review that compared different techniques of origin identification but has no primary data to say that ORC and MCM binding sites overlap with the most reproducible origins.

Author Response

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

Reviewer #1 (Public Review):

This study investigates the context-specificity of facial expressions in three species of macaques to test predictions for the 'social complexity hypothesis for communicative complexity'. This hypothesis has garnered much attention in recent years. A proper test of this hypothesis requires clear definitions of 'communicative complexity' and 'social complexity'. Importantly, these two facets of a society must not be derived from the same data because otherwise, any link between the two would be trivial. For instance, if social complexity is derived from the types of interactions individuals have, and different types of signals accompany these interactions, we would not learn anything from a correlation between social and communicative complexity, as both stem from the same data.

The authors of the present paper make a big step forward in operationalising communicative complexity. They used the Facial Action Coding System to code a large number of facial expressions in macaques. This system allows decomposing facial expressions into different action units, such as 'upper lid raiser', 'upper lip raiser' etc.; these units are closely linked to activating specific muscles or muscle groups. Based on these data, the authors calculated three measures derived from information theory: entropy, specificity and prediction error. These parts of the analysis will be useful for future studies.

The three species of macaque varied in these three dimensions. In terms of entropy, there were differences with regard to context (and if there are these context-specific differences, then why pool the data?). Barbary and Tonkean macaques showed lower specificity than rhesus macaques. Regarding predicting context from the facial signals, a random forest classifier yielded the highest prediction values for rhesus monkeys. These results align with an earlier study by Preuschoft and van Schaik (2000), who found that less despotic species have greater variability in facial expressions and usage.

Crucially, the three species under study are also known to vary in terms of their social tolerance. According to the highly influential framework proposed by Bernard Thierry, the members of the genus Macaca fall along a graded continuum from despotic (grade 1) to highly tolerant (grade 4). The three species chosen for the present study represent grade 1 (rhesus monkeys), grade 3 (Barbary macaques), and grade 4 (Tonkean macaques).

The authors of the present paper define social complexity as equivalent to social tolerance - but how is social tolerance defined? Thierry used aggression and conflict resolution patterns to classify the different macaque species, with the steepness of the rank hierarchy and the degree of nepotism (kin bias) being essential. However, aggression and conflict resolution are accompanied by facial gestures. Thus, the authors are looking at two sides of the same coin when investigating the link between social complexity (as defined by the authors) and communicative complexity. Therefore, I am not convinced that this study makes a significant advance in testing the social complexity for communicative complexity hypothesis. A further weakness is that - despite the careful analysis - only three species were considered; thus, the effective sample size is very small.

Social tolerance in macaques is defined by various covarying traits, among which rates of counter-aggression and conflict resolution are only two of many included (see Thierry 2021 for a recent discussion and review). We do not deviate from Thierry’s definition of social tolerance. We simply highlight that the constellation of behavioral traits in the most tolerant macaque species results in a social environment where the outcome of social interactions is more uncertain (see introduction lines 102-114). As we argue throughout the paper, higher uncertainty can be used as a proxy for higher complexity and thus we conclude that the most tolerant macaque species have the highest social complexity. While most social behavior in macaques is accompanied by some facial behavior, we were careful to define social contexts only from the body language/behavior (e.g., lunge for aggression, grooming for affiliation) of the individuals involved and ignored the facial behavior used (see method lines 371-381). Therefore, the facial behavior of macaques (communication signals) was not used in defining either social tolerance (and by extension complexity) or the social context in which it was used. We feel like this appropriately minimizes any elements of circularity in the analysis of social and communicative complexity.

Regarding the effective sample size of three species, we agree that it is small, and it is a limitation of this study. However, the methodology we used is applicable to any species for which FACS is available (including other non-human primates, dogs, and horses), and therefore, we hope that other datasets will complement ours in the future. Nevertheless, we now acknowledge this limitation in the discussion (lines 314317).

Reviewer #2 (Public Review):

This is a well-written manuscript about a strong comparative study of diversity of facial movements in three macaque species to test arguments about social complexity influencing communicative complexity. My major criticism has to do with the lack of any reporting of inter-observer reliability statistics - see comment below. Reporting high levels of inter-observer reliability is crucial for making clear the authors have minimized chances of possible observer biases in a study like this, where it is not possible to code the data blind with regard to comparison group. My other comments and questions follow by line number:

We agree that inter-observer coding reliability is an important piece of information. We now report in more detail the inter-observer reliability tests that we conducted on lines 384-392.

38-40. Whereas I am an advocate of this hypothesis and have tested it myself, the authors should probably comment here, or later in the discussion, about the reverse argument - greater communicative complexity (driven by other selection pressures) could make more complicated social structures possible. This latter view was the one advocated by McComb & Semple in their foundational 2005 Biology Letters comparative study of relationships between vocal repertoire size and typical group size in non-human primate species.

It is true that an increase in communicative complexity could allow/drive an increase in social complexity. Unfortunately our data is correlational in nature and we cannot determine the direction of causality. We added such a statement to the discussion (lines 311-314).

72-84 and 95-96. In the paragraph here, the authors outline an argument about increasing uncertainty / entropy mapping on to increasing complexity in a system (social or communicative). In lines 95-96, though, they fall back on the standard argument about complex systems having intermediate levels of uncertainty (complete uncertainty roughly = random and complete certainty roughly = simple). Various authors have put forward what I think are useful ways of thinking about complexity in groups - from the perspective of an insider (i.e., a group member, where greater randomness is, in fact, greater complexity) vs from the perspective of an outside (i.e., a researcher trying to quantify the complexity of the system where is it relatively easy to explain a completely predictable or completely random system but harder to do so for an intermediately ordered or random system). This sort of argument (Andrew Whiten had an early paper that made this argument) might be worth raising here or later in the discussion? (I'm also curious where the authors sentiments lie for this question - they seem to touch on it in lines 285-287, but I think it's worth unpacking a little more here!)

In this study we used three measures of uncertainty (entropy, context specificity, and prediction error) to approximate complexity. However, maximum entropy or uncertainty would be achieved in a system that is completely random (and thus be considered simple). Therefore, the species with the highest entropy values, or unpredictability, could be interpreted as having a simpler communication system than a species with a moderately high entropy/unpredictability value. Our argument is that animal communication systems cannot possibly be random, otherwise they would not have evolved as signals. In systems where we know the highest entropy (or unpredictability) will not be due to randomness, as is the case with animal social interactions and communication, we can conclude that the system with the highest uncertainty is the most complex. We have now expanded upon this point in the discussion (lines 286-294). See also response to reviewer 1 below.

115-129. See also:

Maestripieri, D. (2005). "Gestural communication in three species of macaques (Macaca mulatta, M. nemestrina, M. arctoides): use of signals in relation to dominance and social context." Gesture 5: 57-73.

Maestripieri, D. and K. Wallen (1997). "Affiliative and submissive communication in rhesus macaques." Primates 38(2): 127-138.

On that note, it is probably worth discussing in this paragraph and probably later in the discussion exactly how this study differs from these earlier studies of Maestripieri. I think the fact that machine learning approaches had the most difficulty assigning crested data to context is an important methodological advance for addressing these sorts of questions - there are probably other important differences between the authors' study here and these older publications that are worth bringing up.

Our study differs from these two studies in that the studies above classified facial behavior into discrete categories (e.g., bared-teeth, lip-smack), whereas we adopted a bottom-up approach and made no a priori assumptions about which movements are relevant. We broke down facial behavior down to their individual muscle movements (i.e., Action Units). Measuring facial behavior at the level of individual muscle movements allows for a more detailed and objective description of the complexity of facial behavior. This is a general point in advancing the study of facial behavior that is discussed in the introduction (lines 60-71) and discussion (lines 206-208). The reason we don’t draw a direct comparison with the studies above is because they had a slightly different focus. Our study was more focused on complexity of the (facial) communication system in general rather than comparing whether the different species use the same facial behavior in the same/different social contexts.

220-222. What is known about visual perception in these species? Recent arguments suggest that more socially complex species should have more sensitive perceptual processing abilities for other individuals' signals and cues (see Freeberg et al. 2019 Animal Behaviour). Are there any published empirical data to this effect, ideally from the visual domain but perhaps from any domain?

This is an interesting point. We are not aware of any studies showing differences in visual perceptions within the macaque genus. Both crested macaques and rhesus macaques are able to discriminate between individuals and facial expressions in match-to-sample tasks with comparable performances (Micheletta et al., 2015a, 2015b; Parr et al. 2008; Parr & Heinz, 2009). Similarly, several macaque species are sensitive to gaze shifts from conspecifics (Tomasello et al. 1998; Teufel et al. 2010; Micheletta & Waller, 2012).

274-277. I am not sure I follow this - could not different social and non-social contexts produce variation in different affective states such that "emotion"-based signals could be as flexible / uncertain as seemingly volitional / information-based / referential-like signals? This issue is probably too far away from the main points of this paper, but I suspect the authors' argument in this sentence is too simplified or overstated with regard to more affect-based signals.

Emotion-based signals could, in theory, also produce flexible signals and it is possible that some facial expressions reflect an emotional state. However, some previous studies have suggested that facial expressions are only used as a display of emotion, rather than such signals having evolved for a different function such as announcing future intentions. In our study we found that macaques used, in some cases, the same facial expressions (i.e. combination of Action Units) in at least two different social contexts that, presumably, differed in their emotional valence. Thus, it is unlikely that particular facial expressions are bound to a single emotion. We think that this is an important point to make even though it is slightly beyond the scope of our paper.

288 on. Given there are only three species in this study, the chances of one of the species being the 'most complex' in any measure is 0.33. Although I do not believe this argument I am making here, can the authors rule out the possibility that their findings related to crested macaques are all related to chance, statistically speaking?

We are not aware of a way to rule out this possibility. However, we believe that we are appropriately cautious throughout the paper and acknowledge that having only investigated three species is a limitation of this study in the discussion (lines 314-317, see also our response to reviewer 1 above).

329-330. The fact that only one male rhesus macaque was assessed here seems problematic, given the balance of sexes in the other two species. Can the authors comment more on this - are the gestures they are studying here identical across the sexes?

We agree it would have been preferable to collect data on more than one male rhesus macaque, but that was unfortunately not possible. We are not aware of any studies showing differences in the use of facial behavior between male and female rhesus macaques. If differences exist, most likely these would occur in a sexual/mating context. However, in our study we only considered affiliative (non-sexual), submissive, and aggressive contexts, where we have no a priori reason to believe that there are sex differences.

354-371. Inter-observer reliability statistics are required here - one of the authors who did not code the original data set, or a trained observer who is not an author, could easily code a subset of the video files to obtain inter-observer reliability data. This is important for ruling out potential unconscious observer biases in coding the data.

We agree this is an important piece of information. We now report in more detail the inter-observer reliability tests that we conducted on lines 384-392:

“An agreement rating of >0.7 was considered good [Ekman et al 2002] and was necessary for obtaining certification. To obtain a MaqFACS coding certification, AVR, CP, and PRC coded 23 video clips of rhesus macaques and the MaqFACS codes were compared to the data of other certified coders (https://animalfacs.com).

The mean agreement ratings obtained were 0.85, 0.73, 0.83 for AVR, CP, and PRC, respectively. In addition, AVR and CP coded 7 videos of Barbary macaques with a mean agreement rating of 0.79. AVR and PRC coded 10 videos of crested macaques with a mean agreement rating of 0.74.”

Reviewer #1 (Recommendations For The Authors):

Given the long debate on the concept of information exchange in animal communication, I would also recommend being more careful with the term 'exchanges of information' (line 271). Perhaps it's better to be agnostic in the context of this paper.

As suggested, we now changed the phrasing to focus on the behavior of the animals, rather than suggesting that information is being exchanged (lines 270-273),

Line 281: "This result confirms the assumption that facial behaviour in macaques is not used randomly": the authors are knocking down a straw man. Nobody who has ever studied animal communication would consider that signals occur randomly. Otherwise, they would not have evolved as signals.

Indeed, nobody claims that animal communication signals are used randomly. Although it may be taken for granted, we feel it is worthwhile to reiterate this point, given that we used relative entropy and prediction error as measures of complexity. For instance, maximum entropy or unpredictability would be achieved in a system that is completely random (and thus be considered simple). Therefore, the species with the highest entropy values, or lowest predictability, could be interpreted as having a simpler communication system than a species with a moderately high entropy value. But if we are working under the assumption that animal communication systems cannot possibly be random, then we can conclude that the species whose communication system has the highest entropy is in fact the most complex. We tried to make this justification clearer in the discussion (lines 285-294).

I did not follow why there is a higher reliance on facial signals when predation pressure is higher. Apart from the fact that the authors cannot address this question, they may want to reconsider this idea altogether.

We now expand on the logic of why predation pressure might affect the use of facial signals (see lines 308-309): “When predation pressure is higher, reliance on facial signals could be higher than, for example vocal signals, such as to not draw attention of predators to the signaller.”

Technical comments:

One methodological issue that requires clarification is what the units of analysis are. The authors write that each row in their analysis denoted an observation time of 500 ms. How many rows did the authors assemble? The authors mention a sample size of > 3000 social interactions in the abstract. How did they define social interactions? And how many 'time windows' of 500 ms were obtained? Did they take one window per interaction or several? If several, then how was this move accounted for in the analysis? The reporting needs to be more accurate here. Most likely, the bootstrapping took care of biases in the data, but still, this information needs to be provided.

We have now added some additional information to the method section. Social interactions for each context had the following definitions: “Social context was labeled from the point of view of the signaler based on their general behavior and body language (but not the facial behavior itself), during or immediately following the facial behavior. An aggressive context was considered when the signaler lunged or leaned forward with the body or head, charged, chased, or physically hit the interaction partner. A submissive context was considered when the signaler leaned back with the body or head, moved away, or fled from the interaction partner. An affiliative context was considered when the signaler approached another individual without aggression (as defined previously) and remained in proximity, in relaxed body contact, or groomed either during or immediately after the facial behavior. In cases where the behavior of the signaler did not match our context definitions, or displayed behaviors belonging to multiple contexts, we labeled the social context as unclear. Social context was determined from the video itself and/or from the matching focal behavioral data, if available.” (lines 371-382). The total duration of all social interactions per social context, and thus the number of 500ms windows/rows, have been added to Table 1 (lines 395-397). There were several 500ms windows per social interaction. All 500ms time blocks per interaction were used in the statistical analyses in order to retain all the variation and complexity of the facial behavior (Action Unit combinations) used by the macaques (lines 403-405). Indeed the bootstrapping procedure was used to account for any biases in the data.

Overall, I would recommend providing more information on the actual behaviour of the animals. The paper is strong in handling highly derived indices representing the behaviour, but the reader learns little about the animals' behaviour. Thus, it would be great if statements about the entropy ratio were translated into what these measures represent in real life. For context specificity, this is clear, but for entropy, not so much.

A high entropy ratio essentially suggests that a species uses a high variety of unique facial behavior/signals and all signals in the repertoire are used roughly equally often (rather than one facial behavior being used 90% of the time and others rarely used). We have tried our best to better explain this point in the introduction (lines 75-81) and discussion (lines 215-222). Discussing exactly what these signals are and what they mean was beyond the scope of this paper.

Line 106: nepotism, not kinship

Changed as suggested (line 106).

Line 113: I would avoid statements about how a monkey society is perceived by its members.

We think that noting how individuals may perceive their social environment is worthwhile when defining social complexity, so have retained this point but changed the phrasing to be more speculative (lines 112-113).

Line 329: I was very surprised that only one male was represented in the data for rhesus monkeys. The authors try to wriggle their way out of this issue in the supplementary material ("Therefore, we have no a priori reason to expect an overall difference in the diversity and complexity of facial behaviour between the sexes"), but I think this is a major shortcoming of the analysis. They should ascertain whether there are no sex differences in the other two species regarding their variables of interest. They could then make a very cautious case for there being no sex differences in rhesus either. But of course, they would not know for sure.

As with our response to reviewer 2 above, we agree that it would have been preferable to collect data on more than one male rhesus macaque, but that was unfortunately not possible. We are not aware of any studies showing differences in the use of facial behavior between male and female rhesus macaques. If differences exist, most likely these would occur in a sexual/mating context. However, in our study we only considered affiliative (non-sexual), submissive, and aggressive contexts, where we have no a priori reason to believe that there are sex differences. Looking at sex differences in the use of facial behavior would be a worthwhile study on its own, but it is outside the scope of this paper.

This paper would make a stronger contribution if it focussed on the comparative analysis of facial expressions and removed the attempt of testing the social complexity for communicative complexity hypothesis.

A comparative analysis of the contextual use of specific facial movements is important. But this paper is focused on making a more general comparison of the communication style and complexity across species. The social complexity hypothesis for communicative complexity is one of the key theoretical frameworks for such an investigation and allows us to frame our study in a broader context. We contribute important data on 3 species with methods that can be replicated and extended to others species. Therefore, we believe that it is a worthy contribution to investigations of the evolution of complex communication.

REFERENCES

Micheletta, J., J. Whitehouse, L.A. Parr, and B.M. Waller. ‘Facial Expression Recognition in Crested Macaques (Macaca nigra)’. Animal Cognition 18 (2015): 985–90. https://doi.org/10/f7fvnh.

Micheletta, Jérôme, Jamie Whitehouse, Lisa A. Parr, Paul Marshman, Antje Engelhardt, and Bridget M. Waller. ‘Familiar and Unfamiliar Face Recognition in Crested Macaques (Macaca nigra)’. Royal Society Open Science 2 (2015): 150109. https://doi.org/10/ggx9k9.

Parr, L. A., and M. Heintz. ‘Facial Expression Recognition in Rhesus Monkeys, Macaca mulatta’. Animal Behaviour 77 (2009): 1507–13. https://doi.org/10/bbsp5n.

Parr, L.A., M. Heintz, and G. Pradhan. ‘Rhesus Monkeys (Macaca mulatta) Lack Expertise in Face Processing’. Journal of Comparative Psychology 122 (2008): 390–402. https://doi.org/10/d7w6bv.

Micheletta, J., and B.M. Waller. ‘Friendship Affects Gaze Following in a Tolerant Species of Macaque, Macaca nigra’. Animal Behaviour 83 (2012): 459–67. https://doi.org/10/c4f8n2.

Thierry B. Where do we stand with the covariation framework in primate societies? Am. J. Biol. Anthropol. 128 (2021): 5–25. https://doi.org/10.1002/ajpa.24441

Tomasello, M., J. Call, and B. Hare. ‘Five Primate Species Follow the Visual Gaze of Conspecifics’. Animal Behaviour 55 (1998): 1063–69. https://doi.org/10/bmq7xh.

Teufel, C., A. Gutmann, R. Pirow, and J. Fischer. ‘Facial Expressions Modulate the Ontogenetic Trajectory of Gaze-Following among Monkeys’. Developmental Science 13 (2010): 913–22. https://doi.org/10/b6j5r7.

Author Response

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

We are grateful for the helpful comments of both reviewers and have revised our manuscript with them in mind.

One of the main issues raised was that readers may by default assume that our models are correct. We in fact made it very clear in our discussion that the models are merely hypotheses that will need testing by “wet” experiments and we do not therefore agree that even readers unfamiliar with AF would assume that the models must be correct. It was also suggested that readers could be reassured by including extensive confidence estimates such as PAE plots. As it happens, every single model described in the manuscript had reasonably high PAE scores and more crucially the entire collection of output files, including PAE data, are readily accessible on Figshare at https://doi.org/10.6084/m9.figshare.22567318.v2, a fact that the reviewers appear to have overlooked. The Figshare link is mentioned three times in the manuscript. Embedding these data within the manuscript itself would in our view add even more details and we have therefore not included them in our revised manuscript. Likewise, it is rather simple for any reader to work out which part of a PAE matrix corresponds to an interaction observed in the corresponding pdb prediction. Besides which, it is our view that the biological plausibility and explanatory power of models is just as important as AF metrics in judging whether they may be correct, as is indeed also the case for most experimental work.

Another important point was that the manuscript was too long and not readable. Yes, it is long and it could well be argued that we could have written a different type of manuscript, focusing entirely on what is possibly the simplest and most important finding, namely that our AF models suggest that in animal cells Wapl appears to form a quarternary complex with SA, Pds5, and Scc1 in a manner suggesting that a key function of Wapl’s conserved CTD is to sequester Scc1’s Nterminal domain after it has dissociated from Smc3. For right or for wrong, we decided that this story could not be presented on its own but also required 1) an explanation for how Scc1 is induced to dissociate from Smc3 in the first place and 2) how to explain that the quarternary complex predicted for animal cells was not initially predicted for fungi such as yeast. The yeast situation was an exception that clearly needed explaining if the theory was to have any generality and it turned out that delving into the intricate details of the genetics of releasing activity in yeast was eventually required and yielded valuable new insights. We also believe that our work on the recruitment of Eco/Esco acetyl transferases to cohesin and the finding that sororin binds to the Smc3/Scc1 interface also provided important insight into how releasing activity is regulated. We acknowledge that the paper is indeed long but do not think that it is badly written. It is above all a long and complex story that in our view reveals numerous novel insights into how cohesin’s association with chromosomes is regulated and have endeavoured to eliminate any excessive speculation. We feel it is not our fault that cohesin uses complex mechanisms.

Notwithstanding these considerations, we have in fact simplified a few sections and removed one or two others but acknowledge that we have not made substantial cuts.

It was pointed out that a key feature of our modelling, namely the predicted association of Wapl’s C-terminal domain with SA/Scc3’s CES is inconsistent with published biochemical data. The AF predictions for this interface are universally robust in all eukaryotic lineages and crucially fully consistent with published and unimpeachable genetic data. We note that any model that explains all findings is bound to be wrong for the very simple reason that some of these findings will prove to be incorrect. There is therefore an art in Science of judging which data must be explained and accommodated and which should be ignored. In this particular case, we chose to ignore the biochemistry. Time will tell whether our judgement proves correct.

Last but not least, it was suggested that we might provide some experimental support for our proposed SA/Scc3-Pds5-Scc1-WaplC quaternary complex. We are in fact working on this by introducing cysteine pairs (that can be crosslinked in cells) into the proposed interfaces but decided that such studies should be the topic of a subsequent publication. It would be impossible with the resources available to our labs to follow up all of the potential interactions and we therefore decided to exclude all such experiments.

We are grateful for the detailed comments provided by both reviewers, many of which were very helpful, and in many but not all cases have amended the manuscript accordingly.

With regard to the more specific comments:

Reviewer #1 (Recommendations For The Authors):

1) One concern is that observed interfaces/complexes arise because AF-multimer will aim to pack exposed, conserved and hydrophobic surfaces or regions that contain charge complementarity. The risk is that pairwise interaction screens can result in false positive & non-physiological interactions. It is therefore important to report the level of model confidence obtained for such AF calculations:

A) The authors should color the key models according to pLDDT scores obtained as reported by AF. This would allow the reader to judge the estimated accuracy of the backbone and side chain rotamers obtained. At least for the key models and interactions it would be important to know if the pLDDT score is >90 (Correct backbone and most rotamers) or >70 (only backbone is correct).

B) It would also be important to report the PAE plots to allow estimation of the expected position error for most of the important interactions. pLDDT coloring and PEA plots can be shown side-by-side as shown in other published data (e.g. https://pubmed.ncbi.nlm.nih.gov/35679397/ (Supplementary data)

C) The authors should include a Table showing the confidence of template modeling scores for the predicted protein interfaces as ipTM, ipTM+pTM as reported by AlphaFold-multimer. Ideally, they would also include DockQ scores but this may not be essential. Addition of such scores would help classification into Incorrect, Acceptable or of high quality. For example, line 1073 et seq the authors show a model of a SCC1SA and ESCO1 complex (Fig. 37). Are the modeling scores for these interfaces high? It does not help that the authors show cartoons without side chains? Can the authors provide a close-up view of the two interfaces? Are the amino acids are indeed packed in a manner expected for a protein interface? Can we exclude the possibility that the prediction is obtained merely because the sequence segments (e.g. in ESCO1 & ESCO2) are hydrophobic and conserved?

We do not agree that including this level of detail to the text/figures of the manuscript would be suitable. All the relevant data for those who may be sceptical about the models are readily available at https://doi.org/10.6084/m9.figshare.22567318.v2. In our view, the cartoon versions of the models are easier for a reader to navigate. Anyone interested in the molecular details can look at the models directly.

Importantly, no amount of statistical analysis can completely validate these models. What is required are further experiments, which will be the topic of further work from our and I dare from other laboratories.

D) When they predict an interaction between the SA2:SCC1 complex and Sororin's FGF motif, they find that only 1/5 models show an interaction and that the interaction is dissimilar to that seen of CTCF. Again, it would be helpful to know about modeling scores. Can they show a close-up view of the SORORIN FGF binding interface to see if a realistic binding mode is obtained? Can they indicate the relevant region on the PAE plot?

Given that AF greatly favours other interactions of Sororin’s FGF motif over its interaction with SA2-Scc1, we do not agree that dwelling on the latter would serve any purpose.

2) Line 996: AF predicts with high confidence an interaction between Eco1 & SMC3hd. What are the ipTM (& DockQ if available) scores. Would the interface score High, Medium or Acceptable?

As mentioned, see https://doi.org/10.6084/m9.figshare.22567318.v2.

3) Line 1034 et seq: Eco1/ESCO1/ESCO2 interaction with PDS5. Interface scores need to be shown to determine that the models shown are indeed likely to occur. If these interactions have low model confidence, Fig. 36 and discussion around potential relevance to PDS5-Eco1 orientation relative to the SMC3 head remains highly speculative and could be expunged.

See https://doi.org/10.6084/m9.figshare.22567318.v2. It should be clear that the predictions are very similar in fungi and animals. Crucially, we know that Pds5 is essential for acetylation in vivo, so the models appear plausible from a biological point of view.

4) Considering the relatively large interface between ECO1 and SMC3, would the author consider the possibility that in addition to acetylating SMC3's ATPase domain, ECO1 remains bound to cohesin-DNA complex, as proposed for ESCO1 by Rahman et al (10.1073/pnas.1505323112)?

This is certainly possible but we would not want to indulge in such speculation.

5) E.g. Line 875 but also throughout the text: As there is no labeling of the N- and C-termini in the Figures, is frequently unclear what the authors are referring to when they mention that AF models orient chains in a certain manner.

Good point. This has been amended. However, the positions of N- and C- is all available at https://doi.org/10.6084/m9.figshare.22567318.v2.

6) Fig19B: PAE plots: authors should indicate which chains correspond to A, B, C. Which segment corresponds to the TYxxxR[T/S]L motif? Can they highlight this section on the PAE plot?

Good point and amended in the revised manuscript.

Minor comments:

1) Line 440: the WAPL YSR motif is not shown in Fig. 14A

2) Line 691: Scc3 spelling error.

3) Line 931: Sentence ending '... SCC3 (SCC3N).' requires citation.

4) Line 1008: Figure reference seems wrong. It should read: Fig. 34A left and right. Fig. 34B does not contain SCC1.

Many thanks for spotting these. Hopefully, all corrected.

5) Fig. 41 can be removed as it shows the absence of the interaction of Sororin with SMC1:SCC1. Sufficient to mention in the text that Sororin does not appear to interact with SMC1:SCC1.

This is possible but we decided to leave this as is.

Reviewer #2 (Recommendations For The Authors):

Minor points

(1) Are there any predicted models in which one of the two dimer interfaces of the hinge is open when the coiled coils are folded back, as seen in the cryo-EM structure of human cohesin-NIPBL complex in the clamped state?

No AF runs ever predicted half opened hinges. It is possible that the introduction of mutations in one of the two interfaces might reveal a half-opened state and we ought to try this. However, it would not be appropriate for this manuscript, we believe.

(2) Structures of the SA-Scc1 CES bound to [Y/F]xF motifs from Sgo1 and CTCF have been reported, suggesting that a similar motif could interact with SA/Scc3. Surprisingly, AF did not predict an interaction between Scc3/SA and Wapl FGF motifs, which only bind to the Pds5 WEST region. On the other hand, AF predicted interactions of the Sororin FGF motif with both Pds5 WEST and SA CES. Can the authors comment on this Wapl FGF binding specificity? What will happen if a Wapl fragment lacking the CTD is used in the prediction?

This seems to be an academic point as the CTD is always present.

Author Response

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

Reviewer #1 (Recommendations For The Authors):

1) The authors need to validate that RAP1-HA still retains its essential function. As indicated above, if RAP1-HA still retains its essential functions, cells carrying one RAP1-HA allele and one deleted allele are expected to grow the same as WT cells. These cells should also have the WT VSG expression pattern, and RAP1-HA should still interact with TRF.

We demonstrated that C-terminally HA-tagged RAP1 co-localizes with telomeres by a combination of immunofluorescence and fluorescence in situ hybridization (Cestari and Stuart, 2015, PNAS), and co-immunoprecipitate telomeric and 70 bp repeats (Cestari et al. 2019 Mol Cell Biol). We also showed by immunoprecipitation and mass spectrometry that HA-tagged RAP1 interacts with nuclear and telomeric proteins, including PIP5Pase (Cestari et al. 2019). Others have also tagged T. brucei RAP1 with HA without disrupting its nuclear localization (Yang et al. 2009, Cell), all of which indicate that the HA-tag does not affect protein function. As for the suggested experiment, there is no guarantee that cells lacking one allele of RAP1 will behave as wildtype, i.e., normal growth and repression of VSGs genes. Also, less than 90% of T. brucei TRF was reported to interact with RAP1 (Yang et al. 2009, Cell), which might be indirect via their binding to telomeric repeats rather than direct protein-protein interactions.

2) The authors need to remove the His6 tag from the recombinant RAP1 fragments before the EMSA analysis. This is essential to avoid any artifacts generated by the His6-tagged proteins.

Our controls show that the His-tag is not interfering with RAP1-DNA binding. We show in Fig 3CG by EMSA and in Fig S5 by EMSA and microscale thermophoresis that His-tagged full-length rRAP1 does not bind to scrambled telomeric dsDNA sequences, which demonstrates that His-tagged rRAP1 does not bind unspecifically to DNA. Moreover, in Fig 3G and Fig S5, we show that His-tagged rRAP11-300 also does not bind to 70 bp or telomeric repeats. In contrast, the full-length His-tagged rRAP1, rRAP1301-560, or rRAP1561-855 bind to 70 bp or telomeric repeats (Fig 3C-G). Since all proteins were His-tagged, the His tag cannot be responsible for the DNA binding. We have worked with many different His-tagged proteins for nucleic acid binding and enzymatic assays without any interference from the tag (Cestari and Stuart, 2013; JBC; Cestari et al; 2013, Mol Cell Biol; Cestari and Stuart, 2015, PNAS; Cestari et al. 2016; Cell Chem Biol; Cestari et al. 2019 Mol Biol Cell).

3) More details need to be provided for ChIPseq and RNAseq analysis regarding the read numbers per sample, mapping quality, etc.

Table S3 includes information on sequencing throughput and read length. Mapping quality was included in the Methods section “Computational analysis of RNA-seq and ChIP-seq”, starting at line 499. In summary, we filtered reads to keep primary alignment (eliminate supplementary and secondary alignments). We also analyzed ChIP-seq with MAPQ ≥20 (99% probability of correct alignment) to distinguish RAP1 binding to specific ESs, including silent vs active ES (ChIP-seq). We included Fig S4 to show the effect of filtering alignments on the active vs silent ESs. We used MAPQ ≥30 to analyze RNA-seq mapping to VSG genes, including those in subtelomeric regions. Our scripts are available at https://github.com/cestari-lab/lab_scripts. We also included in the Methods, lines 522-524: “Scripts used for ChIP-seq, RNA-seq, and VSG-seq analysis are available at https://github.com/cestari-lab/lab_scripts. A specific pipeline was developed for clonal VSG-seq analysis, available at https://github.com/cestarilab/VSG-Bar-seq.”

4) The authors should revise the Discussion section to clearly state the authors' speculations and their working models (the latter of which need solid supporting evidence). Specifically, statements in lines 218 - 219 and lines 224-226 need to be revised.

The statement “likely due to RAP1 conformational changes” in line 228 discusses how binding of PI(3,4,5)3 could affect RAP1 Myb and MybL domains binding to DNA. We did not make a strong statement but discussed a possibility. We believe that it is beneficial to the reader to have the data discussed, and we do not feel this point is overly speculative. For lines 224-226 (now 234-235), the statement refers to the finding of RAP1 binding to centromeric regions by ChIP-seq, which is a new finding but not the focus of this work. To make it clear that it does not refer to telomeric ESs, we edited: “The finding of RAP1 binding to subtelomeric regions other than ESs, including centromeres, requires further validation.” Since RAP1 binding to centromeres is not the focus of the work, future studies are necessary to follow up, and we believe it is appropriate in the Discussion to be upfront and highlight this point to the readers.

Our model is based on the data presented here but also on scientific literature. We have reviewed the Discussion to prevent broad speculations. When discussing a model, we stated (line 245): “The scenario suggests a model in which …”, to state that this is a working model. Similarly, in Results (line 201) we included: “Our data suggest a model in which…”.

5) The authors should revise the title to reflect a more reasonable conclusion of the study.

We agree that the title should be changed to imply a direct role of PI(3,4,5)P3 regulation of RAP1, which is not captured in the original title. This will provide more specific information to the readers, especially those broadly interested in telomeric gene regulation and RAP1. The new title is: PI(3,4,5)P3 allosteric regulation of repressor activator protein 1 controls antigenic variation in trypanosomes

6) The authors are recommended to provide an estimation of the expression level of the V5-tagged PIP5pase from the tubulin array in reference to the endogenous protein level.

The relative mRNA levels of the exclusive expression of PIP5Pase mutant compared to the wildtype is available in the Data S1, RNA-seq. The Mut PIP5Pase allele’s relative expression level is 0.85fold to the WT allele (both from tubulin loci). We also showed by Western blot the WT and Mut PIP5Pase protein expression (Cestari et al. 2019, Mol Cell Biol). Concerning PIP5Pase endogenous alleles, we compared normalized RNA-seq counts per million from the conditional null PIP5Pase cells exclusively expressing WT or the Mut PIP5Pase alleles (Data S1, this work) to our previous RNA-seq of single-marker 427 strain (Cestari et al. 2019, Mol Cell Biol). We used the single-maker 427 because the conditional null cells were generated in this strain background. The PIP5Pase WT and Mut mRNAs expressed from tubulin loci are 1.6 and 1.3-fold the endogenous PIP5Pase levels in single-marker 427, respectively. We included a statement in the Methods, lines 275-278: “The WT or Mut PIP5Pase mRNAs exclusively expressed from tubulin loci are 1.6 and 1.3-fold the WT PIP5Pase mRNA levels expressed from endogenous alleles in the single marker 427 strain. The fold-changes were calculated from RNA-seq counts per million from this work (WT and Mut PIP5Pase, Data S1) and our previous RNA-seq from single marker 427 strain (24).”

7) The authors are recommended to provide more detailed EMSA conditions such as protein and substrate concentrations. Better quality EMSA gels are preferred.

All concentrations were already provided in the Methods section. See line 356, in topic Electrophoretic mobility shift assays: “100 nM of annealed DNA were mixed with 1 μg of recombinant protein…”. For microscale thermophoresis, also see lines 375-376 in topic Microscale thermophoresis binding kinetics: “1 μM rRAP1 was diluted in 16 two-fold serial dilutions in 250 mM HEPES pH 7.4, 25 mM MgCl2, 500 mM NaCl, and 0.25% (v/v) N P-40 and incubated with 20 nM telomeric or 70 bp repeats…”. Note that two different biochemical approaches, EMSA and microscale thermophoresis, were used to assess rRAP1-His binding to DNA. Both show agreeable results (Fig 3 and 5, and Fig S5. Microscale thermophoresis shows the binding kinetics, data available in Table 1). The EMSA images clearly show the binding of RAP1 to 70 bp or telomeric repeats but not to scramble telomeric repeat DNA.

Reviewer #2 (Recommendations For The Authors):

Major comments:

Figures

All figures should have their axes properly labeled and units should be indicated. For many of the ChIPseq datasets it is not clear whether the authors show a fold enrichment or RPM and whether they used all reads or only uniquely mapping reads. Especially the latter is a very important piece of information when analyzing expression sites and should always be reported. The authors write, that all RNA-seq and ChIP-seq experiments were performed in triplicate. What is shown in the figures, one of the replicates? Or the average?

ChIP-seq is shown as fold enrichment; we clarified this in the figures by including in the y-axis RAP1-HA ChIP/Input (log 2). We included in figure legends, see line 710: “Data show fold-change comparing ChIP vs Input.”. For quantitative graphs (Fig 2B, D, and E, and Fig 5F and G), data are shown as the mean of biological replicates. Graphs generated in the integrated genome viewer (IGV, qualitative graphs) is a representative data (Fig 2A, C, and F, and Fig 5D-E). All statistical analyses were calculated from the three biological replicates. Uniquely mapped reads were used. We also included ChIP-seq analysis with MAPQ ≥10 and 20 (90% and 99% probability of correct alignment, respectively) to distinguish RAP1 binding to ESs. Fig S4 shows the various mapping stringency and demonstrates the enrichment of RAP1-HA to silent vs active ES.

Figure 1 is very important for the main argument of the manuscript, but very difficult (impossible for me) to fully understand. It would be great if the author could make an effort to clarify the figure and improve the labels. Panel Fig 1E. Here it is impossible to read the names of the genes that are activated and therefore it is impossible to verify the statements made about the activation of VSGs and the switching.

We have edited Fig 1E to include the most abundant VSGs, which decreased the amount of information in the graph and increased the label font. We also re-labeled each VSG with chromosome or ES name and common VSG name when known (e.g., VSG2). We included Table S1 in the supplementary information with the data used to generate Fig 1E. In Table S1, the reader will be able to check the VSG gene IDs and evaluate the data in detail. We included in the legend, line 700: “See Table S1 for data and gene IDs of VSGs.”

Figure 1F: This panel is important and should be shown in more detail as it distinguishes VSG switching from a general VSG de-repression phenotype. VSG-seq is performed in a clonal manner here after PIP5Pase KD and re-expression. To show that proper switching has occurred place in the different clones, instead of a persistent VSG de-repression, the expression level of more VSGs should be shown (e.g. as in panel E) to show that there is really only one VSG detected per clone. For example, it is not clear what the authors 'called' the dominant VSG gene.

We showed in supplementary information Fig S1 B-C examples of reads mapping to the VSGs. Now we included a graph (Fig S1 D) that quantifies reads mapped to the VSG selected as expressed compared to other VSG genes considered not expressed). The data show an average of several clones analyzed. Other VSGs (not selected) are at the noise level (about 4 normalized counts) compared to >250 normalized counts to the selected as expressed VSGs.

As mentioned in the public comments, I don't see how the data from Fig 1E and 1F fit together. Based on Fig 1E VSG2 is the dominant VSG, based on Fig 1F VSG2 is almost never the dominant VSG, but the VSG from BES 12.

In Fig 1E, the VSG2 predominates in cells expressing WT PIP5Pase, however, in cells expressing Mut PIP5Pase, this is not the case anymore. Many other VSGs are detected, and other VSG mRNAs are more abundant than VSG2 (see color intensity in the heat map). The Mut cells may also have remaining VSG2 mRNAs (from before switching) rather than continuous VSG2 expression. This is the reason we performed the clonal analysis shown in Fig 1F, to be certain about the switching. While Fig 1F shows potential switchers in the population, Fig 1E confirms VSG switching in clones.

Many potential switchers were detected in the VSG-seq (Fig 1F, the whole cell population is over 107 parasites), but not all potential switchers were detected in the clonal analysis because we analyzed 212 clones total, a fraction of the over 107 cells analyzed by VSG-seq (Fig 1E). Also, it is possible that not all potential switchers are viable. A preference for switching to specific ESs has been observed in T. brucei (Morrison et al. 2005, Int J Parasitol; Cestari and Stuart, 2015, PNAS), which may explain several clones switching to BES12.

Note that in Fig 1F, tet + cells did not switch VSGs at all; all 118 clones expressed VSG2. We relabeled Fig 1F for clarity and included the VSG names. We added gene IDs in the Figure legends, see line 702 “ BES1_VSG2 (Tb427_000016000), BES12_VSG (Tb427_000008000)…”

Statements in Introduction / Discussion

The statement in lines 82/83 is very strong and gives the impression that the PIP5Pase-Rap1 circuit has been proven to regulate antigenic variation in the host. However, I don't think this is the case. The paper shows that the pathway can indeed turn expression sites on and off, but there is no evidence (yet) that this is what happens in the host and regulates antigenic variation during infection. The same goes for lines 214/215 in the discussion.

We agree with the reviewer, and we edited these statements. The statement lines 82-83: “The data provide a molecular mechanism…” to “The data indicates a molecular mechanism…” For lines 224225: “and provides a mechanism to control…” to “and indicates a mechanism to control…”. We also included in lines 261-262: “It is unknown if a signaling system regulates antigenic variation in vivo.” Also edited lines 262-263: “…the data indicate that trypanosomes may have evolved a sophisticated mechanism to regulate antigenic variation...”.

New vs old data

In general, for Figures 1 - 4, it was a bit difficult to understand which panels showed new findings, and which panels confirmed previous findings (see below for specific examples). In the text and in the figure design, the new results should be clearly highlighted. Authors: All data presented is new, detailed below.

Figure 1: A similar RNA-seq after PIP5Pase deletion was performed in citation 24. Perhaps the focus of this figure should be more on the (clone-specific) VSG-seq experiment after PIP5Pase re-introduction.

This is the first time we show RNA-seq of T. brucei expressing catalytic inactive PIP5Pase, which establishes that the regulation of VSG expression and switching, and repression of subtelomeric regions, is dependent on PIP5Pase enzyme catalysis, i.e., PI(3,4,5)P3 dephosphorylation. Hence, the relevance and difference of the RNA-seq here vs the previous RNA-seq of PIP5Pase knockdown.

Figure 2: A similar ChIP-seq of RAP1 was performed in citation 24, with and without PIP5Pase deletion. Could new findings be highlighted more clearly?

Our and others’ previous work showed ChIP-qPCR, which analyses specific loci. Here we performed ChIP-seq, which shows genome-wide binding sites of RAP1, and new findings are shown here, including binding sites in the BES, MESs, and other genome loci such as centromeres. We also identified DNA sequence bias defining RAP1 binding sites (Fig 2A). We also show by ChIP-seq how RAP1-binding to these loci changes upon expression of catalytic inactive PIP5Pase. To improve clarity in the manuscript, we edited lines 129-130: “We showed that RAP1 binds telomeric or 70 bp repeats (24), but it is unknown if it binds to other ES sequences or genomic loci.”

Figure 4: Binding of Rap1 to PI(3,4,5)P3, but not to other similar molecules, was previously shown in citation 24. Could new findings be highlighted more clearly?

We published in reference 24 (Cestari et al. Mol Cell Biol) that RAP1-HA can bind agarose beadsconjugated synthetic PI(3,4,5)P3. Here, we were able to measure T. brucei endogenous PI(3,4,5)P3 associated with RAP1-HA (Fig 4F). Moreover, we showed that the endogenous RAP1-HA and PI(3,4,5)P3 binding is about 100-fold higher when PIP5Pase is catalytic inactive than WT PIP5Pase. The data establish that in vivo endogenous PI(3,4,5)P3 binds to RAP1-HA and how the binding changes in cells expressing mutant PIP5Pase; this data is new and relevant to our conclusions. To clarify, we edited the manuscript in lines 180-182: “To determine if RAP1 binds to PI(3,4,5)P3 in vivo, we in-situ HA-tagged RAP1 in cells that express the WT or Mut PIP5Pase and analyzed endogenous PI(3,4,5)P3 levels associated with immunoprecipitated RAP1-HA”.

Sequencing.<br /> I really appreciate the amount of detail the authors provide in the methods section. The authors do an excellent job of describing how different experiments were performed. However, it would be important that the authors also provide the basic statistics on the sequencing data. How many sequencing reads were generated per run (each replicate of the ChIP-seq and RNA-seq assays)? How long were the reads? How many reads could be aligned?

The sequencing metrics for RNA-seq and ChIP-seq for all biological replicates were included in Table S3 (supplementary information). The details of the analysis and sequencing quality were described in the Methods section “Computational analysis of RNA-seq and ChIP-seq”. To be clearer about the analysis, we also included in Methods, lines 522-524: “Scripts used for ChIP-seq, RNA-seq, and VSG-seq analysis are available at https://github.com/cestari-lab/lab_scripts. A specific pipeline was developed for clonal VSG-seq analysis, available at https://github.com/cestari-lab/VSG-Bar-seq.”.

Minor comments:

Figure 1B: I would recommend highlighting the non-ES VSGs and housekeeping genes with two more colors in the volcano plot, to show that it is mostly the antigen repertoire that is deregulated, and not the Pol ll transcribed housekeeping genes. This is not entirely clear from the panel as it is right now.

The suggestion was incorporated in Fig 1B. We color-coded the figure to include BES VSGs, MES VSGs, ESAGs, subtelomeric genes, core genes (typically Pol II and Pol III transcribed genes), and Unitig genes, those genes not assembled in the 427-2018 reference genome.

Were the reads in Figure 2a filtered in the same way as those in Figure 2C? To support the statements, only unique reads should be used.

Yes, we also added Fig S4 to make more clear the comparison between read mapping to silent vs active ES.

It would be good if the authors could add a supplementary figure showing the RAP1 ChIP-seq (WT and cells lacking a functional PIP5Pase) for all silent expression sites.

We had RAP1 ChIP-seq from cells expressing WT PIP5Pase already. We have it modified to include data from the Mutant PIP5Pase. See Fig S3 and S5.

In Figure 5D, after depletion of PIP5Pase, RAP1 binding appears to decrease across ESAGs, but ESAG expression appears to increase. How can this be explained with the model of RAP1 repressing transcription?

We included in the Results, lines 208-212: “The increased level of VSG and ESAG mRNAs detected in cells expressing Mut PIP5Pase (Fig 5D) may reflect increased Pol I transcription. It is possible that the low levels of RAP1-HA at the 50 bp repeats affect Pol I accessibility to the BES promoter; alternatively, RAP1 association to telomeric or 70 bp repeats may affect chromatin compaction or folding impairing VSG and ESAG genes transcription.”.

