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  1. Jul 2023
    1. 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

      Please find our point-to-point response to the reviewer’s comments below, where we marked all changes implemented in the manuscript in italics.

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

      With the emergence and spread of resistance to Artemisinin (ART), a key component of current frontline malaria combination therapies, there is a growing effort to understand the mechanisms that lead to ART resistance. Previous work has shown that ART resistant parasites harbour mutations in the Kelch13 protein, which in turn leads to reduced endocytosis of host haemoglobin. The digestion of haemoglobin is thought to be critical for the activation of the artemisinin endoperoxide bridge, leading to the production of free radicals and parasite death. However, the mechanisms by which the parasites endocytose host cell haemoglobin remain poorly understood.

      Previous work by the authors identified several proteins in the proximity of K13 using proximity-based labelling (BioID) (Birnbaum et al. 2020). The authors then went on to characterise several of these proteins, showing that when proteins including EPS15, AP2mu, UBP1 and KIC7 are disrupted, this leads to ART resistance and defects in endocytosis leading to the hypothesis that these two processes are inextricably linked.

      In this manuscript, Schmidt et al. set themselves the task of characterising more K13 component candidates identified in their previous work (Birnbaum et al. 2020) that were not previously validated or characterised. They chose 10 candidates and investigated their localisations, and colocalisation with K13, and their involvement in endocytosis and in vitro ART resistance, 2 processes mediated by K13 and some members of the K13 compartments

      The authors show that of their 10 candidates, only 4 can be co-localised with K13. Then, using a combination of targeted gene disruption (TGD) as well as knock sideways (KS), they characterised these 4 proteins found in the K13 compartment. They show that MyoF and KIC12 are involved in endocytosis and are important for parasite growth, however their disruption does not lead to a change in ART sensitivity. The authors also confirm the findings of their previous publication (Birnbaum et al. 2020), using a slightly different TGD

      (note from the authors: we apologise if this has not properly transpired from the manuscript but the difference between the TGDs is substantial and relevant: one has less than 3% of the protein left and hence can be considered to fully inactivate MCA2 and has a growth defect whereas the other contains about two thirds of the protein (1344 amino acids/~66% are left), has no growth defect, although it lacks the MCA2 domain (hence that domain can not be critical for the growth defect)),

      that MCA2 is involved in ART resistance, however they did not check whether its disruption impacts haemoglobin uptake. They also show that KIC11 is not involved in mediating haemoglobin uptake or ART resistance. To finish, the authors used AlphaFold to identify new domains in the proteins of the K13 compartment. This led them to the conclusion that vesicle trafficking domains are enriched in proteins of the K13 compartment involved in endocytosis and in vitro ART resistance.

      The majority of the experiments conducted by the authors are performed to a good standard in biological and technical replicates, with the correct controls. Their findings provide confirmation that their 4 candidate genes seem to be important for parasite growth, and show that some of their candidates are involved in endocytosis. While the KD and KS approaches employed by the authors to study their candidate genes each have their own advantages and can be excellent tools for studying a large sets or genes, this manuscript highlights the many limitations of these approaches. For example, the large tag used for the KS approach can mislocalise proteins or disrupt their function (as is the case for MyoF), resulting in spurious results, or indeed the inability to generate the tagged line (as is the case for MCA2). The KS approach also makes the results of a protein with a dual localisation, like KIC12, extremely difficult to interpret.

      We thank the reviewer for this thorough and insightful review.

      The limitations mentioned above were addressed in the response to the main points and a general detailed response in regards to the systems used for this research are added at the end of this rebuttal. Briefly summarised here: while we agree that there are limitations of the system used, we are convinced that

      • the advantages of using a large tag in most cases outweighs the drawbacks as it permits to track the inactivation of the target, if need be on the individual cell level

      • while not optimal for MyoF, the partial inactivation actually helps in its functional study as detailed in major point 23&28 or reviewer#3 major point 11: it shows a consistent correlation of the phenotype with different causes and degrees of inactivation (this is now better illustrated in Figure 1L1M). Further, regarding the concern of the large tag: the effect of the tag based on localisation was overestimated in the review by what seems to have been a mix up comparing numbers from MyoF with a number from MCA2 (there is a difference, but it is only small) (see reviewer#1 major point #23).

      • KS is the optimal method for most of the assays in this work (e.g. bloated food vacuole assays and RSAs); these assays would be impossible or difficult to use with other inactivation systems currently used in P. falciparum research (see details in the response to the specific points and after the rebuttal)

      In regards to the difficulty to interpret KIC12 data: this is only true for measuring absolute essentiality, everything else we believe we actually have the optimal method. If not KS, which method targets a specific pool of a protein with a dual localisastion? Again, our assays targeting the K13 pool and revealing the specific function would have been difficult or impossible with any other system.

      Ultimately the question is whether any other system would have resulted in a different conclusion on the function of the proteins studied. At present we are confident this would not be the case and other systems probably would not have delivered the specific functional data shown in this work. Clearly, more in depth work will provide more nuanced and detailed insights into the proteins analysed in this work and this likely will also include the use of other systems for specific aspects they are most suitable for. However, this (e.g. different complementations in a diCre cKO) is complex and therefore beyond what fits into this work which had the goal to assess which proteins are true positives for the K13 compartment and to place them into functional groups in regards to endocytosis.

      Moreover, the manuscript is disjointed at times, with the authors choosing to conduct certain experiments for only a subset of genes, but not for others. For example, considering that the aim of this paper was to identify more proteins involved in ART resistance and endocytosis, it is confusing why the authors do not perform the endocytosis assays for all their selected proteins, and why they do not do this for the proteins they identify in their domain search. There is significant room for improvement for this manuscript, and a generally interesting question.

      The reviewer remarks that not every experiment was done for every target. Based on the rebuttal we tried to amend this but also note that there was some sentiment by the reviewers to better stick to the point and not make the manuscript more disjointed. We attempted to balance that as much as possible and hope we were able to honour both aspects (amendments were done as detailed in the point by point response below).

      In regards to endocytosis and choice of targets: We did do endocytosis assays for all proteins that showed a growth phenotype upon inactivation in this work. We therefore assume the reviewer here refers to major point #40 asking for endocytosis assays with KIC4 and KIC5 (which were not studied in this manuscript) as well as MCA2 (point 17). We fully agree with the reviewer that this would fill a gap in the work on K13 compartment proteins but such assays are difficult with TGDs (there are issues with non-comparable samples and compensatory effects) and proteins that are not essential (and hence likely have a smaller impact on endocytosis when truncated). We nevertheless now carried them out, but due to the limitations to do this with these lines would be hesitant to draw definite conclusions (see major point 17 and 40 for details and outcomes).

      But in it's current format, other than confirming that MCA2 is involved in ART resistance (which was already known from the Birnbaum paper), the authors do not further expand our understanding of the link between ART resistance and endocytosis in this manuscript.

      We would like to point out that the importance of the K13 compartment and endocytosis goes beyond ART resistance (see e.g. also newly published papers on the K13 compartment in Toxoplasma, (Wan et al., 2023; Koreny et al., 2023)). Endocytosis is an essential and prominent process in blood stages. However, in contrast to processes such as invasion, our understanding about endocytosis is only rudimentary. Hence, this manuscript provides important insights on an emerging topic that in our opinion deserves more attention:

      • it identifies novel proteins at the K13 compartment and provides 2 new proteins in endocytosis (MyoF and KIC12); getting an as complete as possible list of proteins involved in the process will be critical to study and understand it

      • it leads to the realisation that not all growth-relevant proteins detected at the K13 compartment are needed for endocytosis

      • it provides domains and stage specificity of function for several K13 compartment proteins, overall bolstering the model of endocytosis in ART resistance and providing a framework critical to direct future studies on endocytosis and their detailed mechanistic function at the cytostome

      • the identified vesicle trafficking domains (for instance now also found in UBP1) are expected to strengthen the support for the role of endocytosis of the K13 compartment; this and also the above points are important as (based on the current literature) there still seems to be prominent sentiment in the field that (in part due to the involvement of UBP1 and K13) the cause of ART resistance is due to various unclearly defined stress response pathways

      • with MyoF it also shows the first protein in connection with the K13 compartment that acts downstream of the generation of hemoglobin-filled containers in the parasite and provides the first protein that explains the suspected involvement of actin in endocytosis (so far this was only based on CytD studies)

      Overall we therefore believe this manuscript contains critical information and a framework for future studies on endocytosis and the K13 compartment. We hope the relevance of endocytosis as one of the most prominent and essential processes in the parasites and the connection to various aspects linked with many commercial drugs (in addition to the role of endocytosis in ART resistance), is adequately explained in the introduction. We also would like to mention that the main focus of the work is reflected in the title of the manuscript which does not mention ART susceptibility.

      Major Comments

      1) line 31: please change defined to characterised - defined suggests that novel proteins were identified in this study, which is not the case.

      We apologise, but we do not fully understand this comment. We did identify novel proteins not before known to be at the K13 compartment (MCA2 (admittedly this one was likely but had not previously been verified), MyoF, KIC11 and KIC12). In our view "further defining the composition of the K13 compartment" therefore is an accurate statement. Additionally, the identification of previously not-discovered domains, the stage-specificity and function of these proteins helped to further define the K13 compartment.

      If the reviewer is referring to the fact that the proteins analysed in this study were taken from a previously generated list of hits, we would like to stress that the presence in such a list (obtained from a BioID, but also if from an IP etc) can not be equalled for them to be true positives, they are merely candidates that still need to be experimentally validated. This is what we did in this work to find out which further proteins from the list can be classified as K13 compartment proteins (for hits with lower FDRs this is even more relevant as illustrated by the fact that 6 of the here analysed hits were not at the K13 compartment). In an attempt to address this comment in the manuscript, we changed the wording of this sentence to (line 31): "Here we further defined the composition of the K13 compartment by analysing more hits from a previous BioID, showing that MyoF and MCA2 as well as Kelch13 interaction candidate (KIC) 11 and 12 are found at this site."

      2) line 37: please change 'second' to "another". As explained further below, the authors identified 3 classes of proteins (confer ART resistance + involved in HCCU, involved in HCCU only, or involved in neither).

      We realized that the groups description wasn’t clear in the abstract. Please see response to major comment #41 for a detailed answer to this (endocytosis is an overarching criterion, ART resistance is a subgroup and applies only to those proteins with a function in endocytosis in ring stages). To clarify this (see also major point #8) we added an explanation on the influence of stage-specificity of endocytosis on ART susceptibility to the introduction (line 76): In contrast to K13 which is only needed for endocytosis in ring stages (the stage relevant for in vitro ART resistance), some of these proteins (AP2µ and UBP1) are also needed for endocytosis in later stage parasites (Birnbaum et al., 2020). At least in the case of UBP1, this is associated with a higher fitness cost but lower resistance compared to K13 mutations (Behrens et al., 2021; Behrens et al., 2023). Hence, the stage-specificity of endocytosis functions is relevant for in vitro ART resistance: proteins influencing endocytosis in trophozoites are expected to have a high fitness cost whereas proteins not needed for endocytosis in rings would not be expected to influence resistance.” The abstract was changed in response to this and other comments and hope it is now clearer in regards to the groups.

      3) Line 40: You define KIC11 as essential but according to your data some parasites are still alive and replicating 2 cycles after induction of the knock sideways. Please consider changing "essential" to "important for asexual parasite growth".

      We fully agree with the reviewer, we reworded the sentence as suggested.

      4) Line 40: please change 'second group' to 'this group'

      We reworded this part of the abstract and it know reads: (line 38): “While this strengthened the link of the K13 compartment to endocytosis, many proteins of this group showed unusual domain combinations and large parasite-specific regions, indicating a high level of taxon-specific adaptation of this process.”

      5) line 41: state here that despite it being essential, it is unknown what it is involved in.

      With the newly added data we show that this protein either has a function in invasion or very early ring development although we did not see any evidence for the latter. We therefore changed the sentence to (line 43): “We here identified the first protein of this group that is important for asexual blood stage development and showed that it likely is involved in invasion*..” *

      6) Line 50: the authors should state here that there is actually a reversal in this trend over the last few years.

      Done as suggested.

      7) Line 54: please separate out the references for each of the two statements made in this line (a: that ART resistance is widespread in SEA, and b: that ART resistance is now in Africa) Reference 14 also seems to reference ART resistance in Amazonia - which is not covered by the statement made by the authors (in which case the authors should state ART is now present in Africa and South America). The authors should also reference PMID: 34279219 for their statement that ART resistance is now found in Africa (albeit a different mutation to the one found in SEA).

      Done as suggested.

      8) Line 65: it is also worth mentioning here that there are other mutations in proteins other than K13, such as AP2mu and UBP1 (PMID: 24994911;24270944) that can lead to ART resistance.

      As suggested by the reviewer, we included a sentence about non-K13 mutations linked with reduced ART susceptibility in the introduction (line 74): Beside K13 mutations in other genes, such as Coronin (Demas et al., 2018) UBP1 (Borrmann et al., 2013; Henrici et al., 2020b; Birnbaum et al., 2020; Simwela et al., 2020) or AP2µ (Henriques et al., 2014; Henrici et al., 2020b)* have also been linked with reduced ART susceptibility." *

      We here also added data on fitness cost that is related to this and is also relevant for the issue of proteins with a stage-specific function in endocytosis, making a transition for this statement which might help clarifying the grouping of K13 compartment proteins (see also major point #2).

      9) Line 80, 86: ref 43 is misused. Reference 43 refers to Maurer's clefts trafficking which takes place in the erythrocyte cytosol and is not involved in haemoglobin uptake as far as I know. Please replace ref 43 with one showing the role of actin in haemoglobin uptake.

      We thank the reviewer for pointing this out, Ref 43 was removed from the manuscript.

      10) Line 98: the authors state here that they 'identified' further candidates from the K13 proxiome. This suggests that they identified new proteins in this paper, when in fact the list was already generated in ref 26. All they did was characterise proteins from that list that were not previously characterised. The authors should therefore remove identified from this statement.

      We agree with the reviewer that we did not identify further candidates, we identified new K13 compartment proteins from the list of potential K13 compartment proteins. We therefore changed “identified further candidates” into “identified further K13 compartment proteins” (line 116). Please see also response to major comment #1.

      11) Line 107-108: it is not clear from this sentence why these proteins were left out of the initial analysis in Ref 26. A sentence here explaining this would be valuable for the reader.

      This is a good point. One reason why we did not analyse more in our previous publication was that we had to stop somewhere and adding more would have been very difficult to fit into what was already a packed paper. However, as shown in this work, the list does contain further interesting candidates (e.g. K13 compartment proteins that are involved in endocytosis).

      We altered the relevant part of the introduction to highlight that we previously analysed the top hits, clarifying that the 'remaining' hits analysed in this work were further down in the list. This now reads: (line 113)“We reasoned that due to the high number of proteins that turned out to belong to the K13 compartment when validating the top hits of the K13 BioID (Birnbaum et al., 2020), the remaining hits of these experiments might contain further proteins belonging to the K13 compartment.” We hope this clarifies that we simply moved further down in the candidate list.

      12) Line 117-123: The authors say that PF3D7_0204300, PF3D7_1117900 and PF3D7_1016200 were not studied because they were not in the top 10 hits. However, the current organisation of Supplementary Table 1 shows all 3 proteins among the top 10 hits (MyoF, KIC12, UIS14 and 0907200 being after them). I think the authors should reorganise their table. It is also unclear according to what the proteins in the table are ranked. Could the authors indicate the metric used for the ranking?

      We thank the reviewer for alerting us to this. The issue here is that the 3 non-analysed proteins belong to a 'lower stringency' group comprising hits significant with FDRThe information about ranking is now also included as “Table legend” in the revised manuscript and the Table heading has been changed to: List of putative K13 compartment proteins, proteins selected for further characterization in this manuscript are highlighted.”

      13) Line 129-141: Can the authors be clearer with their explanations of the identification of mutation Y1344Stop? One dataset (ref 61) shows that 52% of African parasites have a mutation in MCA2 in position 1344 leading to a STOP codon. But another dataset (ref 62) shows that the next base is also mutated, reverting the stop codon. That should have been seen in the first dataset as well. Could the authors please clarify.

      This mutation was first spotted in the MalariaGEN database (https://www.malariagen.net) (MalariaGEN et al., 2021), which allows online accessing of the data by using the “variant catalogue” tool, which is in a table format of frequency rather than in a sequence context. Hence, only after further research later on it became evident to us, that this mutation does not occur alone when looking at individual MCA2 sequences from patient samples in (Wichers et al., 2021b). We hope this is accurately reflected in our results section.

      14) Line 147: the authors say that MCA2 is expressed throughout the intraerythrocytic cycle as shown by live cell imaging. In Birnbaum et al 2020 fig 4I, the authors show that MCA2 is mainly expressed between 4 and 16hpi. But in Figure 1B of this manuscript there is a clear multiplication of MCA2 signal between trophozoite and schizont. How do the authors explain this discrepancy? Could expression of the truncated MCA2 be different than the full length? This cannot be assessed as expression and localisation of the full-length HA tag MCA2 is not shown in Schizonts.

      The key difference lies in transcription vs protein expression (usually protein levels peak after mRNA levels peak and - depending on turnover - protein levels can stay high even after mRNA levels have declined). Figure 4 of the Birnbaum et al paper presents transcriptomic data, but with a peak in trophozoites (The axis label in Fig. 4l of that publication is a bit confusing, as hour 0 is at the top, 48 h at the bottom; it is clearer in Fig. S13 of that paper) which would fit very well with the multiplication of the signal between trophozoites and schizonts mentioned by the reviewer. So, overall, the temporal peaks of transcripts and protein of that protein fit well.

      For the signal in rings: Likely the protein has a turnover rate that is sufficiently low for some protein to be taken into the new cycle after re-invasion. Also different transcriptomic datasets e.g. (Otto et al., 2010; Wichers et al., 2019; Subudhi et al., 2020) available on plasmoDB show some mRNA present across the complete asexual development cycle, with each dataset showing maximum peak at a slightly different stage.

      Even when located in foci and hence aiding detection of small amounts of protein (as is the case for MCA2-Y1344-GFP), the MCA2 signal in rings is not strong. For MCA2-TGD, the GFP signal is dispersed and therefore likely below our detection limit, while the same amount of protein concentrated at the K13 compartment is visible as foci in the MCA2-Y1344 cell line. Please note that MCA2-TGD has only 2.8% of the protein left whereas MCA2-Y1344 has 66.5% left and based on our manuscript is almost fully functional, hence fitting the different locations between the two versions.

      Overall we believe this shows that there are actually no significant discrepancies of the expression of the different MCA2 versions.

      15) Line 158: would it not have been more useful for the authors to have episomally expressed MCA2-3xHA in their MCA2Y1344STOP-GFPENDO line to make sure that the truncated protein is indeed going to the correct compartment? The experiments done by the authors suggests that the MCA2Y1344STOP goes to the right location but does not really confirm it.

      We appreciate the reviewers caution here. However, considering that MCA2Y1344STOP-GFPendo co-locates with mCherryK13 and endogenously HA-tagged full length MCA2 does the same to a similar extent, there is in our opinion little doubt that MCA2 is found at the K13 compartment and that this is similar with both constructs. If there are minor differences, these might as well occur if MCA2 is episomally (as suggested in the comment) instead of endogenously expressed. Given the limited insight, we therefore decided against the episomal overexpression (which due to its size of > 6000bp may also be somewhat less straight forward than it may sound).

      16) Line 191: it is stated that MCA2 confers resistance independently of the MCA domain, however in both the MCA2-TGD and MCA2Y1344STOP-GFPENDO parasites, the MCA domain is deleted, and for both parasites, there is resistance (albeit to a lower level in the MCA2Y1344STOP-GFPENDO line). Therefore, how can the authors state that the ART resistance is independent of the MCA domain? This statement should be that resistance is dependent on the loss of the MCA domain.

      We agree that this can’t be categorically excluded. However, a ~5 fold difference in ART sensitivity was observed between the parasites with MCA2 truncated at amino acid 57 compared to those with MCA at amino acid 1344 even though both do not contain the MCA2 domain. Hence, at least this difference is not dependent on the MCA2 domain. The larger construct missing the MCA domain shows only a very moderate reduction in RSA survival, again suggesting the MCA domain is not the main factor. We amended our statement in an attempt to more accurately reflect the data (line 487): This considerable reduction in ART susceptibility in the parasites with the truncation at MCA2 position 57 compared to the parasites still expressing 1344 amino acids of MCA2, despite both versions of the protein lacking the MCA domain, indicates that the influence on ART resistance is not, or only partially due to the MCA domain.” We would be hesitant to state the reviewer's conclusion that “resistance is dependent on the loss of the MCA domain”, as the larger construct missing the MCA2 domain has a milder RSA effect compared to MCA2-TGD, which suggests the reduction in ART susceptibility is independent of the MCA domain. These considerations also agree with the fact that the parasites with the longer MCA2 version (in contrast to the MCA2-TGD) do not have any detectable growth defect which indicates that the protein can fulfil its function without the MCA2 domain.