Reviewer #3 (Recommendations For The Authors):

Line 114 - typo? Procyclic instead of procyclics:

Fixed, thanks.

Line 233 - the phrasing here is confusing, may want to replace "whose" with "which" (if I am interpreting correctly):

Thanks, no changes were needed. I have had the sentence reviewed by a Ph.D.-level scientific writer.

Methods - there is no description of VSG-seq analysis in the methods. Is it done the same way as the RNA-seq analysis? Is the code for analysis/generating figures available online?

The procedure is similar. We included an explanation in Methods, lines 503-504: “RNA-seq and VSG-seq (including clonal VSG-seq) mapped reads were quantified…”. Also, in lines 522-54: “Scripts used for ChIP-seq, RNA-seq, and VSG-seq analysis are available at https://github.com/cestari-lab/lab_scripts. A specific pipeline was developed for clonal VSG-seq analysis, available at https://github.com/cestarilab/VSG-Bar-seq.”.

Fig 1H - Is this from RNA-seq or VSG-seq analysis of procyclics?

The procyclic forms VSG expression analysis was done by real-time PCR. To clarify it, we included it in the legend “Expression analysis of ES VSG genes after knockdown of PIP5Pase in procyclic forms by real-time PCR”. We also amended the Methods, under the topic RNA-seq and real-time PCR, line 402-407: “For procyclic forms, total RNAs were extracted from 5.0x108 T. brucei CN PIP5Pase growing in Tet + (0.5 µg/mL, no knockdown) or Tet – (knockdown) at 5h, 11h, 24h, 48h, and 72h using TRIzol (Thermo Fisher Scientific) according to manufacturer's instructions. The isolated mRNA samples were used to synthesize cDNA using ProtoScript II Reverse Transcriptase (New England Biolabs) according to the manufacturer's instructions. Real-time PCRs were performed using VSG primers as previously described (23).”

Fig 2 A - Where it says "downstream VSG genes" I assume "downstream of VSG genes" is meant? the regions described in this figure might be more clearly laid out in the text or the legend

Fixed, thanks. We included in the text in Results, line 140: “… and Ts and G/Ts rich sequences downstream of VSG genes”.

Fig 2E - what does "Flanking VSGs" mean in this context?

We added to line 705, figure legends: “Flanking VSGs, DNA sequences upstream or downstream of VSG genes in MESs. “

Fig 2H - Why is the PIP5Pase Mutant excluded from the Chr_1 core visualization?

We did not notice it. We included it now; thanks.

This shows how separation from families is common because many don't see each other again which is horrible. He was talking about his personal experience about being sold into different places and suffering emotionally. It's sad and I wish to read and find out about the well-being of his sister and makes me question that did he ever got to see her again like he did last time.

To me, this is part is kind of dark. He was on the slave ship. He saw the men who are being tortured and chained up on the ship. The men were so cruel to them. Thats sad that he had to witness about that. It's heartbreaking that at first, he got kidnapped, his sister got kidnapped, he got departed from his sister, sold into slavery, sold into many different locations, then have to witness the men who are being tortured on the ship. This is very dark and traumatizing. And also, he still feeling hopeless of the desire of returning back home and also reunite with his sister again. It makes me question that would he ever reunite with his sister again.

From my readings in EDSCI so far, this is the first time I have seen someone address the heaviness that may come with being a transformative learner. Many of our biases and student's biases as well as oppressive ideologies might be the only way they have learned. The word trauma exemplifies the impact of unlearning things that perhaps have been the building blocks of your identity. I think about my 7th graders, primarily Latinx, primarily Christian, primarily male, and primarily from low income households surrounding our school;they might experience this trauma when presented with ideas that deviate from what they hold to be truth. However, their truth has been their reality, and rather than negate them, they have to be part of the conversation.

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

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Reply to the reviewers

We thank the reviewers for their thoughtful comments. Here we provide a point-by-point response to their reviews. All additional experiments that are present in the revised manuscript, or that we plan to include in the final manuscript, are numbered.

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

The concept introduced by this paper is exciting and novel. However, the current paucity of presented data can lead to incorrect interpretations of the findings and speculations that might not hold true after a more rigorous assessment of the observed phenomenon.

The premise of this study builds upon an interaction between the PAXT complex and nuclear YTH domain containing proteins. However, figures 1B and C should be improved. The interacting band for the ZFC3H1 presented in panel B does not seem to match the size of the construct used in panel C. Is the Flag version of ZFC3H1 expressing a smaller isoform for this protein? __

The reviewer is correct in that endogenous ZFC3H1 (which migrates at 250kD with a minor band at 150kD, see Figure 1B in the initial manuscript) appears to differ from the FLAG-tagged construct as expressed from a plasmid transfected in HEK293 cells (which migrates as two bands at 180kD and 200kD, see Figure 1C in the initial manuscript). For the endogenous protein, the predicted molecular weight is 226kD and the 250kD band disappears when cells are transduced with lentivirus containing shRNAs against ZFC3H1 (see Figure 4A in the initial manuscript), indicating that it is the correct protein. Both the 250kD endogenous protein (*) and the 200kD overexpressed protein (**) in transfected HEK293 and U2OS cells are detected in immunoblots using anti-ZFC3H1 antibodies (see Figure 1 in this document) indicating that the over-expressed protein is indeed ZFC3H1.

[ Figure 1]

_Figure 1. Molecular Weight Size Comparison of Endogenous ZFC3H1 and FLAG-ZFC3H1 (1-1233). _Lysates from HEK293 and U2OS that were either untransfected or transfected with FLAG-ZFC3H1 (1-1233) plasmid. We labelled the bands corresponding to the endogenous ZFC3H1 “*” and FLAG-ZFC3H1 (1-1233) “**”.

We have sequenced the plasmid, and discovered that it contains an additional sequence inserted within the middle of the ZFC3H1 cDNA with a premature stop codon. As such, the version of the protein that is expressed from the plasmid only contains amino acids 1-1233 of the endogenous protein and is missing amino acids 1234-1989. The deleted region only contains TPR repeats, and is not known to interact with any of the well characterized interactors of ZFC3H1 (Wang, Nuc Acid Res 2021, Figure 3). We have renamed this construct FLAG-ZFC3H1 (1-1233). Given these new considerations, our results are consistent with the idea that the N-terminal portion of ZFC3H1 interacts with U1-70K, YTHDC1 and YTHDC2. We will change the text to reflect this.

We are currently in the process of deleting the small insertion to obtain a plasmid that encodes a full length version of human ZFC3H1. For the final manuscript:

Experiment #1) We will repeat the co-immunoprecipitation experiment with the full length FLAG-ZFC3H1 to determine whether it interacts with YTHDC1 and YTHDC2. This will take a few weeks.

__Also, the YTHDC1-2 interaction in panel C is not as convincing considering the negative controls lane show some degree of binding. __

Although the reviewer is correct that there is substantial background binding in the YTHDC1 immunoblot, we disagree with their characterization of the results with the YTHDC2 immunoblot (see Figure 1B-C in the initial manuscript). In the new manuscript we have included:

Experiment #2) A new co-immunoprecipitate of the FLAG-tagged ZFC3H1 (1-1233) from HEK293 cells under more stringent conditions where the background level of YTHDC1 binding to beads is negligible. We have already completed this experiment (see Figure 1D in the revised manuscript).

__Additionally, can the authors test if their RNaseA treatment worked? __

In the new manuscript we have included:

Experiment #3) A new co-immunoprecipitate of FLAG-YTHDC1 immunoblotted for eIF4AIII from HEK293 cell lysates. We find that without RNAse, there is some eIF4AIII in the precipitates but that the levels diminish substantially after RNAse A/T1 treatment. We have already completed this experiment (see Figure 1B in the preliminary revised manuscript).

__Why do you need 18 hours to observe the nuclear export of your modifiable construct when inhibiting METTL3 in figure 3? Is it possible that your observation is secondary to phenotypes these cells develop as a result of blocking METTL3? __

We treated cells for this period of time so that during the expression of the reporter, all of the newly synthesized mRNA is expressed in the absence of m6A methyl transferase activity. For shorter treatment times, it is unclear whether the bulk of the reporter mRNA, which would be synthesized before the treatment, would lose any pre-existing m6A marks, making a negative result hard to interpret. Previously we found that although 50% of intronic polyadenylated (IPA) transcripts from our reporters are rapidly degraded, about 50% are stable and are nuclear retained over extended periods of time (see Lee at al., PLOS ONE 2015; https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0122743 Figure 3B-G). We believe that the bulk of the reporter mRNA that we are visualizing is stable and accumulates in the nucleus. Given that METTL3-depletion inhibits nuclear retention and that versions of the IPA reporter that lack m6A modification motifs are exported, we think that the most likely interpretation of the 18 hour STM2457 treatment experiments is that the lack of methyltransferase activity had a direct effect, rather than an indirect effect, on nuclear retention. We would be open to performing more experiments if the editors insist, however we ordered STM2457 four weeks ago and it has yet to arrive from Sigma-Millipore. Performing this experiment may substantially delay our ability to resubmit the manuscript in a timely manner.

__Is ALKBH5 nuclear and/or cytoplasmic in the cell system used? __

According to The Human Protein Atlas, ALKBH5 is predominantly nuclear in U2OS cells, with some present in the cytoplasm (https://www.proteinatlas.org/ENSG00000091542-ALKBH5/subcellular#human).

In the revised manuscript we have included:

Experiment #4) Data from subcellular fractionation demonstrating that ALKBH5 is present in both the nucleus and cytoplasm that we have already performed (see Figure 4J in the preliminary revised manuscript).

__Reviewer #1 (Significance (Required)):

The study is highly significant __

------

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

Summary: In the manuscript by Lee et al. entitled "N-6-methyladenosine (m6A) Promotes the Nuclear Retention of mRNAs with Intact 5'Splice Site Motifs", the authors provide evidence that m6A modifications within specific regions of transcripts can confer nuclear retention. These results are important because they add to our understanding of how m6A modifications can contribute to post-transcriptional regulation. Although the authors do not quite come out and say this, data seem to be accumulating to suggest that the location of the m6A modifications within a given transcript can dictate the functional consequences of those modifications.__

We thank the reviewer for pointing this out. We have included a few sentences in the new preliminary revised manuscript pointing out that the location of the m6A modification in IPA transcripts, with respect to intact 5’SS and poly(A) signals, may play a role in promoting nuclear retention.

__The current work builds on previous findings from these authors identifying factors critical for retention of intronic polyadenylated (IPA) transcripts. The present study identified m6A modification as one of the signals for the retention of such transcripts. The authors use reporters for their analysis and also examine validated endogenous IPA transcripts. The data presented supports the conclusions albeit they show a surprising finding for one of the m6A erasers, ALKBH5. However, there is some controversy over the mechanism by which ALKBH5 functions and whether the m6A mark is truly reversible, so these results may continue to add to this point of view.

Major Comments: One experiment that might add to the argument would be overexpression of Mettl3 as compared to catalytically inactive Mettl3. The prediction would be that the reporter transcript with intact DRACH sequences would be even more retained in the nucleus in a manner that depends on Mettl3 catalytic activity. For some of the data presented, the reporter is already wholly nuclear so no difference could be detected, but in the U2OS cells shown in Figure 2B, it appears that an increase in nuclear localization might be evident. Such an experiment would add an orthogonal approach to demonstrate that the methylation by Mettl3 is required for retention. If such an experiment would work with the endogenous IPA transcripts shown in Figure 4, but these transcripts may already be too nuclear to detect any increase in nuclear retention.

__

We have performed two experiments that try to address this but they gave negative results:

Experiment #5) We have over-expressed wildtype and a methyl transferase mutant FLAG-METTL3 and assessed the nuclear export/retention of ftz-Δi-5’SS mRNA. There was no effect (see Figure 2 in this document).

[Figure 2]

__Figure 2. Over-expression of METTL3 does not increase the nuclear retention of ftz-Δi-5’SS. __U2OS cells were co-transfected with ftz-Δi-5’SS reporter and either FLAG-METTL3 or FLAG-METTL3-D395A, which lacks methyl-transferase activity (Wang, Mol Cell 2016). Cells were fixed, stained for ftz mRNA by fluorescent in situ hybridization and METTL3 using anti-FLAG antibodies. The nuclear and cytoplasmic distribution of ftz mRNA was quantified as described in the manuscript. Note that this is the average of one independent experiment (each bar consisting of the average of at least 50 cells). We plan to repeat this two more times, but we anticipate that these will show the same result.

We could include this negative data as a supplemental figure. We believe that there are two possible reasons for this experimental result. First, as the reviewer points out, the reporter transcripts are already too nuclear to detect any significant change. Second, METTL3 is part of a larger complex that includes several proteins including METTL14, WTAP and potentially other proteins (for example see Covelo-Molares, Nuc Acid Res 2021). We may need to co-express all of these proteins to see an effect.

Experiment #6) We have also expressed versions of ftz-Δi and ftz-Δi-5’SS mRNA with optimized m6A modification (i.e. DRACH) motifs (AGACT) to enhance methylation (“e-m6A-ftz”). We only observed a slight increase in nuclear retention but it is not significant (see Figure 2A,C in the revised manuscript).

Again, this result could be explained by the fact that the reporter is too nuclear to detect any significant increase in retention. We had originally performed this in parallel with the no-m6A-ftz-Δi-5’SS reporters but did not report this negative data in the original manuscript.

__Some rather minor changes to the presentation of the data could enhance the impact of this study.

Specific Comments:

The primary question in this manuscript is comparing reporters with m6A site (intact DRACH sequences) to those without. For this reason, organizing the data to the +/- DRACH sites are adjacent to one another might make the most sense. This point is evident in Figure 1C where perhaps simply changing the order of the bars presented to put the ones directly compared adjacent would be preferable. Then the p-value would compare sets of data directly adjacent to one another. __

We thank the reviewer for this suggestion and we have made these changes to the figures in the preliminary revised manuscript.

__While the authors show representative fields/cells for most assays, they do an excellent job of providing quantitation as well. One exception is Figure 3D, which shows a single cell image for the most key panel (the 5'SS-containing reporter upon Mettl3 depletion). If there is not a field with more cells, the authors could create a montage. __

In the revised manuscript, we have replaced this image with one containing multiple cells expressing the reporter.

__Minor Comments:

Figure presentation:

The text in a number of the figures is VERY small (Figures 1B,1C, and 4A) for example. __

We have fixed this in the new manuscript.

__Figure 3A includes the label "shRNA:" at the top, but these cells are treated with Mettl3 inhibitor and there does not appear to be any shRNA employed, so this seems like a labeling error. __

We have fixed this in the new manuscript.

__In Figure 3C, the immunoblot of Mettl3, there are three bands that all disappear completely upon knockdown of Mettl3- are these all Mettl3? This should at least be mentioned in the legend and perhaps indicated in the figure. The authors do mention in the text employing shRNAs to target multiple Mettl3 isoforms, so likely this is the case. __

We have clarified these issues in the new manuscript.

__Minor points (some really minor to just polish the presentation for clarity):

The word "since" should only be used if there is a time element- otherwise the word "as" is preferable.

For example on p. 4, the sentence: "Since inhibition of mRNA export typically enhances the nuclear retention of RNAs with intact 5'SS motifs (Lee et al. 2020),.." would more precisely read "As inhibition of mRNA export typically enhances the nuclear retention of RNAs with intact 5'SS motifs (Lee et al. 2020),..". __

We thank the reviewer for pointing this out. We have fixed this issue in the revised manuscript.

__Reviewer #2 (Significance (Required)):

Summary: In the manuscript by Lee et al. entitled "N-6-methyladenosine (m6A) Promotes the Nuclear Retention of mRNAs with Intact 5'Splice Site Motifs", the authors provide evidence that m6A modifications within specific regions of transcripts can confer nuclear retention. These results are important because they add to our understanding of how m6A modifications can contribute to post-transcriptional regulation. Although the authors do not quite come out and say this, data seem to be accumulating to suggest that the location of the m6A modifications within a given transcript can dictate the functional consequences of those modifications.

This study would be of significant interest to those that study gene expression in any context as well as cell biologists as the data add to our understanding of export of mRNA from the nucleus. This work also adds to our understanding of the biological consequences of m6A modification, which is an area of significant interest. In my opinion, the authors could make a broader conclusion that we do, which is that the location of the modification significantly dictates function- an extension of previous findings mostly focused on processed mRNA transcripts. __

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

Quality control of mRNA is vital for all types of cells. In eukaryotic cells, nuclear export of misprocessed mRNAs containing the 5' splice site is prevented. In this manuscript, Lee and colleagues demonstrate that the nuclear retention of intronic polyadenylated transcripts is dependent on m6A modification. Based on the results shown in yeast, they perform immunoprecipitation experiments and demonstrate the interaction between ZFC3H1, a component of the PAXT complex, and YTHDC1 and YTHDC 2, nuclear YTH RNA-binding proteins that recognize m6A-modified transcripts. The study also shows the interaction of U1-70K with YTHDC1 and with ZFC3H1. Depletion of YTHDC1/2 prevents the nuclear retention of IPA transcripts. Additionally, CLIP-seq analysis is performed, demonstrating that m6A modification is enriched around the 5' splice site motif and the 3' polyadenylation site in IPAs. From these observations, they conclude that m6A modification contributes to the quality control of mRNA by promoting nuclear retention of misprocessed transcripts.

Major Points 1. The interaction between ZFC3H1 and YTHDC1 is clearly shown by immunoprecipitation of FLAG-tagged YTHDC1 in Figure 1B. However, the co-purification of YTHDC1 with FLAG-tagged ZFC3H1 in Figure 1C is rather ambiguous. Additionally, the immunoprecipitated samples do not appear to show signals corresponding to FLAG-tagged ZFC3H1, making it unclear if the immunoprecipitation is working. It is essential to provide a better quality result to clarify these observations. __

Please see our responses to reviewer #1. We have repeated the co-immunoprecipitation of FLAG-ZFC3H1 (1-1233) with YTHDC1 under more stringent conditions and have reduced the background binding (see Figure 1B and D in the new manuscript). We have also determined why the FLAG-ZFC3H1 is smaller than expected as the construct contains a premature stop codon. As explained above, we are in the midst of generating a full-length FLAG-ZFC3H1 and we plan to repeat the co-immunoprecipitation with this new construct.

2. While the authors demonstrate that the m6A modification is dispensable for the targeting of IPA reporter transcripts to the nuclear speckles, it would be valuable to investigate whether m6A is required for their exit from the nuclear speckles. Do reporter transcripts with m6A motifs remain in the nuclear speckles at later time points?

We have now analyzed the colocalization of nuclear speckles (SC35) with ftz-Δi-5’SS, which contains both a 5’SS and DRACH motifs, and no-m6A-ftz-Δi-5’SS, which contains a 5’SS but lacks DRACH motifs, at steady state – i.e. after 18-24 hours of transfection (as opposed to at early time points as shown in Figure 2D-E of the initial manuscript). Unexpectedly, we see that both mRNAs continue to colocalize with nuclear speckles, although the no-m6A-ftz-Δi-5’SS mRNA is well exported from the nucleus and its signal in nuclear speckles is faint (see Figure 2F-H in the new manuscript).

Previously, we observed that ftz-Δi-5’SS required the 5’SS motif to remain in nuclear speckles at these later time points (Lee PLOS ONE 2015 and Lee RNA 2022). Upon closer inspection, ftz-Δi-5’SS mRNA also accumulates in additional nuclear foci that are not SC35-positive. Our new results may indicate that m6A marks promote the transfer of mRNAs from nuclear speckles to other foci, but more data is required to make a firm statement. Given this, we plan to conduct further experiments which may take a month to complete:

Experiment #7) We are now assessing whether these additional ftz-Δi-5’SS foci correspond to either YTHDC-positive foci which were previously shown to partially overlap nuclear speckles and sequester m6A-rich mRNAs (Cheng Cancer Cell 2022), or “pA+ RNA foci” which accumulate MTR4/ZFC3H1-targetted RNAs when the nuclear exosome is inhibited (Silla Cell Reports 2018). These foci are enriched in ZFC3H1. We plan on co-staining ftz-Δi, ftz-Δi-5’SS, no-m6A-ftz-Δi and no-m6A-ftz-Δi-5’SS with SC35, YTHDC1 and ZFC3H1 to determine whether m6A may help to transfer mRNAs from nuclear speckles to YTHDC1 or ZFC3H1-enriched foci.

__3. Figures 5B and 5C suggest that ZFC3H1 is required for the degradation of IPA transcripts. However, the range of the vertical axis is inappropriate and it is difficult to assess the extent of the increase in expression levels. Please adjust the vertical axis range for improved clarity. __

We thank the reviewer for the feedback we have added additional graphs with an expanded vertical axis to demonstrate that ZFC3H1 is required for the degradation IPA transcripts.

Minor Points 1. page 4, line 2 "RNAse" should be corrected to "RNase".

We thank the reviewer for catching this error. We have fixed this.

__ 2. page 7, line 5: Is the statement "prevents the nuclear export and decay of non-functional and misprocessed RNAs" correct? m6A modification promotes the decay of such RNAs. __

We thank the reviewer for pointing this out. We have altered the text to clarify that m6A promotes decay.

__3. Figure 2E: ftz-∆i should be ftz-∆i-5'SS. __

We thank the reviewer for catching this error. We have fixed this.

__4. Figure 5A: It would be helpful to indicate the number of IPA transcripts analyzed. __

We have included this information.

__Reviewer #3 (Significance (Required)):

Overall, the work is sound and generally well-controlled. This study advances our understanding of the quality control of misprocessed transcripts in higher eukaryotes. This reviewer suggests a few points for clarification or improvement. __

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

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Reply to the reviewers

1. General Statements

We would like to thank the editorial staff and the reviewers for their handling of our manuscript. We were very pleased with the timely communications from Review Commons, and we are grateful to have been assigned this insightful and constructive group of reviewers.

The reviewers were well-suited to evaluate our work based on their stated areas of expertise (cancer biology, image analysis, machine learning, cell-based screening, etc.). As such, we received thoughtful and constructive feedback, which we have already incorporated into our attached revision. We are confident that these reviews have improved our manuscript.

Our goal with this manuscript is to present a proof-of-concept study where high-content imaging and morphological profiling are used to characterize drug resistance in clonal cell lines. The main criticism from reviewers was that our original manuscript may have overstated our method’s ability to discriminate the signal of bortezomib resistance and that any extension beyond cultured cells (to patient samples for example) would require significant follow-up studies. The reviewers suggested that such work would be beyond the scope of our study, and recommended toning down our language to better reflect the limitations of this proof-of-concept work. We have embraced this suggestion, extensively revising our text, and we now believe our language and tone more accurately reflects our results. The reviewers also suggested follow-up computational analyses to more robustly characterize the bortezomib resistance signature. We have performed these analyses and added their description to our revised manuscript. We feel that these analyses have improved understanding of the signature, and will help a reader to gain a deeper understanding of our results and methodology.

The reviewers also suggested several minor changes; many of which we embraced fully, but others that we chose not to incorporate. We felt that a lack of clarity in our text contributed to these reviewer suggestions. In these cases, we improved clarity in the text and responded to each comment point-by-point in the “prefer not to carry out” section. Further, we address all reviewer comments in the following document point-by-point, grouped by common themes across reviewers (e.g., tone, clarity, analyses, etc.).

Lastly, a common theme among reviewer comments was their appreciation for our strong methodology and data transparency (examples pasted below). We are extremely gratified by this observation as we feel this is a particular strength of our manuscript. In addition, we were pleased to see reviewers engaged by our work, acknowledging the interest this manuscript is likely to generate among a broad range of scientific disciplines.

Examples of reviewer appreciation of our strong methodology and data transparency:

Reviewer 1: “However, this does not imply that the same approach can not achieve the goal, perhaps by using other cell painting markers for bortezomib-sensitivity, or with the same markers to assess sensitivity of different drugs. The cell painting + analysis approaches are not new and the clinical impact is questionable, but the technical aspects (data, analysis) are exceptional and the concept may hold as I described above.”

Reviewer 2: “The paper is well written, and the text is clear, as is the presentation of data and transparency of methods being utilized. The methods were applied appropriately and followed established standards in the field. The paper's premise is timely and interesting, addressing a pressing issue in cancer therapy: making informed treatment decisions fast, based on markers found in tumors early in tumor development, and using image-based screening for characterizing drug resistance before treatment could be an option. A fascinating bit of the manuscript is the description of the feature selection from the screen is done systematically, considering the technical and biological variability and technical artifacts and modeling covariates using linear models seems a very appropriate way of doing so and could serve as another proof of concept that this is indeed the most robust way of modeling and removing signal of technical covariates from the data.”

Reviewer 3: “The strengths of this study are the machine learning best practice and detailed methodology. The experiments could be reproduced and statistical analysis is more than adequate. The analysis takes into account batch effects, well position, differences in cell numbers, and other sources of technical variation that complicate high-content image analysis. It is a good exemplar of how unsupervised morphological profiling can be applied to imaging data. The major limitation is the generalizability of this particular method for patient samples. This could be addressed in the Discussion.”

1. Description of the planned revisions

We have incorporated all planned revisions.

1. Description of the revisions that have already been incorporated in the transferred manuscript

Text revisions already carried out

1. [Text revision] We have materially toned down our claims in the manuscript in two distinct areas: A) model performance and B) potential clinical application. A) Model performance. We specifically balanced our discussion of the discriminative signal of the Bortezomib Signature. While the signature adequately separated never-before-seen wildtype and resistant clones with metrics well above randomly permuted baselines (accuracy near 80%, average precision about 70%, area under the ROC curve (AUROC) about 84%), there were many limitations that we should have more explicitly highlighted. For example, many individual profiles were incorrectly classified, some clones were predicted entirely incorrectly, and many profiles did not receive Bortezomib Signature scores above the randomly permuted baseline. We have more clearly discussed these limitations and used more balanced language (see key examples of text-based changes below). Additionally, we modified a figure (now Figure 3) to include boxplots of clones that explicitly show the Bortezomib Signature scores of each well profile and permit examination of the strength of the signature for each clone (previously found in Figure 2-Supplement 9). Lastly, we add a new supplementary figure (now Figure 5-Supplement 1) that describes a feature space analysis of misclassified samples. Please note that this figure rearrangement and new analysis helped to balance our claims, but were also performed in response to other tangential reviewer comments. B) Clinical application. In the abstract, introduction, and discussion, we further emphasized that this work is a proof of concept, and that more advances must be made prior to clinical application.

We made these changes in direct response to the following reviewer comments:

Reviewer 1 - Major Comment 1 (relevant excerpts)

While I am convinced that the signature captures morphological phenotypes associated with drug resistance, at the cumulative scale, the discriminative signal of a single cell type seems weak… With Fig. 4, the data fully supports the argument that the bortezomib-signature encodes bortezomib-resistance, but the signal is weak. Thus statements such as "We found the Bortezomib Signature could predict whether a cell line was bortezomib-resistant or bortezomib-sensitive" (line #172) and the specificity statements in the abstract" (line #28) are not supported by the data in my opinion. I would recommend the authors to tune down these and other related statements throughout the manuscript.

Reviewer cross-commenting - Reviewer 1

My main critic is regarding "over selling" a weak discriminative signal. Specifically, I am not convinced that the major claims regarding predicting sensitivity and specificity at the single cell types scales are supported by the data. Since reviewer #2 and #3 did not raise this concern I think it is worth discussion here.

Once these statements are tuned down - I think no significant additional work is needed to make the point that they can measure a discriminative signal. If they want to make these claims, perhaps they'd like to collect more data to gain statistical power (but I am not optimistic this will work at the single cell level).

Personally, I was happy with the authors' choice of cell lines not included in the training dataset. I am not convinced that additional cell lines + validations are necessary for making the point of a proof of principle.

Reviewer cross-commenting - Reviewer 2

I agree that, perhaps, my major criticism of the paper was the manuscript's 'overselling' of claims that were only weakly supported by the data. Yes, if the authors tune down their claims and clearly state that this is an interesting starting point and proof of concept study, it might be ok to publish with only minor revisions. If the claims should be more generalized, then this study needs more data supporting the conclusions and the method's predictive power.

Reviewer 2 - Major Comment 8

Lastly, I find some misfits between the question, the model used, and the conclusions drawn. The authors start by exploring the problem of bortezomib resistance in cancer treatment, which they say is a devastating issue for patients with, e.g., multiple myeloma. Yet, the authors use HCT116 as their model cell line, a microsatellite instable, colorectal cell line with several intrinsic mutations that make it a difficult model to address physiologically relevant medical problems after all. The authors then go on to suppose that their method might be suitable to diagnose resistance in patient samples, but I am not convinced this conclusion can be speculated based on data from HCT cells. I suggest the authors test their approach on at least two other cell lines (maybe from different tissues) and benchmark their results against a dataset of digital pathology where such predictions are made from stained and analyzed tissue slices. This way, after a thorough benchmark against related third-party data sets, the method would significantly gain relevance, the paper would appeal to a broader audience, and the advance gains more merit.

Reviewer 3 - Major Comment 5

It is not clear from the Discussion whether this type of analysis is more broadly applicable to cell lines derived from patients, rather than selected from a parental cell line, or if this approach would be more efficient than genotyping or next-gen sequencing. How many replicates and ground truth cell lines would be necessary for predictive confidence?

We edited the last two sentences of the abstract to tone down specificity claims (“provide evidence”) and clarify that we are establishing a “proof-of-concept framework”.

• This signature predicted bortezomib resistance better than resistance to other drugs targeting the ubiquitin-proteasome system. Our results establish a proof-of-concept framework for the unbiased analysis of drug resistance using high-content microscopy of cancer cells, in the absence of drug treatment.

We revised the last paragraph of the introduction to contrast bortezomib predictions with ixazomib/CB-5083 predictions, and to remove claims about “using microscopy to guide therapy”.

• This morphological signature correctly predicted the bortezomib resistance of seven out of ten clones not included in the signature training dataset. Overall, our results establish a proof-of-concept framework for identifying unbiased signatures of drug resistance using high-content microscopy. The ability to identify drug-resistant cells based on morphological features provides a valuable orthogonal method for characterizing resistance in the absence of drug treatment.

To tone down claims in the figures, we added boxplots to Figure 3 (previous Figure 2) showing specific distribution of signature scores per well profile and updated Figure 4 legend (previous Figure 3).

• Figure 4. Bortezomib Signature has limited ability to characterize clones resistant to other ubiquitin-proteasome system inhibitors.

We modify the following text in the discussion to tone down claims of specificity and clinical utility:

• This Bortezomib Signature correctly predicted the bortezomib resistance of seven out of ten clones not included in the training dataset and was more specific to bortezomib-resistance given its limited ability to identify clones that were resistant to other UPS-targeting drugs.

Though it is unclear whether this method can be extended to patient samples, where identifying intrinsic drug resistance in cells prior to treatment has the potential to improve targeted cancer therapy, our results are an encouraging proof of concept. We expect that further refinement may develop Cell Painting as a tool for identifying drug-resistant cells, perhaps even guiding strategies to overcome intrinsic resistance.

1. [Text revision] We defined LD50 in text (originally line #97), changed description of resistant clone selection to remove main text references to LD90 (originally line #87), and stated drug concentrations used for selection in Methods. We also defined LD90 in the Methods and described its role in determining the drug concentrations to use for clone selection. This change was in response to the following comments:

Reviewer 1 - Minor Comment 2

What is LD90 (line #87)? LD50 (line #97)?

Reviewer 2 - Minor Comment 5

What was the LD 90 per drug on HCT cells? Rather than LD90 foldchanges, absolute concentrations should be used in the results and discussion to allow the reader to vet the conclusions.

• To determine the appropriate drug concentrations to use in order to isolate drug-resistant clones, we performed proliferation assays on HCT116 parental cells with our drugs of interest: bortezomib (proteasome inhibitor), ixazomib (proteasome inhibitor), or CB-5083 (p97 inhibitor) (Fig. 1-Supplement 1 A-D).
• We characterized the bortezomib-resistant clones and found that the median lethal doses (LD50s) were ~2.8- to ~9-fold that of HCT116 parental cells (Fig. 1-Supplement 2 B).
• Briefly, HCT116 cells were plated in 150 mm dishes and grown in the presence of the desired drug at a concentration that resulted in the death of the majority of cells (selection concentrations: bortezomib, 12 nM; ixazomib, 150 nM; CB-5083, 600 and 700 nM).

• Using the data from our proliferation assays, we calculated the median lethal dose (LD50) for each of our drugs of interest by fitting data of normalized growth vs. log[drug concentration] to a sigmoidal dose-response curve using GraphPad Prism (v.9.2.0) (Fig. 1-Supplement 1 D).

• [Text revision] We thank the reviewer for allowing us an opportunity to improve clarity on the clones we used. We now describe the total number of clones generated and removed unnecessary references to specific clones for ease of reading (originally lines #96-98) (We maintain all references to specific clones in the figures, legends, supplement, and methods)

Reviewer 1 - Minor Comment 3

It was not clear to me in the text which and how many cell lines were evaluated and the reader is forced to go to the SI. For example, "(BZ01-10 and BZ clones A and E)" (line #96-97) and "wild-type clones (WT01-05, 10, and 12-15)" (line #98) appeared when presenting the results without a clear explanation and made it harder for me to follow. Summary of the data (for example, based on Figure 2-Supplement 8) can be briefly mentioned in the text to make it more clear for the reader.

We added the following to the second paragraph of the results:

• Together these methods provided a total of twelve bortezomib-resistant, five ixazomib-resistant, five CB-5083-resistant, and twelve bortezomib-sensitive clones as well as HCT116 parental cells for our experiments.

[Text revision] We removed duplicate text (originally lines #115-125).

Reviewer 1 - Minor Comment 5

1. Lines #104-111 were duplicated in lines #114-122.

Reviewer 3 - Minor Comment 4

Ten lines of text are duplicated on page 5.

Reviewer 2 - Minor Comment 4

on page 5, paragraph 4, there is a sizeable copy-and-paste error of text being identically replicated.

1. [Text revision] We provided more intuition of the Bortezomib Signature in the results section (originally lines #150-151).

Reviewer 1 - Minor Comment 6

The "Bortezomib Signature" is a critical measurement but is only briefly mentioned in lines 150-151 ("..based on the direction-sensitive ranking method for phenotype analysis, singscore (Foroutan et al., 2018)"). Please provide more information/intuition.

• We used these 45 features to compute a rank-based resistance score or “Bortezomib Signature” for each well profile based on the direction-sensitive method called singscore (Foroutan et al. 2018). Singscore ranks these 45 resistance-related features on a per sample basis and calculates a normalized score between -1 and 1, with higher values expected for bortezomib-resistant clones and lower values expected for bortezomib-sensitive clones.

• [Text revision] We clarified that DNA sequencing had been performed solely on clones A and E in a previous study (originally lines #88-90). Furthermore, one of the strengths of our approach is that it can identify resistant clones in an unbiased fashion prior to molecular characterization. It is beyond scope to perform these sequencing studies in the present paper.

Reviewer 2 - Minor Comment 3

The authors talk about validating the mutation - PSMB5 by RNA-seq. However, the data for the genotyping/sequencing/characterization of these newly generated BZ-resistant lines are missing.<br />

In the results, we clarify DNA sequencing that was previously performed on clones A and E

• We also isolated bortezomib-sensitive (wild-type; WT) clones by dilution of the HCT116 parental cell line and acquired two bortezomib-resistant clones (BZ clones A and E) both with mutations in PSMB5 identified by RNA sequencing performed in previous work (Fig. 1-Supplement 1 E) (Wacker et al. 2012).

In the last paragraph of the discussion, we highlight the strength of our unbiased approach

• Together, our work has demonstrated the potential for morphological profiling with Cell Painting to be used as an unbiased method to characterize resistance in the absence of drug treatment. Our results indicate that different mechanisms of bortezomib resistance may generate distinct morphological profiles; with larger and broader training datasets, it may be possible to identify signatures for distinct mechanisms of bortezomib resistance as well as signatures of resistance to other drugs. Though it is unclear whether this method can be extended to patient samples, where identifying intrinsic drug resistance in cells prior to treatment has the potential to improve targeted cancer therapy, our results are an encouraging proof of concept. We expect that further refinement may develop Cell Painting as a tool for identifying drug-resistant cells, perhaps even guiding strategies to overcome intrinsic resistance.

• [Text revision] We thank the reviewers for their suggestions. We agree that the description of the experimental design was somewhat unclear and have provided greater detail and clarity, particularly regarding the generation of clones. We used the HCT116 parental cell line to generate drug-resistant clones by identifying single surviving cells after drug treatment and allowing these cells to expand prior to isolating colonies for experimentation. We did not perform experiments to confirm whether these “clones” were isogenic and can not exclude cell migration during expansion or genetic drift as convoluting factors. However, we have provided greater detail in the descriptions of our method for clone isolation in order to address this concern.

Reviewer 1 - Minor Comment 1

More information in Fig. 1's legend would be helpful to follow the experimental design. I found it hard to follow in its current form and had to go back to carefully reading the main text to fully understand.

Reviewer 2 - Minor Comment 6

The description of the resistant clonal populations is confusing. As I understand, no single-cell clones were isolated during the selection procedure. Thus, the training lines are not yet isogenic clones but oligoclonal sub-populations of the parental cell line. The authors could provide more details here and discuss the different characteristics of their sub-populations, e.g., their growth kinetics or molecular alterations.

We bolstered the description in the results.

• We first isolated and characterized drug-resistant cells (Fig. 1 A). To isolate drug-resistant clones, we used an approach we have described previously (Wacker et al. 2012; Kasap, Elemento, and Kapoor 2014) and the HCT116 cell line. These cancer cells express multidrug resistance pumps at low levels and are mismatch repair deficient, providing a genetically heterogeneous polyclonal population of cells (Umar et al. 1994; Papadopoulos et al. 1994; Teraishi et al. 2005) allowing for isolation of drug-resistant clones in 2-3 weeks. We hypothesize that a rapid selection of resistance could favor the isolation of clones with intrinsic resistance. To determine the appropriate drug concentrations to use in order to isolate drug-resistant clones, we performed proliferation assays on HCT116 parental cells with our drugs of interest: bortezomib, ixazomib, or CB-5083 (Fig. 1-Supplement 1 A-D). We also isolated bortezomib-sensitive (wild-type; WT) clones by dilution of the HCT116 parental cell line and acquired two published bortezomib-resistant clones (BZ clones A and E) both with mutations in PSMB5 identified by RNA sequencing performed in previous work (Fig. 1-Supplement 1 E) (Wacker et al. 2012). We characterized the bortezomib-resistant clones and found that the median lethal doses (LD50s) for bortezomib were ~2.8- to ~9-fold that of HCT116 parental cells (Fig. 1-Supplement 2 B). In contrast, bortezomib-sensitive clones had LD50s for bortezomib that ranged from ~0.7- to ~1.2-fold that of HCT116 parental cells (Fig. 1-Supplement 2 A). Together these methods provided a total of twelve bortezomib-resistant, five ixazomib-resistant, five CB-5083-resistant, and twelve bortezomib-sensitive clones as well as HCT116 parental cells for our experiments.

We also updated the legend for Figure 1A.

• Figure 1. Experimental design for using Cell Painting to examine morphological profiles of drug-resistant cells. (A) Graphic of the experimental workflow: we isolated drug-resistant clones by treating parental HCT116 cells with a high dose of the desired drug and then expanded them for experiments. We isolated drug-sensitive clones by diluting HCT116 cells and then expanded them for experiments. We then performed proliferation assays on select clones to screen for multidrug resistance. Next, we performed Cell Painting on both drug-resistant and -sensitive clones, using multiplexed high-throughput fluorescence microscopy of fixed cells followed by feature extraction and morphological profiling to search for features that contribute to a signature of drug resistance.

• [Text revision] We clarified that the Bortezomib Signature did not correspond to well position (originally lines #155-157).

Reviewer 1 - Minor Comment 9

Line #155-156: "We found that the pattern of Bortezomib Signatures corresponded to the cell identity plate layout", the word "not" is missing before "corresponded".

We found that the pattern of Bortezomib Signatures did not correspond to well position relative to the plate (Fig. 2-Supplement 7 B), indicating that the well position for each clone was not strongly contributing to its Bortezomib Signature.

1. [Text revision] We explicitly described the result that some misclassified clones (WT10, WT15, and BZ06) did not have unexpected bortezomib sensitivity as determined by proliferation assays. We also moved the supplementary figure to an updated Figure 3 to better highlight this result (described below in “Figure revisions already carried out”). Lastly, we add a new figure (Figure 5-Supplement 1) to more explicitly analyze the misclassified lines (described below in “New analyses already carried out”).

Reviewer 3 - Minor Comment 3

The bortezomib sensitivity of the WT lines used in the last experiments was determined and did not seem to be greater than parental. This could be mentioned in the text; the figure raises the question and the answer is provided, but it's in the supplemental material.

While the Bortezomib Signature correctly characterized the bortezomib sensitivity of most clones, it consistently misclassified others (WT10, WT15, and BZ06) (Fig 5-Supplement 1 A). Proliferation assays conducted in earlier experiments showed that WT10 and WT15 were sensitive to bortezomib while BZ06 was resistant (Fig. 1-Supplement 2 A and B). By comparing these incorrect predictions with high-confidence correct predictions, we observed differences that varied by clone type, suggesting unique morphology may be driving each of these misclassifications (Fig. 5-Supplement 1 B and C). These results are consistent with the Bortezomib Signature being generalizable to clones not included in the training dataset and suggest that morphological profiling has the potential to identify bortezomib-resistant clones based on the morphological features of cells in the absence of drug treatment.

1. [Text revision] We clarified that the metrics (accuracy and average precision) were based on median Bortezomib Signature scores of all replicate well-level profiles per clone. We can compare samples based on rank, and difference from 95% confidence interval of permuted data. There is no current way for our method to assign a likelihood. Also note that we have updated the discussion to discuss alternative metrics (see Reviewer 1 - Minor Comment 7) These are very important distinctions, and we are grateful to the reviewer for bringing them up.

Reviewer 3 - Major Comment 3

The study classifies cells as binary sensitive or resistant, but would results be improved by scoring based on likelihood of being resistant/sensitive?

Reviewer 3 - Minor Comment 2

It is not clear whether the accuracy was based on a percentage of replicates per cell line that were classified correctly or whether that was referring to classification of the cell line overall as sensitive/resistant.

• We next examined whether the Bortezomib Signature was able to predict the bortezomib resistance of a clone based on morphological profiling data (Fig. 3 A-E and Fig. 3-Supplement 2 A and B). We called the clone bortezomib-resistant if the median Bortezomib Signature of all replicate well profiles was greater than zero and bortezomib-sensitive if the median Bortezomib Signature less than zero. In the training dataset, the Bortezomib Signature correctly predicted the bortezomib resistance of all ten clones, with median Bortezomib Signatures for eight out of ten clones beyond the 95% confidence interval for the randomly permuted data (Fig. 3 A). The accuracy of the Bortezomib Signature was 88% while the average precision was 81% for the training dataset (Fig. 3-Supplement 2 A and B) (see Methods). The signature performed similarly well in the validation dataset (Fig. 3 B), with an accuracy of 92% and an average precision of 89% (Fig. 3-Supplement 2 A and B). In the test dataset the Bortezomib Signature correctly predicted the bortezomib resistance of all clones, though only HCT116 parental cells had a median Bortezomib Signature outside the 95% confidence interval for the randomly permuted data (Fig. 3 C). The test dataset had an accuracy of 80% and an average precision of 68% (Fig. 3-Supplement 2 A and B). Similarly, in the holdout dataset the Bortezomib Signature had an accuracy of 78% and an average precision of 69% (Fig.3 -Supplement 2 A and B), and correctly predicted the bortezomib resistance of twelve out of thirteen clones, with WT01 misclassified as bortezomib-resistant (Fig. 3 D). In the holdout dataset, four of the twelve correctly characterized clones had median Bortezomib Signatures outside the 95% confidence interval for the randomly permuted data.

We also mirrored language when discussing the ixazomib and CB-5083 results.

• However, only two of the four correctly identified ixazomib-resistant clones and one of the three CB-5083-resistant clones had median Bortezomib Signatures outside the 95% confidence interval of the randomly permuted data. The area under the ROC (AUROC) curve for ixazomib-resistant and CB-5083-resistant clones (0.63 and 0.60, respectively) was lower than those calculated for the training, validation, test, and holdout datasets. In addition, many of the Bortezomib Signatures for well profiles of ixazomib- and CB-5083-resistant clones, particularly those for CB-5083-resistant clones, landed within the 95% confidence interval of the randomly permuted data. These results suggest that the Bortezomib Signature is not a general signature of UPS-targeting drug resistance and instead has some specificity for bortezomib.

• [Text revision] We added an explicit note that our image analysis pipelines are also publicly available. Our reporting of our data processing pipelines are documented fully and well above standards in our field. Linking the publicly-available resources with these methods maximizes reproducibility.

Reviewer 1 - Minor Comment 10

Additional details on the processing steps in the analysis pipeline in the Methods will be highly appreciated.

We include all image analysis pipelines at https://github.com/broadinstitute/profiling-resistance-mechanisms (G. Way et al. 2023).

1. [Text revision] We have compared our approach to the on-disease/off-disease scores as introduced in (Heiser et al. 2020). We agree with the reviewer that a discussion of these two methods would help clarify our phenotypic signature concept. The on/off score is about the degree to which a perturbation pushes disease towards a healthy state. In this case we have 3 sets of data: healthy samples (used for training), disease samples (used for training), and the sample we want to score, which should be of the form "disease + perturbation". With our approach, based on singscore, we also have 3 sets of data: sensitive samples (used for training), resistance samples (used for training), and the sample we want to score. Here, our sample we want to score could be anything, not necessarily of the form "resistance + perturbation". Furthermore, singscore does not have the concept of orthogonality to resistance/sensitivity. This would become relevant if we were exploring perturbations or conditions that would induce a resistant cell line to become sensitive, but we are not doing that here. There are other statistical differences (projection vs. rank based etc.) but the key difference is the applicability of the method to the specific problem at hand.