      17) Line 192: Why did the authors not check if MCA2 is involved in endocytosis? They state later on in the manuscript that they did not do endocytosis assays with TGD lines, however if the authors include the correct controls, this could be easily done. It would also be really interesting to see whether endocytosis gets progressively worse going from WT to MCA2Y1344STOP to MAC2TGD. This experiment (as well as doing endocytosis assays for KIC4 and KIC5 TGD lines) would drastically increase the impact of this study. These experiments would not take more than 3 weeks to perform, and would not require the generation of new lines.

      So far were very hesitant to do bloated FV assays with TGDs (even though TGDs were available for the genes encoding MCA2 and KIC4 and KIC5). The reason for this was:

      1. the fact that these proteins could be disrupted indicated either redundancy or only a partial effect on endocytosis which might lead to only small effects that likely are difficult to pick up in an assay scoring for the rather absolute phenotype of bloated vs non-bloated. Using the refined assay measuring FV size could partly amend this but we note that also FV without hemoglobin have a certain size, reducing the relative effect if there are smaller differences.
      2. a TGD line does not permit tightly controlled inactivation of the target which makes comparing the outcome of bloated food vacuole assays difficult if there are smaller growth and stage differences to the 3D7 control.
      3. in contrast to conditional inactivation parasites, the TGD lines had ample times to adapt to loss of the target protein (compensatory mechanisms are well known for endocytosis, for instance in clathrin mediated endocytosis loss of individual components can be compensated (Chen and Schmid, 2020)). We nevertheless see the reviewer's point that this should at least be attempted and now conducted these assays (see also major point 40). For MCA2 (as requested in this point), the data is shown in Figure S5C-E. This assay showed that in MCA2-TGD, MCA2Y1344STOP-GFPendo (similar to the 3D7 control) >95% of parasites developed bloated food vacuoles. Additionally, we also measured the parasite and food vacuole size of individual cells in an attempt to solve some of the problems with TGDs with such assays. In order to specifically solve problem 2 mentioned above, we analysed the food vacuoles of similarly sized parasites, however, they were non-distinguishable between the three lines. Of note, in agreement with the reduced parasite proliferation rate (Birnbaum et al., 2020) a general effect on parasite and food vacuole size was observed for MCA2-TGD parasites, indicating reduced development speed in these parasites. Hence, it is possible that a potential endocytosis reduction was accompanied by a slowed growth, and the comparison of similarly sized parasites may have obscured the effect. It is therefore not sure if there indeed is no endocytosis phenotype, although we can exclude a strong effect in trophozoites.

      Based on the RSA results at least rings can be expected to have a reduced endocytosis in the MCA2-TGD. Apart from options 1-3 mentioned above, it is therefore possible there is an effect restricted to rings, although in that case the reduced growth in trophozoites would be due to other functions of MCA2. Overall, we can conclude that the MCA2-TGD parasites do not have a strongly reduced endocytosis, but given the fact that the parasites are viable, this is not surprising. Whether the MCA2-TGD has no effect at all on endocytosis we would be very hesitant to postulate based on these results.

      18) The authors should consider re-organising the MCA2 section, first showing that the 3xHA tagged line colocalises with K13, then performing the new truncation.

      We attempted to re-organise as suggested but because we now included additional fluorescence microscopy images of schizont and merozoites (in response to reviewer 2 major comment 3) the main figure would become even larger. To prevent this, we kept the 3xHA data in the supplement.

      19) Line 197: Once again ref 43 is not correct to illustrate that actin/myosin is involved in endocytosis

      We thank the reviewer for pointing this out – we removed Ref 43.

      20) Line 202: the authors state that MyoF localises near the food vacuole from ring stage/trophs onwards. However, how can this statement be made in schizonts based on these images (Fig. 2A), where it doesn't look like MyoF is anywhere near the FV? This statement can only be made for schizonts if co-localised with a FV marker (which is done in Fig. 2B), however, based on the number of MyoF foci, it appears that this was not done for schizonts. Please either remove the statement that MyoF is near the food vacuole from trophs onwards (because it is only seen near the FV up until trophs) or show the data in Fig. 2B of schizonts to substantiate these claims.

      This is a valid point. We originally did not focus on schizonts because most markers end up in some focal area in the forming merozoite but other proteins (such as e.g. K13) also have one or more additional foci at the FV, making interpretation unclear, particularly if the schizont is still organizing to become fully segmented. This is why we generally focused the K13 co-localisations on the trophozoite stage to obtain the clearest information on endocytosis. However, given the fact that this manuscript gives the first localization of MyoF in P. falciparum parasites, we now provide a comprehensive time course (Figure 1C, S1A) including schizonts, which show quite a complex pattern: while the MyoF-GFP localization in trophozoites appeared as multiple foci close to K13 and also the FV, the MyoF-GFP pattern changes in late schizonts (fully segmented) and merozoites, appearing as elongated foci no longer close to K13 or the FV. Of note, this pattern has been previously reported for MyoE in P. berghei (Wall et al., 2019).

      We therefore revised the statement about MyoF localization in schizont to better reflect the observed localization: (line 175): In late schizonts and merozoite the MyoF-GFP signal was not associated with K13, but showed elongated GFP foci (Figure 1C, S2A) reminiscent of the MyoE signal previously reported in P. berghei schizonts (Wall et al., 2019).”

      21) Line 204-206: what does this statement bring to the paper? Is it to show that it is the real localisation of MyoF because 2 tag cell line show the same localisation? I don't think this is needed, especially as later in the manuscript an HA-tag MyoF line is used and show similar localisation.

      We see the reviewers point, but prefer to keep this data included in the supplement, particularly because potential differences in the location of tagged MyoF were a major concern.

      Related to the tag issue: in order to get a better understanding of the effect of C-terminally tagging with different sized tags we now performed a more detailed analysis of the MyoF-3xHA cell line (Figure S2F-G), showing that this cell line shows a growth rate similar to the 3D7 wild type parasites, and has less vesicles than the 2x-FKBP-GFP-2xFKBP cell line, but still slightly, but significantly more than 3D7 parasites. Overall, this indicates that the smaller 3xHA tag has less effect on the parasite, than the larger 2x-FKBP-GFP-2xFKBP tag (see also new Figure 1L, showing a correlation of level of inactivation and the endocytosis phenotype for MyoF).

      22) Line 212: The overlap of K13 with MyoF in Figure 2C 3rd panel (1st trophozoite panel) is not obvious, especially as the MyoF signal seems inexistant. I would advise the authors to replace with a better image. Also, why are there no images of schizonts shown in Figure 2C?

      As suggested we exchanged the trophozoite image of panel Figure 2 C (now Figure 1C) and expanded this panel with images covering the complete asexual development cycle including schizonts in response to this and the previous points. As indicated above (point 20), schizont stages are complex to interpret. While late schizonts likely are not very relevant for endocytosis this is the first description of the location of the protein in this parasite and we therefore now provide a more thorough representation of the MyoF location across asexual stages in Figure1C and S2A.

      23) Line 217: the spatial association of MyoF with K13 is very different when it is tagged with GFP and when it is tagged with 3xHA. The way the authors word it here, it seems that there is agreement with the two datasets, when this is not in fact the case (59% overlap for MyoF-GFP and only 16% overlap with MyoF-3xHA). These data suggest that the GFP and the multiple FKBP tags are doing something to the protein and therefore maybe the ensuing results using this line should not be trusted or be taken with a pinch of salt.

      We agree with the reviewer that the location of this MyoF-GFP in the cell might differ due to the partial inactivation but in contrast to this comment, the data does not indicate any large differences. It seems the reviewer mixed something up (the 59% mentioned might come from the MCA2 figure?). The data with the two lines with differently tagged MyoF co-localised with K13 are actually quite comparable: GFP-tagged vs HA-tagged MyoF overlapping with K13 was 8% vs 16% full overlap, 12% vs 19% partially overlapping foci, 36% vs 63% foci that were touching but not overlapping (compare what now is Figure 1D and Figure S2C). Only in the 'no overlap' there is a much smaller proportion in the HA-tagged line. However, given that these are IFAs which on the one hand are more sensitive to see small protein pools but on the other hand also have pitfalls due to fixing of the cells (e.g. tiny increase in focus size due to fixing could increase the number of touching foci that in live cells might be close but did not touch), some variation can be expected to the live cells. We agree though that the partly reduced functionality of MyoF might be the reason for the consistent tendency of a lower overlap even though the difference is much less than indicated in the comment. We added "with a tendency for higher overlap with K13 which might be due to the partial inactivation of the GFP-tagged MyoF" to the sentence "IFA confirmed the focal localisation of MyoF and its spatial association with mCherry-K13 foci"

      While we expect the fact that the difference between these parasites is only small somewhat reduces the "pinch of salt" with the MyoF line, we do agree that the partial functional inactivation of the GFP-tagged MyoF line may have some impact. However, we do not think that this means the results with the MyoF-GFP line are untrustworthy. On the contrary, it provides insights into its function that in some ways is equivalent to a knock down or TGD. Overall all the MyoF lines show: few vesicles occur in the MyoF-HA-line, more in the MyoF-GFP line and even more after knock sideways of MyoF-GFP. Importantly the severity of this phenotype correlates with the growth rates in these lines. Hence, together with the bloated food vacuole assays, this provides consistent data indicating that MyoF has a role in the transport of HCC to the FV and its level of activity correlates with the number of vesicles and growth. To better highlight this, it is now summarised in Figure 1M.

      24) Line 219: the authors state here that they could not detect MyoF-GFP in rings, when in Figure 2C they show MyoF-GFP in rings, and also show that they could detect MyoF in Sup Fig. 3B with the 3xHA tagged line. Is this a labelling mistake in Figure 2C? If the authors could indeed not see MoyF-GFP in rings, this statement should have been made when Figure 2A was presented, and not so late in the manuscript, which causes confusion.

      We thank the reviewer for pointing this out. We now provide a detailed time course (see also previous points) which shows that there is no detectable MyoF-GFP signal during ring stage development until the stage where the parasites starts the transition to trophozoites (i.e. MyoF-GFP signal could only be observed in parasites already containing hemozoin). In addition to the extended time course in Figure 1C (previously 2C) we included a panel of example ring stage images below to further highlight this. We also changed the labelling of the parasite with MyoF-GFP signal the reviewer mentions in Figure 1C to “late ring stage” (it already contains hemozoin) to clarify this.