Reviewer 1 - Minor Comment 7

How is the Bortezomib Signature related to the "on-disease"/"off-disease" scores described in https://www.biorxiv.org/content/10.1101/2020.04.21.054387v1.full? Are there other alternatives used for similar binary phenotypic signatures? What is the justification for using these measurements? I would love to see this generalized concept explicitly discussed in the Discussion.

We added the following to the discussion.

• The Bortezomib Signature is conceptually similar to the on-disease/off-disease score (Heiser et al. 2020). Both require three phenotypic measurements: a target phenotype representing ideal, a disease phenotype, and a new phenotype to classify. However, our approach is technically different (non-parametric compared to linear projection) and our goals are different (phenotypic classification compared to perturbation alignment). Other methods also enable phenotype labeling, but they focus on single-sample annotation without regard to a target phenotype (Wawer et al. 2014; Rohban et al. 2017; Simm et al. 2018; Nyffeler et al. 2020).

Figure revisions already carried out

1. [Figure revision] We moved all boxplots from the original Fig. 2-Supplement 9 to the main text (also splitting Fig. 2 into Fig. 2 and 3). From the original Figure 2, we moved the accuracy and average precision bar graphs to the supplement. We also note that this change increases transparency of the discriminative signal of our signature.

Reviewer 1 - Minor Comment 8

I would highly recommend showing the Bortezomib Signatures from Figure 2-Supplement 9. in Fig. 2. This was the main measurement used throughout the manuscript and in my opinion, it is very important to consistently visualize the data along the manuscript, for clarity and easier reader interpretation.

1. [Figure revision] We adjusted the position of the legend in the accuracy and average precision bar graphs (originally Fig. 2 C and D, now Fig. 3-Supplement 2) for clarity. We also note that keeping the bar chart here is standard best practice (compared to a dot plot).

Reviewer 1 - Minor Comment 4

I found the visualization in Fig. 2C-D not intuitive (it is properly explained in the legend). I suggest replacing the accuracy colorbar with a color marker to make it more distinct from the random permutation (|--*--|) The location of the text "mean +- SD of 100 random permutation" made me first think that it is linked to the holdout.

1. [Figure revision] We changed the point distribution in the boxplots (from expanded to standard) to minimize overlap with the boxplot lines. We also updated the legend text to indicate that individual points in boxplots represent the Bortezomib Signature for well profiles. Note, we paste a representative example of this change above (new Figure 3).

Reviewer 3 - Minor Comment 1

I found the box plots somewhat difficult to interpret (especially where the WT lines had a lot of overlap with the red shaded area). Do the points in these charts correspond to replicate wells?

We also update the figure legend.

• Plots show values for individual well profiles (points), range (error bars), 25th and 75th percentiles (box boundaries), and median.

• [Figure revision] [Response to Reviewer 2 - Major Comment 7] We thank the reviewer for allowing us an opportunity to clarify the mechanism. We feel that it is beyond scope of this manuscript to disentangle the molecular alterations that cause bortezomib resistance based on our Cell Painting insights. This wet lab experimental process is arduous and cost prohibitive, and we argue that one of the benefits of taking a morphology approach to resistance status is that we can detect resistant cells (and therefore cells that won’t die when presented with a treatment) without knowing the molecular mechanism.

Nevertheless, the reviewer has encouraged us to enhance the ability for a reader to view and interpret the signature to perhaps more easily facilitate future work. Previously, we presented our signature in text form in Figure 2-Supplement 4 and in heatmap form in Figure 2-Supplement 5. Here, we add a new figure (Figure 2-Supplement 6; pasted below) which will improve interpretability.

Reviewer 2 - Major Comment 7:

Next to feature importance, the authors do not discuss (or I missed) what biology the features represent. Such the reader is left wondering what the actual mechanism of bortezomib resistance could be and if cell painting could shed light on the molecular alterations that cause the treatment resistance. While reviewing, I thus wondered which audience the authors targeted with their manuscript. A more focused analysis of their data that highlights aspects of the study either for the machine learning community, the cell biology community, or the precision oncology community would greatly benefit the manuscript's impact. In its current form, the study's findings seem diluted and spread across a wide range of research questions.<br />

• Figure 2-Supplement 6. Bortezomib Signature visualized by CellProfiler features. Visualization of CellProfiler features contributing to the Bortezomib Signature. Features with high values (mean signature estimates) in resistant cells are purple while features with low values in resistant cells are green. The mean signature estimates were based on Tukey's Honestly Significant Difference test score and the number in each box represents the number of features used to calculate the mean signature estimate.

Additionally, we add the following to the results section:

• We then examined the grouping of features across compartments and channels and found radial distribution features were higher in resistant cells (Fig 2-Supplement 6).

The code change to generate the signature visualization summary is available at: https://github.com/broadinstitute/profiling-resistance-mechanisms/pull/131

New analyses already carried out

1. [New analysis] [Response to Reviewer 2 - Major Comment 5] We agree that a systematic analysis of feature selection methods will provide additional insights not already in the manuscript. Therefore, we have performed two new computational experiments to compare our linear modeling feature selection approach against other standard approaches. We demonstrate that our linear modeling approach is effective at isolating the core differences between resistant and sensitive classes.

Specifically, we performed two analyses: A) UMAP and B) k-means cluster analysis. We analyzed profiles defined by four different feature selection approaches: 1) Using all traditional CellProfiler features; 2) Using the traditional CellProfiler feature selection approach (removing low variance features, high correlating features, etc.); 3) Using 45 random features (same size as Bortezomib Signature); and 4) Using only the bortezomib signature features. We performed Fisher’s exact tests to derive odds ratios of cluster membership by resistance status and calculated Silhouette widths to quantify relative proximity of clusters.

This analysis generates a new supplementary figure (see below), and demonstrates that the linear-modeling-based feature selection isolated the features driving the differences between the clone types (resistance vs. wildtype) while the standard approaches do not as effectively separate.

Reviewer 2 - Major Comment 5:

A fascinating bit of the manuscript is the description of the feature selection from the screen is done systematically, considering the technical and biological variability and technical artifacts and modeling covariates using linear models seems a very appropriate way of doing so and could serve as another proof of concept that this is indeed the most robust way of modeling and removing signal of technical covariates from the data. Yet, I wondered why the authors do not discuss other means of feature selection or dimensionality reduction; further, they need to show how the features cluster the cell lines or why impact (information content) different features deliver. For an audience interested in the technical aspects of cell painting analysis and machine learning based on the data, that would, IMHO, be the most exciting questions.

• Figure 3-Supplement 3. Benchmarking linear-modeling feature selection to separate clones by bortezomib resistance. Uniform Manifold Approximation and Projection (UMAP) analysis of the qualitative separability of (A) resistance status and (B) Bortezomib Signature scores across four different feature spaces. (C) k-means clustering from k=2 to k=14 of average odds ratio, maximum odds ratio (Fisher’s exact test), and Silhouette width using Bortezomib Signature features.

Additionally, we add the following to the results section:

• We then compared our linear-modeling approach to feature selection against other feature spaces and found that the Bortezomib Signature clusters same-type clones (bortezomib-resistant vs. bortezomib-sensitive) with higher enrichment compared to the full feature space, standard feature selection (see Methods), or a random selection of 45 features (Fig 3-Supplement 3).

And methods section, describing this analysis:

• We were also interested in comparing the ability of different feature spaces to cluster clones of the same type (resistant vs. sensitive). This analysis would determine if the Bortezomib Signature features, which we derived using linear modeling to isolate biological from technical variables, had a greater ability to cluster. We compared the Bortezomib Signature against three other feature spaces: 1) the full feature space, 2) standard feature selection (see Image data processing methods), and 3) 45 randomly selected features. We performed two analyses using these four feature spaces including Uniform Manifold Approximation and Projection (UMAP) (McInnes et al. 2018) and k-means clustering. For UMAP, we used default umap-learn parameters to identify two UMAP coordinates per feature space. We then visualized the clusters by their resistance status and Bortezomib Signature score. The UMAP analysis represents a qualitative analysis. Next, we applied k-means clustering with 25 initializations across a range of 2-14 clusters (k). Prior to clustering and for each feature space, we applied principal component analysis (PCA) and transformed each feature space into 30 principal components. This step was necessary to compare k-means clustering metrics, which are sensitive to the feature space dimensionality. We applied a Fisher’s exact test to each cluster using a two-by-two contingency matrix that specified cluster membership for each clone classification (resistant vs. sensitive). We visualized the mean odds ratio and max cluster odds ratio for each feature space across k. A high odds ratio tells us that the feature space effectively clusters clones of the same resistance status. Lastly, we calculated Silhouette width (the average proximity between samples in one cluster to the second nearest cluster) for each feature space across k.

The code change to derive the UMAP coordinates, perform clustering, and generate the figure is available at https://github.com/broadinstitute/profiling-resistance-mechanisms/pull/132

1. [New analysis] [Response to Reviewer 3 - Major Comment 1] We thank the reviewer for this suggestion, which allowed us to explore the misclassified samples in more depth. We added a new supplementary figure in which we summarized all bortezomib clones (wildtype and resistant) in their accuracy based on the bortezomib signature (panel A). We did not include training set samples in this analysis. Using samples that were consistently incorrectly classified with high confidence (three samples: WT15, BZ06, WT10) we performed two separate two-sample Kolmogorov–Smirnov (KS) tests. Specifically, we compared high incorrect wildtype to high correct wildtype and high incorrect resistant to high correct resistant. Our results indicate that most bortezomib signatures were significantly different between correct and incorrect assignments (panel B), and that the signature features varied between resistant and wildtype misclassification tests (panel C).

Reviewer 3 - Major Comment 1:

While the claims are largely substantiated, there are a few points where further consideration would improve the manuscript. Several cell lines were mis-classified with what appears to be a high degree of certainty. Can the authors tell what was driving those predictions? Was there something in the morphological signature that weighed more heavily in those cases?

• Figure 5-Supplement 1. Examining the accuracy of clone classification and misclassification of clones. (A) Proportion of high-confidence correct, low-confidence correct, low-confidence incorrect, and high-confidence incorrect predictions of well profiles across clones in the test, holdout, and validation sets. High-confidence predictions (high) had a Bortezomib Signatures greater (resistant clones) or less than (sensitive) the 95% confidence interval of randomly permuted data while low-confidence predictions (low) had Bortezomib Signatures within the 95% confidence interval of randomly permuted data. (B) Visualization of Kolmogorov-Smirnov (KS) test statistic means of feature groups across channels and cellular compartments. (C) Plot of the KS test statistic means for feature groups in bortezomib-resistant vs. -sensitive cells. Each feature group is color coded by the imaging channel.

Additionally, we add the following to the results section:

• While the Bortezomib Signature correctly characterized the bortezomib sensitivity of most clones, it consistently misclassified others (WT10, WT15, and BZ06) (Fig 5-Supplement 1 A). Proliferation assays conducted in earlier experiments showed that WT10 and WT15 were sensitive to bortezomib while BZ06 was resistant (Fig. 1-Supplement 2 A and B). By comparing these incorrect predictions with high-confidence correct predictions, we observed differences that varied by clone type, suggesting unique morphology may be driving each of these misclassifications (Fig. 5-Supplement 1 B and C). These results are consistent with the Bortezomib Signature being generalizable to clones not included in the training dataset and suggest that morphological profiling has the potential to identify bortezomib-resistant clones based on the morphological features of cells in the absence of drug treatment.

And methods section, describing this analysis:

Some profiles were consistently predicted incorrectly with high confidence but in the opposite direction (see Figure 5-Supplement 1). For a well-level profile to be categorized as high-confidence (in either the correct or incorrect directions), it needed to score beyond the 95% confidence interval of the randomly permuted data range. For example, a high-confidence incorrect resistant profile would have a Bortezomib Signature below 95% confidence interval of the randomly permuted data. To evaluate the features driving the differences in these samples, we applied two-sample Kolmogorov–Smirnov (KS) tests per Bortezomib Signature feature. We applied these tests to two separate groups: 1) misclassified bortezomib-sensitive vs. high-confidence accurate bortezomib-sensitive and 2) misclassified bortezomib-resistant vs. high-confidence accurate bortezomib-resistant.

The code change to generate the UMAP coordinates and figure is available at https://github.com/broadinstitute/profiling-resistance-mechanisms/pull/130

Description of analyses that authors prefer not to carry out

1. [Response to Reviewer 2 - Minor Comments 1 and 2]: These are interesting suggestions! Still, we prefer not to speculate on the biological mechanism of the Bortezomib signature. Connecting morphological features identified as contributing to the Bortezomib Signature by Cell Painting to specific biological pathways would demand considerable cell-based assays to validate. In addition, our analyses suggest that the features contributing to the Bortezomib Signature are spread across a range of cellular compartments and channels, making it difficult to pin down specific mechanisms or pathways as likely contributors to bortezomib resistance. However, we are adding a figure to increase interpretability of the signature, which will aid in developing future hypotheses. Note that the signature was not possible to detect by eye (Fig. 2 A).

Reviewer 2 - Minor Comment 1:

There could be some speculation on the mechanism of Bortezomib resistance concerning the literature with the existing image data. For example, Bortezomib resistance is connected to serine synthesis and how a particular feature could contribute to the known mechanism.<br />

Reviewer 2 - Minor Comment 2:

Along the same lines, the authors could show that larger cells lead to resistance with microscopic images.

2. [Response to Reviewer 2 - Major Comment 8]: We appreciate the reviewer’s concern that our work using HCT116 clonal cells lines may not directly reflect results from patient samples. Our choice was based on previously published work demonstrating the efficiency with which HCT116 cells generate resistant clones due to diminished DNA mismatch repair and decreased expression of drug efflux pumps. Since our work is a proof of concept rather than a comprehensive demonstration of translating morphological profiling into clinical practice, we believe that experiments using multiple patient cell lines from different tissues as well as digital pathology records to be beyond the scope of this work. We instead chose to tone down the language of our manuscript to more clearly acknowledge the limitations of our work and clarify this as a proof of concept.

Reviewer 2 - Major Comment 8 (relevant excerpt):

I suggest the authors test their approach on at least two other cell lines (maybe from different tissues) and benchmark their results against a dataset of digital pathology where such predictions are made from stained and analyzed tissue slices. This way, after a thorough benchmark against related third-party data sets, the method would significantly gain relevance, the paper would appeal to a broader audience, and the advance gains more merit.<br />

3. [Response to Reviewer 3 - Major Comment 2]: The bortezomib sensitivity of ixazomib- and CB-5083-resistant clones was not determined, and hence can not be ruled out as a possible explanation for their high Bortezomib Signature scores. However, we prefer not to conduct additional proliferation assays for the misclassified clones (IX02, WT06, CB14, CB16) in the presence of bortezomib to determine whether coincidental bortezomib resistance might explain the signature performance. Our rationale is that three other misclassified clones (WT10, WT15, and BZ06) had the expected bortezomib sensitivity in proliferation assays (Fig. 1-Supplement 2), meaning that additional proliferation assays may not reveal any insights regarding the signature performance.

Reviewer 3 - Major Comment 2:

Was the bortezomib sensitivity of the IX (or CB) resistant cell lines determined? If there were differences, this could explain some of the variation in the morphological signatures. This could be easily done in one or two growth experiments.

4. [Response to Reviewer 2 - Major Comment 7]: Thank you for pointing this out. Our goal is to keep the study multi-disciplinary. We are adding a figure to increase interpretability of the signature, and adding text-based clarifications.

Reviewer 2 - Major Comment 7 (relevant excerpt):

While reviewing, I thus wondered which audience the authors targeted with their manuscript. A more focused analysis of their data that highlights aspects of the study either for the machine learning community, the cell biology community, or the precision oncology community would greatly benefit the manuscript's impact. In its current form, the study's findings seem diluted and spread across a wide range of research questions.<br />

5. [Response to Reviewer 2 and 3 - Major Comments 6 and 4]: We prefer not to expand the scope of the model to predict other drug signatures. This would require a substantial amount of work to generate the appropriate drug-resistant clones, collect the imaging data, and analyze it, and we think it important to convey the purpose of our paper is proof of concept. We do not feel that the time invested in performing this analysis would result in adequate returns beyond what we already demonstrate.

Reviewer 2 - Major Comment 6.

Interestingly, the Bortezomib signature is specific to the drug and not a broad range of proteasomal inhibitors. However, seeing the common features between all the proteasomal inhibitors would be interesting.

Reviewer 3 - Major Comment 4

There was some predictive ability of the Bortezomib Signature for ixazomib resistance. Were there some features that were correlated with IX-resistance, i.e. UPS pathway, versus specific to bortezomib? Do the features suggest anything about resistance mechanisms or is the feature set too abstruse to interpret?

References

Foroutan, Momeneh, Dharmesh D. Bhuva, Ruqian Lyu, Kristy Horan, Joseph Cursons, and Melissa J. Davis. 2018. “Single Sample Scoring of Molecular Phenotypes.” BMC Bioinformatics 19 (1): 404.

Heiser, Katie, Peter F. McLean, Chadwick T. Davis, Ben Fogelson, Hannah B. Gordon, Pamela Jacobson, Brett Hurst, et al. 2020. “Identification of Potential Treatments for COVID-19 through Artificial Intelligence-Enabled Phenomic Analysis of Human Cells Infected with SARS-CoV-2.” bioRxiv. https://doi.org/10.1101/2020.04.21.054387.

McInnes, Leland, John Healy, Nathaniel Saul, and Lukas Großberger. 2018. “UMAP: Uniform Manifold Approximation and Projection.” Journal of Open Source Software 3 (29): 861.

Nyffeler, Johanna, Clinton Willis, Ryan Lougee, Ann Richard, Katie Paul-Friedman, and Joshua A. Harrill. 2020. “Bioactivity Screening of Environmental Chemicals Using Imaging-Based High-Throughput Phenotypic Profiling.” Toxicology and Applied Pharmacology 389 (January): 114876.

Rohban, Mohammad Hossein, Shantanu Singh, Xiaoyun Wu, Julia B. Berthet, Mark-Anthony Bray, Yashaswi Shrestha, Xaralabos Varelas, Jesse S. Boehm, and Anne E. Carpenter. 2017. “Systematic Morphological Profiling of Human Gene and Allele Function via Cell Painting.” eLife 6 (March). https://doi.org/10.7554/eLife.24060.

Simm, Jaak, Günter Klambauer, Adam Arany, Marvin Steijaert, Jörg Kurt Wegner, Emmanuel Gustin, Vladimir Chupakhin, et al. 2018. “Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.” Cell Chemical Biology 25 (5): 611–18.e3.

Wacker, Sarah A., Benjamin R. Houghtaling, Olivier Elemento, and Tarun M. Kapoor. 2012. “Using Transcriptome Sequencing to Identify Mechanisms of Drug Action and Resistance.” Nature Chemical Biology 8 (3): 235–37.

Wawer, Mathias J., Kejie Li, Sigrun M. Gustafsdottir, Vebjorn Ljosa, Nicole E. Bodycombe, Melissa A. Marton, Katherine L. Sokolnicki, et al. 2014. “Toward Performance-Diverse Small-Molecule Libraries for Cell-Based Phenotypic Screening Using Multiplexed High-Dimensional Profiling.” Proceedings of the National Academy of Sciences of the United States of America 111 (30): 10911–16.

Way, Gregory, Yu Han, David Stirling, and Shantanu Singh. 2023. Broadinstitute/profiling-Resistance-Mechanisms: Analysis for Preprint. Zenodo. https://doi.org/10.5281/ZENODO.7803787.

Way, Gregory P., Maria Kost-Alimova, Tsukasa Shibue, William F. Harrington, Stanley Gill, Federica Piccioni, Tim Becker, et al. 2021. “Predicting Cell Health Phenotypes Using Image-Based Morphology Profiling.” Molecular Biology of the Cell 32 (9): 995–1005.

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Referee #1

Evidence, reproducibility and clarity

The authors use Cell Painting, a high-content image-based phenotypic assay, to distinguish between clonal cancer cell lines that are resistant versus sensitive to a proteasome inhibitor anti-myeloma drug called bortezomib. The authors characterized a high-dimensional cell morphology signature for bortezomib-resistance, evaluated it on an independent subset of cell lines, and evaluated specificity in respect to other drugs targeting the ubiquitin-proteasome system. The authors thus propose image-based morphology characterization as an alternative method for characterizing drug resistance.

Strengths: solid methodology - cell lines validation of drug resistance, extensive data collection, thorough validation of the analysis pipeline, avoiding potential confounders, biases and proper data partitioning to test and hold-out (what the authors refer to as "machine learning best practices").

Weakness: weak discriminative signal. Some aspects of the writing could be improved to make the manuscript easier to follow (see Minor comments).

Major comments:

While I am convinced that the signature captures morphological phenotypes associated with drug resistance, at the cumulative scale, the discriminative signal of a single cell type seems weak. Specifically, it is not clear whether the signature can effectively capture the drug resistance of a single cell line. In Figure 2-Supplement 9, considering the test (C) and the holdout (D), only 1/9 BZ clones' median signatures were beyond the 95% confidence interval, with 4/6 and 2/6 WT cell types with median signatures beyond the positive and negative 95% confidence interval correspondingly. When defining bortezomib-sensitivity according to the median signatures' sign (>0 or <0) of a cell line, Figure 2-Supplement 9 shows that in the test+holdout there are 9/9 correct bortezomib-resistance (BZ) and 6/7 correct bortezomib-sensitive (WT) predictions. However, similar discrimination levels also appeared in the other drugs (ixazomib, CB-5083), making the statements about specificity less grounded. When the authors evaluate the AUROC they report ~0.6 (line #194) for the non-specific (ixazomib, CB-5083) drugs versus ~0.75 for bortezomib-resistance (line #202). With Fig. 4, the data fully supports the argument that the bortezomib-signature encodes bortezomib-resistance, but the signal is weak. Thus statements such as "We found the Bortezomib Signature could predict whether a cell line was bortezomib-resistant or bortezomib-sensitive" (line #172) and the specificity statements in the abstract" (line #28) are not supported by the data in my opinion. I would recommend the authors to tune down these and other related statements throughout the manuscript. An alternative would be to increase the number of wells and see whether this weak signal can indeed be statistically amplified with many replicates to make a robust and specific characterization of a cell line's bortezomib-sensitivity (but I assume this is a lot of work and probably out of scope of this manuscript). I think it is also important to discuss in more detail the interpretation of these results (including Figure 2-Supplement 9), in this context, in the Discussion.

Minor comments:

Suggested clarifications (some might be less relevant if the manuscript is designed for experts in the more clinical domain who are familiar with these terms / style):

1. More information in Fig. 1's legend would be helpful to follow the experimental design. I found it hard to follow in its current form and had to go back to carefully reading the main text to fully understand.
2. What is LD90 (line #87)? LD50 (line #97)?
3. It was not clear to me in the text which and how many cell lines were evaluated and the reader is forced to go to the SI. For example, "(BZ01-10 and BZ clones A and E)" (line #96-97) and "wild-type clones (WT01-05, 10, and 12-15)" (line #98) appeared when presenting the results without a clear explanation and made it harder for me to follow. Summary of the data (for example, based on Figure 2-Supplement 8) can be briefly mentioned in the text to make it more clear for the reader.
4. I found the visualization in Fig. 2C-D not intuitive (it is properly explained in the legend). I suggest replacing the accuracy colorbar with a color marker to make it more distinct from the random permutation (|--*--|) The location of the text "mean +- SD of 100 random permutation" made me first think that it is linked to the holdout.
5. Lines #104-111 were duplicated in lines #114-122.
6. The "Bortezomib Signature" is a critical measurement but is only briefly mentioned in lines 150-151 ("..based on the direction-sensitive ranking method for phenotype analysis, singscore (Foroutan et al., 2018)"). Please provide more information/intuition.
7. How is the Bortezomib Signature related to the "on-disease"/"off-disease" scores described in https://www.biorxiv.org/content/10.1101/2020.04.21.054387v1.full? Are there other alternatives used for similar binary phenotypic signatures? What is the justification for using these measurements? I would love to see this generalized concept explicitly discussed in the Discussion.
8. I would highly recommend showing the Bortezomib Signatures from Figure 2-Supplement 9. in Fig. 2. This was the main measurement used throughout the manuscript and in my opinion, it is very important to consistently visualize the data along the manuscript, for clarity and easier reader interpretation.
9. Line #155-156: "We found that the pattern of Bortezomib Signatures corresponded to the cell identity plate layout", the word "not" is missing before "corresponded".
10. Additional details on the processing steps in the analysis pipeline in the Methods will be highly appreciated.

Referees cross-commenting

My main critic is regarding "over selling" a weak discriminative signal. Specifically, I am not convinced that the major claims regarding predicting sensitivity and specificity at the single cell types scales are supported by the data. Since reviewer #2 and #3 did not raise this concern I think it is worth discussion here.

Once these statements are tuned down - I think no significant additional work is needed to make the point that they can measure a discriminative signal. If they want to make these claims, perhaps they'd like to collect more data to gain statistical power (but I am not optimistic this will work at the single cell level).

Personally, I was happy with the authors' choice of cell lines not included in the training dataset. I am not convinced that additional cell lines + validations are necessary for making the point of a proof of principle.

Significance

Cell Painting was applied to many applications, but as far as I am aware this is the first attempt for an image-based phenotypic characterization of drug resistance. While the authors established that this approach can measure, to some extent, bortezomib-sensitivity, at the current state of the results, I am not convinced that cell painting can be practically used to assess bortezomib-sensitivity of a single cell line. However, this does not imply that the same approach can not achieve the goal, perhaps by using other cell painting markers for bortezomib-sensitivity, or with the same markers to assess sensitivity of different drugs. The cell painting + analysis approaches are not new and the clinical impact is questionable, but the technical aspects (data, analysis) are exceptional and the concept may hold as I described above.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity):

Summary: Forer and Otsuka provide first-rate evidence for tethers fixed in place between separating anaphase chromosomes using electron tomography. The authors traced the anaphase movement of a number of living cells before fixation for examination using electron tomography. The manuscript is clearly written and provides an excellent introduction and discussion of the known literature. The reader will have an excellent background to see the importance of this work.

Major comments:<br /> - Are the claims and the conclusions supported by the data or do they require additional experiments or analyses to support them?

No further experiments are needed. The data are very supportive, and extremely clear.<br /> - Are the data and the methods presented in such a way that they can be reproduced? Yes.<br /> - Are the experiments adequately replicated and statistical analysis adequate? Yes.

Minor comments:<br /> - Are prior studies referenced appropriately? Yes.<br /> - Are the text and figures clear and accurate? Absulotely.<br /> - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

The authors are to congratulated on their major contribution to this study on tethers between separated daughter chromosomes. It is a tpur deforce to go from the living cells to fixing and identifying the same separated chromosomes using electron tomography to see the ultrastructure of the fibers seen fir.

Referees cross-commenting<br /> Thank you reviewer #2. The manuscript should be published. It is an excellent contribution.

We thank the reviewer for the appreciation of the clarity and quality of our work.

Reviewer #1 (Significance):

Provide contextual information to readers (editors and researchers) about the novelty of the study, its value for the field and the communities that might be interested.

This manuscript is the first to use electron tomography to identify the tethers between separated anaphase chromosomes. Forer and the laetMichael Berns and their co-authors have published a number of papers using phase microscopy and lasers to report on the physical nature and elastic properties of these fibres in the past. Forer and Otsuka have presented first-rate evidence for the reality of these structures using electron tomography. This manuscript should highlighted in the published journal.<br /> The chemical identity of these fibers as the authors state is unclear.

The following aspects are important:

• Audience: describe the type of audience ("specialized", "broad", "basic research", "translational/clinical", etc...) that will be interested or influenced by this research; how will this research be used by others; will it be of interest beyond the specific field?

This exciting contribution will be read by anyone interested in mitosis. It will be of interest to all Cell Biologists because of the careful manner in which the living cells were studied before they were fixed for examination using electron tomography. The readers will be dreaming how they can use this process on their Cell Biology problems._

• Please define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

I am a cell Biologist who has made contributions, both in light microscopy and in transmission microscopy on diving cells, both in tissue culture and in situ in aviav and zebrafish embryos.

We thank the reviewer for appreciating the significance of our work.

Reviewer #2 (Evidence, reproducibility and clarity):

In this paper, the authors use light microscopy and electron tomography to study anaphase chromosomes in crane fly spermatocytes. They find that there are two "tether" structures that connect telomeres of sister chromatids. One tether is thicker (denser) and extends between sister chromatids during early but not late anaphase, whereas a second, less-dense tether maintains contact with both sister chromatids in all examined stages of anaphase. The paper makes arguments as to what the tethers could or could not be. Specifically, they are too numerous to be ultrafine DNA bridges seen in various normal or abnormal segregation events and they also do not affect anaphase chromosome motion the same way ultrafine DNA bridges do.

Major comments:<br /> The major claim that there are tethers that connect sister chromatids in anaphase is supported by the data. Moreover, the data resolves two types of tethers on the basis of their density. While it is unclear what the composition of the tethers are, the paper makes a convincing case that they cannot be the DNA ultrafine bridges seen in other studies. The discussion has sufficient caveats that most readers will see that more work is needed to identify the composition of the two tethers. In my opinion, no further experiments are needed to support the modest claims of this paper. Therefore, I only have minor comments that may hopefully improve the paper's clarity.

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

Minor comments:<br /> It was argued that the tethers reported here were also seen in other species and cellular contexts, where the imaging work was done with projection EM imaging. Presumably, what is new here is the usage of electron tomography. It would help readers if the authors explained why the electron tomography done here was essential to arrive at key conclusions.

Thank you for the useful comment. We have added the explanation of why electron tomography was critical to visualise small tether structures to the last paragraph of the Discussion on page 7.

p.3 mitochondria appeared to be fixed properly ... (e.g., Figs. 1C, 2B) - I don't see any mitochondria in any figures. Perhaps this observation should be noted as "not shown"?

We thank the reviewer for pointing this out. We have added an electron micrograph of mitochondria to the Supplementary Figure 1.

p.3 The images shown in Figs. 1, 2, 4 - The figures should be called out in the order; in this case, Fig 3 has not been called out yet.

We have corrected the order of the figures.

p.4 we did not find any other connecting structures - Because the sample was processed by traditional EM methods, it's safer to add a caveat that other connecting structures could be missed if they were disrupted by sample prep or if they did not pick up stain as well as the two structures presented in this paper.

We have clarified that our sample was chemically fixed in the first paragraph of the Discussion on page 4. Because the details of how our samples were prepared are described in the Method section, we did not add further details to this paragraph.

p.7 we expect such structures to be commonly seen in other cell types as well if they are examined carefully - Instead of saying that examinations should be done "carefully", it would be more helpful to specify how other cell types should be examined. This work shows that the bridges can be found if the cells are either sectioned parallel to the spindle axis or if a sufficiently large volume is sampled.

We have now clarified that 3D electron microscopy techniques such as electron tomography are critical to visualise small tether structures in the last paragraph of the Discussion on page 7.

Please use consistent spelling/hyphenation of ultrafine/ultra-fine and word choice (strands vs. bridges).

Referees cross-commenting<br /> I agree with my co-reviewers's comments and have no further suggestions._

Reviewer #2 (Significance):

This may be the first use of electron tomography to study the structural details of tethers that connect chromosomes in anaphase cells. The data is of sufficient quality to reveal differences in density. Namely, one class of tether appears to be an extension of the chromosome while the other class is composed of thin filaments. This study is novel in that it characterizes a mitosis-associated complex that is poorly studied compared to the microtubule-based spindle apparatus and the kinetochore. Hopefully, the tethers will draw more attention and further characterization by methods like super-resolution microscopy and cryo-electron microscopy. My expertise is in chromatin, mitotic machines, and cryo-electron tomography.

We thank the reviewer for appreciating the novelty and the impact of our work.

Reviewer #3 (Evidence, reproducibility and clarity):

Summary:

Tethers between telomeres of chromosomes in anaphase were inferred from earlier studies of laser microbeam cutting experiments. The current paper presents images from electron tomography of crane fly spermatocytes that substantiates the earlier inference. The authors deduce that the darker filaments and the lighter filaments that they visualize may be the structural tethers at telomeres.

Major comments:

The experiments are carefully done, and the conclusions are appropriately worded to qualify any caveats. This short communication is well-presented, and I have only a few comments._

We thank the reviewer for appreciating the clarity and quality of our work.

The authors should expand their list of references on bridges to include those listed by Warecki et al (Curr Biol 33:1-17, 2023; refs 15-26, etc).

We do not think it is necessary to expand the list of references for ultra-fine DNA bridges. In the article we submitted, we discussed the Warecki at al article in the penultimate paragraph of the Discussion; we concluded that the bridges that Warecki at al described are different from ours in having so few per cell that they couldn’t be tethers, and further that there was no evidence that those bridges were elastic. For those reasons, we do not find discussion of those proteins relevant to tethers, any more than would listing all the proteins associated with ultra-fine DNA bridges be relevant to the elastic tethers.

In the Discussion, we discussed data suggesting that a known elastic protein titin was present; that is as far as we wanted to go on speculation of what the elastic component of tethers might be.

The authors present arguments that the tethers are not the DNA bridges observed by others. However, they should try to address this experimentally by treatment of their preparations with DNase to see if the thick and/or thin filaments disappear.

While we agree that it would be important to identify the components of the tethers, we are concerned that those experiments are beyond the scope of this manuscript. Nevertheless, we appreciate the constructive suggestion for the future research direction.

Moreover, they should discuss in more detail the possible functions of (DNA) bridges, including the recent model from Bill Sullivan's lab (Warecki et al, Curr Biol, 2023) that they help to retain fragments of broken chromosomes. In addition, the authors should summarize the various proteins that may be associated with the bridges (as enumerated in the Warecki et al 2023 paper).

As we describe above, we concluded that the bridges Warecki at al described are different from the tethers that we report in our manuscript. Therefore, we do not think it is necessary to expand the discussion on the proteins and functions associated with ultra-fine DNA.

The authors could add a sentence to the Results or Discussion of whether the thicker tethers might become stretched as anaphase progresses to become the thinner tethers (Fig. 4G).

We thank the reviewer for this suggestion. We actually mentioned this possibility in the third paragraph of our Discussion on page 7.

The authors may want to add a few sentences to the Discussion about the "chromosomal bouquet" stage of leptotene of meiosis prophase I where the telomeres of chromosomes seem pulled together and associate with the nuclear envelope --- they could speculate if this might also be due to the tethers that they describe in spermatocytes.

This is a very interesting possibility. While we would refrain from adding this speculation to our manuscript as it is beyond the scope of the main points, it is certainly an interesting avenue of future research.

Minor comments:

A few additional comments are as follows:

p. 2 last sentence of first paragraph -modify the wording about "no structural evidence that identifies physical connections between separating telomeres", since there is some information from genetic and cell biology light microscopy experiments. Perhaps simply change "structural" to "ultrastructural".

We have changed the wording as the reviewer recommended

p. 6, 5th line of second paragraph - change "ribosome DNA" to "ribosomal DNA"

We have corrected it.

Figure 1D - add the chromosome to the right of the schematic model (as suggested by Fig. 1B).

We are sorry for the confusion. In Figure 1D, the left half of the tethers are 3D modelled and shown. We have clarified this point by modifying the legend of Figure 1D

p. 17 (Methods), line 10 of first paragraph - state if this is light or heavy Halocarbon oil (give details).

It is a mixture of heavy and light Halocarbon oil. We have clarified it on page 17.

p. 17 (Methods), line 12 of first paragraph- state the concentration for fibrinogen and for thrombin.

As we wrote in the original manuscript, the procedures are described in detail in our previous publication (Forer A. & Pickett-Heaps J. (2005) Fibrin clots keep non-adhering living cells in place on glass for perfusion or fixation. Cell Biology International 29: 721–730). Nonetheless, to clarify this point, we have modified the text on page 17.

p. 17 (Methods), line 4 of second paragraph - is there any data to show that the filaments (tethers) occur if there is no cold shock?

Yes, we do see similar filamentous structures in the sample without cold shock. For your information, we show one of the electron micrographs below. In our manuscript, we show the data from the samples prepared with cold shock, because it better visualizes the filamentous structures. We now show these electron micrographs in the Supplementary Figure 2.

Referees cross-commenting<br /> I concur with Reviewers #1 and #2 that this is a fine paper that should be published. My detailed comments submitted with my review are simply meant as revisions to further strengthen this paper.

We thank the reviewer for supporting the publication of our manuscript.

Reviewer #3 (Significance):

Strengths: This is an important conceptual advance and the carefully done ultrastructural imaging provides the foundation for future studies that could delve into the molecular composition and functional significance of the tethers at telomeres of anaphase chromosomes seen here by 3D electron microscopy.

Limitations: the molecular composition and functional roles are not yet known for the tethers seen here by 3D electron microscopy, but to do so would involve an entire new program of experimentation.

Advances: there have only been two earlier ultrastructural papers on tethers at telomeres, and the tethers were peripheral to the main focus of those papers. Thus, the current paper extends our ultrastructural information about tethers.

Audience: this work is of importance for scientists who study the mechanics of chromosome movement on spindles, including regulation to combat aneuploidy. This work will also be important for a broader audience to inform them about transmission of the hereditary information to daughter cells._

We thank the reviewer for appreciating the significance and the impact of our work.

With 126 published definitions of "communication," touching on other forms of communication other than merely speaking in a speech class is vital. With humans having some of the widest range of speech (i.e. various languages) that often times are not seamless, other universal abstract symbolism in conjunction with spoken communication is necessary to bridge the gap. Even our written language and assigned meaning to certain methodic squiggles displayed on paper varies widely, as well as other less obvious ways of communicating like gestures and body languages that could seem inconsequential to one may be monumentally offensive to others, the intricate woven methods to communicate within the complexities we as a human species have created is a fascinating study beyond merely standing in front of a group of peers and talking at them for 3-5 minutes about a chosen topic.

Everyone on this planet has intrapersonal communication. I talk to myself every day, and I have conversations with myself on what I'm going to do or what I need to do. Some people talk to themselves to calm down, or they journal to ease their minds. When something surprising happens people usually react somehow in their head, basically when anything happens people react to themselves. Just as the text states, "We also use intrapersonal communication or “self-talk” to let off steam, process emotions, think through something, or rehearse what we plan to say or do in the future." Intrapersonal communication happens almost every second throughout one person's day.

Making things messy from the start as advice for getting started.

I've seen this before in other settings, particularly in starting new notebooks. Some have suggested scrawling on the first page to get over the idea of perfection in a virgin notebook. I also think I've seen Ton Ziijlstra mention that his dad would ding every new car to get over the new feeling and fear of damaging it. Get the damage out of the way so you can just move on.

The fact that a notebook is damaged, messy, or used for the smallest things may be one of the benefits of a wastebook. It averts the internal need some may find for perfection in their nice notebooks or work materials.

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

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity):

The manuscript by Rigger and Brenner details the role of vimentin network, in advancing OA pathogenesis by exacerbating premature senescence. The data is well presented and the study of interest, in that there is little known about vimentin in cartilage biology.<br /> The authors used OA derived cartilage explants and chondrocytes cultures, were graded for severity and compared accordingly. Figure 1 shows that markers of senescence are increased with structural damage, which is well established and consistant with the literature. Using a DOX model the authors induce premature senescence and exhibit a disrupted vimentin network. However, upon KD of CDKN2A, a marker of senescence, but did not observe complete reversal of CSV presentation.<br /> Next the authors show in figure 4 and 5, that the reduction or dismemberment of vimentin structures are linked to senescence and may act as contributing factors.<br /> Figures 6 and 7 then go on to show that upon advanced passage chondrocytes lose their vimentin network, and tend to senesce and mineralize.

Reviewer #1 (Significance):

Strength:<br /> This is a very novel study showing a link between vimentin and senescence in chondrocytes. The data are in line with other data. The work is clearly written structured and well displayed.

Author´s response:<br /> We thank reviewer #1 for their interest in our work and their overall positive report.

Suggestions for improvement:

While the study is very thorough ought in describing the markers of senescence and vimentin network, it lacks insight regarding mechanism which isn't completely deciphered. Are there links to key transcription factors?

Author´s response:<br /> The transcriptional regulation of vimentin in human cells is very complex. The VIM promoter region comprises multiple elements, such as a NF-kB- binding site, a PEA3-binding site and two AP1-binding sites (Zhang et al., 2003). Moreover, it was recently demonstrated that redox signaling is involved in vimentin expression at the wound margin after tissue injury in zebra fish (LeBert et al., 2018). However, it has also been reported that IL-1ß stimulation results in reduced gene expression of vimentin via p38-signalling in cartilage degeneration and OA progression (see manuscript REF. 36,37).

In our study, we observed that enhanced CSV levels are associated with a decreased vimentin gene expression, indicating a lower stability of the mRNA or decreased transcription of VIM in senescent chondrocytes (maybe due to enhanced p38-signalling as mentioned above). Since the transcriptome in senescent cells is radically changed, this question cannot be answered easily.

In future studies, we will rather try to clarify the underlying mechanism of vimentin externalization. There are still many questions to be answered: is the CSV anchored in the cell membrane (which anchor protein?) and is there still a connection to the intracellular vimentin network? Which proteins are involved in the externalization process: maybe comparable to phosphatidylserine exposure, mediated by flippases, scramblases, and lipid transfer proteins or rather by vesicles?

Literature mentioned above (not included in manuscript):

LeBert et al., 2018: Damage-induced reactive oxygen species regulate vimentin and dynamic collagen-based projections to mediate wound repair. DOI: 10.7554/eLife.30703

Zhang et al., 2003: ZBP-89 represses vimentin gene transcription by interacting with the transcriptional activator, Sp1. DOI: 10.1093/nar/gkg380

It is also unclear if disruption of the network is more detrimental than KD in promoting senescence.

Author´s response:<br /> KD of Vimentin led to a gradually decrease of intracellular Vimentin content and consequent stress. The cells were analyzed 7 days after induction of the KD and exhibited a stable senescent phenotype, comparable to Doxorubicin-treated chondrocytes (treated with very low concentrations over several days to produce only mild but ongoing stress). These models might reflect the pathophysiologic situation: We think that cellular stress due to mechanical impact and subsequent oxidative stress/ low-grade inflammation might lead to a gradual disruption or re-organization of the vimentin network, which is accompanied by decreased vimentin gene expression.

In case of the disruption of the vimentin network by Simvastatin, the stress response was very intense and rapid (24 h), and was only conducted as a proof-of-principle experiment. Despite the upregulation of some senescence-associated markers, we don`t think that permanent Simvastatin treatment would be suitable to obtain a stable senescent phenotype, but rather expect the cells to die due to excessive stress.

It would have been good to include models OA murine models to understand these processes better, and make a stronger physiological connection with OA of the joint.

Author´s response:<br /> The CSV antibody is only suitable for human cells and cannot be used for immunohistochemistry. Therefore, all previous reports of CSV are based on human (isolated) cells. At the current time point, it would not be possible to stain CSV in joints of mice after induction of PTOA due to the methodological limitations. We actually tested the CSV-antibody in isolated lapine chondrocytes and found a high percentage of CSV-positive cells, even at low passages. Although stress increased the amount of CSV-positive lapine cells, we did not consider the results as reliable due to the high percentage in un-stressed cells, which might result from unspecific antibody binding.

Overall, we think that the usage of clinical OA samples is convincing and reflect the pathophysiologic situation in the human OA joint.

Reviewer #2 (Evidence, reproducibility and clarity):

The manuscript provides solid evidence for an association between cell surface vimentin (CSV) and chondrocyte senescence. Human cartilage and cultured chondrocytes are used with a wide range of approaches to provoke senescence: natural osteoarthritis, traumatic loading ex vivo, doxorubicin to cells in monolayer, vimentin siRNA, and simvastatin. In contrast, relatively little was done to try and interrupt or reverse the role of CSV in senescence, with CDKN2A siRNA representing one attempted intervention. The manuscript is well written and the data are presented in a logical and clear manner, with a high likelihood of being reproduced in subsequent studies.

Author´s response:<br /> We thank reviewer #2 for their interest in our work and their mainly positive report.<br /> Regarding their comment on our attempts to reverse CSV on senescent chondrocytes, we would like to add the following: Reversal of cellular senescence is a very ambitious challenge. But in fact, we are currently preparing a manuscript in which we characterize an appropriate senolytic strategy to “rejuvenate” human chondrocytes and plan to use this approach to reduce the amount of senescent and thus CSV-positive cells in future experiments.

_Major comments:

In the doxorubicin experiments, the senescent cells show a spread morphology as expected. Given the importance of vimentin in cell spreading (as the authors own data show), the possibility that spread morphology itself (and not senescence) leads to CSV should probably be examined. This could perhaps be achieved by plating with different concentrations of fibronectin or other matrix proteins that produce a spread morphology to a degree that matches the doxo. If the cells remain spread for ~10 days but don't become senescent and don't have CSV, this would provide further support for a direct relationship.

Author´s response:<br /> We agree that cell spreading is associated with various cellular processes (for example by the YAP signaling pathway). Moreover, we would like to thank the reviewer for the proposed experiment.

Seeding of cartilage cells on fibronectin coated plates is a commonly used procedure to isolate chondrogenic stem progenitor cells, due to their higher affinity to fibronectin. The cells are usually cultured for several days on the coated plates and do not exhibit a flattened, senescent-like phenotype (as we observe for Doxorubicin-treated cells), but an elongated, fibroblast-/ stem cell-like shape. Our results (Figure 6E) demonstrate that CSPC have no increased CSV levels, despite their elongated (not flat) morphology.

There are some findings supporting the assumption that CSV leads to enhanced cell adhesion, but not that adhesion or cell spreading promotes CSV: we included experiments with HeLa (low CSV levels) and SaOS-2 (high CSV levels), which demonstrated that high CSV levels are associated with increased plastic adhesion (Figure S5). In line with this, we demonstrated that higher CSV levels on chondrocytes were associated with enhanced fibronectin and vitronectin binding, which might explain increased plastic adhesion. Moreover, Simvastatin stimulation and subsequent cellular stress by Vimentin disruption resulted in enhanced CSV but did not lead to cell spreading (Actin not affected, cells rather elongated, not flattened).

Minor comments:

The CSV antibody and staining method appeared to have generated some signal from debris, which makes it challenging to assess the localization of true staining. Presumably the true staining would be present only on the cell surface. While the widefiled view is appreciated, perhaps insets with a higher magnification would clarify.

Author´s response:<br /> In Figure 2h and Figure 2i, we provide insets of the IF-staining and an exemplary image made by scanning electron microscopy (SEM). CSV is not localized on debris – Figure 2h, actually represents the cell surface. The magnified, Doxo-treated cell is highly senescent and thus flattened. The uneven (rather spotted) staining pattern of CSV and the unusual shape of the cell might suggest that this is debris, not the cell membrane.

For figure 1k, it is a bit surprising that CDKN2A would peak so early after injury and then drop off. Most studies in other systems show a gradual increase in CDKN2A levels with persistent stress as opposed to a rapid increase in response to acute stress. Could the drop-off be due to preferential death of these cells? The CSV % in 1m was taken from 7d after trauma (plus 7 days in monolayer it appears). Further discussion on the timing of traditional senescence markers as compared to the emergence of CSV would be useful.

Author´s response:

We would like to thank the reviewer for this comment. That CDKN1A was induced by mechanical trauma without significant decrease at the later time points was in line with the P53 expression, which we detected via immunohistochemistry (IHC; positive staining of chondrocyte nuclei in cartilage). P53 and P21 are regarded as interconnected senescence markers. Interestingly, P53 is not regulated on gene expression level upon cartilage trauma or Doxorubicine stimulation – but there is a significant increase in P53 nuclear translocation.

Although such a discrepancy between gene expression and protein activity has not been reported in case of P16 or P21, we plan to investigate the dynamics of these cell cycle regulators and its connection to CSV after cartilage trauma in more detail in future studies.

We included the following statement in the discussion part:

“In the current study, we observed that CSV on chondrocytes was reduced by siRNA-mediated silencing of CDKN2A and increased after Doxo treatment or cartilage trauma. While we confirmed that mRNA levels of both CDKN1A and CDKN2A were significantly enhanced upon injury but exhibited different expression levels over time, we determined CSV-positive cells only at one time point after ex vivo cartilage trauma. Future studies might also consider earlier and later time points after cartilage injury to identify a potential time-dependent peak or decline in CSV-positive chondrocytes. In this way a potential association between CSV and the expression levels of CDKN1A and CDKN2A, which are thought to play differential roles in initiating and maintenance of senescence, respectively [50], might be clarified.”

[50] Stein G, Drullinger L, Soulard A, and Dulić V. Differential Roles for Cyclin-Dependent Kinase Inhibitors p21 and p16 in the Mechanisms of Senescence and Differentiation in Human Fibroblasts. Mol Cell Biol. 1999;19(3): 2109–2117. https://doi.org/10.1128/mcb.19.3.2109.

There is no CSV staining shown for figures 4 and 5. While the quantification of CSV was done by flow cytometry, it would nice confirmation to see the increase in CSV on the surface of cells with either siRNA for vimentin or the simvastatin.

Author´s response:

CSV-IF of simvastatin-treated chondrocytes is provided in Figure 5 (b). We did not perform exemplary staining of CSV after VIM-KD, because the quantification was performed via flow cytometry.

Reviewer #2 (Significance):

The strengths of the study include a rigorous design and the establishment of a potential new cell surface marker of chondrocyte senescence. The main limitation is that the conclusions are largely descriptive in nature.

If CSV is confirmed as a robust marker of senescence, this would be of value to the field. While this marker has been explored previously in other systems, there is value in this manuscript given the wide range of contexts investigated for a cell type in which senescence likely has an important role.

Reviewer #3 (Evidence, reproducibility and clarity):

This study presents a sound piece of science in the puzzle about extracellular vimentin in the differentiation/dedifferentiation of human chondrocytes and senescence and osteoarthritis. Eventhough, no mechanism is elucidated, the results clearly point towards a correlation of the amount of extra cellular vimentin and the level of chondrocyte senescence, and therefore signs of osteoarthritic changes in the cultivated chondrocytes. The methods applied are state-of-the art and provide the means to generate meaningful results in this experimental setting. The paper is concise and clearly written, there are only minor remarks.

Author´s response:

We thank reviewer #3 for their interest in our work and their overall positive report.

Minor comments:

1. The main clue of the paper is extra cellular vinemtin around chondrites in culture, please provide better pictures (1g) to support this. Why is the extra cellular staining seen so broad and not concentrated on the cells surface? The picture chosen imply a huge amount of vimentin to be externilized in disease states. It also indicates that in diseased chondrocytes no intact or semi-intact vimentin network is found intracellular. Please comment.

Author´s response:

In Figure 1g, CSV is located on the cell membrane. The pattern of the staining was surprising to us, as well. CSV was not equally distributed on the membrane, but rather represented an inconsistent pattern. Sometimes the staining was located at the filopodia of the cells, sometimes the whole cell was covered by spots. We also observed this on cancer cells, which was in line with other studies using this antibody. It remains unclear whether the distribution of the CSV has any effect. But we assume that the high abundance in filopodia might be connected with cell adhesion and mobility, which was positively associated with CSV.

Yes, chondrocytes isolated from highly degenerated tissue exhibited higher CSV levels as compared to cells derived from macroscopically intact regions. Although we did not investigate the vimentin network of these cells, our observations in Doxo-treated cells imply, indeed, that intracellular vimentin might be altered in diseased chondrocytes. According to this, Blain et al (Ref. 13) reported that there is a disassembly of the intracellular vimentin network in OA chondrocytes, which can disturb the chondrocyte phenotype and contributes to the development of OA (see discussion).

1. In the doxo experiment no extracellular vimentin is found? Please explain.

Author´s response:

Doxo-treated cells are highly positive for CSV (= extracellular vimentin on membrane). However, the intracellular vimentin is strongly decreased and some cells seem to be negative. We have not clarified the underlying mechanism by now, but it seems that senescence/ disease progression negatively affects the transcription of vimentin and, at the same time, promotes the externalization of the existing intracellular vimentin. Altogether, this might result in a decline in intracellular vimentin.

1. The SEM picture is showing what. IGH? The red dots are colloidal gold particles? In any case the quantity of stain gathered EM level would not correlate to the huge amount seen in LM staining. Please comment.

Author´s response:

For the SEM analysis, a gold particle-coated secondary antibody was used. The positive signal usually appears in white and was subsequently colored via a software. In IF and ICC staining, we had a signal amplification due to the biotin-streptavidin system and the magnification makes, of course, a huge difference.

1. Why the ICC in Fig. 3c? The siRNA is not detected in the KD? A reduction of Vimentin could be shown via WB.

Author´s response:

In Figure 3c, the KD of P16 was confirmed on protein level. In addition to the gene expression analysis, we chose the ICC (IF) to confirm that there is a decline in active (nuclear) CDKN2A. In case of P53, we made the experience that gene expression and the amount of cytoplasmic/ nuclear protein might not be consistent.

In Figure 4, we confirmed the successful KD of vimentin on mRNA and protein level (flow cytometry plus IF). Of course, WB would also be possible, but we decided to use the methods in which the antibody was well established and we wanted to visualize the disturbance of the intracellular vimentin network upon KD.

1. Fig. 4c, why are there no remnants of the vimentin networks seen in the chondrocytes? A Knock-down, not a KO is shown.

Author´s response:

In fact, most of the intracellular vimentin seems to be gone. However, there are some remnants (condensed fibers/ bundles) of the former vimentin network. We applied the VIM-KD over seven days. Usually, a KD experiment is only conducted for 2-3 days. But since we were not sure how stable the vimentin protein would be, we chose seven days. This long-lasting KD might have resulted in a strong decline of the protein. Moreover, the CSV levels on these cells were very high, indicating that existing vimentin was externalized and additionally decreased the amount of intracellular vimentin.

1. Please comment of the concentration of simvastatin, why not nmolar?

Author´s response:

The concentration of Simvastatin was chosen in accordance with Trogden et al. (Ref. 26), who first described the effects of simvastatin on the vimentin network. A lower concentration might have had the advantage, that the effects were less severe, allowing a longer observation time than 24h. However, as a proof-of-principle model to demonstrate the connection between vimentin network collapse ant CSV expression, the concentration worked quite well.

1. CSV+ is misleading in Fig. 6g, it's not an over expression.

Author´s response:

We would like to thank the reviewer for this comment and removed the “+” to make it less misleading.

1. The concept of EMT is debatable, at least in kidney fibrosis, and chondrocytes are not epithelial cells. Please add a more critical discussion point.

Author´s response: The authors agree with the reviewer’s argument that chondrocytes are no epithelial cells ant that the term EMT doesn’t seem to be appropriate. However, this is one leading hypothesis proposed by the working group of Prof. Mayán, who described CX43 and other EMT-markers on/ in senescent chondrocytes (see reference 31; more recently: Cell Death Dis. 2022;13(8):681. doi: 10.1038/s41419-022-05089-w).

We added the following passage in the discussion part to indicate that this hypothesis is a controversial concept:

“Nevertheless, the hypothesis that chondrocytes might undergo an EMT-like process remains controversially discussed, because chondrocytes are mesenchymal and not epithelial cells. In a recent review, Gems and Kern propose to consider senescent chondrocytes as activated and hyperfunctional remodeling cells occurring during OA progression [49]. Accordingly, chondrosenescence might represent an unsuccessful attempt of tissue repair. They further suppose that the senescent or activated chondrocytes are associated with a hypertrophic, bone-forming phenotype, following the process of bone development rather than hyaline cartilage formation. In line with this, we observed that CSV was associated with enhanced osteogenic capacities and a decline in chondrogenic properties.”

[49] Gems and Kern, 2022): Geroscience. 2022;44(5):2461-2469. doi: 10.1007/s11357-022-00652-x.

Reviewer #3 (Significance):

The manuscript provides novel insight in the role of intermediary filaments, i.e. vimentin, on chondrocyte senescence and osteoarthritic changes in vitro. It's strength is a thorough elucidation of the connection with a wealth of experimental data, a weakness is the missing elucidation, or first experiments in the direction, of the cell biological mechanism.<br /> It is well suited for a broad audience, because it deals with fundamental cell biological phenomena, definitely it's important for the OA /chondrocyte biology community.

Author Response

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

Reviewer #1 (Recommendations For The Authors):

• Introduction: "In plants, IP7 and IP8 decrease upon Pi starvation and mutants lacking either of the enzymes necessary for their synthesis induce the phosphate starvation response, leaving it open whether IP7 , IP8 , or both, control the Pi starvation program (10, 13, 14)" In plants, ITPK enzymes catalyze the formation of 5-InsP7 from InP6 https://pubmed.ncbi.nlm.nih.gov/34274522/ and VIH enzymes the formation of 1,5-InsP8 from 5-InsP7 https://pubmed.ncbi.nlm.nih.gov/25901085/ . Loss-of-function of both ITPK1 https://pubmed.ncbi.nlm.nih.gov/34274522/ and of VIH1/2 https://pubmed.ncbi.nlm.nih.gov/31436531/ https://pubmed.ncbi.nlm.nih.gov/31419530/ results in constitutive Pi starvation responses. vih1/vih2 mutants lack 1,5-InsP8 and hyperaccumulate 5-InsP7 https://pubmed.ncbi.nlm.nih.gov/31436531/ and act directly upstream of the transcription factors PHR1/PHL1 https://pubmed.ncbi.nlm.nih.gov/31436531/ https://pubmed.ncbi.nlm.nih.gov/33452263/ https://pubmed.ncbi.nlm.nih.gov/34857773/ , the case for 1,5-InsP8 is settled in plants. I would suggest revising this statement and citing all relevant literature.

We don't see the case for 1,5-IP8 as settled in plants, and none of the papers mentioned above draws this strong conclusion. This may be due to several limitations in the available data. The mentioned studies do not allow to differentiate the effects of 1-IP7 and 1,5-IP8 and, where binding or competition experiments have been performed, e.g. on the transcription factors, the differences in the Kd values for IP7 and IP8 were minor. Furthermore,1,5-IP8 levels and Pi starvation response do not always correlate. IPTK1 mutants, for example, show Pi overaccumulation, and low 5-IP7, but normal 1,5-IP8 (Riemer et al., 2021). Finally, plants are complex organisms with multiple tissue types that serve for accumulating, exporting, transporting or finally consuming Pi. Therefore, correlating inositol pyrophosphate levels from whole-plant extracts with a Pi starvation response is problematic, except if these data could both be obtained from the same cell types or at least tissues.

The comment of the reviewer made us recognize that the complex situation in plants deserves a more detailed coverage and we have therefore adjusted the introduction accordingly.

Results: "We determined the corresponding lysines in Pho81 (Fig. S3), created a point mutation in the genomic PHO81 locus that substitutes one of them, K154, by alanine, and investigated the impact on the PHO pathway."

In my opinion, it would be important to test here in a quantitative in vitro binding assay if (i) the SPX domain of Pho81 can bind PP-InsPs including 1,5-InsP8, (ii) if the dissociation constant is in agreement with the cellular levels of 1,5-InsP8 in yeast (compare Fig. 2) and (iii) if the K154A mutation blocks or reduces the binding of 1,5-InsP8. Without such experimentation, I find the statement "this result underlines the efficiency of the K154A substitution in preventing PP-IP binding to the Pho81 SPX domain." to be overly speculative, as no binding experiment has been conducted.

We agree with the comment of the reviewer concerning the overstatement in the phrase. It has been deleted.

As mentioned already in our previous work (Wild et al., 2016), Pho81SPX counts among the SPX domains that we could not express recombinantly. Likewise, full-length Pho81, which would be the relevant object for correlating in vitro binding studies with the cellular concentrations, has not been accessible. Expression in yeast did not provide sufficient material for ITC or other quantitative techniques. Therefore, we refrained from pursuing binding studies. Nevertheless, given the high conservation of the positively charged patch on SPX domains and the fact that, in every case where it has been tested so far, SPX domains showed inositol polyphosphate binding activity, we find it a conservative assumption that the Pho81SPX binds them as well. This is supported by the effects of the binding site mutant, which mimics the effect of ablating IP8 synthesis.

Results: "Inositol pyrophosphate binding to the SPX domain labilizes the Pho81-Pho80 interaction." Again, in the absence of any protein - protein interaction assay I find this statement not to be supported by the experiments outlined in the manuscript. The best way to address this point would be to perform either co-IP or in vitro pull-down experiments between Pho81-SPX and Pho81-85, in the pre- and absence of 1,5-InsP8 and/or using the Pho81 point-mutants described in the text.

Since Pho81 could not be produced recombinantly, neither by us nor by others who worked on this protein previously, quantitative in vitro binding assays are not accessible for now. A simple IP suffers from the problem that Pho81 interacts with Pho85-Pho80 not only through the SPX domain but also through the minimum domain. The latter interaction may be constitutive. Since the main point of the manuscript is not to dissect the exact mechanisms of Pho85-Pho80 regulations, but only to address the point why the postulated inactivation of this kinase by an 1-IP7/minimum domain complex makes no sense, we prefer not to show a profound (and more complex) analysis of how the different Pho81 domains contribute to binding.

To test the potential of the SPX domain for binding Pho85/Pho80 in vivo, we have created a GFP-fusion of the SPX domain of Pho81. This fusion protein localizes mainly to the cytosol when cells are on high-Pi. Upon Pi starvation, it concentrates in the nucleus. This concentration is not observed in pho80 mutant background (New Fig. S7).

In line with this, I would suggest to move the molecular modelling/docking studies from the discussion into the results section and to use these models to design some interface mutations that could be tested in coIP and/or pull-down assays. Alternatively, the authors may choose to omit the discussion section starting with: "Even though the minimum domain is unlikely to function as a receptor for PP-IPs this does not ... and ending with . In sum, multiple lines of evidence support the view that the SPX domain exerts dominant, 1,5-IP8 mediated control over Pho81 activity in response to Pi availability."

We have now moved the modelling data to the Results section. The structure prediction of the interface is experimentally validated. Data on the effect of interface substitutions are already published, although these substitutions had not been recognized as affecting a common interface at the time. Substituting the interface residues either on the side of Pho80 or of Pho81 constitutively activates Pho85-Pho80 kinase and destabilizes its interaction with Pho81. This was shown by Co-IP experiments from cell extracts by Huang et al. We mention the respective substitutions in the manuscript and cite the paper in which their effect on PHO pathway activation had been described.

Reviewer #2 (Recommendations For The Authors):

Some points need additional attention by the authors:

• In general, it would be helpful to introduce abbreviations more thoroughly (certain enzyme names, PA, MD, ...)

We paid more attention to this.

• Also in general, the authors may want to think about the nomenclature of inositol pyrophosphates. Given the expansion of PP-IPs that are being detected in different organisms these days it may be a good time to convert to a more precise nomenclature, i.e. 5PP-IP5 instead of 5-IP7; and 1,5(PP)2-IP4, instead of 1,5-IP8. The latter could just be stated once, and then be abbreviated as IP8.

To our understanding the field has not yet come up with a unified nomenclature. Therefore, we prefer to stick with the more practical nomenclature that we have chosen, which also corresponds to what is commonly used in presentations and discussions among colleagues. We have now introduced a sentence making the link to the nomenclature that the reviewer has proposed.

• p. 1, Abstract: "negative bioenergetic impacts" - the phrasing seems really vague

Agreed, but we find it difficult to be more explicit and precise in the abstract while remaining concise and not distracting from the main message. This aspect is better explained in the introduction.

• p. 3, Significance statement: "... unified model across all eukaryotic kingdoms" While the intended meaning of this wording is better explained in the text later, the phrasing here suggests a more all-encompassing study at hand, instead of a conclusion that fits more closely with established reports from other organisms. Please rephrase.

We have adapted the phrase to avoid this impression.

• p. 4: "IPTKs" - are the ITPKs meant here?

Yes, that was a typo.

• p. 7, the introduction ends abruptly and could use a concluding sentence.

Done

• p.7, "enzymes diphosphorylation either the..."; I understand what the authors are trying to say with diphosphorylating, but the enzymes are phosphorylating a phosphorylated substrate.

Yes. We changed the phrase to "....adding phosphate groups at the 1- or 5-positions....".

• p. 7, subtitle "...concentrations and kinetics of..."; kinetics of what? Synthesis/turnover?

We corrected this subtitle

• p. 8, with regards to the recovery experiment: Was this recovery determined elsewhere (please cite)? Otherwise it would be beneficial to include an extra figure to illustrate these recoveries in the supplementary information. And do the authors suspect some hydrolysis of IP8 given the lower recovery?

We have now added the experiment testing recovery of IPPs as the new Fig. S1.

• p. 9: It is appreciated that the authors point out the concentration of IP6 in S. cerevisiae. I found that concentration rather low, and the authors could highlight this a bit more, given their ability to carry our absolute quantification.

This was a leftover from a previous version of the paper. Since the paper does not treat IP6 or lower inositol polyphosphates, we have deleted this phrase.

• p. 9, Fig 2: The exponential decay of 5-IP7 is very nicely shown in Figure 2c. But one of the most important discussion points is IP8 being the key controller of the PHO pathway - it would therefore be beneficial for the argument to also show the same kind of graph for IP8 and if possible, fit a function to the data points to better quantify and compare the decay processes (e.g. via "half-life time" of PP-IPs during starvation, in addition to the suggested "critical concentration" which was only discussed for 5-IP7 thus far).

Kinetic resolution is an issue here. The approach shown in Figs. 2 and 5 is not apt to determine a critical concentration of IP8 because the decline upon transfer to starvation conditions is too fast and difficult to relate to the equally rapid induction of the PHO pathway. We shall address this point in a more appropriate setup in a future study.

• p.9, Fig 2a: Where does the 5-IP7 come from in the kcs1Δ strain? In the text the authors state that 5-IP7 in kcs1Δ was not detected, but the figure suggests otherwise. Please explain.

Currently, we do not know where these residual signals stem from. One possibility is that they represent other isomers that exist in minor concentrations and that are not resolved from 5-IP7 in CE. We added a sentence to the figure legend to indicate this.

• p. 10: "IP8 was undetectable in kcs1Δ and decreased by 75% in vip1Δ. kcs1Δ mutants also showed a 2 to 3-fold decrease in 1-IP7, suggesting that the synthesisof 1-IP7 depends on 5-IP7. This might be explained by assuming that a significant source of 1-IP7 is synthesis of 1,5-IP8 through successive action of Kcs1 and Vip1, followed by dephosphorylation to 1-IP7." - Please specify this statement. Do the authors mean that 1,5-IP8 is only produced transiently below the detection capabilities of the method but that there still is a (reduced) flux from 5-IP7 to 1,5-IP8 to 1-IP7? Otherwise it would seem paradoxical to have a dependency on a non-existing metabolite in that cell line.

This was not clearly expressed. The revised version now says: " ... a 2 to 3-fold decrease in 1-IP7, suggesting that the synthesis of 1-IP7 depends on 5-IP7. This might be explained by assuming that, in the wildtype, most 1-IP7 stems from the conversion of 5-IP7 to 1,5-IP8, followed by dephosphorylation of 1,5-IP8 to 1-IP7.". We hope that this clarifies the matter.

• p. 10: "pulse-labeling approaches are not available for PP-IPs." While this statement is correct, a recent paper co-authored by Qui and Jessen showed nice pulse-labeling data for the lower Ips and could be cited here (PMID: 36589890)

Yes, indeed, we should have been more precise here. What we wanted to express was that rapid pulse-labeling methods for following phosphate group turnover were lacking, with a temporal resolution of minutes rather than hours. Existing pulse labeling approaches, including the study mentioned by the reviewer, do not provide that. We have changed the phrase accordingly.

• p. 10: continuation of caption of Fig 2: "were extracted [and] analyzed"

Corrected. Thank you.

• p. 12: How is 1-IP7 made in the vip1 kcs1 double mutant?

As explained above, we suspect that these may be side products of IPMKs, which accumulate in the absence of vip1 phosphatase.

• p. 13, caption to Figure 3: "XXX cells were analyzed" please replace the place holder XXX.

Done. Thank you.

• p. 13, Fig 3B, C, D and p. 50, Fig. S4: On screen the contrast between the different shades of grey of the bars are just visible enough, but not on paper, I suggest using a higher contrast/ different colouring scheme.

We enhanced the contrast.

• p. 24, 25, Fig 7.: I could not really appreciate the AlphaFold part, and found it unnecessary. No docking or molecular dynamics simulations were carried out here, and it was not clear to me what information should be gleaned from this part.

Following this comment, we have modified the respective part of the text. This part refers to a publication from the O'Shea lab (Nat. Chem Biol. 4,25) proposing the model that 1-IP7 and the Pho81 minimum domain bind competitively to the active site of Pho85 to inhibit its kinase activity. Modeling of complexes between Pho81, Pho80 and Pho85, which we present in the manuscript, rather suggests binding of the minimum domain to a groove in Pho80. This is important because it provides a viable alternative model for the action of the minimum domain. It suggests the minimum domain as a constitutive linker that attaches Pho80 to Pho85. Importantly, this model accounts perfectly for the results of previous random mutagenesis studies on Pho80 and on the minimum domain, which had independently identified both the Pho80 groove and the minimum domain residues that bind it in the prediction as critical residues for inhibition of Pho85, and for integrity of the Pho85/Pho80/Pho81 complex. We find this alternative explanation for Pho85-Pho80 regulation by Pho81, which we can derive by combining the predictions with already published experimental data, an important element to re-evaluate the relevance of 1-IP7 in PHO pathway regulation and resolve one of the existing discrepancies.

• p. 28: No experiments were carried out with plants or mammals. The relevance for plants or mammalian systems therefore seems to be overstated at this point in time.

We are not quite sure how to interpret this remark. We do not claim that our data support a role for IP8 in mammals and plants. But we refer to and cite studies providing the strongest evidence in favor of it in these systems. The relevance of our current study relies in refuting seemingly strong evidence from yeast, which had been diametrically opposed to the data obtained in plants and mammals. The revision of the situation in yeast now paves the way to drawing a coherent concept for fungi, plants and mammals. We feel that this is important and should be underlined.

• p. 31: "300 mL of 3% ammonium" - 300 µL?

Yes. Thank you.

• p. 45, CE-ESI-MS parameters: "1IP8"

Corrected.

• p. 47: Figure S1: Please include more experimental details in the caption and/or methods section. Was a similar analysis software used as e.g. Figure S2 (NIS Elements Software)? Please also include all the analysis software in the Methods section under "fluorescence microscopy". Unless these additional experimental details already clarify the following point: Can the authors briefly comment on why the morphological determination in S1 requires trypan blue staining while in later experiments the yeast cells are readily recognized by the software in "simple" brightfield images?

Trypan blue staining is not strictly required for this. It is just a simple method to fluorescently stain the cell wall. There are many other ways of delineating the cells. It could also have been done in a brightfield image.

We updated the figure legend to better describe how these measurements were done and deposited the script and training file on figshare.

• p. 48: "can be downloaded from **" please insert the link once the script is available online.

It has been deposited at Figshare under DOI 10.6084/m9.figshare.c.6700281

Reviewer #3 (Recommendations For The Authors):

1) Italicize the scientific names of the organisms; this was inconsistent throughout the manuscript. Also, gene names should be italicized; this was also inconsistent (e.g., p.12 "... did not induce the PHO84 and PHO5 [sic] promoters...).

Done

2) Summary of the Figure 2A data in the text (p.9) probably has swapped the determined concentrations for 1-IP7 and IP8 (0.3 µM or 0.5 µM) as compared with the data figure.

Yes, indeed. We have corrected this.

3) Figure 2A: which of the mutant PP-IP levels are significantly different from the WT control?

We have now added asterisks to indicate the significance for every mutant.

4) In the discussion on the data (Fig. 2A), I was tripped up by the verb tense in this phrase "5-IP7 has not been detected in the kcs1Δ mutant and 1-IP7 has been strongly reduced..."; I think you want to use the past tense "was" in both cases [as is used in the next sentence]. It made me wonder if there was a difference in the detection of 5-IP7 and IP8 in the kcs1Δ mutant, you could detect 5-IP7 but not IP8; if so, where did the 5-IP7 come from?

We have corrected the tense. Thank you for highlighting this. For the residual inositol pyrophosphate signal in kcs1Δ. We do not know its origin. One possibility, which we now mention in the text, is that it stems from IPMK side activity. It should be underlined that all signals disappear upon PI starvation.

Figure 2C, include the data points that the lines are built from (suggestion).

We refrained from that for the line graphs. For reasons of consistency, we should do this for every line graph. If we did that, Fig. 4B would become quite hard to read.

6) Figure 3B-D, please check that the stipples or hatches are in the figure - the printed copy lacked them although I could see them in the electronic version; this was also true for Figures 5 and 6 (I do not know if it is a printer issue, but other hatches were visible: e.g., not seen in S4 but seen in S5).

They are visible in our copies, also after printing. They may have been lost during file conversion at the journal.

7) The text description of the Pho4-yEGFP, Pho5-yEGFP and Pho84-yEGFP says that the kcs1Δ mutant "showed Pho4-yEGFP constitutively in the nucleus already ... and PHO5 and PHO84 were activated". However, the data is more complex than that: whereas the localization of Pho4-yEGFP is constitutively nuclear, there is a higher basal (repressed) expression of both Pho5 and Pho84 as well as increased expression of both proteins under -Pi conditions. What accounts for the increased expression when Pho4 is already nuclear? This is also seen in the vip1Δ kcs1Δ mutant.

We agree with the reviewer, but we cannot explain this effect with certainty. One possibility could be a wider dysregulation of Pi metabolism in kcs1 mutants. To name a few possibilities: Wildtype cells have polyphosphate reserves that are gradually mobilized during the first hours of P-starvation. kcs1 mutants don't have those and might fall into a "deeper" state of starvation faster. It should be kept in mind that the starvation response is also regulated at the level of chromatin structure, and by antisense transcripts. The influence of kcs1 on these processes is unclear.

8) Figure 9 legend: please add a definition of the MP region (in red) and include it more explicitly in the described model.

We now mention the relevant region also in the legend and have labeled the relevant regions in the images (Huang et al., 2001).

9) Figure S2 legend: information is missing (downloading link).

It has been deposited at Figshare under DOI 10.6084/m9.figshare.c.6700281

10) Figure S4 and S5, missing statistics.

They have been added to the new Fig. S6, which interprets differences between strains and conditions. Fig. S4 (now S3) shows timecourses of IPPs down to zero. Adding statistics for all pairwise differences between the timepoints would be almost an overkill.

Author Response

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

eLife assessment

It is very important to find practical and efficient means in order to increase agricultural productivity. Drawing on data from variable field environments, this study provides a useful theoretical framework to identify new factors that could increase agricultural production. There is solid evidence to support the authors' claims, though following the fate of candidate species after introduction into rice fields would have strengthened the study. Plant biologists and ecologists working in nature and fields will find the work interesting.

Thank you so much for your careful evaluation of our manuscript. We are very pleased to hear that you found our framework useful. We have revised our manuscript according to the "Recommendations for the Authors" to improve our manuscript.

Public Review

Reviewer #1 (Public Review):

This manuscript describes the identification of influential organisms on rice growth and an attempt of validation. The analysis of eDNA on rice pot and mimic field provides rice growth promoting organisms. This approach is novel for plant ecology field. However current results did not fully support whether eDNA analysis-based detection of influencing organism.

Thank you so much for evaluating our manuscript. We have carefully read and responded to your comments. We hope our responses resolve your concerns on our study.

The strength of this manuscript is to attempt application of eDNA analysis-based plant growth differentiation. The weakness is too preliminary data and experimental set-up to make any conclusion. The trials of authors experiments are ideal. However, the process of data analysis did not meet certain levels. For example, eDNA analysis of different time points on rice growth stages resulted in two influential organisms for rice growth. Then they cultivate two species and applied rice seedlings. Without understanding of fitness and robustness, how we can know the effect of the two species on rice growth.

We agree with your comments that we did not have the fitness data of the two species and/or rice seedlings. Thus, it is still difficult to obtain deep understanding of the mechanisms of our findings that the species introduced in the system would influence rice growth. Nonetheless, our study demonstrated the effectiveness of our research framework as we found evidence that the species that were discovered by the eDNA monitoring and time series analysis indeed cause changes in the system. We believe that the first step is to show that the framework is workable and that detailed understanding of the mechanisms or genetic pathway was not a focus of our study. To avoid misunderstanding, we have added several explanations regarding this point in L426–431 and L447. For example, in L426, we have added the following statement: "... the detailed dynamics of the two introduced species was unclear (i.e., the fate of the introduced species). This is particularly important for understanding how the introduced organisms affected rice performance...".

The authors did not check the fate of two species after introducing into rice. If this is true, it is difficult to link between the rice gene expression after treatments and the effectiveness of two species. I think the validation experiment in 2019 needs to be re-conducted.

We did not check the fate of the two species (except measuring the eDNA concentrations of the species), and it is true that we cannot show evidence of "how" these two species influence the rice gene expression. Understanding molecular mechanisms of the phenomenon that we found is important (especially from the viewpoint of molecular biology), but our primary objective was to demonstrate that our "eDNA x time series analysis" framework is feasible for detecting previously overlooked but influential organisms. To this end, we believe that we achieved our objective and repeating the validation experiment should be for a different purpose (i.e., for understanding molecular mechanisms). We have clarified these points in L426–431 and L447 as explained above.

Reviewer #2 (Public Review):

The manuscript "Detecting and validating influential organisms for rice growth: An ecological network approach" explores the influence of biotic and abiotic entities that are often neglected on rice growth. The study has a straightforward experimental design, and well thought hypothesis for explorations. Monitoring data is collected to infer relationships between species and the environment empirically. It is analyzed with an up-to-date statistical method. This allowed the manuscript to hypothesize and test the effects most influential entities in a controlled experiment.

Thank you so much for your careful evaluations. We are pleased to see that you evaluated our manuscript positively. We have further revised our manuscript according to your comments and hope the revision has resolved your concerns.

The manuscript is interesting and sets up a nice framework for future studies. In general, the manuscript can be improved significantly, when this workflow is smoothly connected and communicated how they follow each other more than the sequence and dates provided. It is valuable philosophical thinking, and the research community can benefit from this framework.

Thank you for your suggestions. In order to improve the logic flow and readability of our manuscript, we have revised the descriptions of workflow and clarified how the experimental and statistical steps were connected to each other. To do so, we have added brief explanations about what/how we did at the first sentence of Results subsections (some of these explanations were only in Materials and Methods in the original manuscript). Also, we have moved all of the Supplementary Materials and Methods to the main text. We have thoroughly revised the manuscript, and we hope that all the parts of our manuscript have been connected more smoothly than in the original manuscript.

I understand the length and format of the manuscript make it difficult to add more details, but I am sure it can refer to/clear some concepts/methods that might be new for the audience. How/why variables are selected as important parts of the system, a tiny bit of information about the nonlinear time series analysis in the early manuscript, and the biological reasoning behind these statistically driven decisions are some examples.

We have explained how/why variables are selected (in L125), added more information about the nonlinear time series analysis (in L129 and L175) , and added the biological reasoning behind the statistical decisions (L195).

Reviewer #3 (Public Review):

Most farming is done by subtracting or adding what people want based in nature. However, in nature, crops interact with various objects, and mostly we are unaware of their effects. In order to increase agricultural productivity, finding useful objects is very important. However, in an uncontrolled environment, it coexists with so many biological objects that it is very inefficient to verify them all experimentally. It is therefore necessary to develop an effective screening method to identify external environmental factors that can increase crop productivity. This study identified factors presumed to be important to crop growth based on metabarcoding analysis, field sampling, and non-linear analysis/information theory, and conducted a mesocosm experiment to verify them experimentally. In conclusion, the object proposed by the author did not increase rice yield, but rather rice growth rate.

Thank you so much for your evaluation of our manuscript. We have revised our manuscript based on your comments, and hope it has been improved compared with the original version.

Strength

In actual field data, since many variables are involved in a specific phenomenon, it is necessary to effectively eliminate false positives. Based on the metabarcoding technique, various variables that may affect rice growth were quantitatively measured, although not perfectly, and the causal relationship between these variables and rice growth was analyzed by using information transfer analysis. Using this method, two new players capable of manipulating rice growth were verified, despite their unknown functions until now. I found this process to be very logical, and I think it will be valuable in subsequent ecological studies.

We are very pleased to see that you found our framework is very logical and potentially beneficial for future ecological studies.

Weaknesses

CK treatment's effectiveness remains questionable. Rice's growth was clearly altered by CK treatment. The validation of the CK treatment itself is not clear compared to the GN treatment, and the transcriptome data analysis results do not show that DEG is not present. The possibility of a side effect caused by a variable that the author cannot control remains a possibility in this case. Even though this part is mentioned in Discussion, it is necessary to discuss various possibilities in more detail.

We agree that the effectiveness of the CK treatment was questionable. We have added some more discussion about this point in L376: "The unclear effects of the CK treatment relative to those of the GN treatment could be due to the relatively unstable removal method (i.e., C. kiiensis larvae were manually removed by a hand net) or incomplete removal of the larvae (some larvae might have remained after the removal treatment)."

Reviewer #1 (Recommendations For The Authors):

Comment #1-1 This manuscript describes identification of influential organisms on rice growth and an attempt of validation. The analysis of eDNA on rice pot and mimic field provides rice growth promoting organisms. This approach is novel for plant ecology field. However current results did not fully support whether eDNA analysis-based detection of influencing organism.

Thank you for your careful evaluations of our manuscript. We are pleased to see you found that our approach is novel. We have revised our manuscript in accordance with your comments, and we hope that the revision and responses resolved your concerns.

Comment #1-2 1. Experimental setting: Authors made up small scale pot system in 2017 and then expanded manipulative experiment. I do not understand how two influencing organism sequences were identified from the single treatment depending on different time points. How they can be convince the two organisms affect the rice growth rather than other biological and environmental factors.

In 2017, we performed an intensive monitoring of the experimental rice plots and obtained large time series data (122-day consecutive monitoring x 5 plots = 610 data points). The time series data were analyzed using the information-theoretic causal analysis. The analysis is critically different from correlational analyses and designed to identify causal relationships among variables. Although we understand that field manipulation experiments are a common and straightforward approach to identify causal relationships among organisms, we chose the "fieldmonitoring + time-series-based causal analysis" approach. This is because, as explained in the main text, there are numerous factors that could influence rice performance, and it is practically impossible to perform manipulative experiments for all the potential factors that could influence rice growth. On the other hand, our "field-monitoring + timeseries-based causal analysis" approach has a potential to identify multiple factors under field conditions, even by the single experimental treatment.

Nonetheless, we must admit that our time-series-based approach still has a chance to misidentify causal factors. Our framework relies on statistics, so the chance of false-positive detection of causality cannot be zero. This was exactly the reason why we performed the "validation" experiment in 2019. To complement the statistical results of the 2017 experiments, we performed another experiment in 2019.

Comment #1-3 2. eDNA technology: The eDNA analysis based on four universal primers 16s rRNA, 18s rRNA, ITS, and COI regions must not be enough to identify specific species. The resolution of species classification may not meet to confirm exact species. Thus, the accuracy of two species that they selected for further experiment is difficult to be confirmed. Authors also referred to "putative Globisporangium".

Your point is correct. The DNA barcoding regions we selected are short and it is often difficult to identify species. However, this limitation could not have been overcome even if we had chosen a different genetic marker. The long-read sequencing technology could partially solve the issue, but the number of sequence reads generated by the long-read technique is less than that by the short-read sequencing technology, and comprehensive detection of all species in an ecological community was still challenging. Our approach struck a balance among the identification resolution, comprehensiveness of the analysis, and sequencing costs. In addition, even though we could not identify most ASVs at the species level, some ASVs could be identified at the species level (52 ASVs among the 718 ASVs which had causal influences on rice growth), and we selected the two species (G. nunn and C. kiiensis) from the 52 species.

Further, the taxa assign algorithm we used here (i.e., Claident; Tanabe & Toju 2012 PLoS ONE 10.1371/journal.pone.0076910) adopted conservative criteria for species identification and has a low falsepositive probability.

More importantly, this is also the reason why we performed the "validation" experiment in 2019. The species identified in the 2017 experiment are still "potential" organisms that influence rice growth (i.e., the hypothesis-generating phase), and we tested the hypothesis in 2019.

Nonetheless, we must admit that clear description of potential limitations is important. Thus, we have discussed this in L418: "As for the second issue, short-read sequencing has dominated current eDNA studies, but it is often not sufficient for lower-level taxonomic identification. Using long-read sequencing techniques (e.g., Oxford Nanopore MinION) for eDNA studies is a promising approach to overcome the second issue".

Comment #1-4 3. Biological relevance 1: Authors identify two organisms as influencing organism for rice growth. As conducting the first experiment in 2017, the 2019 experiment was different from natural condition. The two experiments in 2017 and 2019 were conducted under different conditions. How do they compare the experiments? At least, the eDNA analyses in 2017 and 2019 should be very similar. I cannot find such data.

The experimental conditions were different between 2017 and 2019 because they were conducted in different years. Theoretically, it is ideal if the experimental conditions in 2019 are covered by the range of experimental conditions in 2017 (e.g,. rice variety, air temperature, rainfall, and solar radiation). If this condition were satisfied, the attractor (i.e., rice growth trajectory delineated in the state space) in 2019 would be within that in 2017, and our model prediction in 2017 would be used to predict dynamics in 2019 accurately. To fulfill the conditions, we made as much effort as possible: we used the same rice variety and soils in 2019 as those used in 2017, and started our experiment at the same timing in 2019 as that in 2017.

Although natural ecological dynamics cannot be precisely controlled, our monitoring revealed that the ecological dynamics in 2019 was qualitatively similar to that in 2017. To demonstrate that the experimental conditions and eDNA community data were similar between the two experiments, we have presented the climate and eDNA data in an inset figure in Figure 3a, Figure 1–figure supplement 2, Figure 3–figure supplement 2. We must admit that these dynamics are not identical, but we hope that this resolves your concern.

Comment #1-5 4. Lack of detail description: In the Materials and Methods, there are many parts which lack on detail description. For instance, authors must described the two species cultivation, application concentrations, and application methods.

We have moved Supplementary Materials and Methods to the main text and added more detailed descriptions in Materials and Methods. Also, to improve the logical flow and readability of our manuscript, we have added brief explanations about what/how we did at the first sentence of Results subsections (some of these explanations were only in Materials and Methods in the original manuscript). We have added the reference for how to cultivate G. nunn in L608 (Kobayashi et al., 2010; Tojo et al., 1993) (C. kiiensis was not cultivated but removed from the system as in Materials and Methods), and application concentrations. Application methods were described in Materials and Methods, the section Field manipulation experiments in 2019 in L596.

Comment #1-6 5. Validation: Application of one species clearly resulted to promote rice growth. They must include appropriate control treatment. If they pick same genus but different species that identified no specific effect on rice growth through eDNA analysis, no effect on growth can be provided. Generally application of large population of certain non-harmful organism confer plant growth promotion. It is not surprising result. Authors need to prove effectiveness of eDNA analysis. In addition, the field experiments required at least two years of consistent data for publication because environmental factors are so dynamic.

Thank you for pointing this out. We agree with your comment that species that were predicted to have no effect should not promote rice growth in a validation experiment. It was also one of our inititial experimental plans to include such species in our manipulation experiment in 2019, but we could not include them because of the limitation of time, labor, and money. More extensive validation of the statistical results of the 2017 data, including multi-year experiments, would further validate the effectiveness of our approach, which should be done as future studies. To clarify this point, we have added statements in the paragraph starting at L396.

Comment #1-7 In conclusion, I suggest that authors need more large data analysis and validate with more accurate and meaningful protocol.

As we explained in the revised manuscript and the Response to Comments #1-2 to #1-7, our study demonstrated a novel research framework to detect previously overlooked influential organisms under field conditions. We agree that larger data analysis would be ideal to further validate our approach, but whether and how to collect larger data is constrained by time, money, and labor. We believe that our study was designed carefully and could provide meaningful avenues for developing an ecological-network based, novel, and environment-friendly agriculture solutions.

Reviewer #2 (Recommendations For The Authors):

Comment #2-1 Lines 97-110: This is so cool. Modeling with empirical data is very powerful. But a rice field is an open system consisting of metacommunity dynamics. Maybe a tiny bit of biological and biogeochemical background here would be good.

Thank you for your comments. We have added a few examples of how and in which systems these methods were used to evaluate community dynamics and detect biological interactions in L109-L118.

Comment #2-2 Lines 111-126: I like the summary of the study here. I think the influential species concept can be a little more elevated. Paine's famous keystone species work has been cited but a couple more pieces of literature can help to enhance the ecological importance of this work.

We have explained the work by Paine (1966) a bit more and added one more paper that showed the effect of multiple predator species on the system dynamics at L88. We have also added a relevant sentence at L137 to emphasize the ecological/agricultural significance of our work.

Comment #2-3 Experimental design/Figure 1:

Is there any rationale behind choosing red individuals to measure the growth?

Is there any competition between the individuals in the pots?

Figure 1e: It is nice to show the ASVs in time. I wonder how the plot would look like when normalized by biomass/DNA content/coverage/rarefaction because of the seasonality.

As for the first question, we chose the four individuals to minimize the edge effects (i.e., effects of microclimates and neighboring rice would be different between the four rice individuals and those planted in the edge regions). We have mentioned this in the legend of Figure 1.

As for the second question, there might be competition among the individuals in the pot. However, we did not measure the effect of competition (e.g., by comparing the growth with/without other rice individuals).

As for the third question, we published detailed dynamics of ecological community in the Supplementary Figures in Ushio (2022) Proceedings B https://doi.org/10.6084/m9.figshare.c.5842766.v1. In addition, we have uploaded a video showing the temporal dynamics of some top (= most abundant) ASVs in https://doi.org/10.6084/m9.figshare.23514150.v2.

We have mentioned the supporting information in L153.

Comment #2-4 Line 146-147: Is this damage influence the inferences? Maybe it is better to justify.

While we occasionally observed physical damages, it is unlikely that they affected our causal inference because the changes in the rice heights due to the damages were smaller and less frequent than those due to growth. We have noted this at L151.

Comment #2-5 Line 161-162: Maybe refer readers to the methods section where you explain UIC analysis. It'd be easier to interpret the figures.

Mentioned.

Comment #2-6 Line 175-176: I believe very brief information in the intro about the organisms might help explain the hypothesis and interpret the results better.

We have included brief information of the two species at L197.

Comment #2-7 Figure 2: Species interaction strength: Are these proxies to the Jacobians? Is there a threshold for the influence we can consider strong/weak? For example, influential species compared to diagonal elements of the Jacobians (intraspecies interactions) could be shown as a mean vertical line in Figure 2b.

"Influences to rice growth" in Figure 2b is transfer entropy (TE) from a target ASV to rice growth. They are not proxies of the Jacobians, but they might positively correlate with the absolute value of the Jacobians. We have clarified this point in the legend (L953). More direct estimations of the Jacobian can be done using the MDR S-map method (Chang et al. 2021 DOI:10.1111/ele.13897), but we did not perform the MDR S-map in the present manuscript (see Ushio et al. 2023 https://doi.org/10.7554/eLife.85795 for the application of the MDR S-map). As for TE, there is no clear threshold to distinguish strong/weak interactions.

Comment #2-8 Figure 2: Looking at panels c and d, it looks like there is a negative frequency selection between two influential species. Is it a reasonable observation?

This is an interesting point. In this manuscript, we have not carefully examined the interspecific relationship between these two particular species. However, the interspecific interactions were examined in detail and reported in Ushio (2022) Proceedings of the Royal Society B DOI:10.1098/rspb.2021.2690). We re-checked the result in Ushio (2022); although there is a negative correlation between them, we did not find any (statistical) causal relationship between them.

Comment #2-9 Line 209: What is t-SNE analysis? Because of the manuscript's format, maybe methods should be shortly referred to in the relevant section or explained in brackets.

We have spelled out t-SNE.