      The description of Figure 1A is now changed to: (line 153) *“The tagged MyoF was detectable as foci close to the food vacuole from the stage parasites turned from late rings to young trophozoite stage onwards, while in schizonts multiple MyoF foci were visible (Figure 1A, S2A).” *

      Please see our answer to major comment #45 where we provide an explanation for the difference between MyoF-3xHA and MyoF-GFP signal in ring stage parasites.

      [Figure MyoF]

      25) Line 237: Showing a DNA marker (DAPI, Hoecht) for Figure 2E, and subsequent figures using mislocalisation to the nucleus, would help the reader assess efficiency of the mislocalisation.

      Please see response to major comment #64 for a detailed answer on why we did not include DNA staining in the imaging used to assess mislocalization upon knock-sideways.

      26) Line 254-256: authors should show the results of the bloating assay for parental 3D7 parasites (+ and - rapalog) to see whether the MyoF line - rapalog has increased baseline bloating. This applies to all subsequent FV bloating assays.

      We did do several controls for bloated assays (including +/- rapalog of an irrelevant knock sideways line as well as using a chemical insult for which the control was 3D7 without treatment) in previous work (Birnbaum et al., 2020), which indicated that there is no effect of rapalog to reduce bloating. Although these controls are more stringent, we nevertheless did a 3D7 +/- rapalog control and added this to the manuscript (Figure S2I). As it is not possible to do this side by side with the assays that are already in the manuscript and the +/- rapalog 3D7 cells consistently showed no or very low numbers of cells without bloating (and stringent controls in the past equally did not show an effect), we believe adding this control once suffices.

      27) Line 254-257: The authors say that because fewer parasites show a bloated food vacuole upon inactivation of MyoF it means that less hemoglobin reached the food vacuole. I understand the authors statement, however, shouldn't they look at the size of the food vacuole, instead of the number of parasites with bloated FV, to make such a statement? This has been done for KIC12 so why not doing it for MyoF?

      This was now done and is provided as Figure 1J-K, S2J. The results confirm the assessment scoring bloated vs non-boated food vacuoles.

      28) Line 259-261: these results would be difficult to interpret namely because the authors have dying parasites, which is exacerbated with the protein being knocked sideways. The authors should mention the pitfalls their knock sideways and tagging design here. Line 260-261: RSA is an assay relying on measuring parasite growth 1 cycle after a challenge with ART for 6 hours.

      Fortunately, this concern is unfounded, as the survival (measured by parasitemia after one cycle) of the same sample + and - DHA is assessed, isolating the DHA effect independent of potential growth defects which are cancelled out. Hence, if there were parasites dying in the MyoF line (please note that they might not actually die, but simply grow more slowly), this factor applies for both the + and - ART condition. As we are testing for a decreased susceptibility to ART which would manifest as an increased survival in RSA surfacing above 1%, antagonistic effects of reduced MyoF function and ART treatment would not result in detectable differences as without effect, the RSA survival is always close to zero.

      The same applies for the knock sideways where we assess the survival of +rapalog between +ART and -ART. If the reduced MyoF activity of the knock sideways leads to a decreased survival, this applies to both +ART and -ART. Please also note that rapalog was lifted after the DHA pulse (see e.g. Figure S2K).

      That effects on growth are cancelled out is nicely illustrated for proteins where there is a stronger and more rapid effect on growth upon their conditional inactivation. For instance when KIC7 is knocked aside, there is a considerable increased of RSA survival, even though continued inactivation of KIC7 would have a severe growth defect (Birnbaum et al., 2020). Vice versa, a growth defect alone does not result in reduced RSA susceptibility as evident from knock sideways of an unrelated protein or using a chemical insult (Figure 4H in (Birnbaum et al., 2020) or simply slowing the ring stage by e.g. reducing EXP1 levels (Mesén-Ramírez et al., 2019). Hence, a growth reduction is not expected to alter the RSA outcome. And even if it did, it would only lead to an underestimation of the readout if growth is too severely affected (which would be obvious in the + rapalog without DHA sample, which was not the case).

      In that respect it is valuable to have the rapid kinetics of knock sideways which permit inactivation of a protein before severe growth defects occur (although the only partial responsiveness of MyoF clearly is not the most optimal). In contrast, the absolute loss of a gene (as is the case if diCre is used) prevents (or at least makes it extremely difficult as the timing would need to exactly hit sufficient protein reduction without killing the parasite until the end of the RSA) using this system in these experiments (again see (Mesén-Ramírez et al., 2021) where in a EXP1 diCre based knock out RSA was only possible because we complemented with a lowly, episomally expressed EXP1 copy to have parasites with only a partial phenotype to do this assay).

      29) Line 261-263: the authors sate that MyoF has a function in endocytosis but at a different step compared to K13 compartment proteins. I am not sure what they mean here. Can this be clarified?

      The different steps in endocytosis are explained in the introduction and we now tried to further clarify this (line 98). So far VPS45 (Jonscher et al., 2019), Rbsn5 (Sabitzki et al., 2023), Rab5b (Sabitzki et al., 2023), the phosphoinositide-binding protein PX1 (Mukherjee et al., 2022), the host enzyme peroxiredoxin 6 (Wagner et al., 2022) and K13 and some of its compartment proteins (Eps15, AP2µ, KIC7, UBP1) (Birnbaum et al., 2020) have been reported to act at different steps in the endocytic uptake pathway of hemoglobin. While inactivation of VPS45, Rbsn5, Rab5b, PX1 or actin resulted in an accumulation of hemoglobin filled vesicles (Lazarus et al., 2008; Jonscher et al., 2019; Mukherjee et al., 2022; Sabitzki et al., 2023), indicative of a block during endosomal transport (late steps in endocytosis), no such vesicles were observed upon inactivation of K13 and its compartment proteins (Birnbaum et al., 2020), suggesting a role of these proteins during initiation of endocytosis (early steps in endocytosis).

      VPS45 has not apparent spatial connection to the K13 compartment but the fact that MyoF does - and its inactivation also results in vesicle accumulation - indicates that it is downstream of vesicle initiation, providing the first connection from the initiation phase to the transport phase. More evidence for these different steps of endocytosis has been published in a recent preprint from our lab, where we simultaneously inactivated a protein of both “endocytosis steps” (Sabitzki et al., 2023).

      To clarify this in the results as requested, we changed the statement to: (line 256) Overall, our results indicate a close association of MyoF foci with the K13 compartment and a role of MyoF in endocytosis albeit not in rings and at a step in the endocytosis pathway when hemoglobin-filled vesicles had already formed and hence is subsequent to the function of the other so far known K13 compartment proteins.”

      30) Do the authors mean that it is involved in endocytosis but not in ART resistance? If so, this is a very difficult statement to make since the parasites are dying. Is there any evidence of point mutations in MyoF in the field?

      We split this point to address all issues raised here. Please see response to point 29 which clarifies that this was meant in a different way and our response to point 28 which explains why the dying parasite issue is not expected to affect the RSA (please also note that we do not have evidence of actually dying parasites in the MyoF-2xFKBP-GFP-2xFKBP line, most likely the growth is slowed).

      The mutation issue is interesting. In fact evidence exists that MyoF mutations may be associated with resistance (Cerqueira et al., 2017) (please note that there it is still called MyoC) but in a recent preprint from our lab we did not find any evidence for a significantly changed RSA survival in 12 tested mutations in the corresponding gene (Behrens et al., 2023).

      To clarify this we added the following statement to the discussion (line 709): "Of note, mutations in myoF have previously been found to be associated with reduced ART susceptibility (Cerqueira et al., 2017), but 12 mutations tested in the laboratory strain 3D7 did not result in increased RSA survival (Behrens et al., 2023)*. *

      31) Line 298: the authors state that there is no growth defect in the first cycle when rapalog is added to the KIC11 line, however based on Figure 3D, there is evidently a 25% reduction in growth compared to - rapalog at day 1 post treatment, and a 60% reduction by day 2, which is still within the 1st growth cycle. The authors should either revise their statement or provide an explanation for these findings. The authors should also explain why their Giemsa data in Fig. 3E is not in accordance with their FACS data.

      We think there is a misunderstanding here, as our figure legend was not detailed enough and we apologise if this had been misleading. The growth effect is restricted to invasion or possibly the first hours of ring stage development (see point 4&5, reviewer 2), which in asynchronous cultures more rapidly takes effect as the culture also contains schizonts that immediately generate cells that re-invade but can't due to inactivation of KIC11 (due to the rapid action of the knock sideways, KIC11 is already inactivated). In contrast, in highly synchronous cultures, this effect can only be evident once the parasites reached the schizont stage (starting with rings this takes close to 2 days). We now clarify that Figure 2E (previously Figure 3D) shows growth data obtained with an asynchronous parasite culture, while in Figure 2F the growth assay is performed with tightly synchronized (4h window) parasites as stated in the Figure legend.

      We now explicitly state in each Figure legend and for each growth experiment throughout the manuscript whether we used asynchronous or synchronized parasites for growth assays.

      Related to this, the incorrect y-axis label of what is now Figure 2E mentioned in major comment #58 is now corrected.

      32) Line 301: KIC11 could also be important very early for establishment of the ring stage for example for establishment of the PV. Also, was mislocalisation assessed in rapalog-treated parasites at 72 hours or in cycle 3?

      This is a valid point and this has now been addressed. We performed an invasion/egress assay revealing similar schizont rupture rates, but significantly reduced numbers of newly formed ring stage parasites (Figure 2H, S3G), indicating an effect of KIC11 inactivation either on invasion or possibly the first hours of ring stage development. A very similar point was raised by Reviewer 2, please see reviewer 2; major comment #4. This is now also reflected in line 302, which now reads: ”… indicating an invasion defect or an effect on parasite viability in merozoites or early rings but no effect on other parasite stages (Figure 2F-H, Figure S3F-G).”

      We further included an assessment of mislocalization 80 hours after the induction of knock-sideways by addition of rapalog in Figure S3E which showed mislocalization of KIC11 to the nucleus.

      33) Line 311: the authors should change the sentence from 'not related to endocytosis' to 'not related to endocytosis or ART resistance'.

      Done as suggested.