Comment #2-10 Line 212-214: Maybe briefly explain what the hypotheses are for the alternative analysis, and what is the contribution of the results to the study.

We have added a brief explanation at L241: "Alternative statistical modeling that included the treatments (the control versus GN or CK treatments) and manipulation timing (i.e., before or after the manipulation), which simultaneously took the temporal changes of all the treatments into account, also showed qualitatively similar results (Supplementary file 4), further supporting the results."

Comment #2-11 Figure 3b/c: Maybe species names as panel titles could be helpful. d: Treatment names with initials in the legend could be also helpful to read the plots.

We have added species name as panel titles of Figure 3b,c. Treatment names were included in the legend of Figure 3.

Comment #2-12 Line 233: Maybe mention why the manuscript uses the word "clear".

We have mentioned this in L185.

Comment #2-13 Line 234-236: I think that these alternative tests should be explained somewhere.

We have revised the sentence so that it includes some explanations (L241). Also, we have referred to Materials and Methods.

Comment #2-14 Figure 4: The title says ecological community compositions, and panels show the growth rates and cumulative growth.

Thank you for pointing this out. This was a typo and we have corrected it.

Comment #2-15 Lines 246-269: Can these expression patterns be transient and relevant to the time point that the sample is taken?

Yes, these expression patterns were transient. We collected rice leaf samples for RNA-seq 1 day before the first manipulation and 1, 14, and 38 days after the third manipulation (see Supplementary file 3 for the sampling design). When we merged the pot locations, we observed no difference in the gene expression for samples 1 day before the first manipulation and 14 and 38 days after the third manipulation (except for two genes in samples 38 days after the manipulation), and thus, we consider the DEGs that appeared only in the short period after the manipulation. We have mentioned this in L278 and L383: "We found almost no DEGs for leaf samples taken one day before and 14 and 38 days after the third manipulation (the leaf sampling event 1, 3, and 4), suggesting that the influences of the treatments on the gene expression patterns were transient." (L278) and "These changes were observed relatively quickly and transient." (L383)

Comment #2-16 I wonder if a conceptual framework figure would help to generalize the workflow that can be used for other studies.

Thank you for your suggestion. Although we agree with your comment that such a figure would be helpful to generalize the workflow, we believe that our framework is clear and decided not to include it in the present manuscript. We might consider including such a figure (like Figure 1a in Ushio 2022) if we have an opportunity to write a review paper regarding this topic.

Comment #2-17 Lines 329-335: I feel this information is unclear in the early manuscript. Maybe it's necessary to clearly communicate in the beginning.

We have explained that we could not find any relevant information at least at the time we detected the ASVs in L189.

Comment #2-18 Lines 336-337: Can these species be identified in the previous data set from the ASV sequences?

Yes, these species were identified in the DNA data set obtained in 2017.

Comment #2-19 Lines 387-397: Are there any measurements such as total biomass, and statistical methods to help with the eDNA bias and data compositionality?

We have confirmed that our quantitative eDNA metabarcoding generates comparable results with the fluorescence-based method and quantitative PCR (e.g., see Supplementary Figures in Ushio 2022) (mentioned in L310 in the revised manuscript). However, at least in this study, we could not perform a direct comparison of the eDNA data with species abundance and/or biomass. This is partly because the number of our target species was too large (> 1,000 species). The accurate estimation of species abundance and/or biomass is one of our next goals.

Comment #2-20 Line 472: Maybe mention transfer entropy somewhere in the early manuscript.

We have mentioned this in L175.

Comment #2-21 Lines 494-503: Maybe a summary of this reasoning should be mentioned somewhere in the early manuscript too.

We have described a brief summary of the reasoning in L195.

Comment #2-22 Lines 29-33 If this sentence is simplified it might be easier to follow.

The sentence has been divided into two sentences in L28. Also, each sentence has been simplified.

Comment #2-23 Line 38 Maybe "macrobes" can be explicitly mentioned. Fungi, protozoa, etc.

Mentioned.

Comment #2-24 Line 139: I am not sure if the date should be in the title.

Similar monitoring was done in 2017 and 2019. Thus, we think the date is necessary in the section title.

Comment #2-25 Figure 1: There are 4 red individuals in the design but 5 measurements in the plots.

Heights and SPAD of the four individuals were measured for each plot and the averaged values were used as representative values for each plot. Therefore, 20 measurements (= 4 rice individuals 5 plots) were done every day, but each plot has one rice height for each day. We have clarified this in the legend of Figure 1: "the average values of the four individuals were regarded as representative values for each plot."

Comment #2-26 Figure 1b: Maybe use the same axis length for the temperature as the other plots?

Corrected.

Comment #2-27 Lines 259-261: Are there the names of the genes in databases?

Yes, these are gene names used in the rice databases (e.g., The Rice Annotation Project Database; https://rapdb.dna.affrc.go.jp/inde x.html).

Reviewer #3 (Recommendations For The Authors):

Comment #3-1 Additionally, RGR is not statistically significant, but statistical significance is observed only in cumulative growth because data presentation does not reflect plant characteristics. RGR changes according to the developmental stage of the plant. Therefore, if RGR data are shown separately according to the rice growing season, the cumulative growth pattern and the pattern will appear similar.

RGRs were calculated daily (i.e., cm/day) and they changed depending on the developmental stage of the rice (Figure 1 and Figure 4–figure supplement 1). Therefore, we might find similar RGR patterns if we focus on a specific period of the growing season. However, unfortunately, we performed the intensive (i.e., daily) monitoring in 2019 only during the field manipulation period (middle June to middle July 2019), and we cannot investigate the changes in cumulative growth throughout the growing season (this depends on how many days we add up RGR to calculate the cumulative growth, though). We agree that, if we had investigated the detailed pattern of RGR throughout the growing season in 2019, we could have found similar pattens between RGR and cumulative growth rate at a certain period in the growing season. In Figure 4, the cumulative growths were calculated based on the RGRs before the third manipulation or during 10 days after the third manipulation. We clarified this in the legend of Figure 4.

12:3 Those who are wi se[a] will shine like the brightness of the heavens, and those who lead many to righteousness, like the stars for ever and ever.

• https://www.americamagazine.org/politics-society/2020/05/08/its-time-rethink-electoral-college

• https://www.npr.org/sections/itsallpolitics/2011/12/20/144016912/we-the-people-npr-readers-would-ratify-four-new-amendments

• https://www.americamagazine.org/politics-society/2020/05/08/its-time-rethink-electoral-college

• https://www.npr.org/sections/itsallpolitics/2011/12/20/144016912/we-the-people-npr-readers-would-ratify-four-new-amendments

• https://constitutioncenter.org/blog/vote-now-an-amendment-to-end-the-electoral-college

• https://www.nytimes.com/2020/02/09/opinion/letters/electoral-college.html

• https://www.latimes.com/opinion/readersreact/la-ol-le-electoral-college-20180904-story.html

you are offline

• https://slate.com/news-and-politics/2014/05/amending-the-constitution-is-much-too-hard-blame-the-founders.html

we the people rise again

• https://slate.com/news-and-politics/2012/06/fix-the-constitution-amending-by-national-referendum.html

safe souls, safe fu

• https://slate.com/news-and-politics/2012/06/fixing-the-constitution-protecting-informational-privacy.html

• https://slate.com/news-and-politics/2020/05/new-reconstruction-constitution-democracy.html

We the People of Slate ...

The U.S. Constitution, as you [mighta been, shoulda "come" on ... its someday] rewrϕte it.

"Politicians talk about the Constitution as if it were as sacrosanct as the Ten Commandments [interjection: spec. it is actually almost exactly related!]. But the document itself invites change and revision. What if the president served only one six-year term instead two four-year terms? What if your state's population determined how many senators represent it? What if the Constitution included a right to health care? We asked legal scholars and Slate readers to cross out what they didn't like in the Constitution and pencil in their hearts' desires. Here's what the document would look like with their best ideas."

• Slate: u_s_constitution as_rewritten by_slate_legal_experts_and_readers

多也了了夕 "with a ~~wand~~ of scheffilara, 并#亦太 he begins ... "I am now on the Staff of Menelaus, the Spears of Longinus and Lancelot; and the name "Mosche ex Nashon."

Logically the recent mentions of Gilgamesh and the simultaneous 同時 overlaping 場道 of the eventual link between the famous ruling of Solomon on the separation of babies and mothers and waters and land ... to a story of many "two cities" that culminates in a cultural or societal or "evolutionary" link to Sodom and Gomorrah and the city-state of Babylon (and it's Hanging Gardens) and also of course to Paris and Troy and "Masstodon" and city-states [ciudadestado] and perhaps planet-cities; from Cambridge to Cambridge across the "Cable" to see state to "London" ... recently I called it "the city of realms" ... I started out logically intending to link "game theory" and John Nash to the mathematical story of Sputnik and a revival of American physics; but in my usual way of rambling into the woods [I mean neighborhood] of stream of consciousness ... turned into a premonitory discourse of "two cities" and how sometimes even things as obvious as the number of letters in the word "two" don't do a good enough job of conveying ... how and/or why one is simply never enough, and two isn't much better--but in the end a circle ... is drawn; the perfect circle in our imaginary mathematical perfection ... I see a parted "line" in the letter pronounced "tea" (and beginning that word); and two "vee" (pron. of "v") symbols joined together in a word we pronounce as "double-you" ... and symbolically because I know "V" is the Roman Numeral for 5 (five) and I know not how to multiply in Roman numerals--

It's important to pause; here. I am going to write a more detailed piece on "the two cities" as I work through this maze like crossroads between "them" and "demo..." ... here demorigstrably I am trying to fuse together an evolutionary change in ... lit. biological evolution as well as an echelon leap forward in "self-government" ... in a place where these two things are unfathomable and unspokenly* connected.

• https://www.google.com/search?q=prometheuslocke+%2Bsite%3Agodlikeproductions.com

• "Silence is betrayal" -MLK

To a question on the idiom; is Bablyon about "the law" or "of the land of Nod?"

"What is democracy" ... the song, Metallica's "ONE" echoes and repeats; as we apparently scrive together the word "THEM" ... I question myself ... if Babylon were the capital city of some mythical Nation of Time ... if it were the central "turning point" of Sheol; ... >|<

Can you not see that in this place; in a world that should see and does there is a gigantic message proving that we are not in reality and trying to show us how and why that's the best news since ... ever---that it's as simple as conjoining "the law of the land" with a basic set of rules that automatically turn Hell into something so much closer to Heaven I just do not understand---why we cant stand up together and say "bullets will not kill innocent children" and "snowflakes will not start avalanches ...." that cover or bury or hide the road from Earth to Verital)e .... or from the mythical Valis to Tanis---or from Rigel to Beth-El ... "guess?"

## as "an easy" answer; I'm looking for a fusion of "law and land" that somehow remembers a "jok'er a scene" about "lawn" seats; and "where the girls are green;"

It's as simple as night and day; Heaven and Hell ... the difference between survival and--what we are presented with here; it's "doing this right"--that ends the Hell of representative democracy and electoral college--the blindness and darkness of not seeing "EXTINCTION LEVEL EVENT" encoded in these words and in our governments foundation ... *by the framers [not just of the USA; but English .. and every language] *

... is literally just as simple as "not caring" or thinking we are at the beginning of some long process--or thinking it will never be done--that special "IT" that's the emancipation of you and I.

Here words like "gnosis" and "gaudeamus" pair with my/ur "new ntersanding*" of the difference between Asgard and Medgard and really understanding our purpose here is to end "evil" ... things like "simulating disease and pain" (here, simulating meaning ... intentionally causing, rather than "gamifying away") and successfully linking the "Pillars of Hercules" to Plato's vision of Atlantis and the letter sequences "an" and "as" ... unlock a fusion of religion and mythology and "cryptographic truth" that connects "messianic" and "Christian" to "Roman" ... "Chinese" and "American" ... literally the key to the difference between the phrases "we are" and "we were" ....

in "sight" of "silicon" in simulation and Israel, Genesis, and "silence" ... trying to the raising of Asgardian enlightenment ... and seeing "simple cypher" connecting to "Norse" ...

and the "I AM THAT" surer than shit ... the intention and design of all religion and creation is to end "simulated reality" and also not seeing "SR" ... in Israel and Norse ... "for instance."

• https://www.google.com/search?q=%22I+AM%22+%22WE+ARE%22+%2Bsite%3Afromtaws
• "SOIS" a key--in two languages conjugated literally as both "I AM" and "WE ARE" simultaneously;
• Search: I know that if I am than so are you ... and it is because we have overcome .... something I truly cannot figure out, fathom, or believe ... was truly here before us--a spiralling series of failures ... speaking: to the heavens; but in secret and in action; "doing everything possible to succeed."

It's a simple linguistic concept; the "singularity" and the "plurality" of a simple word--"to be"--but it goes to the heart of everything that we are and everything that is around us. This is a message about understanding and preserving individuality as well as liberty; and literally seeing "ARXIV" and understanding "often" and failing to connect God and prescience to "IV" and the Fourth Amendment ... it's about blindness and ... "curing the blind instantly" ... and fathoming how and why this message has been etched into our entire history and and all religions and myths and music--to help us "to be THAT we" that actually "are responsible" for the end of Hell.

• I neglected to mention "Har-Wer" and "Tower of Babel" which are both related lingusitically, religiously and topically: "to who ..." and while we're on "four score and [seven years from now]" seeing the fourth "living thing" in Eden and it's (the name, Abel) connection to Babel and Abraham Lincoln; slavery and ... understanding we live in a place where the history of the United States also, like Monoceros and "Neil Armstrong's first step" are a time shifted ... overlayed map to achieving freedom ... it's about becoming a father-race ... and actually "doing" the technological steps required to "emancipate the e's of 'me&e'" and survive in exo-planetary space---

it might be as simple as adding "because we did this" here and now; and having it be something we are truly proud of .... forevermore™ ... for certain in the heart of this story about cyclicality and repetition of error--its not because we did "this" or something over and over again; it's about changing "the problem" and then helping others to also overcome ... "things like time travel ... erasing speech" --- however that happenecl.

• I also failed to mention that "I am in Hell" ... as in this world is hellacious to me; in an overlay with the Hellenic period and this message that we are in the Trojan Horse ... a small gem .... "planet" truly is the Ark of the Covenant---and it's the simple understanding that "reality is hell" is to "living without air conditioning and plumbing is hell" just as soon as you achieve ... "rediscovering" those things---

• I can't figure out why I am the only person screaming "this is Hell." That's also, Hell.

... but recently suggested an old joke about "there being 10 kinds of people in the world (obv an anti-tautology and a tautology simultaneously)" only after that brief bit of singularity and duality mentioning the rest of the joke: "those that understand binary and those that don't know how to base convert between counting with two hands and counting with only an 'on and off.'" It's not obvious if you aren't trying to figure it out, I suppose; but 10 is decimal notation for "kiss" and the "often" without "of" ... and binary notation for the decimal equivalent of "2." A long long time ago in a state that simply non-randomly ties to the heart of the name of our galaxy ... I was again thinking of the "perfect imperfections" of things like saying "three equals one equals one" (which, of course was related to the Holy Trinity and it's "prescient/anachronistic Adamic presence encoded in the name Ab|ra|ha|m" which means "father of a great multitude") ... I brought that one back in the last few months; connecting the letter K and in this "logos-rythmic" tie to the "base of a number system" embellish the truth just a bit and suggest a more accurate rendition of the original [there is no such thing as equality, "is" of separate objects--as in no two snowflakes are the same unless they are literally the same one; true of ancient weights and with the advent of (thinking about) time no two "planets" are the same even if they're the exact same one--unless it's at a fixed moment in time.

• This name may be viewed either as meaning "father of many" in Hebrew or else as a contraction of ABRAM (1) and הָמוֹן (hamon) meaning "many, multitude". The biblical patriarch Abraham was originally named Abram but God changed his name (see Genesis 17:5).

• https://en.wikipedia.org/wiki/Yeshua#Yeshua,_Yehoshua,_and_Yeshu_in_the_Talmud

K=3:11 ... to a handle on the music, the DHD of the gate and the *ring of David's "sling" ...

---and that's a relationship of "3 is to 11" as [the SAT style "analogy)]y" as a series of alpha, two mathematic, and two numeric symbols ... may only tie in my mind alone to the books of Genesis and Matthew and the phrase "chapter and verse" and to the stories of Lot and Job ... again in Genesis and the eponymous "Book of Job." So ... "tying up loose ends one 10b [III] iv. " as it appears I've taken it upon myself to call a Job and suggest is my "Lot in life [x]i* [3]"

• I worry sometimes that important things are missing, or will disappear---for instance Mirriam Webster, which is a "canonical/standard dictionary) should probably have an entry for "lot in life" non-idiomatically as "granny apples to sour apples" as

2 MANY ALSO ICI; 1twoⅱ ... following in Mitnick's bold introductory word steps; the curve and the complement ... the missiles and the canoes; the line and the blank space ... "supposedly two examples of two kinds, which could be three not nothings ... Today I write about something monumental; as if as important as the singularity depicted in Arthur C. Clarke's 2001 "A Space Odyssey" ... and remember a day when I thought it very novel and interesting to see the words "stillborn and yet still born" connected in a single piece of writing to "Stillwater and yet still water" ... today adding in another phrase noting the change wrought only by one magical single "space" (also a single capital letter; and a third phrase): "block chains with a great blockchain."

• http://www.goodmath.org/blog/2015/07/21/arabic-numerals-have-nothing-to-do-with-angle-counting/

• https://gizmodo.com/no-this-viral-image-does-not-explain-the-history-of-ar-1719306568

• https://en.wikipedia.org/wiki/Chinese_word_for_%22crisis%22

• https://dictionary.hantrainerpro.com/chinese-english/translation-ji_howmany.htm
• https://dictionary.hantrainerpro.com/chinese-english/translation-duo_many.htm

• https://en.wikipedia.org/wiki/Euripides, Iphigenia in Aulis or Iphigenia at Aulis[1] (Ancient Greek: Ἰφιγένεια ἐν Αὐλίδι, Iphigeneia en Aulidi; variously translated, including the Latin Iphigenia in Aulide) is the last of the extant works by the playwright Euripides. Written between 408, after Orestes, and 406 BC, the year of Euripides' death, the play was first produced the following year[2] in a trilogy with The Bacchae and Alcmaeon in Corinth by his son or nephew, Euripides the Younger,[3] and won first place at the City Dionysia in Athens.

• The play revolves around Agamemnon, the leader of the Greek coalition before and during the Trojan War, and his decision to sacrifice his daughter, Iphigenia, to appease the goddess Artemis and allow his troops to set sail to preserve their honour in battle against Troy. The conflict between Agamemnon and Achilles over the fate of the young woman presages a similar conflict between the two at the beginning of the Iliad. In his depiction of the experiences of the main characters, Euripides frequently uses tragic irony for dramatic effect.

J.K. Rowling spurred just this past week a series of explanations about just exactly what is a blockchain coin worth ... and why is it so; her final words on the subject (artistic liberty taken, obviously not the last she'll say of this magic moment) "I don't think I trust this."

Taken directly from an off the cuff email to ARXM titled: "Slow the S is ... our Hypothes.is"

I imagine I'll be adding some wiki/ipfs stuff to it--and try to keep it compatible; the design and layout is almost exactly what I was dreaming about seeing--as a "first rough draft product." Lo, and behold. It's been added to the many places I host my tome; the small compilation of nearly every important email that has gone out ... all the way back to the days of the strange looking Margarita glass ... that now very much resembles the "Cantonese character 'le'" which I've come to associate with a "handle" on multiple corners of a room--something like an automatic coat rack conveyor belt connecting different versions of "what's in the box." I'm planning on using that symbol 了 to denote something like multiple forks of the same page. Obviously I'm thinking forward to things like "the Transhumaist Chain Party" (BDSM, right?)'s version of some particular piece of legislation, let's say everything starts with the sprawling "bulbing" of "Amendment M" ideas and specific verbiage ... and then we'll of course need some kind of new git/subversion/cvs style version control mechanism to merge intelligently into something that might actually .... really should ... make it into that place in history--the first constitutional amendment ratified by a "Continental Congress of All People" ... but you could also see it as an ongoing sort of forking of something like the "wikipedia page" on what some specific term, say "technocracy" means, and how two parties might propagandize and change the meaning of such thing; to suit the more intelligent and wise times we now live in. For instance, we might once have had a "democracy" and a "democractic" party that had some Anarchist Cook Book version of the history of it ending in something like Snipes and Stallone's "DEMOLITION MAN."

Just kidding, we all know "democracy" has everything to do with "d is cl ... and not th" ... to be the them that is the heart of the start of the first true democracy. At least the first one I've ever seen, in my old "to a republic" ... style. As it is you can play around with commenting and highlighting and annotating all the stuff I've written and begged and begged for comments on--while I work on layering the backend to to perma-store our ideas and comments on both a blockchain (probably a new one; now that i've worked a little with ethereum) with maybe some key-merkle-tree-walk-search stuff etched into the original Rinkeby ... and then of course distributed data in the "public owned and operated" IPFS. To be clear, I plan on rewriting the backend storage so that we will have a permanent record of all comments; all versions of whatever is being commented on; and changes/revisions to those documents--sort of turning the web into a massive instant "place of collaboration, discussion, and co-authoring" ... if you use the wonderful LEGO pieces that have been handed to us in ideas from places like me, lemma--dissenter, and of course hypothes.is who has brought you and i such a polished and nice to look at "first draft" of something like the living Constitution come repository of all human knowledge. I do sort of secretly wich they would have called this project something like "annotating and reflecting (or real or ...) knowledge" just so the movement could have been called ARK. ... or something .... but whatever join the "calling you a reporter" group or ... "supposedly a scientist?"

NOIR INgR .. I CITE SITE OF ENUDRICAM; a rekindling of the dream of a city appearing high above in the sky, now with a boldly emblazened smiling rainbow and upsidown river ... specifically the antithesis of "angel falls," there's a lagoon too--actually a chain of several ponds underneith the floating rock ... and in some versions of this waking dream there are rings around the thing; you might imagine an artificial set of centripetal orbitals something like a fusion of the ring Eslyeum and the "Six-Axis ride" of the JKF Center's "Spacecamp." I write as I dream, and though I cannot for certain explain exactly how; it's become a strong part of my mythology that this spectacular rendition of "what ends the silence" has something to do with the magical delivery of "a book" ... something not of this Earth but an unnatural thing; one I've dreamt of creating many times. This book is something like the DSM-IV and something like a Merck diagnostic manual; but rather than the old antiquated cures of "the Norse Medgard" this spectacle nearly "itsimportant" autoprints itself and lands on something like every doorpost; what it is is a list of reasons why "simply curing all disease" with no explanation and no conversation would be a travesty of morality--how it would render us half-blind to the myriad of new solutions that can come from truly understanding why "ITIS" to me has become a kind of magical marker: an "it is special" as in, it's cure could possibly solve a number of other problems.

Through that missing "o," English on the ball, we see a connection between a number of words that shine bright light including Exodus itself which means "let there be light," the word for Holy Fire and the Burning Bush.. .reversed to hSE'Ah, and a story about the Second Coming parting our holy waters.

This answer connects the magical Rod's of Aaron in Exodus and the Iron Rod of Jesus Christ to the Sang Rael itself... in a fusion that explains how the Periodic Table element for Iron links not just to Total Recall and Mars, but also to this key

my dream of what the first day of the Second Coming might be like; were the Rod of Christ... in the right hands. In a story that also spans the Bible, you might understand better how stone to bread and your input make all the difference in the world between Heaven and Adam's Hand. Once more, what do you think He ....

Since the very earliest days of this story, I have asked for better for you, even than see

Nearly all of the original parts of the original "post-origination dream" remain intact; there's a walkway that magically creates new paths and "attractions" based on where you walk, something like an inversion of the artificial intelligence term "a random walk down a binary tree" ... for instance going left might bring you to the Internet Cafetornaseum of the Earl of Sandwich; and going to the right might bring you to the ICIMAX/Auditorium of Science and Discovery--there's a walkway to "Magical GLAS D'elevators" that open a special "instantiation" of the Japan Room of the Potter and the Toolmaker ... complete with a special [second level and hidden staircase] Pool of Bethesdaibo verily delivering something like youth of mind and body ... or at least as close to such a thing as a sip of Holy Water or Ambrosia or a dip in the pool of Coccoon and Ponce De'Leon could instantly bring ... to those that have seen Jupiter Ascending ... the questions of "nature versus nurture" and what it means to be "old and wise" and "young at heart" truly mean---

• https://www.youtube.com/watch?v=M8CyN1awWls
• https://link.springer.com/chapter/10.1057/9780230366688_16
• https://www.youtube.com/watch?v=YDo5zvYNn3A

Somewhere between the outdoor rafting ride and the level with the special "ballroom of the ancient gallery" ... perhaps now being named or renamed or recalled as something about "Face [of] the Music" lies a magical "mini-maize" ... a look at a mock-up (or #isitit) of Merlink and Harthor's "round table" that displays a series of ... (at least to me) magical appearing holographic displays and controls that my dreams have stolen from Phillip K. Dick's Minority Report and something of what I hope Microsoft's Dynamics/Hololens/Surface will become---a series of short "focus groups" .... to guage and discuss the information in the "CITIES-D5AM-MERCK" ... how to end world hunger and nearly all disease with the press of a magical buzzer--castling churches to something like "political-party-town-hall-meeting centers" and replacing jails and prisons and hospitals with something like the "Hospitalier's PRIDE and DOJOY's I practiced "Kung-fun-dance" ... a fusion of something like a hotel and a school that probably looks very much like a university with classrooms and dorms and dining hall's all fit into a single building. I imagine a series of 2 or 3 "room changes" as in you walk from the one where you get the book and talk about it ... to the one where you talk about "what everyone else said about it" and maybe another one that actually connects you to other people with something like Facebook's Portal; the point of the whole thing to really quickly "rubber stamp" the need for an end to "bars in the sky" nonalcoholic connotation--as in "overcoming the phrase the sky is the limit" and showing us the need for a beacon of glowing hope fulfilled--probably actually the vision of a holographic marker turning into actual rings around the single moon of Earth, the focus of the song annoucing the dawn of the age of Aquarius---

It might lead us also to Ceres; and another set of artificial rings, or to Monoceros and a rehystorical understanding of the birthplace and birthing of the "river roads" that bridge the "space gaps" in the galaxy from our "one giant leap for mankind" linking the Apollo moon landing to the mythological connection to the sun; and connecting how the astrological charts of the ancients might detail a special kind of overlapping--the link between Earth's SOL and something like Proxima or Alpha Centauri; and how that "monostar bridge" might overlap to Orion and from there through Sagitarius and the center of the Milky Way ... all the way to Andromeda and more dreams of being in a place where there's a map to a tri-galactic system in the constellation Cancer and a similar one in Leo ... and just incase you haven't noticed it--a special marker here, I thought to myself it might be cool to "make an acronymic tie to Monoceros" and without even thinking auto-wrote Orion (which was the obvious constellation next to Monoceros, in the charts) and then to Sagitarrius; which is the obvious ... heart of our astrological center and link to "other galaxies."

----I've dreamt or scriven or reguessed numerous times how the Milky Way's map to an "Atlas marked through time by the ages and the ancients" might tie this place and this actual map to the creation of the railways between stars to the beginning and the end of time and of course to this message that links it all to time travel. There's a few "guesses" I've contemplated; that perhaps the Milky Way chart is a metal-cosmic or microcosmic map to the dawn of time in the galactic vision of ... just after the big bang; or it might tie to a map of something like the unthinkable--a civilization that became so powerful it was able to reverse the entropy of "cosmic expansion" and reverse the thing Asimov wrote of in "The Last Question" as the end of life and the ability to survive basically due to "heat loss."

"The Last Question." (And if you read two, why not "The Last Answer"?). Find these readings added to our collection, 1,000 Free Audio Books: Download Great Books for Free.

• https://archive.org/details/texts
• http://zlibraryexau2g3p.onion.pet/

Looking for free, professionally-read audio books from Audible.com, including ones written by Isaac Asimov?

* all "asterisks" in the abovə document denote a sort of Adamic unspoken relationship between notations and meanings; here adding the "Latin word for three" and source of the phrase "t.i.d." (which is doctor/pharmacy latin for "three times a day") where the "t" there is an abbreviation of "ter" ... and suppose the link between K and 11 and 3 noting it's alphanumeric position in the English alphabet as the 11th letter and only linking cognitively to three via the conversion between hex, and binarryy ... aberrative here is the overlapping "hakkasan" style (or ZHIV) lack of mention of the answer in "state of Kansas" and the "citystate of Slovakia" as described in the ICANN document linked [in] the related subsection or slice of the word "binarry" for the state of India. Tetris could be spelled with the addition of only a single letter [in] "tea"---the three letters "ris" are the hearts of the words "Christ" and "wrist" [and arguably of Osiris where you also see the round table character of the solar-system/sun glyph and the chemical element for The Fifth Element (as def. by i) via "Sinbad" and "Superman." The ERIS Free Network should also be mentioned here in connection with the IRC network I associate in the place between skipping stones and sacred hearts defined by "AOL" and "Kdice" in my life. In the lexicon of modern HTML, curly braces are generally relative to "classes" and "major object definitions (javascript/css)" while square brackets generally only take on computer-interpreted meaning in "Markdown" which is clearly (by definition, by this character set "[]") a superset (or at least definately not a subset) of HTML.

Dr. Will Caster (Johnny Depp) is a scientist who researches the nature of sapience, including artificial intelligence. He and his team work to create a sentient computer; he predicts that such a computer will create a technological singularity, or in his words "Transcendence". His wife, Evelyn (played by Rebecca Hall), is also a scientist and helps him with his work.

Following one of Will's presentations, an anti-technology terrorist group called "Revolutionary Independence From Technology" (R.I.F.T.) shoots Will with a polonium-laced bullet and carries out a series of synchronized attacks on A.I. laboratories across the country. Will is given no more than a month to live. In desperation, Evelyn comes up with a plan to upload Will's consciousness into the quantum computer that the project has developed. His best friend and fellow researcher, Max Waters (Paul Bettany), questions the wisdom of this choice, reasoning that the "uploaded"

Just from my general understanding and memory "st" is not ... to me (specifically) an abbreviation of "state" but "ste" is a U.S. Postal code (also "as I understand it") for the name of a special room or set of rooms called a "suite" and in Adamic "connotation" I sometimes read it as "sweet" ... which has several meanings that range from "cool" to "a kind of taste sensation" to "easy to sway or fool."

If you asked me though, for instance if "it" was an abbreviation or shorthand notation or acronym for either "a United state" or "saint" ... you'd be sure.

While it's clear from studying linguistic cryptography ... (If I studied it a little here and some there, its also from the "universal translator of Star Trek") and the personal understanding that language is a kind of intelligent code, and "any code is crackable" ... that I caution here that "meaning" and "face value" often differ widely and wildly ... even in the same place or among the same group of people ... either varying over time or heritage.

Menelaus, in Greek mythology, king of Sparta and younger son of Atreus, king of Mycenae; the abduction of his wife, Helen, led to the Trojan War. During the war Menelaus served under his elder brother Agamemnon, the commander in chief of the Greek forces. When Phrontis, one of his crewmen, was killed, Menelaus delayed his voyage until the man had been buried, thus giving evidence of his strength of character. After the fall of Troy, Menelaus recovered Helen and brought her home. Menelaus was a prominent figure in the Iliad and the Odyssey, where he was promised a place in Elysium after his death because he was married to a daughter of Zeus. The poet Stesichorus (flourished 6th century BCE) introduced a refinement to the story that was used by Euripides in his play Helen: it was a phantom that was taken to Troy, while the real Helen went to Egypt, from where she was rescued by Menelaus after he had been wrecked on his way home from Troy and the phantom Helen had disappeared.

• https://www.britannica.com/topic/Menelaus-Greek-mythology

This article is about the ancient Greek city. For the town of ancient Crete, see Mycenae (Crete). For the hamlet in New York, see Mycenae, New York.

Μυκῆναι, Μυκήνη

The Lion Gate at Mycenae, the only known monumental sculpture of Bronze Age Greece

37°43′49"N 22°45′27"ECoordinates: 37°43′49"N 22°45′27"E

This article contains special characters. Without proper rendering support, you may see question marks, boxes, or other symbols.

Mycenae (Ancient Greek: Μυκῆναι or Μυκήνη, Mykēnē) is an archaeological site near Mykines in Argolis, north-eastern Peloponnese, Greece. It is located about 120 kilometres (75 miles) south-west of Athens; 11 kilometres (7 miles) north of Argos; and 48 kilometres (30 miles) south of Corinth. The site is 19 kilometres (12 miles) inland from the Saronic Gulf and built upon a hill rising 900 feet (274 metres) above sea level.[2]

In the second millennium BC, Mycenae was one of the major centres of Greek civilization, a military stronghold which dominated much of southern Greece, Crete, the Cyclades and parts of southwest Anatolia. The period of Greek history from about 1600 BC to about 1100 BC is called Mycenaean in reference to Mycenae. At its peak in 1350 BC, the citadel and lower town had a population of 30,000 and an area of 32 hectares.[3]

3. Chew 2000, p. 220; Chapman 2005, p. 94: "...Thebes at 50 hectares, Mycenae at 32 hectares..."

• https://en.wikipedia.org/wiki/Clymene_(mythology)

Melpomene (/mɛlˈpɒmɪniː/; Ancient Greek: Μελπομένη, romanized: Melpoménē, lit. 'to sing' or 'the one that is melodious'), initially the Muse of Chorus, she then became the Muse of Tragedy, for which she is best known now.[1] Her name was derived from the Greek verb melpô or melpomai meaning "to celebrate with dance and song." She is often represented with a tragic mask and wearing the cothurnus, boots traditionally worn by tragic actors. Often, she also holds a knife or club in one hand and the tragic mask in the other.

Melpomene is the daughter of Zeus and Mnemosyne. Her sisters include Calliope (muse of epic poetry), Clio (muse of history), Euterpe (muse of lyrical poetry), Terpsichore (muse of dancing), Erato (muse of erotic poetry), Thalia (muse of comedy), Polyhymnia (muse of hymns), and Urania (muse of astronomy). She is also the mother of several of the Sirens, the divine handmaidens of Kore (Persephone/Proserpina) who were cursed by her mother, Demeter/Ceres, when they were unable to prevent the kidnapping of Kore (Persephone/Proserpina) by Hades/Pluto.

In Greek and Latin poetry since Horace (d. 8 BCE), it was commonly auspicious to invoke Melpomene.[2]

See also [AREXMACHINA]

• Muses in popular culture
• The Nine Muses

Flagstaff (/ˈflæɡ.stæf/ FLAG-staf;[6] Navajo: Kinłání Dookʼoʼoosłííd Biyaagi, Navajo pronunciation: [kʰɪ̀nɬɑ́nɪ́ tòːkʼòʔòːsɬít pɪ̀jɑ̀ːkɪ̀]) is a city in, and the county seat of, Coconino County in northern Arizona, in the southwestern United States. In 2018, the city's estimated population was 73,964. Flagstaff's combined metropolitan area has an estimated population of 139,097.

Flagstaff lies near the southwestern edge of the Colorado Plateau and within the San Francisco volcanic field, along the western side of the largest contiguous ponderosa pine forest in the continental United States. The city sits at around 7,000 feet (2,100 m) and is next to Mount Elden, just south of the San Francisco Peaks, the highest mountain range in the state of Arizona. Humphreys Peak, the highest point in Arizona at 12,633 feet (3,851 m), is about 10 miles (16 km) north of Flagstaff in Kachina Peaks Wilderness. The geology of the Flagstaff area includes exposed rock from the Mesozoic and Paleozoic eras, with Moenkopi Formation red sandstone having once been quarried in the city; many of the historic downtown buildings were constructed with it. The Rio de Flag river runs through the city.

Originally settled by the pre-Columbian native Sinagua people, the area of Flagstaff has fertile land from volcanic ash after eruptions in the 11th century. It was first settled as the present-day city in 1876. Local businessmen lobbied for Route 66 to pass through the city, which it did, turning the local industry from lumber to tourism and developing downtown Flagstaff. In 1930, Pluto was discovered from Flagstaff. The city developed further through to the end of the 1960s, with various observatories also used to choose Moon landing sites for the Apollo missions. Through the 1970s and '80s, downtown fell into disrepair, but was revitalized with a major cultural heritage project in the 1990s.

The city remains an important distribution hub for companies such as Nestlé Purina PetCare, and is home to the U.S. Naval Observatory Flagstaff Station, the United States Geological Survey Flagstaff Station, and Northern Arizona University. Flagstaff has a strong tourism sector, due to its proximity to Grand Canyon National Park, Oak Creek Canyon, the Arizona Snowbowl, Meteor Crater, and Historic Route 66.

PSANSDISL #LWDISP either without gas or seeing cupidic arroz in "thank you" or "allta, wild" ...

pps: a magnanimous decision ...

I stand here on the brink of what appears to be total destruction; at least of everything I had hoped and dreamed for ... for the last decade in my life which appears literally to span thousands of years if not more in the eyes of some other beholder. I spent several months in Kentucky telling a story of a post apocalyptic and post-cataclysmic delusion; some world where I was walking around in a "fake plane" something like a holodeck built and constructed around me as I "took a walk around the world" to ... it did anything but ease my troubled mind.

Recently a few weeks in Las Vegas, and a similar story; telling as I walked penniless down the streets filled with casino's and anachronistic taxi-cabs ... some kind of vision of the entirety of the heavens or the Earth or the "choir of angels" I think of when I echo the words Elohim and Aesir from mythology ... there with me in one small city in superposition; seeing what was a very well put together and interesting story about a "star port" Nirvane ... a place that could build cities into the face of mountains and half working monorails appearing in the sky---literally right before my eyes.

I suppose this is the place "post cataclysm" though I still have trouble understanding what it is that's actually about ... in my mind it connects to the words "we are losing habeas" echo'ed from the streets of Los Angeles in a more clear and more military voice than usual--as I walked block by block trying to evade a series of events that would eventually somehow connect all the way to the "outskirts of Orlando, Florida" in a place called Alhambra.

Apparently the name of a castle; though I wasn't aware of that until much later.

It doesn't feel at all like a "cataclysm" to me; I see no great rift--only a world filled with silent liars, people who collectively believe themselves to have stolen something--something gigantic--at least that's the best interpretation of the throws and impetus behind the thing that I and mythology together call Jormungandr. With an eye for "mythological connections" you could clearly see that name of the Great Serpent of Revelation connects to something like the Unseelie; the faeries of Gaelic lore. To me though this world seems still somewhat fluid, it's my entire life--moving from Plantation to a place where the whole of it might be Bethlehem and to "clear my throat" it's not hard to see here how that land of "coughs" connects to the Biblical land of Nod and to the "Adamically sieved" Snifleheim ... from just a little twist on the ancient Norse land most probably as close to Hel as anyone ever gets--or so I dream and hope---still today. It all looks so real and so fake at the same time; planned for thousands of generations, the culmination of some grand masterpiece story that certainly ties history and myth and reality into a twisted heap of "one big nothing, one big nothing at all."

I've tried to convey to the world how important I believe this place and this time to be--not by some choice of my own ... but through an understanding of the import of our history and the impact of having it be so obviously tuned and geared towards this specific time ... many thousands of years literally all focused on a single moment, on one day or one hour or even just a few years where all of that gets thrown down on the table as if some trump card has been played--and whether or not you fathom the same magnanimous statement or situation or position ... to me, I think it depends on whether or not you grew up in the same kind of way, believing our history to be so fixed and so difficult to change. I don't particularly feel like that's the "zeitgeist" of today; I feel like the children believe it to be some kind of game, and that it is such as easy thing to "sed" away or switch and turn into something else--another story, another purpose ... anyone's personal fantasy land come true.

I don't think that's the case at all, it's clearly a personal nightmare; and it's clearly one we've seen time and time again--though not myself--the Jesus Christ that is the same yesterday, today; and once again perhaps echoing "no tomorrow" never remembers or believes that we've "seen it all before" or that we've ever really gotten the point; the thing you present to me as "factual reality" is a sickness, it disgusts me; and I'd do anything to go back to the world "where I was so young, and so innocent" and so filled with starry-eyed hope that we were at the foot of something grand and amazing that would become an empire turned republic of the heavens; filling the stars ... with the kind of love for kindness and fairness that I once associated very strongly with the thing I still believe to be the American Spirit.

"Suddenly it changes, violently it changes" ... another song echoes through the ages--like the "words of the prophets dancing ((as light)) through the air" ... and I no longer even have a glimmer of hope that the thing I called the American People still exist; I feel we've been replaced by some broken container of minds, that the sky itself has become corrupt to the point that there's no hope of turning around this thing that I once believed with all my heart and all my mind was so obviously a "designed downward spiral" one that was---again--so obviously something of a joke, intended to be easy to bounce off a false bottom and springboard beyond "escape velocity" and beyond the dark waters of "nearest habitable star systems (being so very far away)" into a place where new words and new ideas would "soar" and "take flight."

Here though; I am filled with a kind of lonely sadness ... staring at what appears to be the same mistake(s) happening over and over again; something I've come to call "skipping stones in the pond of reality" and really do liken it to this thing that appears to be the new meaning of "days" and ... a civilization that spends absolutely no love or lust to enter a once sacred and holy place and tarnish it with their sick beliefs and their disgusting desires. You all ... you appear to be some kind of springboard to "bunt" forth yet another age or era of nothingness into the space between this planet and "none worth reaching" and thank God, out of grasp. Today, I'd condemn the entirety of this world simply for it's lack of "oathkeepers" and understanding of what the once hallowed words of Hippocrates meant to ... to the people charged and dharmically required to heal rather than harm.

It appears the place and time that was once ... at least destined to be the beginning of Heaven ... has become a "recurring stump" of some future unplanned and tarnished by many previous failed efforts and attempts to overcome this same "lack of conversation or care" for what it meant to be "humane" in a world where that was clearly set high aloft and above "humanity" in the place where they--where we were the best nature had to offer, the sanest, the kindest; the shining last best hope.

Today I write almost every day ... secretly thanking "my God" for the disappearance of my tears and the still small but bright hope that "Tearran" will one day connect the Boston Tea Party and the idea that "render to Caesar" and Robin of Loxley ... all have something to do with a re-ordering of society and the worth and import of "money" ... to a place that cares more for freedom from murder than it does ... "freedom from having to allow others to hear me speak." I hold back tears and emotions; not by conscious choice or ability but ... still with that strange kind of lucky awkward smile; and secretly not so far below the surface it's the hope of "a swift death" that ... that really scares me more than the automatons and mechanical responses I see in the faces of many drivers as they pass me on the street--the imagery of connecting it to the serpentine monster of the movie Beetlejuice ... something I just "assume" the world understands and ... doesn't seem to fear (either); as if Churchill had gotten it all wrong and backwards--the only thing you have to fear, is the loss of fear of "loss."

Here my crossroads---halfway between the city my son lives in and the city my parents live in--it's on making a decision on whether I should continue at all, or personally work on some kind of software project I've been writing about, or whether I should focus on writing about a "revolution" in government and society that clearly is ... "somewhat underway." In my mind it's obvious these things are all connected; that the software and the governance and the care of whether or not "Babylon" is remembered as a city of great laws and great change or a city of demons and depravity ... that these thi]ngs all hinge and congeal around a change in your hearts; hoping you will chose to be the beginning of a renaissance of "society and civilization" rather than the kings and queens of a sick virtual anarchy ... believing yourselves to have stolen "a throne of God" rather than to literally be the devastating and demoralizing depreciation of "lords and fiefdoms" to something more closely resembled by the time of the Four Horsemen depicted in Highlander.

These words intended to be a "forward" to yet another compliment of a ((nother installment of a partial)) chain of emails; whimsically once half-joking ... I called it the Great Chain of Revelation. The software too; part of the great chain, this "idea" that the blockchain revolution will eventually create a distributed and equal governance structure, and a rekindling of monetary value focused on "free and open collaboration" rather than "survival of the most unfit"--something society and civilization seem to have turned the "call of life" from and to ... literally just in the last few years as we were so very close to ... reaching beyond the Heaven(s).

I don't think its hard to imagine how a "new set of ground rules" could significantly change the "face of a place" -- make it something shiny and new or even on the other side of the coin, decayed or depraved. It's not hard to connect the kind of change I'm hoping for with "collision protection" and "automatic laws" to the (perhaps new, perhaps ... ancient) Norse creation story of the brothers of Odin: Vili and Ve.

It might be hard to see today how a new "kind of spiritual interaction" might be only a few "mouse clicks" away though--how it could change everything literally in a flash of overnight sensation ... or how it might take something like a literal flash of stardom (or ... on the other hand, something like totalitarian or authoritarian "iron fisting") to make a change like this "ubiquitious" or ... something like the (imagined in my mind as ... messianic) "ED" of storming through the cosmos or the heavens and turning something that might appear to be "free and perfect feeling" today into a universe "civlized overnight" and then ...

I wonder how long it would take to laud a change like that; for it to be something of a voluntary "reunderstanding" of a process ... to change the meaning of every word or every thought that connects to the process of "civilization" to recognize that something so great and so powerful has happened as to literally change the meaning of the word, to turn a process of civilization into something that had a ... "signta-lamcla☮" of forboding and then a magical staff struck into the heart of a sea and then ... and then the word itself literally changes to introduce a new "mid term" or "halfway point" in which a great singularity or enlightenment or change in perspective or understanding sort of acknowledges ...

that some "clear outside" force not only intervened on the behalf of the future and the people of our world but that it was uniquely involved in the whole of--

"waking up" tio a nu def of #Neopoliteran.

^Like the previous notation; the below text comes from an email previously sent; and while i stand behind things like my sanity, my words; and my continued and faithful attempt to speak and convey both a useful and helpful truth to the world---sometimes just a single day can make all the difference in the world.

Sometimes it's just a single moment; a flash or a comment about ^th@ blink of an eye" ... and I've literally just "thought up/had/experienced/transitioned thru" that exact moment. The lies standing between "communication" and either "cooperation" or .... some other kind of action have become more defined. More obvious. Because of this clarification; like a kind of "ins^tant* gnosis"

... search high and lo ... the depths all the way to above the heavens ...\ \ for a festive divorce ceremonial ritual ... that looks something like a bachelor party ':;]

--- @amrs@koyu.SPACe ... @suzq@rettiwtkcuf.social (@yitsheyzeus) May 22, 2020

I ... TERON;

Gjall are painting me into a corner here; and I don't see around it anymore--I don't see the light, and I don't see the point. I was a happy-go-lucky little kid in my mind; that's not "what I wanted to be" or what I wanted to present, it's who I was. I saw "Ashkenazi" and ... know I am one of those ... and I kind of understood that something horrible might have happened, or might happen here--and I kind of understand that crying smashing feeling of "to ash" that echoes through the ages in the potpourri songs about pockets full of Parker Posey .. and ancient Psalms about "from the ashes of Edom" we have come--and from that you can see the cyclical sickness of this ... place so sure it's "East of Eden" and yet gung-ho on barrelling down the same old path towards ash and towards Edom and towards ... more of Dave's "ashes to ashes dust to dust" and his "smoke clouds roll and symphony of death..." and few words of solace in a song called Recently that I imagine was fleeting and has recently come and gone--people stare, I can't ignore the sick I see.

I can't ignore his "... and tomorrow back to being friends" and all but wonder who among us doesn't realize it's "ash" and "gone" and "no memory of today" that's the night between now and ... a "tomorrow with friends" not just for me--but for all of you--for this place that snickers and pantomimes some kind of ... anything but "I'm not done yet" and "there's more ... vendetta ... and retribution to be had, Adam ... please come back in a few more of our faux-days." This is sickness; and happy-go-lucky Himodaveroshalayim really doesn't do much but complain about that word, the "sickle" and the tragic unavoidable ... ash of it all ... these days--you'd think we could "pull out" of this mess, turn another way; smile another day, but it seems there's only one way to get to that avenu in the mind of ... "he who must not know or be me."

I have to admit I found some joy in the epiphany that the hidden city of Zion and it's fusion with the Namayim' version of how that "Ha" gels and jives with the name Abraham and the Manna from Heaven and the bath salt and the tina and the "am in e" of amphetamine--maybe a glimmer or a shimmer or a glow of hope at the moment "Nazion" clicked ... and I said ... "no, not me ... I'm nothing like a king, no dreams of authoritarianism at all in the heart of Kish@r;" even as I wrote words that in the spirit of the moment were something of a "tis of a'we" that connected to my country and the first sing-songy "tisME" that I linked to trying to talk in the rhyming spirit of some "first Christ" that probably just like me was one limmerick away from the end of the rainbow and one "Four Non Blondes" song away from tying "or whatever that means" and this land crowned with "brotherhood" (to some personal "of the Bell, and of the bell towers so tall and Crestian") to just one Hopp skip and jump away from the heart of the obvious echoes of a bridge between haiku and Heroku... a few more gears shift into place, a click and and a mechanical turn of the face of the clock's ku-ku striking ... it was the word "Earthene" that was the last "Jesusism" around the post Cimmerian time linking Dionysus and Seuss to that same "su-s" that's belonging to a moment in the city of Uranus--codified and etched in stone as "MCO"--not just for its saucer and warp nacelles and "deflector dish" but for it's underground caverns and it's above ground "Space Mountain" and that great golf ball in the heart of it all.

The gears of time and the dawns of civilizequey.org query the missing "here" in our true understanding of what "in the beginning, to hear; to here ... to rue the loss of the Maize from Monoceros to the VEGA system and the tri-galactic origin of ... "some imaginary universal ... Earthene pax" to have dropped the ball and lost it all somewhere between "Avenu Malkaynu" and melaleuca trees--or Yggrasil and Snifleheim--or simply to miss the point and "rue brickell" because of bricks rather than having any kind of love or nostalgia linking to a once cobblestone roadway to the city in the Emerald skies paved in golden "do not return" signs ... to have lost Avenues well after not realizing it was "Heaven'es that were long gone far before I stepped foot on this road once called too Holy for sandals" in a place where that Promised Land and this place of "K'nanites" just loses it's grip on reality when it comes to mentioning the possibility that the original source and story of Ca'anan was literally designed to rid the world of ... "bad nanites" and the mentality of ... vindictiveness that I see behind every smirk.

The final hundred nanoseconds on our clock towards doom and gloom cause another bird to fly; another snake to curl up and listen again to the songs designed to charm it into oblivion; whether that's about a club in South Beach or a place not so far from our new "here..." all remains to be seen in my innocent eyes wondering what it truly is that stands between what you are ... and finding "forgiveness not needed--innocent child writes to the mass" ... and the long arm of the minute hand and the short finger of the hour for one brief moment reconcile and move towards "midnight" together; and it's simply idyllic, the Nazarene corner between nil and null you've relegated the history of Terran poast futures into ... "foreves mas" or so they (or you) think.

I'm still so far from "Five Finger Death Punch" though; and so far from Rammstein and so far from any kind of sick events that could stand between me and "the eternal" and change my still "casual alternative rock" loving heart to something more death metal; I rue whatever lies between me and there being any kind of Heaven that thinks there could exist a "righteous side" of Hell and it... simultaneously.

I still see light here in admonishing the masses and the angels standing against the story and the message God brings us in our history. I still see sparks in siding with the "causticness" of "no holodecks in sight" and the hunger and the pain of simulating ... "the hells of reality" over the story of decades or centuries of silence refusing to see "holography" and "simulated" in the word Holocaust and the horrors of this place that simply doesn't seem to fathom or understand the moments of hunger pangs and the fear of "dark Earth pits" or towers of "it's not Nintendo-DS" linking the Man in the High Castle to an Iron Mask.

I rally against being what I clearly am raised high on some pedestal by some force beyond my comprehension and probably beyond that of the "perfect storm in time" that refuses to itself acknowledge what it means to gaze at such an unfathomable loss of innocence at the cost of a "happy and serene future" or even at the glimmer of the Never-Never-Land I'd hoped we would all cherish and love and share ... the games and the newfound freedom that comes not just from "seeing Holodeck" turn into "no bullets" and "no cages" but into a world that grows and flourishes into something that's so far beyond my capability to understand that I'm stuck here; dumbfounded; staring at you refusing to stop car accidents and school shootings ... because "pedestal." For the "fire and the glory" of some night you refuse to see is this one--this place where morality rekindles from ... from what appears tobe one small candle, but truly--if it's not in your heart, and it's not coming from some great force of goodness--fear today and a world of "forever what else may come."

Here in a place the Bible calls Penuel at the crossing of a River Jordan ... the Angel of the Lord notes the parallels in time and space between the Potomac and the Rhine--stories of superposition and cities and nation-states that are nothing more than a history of a history of things like the Monoceros "arroz" linking not just to the constellation Orion but to Sagittarius and to Cupid and of course to the Hunter you know so well--

Searching for a Saturday; a sabbath to be made Holy once more ... "at the Rubycon"

The Einstein-Rosen Wormhole and the Marshall-Bush-JFKjr Tunnel

The waters are called narah, (for) the waters are, indeed, the offspring of Nara; as they were his first residence (ayana), he thence is named Narayana.

--- Chapter 1, Verse 10[3]

In a semi-fit of shameless arexua-self recognition i'm going to mention Amazon's new series "Upload" and connect it to the PKD work that my Martian-in-simulcrum-ciricculum-vitae on "colonization education" ... tying together Transcendance, Total Recall and ... well; to be honest it actually gave me another "uptick" in the upbeat ... maybe i'll stick around until I'm sure there's at least one more copy of me in the ivrtual-invverse ... oh, that reminds me ... Farmer)'s Lord of Opium also touches on this same "mind of God in the computer" subject (which of course leads to Ghost in the Shell and Lucy--thanks Scarlette :).

While I'm listing Matrix-intersected pieces of the puzzle to No Jack City, Elon Musk's neuralace and Anderson's Feed are also worth a mention. Also the first link in this paragraph is titled ... "the city of the name of time never spoken after time woke up and stfu'd" (which of course is the primary subject of this ... update to the city Aerosol).

The ... "actual original typed dream" included a sort of "roller coaster ride" through space all the way to Mars; where the real purpose of "the thing" I am calling the "Mars Hall" was to display previous victories and failures ... and the introduction of "older or future" culture's suggestions for "the right way" to colonize a new habitat. If it were Epcot Center, this would be something like SpaceMountain taking you to to the foture of "Epcot Countries" as if moving from "countries" to planets were as easy as simply ... "reading backwards."

THE SOFTWARE, SINGERS, AND SHIELD(S)

OF

HEIROSOLYMITHONEYY

Thinking just a little bit ahead of myself, but I'm on "Unreal Object/Map Editor within the VR Server" and calling it something like "faux-wet-ware" ... which then of course leads to a similar onomonopeia of "weapons and ..." where-with-all to find a better singer's name to connect the road of "sword" to a Wo'riordan ... but I think that fusion of warrior and woman probably does actually say ... enough of it all; on this road to the living Bright Water that the diety in my son's middle name defines well here, as "waking up," stretching it's tributaries and it's winding wonders and wistfully ....

Narayana (Sanskrit: नारायण, IAST: Nārāyaṇa) is known as one who is in yogic slumber on the celestial waters, referring to Lord Maha Vishnu. He is also known as the "Purusha" and is considered the Supreme being in Vaishnavism.

andromedic; the ports of call ... to the mediterranean (literally) from the gulf coast;

... ho engages in the creation of 14 worlds within the universe as Brahma when he deliberately accepts rajas guna, himself sustains, maintains and preserves the universe as Vishnu by accepting sattva guna. Narayana himself annihilates the universe at the end of maha-kalp ...

.

there's no place like home. there's no place like home. there's no place like home.

and so it begins ... "f:

r e l i g i o n

find out what it means to me. faucet, ever single one, stream of purity ...

from Fort Myers ... f ... flicks ... Flint.

"

^this notation will from this email forward in linear time denote some form of contact method or information related to the context of the message you are reading. This particular one sends me an encrypted email. 5if there is an "@" symbol involved in the "anchor's hypertext reference" (technically an "a href=" in HTML4) your browser should attempt to open an email client to send a message over an anonymous SMTP relay. Understand that "anonymous" in this case may or may not mean your sending email address is hidden or obvuscated--so if you want to receive a reply you must include it in the DATA of your SMTP transmission defined by the RFC5321 attached. In most cases "anonymous" also means that you will not have the recipients direct contact information unless they have made it public---additionally the exact server/system/relay used may or may not be the "Sbroken Berkman Perl Script" linked to in the "hypertext reference" specifically anchored to the words "an anonymous SMTP relay" above.

A simple "hat character" (^) and the letter "t" as you see beginning the above paragraph will denote a contact method or form that works over the internet using an HTTP protocol defined in a series of RFC's including (but not limited to) RFC's numbered as 2616, 7230, 7235, 2068 and use a simple language which is based on a definition suggested or proposed currently by an organization called the "W3C Consortium"

---and ... previously set and defined by an organiza^tion located at html.spec.whatwg.org; which appears (to me, for the first time as I write these words) to follow the conceptual spirit of the "living document" defined by the several "Continental Congresses, et alia." I personally now conjoin this document in my head to a procession of patrilineal or matrilnear predecessors to the actual event .... still to be defined ... but related to this specific email, this mailing list; its contributors and readers as well as actual members of the organization (still to be created, defined, or named) that creates a "round table" of members that is open to the public, to all voters educated enough to understand the specific issue being voted on (up to a standard that; in this place and time appears to be unset and unmet but materially related to reawching the age of 18 years old; growing up in or being born in the United States of America (related spec. to the Constitution of the United States of America which is officially "self-defined" through a process which includes all three branches of the government which it also "self-defines" and purports to be "of, for, and by the people"--though the general population is only able to contribute through an indirect process (read:the people cannot directly contribute to the constitution without either running for office (like a senator) or being appointed to a specific government position (like a judge or executive branch public servant).

The current state of American representative democracy is the highest standard to which I am currently knowledgable of "extant"--and it is specifically substandard, inferior, and "just not good enough" as a comparison to the process required to vote in the organization being "self-defined" through this process*. It is my sincere and clear hope that "this process" will result in a legal and moral amendment to the document shown in the previous link and presented by the Legislative Branch of the United States here. It is my current and faithful belief that anything else would also be significantly below the standards morally required by "this process" which of course includes over 200 years of American citizenship and (other international relations; i.e., e.g, for "iv" example, id est, exemplia gratia) as well as the Sons of Liberty and prior to that contributions from the Crown and the "Parliament and Crown" of the United Kingdom; among others et alea's ifndef: 'swikipedia/et_al..

To note specifically because of lack of personal knowledge and public notoriety (assuming all other requiremnant* achem requirements)

alas, babylon.

i listened to a man yesterday who was talking about "true heroes" ... he of course noted jesus christ and superman together, suggesting the first was one, and the second just a fiction. he also talked about people like ghandi and "leaders who use non-violent means to "change the world." i at least agree with him on the third, ghandi is a good prototype for some kind of hero. staring at this ... "to be completed" work on tales of two cities, whether from sodom and gomorrah all the way to athens and sparta and perhaps even london and paris--and this particular city, babylon; it stands out as one which truly has no equal or even "mirror" in the history of the world. i suppose i'd add "alexandria" and suggest the library and the laws; something that are fundamental to the ethos of the planet i call "athens."

i imagine he did not know "hammurabi's" name; and even today in this place where i ask and do not receive answers; i imagine you still don't connect muhammad or amsterdam ... to this king who in our history is set apart and lifted high on a pedestal of having "codified and written down" laws ... for the very first time. it's almost comical, it took me a paragraph and a sentence to connect "the king and i" to this mirror world, where the bible and the people have most assuredly decided "babylon" is a negative thing or a depraved place.

"fallen, fallen, is [the city of] babylon the great"

... just a quote from one of my favorite movies; which of course is re-quoting "dante" and/or "the bible"

"a dwelling place [of] (the) demons (say), it has become."

• www.icann.org/news/blog/the-problem-with-the-seven-keys

• kauri on IPFS: has-abaslom-and-the-ethos-of-arcadia

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

We would like to thank the Review Commons editor and three reviewers for their enthusiastic response, including their constructive suggestions and appreciation of the high impact and originality of our study. We have completed the revisions and new analyses suggested by the reviewers, and we thank the reviewers for their suggestions to increase the impact and interest in this work and for guiding us towards this much improved manuscript.

In this response letter, we present the response to each reviewer comment and associated revisions made to the text and figures as bullet points below the reviewers' text (black text).

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

Summary:

Yang et al. took advantage of recently published long-read-based genomic sequences of nearly homozygous genomes from complete hydatidiform moles to retrieve allelic sequences of LINE-1, the currently only active and autonomous retrotransposon of the human genome, and produced the repertoire of intact LINE-1 in a genome. The authors performed cell-culture-based retrotransposition assays measurements and in vivo fitness estimations of all identified intact LINE-1 to infer evolutionary dynamics. In this article, the authors further validate the major contribution of polymorphic LINE-1 to the de novo retrotransposition events in the human genome. They also described, at unprecedented resolution, allelic variations among LINE-1 loci and the potential impact of these variations to the interpretation of mutagenic potential of each LINE-1 locus.

Major comments:

1 - The key conclusions of the article are mostly convincing. However, it would be a substantial improvement to consolidate the data of the article with information about known active LINE-1s in germ cells or in cancer by using data from recent publications of the Devine and Tubio labs (for example PMID: 34772701, 32024998, 25082706). Across the article, no mention is made of the transductions generated during LINE-1 de novo retrotransposition, which is instrumental to monitor in vivo activity of a group of LINE-1 active copies. It would be of particular interest to make a link between in vitro activity from this study with LINE-1 classification based on their observed activity in cancer (PMID: 32024998, Figure 3b).

• We thank this and the other reviewers for this suggestion. We agree that a more explicit comparison to the often-reported counts of 3’ transductions would be a valuable addition to our analyses. We have added the 3’ transduction counts from PMID:34772701, PMID:32024998 and PMID:25082706 to Table S2 (column Y, Z and AA), and made a comparison between these data and our Hamming-distance-based in vivo activity, as the new Figure S5. We found correlations between the two measurements in a significant proportion of LINE-1s, but some interesting exceptions exist which likely reflects the fact that most catalogued 3’ transductions come from cancer genomes, and cancer and germline cells represent distinct cellular environments in which distinct sets of LINE-1s are able to replicate (and leave 3’ transductions). In addition to the new figure (Figure S5), we have added a discussion paragraph focused on this interesting comparison.

2 - The use of CHM1 BAC library Sanger sequencing validation and comparison with CHM13 and hg38 sequences is instrumental to support the building of LINE-1 repertoire in CHM1 genome, which is a valuable contribution of the article. The use of a distance-based metric to infer fitness of a LINE-1 is an interesting approach and allow to group LINE-1 copies based on their in vivo activity potential. Again, it would be beneficial to correlate the inferred fitness and retrotransposition activity of copies/alleles, when known, from the above-mentioned literature.

• The sequence validation of LINE-1 sequences in CHM1 is an important point which we have addressed in the edited manuscript. Specifically, we used three forms of sequence validation including end-sequencing of one clone of each LINE-1 after it was cloned into the retrotransposition vector and whole-plasmid sequencing of select LINE-1s with discrepant activity amongst the three clones we assayed. In addition, we sequenced the entire LINE-1 sequence for four LINE-1s which had the largest number of mutations relative to their allelic counterpart in CHM13. Please see the above response to ‘Major comment 1’ for details of our new analysis comparing the previous literature to our data.

3 - Some aspects of the writing of the article should be improved to better support the conclusions.

• We thank the reviewer for providing these examples of parts of the text that were particularly difficult to read and comprehend. We have deeply streamlined and improved the text throughout the manuscript based upon detailed editing for readability and clarity by two experienced scientific writers. Below, we detail how we revised the particular sections presented by the reviewer, but we think the entire manuscript is now more succinct and clearer.

• In general, the descriptions are dense, and details could be provided in a more direct way to lighten the results section. Several redundancies in the discussion can be combined to increase clarity.

• We have spent considerable time tightening up the text, including removing several overlapping sections from the discussion which can be seen in the included version with changes tracked.

• There is a lack of clarity in the description of how was handled each pair of alleles for which retrotransposition measurements vary between the study and the literature (last paragraph of the "Comprehensive measurement of LINE-1 in vitro activity in a human genome" section). It is not completely clear how the analysis was done and the way the data is presented in File S3 is not helping to support the conclusion. It could be useful to include some illustrative examples in a panel of Figure 2.

• We agree that this description was hard to parse, and we have rewritten this and accompanying methods to simplify our explanation of these results. In addition, we have revised Figure 2 to show the data in much more detail. To further aid the logic flow related to this section, we moved the previous Figure 5B to Figure 2B, updated it with more suitable examples and edited the associated descriptions.

• Regarding inferred in vivo activity, the text contains alternative description with the use of "fit" / "unfit", in vivo "active" / "inactive" or "no closely related LINE-1s" terms. The authors should find a way to clearly define and systematically use one set of terms to enhance clarity along the article. To parallel with in vitro active/inactive, it would be useful to use in vivo fit/unfit.

• We thank the reviewer for this suggestion and agree with their suggested unified use of ‘in vivo fit/unfit’. To clarify and simplify these terms as much as possible, we added detailed explanations of in vivo / in vitro activity and systematically defined in vitro "active/inactive" (page 5, right column, line 50) and in vivo "fit/unfit" (page 8, left column, line 26) at their first appearance in the article, and we changed most instances of "in vivo activity" to "in vivo fitness" when context permits.

4 - The authors suggest that in vitro activity can be predicted by integration of population frequency and in vivo activity (/fitness) (second paragraph of the "An analysis of LINE-1 evolutionary history [...] and in vivo activity" section). It would be beneficial to strengthen the writing of this section and ultimately validate/test the model by including data from some of the previous studies (e.g. Brouha 2003, Lutz 2003, Seleme 2006, Beck 2010, Rodriguez-Martin 2020, Chuang 2021).

• We have thoroughly revised this section of the results (see response to ‘Major comment 3’ above), per the reviewers suggestion, to increase reader comprehension of this important data. In addition, we greatly appreciate the reviewer’s suggestion of a very interesting experimental direction – moving beyond a single long-read-based genome to many diverse genomes, and ultimately calculating the in vivo fitness of the LINE-1s from these diverse genomes. For a long time this has not been possible, but the recent publication of the Human Pangenome presents an opportunity to study this interesting question. Though beyond the scope of this paper, our lab is actively working on this fascinating question, and we appreciate the reviewer’s shared interest in this question.

5 - The identification of adaptive mutations is only partially described and not strongly supported by experimental or analytical data. It would be interesting to explore the role of phylogenetically informative sites described in Figure 5B/C by testing non CHM1 alleles in retrotransposition assay (by introducing amino acid changes into the cloned CHM1 LINE-1 alleles) or by positioning the sites in ORF1p or ORF2p structure and/or domains to infer impact on functionality.

• The reviewer rightly points out that this is one of the most interesting and novel findings of our manuscript. However, the testing of potentially adaptive mutations is potentially complicated and nuanced. Specifically, we don’t know the mechanism by which these mutations might be adaptive. It is possible that they simply increase in vivo germline retrotransposition activity and this increase would be reflected by an increase of in vitro retrotransposition activity. However, another possibility is that these adaptive phenotypes only show themselves in vivo or in the context of the host restriction factors expressed in the germline. We strongly agree with the reviewer that experimental and analytical data on the phylogenetic informative sites associated with the Figure 5 phylogeny is the key to finding out the mechanisms for these changes to affect LINE-1 activity/fitness, and we are, indeed, exploring this very question in the lab now with related projects. We respectfully suggest that these (extremely cool) experiments are beyond scope of this paper, but we have also added some more detailed description and analyses of the potentially adaptive LINE-1 variations from Figure 5 (from page 9, right column, line 50 to page 10, left column, line 5).

Minor comments:

1 - Regarding the in vitro retrotransposition assay, it would be beneficial to provide more data. The current Figure 2 could be enriched by the addition of data related to the variation in the replicates of the experiment (technical but mostly biological with the three clones per LINE-1 tested). Figure 2 could include a dashed line for 100% L1RP and 5% (since it is used as a threshold). It would be useful to provide an additional panel in Figure 2 to illustrate alleles of LINE-1 that are active in this study and compare the values obtained previously in other studies. Similarly, a supplemental table or alignment could be provided to document amino acid changes in the two alleles of each pair (see comment above in the Major Comment 5). The L1Hs subfamilies could also be included in the graph of Figure 2 to support the conclusions of remaining active old L1Hs at allelic forms in the human genome.

• Upon consideration of this helpful comment, we now augment the presentation of our in vitro activity data with a remade Figure 2 with boxplots to show the variation of the data, as well as a horizontal dashed line showing the active-cutoffs and star signs showing which LINE-1s belong to L1Hs or L1PA2.

2 - Also, the validation of cloning is not well described. The choice of PCR validation must be supported by more technical details on the design of the primers used to validate each copy. The authors should clearly state that the strategy chosen for retrotransposition assay does not rely on the transcription from LINE-1 5UTR but from an upstream strong promoter, ruling out the role of potential mutations in LINE-1 promoter.

• As detailed above in the response to ‘Major Comment 1’, we used a combination of end sequencing, whole plasmid sequencing, and multi-read Sanger sequencing to validate the sequences of each LINE-1 cloned from a CHM1 clone. When cloning each LINE-1, we used a specific set of primers designed for the ends of the UTRs for each LINE-1. We have updated the methods and text to clarify this cloning step, and the sequences of these oligos are included in Table S2.
• To clarify the fact that our retrotransposition assays use a common, strong promoter, we added text in several places stating this setup and discussing (paragraph that starts at page 11, right column, line 18) how 5'UTRs and other non-ORF factors can affect the rate of LINE-1 in vitro activity.

3 - There are discrepancies with the reported numbers of LINE-1s between Figure 1A and Table S1: 154 vs. 151 in CHM1, 144 vs. 143 in CHM13, respectively.

• We thank the reviewer for spotting this error on our part. The numbers in Figure 1 and the main text were correct, and we have revised Table S1 to reflect this data.

4 - The choice of colors in Figure 3 is not perfectly clear and sometimes not as reported in the text (green highlight and orange highlight). Part of the Figure 3 legend is missing. It should include a description of the color code chosen for the right histogram.

• We thank the reviewer for bringing this inconsistency to our attention. Based upon feedback from all reviewers, we have simplified the color scheme in Figure 3 and Figure 5 to focus on the core conclusions of these two figures. Specifically, in Figure 3, we have removed the quadrant shading and more clearly presented the cutoffs of ‘polymorphic/high frequency’ and ‘in vitro active/inactive’ as dashed lines in the scatter plot. In Figure 5, we have simplified to two colors – black for in vivo unfit and orange to show the in vivo fit LINE-1s which is also used in Figure 4 to show the definition of in vivo activity. These updated colors are now defined in the figure legends and main text, and we have made references to these colors consistent throughout.

5 - For Figure 4, it would be useful to define in the legends the color code for the top histogram. To better read the scatter plot, the words "fit" and "unfit" could be added on each side of the vertical dashed line.

• We thank the reviewer again for suggestions to improve the clarity of our figures. As mentioned above in ‘Minor comment 1’, we have removed unnecessary colors including the gradient of the histograms in Figure 3 and Figure 4, since the boundaries of each bin are already defined by the axis labels and tics. As suggested, we have also added ‘fit’ and ‘unfit’ labels to the dashed cutoff line in Figure 4 to clarify the meaning of this line.

6 - In panel B of Figure 5, it seems that the color code and hot/cold description is not fully formatted.

• This formatting error has been corrected.

Reviewer #1 (Significance (Required)):

In this article, Yang and colleagues present an unprecedented view of the allelic diversity of young LINE-1 copies related to variable retrotransposition activity in an individual genome. One key aspect of their work is the description of the presence of young active LINE-1 alleles that are absent or non-intact in other genome assemblies, while described at a lower scale in initial work from the Kazazian and Moran labs, cited in the manuscript. The work of Yang et al. demonstrates the requirement of multiple approaches and long-read-based sequencing of individual genomes to fully infer the mutagenesis risk of LINE-1 activity.

The data and methods provided by the authors open the door to a more systematic analysis of mutations and rare allelic forms to understand both mechanistic aspects and evolution of LINE-1 retrotransposition in the human genome. The identification of rare allelic forms of old LINE-1 that retain activity despite previously being considered as inactive is particularly interesting in the light of LINE-1 evolution in the human genome. The authors also describe allelic diversity inside of the Ta1d subfamily, suggesting further diversification and emergence of LINE-1 subgroups. Together with the identification of nucleotide polymorphism among LINE-1 copies, these findings strengthen the notion of individual genomes with individual set of potentially mutagenic LINE-1 alleles.

The findings and methods described in this article are of great interest to a wide audience including the fields of research focusing on human genome evolution, transposable elements, genomic instability, human genetic variation, and personalized medical diagnostic.

Aurélien J. Doucet CNRS - Université Côte d'Azur

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

This manuscript is an interesting and well-crafted study of LINE-1 activity at the single genome human genome level using long read-based haploid assemblies. The manuscript has some real gems and address critical aspects of LINE- biology that are typically not rigorously examined. The authors are to be commended for undertaking this exercise and for providing interesting perspectives that challenge the dogma that dominates the field in several areas. Despite the noted strengths of the contributions, the manuscript ignores the clear limitations inherent to the approaches taken and at times appears as dogmatic as the dogma that they themselves are trying to challenge. These deficiencies should be addressed before this manuscript is published.

• We thank Reviewer 2 for their enthusiastic appreciation of the value and innovation of our manuscript. We also thank the reviewer for encouraging us to make careful consideration of the missing references relevant to our findings. We have had two researchers with experience in relevant fields edit our text for both readability, clarity, and proper inclusion of relevant references. We have added these throughout and taken careful effort to replace ‘dogmatic’ statements with clear presentations of the data and thorough referencing of the relevant literature.

Several major and minor points to consider during revision include:

Major:

1. Several strategies have been published in the past that have confidently assign LINE-1s to specific loci despite use of shorter reads. These works should be acknowledged, even if as stated in the manuscript, use of longer reads will only continue to add confidence and validity to future assignments.

2. We thank the reviewer for this suggestion, and we apologize for the omission of these important publications. As noted above, we have added numerous relevant references (reference 17-27 in the revised text) throughout the text including previous work that used short reads to confidently assign polymorphic/non-reference LINE-1s to specific loci. For example, we now cite the MELT pipeline to detect de novo L1 insertions with short reads (PMID: 28855259), and Iskow et al. 2010, which detects LINE-1s with junction fragment sequencing (PMID: 20603005). We have also added additional text to clarify that short reads are, indeed, often sufficient to place new LINE-1 insertions, while long reads are especially useful for resolving the sequence and location of these insertions. The new text (page 2, left column, line 22-30) presents the advantages/disadvantages of both short reads and long reads.

3. One of the important requirements for precise quantification of LINE-1 activity and predicted risk scores cited in the manuscript was the need to predict activity based on sequence and location. This requirement, as posited in the manuscript, ignores the critical role of epigenetic control in the regulation of LINE-1 activity. As such, a discussion that acknowledges the critical roles of histone and DNA covalent modifications, and that integrates epigenomic insight into predictions of LINE-1 activity must be included in the manuscript.

4. We thank the reviewer for suggesting this important discussion point. In response, we have expanded our discussion of this topic to place our data in the context of other literature on the effects of epigenomic regulation on in vivo LINE-1 activity, including histone and DNA modifications, as well as the effects of post transcriptional restriction factors (paragraph starting at page 11, right column, line 42).

5. The limitations associated with the use of the CHMI were not addressed in the manuscript. While CHMI contain a paternal only genome, with no maternal contribution, the moles may arise from fertilization of an anuclear empty ovum by a haploid 23,X sperm or fertilization by two sperm giving rise to 46,XX or 46,XY karyotype. As such, generalizable conclusions about CHMI genetics should be carefully made given that the loss of maternal epigenetic imprinting and gain of paternally imprinted expression may result in abnormal gene expression, including that of LINE-1s. These variances will in turn impact LINE-1 activity profiles.

6. We thank the reviewer for pointing out this confusingly written section of our manuscript, and we agree with the reviewer that LINE-1 activity measurements could be complicated in the CHM cell lines; however, all of our retrotransposition assays were carried out in the common background of 293T cells (chosen because of their low expression of know LINE-1 restriction factors (PMID: 25182477). We have modified the text (page 11, right column, line 52) to clarify these points.

Minor

1. Important citations of previously published work are not properly referenced throughout the manuscript. These are too numerous to identify individually, but the authors should carefully read the manuscript to ensure that proper documentation and reference to previous work is duly acknowledged.

2. Please see our above response to ‘Major point 1’.

There are several typos and missing prepositions that should be corrected. For instance, on page 7, the word "great" should be "greater".

• Please see our above response to ‘Major point 1’ and Reviewer 1’s ‘Major comment 3’ for details on our in depth editing of the manuscript.

Reviewer #2 (Significance (Required)):

The contribution is highly significant as it challenges previously held concepts and advances our understanding of critical structure and function relationships of Line-1s.

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

Yang et al. perform an in-depth analysis of potentially mobile source L1 alleles in a single human genome (CHM1) previously subjected to Pacbio whole genome sequencing. The retrotransposition efficiencies of source L1 alleles with intact ORFs were tested in vitro, and these efficiencies compared to a model of in vivo activity based on Hamming distance to other ORF-intact L1 alleles. Comparisons of CHM1 L1 alleles are made to CHM13 (used for the recent T2T reference assembly), and also to population-scale sequencing efforts to establish how widespread each source L1 allele is. These data showcase the advantages of being able to resolve L1 alleles with long-read sequencing, allowing the field to make much more accurate predictions of retrotransposition potential in a given genome. The core analyses appear robust and for the most part enough detail is provided to follow what was done.

• We thank Reviewer 3 for their in depth reading and analysis of our manuscript and data, and for their enthusiasm about the importance of this work in the context of foundational research from their lab and many others in the field. We have carefully considered each comment and completed several new analyses of our data and related data from other publications. We feel that our manuscript is much improved with this new data, as detailed below. Comments:

1) The text overlooks the potential importance of L1 5'UTR mutations in L1 activity and evolution, as per PMID:25274305, PMID:1701022, and other studies, as well as the impact of genomic context on source L1 activity, as per PMID:27016617, PMID: 33186547 etc. L1 promoter evolution is arguably a major driver of L1 lineage emergence.

• We thank the reviewer for suggesting these important additions. To present the relevance of 5'UTR mutations on LINE-1 activity and evolution, we added a discussion paragraph (paragraph starting at page 11, right column, line 16) to address how 5'UTRs and other non-ORF factors can affect the rate of LINE-1 in vitro activity. Several key references have been added and discussed in the paragraph: PMID:25274305 reported the regulation of human LINE-1 by the evolution of its 5'UTR; PMID:1701022 was one of the earliest papers that found the effect the 5'UTR promoters on human LINE-1 retrotransposition; PMID: 27016617 and PMID: 33186547 reported specific L1 loci regulated by different promoters and was included in the discussion; PMID:9430649 was one of the examples of non-human LINE-1 lineages emerging because of different promoters and was cited in the added discussion paragraph. We have also added discussion points to make clear that genomic content has a clear role in the activity of source LINE-1s (paragraph starting at page 11, right column, line 42).

2) The way the retrotransposition assay is done here (I think) removes parts of the UTRs as part of introducing L1s into retrotransposition vectors, meaning that the assay tests the biochemical activity of the ORFs. It would be helpful to readers to have a more detailed method for this assay, including the origins of the reporter plasmids, whether there is a CMVp boosting the L1 promoter etc, and some clarity about how much of each L1 was cloned into the assay.

• We have added relevant details to the results (page 6, left column, line 5), discussion (page 11, right column, line 52), and methods (page 13, right column, line 16 and 30) sections to clarify the reviewer’s important points. The LINE-1s tested for in vitro activity were cloned in their entirety (UTRs and ORFs) but driven by both their native promoters in the 5'UTR as well as an upstream CMV promoter. Also, please see our response to Reviewer 1 ‘Minor comment 2’ above.

3) Pacbio long-read sequencing has been used previously to locate and characterise L1 alleles in human DNA. The Introduction states: "These represent the first scalable methods to catalog LINE-1 locations and sequences in individual human genomes". The "first" here is questionable. Citations to PMID:31853540 and PMID:34772701 should be included. The latter is particularly relevant at it not only resolves source L1 sequences with PacBio sequencing but also summarises their retrotransposition efficiencies in vitro and population frequencies.

• We apologize for leaving out these and other important references, and we agree that the “first” claim is unnecessary. We have added the references suggested for the reviewer as well as several other important references as detailed in the above response to Reviewer 2 ‘Major point 1’. In addition, we have revised the adjacent text and deleted any references to our work as the “first” in these approaches.

4) I am very interested in the two source L1s (on chr7 and chr9) that were found here to be more active in vitro than L1RP (to my knowledge the most active such element isolated to date, or close to it). Is there anything unusual about these two L1s? A quick look at the supplemental suggested the chr9 element was 5' truncated, was it tested as such in vitro? Also I think it would be worth contrasting the assay (all in HEKs) used here to test efficiency with the assay used by Brouha ... I feel readers may be surprised to find two L1s more mobile than L1RP in one genome.

• To provide more details about the two active L1s (chr7 and chr9), we investigated key changes that could be related to the in vitro activity of these elements and now show them in Figure 2B and File S3. In the process of this updated analysis and suggested modifications to Figure 2 by this reviewer and Reviewer 1, we saw that the chr7 L1, mentioned here, had one very high activity measurement pulling its activity above L1RP. As such, we decided to more rigorously normalize our data by using the positive and negative controls across all plates of each day instead of normalizing to the controls of individual plates, as we had previously done. In addition, for any L1 with discrepant activity among the three clones we assayed, we used whole plasmid sequencing to confirm the identity and consistency of all three clones. In three cases, we found that one or two of the three clones was the wrong L1, and hence excluded them for the in vitro activity calculation. After this validation and testing of additional clones, all clones from the same L1 have consistent in vitro activity (see updated Figure 2). The updated in vitro activity of the chr7 L1 is at 86.7% L1RP, and the chr9 L1 is at 261.4% L1RP in addition to the chr17 LINE-1 with 117% L1RP and two additional LINE-1s that have near-L1RP activity levels (Table S2, column S). These changes in L1 activity were updated in the text, figures, and supplemental materials. Also, we note that the chr9 element is 6019bp in length and was tested as such in vitro. Current work in the lab is attempting to understand the mechanisms of increased LINE-1 in vitro and in vivo activity, as described in detail in response to Reviewer 1’s ‘Major comment 5’.

5) In several places it is mentioned how L1 alleles may differ from sequences provided in reference assemblies, and may therefore explain discrepancies between assay results here and in other studies (e.g. Brouha). The Seleme and Lutz papers are correctly mentioned here, but arguably the most complete demonstration of this concept, from PMID:31230816, is overlooked. This study reports a chr13 source L1 that was previously found to be inactive by Brouha, and with broken ORFs in the reference genome, has both mobile and immobile alleles in the human population. This L1 is actually in CHM13, but not CHM1, and is "hot" in some individuals and not others. There are several places in the manuscript where this earlier study is very relevant and it would be fair to ask it to be mentioned, especially as the results are concordant. The same concept is reinforced by an even more recent paper (PMID:35728967), except in macaque, showing that this is a general consideration for primate L1 lineages, and actually that source L1 is relatively old and yet jumps extremely well in vitro, which fits an observation made in the present study. Mutually supporting observations like these really add confidence that what is reported in the present study is robust.

• We thank the reviewer for their suggestion to include these highly relevant and important papers; we apologize for this initial omission. We have now added several sentences to the introduction and discussion (top left paragraph page 11) in addition to citations of these papers.

6) Hamming distance between ORF-intact source L1 alleles is used to assess in vivo activity. This seems reasonable. However, in other works, transductions have been used to identify families of very closely related L1s. I realise that many highly mobile source L1s will rarely generate insertions carrying transductions, and yet I wonder if any of the youngest L1s in the present study form transduction families, and whether estimates of in vivo activity based on transductions found in population-scale data would reconcile better with in vitro retrotransposition assay data.

• We thank the reviewer for pointing out our exclusion of data on 3' transductions, the most commonly used surrogates of in vivo activity, while also acknowledging that only a small percent of new L1 retrotranspositions carry 3' transduction. Please see our above response to Reviewer 1’s ‘Major comment 1’ for details on our newly added comparison of our in vivo activity data to the 3' transduction-based somatic LINE-1 retrotransposition landscape of those reported in PMID:34772701, PMID:32024998 and PMID:25082706.

7) In the Introduction, it is stated that L1 only transmits vertically. It may be prudent to mildly qualify this position, based on PMID:29983116.

• The referenced text in the introduction has been changed from "LINE-1s only transmit vertically" to "LINE-1s generally transmit vertically with few exceptions", with the addition of the suggested citation.

8) A column in Table S2 looks mislabelled: Column R should be CHM1 not CHM13?

• We thank the reviewer for seeing this error. Column P (Column R in the previous version) of Table S2 is now correctly labeled as "CHM1 L1 intactness".

Geoff Faulkner (University of Queensland)

Reviewer #3 (Significance (Required)):

This is a well-executed study of considerable interest to the mobile DNA field, and anyone working with long-read DNA sequencing. Its strengths are the genomic and bioinformatic analysis, leveraging the PacBio long-read data and BAC library available for CHM1 to full effect. One limitation (in current form) is its near-exclusive focus on ORFs to encapsulate how mobile a given L1 allele is, when genomic context and L1 promoter mutations could also contribute heavily. Although I liked the manuscript very much and enjoyed reviewing it, some of the conceptual advances are encroached upon by other work (including some very relevant and yet uncited literature). These issues can very likely be addressed via a revision, additional analyses may be required but not new experiments.

Geoff Faulkner (University of Queensland)

Author Response

We would like to thank the reviewers for their positive and constructive comments on the manuscript.

We are planning the following revisions to both DGRPool and the corresponding manuscript to address the reviewers’ comments:

1) We agree with reviewer #1 that normalizing the data could potentially improve the GWAS results. Thus, we plan to explore the implementation of this option and assess its impact on the overall results. We will also investigate replacing the ANOVA test with a KRUSKAL test. Instead of upfront data normalization, we will consider using the PLINK –pheno-quantile-normalize option. Both options will be compared on a set of phenotypes where we can analyze the output (i.e., for phenotypes where we expect to find specific variants), to determine whether these strategies enhance the detection power.

2) We also agree with both reviewers that gene expression information is of interest. However, we recognize that incorporating such information would entail substantial work (as elaborated in our response to comments below). We feel that this extensive work is beyond the current scope of this paper, which primarily focuses on phenotypes and genotype-phenotype associations. Nonetheless, we are committed to enhancing user experience by including more gene-level outlinks to Flybase. Additionally, we will link variants and gene results to Flybase's online genome browser, JBrowse. By following the reviewers' suggestions, we aim to guide DGRPool users to potentially informative genes.

3) In agreement with reviewer #2, we acknowledge that additional tools could enhance DGRPool's functionality and facilitate meta-analyses for users. Therefore, we are in the process of developing a gene-centric tool that will allow users to query the database based on gene names. Moreover, we intend to integrate ortholog databases into the GWAS results. This feature will enable users to extend Drosophila gene associations to other species if necessary.

4) Finally, we also concur with both reviewers about making minor edits to the manuscript to address their feedback.

Reviewer #1 (Public Review):

This is a technically sound paper focused on a useful resource around the DRGP phenotypes which the authors have curated, pooled, and provided a user-friendly website. This is aimed to be a crowd-sourced resource for this in the future.

The authors should make sure they coordinate as well as possible with the NC datasets and community and broader fly community. It looks reasonable to me but I am not from that community.

We thank the reviewer for the positive comments. We are relatively well-connected to the D. melanogaster community and aim to leverage this connection to render the resource as valuable as possible. DGRPool in fact already reflects the input of many potential users and was also inspired by key tools on the DGRP2 website. Furthermore, it also rationalizes why we are often bridging our results with other resources, such as linking out to Flybase, which is the main resource for the Drosophila community at large.

I have only one major concern which in a more traditional review setting I would be flagging to the editor to insist the authors did on resubmission. I also have some scene setting and coordination suggestions and some minor textual / analysis considerations.

The major concern is that the authors do not comment on the distribution of the phenotypes; it is assumed it is a continuous metric and well-behaved - broad gaussian. This is likely to be more true of means and medians per line than individual measurements, but not guaranteed, and there could easily be categorical data in the future. The application of ANOVA tests (of the "covariates") is for example fragile for this.

The simplest recommendation is in the interface to ensure there is an inverse normalisation (rank and then project on a gaussian) function, and also to comment on this for the existing phenotypes in the analysis (presumably the authors are happy). An alternative is to offer a kruskal test (almost the same thing) on covariates, but note PLINK will also work most robustly on a normalised dataset.

We thank the reviewer for raising this interesting point. Indeed, we did not comment on the distribution of individual phenotypes due to the underlying variability from one phenotype to another, as suggested by the reviewer. Some distributions appear normal, while others are clearly not normally distributed. This information is 'visible' to users by clicking on any phenotype; DGRPool automatically displays its global distribution if the values are continuous/quantitative. We acknowledge the reviewer's concerns regarding the use of ANOVA tests. However, we consider it acceptable to perform linear regression (including ANOVA tests) on non-normally distributed data, as only the prediction errors need to follow a normal distribution.

Furthermore, the ANOVA test is solely conducted to assess whether any of the potential covariates (such as well-established inversions and symbiont infection status) are associated with the phenotype of interest. PLINK2 automatically corrects for the effects of these covariates during GWAS by considering them as part of the regression model.

Nevertheless, we concur with the reviewer that normalizing the data could potentially enhance GWAS results. Consequently, we commit to exploring the impact of data normalization on the overall outcomes. Additionally, we will consider replacing the ANOVA test with a KRUSKAL test, and using the PLINK –pheno-quantile-normalize option. We intend to compare both approaches using a set of phenotypes where we can compare the output (i.e., where specific variants are expected to be identified). This comparison will help us determine if either method enhances the detection power.

Minor points:

On the introduction, I think the authors would find the extensive set of human GWAS/PheWAS resources useful; widespread examples include the GWAS Catalog, Open Targets PheWAS, MR-base, and the FinnGen portal. The GWAS Catalog also has summary statistics submission guidelines, and I think where possible meta-data harmonisation should be similar (not a big thing). Of course, DRGP has a very different structure (line and individuals) and of course, raw data can be freely shown, so this is not a one-to-one mapping.

Thank you for the suggestion. We will cite these resources in the Introduction and check the GWAS catalog submission guidelines to compare to the ones we are proposing in this paper.

For some authors coming from a human genetics background, they will be interpreting correlations of phenotypes more in the genetic variant space (eg LD score regression), rather than a more straightforward correlation between DRGP lines of different individuals. I would encourage explaining this difference somewhere.

We appreciate this potential issue and we will make this distinction clearer in the manuscript to avoid any confusion.

This leads to an interesting point that the inbred nature of the DRGP allows for both traditional genetic approaches and leveraging the inbred replication; there is something about looking at phenotype correlations through both these lenses, but this is for another paper I suspect that this harmonised pool of data can help.

We agree with the reviewer and hope that more meta-analyses will be made possible by leveraging the harmonized data that are made available through DGRPool.

I was surprised the authors did not crunch the number of transcript/gene expression phenotypes and have them in. Is this because this was better done in other datasets? Or too big and annoying on normalisation? I'd explain the rationale to leave these out.

This is a very good point raised by the reviewer, and this is in fact something that we initially wanted to do. However, to render the analysis fair and robust, it would require processing all datasets in the same way. This implies cataloging all existing datasets and processing them through the same pipeline. Then, it also requires adding a “cell type” or “tissue” layer, because gene expression data from whole flies is obviously not directly comparable to gene expression data from specific tissues or even specific conditions. This would be key information as phenotypes are often tissue-dependent. So, as implied by the reviewer, we deemed this too big of a challenge beyond the scope of the current paper. Nevertheless, we plan to continue investigating this avenue, especially given the strong transcriptomics background of our lab, in a potential follow-up paper.