      34) Line 323-325: Authors say that a nuclear GFP signal can be observed in early schizonts for KIC12. According to the pictures provided in Figure 4A and Figure S5A it is not very obvious. Also faint cytoplasmic GFP signal could only be background as we can see that exposure is higher for schizont pictures

      We changed the sentence (line 339) to: “…nuclear signal and a faint uniform cytoplasmic GFP signal was detected in late trophozoites and early schizonts and these signals were absent in later schizonts and merozoites (Figure 3A, Figure S4A,B).” in order to emphasize that the nuclear signal disappears early during schizont development.

      35) Line 326-328: The authors say that kic12 transcriptional profile indicate mRNA levels peak (no s at peak) in merozoites. Should they show live cell imaging of merozoites then? Because from the Figure 4A schizont pictures where schizonts are almost fully segmented no signal can be observed.

      The observation that mRNA levels of early ring stage expressed proteins tend to increase already in mature schizonts and merozoites is well established (e.g. (Bozdech et al., 2003)). A very good example for this are exported proteins of which most show a transcription peak in schizonts but the proteins are only detected in rings see e.g. (Marti et al., 2004). Hence, our observation for KIC12 is quite typical.

      We originally did not include merozoites, as in the last row of Figure 3B fully developed merozoites within a schizont with already ruptured PVM are shown and no GFP signal can be detected in these parasites. We now provide images of free merozoites in Figure S4A-B showing again no detectable GFP signal.

      We thank the reviewer for pointing out the typo, "peak" has been corrected.

      36) Line 347: The authors state that using the Lyn mislocaliser the nuclear pool of KIC12 is inactivated by mislocalisation to the PPM. This tends to suggest that only the nuclear pool of KIC12 is mislocalised. How is it possible that only the nuclear pool is mislocalised?

      The Lyn mislocaliser is at the PPM which is continuous with the cytostomal neck where the K13 compartment likely is found. The effect of the Lyn mislocalizer on the KIC12 protein pool localizing at the K13 compartment is therefore somewhat unclear. For this reason we already had the following statement in the original submission (line 400): “Foci were still detected in the parasite periphery and it is unclear whether these remained with the K13 compartment or were also in some way affected by the Lyn-mislocaliser.” We would like to stress here that the same does not apply to the nuclear mislocaliser, which is only a trafficking signal delivering KIC12 to the nucleus and hence likely does not affect the nuclear pool of KIC12, only the K13 compartment pool (the main interest of this manuscript).

      We realised that the statement towards the end of this paragraph was unnecessarily ambiguous in regards to the K13 compartment pool of KIC12 which might have caused some confusion about the function of this pool of KIC12 and therefore modified it to (line 374): "Due to the possible influence on the K13 compartment located foci of KIC12 with the Lyn mislocaliser, a clear interpretation in regard to the functional importance of the nuclear pool of KIC12 other than that it confirms the importance of this protein for asexual blood stages is not possible. In contrast, the results with the nuclear mislocaliser indicate that the K13 located pool of KIC12 is important for efficient parasite growth.". It is also important to note that this limitation does not apply to the NLS knock sideways in regard to the K13 compartment and that the endocytosis function of this pool of KIC12 seems solid which with this statement is enforced.

      37) Line 368-369: Effect was also only partial for MyoF. Why didn't you measure the same metrics for MyoF?

      This was now done and is provided as Figure 1J-K, S2J, confirming our previous interpretation, see also point #27 which raises the same point.

      38) Line 379: you don't know if all proteins acting later in endocytosis will have an increased number of vesicles as a phenotype

      This is based on our current definition as stated in the introduction. It assumes a directional vesicular transport of hemoglobin to the food vacuole where inhibition of early stages will prevent transport before HCC-filled autonomous vesicular containers have formed and entered the cell. In contrast later inhibition stops such containers from further transport, leading to their accumulation. Such an accumulation is visible after VPS45-inactivation and other proteins (Jonscher et al., 2019; Mukherjee et al., 2022; Sabitzki et al., 2023) or treatment with cytochalasin D (Lazarus et al., 2008). While it is possible that there may be smaller intermediates formed at the K13 compartment that later on unite or fuse with the compartment evident after VPS45 inactivation and these might be missed due to small size (i.e. inhibition of a step between K13 compartment and an early endosome or equivalent), this would still be upstream of the VPS45 induced containers and hence would be earlier. We therefore believe that based on the framework given in the introduction (see also (Spielmann et al., 2020)) to assume that a phenotype manifesting as reduced food vacuole bloating without formation of detectable vesicles likely signifies inhibition of the process early whereas reduced bloating but with vesicles signifies inhibition later in the process.

      39) Line 413-414: The authors state that no growth defect was observed upon KS of 1365800. Is growth alone enough to say that there is no impact on endocytosis?

      This is an interesting point. The endocytosis proteins we studied so far indicate that efficient impairment of endocytosis manifests as a severe growth defect. Hence, lack of a growth defect can be assumed to be an indicator for absence of an important role for endocytosis (or any other growth relevant process). Clearly there is a gradual response, such as seen in the different MyoF versions resulting in proportional growth and vesicle appearance phenotypes. Hence, a protein with a minor role might have slipped our attention but then it probably is also not a very important protein in endocytosis.

      To further strengthen our assessment of PF3D7_1365800 importance for asexual blood stage development, we now also generated a cell line expressing the PPM Mislocalizer, enabling knock sideways to the PPM. This was done because this protein consistently has a focus at the nucleus that may be within the nucleus. Again this revealed no growth defect upon inactivation (Figure S7D).

      40) Line 432: in this section, the authors state that KIC4 and KIC5 seem to have domains that may suggest these proteins are involved in endocytosis, based on the alpha fold data that is publicly available. Considering the authors have TGD-SLI versions of these lines (Birnbaum et al. 2020) and have already confirmed in this previous publication that they confer resistance to ART; it would make sense to look at endocytosis for these genes. This would be a relatively simple and straightforward experiment, taking no longer than two to three weeks, and would require no additional reagents or line generation. Doing these experiments would add a lot more weight to this final section. The authors later state that KIC4 and 5 are TGD lines, so not the best for endocytosis assays. It is unclear why this would be difficult to do if an adequate control is contained in the experiment (such as parental 3D7). It explains why they did not perform the MCA2 endocytosis assays further up, but in my opinion, an attempt at doing these assays is important and would significantly increase the impact of this paper. Identical as major comment #17.

      As stated in the manuscript and above, we were originally hesitant to do these assays due to the fact that we can't induce inactivation which is less ideal than comparing the identical parasite population split into plus and minus and is further complicated by the likely smaller effect as the TGDs still permitted growth. However, we see the point of the reviewer and now performed these assays using 3D7 as controls and taking extra care to account for stage differences between the TGD lines and 3D7. However, there was no significant difference in the bloated food vacuole assays with these cell lines. Due to the reasons mentioned in major point 17, we are not sure this indeed means these proteins have no role in endocytosis. One possible reason why we were able to obtain these TGDs may have been because the effect on endocytosis is less than in the essential proteins (or is ring stage specific) and in a TGD an endocytosis defect may therefore not be detectable with our assays (see details and further possible explanations in response to point 17).

      In an attempt to address the TGD issue, we generated knock sideways cell lines for KIC4 and KIC5. Unfortunately, the mislocalization of KIC5 to the nucleus was inefficient (see figure below). As this did not result in a growth defect (in contrast to the clear KIC5-TGD growth defect (Birnbaum et al., 2020)), this line is not suitable to study a potential role of this protein in endocytosis. Therefore, we performed the bloated food vacuole assay only with KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser parasites. However, this revealed no effect on HHC uptake, which is in line with the normal growth of KIC4-TGD parasites (Birnbaum et al., 2020) and suggests that this protein could only have a minor or redundant role in endocytosis (it is the line that shows the smallest effect in RSA). As the KIC4 and KIC5 knock sideway lines did not permit any conclusions, we did not include them into the revised manuscript but they can be found here:

      [Figure KIC4 knock sideways & KIC5 knocksideways]

      Figure legend: (A) Live-cell microscopy of knock sideways (+ rapalog) and control (without rapalog) KIC4-2xFKBP-GFP-2xFKBPendo+ 1xNLS mislocaliser parasites 4 and 20 hours after the induction of knock-sideways by addition of rapalog. Scale bar, 5 µm. Relative growth of asynchronous KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser plus rapalog compared with control parasites over five days. Three independent experiments were performed. Growth of knock sideways (+ rapalog) compared to control (without rapalog) KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser (blue) or KIC5-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser (red) parasites over five days. Mean relative parasitemia ± SD is shown. (B) Live-cell microscopy of knock sideways (+ rapalog) and control (without rapalog) KIC5-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser parasites 4 and 20 hours after the induction of knock-sideways by addition of rapalog. Scale bar, 5 µm. Growth of asynchronous KIC5-2xFKBP-GFP-2xFKBPendo+ 1xNLSmislocaliser plus rapalog compared with control parasites over five days. Four independent experiments were performed. __(C) __Bloated food vacuole assay with KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser parasites 8 hours after inactivation of KIC4 (+rapalog). Cells were categorized as with ‘bloated FV’ or ‘non-bloated FV’ and percentage of cells with bloated FV is displayed; n = 3 independent experiments with each n=19-30 (mean 21.4) parasites analysed per condition. Representative DIC are displayed. Area of the FV, area of the parasite and area of FV divided by area of the corresponding parasites were determined. Mean of each independent experiment indicated by coloured symbols, individual datapoints by grey dots. Data presented according to SuperPlot guidelines (Lord et al., 2020); Error bars represent mean ± SD. P-value determined by paired t-test. Area of FV of individual cells plotted versus the area of the corresponding parasite. Line represents linear regression with error indicated by dashed line.

      41) Line 490-493: the authors state that the K13 compartment proteins fall in two groups, some that are involved in ART resistance AND endocytosis, and some that have different functions. However, in this manuscript the authors have demonstrated 3 flavours that K13 compartment proteins can come in: • Some that confer ART resistance and are involved in HCCU (MCA2) • Some that are involved in HCCU but not ART resistance (MyoF & KIC12) • Some that are involved in neither (KIC11) The authors should therefore revise this statement.

      We agree that this was not well phrased. To account for the fact that not all endocytosis proteins confer increased RSA survival to the parasites when inactivated we changed this statement (line 604): "This analysis suggests that proteins detected at the K13 compartment can be classified into at least two groups of which one comprises proteins involved in endocytosis or in vitro ART resistance whereas the other group might have different functions yet to be discovered.