I think 25% FDR is dangerously close to "random chance of being wrong". I'd just redo this section at a higher FDR, even if it makes the results less 'exciting'. This is not the point of the paper anyway.

We agree with the reviewer that this threshold implies a higher risk of false positive results. However, this is not an uncommonly used threshold (Li et al., PLoS biology, 2008; Bevers et al., Nature Metabolism, 2019; Hwangbo et al, Elife, 2023), and one that seems robust enough in our analysis since similar phenotypes are significant in different studies. Nevertheless, we will revisit these results and explore how a more stringent threshold may impact the results.

I didn't buy the extreme line piece as being informative. Something has to be on the top and bottom of the ranks; the phenotypes are an opportunity for collection and probably have known (as you show) and cryptic correlations. I think you don't need this section at all for the paper and worry it gives an idea of "super normals" or "true wild types" which ... I just don't think is helpful.

This section of the paper was intended to investigate anecdotal evidence suggesting that certain DGRP lines consistently rank at the top or bottom when examining fitness-related traits. If accurate, this observation could imply that inbreeding might have made these lines generally weaker, potentially introducing bias into studies aimed at uncovering the genetic basis of complex traits. However, as per the analyses presented, we did not discover support for this phenomenon. Nevertheless, we consider this message important to convey. In response to the reviewer's feedback, we intend to provide a clearer explanation of the reasoning behind this section of the paper and its main conclusion.

I'd say "well-established inversion genotypes and symbiot levels" rather than generic covariates. Covariates could mean anything. You have specific "covariates" which might actually be the causal thing.

Thank you. We will update the manuscript accordingly.

I wouldn't use the adjective tedious about curation. It's a bit of a value judgement and probably places the role of curation in the wrong way. Time-consuming due to lack of standards and best practice?

Thank you. We will update the manuscript accordingly.

Reviewer #2 (Public Review):

Summary:

In the present study, Gardeux et al provide a web-based tool for curated association mapping results from DRP studies. The tool lets users view association results for phenotypes and compare mean phenotype ~ phenotype correlations between studies. In the manuscript, the authors provide several example utilities associated with this new resource, including pan-study summary statistics for sex, traits, and loci. They highlight cross-trait correlations by comparing studies focused on longevity with phenotypes such as oxphos and activity.

Strengths:

-Considerable efforts were dedicated toward curating the many DRG studies provided.

-Available tools to query large DRP studies are sparse and so new tools present appeal

Weaknesses:

The creation of a tool to query these studies for a more detailed understanding of physiologic outcomes seems underdeveloped. These could be improved by enabling usages such as more comprehensive queries of meta-analyses, molecular information to investigate given genes or pathways, and links to other information such as in mouse rat or human associations.

We appreciate the reviewer's kind comments.

Regarding the tools, we concur with the reviewer that incorporating additional tools could enhance DGRPool and facilitate users in conducting meta-analyses. Therefore, we intend to introduce a gene-centric tool that enables users to query the database based on gene names. Additionally, we will establish links to ortholog databases within the GWAS results, thereby allowing users to extend fly gene associations to other species, if required.

Furthermore, we have plans to link out to a 'genome browser-like' view (Flybase’s JBrowse tool) of the GWAS results centered around the affected variants/genes. We are considering integrating this feature into the new gene-centric tool as well.

Another potential downstream analysis we are considering is gene-set enrichment. This analysis would involve assessing the enrichment of genes in Gene Ontology or other pathway databases directly from the GWAS results page.

Author Response

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

We greatly appreciate the positive feedback of the reviewers and have modified the manuscript to address their comments, including changes to the text, figures, and methods. We believe that these revisions have strengthened and improved the manuscript. Reviewers’ comments in blue and detailed responses in black are below.

Reviewer #1 Weaknesses:

• Is "function" of the ISNs to balance "nutrient need" or osmolarity? Balancing hemolymph osmolarity for physiological homeostasis is conceptually different from balancing thirst and hunger.

We have added the following text to the introduction to address this: “Thus, the ISNs sense both AKH and hemolymph osmolality, arguing that they balance internal osmolality fluctuations and nutrient need (Jourjine, Mullaney et al., 2016).” (ln 80-82).

• The final schematic nicely sums up how the different peptidergic pathways might work together, but it is unclear which connections are empirically-validated or speculative. It would be informative to show which parts of the model are speculative versus validated. For example, does FAFB volume synapse = functional connectivity and not just anatomical proximity? A bulk of the current manuscript relies on "synapses of relatively high confidence" (according to Materials and methods: line 522). I recommend distinguishing empirically tested & predicted connections in the final schematic, and maybe reword/clarify throughout the manuscript as "predicted synaptic partners"

We modified the schematic to clarify EM based connections versus functionally validated connections. We also clarified the EM predicted synaptic partners, using “predicted synaptic partners” throughout the manuscript.

Reviewer #2 Areas for further development:

• Does BIT inhibit all of the IPCs or some of them? I think it is critical to indicate the ROIs used for each neuron in the methods. Which part of the neuron is used for imaging experiments? Dendrites, cell bodies, or synaptic terminals?

ROIs used for quantification are described in the figure legends: “ArcLight response of BiT soma…” (Fig 2, Fig S2), “Calcium responses of CCHa2R-RA neurites in SEZ…” (Fig 4), “Calcium response of CCHa2R-RA SEZ neurites…” (Fig S4), “Calcium response of CCAP neurites…” (Fig 5, Fig S5), “Calcium response of all IPC somas…” (Fig S3). We have added ROIs used for quantification to the ‘In vivo calcium imaging’ and the ‘In vivo voltage imaging’ methods sections (ln 493-494).

• The discussion section is not giving big picture explanation of how these neurons work together to regulate sugar and water ingestion. Silencing and activation experiments are good, but without showing the innate activity of these neural groups during ingestion, it is not clear what their functions are in terms of regulating fly behavior.

We agree that how these peptidergic neurons coordinately regulate feeding is unclear. As peptide signals may act at a distance and may cause long-lasting neural activity state changes, studying their integration over space and time is challenging. Acute imaging during feeding would only in part address this challenge, as cumulative changes in nutrient need signals may impart circuit changes that are not apparent by monitoring the acute activity of peptidergic neurons. We modified a paragraph in the discussion to address this (ln 434-443).

“Overall, our work sheds light on neural circuit mechanisms that translate internal nutrient abundance cues into the coordinated regulation of sugar and water ingestion. We show that the hunger and thirst signals detected by the ISNs influence a network of peptidergic neurons that act in concert to prioritize ingestion of specific nutrients based on internal needs. We hypothesize that multiple internal state signals are integrated in higher brain regions such that combinations of peptides and their actions signify specific needs to drive ingestion of appropriate nutrients. As peptide signals may act at a distance and may cause long-lasting neural activity state changes, studying their integration over space and time is a future challenge to further illuminate homeostatic feeding regulation.”

Reviewer #1 (Recommendations For The Authors):

• For the final schematic figure, it may be informative to include nanchung and AKHR in the schematic.

We now include this (Fig 6).

• For the ingestion duration with optogenetic activation, I don't think the right way to represent the data is by normalizing them to the no LED control. I think it should show raw ingestion time. I understand that the normalized data make the figure "cleaner" (no need to show +/- LED separately) but I think visualization of the raw data is important.

We now include this in a new Supplemental Figure (Fig S6).

• Methods for ingestion with optogenetic activation should be detailed in the Methods section.

We expanded upon this in the ‘Temporal consumption assay (TCA)’ methods section. (ln 461-466).

Reviewer #2 (Recommendations For The Authors):

1) I think the authors are not following the recommendations of the Flywire community which recommends that people who contributed to the tracing of neurons are offered authorship in the published papers. I see the authors are thanking other lab members who have done tracing for the neurons described in this study, but I would like them to clarify whether they are following the guidelines provided by Flywire.

We followed the Flywire guidelines and contacted all Flywire users contributing more that 10% to neuron edits for permission to publish with acknowledgements. (see Flywire guidelines https://docs.google.com/document/d/1bUkOB5JnT3u__JDvAoVDHJ3zr5NXQtV_63yx2w6Tcc/edit).

2) The method section for voltage imaging is missing.

We now include a section on voltage imaging (ln 496-498).

3) ROIs for imaging are not indicated in the methods or in the figures. It is hard to judge what is the origin of neural activity plotted in the figures; are they imaging cell bodies, dendrites, or axons?

ROIs used for quantification are described in the figure legends: “ArcLight response of BiT soma…” (Fig 2, Fig S2), “Calcium responses of CCHa2R-RA neurites in SEZ…” (Fig 4), “Calcium response of CCHa2R-RA SEZ neurites…” (Fig S4), “Calcium response of CCAP neurites…” (Fig 5, Fig S5), “Calcium response of all IPC somas…” (Fig S3). We have added ROIs used for quantification to the ‘In vivo calcium imaging’ and the ‘In vivo voltage imaging’ methods sections (ln 493-494).

Author Response

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

We would first like to thank the reviewers and the editor for their insightful comments and suggestions. We are particularly glad to read that our so<ware package constitutes a set of “well-written analysis routines” which have “the potential to become very valuable and foundational tools for the analysis of neurophysiological data”. We have updated the manuscript to address their remarks where appropriate.

Additionally, we would like to stress that this kind of tools is in continual development. As such, the manuscript offered a snapshot of the package at one point during this process, which in this case was several months ago at initial submission. Since then, several improvements were implemented. The manuscript has been further updated to reflect these more recent changes.

From the Reviewing Editor:

The reviewers identified a number of fundamental weaknesses in the paper.

1) For a paper demonstrating a toolbox, it seems that some example analyses showing the value of the approach (and potentially the advantage in simplification, etc over previous or other approaches) are really important to demonstrate.

As noted by the first reviewer, the online repository (i.e. GitHub page) conveys a better sense of the toolboxes’ contribution to the field than the present manuscript. This is a fair remark but at the same time, it is unclear how to illustrate this in a journal article without dedicating a great deal of page space to presenting raw code, while online tools offer an easier and clearer way to do this. As a work-around, our strategy was to illustrate some examples of data analysis in Figures 4&5 by comparing each illustrated processing step to the corresponding command line used by the Pynapple package. Each step requires a single line of code, meaning that one only needs to write three lines of code to decode a feature from population activity using a Bayesian decoder (Fig. 4a), compute a cross-correlograms of two neurons during specific stimulus presentation (Fig. 4b) or compute the average firing rate of two neurons around a specific time of the experimental task (Fig. 4c). We believe that these visual aides make it unnecessary to add code in the main text of this manuscript. However, to aid reader understanding, we now provide clear references to online Jupyter notebooks which show how each figure was generated in figure legends as well as in the “Code Availability” section.

https://github.com/pynapple-org/pynapple-paper-2023

Furthermore, we have opted-in for the “Executable Research Articles” feature at eLife, which will make it possible to include live scripts and figures in the manuscript once it is accepted for publication. We do not know at this stage what it entails exactly, but we hope that Figures 4&5 will become live with this feature. The readers will have the possibility to see and edit the code directly within the online version of the manuscript.

2) The manuscript's claims about not having dependencies seem confusing.

We agree that this claim was somewhat unfounded. There are virtually no Python packages that do not have dependencies. Our intention was to say that the package had no dependencies outside the most common ones, which are Numpy, Scipy, and Pandas. Too many packages in the field tend to have long list of dependencies making long-term back-compatibility quite challenging. By keeping depencies minimal, we hope to maximise the package’'s long term back-compatibility. We have rephrased this statement in the manuscript in the following sections:

Figure 1, legend.

“These methods depend only on a few, commonly used, external packages.”

Section Foundational data processing: “they are for the most part built-in and only depend on a few widely-used external packages. This ensures that the package can be used in a near stand-alone fashion, without relying on packages that are at risk of not being maintained or of not being compatible in the near future.”

3) Given its significant relevance, it seems important to cite the FMATool and describe connections between it (or analyses based on it) and the presented work.

Indeed, although we had already cited other toolboxes (including a review covering the topic comprehensively), we should have included this one in the original manuscript. Unfortunately, to the best of our knowledge, this toolbox is not citable (there is no companion paper). We have added a reference to it in plain text.

4) Some discussion of integration between Pynapple and the rest of a full experimental data pipeline should be discussed with regard to reproducibility.

This is an interesting point, and the third paragraph of the discussion somewhat broached this issue. Pynapple was not originally designed to pre-process data. However, it can, in theory, load any type of data streams a<er the necessary pre-processing steps. Overall, modularity is a key aspect of the Pynapple framework, and this is also the case for the integration with data pre-processing pipelines, for example spike sorting in electrophysiology and detection of region of interest in calcium imaging. We do not think there should be an integrated solution to the problem but, instead, to make it possible that any piece of code can be used for data irrespective of their origin. This is why we focused on making data loading straightforward and easy to adapt to any particular situation. To expand on this point and make it clear that Pynapple is not meant to pre-process data but can, in theory, load any type of data streams a<er the necessary pre-processing steps, we have added the following sentences to the aforementioned paragraph:

“Data in neuroscience vary widely in their structure, size, and need for pre-processing. Pynapple is built around the idea that raw data have already been pre-processed (for example, spike sorting and detection of ROIs).”

5) Relatedly, a description of how data are stored a<er processing (i.e., how precisely are processed data stored in NWB format).

We agree that this is a critical issue. NWB is not necessarily the best option as it is not possible to overwrite in a NWB file. This would require the creation of a new NWB file each time, which is computationally expensive and time consuming. It also further increases the odds of writing error. Theoretically, users who needs to store intermediate results in a flexible way could use any methods they prefer, writing their own data files and wrappers to reload these data into Pynapple objects. Indeed, it is not easy to properly store data in an object-specific manner. This is a long-standing issue and one we are currently working to resolve.

To do so, we are developing I/O methods for each Pynapple core objects. We aim to provide an output format that is simple to read and backward compatible in future Pynapple releases. This feature will be available in the coming weeks. To note, while NWB may not be the central data format of Pynapple in future releases, it has become a central node in the neuroscience ecosystem of so<ware. Therefore, we aim to facilitate the interaction of users with reading and writing for this format by developing a set of simple standalone functions.

Reviewer #1 (Public Review):

A typical path from preprocessed data to findings in systems neuroscience o<en includes a set of analyses that o<en share common components. For example, an investigator might want to generate plots that relate one time series (e.g., a set of spike times) to another (measurements of a behavioral parameter such as pupil diameter or running speed). In most cases, each individual scientist writes their own code to carry out these analyses, and thus the same basic analysis is coded repeatedly. This is problematic for several reasons, including the waste of time, the potential for errors, and the greater difficulty inherent in sharing highly customized code.

This paper presents Pynapple, a python package that aims to address those problems.

Strengths:

The authors have identified a key need in the community - well-written analysis routines that carry out a core set of functions and can import data from multiple formats. In addition, they recognized that there are some common elements of many analyses, particularly those involving timeseries, and their object- oriented architecture takes advantage of those commonalities to simplify the overall analysis process.

The package is separated into a core set of applications and another with more advanced applications, with the goal of both providing a streamlined base for analyses and allowing for implementations/inclusion of more experimental approaches.

Weaknesses:

There are two main weaknesses of the paper in its present form.

First, the claims relating to the value of the library in everyday use are not demonstrated clearly. There are no comparisons of, for example, the number of lines of code required to carry out a specific analysis with and without Pynapple or Pynacollada. Similarly, the paper does not give the reader a good sense of how analyses are carried out and how the object-oriented architecture provides a simplified user interaction experience. This contrasts with their GitHub page and associated notebooks which do a better job of showing the package in action.

As noted in the response to the Reviewing Editor and response to the reviewer’s recommendation to the authors below, we have now included links to Jupyter notebooks that highlight how panels of Figures 4 and 5 were generated (https://github.com/pynapple-org/pynapple-paper-2023). However, we believe that including more code in the manuscript than what is currently shown (I.e. abbreviated call to methods on top of panels in Figs 4&5) would decrease the readability of the manuscript.

Second, the paper makes several claims about the values of object-oriented programming and the overall design strategy that are not entirely accurate. For example, object-oriented programming does not inherently reduce coding errors, although it can be part of good so<ware engineering. Similarly, there is a claim that the design strategy "ensures stability" when it would be much more accurate to say that these strategies make it easier to maintain the stability of the code. And the authors state that the package has no dependencies, which is not true in the codebase. These and other claims are made without a clear definition of the properties that good scientific analysis so<ware should have (e.g., stability, extensibility, testing infrastructure, etc.).

Following thFMAe reviewer’s comment, we have rephrased and clarified these claims. We provide detailed response to these remarks in the recommendations to authors below.

There is also a minor issue - these packages address an important need for high-level analysis tools but do not provide associated tools for preprocessing (e.g., spike sorting) or for creating reproducible pipelines for these analyses. This is entirely reasonable, in that no one package can be expected to do everything, but a bit deeper account of the process that takes raw data and produces scientific results would be helpful. In addition, some discussion of how this package could be combined with other tools (e.g., DataJoint, Code Ocean) would help provide context for where Pynapple and Pynacollada could fit into a robust and reliable data analysis ecosystem.

We agree the better explaining how Pynapple is integrated within data preprocessing pipelines is essential. We have clarified this aspect in the manuscript and provide more details below.

Reviewer #1 (Recommendations For The Authors):

Page 1

• Title

The authors should note that the application name- "Pynapple" could be confused with something from Apple. Users may search for "Pyapple" as many python applications contain "py" like "Numpy". "Pyapple" indeed is a Python Apple that works with Apple products. They could consider "NeuroFrame", "NeuroSeries" or "NeuroPandas" to help users realize this is not an apple product.

We thank the referee for this interesting comment. However, we are not willing to make such change at this point. The community of users has been growing in the last year and it seems too late to change the name. To note, it is the first time such comment is made to us and it does not seem that users and collaborators are confused with any Apple products.

• Abstract

The authors mentioned that the Pynapple is "fully open source". It may be better to simply say it is "open source".

We agree, corrected.

Assuming the authors keep the name, it would be helpful if the full meaning of Pynapple - Python Neural Analysis Package was presented as early as possible.

Corrected in the abstract.

• Highlight

An application being lightweight and standalone does not imply nor ensure backward compatibility. In general, it would be useful if the authors identified a set of desirable code characteristics, defined them clearly in the introduction, and then describe their so<ware in terms of those characteristics.

Thank you for your comment. We agree that being lightweight and standalone does not necessarily imply backward compatibility. Our intention was to emphasize that Pynapple is designed to be as simple and flexible as possible, with a focus on providing a consistent interface for users across different versions. However, we understand that this may not be enough to ensure long-term stability, which is why we are committed to regular updates and maintenance to ensure that the code remains functional as the underlying code base (Python versions, etc.) changes.

Regarding your suggestion to identify a set of desirable code characteristics, we believe this is an excellent idea. In the introduction, we briefly touch upon some of the core principles that guided our development of Pynapple: a lightweight, stable, and simple package. However, we acknowledge that providing a more detailed discussion of these characteristics and how they relate to the design of our so<ware would be useful for readers. We have added this paragraph in the discussion:

“Pynapple was developed to be lightweight, stable, and simple. As simplicity does not necessarily imply backward compatibility (i.e. long-term stability of the code), Pynapple main objects and their properties will remain the same for the foreseeable future, even if the code in the backend may eventually change (e.g. not relying on Pandas in future version). The small number of external dependencies also decrease the need to adapt the code to new versions of external packages. This approach favors long-term backward compatibility.”

Page 2

• The authors wrote -

"Despite this rapid progress, data analysis o<en relies on custom-made, lab-specific code, which is susceptible to error and can be difficult to compare across research groups."

It would be helpful to add that custom-made, lab-specific code can lead to a violation of FAIR principles (https://en.wikipedia.org/wiki/FAIR_datadata). More generally, any package can have errors, so it would be helpful to explain any testing regiments or other approach the authors have taken to ensure that their code is error-free.

We understand the importance of the FAIR principles for data sharing. However, Pynapple was not designed to handle data through their pre-processing. The only aspect that is somehow covered by the FAIR principles is the interoperability, but again, it is a requirement for the data to interoperate with different storage and analysis pipelines, not of the analysis framework itself. Unlike custom-made code, Pynapple will make interoperability easier, as, in theory, once the required data loaders are available, any analysis could be run on any dataset. We have added the following sentence to the discussion:

“Data in neuroscience vary widely in their structure, size, and need for pre-processing. Pynapple is built around the idea that raw data has already been pre-processed (for example, spike sorting and ROI detection). According to the FAIR principles, pre-processed data should interoperate across different analysis pipelines. Pynapple makes this interoperability possible as, once the data are loaded in the Pynapple framework, the same code can be used to analyze different datasets”

• The authors wrote -

"While several toolboxes are available to perform neuronal data analysis ti–11,2ti (see ref. 29 for review), most of these programs focus on producing high-level analysis from specified types of data and do not offer the versatility required for rapidly-changing analytical methods and experimental methods."

Here it would be helpful if the authors could give a more specific example or explain why this is problematic enough to be a concern. Users may not see a problem with high-level analysis or using specific data types.

Again, we apologize for not fully elaborating upon our goals here. Our intention was to point out that toolboxes o<en focus on one particular case of high-level analysis. In many cases, such packages lack low level analysis features or the flexibility to derive new analysis pipelines quickly and effortlessly. Users can decide to use low-level packages such as Pandas, but in that case, the learning curve can be steep for users with low, if any, computational background. The simplicity of Pynapple, and the set of examples and notebooks, make it possible for individuals who start coding to be quickly able to analyze their data.

As we do not want to be too specific at this point of the manuscript (second paragraph of the intro) and as we have clarified many of the aspects of the toolbox in the new revised version, we have only added the following sentence to the paragraph:

“Users can decide to use low-level data manipulation packages such as Pandas, but in that case, the learning curve can be steep for users with low, if any, computational background.”

• The authors wrote -

"To meet these needs, a general toolbox for data analysis must be designed with a few principles in mind"

Toolboxes based on many different principles can solve problems. It is likely more accurate to say that the authors designed their toolbox with a particular set of principles in mind. A clear description of those principles (as mentioned in the comment above) would help the reader understand why the specific choices made are beneficial.

We agree that these are not “universal” principles and clearly more the principles we had in mind when we designed the package. We have clarified these principles and made clear that these are personal point of views.

We have rephrased the following paragraph:

“To meet these needs, we designed Pynapple, a general toolbox for data analysis in systems Neuroscience with a few principles in mind.“

• The authors wrote -

"The first property of such a toolbox is that it should be object-oriented, organizing so<ware around data."

What facts make this true? For example, React is a web development library. A common approach to using this library is to use Hooks (essentially a collection of functions). This is becoming more popular than the previous approach of using Components (a collection of classes). This is an example of how Object-oriented programming is not always the best solution. In some cases, for example, object- oriented coding can cause problems (e.g. it can be hard to find the place where a given function is defined and to figure out which version is being used given complex inheritance structures.)

In general, key selling points of object-oriented programming are extension, inheritance, and encapsulation. If the authors want to retain this text (which would be entirely reasonable), it would be helpful if they explained clearly how an object-oriented approach enables these functions and why they are critical for this application in particular.

The referee makes a particularly important point. We are aware of the limits of OOP, especially when these objects become over-complex, and that the inheritance become unclear.

We have clarified our goal here. We believe that in our case, OOP is powerful and, overall, is less error- prone that a collection of functions. The reasons are the following:

An object-oriented approach facilitates better interactions between objects. By encapsulating data and behavior within objects, object-oriented programming promotes clear and well-defined interfaces between objects. This results in more structured and manageable code, as objects communicate with each other through these well-defined interfaces. Such improved interactions lead to increased code reliability.

Inheritance, a key concept in object-oriented programming, allows for the inheritance of properties. One important example of how inheritance is crucial in the Pynapple framework is the time support of Pynapple objects. It determines the valid epoch on which the object is defined. This property needs to be carried over during different manipulations of the object. Without OOP, this property could easily be forgotten, resulting in erroneous conclusions for many types of analysis. The simplest case is the average rate of a TS object: the rate must be computed on the time support ( a property of TS objects), not the beginning to the end of the recording (or of a specific epoch, independent of the TS). Finally, it is easier to access and manipulate the meta information of a Pynapple object than without using objects.

• The authors wrote -

"drastically diminishing the odds of a coding error"

This seems a bit strong here. Perhaps "reducing the odds" would be more accurate.

We agree. Now changed.

Page 3

• The authors wrote -

". Another property of an efficient toolbox is that as much data as possible should be captured by only a small number of objects This ensures that the same code can be used for various datasets and eliminates the need of adapting the structure"

It may be better to write something like - "Objects have a collection of preset variables/values that are well suited for general use and are very flexible." Capturing "as much data as possible" may be confusing, because it's not the amount that this helps with but rather the variety.

We thank the referee for this remark. We have rephrased this sentence as follows:

“Another property of an efficient toolbox is that a small number of objects could virtually represents all possible data streams in neuroscience, instead of objects made for specific physiological processes (e.g. spike trains).”

• The authors wrote -

"The properties listed above ensure the long-term stability of a toolbox, a crucial aspect for maintaining the code repository. Toolboxes built around these principles will be maximally flexible and will have the most general application"

There are two issues with this statement. First, ensuring long-term stability is only possible with a long- term commitment of time and resources to ensure that that code remains functional as the underlying code base (python versions, etc.) changes. If that is something you are commisng to, it would be great to make that clear. If not, these statements need to be less firm.

Second, it is not clear how these properties were arrived at in the first place. There are things like the FAIR Principles which could provide an organizing framework, ideally when combined with good so<ware engineering practices, and if some more systematic discussion of these properties and their justification could be added, it would help the field think about this issue more clearly.

The referee makes a valid point that ensuring long-term stability requires a long-term commitment of time and resources to maintain the code as the underlying technology evolves. While we cannot make guarantees about the future of Pynapple, we believe that one of the best ways to ensure long-term stability is by fostering a strong community of users and contributors who can provide ongoing support and development. By promoting open-source collaboration and encouraging community involvement, we hope to create a sustainable ecosystem around Pynapple that can adapt to changes in technology and scientific practices over time. Ultimately, the longevity of any scientific tool depends on its adoption and use by the research community, and we hope that Pynapple can provide value to neuroscience researchers and continue to evolve and improve as the field progresses.

It is noteworthy that the first author, and main developer of the package, has now been hired as a data scientist at the Center for Computational Neuroscience, Flatiron Institute, to explicitly continue the development of the tool and build a community of users and contributors.

• The authors wrote -

"each with a limited number of methods..."

This may give the impression that the functionality is limited, so rephrasing may be helpful.

Indeed! We have now rephrased this sentence:

“The core of Pynapple is five versatile timeseries objects, whose methods make it possible to intuitively manipulate and analyze the data.”

• The authors wrote that object-oriented coding

"limits the chances of coding error"

This is not always the case, but if it is the case here, it would be helpful if the authors explain exactly how it helps to use object-oriented approaches for this package.

We agree with the referee that it is not always the case. As we explained above, we believe it is less error-prone that a collection of functions. Quite o<en, it also makes it easier to debug. We have changed this sentence with the following one:

“Because objects are designed to be self-contained and interact with each other through well-defined methods, users are less likely to make errors when using them. This is because objects can enforce their own internal consistency, reducing the chances of data inconsistencies or unexpected behavior. Overall, OOP is a powerful tool for managing complexity and reducing errors in scientific programming.”

• Fig 1

In object-oriented programming, a class is a blueprint for the classes that inherit it. Instantiating that<br /> class creates an object. An object contains any or all of these - data, methods, and events. The figure could be improved if it maintained these organizational principles as figure properties.

We agree with the referee’s remark regarding the logic of objects instantiation but how this could be incorporated in Fig. 1 without making it too complex is unclear. Here, objects are instantiated from the first to the second column. We have not provided details about the parent objects, as we believe these details are not important for reader comprehension. In its present form, the objects are inherited from Pandas objects, but it is possible that a future version is based on something else. For the users, this will be transparent as the toolbox is designed in such a way that only the methods that are specific to Pynapple are needed to do most computation, while only expert programmers may be interested in using Pandas functionalities.

• The authors wrote that Pynapple does -

"not depend on any external package"

As mentioned above, this is not true. It depends on Numpy and likely other packages, and this should be explained. It is perfectly reasonable to say that it depends on only a few other packages.

As said above, we have now clarified this claim.

Page 5.

• The authors wrote -

"represent arrays of Ts and Tsd"

For a knowledgeable reader's reference, it would be helpful to refer to these either as Numpy arrays (at least at first when they are defined) or as lists if they are native python objects.

Indeed, using the word “arrays” here could be confusing because of Numpy arrays. We have changed this term with “groups”.

• The authors wrote -

"Pynapple is built with objects from the Pandas library ... Pynapple objects inherit the computational stability and flexibility"

Here a definition of stability would be useful. Is it the case that by stability you mean "does not change o<en"? Or is some other meaning of stability implied?

Yes, this is exactly what we meant when referring to the stability of Pandas. We have added the following precision:

“As such, Pynapple objects inherit the long-term consistency of the code and the computational flexibility computational stability and flexibility from this widely used package.”

Page 6

• Fig 2

In Fig 2 A and B, the illustrations are good. It would also be very helpful to use toy code examples to illustrate how Pynapple will be used to carry out on a sample analysis-problem so that potential users can see what would need to be done.

We appreciate the kind works. Regarding the toy code, this is what we tried to do in Fig. 4. Instead of including the code directly in the paper, which does not seem a modern way of doing this, we now refer to the online notebooks that reproduce all panels of Figure 4.

• The authors wrote -

"While these objects and methods are relatively few"

In object-oriented programming, objects contain methods. If a method is not in an object, it is not technically a method but a function. It would be helpful if the authors made sure their terminology is accurate, perhaps by saying something like "While there are relatively few objects, and while each object has relatively few methods ... "

We agree with the referee, we have changed the sentence accordingly.

• The authors wrote -

"if not implemented correctly, they can be both computationally intensive and highly susceptible to user error"

Here the authors are using "correctly" to refer to two things - "accuracy" - gesng the right answer, and "efficiency" - gesng to that answer with relatively less computation. It would be clearer if they split out those two concepts in the phrasing.

Indeed, we used the term to cover both aspects of the problem, leading to the two possible issues cited in the second part of the sentence. We have changed the sentence following the referee’s advice:

“While there are relatively few objects, and while each object has relatively few methods, they are the foundation of almost any analysis in systems neuroscience. However, if not implemented efficiently, they can be computationally intensive and if not implemented accurately, they are highly susceptible to user error.”

• In the next sentence the authors wrote -

"Pynapple addresses this concern."

This statement would benefit from just additional text explaining how the concern is addressed.

We thank the referee for the suggestion. We have changed the sentence to this one: “The implementation of core features in Pynapple addresses the concerns of efficiency and accuracy”

Page 9

• The authors wrote -

This is implemented via a set of specialized object subclasses of the BaseLoader class. To avoid code redundancy, these I/O classes inherit the properties of the BaseLoader class. "

From a programming perspective, the point of a base class is to avoid redundancy, so it might be better to just mention that this avoids the need to redefine I/O operations in each class.

We have rephrased the sentence as follows:

“This is implemented via a set of specialized object subclasses of the BaseLoader class, avoiding the need to redefine I/O operations in each subclass"

• The authors wrote -

"classes are unique and independent from each other, ensuring stability"

How do classes being unique and independent ensure stability? Perhaps here again the misunderstanding is due to the lack of a definition of stability.

We thank the referee for the remark. We first changed “stability” for “long-term backward compatibility”. We further added the following sentence to clarify this claim. “For instance, if the spike sorting tool Phy changes its output in the future, this would not affect the “Neurosuite” IO class as they are independent of each other. This allows each tool to be updated or modified independently, without requiring changes to the other tool or the overall data format.”

• The authors wrote -

"Using preexisting code to load data in a specific manner instead of rewriting already existing functions avoids preprocessing errors"

Here it might be helpful to use the lingo of Object-oriented programming. (e.g. inheritance and polymorphism). Defining these terms for a neuroscience audience would be useful as well.

We do not think it is necessary to use too much technical term in this manuscript. However, this sentence was indeed confusing. We have now simplified it:

“[…], users can develop their own custom I/O using available template classes. Pynapple already includes several of such templates and we expect this collection to grow in the future.”

Page 10

• The authors wrote -

"These analyses are powerful because they are able to describe the relationships between time series objects while requiring the fewest number of parameters to be set by the user."

It is not clear that this makes for a powerful analysis as opposed to an easy-to-use analysis.

We have changed “powerful” with “easy to use".

Page 12

"they are built-in and thus do not have any external dependencies"

If the authors want to retain this, it would be helpful to explain (perhaps in the introduction) why having fewer external dependencies is useful. And is it true that these functions use only base python classes?

We have rephrased this sentence as follows:

“they are for the most part built-in and only depend on a few common external packages, ensuring that they can be used stand-alone without relying on packages that are at risk of not being maintained or of not being compatible in the near future.”

Other comments:

• It would be helpful, as mentioned in the public review, to frame this work in the broader context of what is needed to go from data to scientific results so that people understand what this package does and does not provide.

We have added the following sentence to the discussion to make sure readers understand:

“The path from data collection to reliable results involves a number of critical steps: exploratory data analysis, development of an analysis pipeline that can involve custom-made developed processing steps, and ideally the use of that pipeline and others to replicate the results. Pynapple provides a platform for these steps.”

• It would also be helpful to describe the Pynapple so<ware ecosystem as something that readers could contribute to. Note here that GNU may not be a good license. Technically, GNU requires any changes users make to Pynapple for their internal needs to be offered back to the Pynapple team. Some labs may find that burdensome or unacceptable. A workaround would be to have GNU and MIT licenses.

The main restriction of the GPL license is that if the code is changed by others and released, a similar license should be used, so that it cannot become proprietary. We therefore stick to this choice of license.

We would be more than happy to receive contributions from the community. To note, several users outside the lab have already contributed. We have added the following sentence in the introduction:

“As all users are also invited to contribute to the Pynapple ecosystem, this framework also provides a foundation upon which novel analyses can be shared and collectively built by the neuroscience community.”

• This so<ware shares some similarities with the nelpy package, and some mention of that package would be appropriate.

While we acknowledge the reviewer's observation that Nelpy is a similar package to Pynapple, there are several important differences between the two.

First, Nelpy includes predefined objects such as SpikeTrain, BinnedSpikeTrain, and AnalogSignal, whereas Pynapple would use only Ts and Tsd for those. This design choice was made to provide greater flexibility and allow users to define their own data structures as needed.

Second, Nelpy is primarily focused on electrophysiology data, whereas Pynapple is designed to handle a wider range of data types, including calcium imaging and behavioral data. This reflects our belief that the NWB format should be able to accommodate diverse experimental paradigms and modalities.

Finally, while Nelpy offers visualization and high-level analysis tools tailored to electrophysiology, Pynapple takes a more general-purpose approach. We believe that users should be free to choose their own visualization and analysis tools based on their specific needs and preferences.

The package has now been cited.

Reviewer #2 (Public Review):

Pynapple and Pynacollada have the potential to become very valuable and foundational tools for the analysis of neurophysiological data. NWB still has a steep learning curve and Pynapple offers a user- friendly toolset that can also serve as a wrapper for NWB.

The scope of the manuscript is not clear to me, and the authors could help clarify if Pynacollada and other toolsets in the making become a future aspect of this paper (and Pynapple), or are the authors planning on building these as separate publications.

The author writes that Pynapple can be used without the I/O layer, but the author should clarify how or if Pynapple may work outside NWB.

Absolutely. Pynapple can be used for generic data analysis, with no requirement of specific inputs nor NWB data. For example, the lab is currently using it for a computational project in which the data are loaded from simple files (and not from full I/O functions as provided in the toolbox) for further analysis and figure generation.

This was already noted in the manuscript, last paragraph of the section “Importing data from common and custom pipelines”

“Third, users can still use Pynapple without using the I/O layer of Pynapple.”.

We have added the following sentence in the discussion

“To note, Pynapple can be used without the I/O layer and independent of NWB for generic, on-the-fly analysis of data.”

This brings us to an important fundamental question. What are the advantages of the current approach, where data is imported into the Ts objects, compared to doing the data import into NWB files directly, and then making Pynapple secondary objects loaded from the NWB file? Does NWB natively have the ability to store the 5 object types or are they initialized on every load call?

NWB and Pynapple are complimentary but not interdependent. NWB is meant to ensure long-term storage of data and as such contains a as much information as possible to describe the experiment. Pynapple does not use NWB to directly store the objects, however it can read from NWB to organize the data in Pynapple objects. Since the original version of this manuscript was submitted, new methods address this. Specifically, in the current beta version, each object now has a “save” method. Obviously, we are developing functions to load these objects as well. This does not depend on NWB but on npz, a Numpy specific file format. However, we believe it is a bit too premature to include these recent developments in the manuscript and prefer not to discuss this for now.

Many of these functions and objects have a long history in MATLAB - which documents their usefulness, and I believe it would be fisng to put further stress on this aspect - what aspects already existed in MATLAB and what is completely novel. A widely used MATLAB toolset, the FMA toolbox (the Freely moving animal toolbox) has not been cited, which I believe is a mistake.

We agree that the FMA toolbox should have been cited. This ha now been corrected.

Pynapple was first developed in Matlab (it was then called TSToolbox). The first advantage is of course that Python is more accessible than Matlab. It has also been adopted by a large community of developers in data analysis and signal processing, which has become without a doubt much larger than the Matlab community, making it possible to find solutions online for virtually any problem one can have. Furthermore, in our experience, trainees are now unwilling to get training in Matlab.

Yet, Python has drawbacks, which we are fully aware of. Matlab can be very computationally efficient, and old code can usually run without any change, even many years later.

A limitation in using NWB files is its standardization with limited built-in options for derived data and additional metadata. How are derived data stored in the NWB files?

NWB has predetermined a certain number of data containers, which are most common in systems neuroscience. It is theoretically possible to store any kind of data and associated metadata in NWB but this is difficult for a non-expert user. In addition, NWB does not allow data replacement, making is necessary to rewrite a whole new NWB file each time derived data are changed and stored. Therefore, we are currently addressing this issue as described above. Derived data and metadata will soon be easy to store and read.

How is Pynapple handling an existing NWB dataset, where spikes, behavioral traces, and other data types have already been imported?

This is an interesting point. In theory, Pynapple should be able to open a NWB file automatically, without providing much information. In fact, it is challenging to open a NWB file without knowing what to look for exactly and how the data were preprocessed. This would require adapting a I/O function for a specific NWB file. Unfortunately, we do not believe there is a universal solution to this problem. There are solutions being developed by others, for example NWB Widgets (NWB Widgets). We will keep an eye on this and see whether this could be adapted to create a universal NWB loader for Pynapple.

Reviewer #2 (Recommendations For The Authors):

Other tools and solutions are being developed by the NWB community. How will you make sure that these tools can take advantage of Pynapple and vice versa?

We recognize the importance of collaboration within the NWB community and are committed to making sure that our tools can integrate seamlessly with other tools and solutions developed by the community.

Regarding Pynapple specifically, we are designing it to be modular and flexible, with clear APIs and documentation, so that other tools can easily interface with it. One important thing is that we want to make sure Pynapple is not too dependent of another package or file format such as NWB. Ideally, Pynapple should be designed so that it is independent of the underlying data storage pipeline.

Most of the tools that have been developed in the NWB community so far were designed for data visualisation and data conversion, something that Pynapple does not currently address. Multiple packages for behavioral analysis and exploration of electro/optophysiological datasets are compatible with the NWB format but do not provide additional solutions per se. They are complementary to Pynapple.

Reviewer #1 (Public Review):

The authors developed an extension to the pairwise sequentially Markov coalecent model that allows to simultaneously analyze multiple types of polymorphism data. In this paper, they focus on SNPs and DNA methylation data. Since methylation markers mutate at a much faster rate than SNPs, this potentially gives the method better power to infer size history in the recent past. Additionally, they explored a model where there are both local and regional epimutational processes.

Integrating additional types of heritable markers into SMC is a nice idea which I like in principle. However, a major caveat to this approach seems to be a strong dependence on knowing the epimutation rate. In Fig. 6 it is seen that, when the epimutation rate is known, inferences do indeed look better; but this is not necessarily true when the rate is not known. A roughly similar pattern emerges in Supp. Figs. 4-7; in general, results when the rates have to be estimated don't seem that much better than when focusing on SNPs alone. This carries over to the real data analysis too: the interpretation in Fig. 7 appears to hinge on whether the rates are known or estimated, and the estimated rates differ by a large amount from earlier published ones.

Overall, this is an interesting research direction, and I think the method may hold more promise as we get more and better epigenetic data, and in particular better knowledge of the epigenetic mutational process. At the same time, I would be careful about placing too much emphasis on new findings that emerge solely by switching to SNP+SMP analysis.

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

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Reply to the reviewers

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

Summary: This manuscript by Lan et al. addresses the still incompletely resolved question as to how branching morphogenesis of the embryonic mammary epithelium is regulated at the molecular and cellular level. Using (combinatorial) primary explant cultures of wildtype and genetically engineered mouse embryos, in which the authors have developed a unique expertise over many years, together with imaging and RNAseq analyses, they (i) show that the timing of epithelial branching is dictated by the biological age of the epithelium, but that an epithelial-mesenchymal interaction is required to bestow branching ability on the mammary epithelium somewhere between E13.5 and E16.5, (ii) seek to determine if and how lineage and cell proliferation affect branching, (iii) show that while salivary mesenchyme can promote growth (i.e. branching density) of the E16.5 mammary epithelium, the mode of branching (i.e. lateral branching vs tip-clefting) is an intrinsic property of the mammary epithelium, (iv) use transcriptomics to identify genes that are likely to control either mammary- or salivary gland specific growth and/or branching patterns, (v) hypothesize that low levels of WNT signaling in the mammary gland mesenchyme (due to relatively high expression of WNT signaling inhibitors) are responsible for mammary specific branching, (vi) show that hyperactivation of WNT/CTNNB1 signaling in the mesenchyme indeed induces hyperbranching, (vii) identify Eda and Igf1 as putative mediators and paracrine signaling factors that regulate branching of the mammary epithelium upon secretion from the mesenchyme downstream of WNT/CTNNB1 signaling and (viii) show that mammary gland branching is impaired in Igfr1 null embryos.

Major comments: 1. Overall, this is a solid study that is well controlled and technically of high quality. The materials and methods should allow follow up and replication by others and the transcriptomic data have been made available via NCBI GEO. I think the authors convincingly demonstrate points (i), (iii), (iv) and (vi) and (viii). I have some questions regarding (ii), (v) and (vii) and (viii) that I will pose below.

Our response:

We thank the reviewer for the careful assessment and recognition of our work. In the subsequent sections, we have tried to address all the concerns raised by the reviewer.

Re: (ii): The authors try to study the link between basal cell fate and branching. They use position of the cells (which they describe clearly and which is a good choice), since they cannot use specific markers due to the fact that the basal and luminal linages have not yet segregated at this point. This part of the manuscript is not the most straightforward to follow. The most obvious experiment would have been to focus on the location of the cells and their associated cell cycle profile - but the authors themselves have just recently published a pre-print (their REF #54, now also out in JCB) that is an in-depth study of the link between cell proliferation + cell motility and branching, but this only becomes apparent in the discussion. In that sense, Fig2 of the current manuscript is less novel, although it is nice to see that it holds up in a slightly different analysis.

Our response:

We thank the reviewer for acknowledging our recently published work, which is focusing on the active branching phase during late embryogenesis/around birth. In the current proliferation analysis, however, our focus was on a different aspect of embryonic mammary gland development: understanding the mechanism underlying the ability to acquire competence to branch, i.e. how the epithelium changes between late bud and sprout stages. Our data obtained from tissue recombination and 3D culture experiments suggest that heterotypic mesenchymes or mesenchyme-free 3D organoid culture conditions do not provide sufficient signals to support branching of mammary epithelia before E16.5. We have rephrased the text to better emphasize this point.

Instead of focusing on the cell cycle markers, the authors turn to a K14-Eda mouse model - which shows precocious branching and a temporary reduction in K8 expression. They also analyze Eda-KO embryos. Quite frankly, I find the authors' reasoning difficult to follow here and I cannot deduce how these experiments really address the question at hand (i.e. how lineage and cell proliferation affect branching), so I hope they can rewrite this section of the paper to make the arguments more clear and easy to follow for the reader who, at this point, knows little about Eda. For example, the authors present the argument that K14-Eda mice show a transient reduction in K8 expression - but we don't know if that also really means a (temporary?) change in (future?) luminal cell fate. In fact, since Eda later also makes an appearance as a candidate factor to be secreted by the mesenchyme together with Igf1, I wonder if their K14-Eda data would not be better suited to underscore that point instead and if the authors should perhaps eliminate this section altogether and just refer to their prior work in REF #45. If the authors think the current data add something more, than they need to be more explicit about this (and then also introduce the link to REF #45 in the results section).

__Our response: __

We agree with all the reviewers in that this part of the manuscript was not mature enough and provided only indirect evidence on the potential link between lineage segregation and branching ability. This is an important question in the field that merits a study of its own and should be addressed with better tools than those available to us at present. As suggested by reviewers #1 and #3, we have omitted this part in the revised manuscript.

Re: (v): Do the authors have any WNT/CTNNB1 target genes that they can include in their transcriptomics analysis to show that the WNT/CTNNB1 signaling levels are indeed lower in the mammary mesenchyme? Axin2 comes to mind, but there are some other negative feedback targets that are often induced across tissues, e.g. Rnf43 and/or Znrf3 and/or Sp5?E.g. to include in FIg6E?

__Our response: __

In the original manuscript (lines 339-342), we have performed the GSVA analysis comparing the KEGG database, and the significantly altered pathways comparing different mammary mesenchymes with salivary gland mesenchyme have been pooled and displayed as heatmap in Supplementary Fig 4b. The WNT signaling pathway is lower in the mammary mesenchyme, especially at E16.5.