      Generally, we believe that endocytosis is the overarching criterion and we therefore would like to keep the definitions of the main groups (endocytosis or not). As indicated by the title, the focus of the manuscript is on the K13 compartment for which so far endocytosis is the only experimentally associated function. That this group contains proteins that do not confer reduced ART susceptibility when conditionally inactivated (KIC12 and MyoF) is explained by their stage-specificity, making this a subgroup of the overarching endocytosis group.

      We realise that with the endocytosis data on the KIC4, KIC5 and MCA2 TGD there is now also a subgroup we were unable to demonstrate an endocytosis effect in trophozoites although they show changes in RSA survival. However, as indicated above, we would be hesitant to fully exclude some role of these proteins in endocytosis in rings. Particularly as a comparably small reduction in endocytosis protein activity or abundance is sufficient to increase RSA survival (Behrens et al., 2023). A principal classification of "endocytosis or ART resistance" or "neither endocytosis nor ART resistance" still accounts for this and therefore seems to us to be the most useful, particularly also in light of our domain identification that then can be linked with one or the other group.

      42) Line 508: the authors state that they expanded the repertoire of K13 compartments, when in fact they functionally analysed them - they did not do another BioID to identify more candidates.

      We respectfully disagree with the reviewer in this point, we did expand the repertoire of known K13 compartment proteins. Only independently experimentally validated proteins from proximity biotinylation experiments can be considered part of the K13 compartment (or any other cellular site or complex). Without validation of the location, the identified proteins can only be considered candidates. This is highlighted in this manuscript by the finding that several proteins of the list did not localize at the K13 compartment.

      43) Line 570-572: has anyone ever tested whether CytoD or JAS treatment in rings, is sufficient to mediate ART resistance? Something similar to what was done in PMID 21709259 with protease inhibitors. If not this would be a pretty interesting experiment for the authors to do that could shed more light on the MyoF data. It would take maybe 2 weeks to do and not require the generation of any new lines. This would clarify whether other Myosins other than MyoF are involved in endocytosis, as is suggested by previous publications (PMID: 17944961).

      We now included this experiment. In agreement with a lacking need of MyoF in rings and no effect on RSA survival, there was no increased survival of the parasites in RSA (neither on 3D7 nor on K13 C580Y parasites) after cytD treatment (new part in Figure 1M). We thank the reviewer for pointing out that this experiment might also inform on whether other myosins influence endocytosis in ring stages. We added (line 250): Similarly, also incubation with the actin destabilising agent Cytochalasin D (Casella et al., 1981), had no effect on RSA survival in 3D7 or K13C580Y (Birnbaum et al., 2020) parasites, indicating an actin/myosin independent endocytosis pathway in ring stage parasites (Figure 1M) and speaking against other myosins taking over the MyoF endocytosis function in rings.”

      44) Line 608: inhibitors targeting the metacaspase domain of MCA2 may inadvertently inactivate other essential parts of the protein. They authors should acknowledge this possibility in the text.

      The inhibitors used in the cited studies (Kumari et al., 2018) are validated metacaspase inhibitors, such as Z-FA-FMK (Lopez-Hernandez et al., 2003). Activity against the other parts of PfMCA2 - which apart from the MCA domain shows no homology to other proteins - is therefore unlikely.

      45) Line 624-625: the authors state that MyoF is 'lowly expressed in rings' - indeed this is the case in their MyoF-2xFKBP-GFP-2xFKBP line which the authors established has defects due to the tag, but it appears from their MyoF-3xHA tagged line that it is expressed in rings. The authors should therefore revise their statement, and be careful of making claims based on their defective line and using fluorescence imaging as their only metric. If they do want to make the statement that it is not there in rings, they should also do a western blot, which is much more sensitive since it amplifies the signal compared to an image of one parasite.

      This comment is related to major point #24. We also would like to stress that while the MyoF-GFP line already shows a phenotype, the impression of defectiveness based on its location is due to a mix up (see major point #23).

      We now provide a comprehensive time course of the MyoF-GFP signal (Figure 1C, S2A) showing that there is no detectable MyoF-GFP signal until the transition from ring to trophozoite stage. As this is all under the endogenous promoter, we do not think the partial functional inactivation of the tagging is the reason for the absence of the signal. If anything, we would have expected adding a stably folded structure such as GFP to increase the stability of the protein. The main reason for the discrepancy of MyoF signal in rings between the GFP-tagged line (of note there is also no detectable MyoF-GFP signal in MyoF-2xFKBP-GFP ring stage parasites (Figure S2B)) and the HA-tagged line likely is that IFA is much more sensitive than live GFP detection (similar to the high sensitivity the reviewer mentions in regards to WB). This discrepancy therefore is likely due to the fact that the lowly expressed MyoF only become apparent with the HA-tagged line due to the IFA. We therefore believe that MyoF is 'lowly expressed in rings' is an appropriate description of our results obtained with three different cell lines (MyoF-2xFKBP-GFP-2xFKBP, MyoF-2xFKBP-GFP and MyoF-3xHA). We hope this is sufficiently well reflected in the manuscript where we write ‘a low level of expression of MyoF in ring stage parasites.’ not that it is ‘not there in rings’ (line 174).

      46) Line 635: arguably this is the 3rd variety and not the 2nd (the authors already mentioned 2 types - ones that are involved in HCCU AND ART and those involved in HCCU only). See comment for line 490-493 above.

      See response for major comment #41, we now consistently used "or" instead of "and". See line 490-493 how this was resolved for what previously was line 635.

      47) Line 785: Bloated food vacuole assay/E64 hemoglobin uptake assay method specify that a concentration of 33mM E64protease inhibitor was used. However, in reference 44, cited in the manuscript, a concentration of 33µM E64 was used. Please confirmed if this is just a typo or if 1000x E64 concentration was used which renders the experiment invalid.

      We thank the reviewer for pointing this out, we corrected this typo and will look out for symbol font conversion errors for the resubmission.

      48) Line 788: it is unclear from this section what is considered a bloated food vacuole - is there an area above which the FV is considered bloated? Do the authors do these measurements manually or use an addon in FIJI/ImageJ? What is the cutoff for if a FV is bloated? Please clarify. Additionally, for the representative images + rapalog for Figures 2H and 4H, it would be useful to see where the authors delineate the FV (add a white circle showing what is actually measured).

      The bloated FV assay is well established (Jonscher et al., 2019; Birnbaum et al., 2020; Sabitzki et al., 2023). Although the bloating of the FV is a human judgment call, it is actually quite obvious: bloating appears as an easily spotted bulging of the FV in DIC. As also minor bloating is scored as 'bloated', it is a very conservative assay. Using an-add on to measure this is not straight forward. It is unclear how this bulging effect of the FV in DIC could be spotted by a software and due to the obviousness to human operators, potentially lengthy and complicated efforts to design appropriate machine learning options were not undertaken. The situation faced by the scorer of the assay is evident from Figure S4F-G which contains close to 50 "on rapalog" cells and close to 50 control cells, giving representative cells from all replicas of bloated FV assays with KIC12. Please note that these images shows the most complicated situation as far as bloated assays go, because the phenotype is not 100% (see Figure 3F) compared to e.g. KIC7 inactivation which leads to lack of bloating in almost all cells (see (Birnbaum et al., 2020) Figure 3E) but nevertheless the difference is still obvious. We are aware that in such situations (less than absolute inhibition) this assay scoring of "yes" or "no" is a surrogate for the actual level of inhibition and may be more subjective. This is why in this case we also did the FV size measurements (which are less dependent on human judgment) to further support this and give a better quantifiable measure. Of note, the bloated food vacuole judgments are done "blinded", i.e. the examiner does not know which sample they are looking at.

      In response to this reviewer's point we now also added the FV size refinement of the assay for MyoF inactivation which is one of the cases where inhibition of bloating is not in 100% of the cells (see major comment #27). Please also note here the advantage of the rapidly acting knock sideways technique for these assays which shows the sum of effect 8 h after initiating inactivation and for which we carefully control size of the cells which shows that there is no significant growth reduction over the assay time, excluding secondary effects due to a generally reduced viability. Compared to slower acting systems suggested to have been used instead (see introductory part and significance of this review), the rapid speed of knock sideways reduces the risk of potential pleiotropic or compensatory effects due to the time needed for proteins to be depleted if the gene or mRNA is targeted instead.

      The suggestion to include a ‘white circle’ (raised also as minor comment#27) is useful as an aid to see the food vacuole. However, in contrast to the Figures in (Birnbaum et al., 2020) (where we did add such a circle), we here included the DHE staining images in the figure, labelling the parasite cytosol which readily shows the FV (the FV corresponds to the region where there is no DHE staining). As this shows the position of the FV we would prefer to not obscure the DIC images with additional features to permit the reader to see the difference between bloated or non-bloated food vacuoles and keeping the image as natural as possible.

      49) Line 863-864: this sentence seems to be out of place.

      We thank the reviewer for pointing this out, the details of nucleus staining were moved to the correct part.

      50) Line 875: the authors state that there is a light blue wedge, when the circle consists of grey and black wedges. Please revise this.

      This has been corrected.

      51) Line 1059-1061: it is unclear whether the individual growth curves are different clones or whether they are just the same experiment repeated? If it is the latter, then why are they not combined, as is traditionally done?

      These are the individual replicates of the growth curves shown in Figure 1G of the same cell lines done on a different occasion. We always try to show as much of the primary data as possible and believe that showing individual data points from the different experiments is better than only the combined values which obscure the actual course of each experiment.

      52) Line 919-924: the authors mention a blue and red line, but there is only a black line in figure 3D. Moreover, the experiment of using the LYN mislocaliser was only done for KIC12 according to the manuscript. Additionally, the y axis of the figure states relative growth day 4[%] compared to rapalog, but then on the x axis there are several days. In the text it says there is no growth defect until the second cycle, but from this graph it appears the growth defect is evident as early as 1 day post rapalog treatment. Can the authors please clarify and correct the issues pointed out.

      We thank the reviewer for pointing this out, this was due to a copy & paste error in the figure legend that was now amended. We also fixed the incorrect axis label. For the last part (growth defect) please see detailed answer to Major comment#31 raising the same concern for KIC11 (in synchronous parasites the defect only takes effect once the cells reached the relevant stage whereas in asynchronous cultures there are always cells in the relevant stage that due to the rapid effect of the knock sideways already have a growth phenotype).