As suggested by the reviewer, we have analyzed Axin2, the most commonly used readout of WNT/CTNNB1 signaling activity in our RNA-seq data that we include as a __new Supplemental Fig. 4c __in the preliminary revised manuscript. Axin2 data indicate that Wnt/β-catenin signaling activity is lower in the E16.5 fat pad, where branching takes place, compared to younger stages of mammary gland and the salivary gland.

Plan for the final revision:

Additionally, we will provide expression data of a transgenic Wnt reporter from the same developmental stages and tissues that were used to generate the RNA-seq data.

Re: (vii) and (viii): The authors convincingly show the phenotype of the Igfr1 KO mice, but I hope the authors concur that an epithelial only Igfr1 KO (or alternatively a mesenchymal only Igf1 KO, or epithelial/mesenchymal recombination experiments with WT vs IGFR1 null or IGF1 null tissue, or experiments with small molecule inhibitors of IGF1/IGFR1 signaling) would have given more solid mechanistic evidence regarding the presumed paracrine effect of IGF1 signaling. I am not asking the authors to perform another mouse experiment or even generate or use these conditional strains, but if the authors agree, then I do think this would merit some attention in the discussion section. See also my comments regarding Eda in point 1.

Our response:

As shown in the current manuscript, Igf1 is expressed in the mammary and salivary gland mesenchyme. This finding is in line with E14 in situ expression data available in Genepaint (https://gp3.mpg.de/results/Igf1) showing that overall in embryonic tissues, Igf1 is mainly produced in mesenchymal tissues. Of note, in Genepaint, a clear signal can be detected in the salivary gland mesenchyme, not the epithelium. Published E16 and E18 datasets indicate low level of Igf1 expression in the mammary epithelium (https://wahl-lab-salk.shinyapps.io/Mammary_snATAC/). Hence, we conclude that Igf1 is mainly produced by mesenchymal cells. Instead, Igf1r appears to be rather ubiquitously expressed.

A previous study assessed BrdU incorporation in Igf1r-/- mammary buds at E14.5, and reported a specific proliferation defect in the epithelium, while no difference was detected in the mesenchyme (Fig. 9, Heckman et al., 2007; PMID:17662267). However, we cannot exclude the possibility of autocrine, mesenchymal Igf1/Igf1r signaling, which in turn could lead to upregulation of a paracrine factor to regulate epithelial growth.

We agree with the reviewer in that novel conditional mouse models are beyond the scope of the current study. However, we do not think that small molecule drugs could be used to block Igf1r activity in a tissue-specific manner neither.

Plan for the final revision:

To further delineate the paracrine and/or autocrine role of Igf1/Igf1r pathway during mammary epithelial growth and branching, we will perform tissue recombination experiments between Igf1r-/- and control mammary epithelium and mesenchyme, as suggested by the reviewer.

Minor comments: - A few minor spelling/grammar errors, including a couple of "the"s missing (first line of the abstract, and also preceding "Majority" in line 148.

Our response:

We apologize for these slips. They have been corrected in the revised manuscript.

• Line 517-518: please also include the details for the Eda mice.

Our response:

We apologize for missing this important information in materials and methods. We have included a short introduction of the K14-Eda mice, a new reference for the original publication producing them, as well as the Jackson Laboratories strain number for Eda-/- (a.k.a. Tabby) mice in the revised manuscript.

• 1f spelling error: separation

Our response:

The spelling error has been corrected in the revised manuscript.

**Referees cross-commenting**

Having read all three review reports I think they are pretty much in agreement, with shared questions about the inclusion/meaning/discussion of the lineage specification data and also agreement about the overall technical solidity of the data and this approach.

I gather that reviewer #2 asks for more controls than myself or reviewer #3 and while I think all of their points are valid, in principle, I don't think all of these are required. I should add that I am inclined to trust the authors on their ability to separate mesenchyme and epithelium as they have been developing and optimising this system over many years.

Our response:

We are grateful to the reviewer for the reliance on the technical aspect of our experiments. We do routinely monitor tissue purity in the recombinants (for more details, see our response to reviewer #2). To demonstrate this, we have included new data in new Supplementary Fig. 1a,b and new Supplementary Fig. 3. We believe these additions will further enhance the validity of our findings and effectively address the concerns raised by reviewer 2.

Reviewer #1 (Significance (Required)):

General assessment: This is a carefully executed study in which an impressive amount of (combinatorial) embryonic mammary tissue explant experiments are combined with quantitative imaging and transcriptomics analysis.

The main limitations of the work lie in the fact that the investigation of a potential link between branching and the cell cycle is not entirely novel, as the authors themselves recently published an nice pre-print (now also out in JCB) describing similar analyses. In addition, the mechanistic link between WNT/CTNNB1 signaling in the mesenchyme and the paracrine signaling activities of the presumed downstream effectors EDA and IGF, while plausible, is not yet complete. The work also does not yet addresses what exactly the branching identity is that is bestowed upon the mammary epithelium between E13.5 and E16.5 and how this then becomes an intrinsic (epigenetic?) feature of the mammary gland.

Advance: This work provides more insight into the embryonic branching of the mammary gland - a stage of mammary gland development that is still poorly understood and that is, in general, understudied. In part, the work confirms prior work in the literature (their REF #19) regarding mammary and salivary gland tissue recombination experiments. It supplements this with a more elaborate time series of heterochronic and heterologous epithelium/mesenchyme explant cultures, using genetically engineered (and fluorescently labeled) mouse tissues to allow better and quantitative imaging. The transcriptomic analysis of different mesenchyme populations is also informative and allows the researchers to propose a putative mechanism for why the mammary gland branches differently from the salivary gland. The advance is both technical and functional, as well as conceptual, with some advance in terms of mechanism.

Audience: This works should appeal to mammary gland biologists interested in the molecular and cellular mechanisms of (early) mammary gland development, as well as to a broader community of developmental biologists studying branching morphogenesis in tissues such as lung, kidney and salivary gland.

My expertise: WNT signaling and mammary gland biology, at the intersection of developmental, stem cell and cancer biology

__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __

The mammary gland is a branched structure that consists of a bilayered epithelium embedded in a specialized mesenchyme. In mice, at 11,5 days of embryogenesis, the ectoderm thickens forming 5 pairs of peculiar structures called placodes. During the following days, the placodes will grow and invaginate into the surrounding mammary mesenchyme and they will finally start to branch by the end of embryogenesis (E16). It has been suggested that the bidirectional communication between the growing mammary gland and the surrounding mesenchyme plays a pivotal role in the determination of each step of mammary gland development (placode formation, mammary bud invagination, gland outgrowth, branching). The role of different signalling molecules has already been shown, particularly for the placode growth and mammary bud invagination. Nevertheless, the pathways regulating embryonic mammary gland branching are still incompletely understood. In this manuscript, Lan and colleagues aim to decipher the correlation between different stages of mammary gland development such as proliferation, lineage segregation and ductal branching. Furthermore, they want to define which stage of mammary development is intrinsically determined by the epithelium and which one requires the supportive guidance of the mesenchyme. Lastly, they aim to discover the key signal for the growth and branching of mammary epithelium. To these purposes, they used an ex vivo model of heterochronic epithelial-mesenchymal recombination. In particular, they micro-dissected the epithelium and/or the mesenchyme from murine mammary glands at different stages of embryonic development (i.e. at E13,5 for the quiescent phase or 16,5 for branching phase) and explanted them together in different combinations using fluorescent reporters. To assess the role of the mesenchyme they also cultured the epithelium in a mesenchyme free 3d structure. Through this model they demonstrated that the presence of the mesenchyme is necessary for the priming of mammary epithelium for branching, since only E16,5 epithelial cells were able to grow and branch in a mesenchyme free 3D experiment. Nevertheless, intrinsic properties of the epithelium are necessary for the timing of branching, since E16,5 mesenchyme was not able to accelerate the outgrowth of E13,5 epithelia. In order to determine which epithelial properties are important, the authors correlated the beginning of cell proliferation in the embryonic mammary gland to the beginning of the branching phase. They indeed used the Fucci2a mouse model to carefully characterise the timing of mammary cells proliferation at different stages of embryonic development, concluding that the great majority of proliferating cells reside in the inner part of the mammary bud until E14,5, while in the external part at later stages. Regarding the importance of cell proliferation, Lan and colleagues claim that the beginning of the branching phase is not its direct consequence, thanks to the use of the K14Cre- Eda mouse model, known to have anticipated mammary gland development. Using this and the Eda-/- models, the authors also sustain that the branching occurs independently of the lineage specification of the epithelium. The use of salivary mesenchyme instead the mammary one was able to increase the number of branching of E16,5 mammary epithelium. Nevertheless, this model demonstrated that the branching pattern (side branching vs tip bifurcation) is an intrinsic feature of the epithelium. Lan and colleagues also defined the transcriptomic profiles of the mammary and salivary mesenchymes at different stages. In particular, they observed an increased expression of negative regulators of Wnt pathway in the mammary mesenchyme compared to the salivary mesenchyme. Moreover, using a mouse model where B-catenin is stabilised, they observed increased tip production in the mammary gland epithelium. They also showed that IGF1 production is increased after Wnt pathway activation and they tested its function, both treating their ex vivo cultures with exogenous IGF1 and using Igf1r-/- mouse models.

Major comments 1- The great majority of the results of the manuscript are based on an ex vivo model of heterochronic epithelial-mesenchymal recombination. Since the authors are studying the effect of the mesenchyme of different stages on the epithelium (and vice versa), the purity of the two compartments after the dissection is particularly important. Although they said that the purity is evaluated (line 112), it would be important to show a control staining in which they use known markers of the mesenchyme with no colocalization with the fluorescent reporter of the epithelium.

Our response:

We agree with the reviewer that the purity of the separated tissues is very important for our conclusions. This is why we have used genetically labeled tissues in all recombination experiments: the epithelium and the mesenchyme were always isolated from embryos ubiquitously expressing GFP or tdTomato. We find this the most reliable way to assess the origin and purity of the isolated tissues. If there was any carry-over mesenchyme isolated with the GFP+ epithelium, this would be revealed as GFP+ mesenchymal cells in the recombinants consisting of otherwise tdTomato+ mesenchyme. And vice versa: any carry-over tdTomato+ epithelium isolated with the mesenchyme would be revealed as tdTomato+ epithelial cells in the recombinants. We apologize for not making this clear enough in the original manuscript. In the revised manuscript, we now provide confocal high-resolution images of the recombinant explants (new Supplementary Fig. 1a,b). The explants have been co-stained with the epithelial marker EpCAM, revealing a robust colocalization between the ubiquitously expressed florescent labels in the designated epithelial tissues and the EpCAM.

2- Another important point for understanding the quality and impact of these findings is to assess the similarities and differences, if there are, between the in vivo mesenchyme and the ex vivo one. Indeed, once explanted and put in culture, mesenchymal cells could change their transcriptomic profile and consequently change their signals to the epithelium. The authors should assess the expression of the genes and pathways studied during embryonic development in vivo.

Our response:

The reviewer is correct in that the transcriptomes will likely undergo some changes when organs are cultured ex vivo. This is why RNA-seq was done on freshly isolated tissues. Regarding the potential changes taking place ex vivo, however, we do not consider them relevant with respect to the questions we are addressing in this study. The reason is (as reported in the manuscript) that all control recombinations (homochronic recombinations such as E13 epithelium + E13 mesenchyme, E16 epithelium + E16 mesenchyme etc.) branched essentially as in vivo. Therefore, we find the results and conclusions made from the tissue recombination experiments solid.

3- The authors clearly showed that E16,5 epithelium is able to branch in a mesenchyme free 3D culture model, while epithelia from earlier stages don't. This led to the conclusion that mesenchyme is necessary for acquiring the branching ability. Nevertheless, the authors also said that early stages epithelia scarcely grow in the mesenchyme free 3D culture. Therefore, the lack of branching may be due to the lack of growth, if not the increase of death, of epithelial cells. The authors should quantify the size and the cell death of the epithelia in the different culture conditions and discuss better this point.

Our response:

The reviewer is correct in that one of the key functions of the mammary mesenchyme up to E16.5 may be to provide survival signals for the epithelium, and this might explain why epithelia younger than E16.5 fail to grow/branch when recombined with salivary gland mesenchyme and in mesenchyme-free organoid culture.

Plan for the final revision:

To address this issue, we will assess apoptosis in mammary epithelia cultured in the mesenchyme-free 3D culture organoid set-up.

4- The Fucci2a model allowed to assess the proliferation of embryonic mammary epithelium, showing that the great majority of proliferating cells are basal, at late stages of development (line 182). As it has already been shown, lineage specification is a late process during mammary gland development. The fact that the proliferating cells reside at the external part of the bud does not mean that they are basal cells yet. A p63/K8 staining could be important to understand if the increased proliferation occured in already specified basal cells or not.

__Our response: __

Indeed, mammary lineage specification is a later process. As pointed out in the manuscript and by reviewer #1, the widely used basal and luminal lineage markers have not yet segregated to separate compartments at the developmental stages analyzed in our study, and therefore cannot be used as tools for this purpose. We would like to emphasize that in the manuscript, we analyzed the cells based on their position, and have used the term basal to indicate the basal position, not the prospective lineage. Accordingly, we used the term inner instead of luminal cells to indicate their location, not lineage. We have further clarified this point in the preliminary revised manuscript.

5- The use of Fucci2a model showed that 20% of epithelial cells are proliferative at E13,5. This phase is considered as "quiescent" by the authors (line 120), but the moderate proliferation rate shown in this experiment demonstrated that it is not. A change of the nomenclature is needed.

__Our response: __

We have removed the word “quiescent” from the text.

6- Through the use of K14-Eda and Eda-/- models, the authors claimed that the lineage specification is not a prerequisite for ductal branching. To support this point, they showed that the K14-Eda mice have an anticipated branching although the expression of K8 in the inner part of the bud is transitorily decreased. The authors link the K8 downregulation to a transient suppression of the luminal lineage, but this is clearly overclaimed. Although K8 is a known marker of luminal lineage, the downregulation of one marker is not sufficient to support their thesis. They should first check more markers and in particular critical regulators of luminal lineage as Notch1, Foxa1 and Elf5. Lately, the use of different models that drive embryonic epithelial cells to a forced lineage commitment (Notch1 or Δnp63 overexpression) would support more their claim. As additional evidence, the authors showed that Eda is able to promote basal cell signature. Firstly, the authors should better explain why this point would support their thesis. Secondly, the supplementary figure 2b does not show which genes are taken into account to define the basal signature. A list of these genes would be helpful, as well as staining for some representative proteins.

Our response:

We thank the reviewer for these constructive suggestions. We agree with all reviewers in that this part of the manuscript was not mature enough and provided only indirect evidence on the potential link between lineage segregation and branching ability. This is an important question in the field that merits a study of its own to be addressed with better tools than those available to us at present. As suggested by reviewers #1 and #3, we have omitted this part in the revised manuscript.

7- The authors used the same mouse models to assess the importance of proliferation in the determination of ductal branching and they claimed that proliferation is not a sufficient feature. This conclusion was supported by two observations. The first one is the fact that the K14-Eda model shows an increased cell proliferation at early stages compared to wt, coupled with anticipated branching. Secondly, although having smaller glands compared to wt and showing a delay in ductal branching, Eda-/- mice have an epithelial proliferation rate very similar to wt. Again, the conclusion that proliferation is not sufficient for branching is overclaimed. Firstly, the authors should explain how the buds in wt and Eda-/- mice have different sizes although the similar proliferation (increased cell death?, cellular volume?). Secondly, to support the thesis that proliferation is not sufficient for branching, functional experiments should be performed (see point 12). For instance, the short-time treatments with inhibitors or promotors of proliferation may help to understand the effective role of proliferation in the determination of branching.

Our response:

We show that there is no direct link between onset of proliferation and acquisition of branching ability. However, we are not claiming that proliferation is not important for branching, as obviously new cells are needed as building blocks of growing tissues. In a recently published paper, we have assessed the role of proliferation in branch point formation in embryonic mammary glands. Using mitomycin C to block proliferation, we showed that initiation of new branches occurs even when proliferation is blocked (Myllymäki et al., JCB2023, PMID: 37367826).

The reviewer was also asking why Eda-/- mammary primordia are smaller at E15.5-E16.5 despite similar proliferation rates. In the revised manuscript, we have quantified the volume of E13.5 Eda-/- and control mammary buds and show that Eda-/- buds are ~25% smaller (3.5 ± 0.8 x 105 µm3 in Eda-/- vs. 4.6 ± 0.7 x 105 µm3 in control, mean ± SD) already at the bud stage (new Supplementary Fig. 2c,d).

We have also quantified the cellular size in Eda-/- and control mammary glands at E13.5 and E15.5 and found that mammary epithelial cells in Eda-/- embryos are ~15% smaller (new Supplementary Fig. 2e,f). Together, these data indicate that the smaller size of E15.5-E16.5 Eda-/- mammary glands is a combinatorial effect the smaller mammary anlage at E13.5 and smaller cell size. These findings, while interesting on their own, do not challenge our conclusions regarding the link between onset of proliferation and acquisition of branching ability.

8- The heterotypic epithelial-mesenchymal recombination using the salivary gland is interesting. Nevertheless, some stainings to assess the purity of their systems are again required (e.g., marker of salivary epithelium to verify the purity of the mesenchyme and vice versa).

__Our response: __

As mentioned above, all tissue recombination experiments were performed so that the epithelium and the mesenchyme originated from genetically labelled embryos expressing different fluorescent proteins. In the revised manuscript, we provide confocal images of the salivary-mammary tissue recombinants (new Supplementary Fig. 3), confirming the purity of the tissue compartments used in these experiments.

This model clearly showed that the mammary epithelium can form more branching when combined with the salivary mesenchyme. Moreover, the salivary epithelium preferentially branches through tip bifurcation, while mammary epithelium combined with the salivary mesenchyme has a mixed pattern of tip bifurcation and side branching (typical of the mammary gland). The authors thus concluded that the branching pattern is an intrinsic feature of the epithelium. However, a comparison between the percentage of tip bifurcation and side branching in the heterotypic combination and the homotypic combination between mammary epithelium and mammary mesenchyme is crucial to understand this point. Indeed, these results are not sufficient to exclude that the branching pattern is partially determined by intrinsic features and partially by extrinsic signals. The authors should carefully quantify the branching pattern in the homotypic combination and compare that to the heterotypic one. If the percentage of tip bifurcation do not change, their conclusion is correct; if this percentage increases in the heterotypic combination, it would be a sign of a partial effect of the signals of the mesenchyme.

Our response:

We thank the reviewer for raising this question. We have independently generated data on the type of mammary gland branching events in two papers with somewhat different culture and imaging conditions (Lindström et al., BiorXiv 2022 and Myllymäki et al., JCB, 2023, PMID: 37367826). Both analyses showed that in embryonic mammary glands, the majority of branching events (~70%) occurs by side-branching. These data are in line with the current study that we have now complemented to include also the mammary-mammary recombination experiments (revised Supplementary Video 1, revised Fig. 4b). Quantification of branching events revealed no significant difference in the type of branching events of mammary epithelia grown with salivary or mammary gland mesenchyme (revised Fig. 4c), further supporting our initial conclusions.

9- Through the analysis of their transcriptomic data, Lan and colleagues found that the mammary mesenchyme expresses higher levels of negative regulators of Wnt pathway compared to the salivary mesenchyme. To demonstrate the value of their findings, they should confirm this in vivo, through staining of known Wnt proteins on the salivary and mammary mesenchymes at the embryonic stage.

Our response:

In mammals, there are 19 Wnt ligands, over a dozen secreted Wnt inhibitors, 10 Frizzled receptors, two Lrp co-receptors, and numerous other pathway modifiers that contribute to the net Wnt signaling activity in a complex manner. Furthermore, it has been “notoriously difficult to generate useful antibodies to vertebrate Wnt proteins...In general, these sera do not detect endogenous Wnt proteins in cell extracts, nor do they detect Wnt proteins in tissues by staining techniques. Hence, there are few data on Wnt protein distribution in intact vertebrate animals.” This is a direct citation from the Wnt Homepage, maintained by the Nusse Lab; https://web.stanford.edu/group/nusselab/cgi-bin/wnt/reagents#antibod.

For all these reasons, we do not find this approach feasible nor informative.

Instead, in the revised manuscript, we report the expression levels of Axin2, the most commonly used transcriptional readout of canonical Wnt activity in our RNA-seq data (new Supplementary Fig. 4c). Axin2 levels are lowest in the E16 fat pad where mammary branching takes place, much lower than in any other tissues analyzed in the study.

Plan for the final revision:

To complement these findings, we will additionally provide expression data of a transgenic Wnt reporter from the same developmental stages and tissues that were used to generate the RNA-seq data.

10- Since the ability of the salivary mesenchyme to promote a higher rate of branching in the mammary epithelium, the authors wanted to assess what could be the role of Wnt signalling. To do so, they used a mouse model where B-catenin is stabilised, allowing an increased Wnt signalling in the mammary mesenchyme. As a result, they observed increased branching in the mammary epithelium. They also found that IGF1 is a ligand regulated by Wnt pathway in the mesenchyme. Therefore, the use of exogenous IGF1 in their ex vivo model was able to increase the branching of the mammary epithelium. Moreover, Igf1r-/- embryos showed a significant decrease of mammary gland branching. The conclusion based on these experiments was that the Wnt-Igf1-Igf1r axis plays a pivotal role in the promotion of mammary gland branching during embryogenesis. This conclusion is overclaimed for different reasons. Firstly, the normalization of the ductal branching to the body weight is insufficient to exclude that the impact of the Igf1r knockout may have severe consequences on the mammary gland formation, upstream of the ductal branching. Another parameter for this normalization is required (e.g., size of the bud before branching, proliferation status, etc).

Our response:

We agree with the reviewer in that Igf1r knockout may affect mammary gland formation in multiple ways, and also prior to onset of branching, as already indicated in the original manuscript: “…apart from one study reporting the smaller size of the E14 mammary bud in IGF-1R deficient embryos …” (line 398-399 in the revised version) and ‘…mammary gland 3 that was consistently absent.’ (line 414-415 in the revised version).

To assess whether the reduced size and branching of E16.5/E18.5 Igf1r-/- mammary glands is merely a consequence of the smaller anlage, the revised manuscript includes new data reporting quantification of the volume of mammary gland 2 of Igf1r-/- and wild type littermate embryos at E13.5, E16.5, and E18.5 from 3D confocal images of whole mount EpCAM stained mammary glands. As can be seen from the new Fig. 7g-h, at E13.5, the mutant mammary buds are about 60% of the size of the controls, at E16.5, 25% and at E18.5 only 20 % revealing a progressive defect, indicative of a specific defect at the outgrowth and branching stage. This conclusion was validated by normalization to the body weight: at E13.5 the size of Igf1r-/- mammary anlage did not differ from that of the wild type embryos (p = 0.11), at E16.5 the sprouts were smaller in the mutants, though the difference did not reach statistical significance (p = 0.08), while at E18.5, the Igf1r-/- mammary glands were significantly smaller (p = 0.000021) (new Fig. 7i). We find these data compelling evidence for a specific role for Igf1r in outgrowth and branching of the embryonic mammary gland.

The use of alternative models to specifically knockout the receptor in the epithelium or the ligand in the mesenchyme (e.g. viruses) would be even more useful to specifically focus on the role of this pathway for ductal branching excluding side effects.

Our response:

We thank the reviewer for this suggestion. Unfortunately, based on our experience, viral shRNA delivery is not sufficiently efficient for effective gene silencing, unlike Cre delivery for a gain-of-function approach (used in the current study to flox out exon 3 of beta-catenin) in case where the endogenous pathway activity is very low and therefore, targeting even a subset of cells is sufficient for upregulation of paracrine factors.

Plan for the final revision:

To address the question on the autocrine or paracrine role of Igf1r, we will perform tissue recombination experiments between Igf1r-/- and control mammary epithelium and mesenchyme.

Another limit of this model is the fact that Igfr1 can be bound by Igf2 as well and we cannot exclude that this has an impact too (except if Igf2 is not expressed at this stage). A quantification of Igf2 expression may be useful.

Our response:

Indeed, we cannot exclude the possibility that Igf2 could also play a role (Igf2 expression was similar to Igf1 in our RNA-seq dataset, see Supplementary Fig. 5), but the connection of mesenchymal Wnt signaling activity was to Igf1, not Igf2 – in fact Igf2 was somewhat downregulated in Wnt3A treated sample reported by Wang et al. (Wang et al., 2021) (highlighted by an arrow in the revised Fig. 6). We have also clarified this point in the Discussion of the preliminary revised manuscript.

11- From the experiments presented in this section it is clear that Wnt-Igf1-Igf1r axis has to be finely regulated to have the correct amount of ductal branching in the embryonic mammary epithelium. Nevertheless, the author just showed the RNA levels of Igf1 in the different compartments they have analysed. Stainings to see the effective presence of the ligand on the tissue is mandatory to clarify the role of this axis in the ductal branching in vivo.

Our response:

Igf1-Igf1r signaling plays a critical growth promoting function during embryonic and postnatal development. The expression of Igf1 at RNA and protein level has been detected in almost all tissues in humans (Daughaday et al., Endocr. Rev., 1989; PMID: 2666112). Given that Igf1 is a secreted protein and multiple Igf binding proteins (Igfpbs) (that regulate the bioactivity of Igf1 by sequestering it) are expressed in the mammary and salivary gland mesenchyme (Supplementary Fig. 5), we find it unlikely that Igf1 staining would provide any additional information to the current study, as they cannot be used to assess the source of Igf1, nor the location of the signaling activity.

Furthermore, as underlined by the authors, this axis is specifically important and upregulated in the salivary gland. Due the limit of the Igf1R-/- model, we cannot exclude that, although Wnt-Igf1-Igf1r axis is able to increase the branching ability of mammary epithelium, the normal branching rate observed in wt mice is due to other pathways.

Our response:

We agree with the reviewer in that other pathways are also important in regulating normal mammary gland branching, for example, Eda/NF-κB and FGF pathways as we described in the Introduction. Our results do not exclude the possibility that also pathways other than Wnt regulate Igf1 expression. The reviewer is correct that if a paracrine factor is expressed in the salivary gland but not in the mammary mesenchyme, its physiological effect may be limited to the salivary gland. Indeed, cluster 5 identified by the mFuzzy analysis (Fig. 5f) is likely to include some genes like that. This is why we decided to focus on cluster 6 genes like Igf1. In the revised manuscript, we have better highlighted the difference between cluster 5 and 6 genes.

Unfortunately, with the currently available tools, we cannot test the importance of the endogenous mesenchymal Wnt signaling activity by inactivating Wnt signaling activity specifically in the mesenchyme at the time point when branching begins. This would require an inducible mesenchymal Cre line (mesenchymal β-catenin is essential for the early fate specification of the primary mammary mesenchyme; Hiremath et al., 2012, PMID: 23034629), and conditional β-catenin null mouse. We do not have such mice available and we find that these experiments are beyond the scope of the current study.

12- Lastly, once claimed to have found the key factor necessary for ductal branching promotion, the authors should also test if the proliferation and lineage segregations are unaffected in this context, confirming their dispensable role claimed in the initial part of the manuscript.

__Our response: __

Igf1/Igf1r is well-known for its growth promoting function via cell proliferation. We have no reasons to think that this would not be the case also in the mammary gland, and it was not our intention to give the impression that proliferation was not affected. In fact, Hiremath et al. (2012) already reported a defect in epithelial cell proliferation in Igf1rmammary buds at E14. Our key finding is that compared to other organs, the mammary gland is particularly sensitive to loss of Igf1r during branching morphogenesis. Finally, as pointed out earlier, better tools will be needed to assess the potential link between lineage segregation and onset of branching, a topic that we hope to address in the future.

Minor comments: 1- An important paper on mammary gland ductal branching was published on Nature in 2017 by Scheele and colleagues and should be presented in the introduction, even though it is at later stages (after birth).

Our response:

We thank the reviewer for the suggestion. In the revised manuscript, we have added the findings from Scheele et al. 2017 in the introduction.

2- In line 136 and 139 the authors referred to Fig 2 but it should be Fig 1

Our response:

We apologize for these slips. They have been corrected in the revised manuscript.

3- The sentence on line 142 should be rephrased, since "advanced developmental stages" may be referred to pubertal development. The authors should specify that they are talking about embryonic development.

Our response: We apologize for the potential misunderstanding. In the revised manuscript, we have used the phrase “advanced embryonic developmental stage” to describe our conclusion more precisely.

Reviewer #2 (Significance (Required)):

Overall, the authors concluded that embryonic mammary gland development and branching are extremely sensitive to the loss of IGF1, normally produced by the mesenchyme. The topic of the paper is interesting, the experimental approaches are well conceived, the data are convincing and the findings are of interest to developmental biologists. Nevertheless, there are some significant points that need to be further investigated before considering the manuscript suitable for publication:

Our response:

We thank the reviewer for the careful assessment and positive feedback of our manuscript. We have already addressed most of the points raised and most remaining ones will be addressed in the final revised manuscript.

__Reviewer #3 (Evidence, reproducibility and clarity (Required)): __

Here the authors use classical embryonic tissue recombination and pharmacological manipulation of explants in conjunction with cutting edge 3D imaging of tissue derived from highly sophisticated reporter and knock-out mouse models and state of the art transcriptomic analysis to masterfully delineate and dissect regulatory pathways critical for embryonic mammary development. Specifically, they set out to parse regulation of proliferation from that of branch patterning.

While it has long been established that epithelial-mesenchymal interaction is necessary for mammary branching this work shows by heterochronic recombination that initiation mammary branching is not advanced by mesenchymal stage. By examining Fucci2a embryos the authors demonstrate that branching is preceded by a significant increase in basal cell-biased proliferation but, through further analysis of Eda gain and loss of function mice, conclude that proliferation per se does not cause branching. They show by heterotypic recombination with salivary tissue that early mammary epithelia rudiments require their own mesenchyme for survival and that although later E16.5 rudiments expand more robustly when in contact with salivary mesenchyme they nevertheless retain their characteristic mammary branch pattern. Thus, they establish that initiation and patterning are intrinsic properties of the epithelium but that early survival and later expansion/proliferation is regulated by the mesenchymal context. By transcriptomic comparison of mammary and salivary mesenchyme they reveal that genes encoding canonical Wnt attenuators and antagonists are highly expressed in early mammary mesenchyme and drop as branching ensues. The low expression of these negative regulators of Wnt signaling in salivary mesenchyme is proposed as an explanation for its growth and branch stimulating capability. In keeping with these observations, the authors show that experimental activation of mammary mesenchymal Wnt signaling augments both growth and branching. Lastly, they identify transcriptomic changes in IGF1 coincident with the initiation of mammary branching and confirm its role by extending analyses of the effects of gain and loss of function of IGF1 on embryonic mammary development.

This is a thorough, well-constructed paper that adds new knowledge and important conceptual nuance and mechanistic insight to classical findings on branch patterning. This work is a technical tour de force and backed by solid quantitative and statistical analysis throughout. Their experimental approach is superb and the conclusions are sound. Their findings will be of great interest to the community of mammary gland biologists and to the wider field of embryologists focused on early development of a broad range of ectodermal appendages.

I have some minor criticisms that I believe can be quickly remedied in a minor rewrite and suggestions for the authors consideration to improve the manuscript discussion as follows:

Minor issues Abstract, line 37: The authors misuse the word "decompose" - it should be "deconstruct"

__Our response: __ We thank the reviewer for pointing out our mistake, which we have corrected in the revised manuscript.

Results, p7 line 48: Add "The" to the sentence: "The majority...."

__Our response: __ Corrected it in the revised manuscript.

P8 line 173 This sentence refers to Figure 2G which is a quantitative plot. I would suggest replacing the word "cluster" which implies a spatial organization with the word "subset" or "significant fraction" The spatial data in Fig 2d support basal bias but do NOT to my eye show any clustering - in fact the proliferative basal cells appear to be evenly dispersed within the basal layer.

Our response:

We thank the reviewer for highlighting this aspect. We agree that “significant fraction” is a more suitable term than “cluster”.

P9 line 188: The statement on basal cell lineage specification needs a reference.

__Our response: __

Following the suggestions from reviewers #1 and 3, we have removed the content about lineage segregation in Results, together with this sentence.

P10 line 201-216 I found the section on lineage specification (fig S2) weaker than the rest and a distraction from the main thrust of the paper making it difficult for the reader to focus. I suggest omitting this section and supplemental figures associated with it altogether.

__Our response: __

We agree with all reviewers in that this part of the manuscript was not mature enough and provided only indirect evidence on the potential link between lineage segregation and branching ability. This is an important question in the field that merits a study of its own that should be addressed with better tools than those available to us at present. As suggested by reviewers #1 and #3, we have omitted this part in the revised manuscript.

P9 line 190: "displays precocious onset of branching" it is sufficient to say: displays precocious branching - the use of both "precocious" and "onset' is redundant.

P10 line 229 Similarly, delete "the onset of branching was delayed" it is sufficient to say: branching was delayed.

__Our response: __ Both sentences have been corrected it in the revised manuscript.

P11 line 243: Delete "on the regulation of the" and substitute the word "to" in the sentence: "Next, we shifted our focus on the regulation of the branching pattern, which is thought to be determined by mesenchymal cues."

__Our response: __ Corrected it in the revised manuscript.

P11 line 241 subtitle and Figure 4 title: The disparity in titles here is jarring for the reader: Results text subtitle: "Salivary gland mesenchyme is rich in growth-promoting cues, but does not alter the mode of branch point formation of the mammary epithelium". Figure 4 Title: "Mammary mesenchyme is indispensable for the branching ability of the mammary gland". I suggest to the authors divide the figure as well as the text to make the two points indicated by their disparate titles separately.

__Our response: __ We thank reviewer for the suggestion to clarify the Results part of the manuscript. As suggested, we have split the data under two separate subtitles, but due to limitations in figure numbers, we prefer to report these data in one figure panel.

P12 line 279 From here on out the manuscript has a tendency to use the term "growth" ambiguously - in many instances it is unclear do they mean expansion, proliferation, increased branch number/ morphology?? Please try to clarify.

__Our response: __

Our aim is to use the term growth to mean tissue growth (expansion). We hope that this is clearer in the revised manuscript.

P16 line 341 use word "prompted" instead of word "promoted"

__Our response: __ We thank reviewer for spotting out the slip, which we have corrected in the revised manuscript.

P16 line 382: include word "embryonic" before "mammary development"

__Our response: __ We have modified the text in the revised manuscript.

Discussion P18 line 416: Add the words "later stage (E16.5)" to the sentence: "Importantly, we demonstrate that salivary gland mesenchyme could only promote the growth of later stage (E16.5) mammary epithelium"

__Our response: __ We thank reviewer for the suggestion. We have modified the text in the revised manuscript.

P19 line 437: Given the authors statement "Instead, cell motility is critical for branch point formation in the mammary gland" they should consider a brief sentence mentioning their transcriptomic findings on cadherin 11 and Tenascin.

__Our response: __ We thank the reviewer for appreciation of our transcriptomic data. In the revised manuscript, we have added the following text in discussion: “Accordingly, we observed significantly increased expression of cell migration promoting genes such as Cdh11 (encoding Cadherin 11), and Tnc (encoding Tenascin C) 60,61 in the E16.5 mesenchyme compared to E13.5 (Supplementary Table 2).”

P19 line 451: Similarly, given their statement "This observation suggests that mammary epithelium itself carries the instructions dictating the mode of branching" they could consider their transcriptomic data on Ltbp1 in "mammary specific" clusters 7,8,9 as a matrix molecule initially expressed by mammary mesenchyme but which becomes expressed by luminal epithelial cells at precisely the time they acquire lineage specification and intrinsic branching capability.

__Our response: __ This is an excellent suggestion. We have added following text in discussion: “It is worth noting that certain mesenchymal factors, such as Ltbp1, began transitioning towards epithelium-specific expression around E16.5 69. Exploring the potential impact of these factors on the self-instructed branching capacity of the mammary epithelium could yield valuable insights.”

P20 lines 462-470 The authors should address their theory of Wnt suppression in the mammary mesenchyme in the context, albeit conflictingly, of earlier studies showing expression of Wnt signaling reporters, in either epithelial or mesenchymal locations during early stages.

Our response: __ We thank reviewer for the suggestion. In the preliminary revised manuscript, we report Axin2 expression data as __new Supplementary Fig. 4c. Axin2 expression data suggest that Wnt/β-catenin activity is lowest in the E16.5 fat pad (where branching takes place) compared to all other tissues analyzed in the study.

Plan for the final revision:

For the final revised manuscript, we will additionally generate transgenic Wnt reporter expression data (see also our response to point 3 of Reviewer #1). These results will be discussed in light of the published Wnt reported literature in the final revised manuscript.

Reviewer #3 (Significance (Required)):

Here the authors use classical embryonic tissue recombination and pharmacological manipulation of explants in conjunction with cutting edge 3D imaging of tissue derived from highly sophisticated reporter and knock-out mouse models and state of the art transcriptomic analysis to masterfully delineate and dissect regulatory pathways critical for embryonic mammary development. Specifically, they set out to parse regulation of proliferation from that of branch patterning.

This is a thorough, well-constructed paper that adds new knowledge and important conceptual nuance and mechanistic insight to classical findings on branch patterning. This work is a technical tour de force and backed by solid quantitative and statistical analysis throughout. Their experimental approach is superb and the conclusions are sound. Their findings will be of great interest to the community of mammary gland biologists and to the wider field of embryologists focused on early development of a broad range of ectodermal appendages.

Our response:

We much appreciate the positive evaluation of our manuscript. We have addressed all the feedback provided by the reviewer 3 in the preliminary revised manuscript, except the last point, which will be included in the final revision along with the new data on the Wnt reporter expression.

Field of expertise: Embryonic and adult mammary development, Wnt signaling, cell adhesion

Author Response

eLife assessment

This useful paper examines changes (or lack thereof) in birds' fear response to humans as a result of COVID-19 lockdowns. The evidence supporting the primary conclusion is currently inadequate, because the model used does not properly account for many potentially confounding factors that could influence the study's outcomes. If the analytic approach were improved, the findings would be of interest to urban ecologists, behavioral biologists and ecologists, and researchers interested in understanding the effects of COVID-19 lockdowns on animals.

Many thanks for these supportive words. We did our best to improve our manuscript according to the reviewers and editor comments. Importantly, we regret being unclear in the Methods, as our models already controlled for most of the confounds (see below) discussed by the reviewers.

For example, given that a single observer collected the data at most sites, site as a random intercept in the models controls also for the observer effects (which is one of the reasons why site is in the model). We added details to Methods (L352-356, see also “Statistical analyses” in the main text).

The first reviewer asked us to use “some measure of urbanity (e.g. Human Footprint Index) that varies across the cities included here”. Our main results are now based on country-specific models and hence, the use of a single value predictor for each city is not appropriate. Please, see also below.

The second reviewer is concerned about multicollinearity in our models because of the 0.95 correlation between Period and Stringency Index. However, these are key predictor variables of interest that have never been used within the same model as predictors. We now clearly explain this in the Methods (L458-538, 548-550) and within legend of Figure S2.

The third reviewer suggested that our models would benefit from controlling for day in the species-specific breeding cycle. Although we don’t have precise city-specific information on the timing of breeding stages in the sampled populations of birds, we partly control for these effects by including a random intercept of day within each year and species. This random factor explained most of the variance (see Table S1-S2) – something that could have been expected. In other words, we do control for what the third reviewer asked for. Similarly, we account for habitat features that may influence escape distance by including site in the models. Site usually refers to a specific park (we assume that within-park heterogeneity is lower than between park variation) and hence partly addresses the reviewer’s concern. Again, we highlight this within the Methods (L466-476).

Reviewer #1 (Public Review):

This paper uses a series of flight initiation "challenges" conducted both prior to and during COVID-19-related restrictions on human movement to estimate the degree to which avian escape responses to humans changed during the "anthropause". This technique is suitable for understanding avian behavioral responses with a high degree of repeatability. The study collects an impressive dataset over multiple years across five cities on two continents. Overall the study finds no effect of lockdown on avian escape distance (the distance at which the "target" individual flees the approaching observer). The study considers the variable of interest as both binary (during lockdown or prior to lockdown) and continuous, using the Oxford Stringency Index (with neither apparently affecting escape distance). Overall this paper presents interesting results which may suggest that behavioral responses to humans are rather inflexible over "short" (~2 year) timespans. The anthropause represents a unique opportunity to disentangle the mechanistic drivers of myriad hypothesized impacts humans have on the behavior, distribution, and abundance of animals. Indeed, this finding would provide important context to the larger body of literature aimed at these ends.

Thank you very much for your positive feedback.

However, the paper could do more to carefully fit this finding into the broader literature and, in so doing, be a bit more careful about the conclusions they are able to draw given the study design and the measures used. Taking some of these points (in no particular order):

Thank you. We did our best in addressing your comments (see below and updated Methods, Results and Discussion sections).

1) Oxford Stringency Index is a useful measure of governmental responses to the pandemic and it's true that in some scenarios (including the (Geng et al. 2021) study cited by this paper) it can correlate with human mobility. However, it is far from a direct measure of human mobility (even in the Geng study, to my reading, the index only explained a minority of the variation). Moreover, particular sub-components of the index are wholly unrelated to human mobility (e.g. would changes to a country's public information campaign lead to concomitant changes in urban human mobility?). Finally, compliance with government restrictions can vary geographically and over time (i.e. we might expect lower compliance in 2021 than in 2020) and the index is calculated at the scale of entire countries and may not be very reflective of local conditions. Overall this paper could do more to address the potential shortcomings of the Oxford Stringency Index as a measure of human mobility including attempting to validate the effect on human mobility using other datasets (e.g. the google dataset and/or those discussed in (Noi et al. 2022). This is of critical importance since the fundamental logic of the experimental design relies on the assumption that stringency ~ mobility.

Thank you for this comment. First, Oxford Stringency Index seemed to us as the best available index for our purposes, i.e to estimate people's mobility during the shutdown because restrictions surely influenced the possibility that people would be outside, and because the index is a country-specific estimate. However, in addition, we now checked all indices mentioned in Noi et al. 2022 and found useful only the Google Mobility Reports, which we now use, because (a) it is publicly available, (b) it is available also for territories outside US, and (c) provides data for each city included in our dataset as well as for urban parks where most of our data were collected. Note that some platforms are no longer providing their mobility data (e.g. Apple).

However, Google Mobility provides day-to-day variation in human mobility, whereas we are interested in overall increase/decrease in human mobility. Nevertheless, we correlated the Google mobility index with the Stringency index and found that human mobility generally decreases with the strength of the anti-pandemic measures adopted in sampled countries (albeit the effect for some countries, e.g. Poland, is small; Fig. 5).

Moreover, we also added analysis using # of humans collected directly in the field during escape trials (e.g. Fig. 6 and S6) and found that the link between # of humans and Stringency index or Google Mobility was weak and noise, 95%CIs widely crossing zero (Fig. 6).

Importantly, if we use Google Mobility and # of humans, respectively, as predictors of escape distance, the results are qualitatively very similar to results based on Oxford Stringency Index (Fig. S6), or Period, with tiny effect sizes for both (95%CIs for Google Mobility -0.3 – 0.06, Table S5, for # of humans -0.12 – 0.02, Table S6) supporting our previous conclusions.

Note that Google Mobility and the number of humans have their limitations (see our comment to the editor and the Methods section in the main manuscript, e.g. L418-433). The lack of Google Mobility data for years before the COVID-19 pandemic does not allow us to fully explore whether overall human activity decreased during COVID-19 or not (our test for period prior and during COVID-19). If the year 2022 reflects a return to “normal” (which is to be disputed due to COVID-19-driven rise in home office use) the 2020 and 2021 had on average lower levels of human activity (Fig. 4). Whether such a difference is biologically meaningful to birds is unclear given the immense day-to-day change in human mobility and presence (Fig 4). Moreover, the number of humans capture within- and between-day variation rather than long-term changes in human presence.

We added details on the new analysis into the method and results sections (e.g. Fig. 4-6; L142-165, 418-438, 495-535) and Supplementary Information (Figs. S5-S9 and associated Tables) and discuss the problematic accordingly. Moreover, to enhance clarity about country specific effect (or their lack), we also add country specific estimates to the Results (Fig. 1 and Fig. S6 and respective Tables). Finally, our statistical design and random structure of the model allowed us to control for spatial and temporal variation in compliance with government restrictions.

2) The interpretation of the primary finding (that behavioral responses to humans are inflexible) could use a bit more contextualization within the literature. Specifically, the study offers three potential explanations for the observed invariance in escape response: 1) these behaviors are consistent within individuals and this study provides evidence that there was no population turnover as a result of lockdowns; 2) escape response is linked to other urban adaptations such that to be an urban-dwelling species dictates escape response; and/or 3) these populations already exhibit maximum habituation and the reduction in human mobility would only have increased that habituation but that trait is already at a boundary condition. Some comments on each of these respectively:

Thank for these comments. We incorporated them in the main text (L293-329). Your point 1) corresponds to our point (i): “Most urban bird species in our sample may be relatively inflexible in their escape responses because the species may be already adapted to human presence” (L293-306); your point 2) to our point (ii): “Urban environment might filter for bold individuals (Carrete and Tella, 2013, 2010; Sprau and Dingemanse, 2017). Thus, the lack of consistent change in escape behaviour of urban birds during the COVID-19 shutdowns may indicate an absence (or low influx) of generally shy, less tolerant individuals and species from rural or less disturbed areas into the cities…” (L307-314); your point 3) to our point (iii): “Urban birds might have been already habituated to or tolerant of variation in human presence, irrespective of the potential changes in human activity patterns” (L315-329). To distinguish between (ii) and (iii) or the two from (i), individually-marked birds and comprehensive genetic analyses are needed, which we now note in the Discussion (L330-348). Importantly, we also discuss that the lack of response might be due to relatively small changes in human activity (L253-292), which we unfortunately could not fully quantify.

a) Even had these populations turned over as a result of a massive rural-to-urban dispersal event, it's not clear that the escape distance in those individuals would be different because this paper does not establish that these hypothetical rural birds have a different behavioral response which would be constant following dispersal. Thus the evidence gathered here is insufficient to tell us about possible relocations of the focal species.