      53) Figure 1 panel B & C: the label of the figure where the signal from MCA2Y1344STOP-GFP is shown with the DAPI signal overlayed is deceptive since it suggests that this is the signal of full length MCA2. Please change the label of this panel from MAC2/DAPI to MCA2Y1344STOP/DAPI. The same is true for Panel C for the image labeled MCA2/K13 - please change this to MCA2Y1344STOP/K13.

      Done as requested.

      54) Figure 2B: what stages are these parasites? Please state this in the figure. Based on the MyoF pattern, it looks like rings in the upper panel and trophs in the bottom pannel. Why were schizonts not shown?

      Both are trophozoites (early trophozoite in top panel and late trophozoite in bottom panel). This is now labelled in what now is figure 1B. As stated above, schizont stages are less relevant for the topic of this manuscript and in order to prevent the manuscript from getting more disjointed and keeping it more focussed on the main topic, we decided to not include a schizont in the manuscript. Nevertheless, we included an example image below.

      [Figure MyoF_p40px schizont]

      55) Figure 2D&F: it is not very meaningful when growth assays are shown as a final bar after 4 days of growth. It is much more useful and informative to see a growth curve instead (as is shown in the supplementary), since it shows if the defect is apparent in the first growth cycle or later. With the way the data is currently shown, this is not apparent. I would advise the authors to switch the graph in 2F out of a combined graph of all the biological replicates growth curves for S3D - showing error bars.

      While we in principle fully agree with the reviewer in showing the course of the full experiment (which is available in Figure S2E), the key here is to show the overall difference. Hence, we would like to keep this comparison of the overall effect on growth in what now is Figure 1E and G. It is part of the argument to the doubts this reviewer raises to the function of MyoF (mainly in the overall assessment and the significance statement) to show that the phenotype is actually very consistent (partial inactivation through tagging or further inactivation using knock sideways increases endocytosis phenotypes, correlating with parasite viability).

      Please also note, that the growth curves upon knock sideways shown in Figure 1G, S2E are performed with asynchronous parasite cultures, which doesn’t allow us to draw direct conclusions about growth cycle effects.

      Nevertheless, we now also included the suggested combined data representation in Figure S2E.

      56) Figure 3: why were the calculation of FV area, parasite area and FV/parasite area only done for KIC12 and not done for MyoF? It would be interesting to see if any of these values are different for MyoF - whether the parasites are smaller in area and therefore FV smaller. Please present them Figure 2. Images should be already available and would not require further experiments to be done, only the analysis.

      This now has been done (confirming our results) and is included as Figure 1J-K, S2J. This point was also raised as major comment #37, please also see detailed answer there.

      57) Figure 3B: why is there no spatial association assessment for KIC11 and K13 as was done for the MCA2 and MyoF? The authors should show a pie chart showing the degree of association here as was done for the other proteins.

      This is now included in Figure 2C.

      58) Figure 3D: The y axis of the figure states relative growth day 4[%] compared to rapalog, but then on the x axis the experiment takes place over several days. Is this a typo in the y axis? Additionally, the authors state in line 287-290 that the growth defect upon addition of rapalog is only seen in the second cycle, but from this graph it appears the growth defect is already evident 1 day post rapalog addition. The figure legend also does not make sense for this figure since it mentions a blue and a red line, when there is only a black line present. The legend also mentions the LYN mislocaliser which was used for KIC12 not KIC 11 (see above).

      We apologise for the inadequate legend and colour issues, this was amended. This point was also raised in major comment #31 and #52, please find detailed answer there.

      59) Figure 3E: the colour for Control and Rapalog 4 hpi are very similar and very hard to discern. Please choose an alternative colour or add a pattern to one of the samples. The y axis is also missing a label. Is this supposed to be parasitemia (%)?

      We thank the reviewer for pointing this out, the missing label is now included and the colour has been adapted to make them better distinguishable.

      60) Figure 4A: the ring shown in this figure does not appear to be a ring (it is far too large and appears to have multiple nuclei?). Do the authors have any other representative images to show instead?

      This is in fact a ring, but we realize that we accidentally included an incorrect size bar in the ring image of Figure 4A (now Figure 3A) (size bar for 63x objective instead of the correct one for the 100x objective), we apologise for this oversight. We don’t think this parasite has multiple nuclei, instead the Hoechst signal shows the often elongated nucleus seen in rings that can appear as two foci in Giemsa stained smears which leads to the typical diagnostic feature of P. falciparum rings in diagnostics. In order to exclude any doubts about the nuclear localization of KIC12 in rings, we here attached a panel with more examples of KIC12-2xFKBP-GFP-2xFKBP ring stage parasites.

      [Figure KIC12]

      61) Figure 4B: why is there no spatial association assessment for KIC12 and K13 as was done for the MCA2 and MyoF? The authors should show a pie chart showing the degree of association here as was done for the other proteins. This should be done for the different life cycle stages considering the changing localisation of KIC12.

      This is now provided in Figure S4A. As suggested by the reviewer, we independently quantified the association for ring stage, early trophozoite and late trophozoites stage. As there is no KI12 signal in schizonts, we did not include a quantification for this stage.

      62) Figures 4C&E: it is extremely important to show the DNA stain in both these samples considering that a portion of KIC12 is in the nucleus! Please add the DAPI signal for these figures (as for all other figures!).

      Please see major comment #64 for a detailed answer why we did not include DNA staining in the imaging used to assess mislocalization upon knock-sideways.

      63) Figure 4E: this figure should be presented before 4D (considering the line being presented in 4E is used in an experiment in 4D). The authors should switch the order of these two.

      We see the point the reviewer is raising here, Figure 4D (now Figure 3D) also contains the data with the Lyn mislocaliser while we first talk about the NLS mislocaliser. This permits a better comparison between the two mislocaliser lines. However, first explaining the Lyn-mislocaliser and then going back to the NLS would make it rather complicated for the reader to follow the storyline and therefore we would like to keep the order as it is. We realise that this means the reader has to go back one figure part for seeing the Lyn growth data, but believe this is worth the benefit that the data is there compared to the NLS result.

      64) It is unclear why in many of the fluorescence images the authors do not show the DAPI signal - particularly when colocalising with K13 and when doing the knock sideways experiments. Please add these images to the figures - I would assume they have already been taken, so would simply involved adding the images to the panel.

      We did not include DNA staining (DAPI or Hoechst) for any of the images used to assess the efficacy of mislocalization, as we would prefer to keep the parasites as representative of a viable parasites in culture as possible. Hence they were imaged without DNA stain (these stains are toxic). We would like to point out that a DNA stain is not necessary, as the mislocaliser already marks the nucleus (in the case of the NLS mislocaliser), actually even somewhat more accurately, as it fills the entire nuclear space rather than only the DNA which is marked by DAPI or Hoechst.

      For LYN this admittedly is not the case, there the mislocaliser marks the plasma membrane. However, we think the proper control for efficient mislocalisation is the comparison between the GFP-tagged protein of interest and the mCherry mislocaliser to show mislocalisation, as previously done in our lab (e.g. (Birnbaum et al., 2017; Jonscher et al., 2019; Birnbaum et al., 2020)).

      Due to their toxicity, we also avoided nuclear staining in some other parts of the manuscript when we were of the opinion that a nucleus signal was not necessary.

      65) Throughout the manuscript, there is no western blot confirming the correct size of their modified proteins. This should be provided.

      We did perform Western blot analysis for both MCA2 cell lines. MCA2 is the only gene-product for which we generated a disruption for this work, and together with the severe truncation from previous work, we provided a Western blot-based confirmation of the correct size.

      The MCA2 disruptions are at least partially dispensable for in vitro parasite growth, hence if degradation occurred, this might not have been noticed. In that case we considered it relevant to show that the truncations were of the expected size. The other proteins in the main figures are essential for growth. Hence, if the tagging approach would lead to unexpected changes in protein integrity (which we assume is what was intended by this concern to be assessed with a Western blot), the parasites expressing the tagged MyoF, KIC11 and KIC12 would - due to their importance for asexual blood stage development - not have been obtained. Hence, we can assume the integrity of the tagged protein is very unlikely to have been affected in a functionally relevant way.

      66) None of the figures are appropriate for individuals with colour blindness, limiting their accessibility to the paper. Please change the colour schemes for all fluorescent images using magenta/green or an alternative colour combination appropriate for colourblind individuals.

      We thank the reviewer for this comment. This has now been amended, individual channels of fluorescence microscopy images are now shown in greyscale, while the overlay was changed to green/magenta.

      Minor Comments

      1) line 29: remove 'are'.

      Done.

      2) Line 29: the text says "HCCU is critical for parasite survival but is poorly understood, with the K13 compartment proteins are among the few proteins so far functionally linked to this process." The sentence should be: 'HCCU is critical for parasite survival but is poorly understood, with the K13 compartment proteins among the few proteins so far functionally linked to this process."

      Done.

      3) line 44: remove 'the'

      Done.

      4) Line 48: consider mentioning here that malaria is caused by the parasite Plasmodium - otherwise the first mention of parasite in line 52 is confusing for the non-specialist reader.

      Done.

      5) Line 49: estimated malaria-related death and case numbers are from the 2021 WHO World malaria report. You cite the 2020 WHO World malaria report.

      We now cite the newest WHO report.

      6) Line 53: please insert the word 'have' between now and also.

      Done.

      7) Line 54: please change 'was linked' to is linked

      Done

      8) Line 72: I would specify that free heme is toxic to the parasite. Especially as you mention that hemozoin is nontoxic.

      Sentence would be "where digestion results in the generation of free heme, toxic to the parasite, which is further converted into nontoxic hemozoin"

      Done.

      9) Line 90: authors should either say "in previous works" or "in a previous work"

      The text has been altered to say: “ in a previous work”.

      10) Line 91: "We designated these proteins as K13 interaction candidates (KICs)"

      Done.

      11) Line 95: please change 'rate' to number

      Done.

      12) Line 109: Please include a coma before (ii).

      Done.

      13) Line 112: as shown by Rudlaff et al in the paper you are citing, PPP8 is actually associated with the basal complex. You can say that "(ii) were either linked or had been shown to localise to the inner membrane complex (IMC) or the basal complex (PF3D7...).

      Done.

      14) Line 114: Protein PF3D7_1141300 is called APR1 in the manuscript but ARP1 in Supplementary Table 1. Please correct.

      Done.

      15) Line 131: please define SNP - this is the first use of the acronym.

      Done.

      16) Line 133-134: South-East Asia instead of "South Asia"

      Done.

      17) Line 135: please explain what TGD is - it is referred to over and over again in the manuscript without ever being explained.

      We apologise for this oversight. We now explain what is meant with TGD at the suggested point of the manuscript.

      18) Line 145: change 'Western blot' to western blot - only Southern blot is capitalised since it is named after an individual, while the other techniques are not.

      To the best of our knowledge this issue has not been resolved, some Journals capitalize the “W” (e.g. Science), while others don’t (e.g. Nature). We would prefer to continue to capitalize the “W”, as this is consistent with the original publication from (Burnette, 1981), but if there are strong objections, we would be happy to change this____.

      19) Line 152: add "the" between 'and spatial'

      Done.

      20) Line 158: please define SLI as selected linked integration, since it is the first use of the acronym.

      Done.

      21) Line 178: introduce a coma after protein. Sentence should be "Proliferation assays with the MCAY1344STOP-GFPendo parasites which express a larger portion of this protein, yet still lacking the MCA domain (Figure 1), indicated no growth ...

      Done.

      22) Line 195: the authors could mention that MyoF was previously called MyoC in the Birnbaum 2020 paper. I wanted to check back in the Birnbaum 2020 paper and could not find MyoF

      Good point, this was done.

      23) Line 200: "Expression and localisation of the fusion protein was analysed by fluorescent microscopy". Why expression was not analysed also by western Blot same as for MCA2?

      Please see major comment #64 for a detailed answer.

      24) Line 204: I could not find any mention of MyoF (Pf3D7_1329100) in reference 65. Please remove reference 65 if not correct. Also reference 66 looks at Plasmodium chabaudii transcriptomes so I would specify that "This expression pattern is in agreement with the transcriptional profile of its Plasmodium chabaudii orthologue"

      Reference 65 (Wichers et al., 2019) provides an RNAseq transcriptome dataset for asexual blood stage development of 3D7 (originating from the same source as the 3D7 used in this study). While Ref 66 (Subudhi et al., 2020) indeed contain transcriptomic data from P. chabaudi, the authors also provide a nice 2h window RNAseq transcriptome dataset for asexual blood stage development of Plasmodium falciparum. Both datasets are therefore suitable as reference for the statement about myoF transcription pattern. Both datasets are also easily accessible and show the pattern in a graph in PlasmoDB.

      25) Line 208: Please indicate a reference for P40 being a marker of the food vacuole

      Done.

      26) Line 220-224: The authors should consider changing to " Taken together these results show that MyoF is in foci that are mainly close to K13 and, at times, overlapping, indicating that MyoF is found in a regular close spatial association with the K13 compartment."

      The suggested wording introduces "mainly" for "frequently" and likely was in part motivated by the discrepancy in location between cell lines that we hope we now could clarify to be only minor (see major point #23). We therefore think the original wording appropriately summarises the findings (line 178): “*Taken together these results show that MyoF is in foci that are frequently close or overlapping with K13, indicating that MyoF is found in a regular close spatial association with the K13 compartment and at times overlaps with that compartment.” *

      27) Line 255: In Figure 2H, and subsequent figures showing bloated FV assay, I would delineate the food vacuole with dashed line as in Birnbaum et al. 2020 to help the reader understanding where the food vacuole is.

      In contrast to the Figures in Birnbaum et al. 2020, we here included the DHE staining (parasite cytosol) in images of bloated FV assays which visualizes the FV. We therefore decided to avoid any further marking, to keep the image as unprocessed as possible (see also major point 48).

      28) Line 265-266: Here the title says that KIC11 is a K13 compartment associated protein, but the title of Figure 3 says KIC11 is a K13 compartment protein. I noticed that you make the difference between K13 compartment protein et K13 compartment associated protein for MyoF for example which is not clearly associated with the K13 compartment. Which one is it for KIC11?

      The interpretation of the reviewer is correct, we indeed graded this subconsciously based on level of overlap. Based on the newly added quantification shown in Figure 2C, we describe KIC11 now as K13 compartment protein.

      29) Line 309-310: indicate a reference for your statement "which is in contrast to previously characterised essential K13 compartment proteins".

      Done, we now included Birnbaum et al. 2020 as reference for this.

      30) Line 377: Figure 4I, please correct 1st panel Y axis legend

      Done.

      31) Line 404: replace "dispensability" with dispensable

      Done.

      32) Line 416: can the authors provide any speculation as to why they observed these proteins as hits in the BioID experiments?

      As some of these proteins were less well or less consistently enriched, they could be background of the experiment. Alternatively, some could be proteins that only transiently interact with the K13 compartment.

      33) Line 451: Where the "97% of proteins containing these domains also contain an Adaptin_N domain and function in vesicle adaptor complexes as subunit a" come from. Do you have a reference?

      The statement now includes references and reads (with small changes to original submission): "More than 97% of proteins containing these domains also contain an Adaptin_N (IPR002553) domain (Blum et al., 2021) and in this combination typically function in vesicle adaptor complexes as subunit α (Hirst and Robinson, 1998; Traub et al., 1999) (Figure 5D) but no such domain was detectable in KIC5."

      34) Line 465-467: the same could be said for KIC4 as it also has a VHS domain.

      The critical issue is the combination of domains and their position within the protein. While KIC4 also contains a VHS domain, the VHS domain in KIC4 is N-terminal, not in a central position and it is also not the first structural domain to be identified in KIC4. The similarity to adaptin domains was already described ((Birnbaum et al., 2020) and annotated in PlasmoDB) and these domains are also involved in vesicle formation and trafficking. These aspects of the statement can therefore not be extended to KIC4. With regards to VHS domains being involved in vesicle trafficking, this is already stated in line 538: «KIC4 contained an N-terminal VHS domain (IPR002014), followed by a GAT domain (IPR004152) and an Ig-like clathrin adaptor α/β/γ adaptin appendage domain (IPR008152) (Figure 5A-C, Figure S8). This is an arrangement typical for GGAs (Golgi-localised gamma ear-containing Arf-binding proteins) which are vesicle adaptors first found to function at the trans-Golgi (Dell’Angelica et al., 2000; Hirst et al., 2000)

      35) Line 477-479: Can be rephrased to "However, we found this protein as being likely dispensable for intra-erythrocytic parasite development and no colocalisation with K13 could be demonstrated, suggesting a limited role for PF3D7_1365800 in endocytosis. Or something like that. Makes it clearer.

      We rephrased this sentence and it now reads (line 592): However, we found this protein as being likely dispensable for intra-erythrocytic parasite development and no colocalisation with K13 was observed, suggesting PF3D7_1365800 is not needed for endocytosis“.

      36) Line 535: Have AP-2a or AP-2b been shown to be at the K13 compartment?

      AP2m is at the K13 compartment (Birnbaum et al., 2020). Adaptor complexes are heterotetramers and their subunits do not typically function on their own and this is conserved across evolutionarily distant organisms. In agreement that this is also the case in P. falciparum, Henrici et al. (Henrici et al., 2020a) showed that both, AP-2a and AP-2b, were present in an AP2µ Co-IP, indicating that the AP2 complex consist of the ‘classical’ subunits in P. falciparum. Therefore, the presence of all subunits at the K13 compartment is very likely, although this has only been experimentally confirmed for AP2µ. Of note, for Toxoplasma gondii the presence of AP-2a and AP-2b at the micropore has been experimentally confirmed (Wan et al., 2023; Koreny et al., 2023) and interaction suggested by presence in the same IP as DRPC (Heredero-Bermejo et al., 2019).

      37) Line 569: reference 43 is wrong

      We thanks the reviewer for pointing this out – we removed Ref 43.

      38) Line 746: typo "ot" instead of or.

      Changed.

      39) Line 801: method for Domain Identification using AlphaFold specify that RMSDs of under 5Å over more than 60 amino acids are listed in the results. However, there is a typo in Figure 5B for KIC5 where it says "RMSD 4.0 Å over 8 aa". Please correct.

      Done. In addition, we have now applied a more stringent cut-off of 4Å over more than 60 amino acids to ensure a higher reliability of our hits. This decision was based on results from our preprint (Behrens and Spielmann, 2023). Because of this the phosphatase domain in KIC12 is no longer included in this manuscript and accordingly the following sentence has been deleted. In KIC12 we identified a potential purple acid phosphatase (PAP) domain. However, with the high RMSD of 4.9 Å, the domain might also be a divergent similar fold, such as a C2 domain, which targets proteins to membranes.”

      40) Line 856: In Figure 1E, please use the same Y axis legend as in Figure 2D "relative growth at day 4 [%] compared with 3D7"

      Done.

      41) Figure S1: Some PCR gels check for integration are presented as 5', 3' and ori whereas other gels are presented as ori, 5' and 3'. This is confusing.

      We agree that ideally the order of sample loading should be consistent and we apologise for this. The explanation for this is that these gels were run by different people at different times before we were able to better standardize the loading scheme. However, in the interest of not unnecessarily using resources for something that has a similar meaning, we would prefer not to repeat these PCRs and re-run them only for consistency reasons (as the conclusion is not affected by the different loading schemes).

      42) Figure S1: Why was the expression of only MCA2 was verified by Western blot? What about the other proteins?

      See response to major comment 56.

      43) Line 493: Considering KIC11 was not involved in HCCU or ART resistance it might be worth mentioning in this section that it is of note that there are no domains detected that would be involved in endocytosis.

      We agree that this is the case, however it is also the case for all other proteins that either are not involved in endocytosis and/or lowered susceptibility to ART. We therefore now added a summary statement addressing this in line 602: In contrast, the K13 compartment proteins where no role in ART resistance (based on RSA) or endocytosis was detected, KIC1, KIC2, KIC6, KIC8, KIC9 and KIC11, do not contain such domains (Figure 5E).” We did not add this at the suggested part of the manuscript as at that point the domain search results are not yet introduced and doing this each time for all the individual proteins would disconnect the flow of the manuscript.

      44) Line 503-506: is it wise to generate more drugs that target a pathway that is already highly susceptible to mutations? The authors should add a statement explaining how this might be avoided.

      The only protein for which mutations do not have a large fitness cost is K13 (see also our preprint on fitness cost of ubp1 mutation (Behrens et al., 2023) and even with K13 the level of resistance seems to be limited by amino acid deprivation when endocytosis is reduced (Mesén-Ramírez et al., 2021). We therefore do not think that this pathway is particularly prone for mutations. Further, the number of commercial drugs targeting the "endproduct" of endocytosis (hemoglobin digestion and detoxification of heme) highlight it as the most prominent vulnerability for drug-based intervention if we go by number of commercially available drugs acting on things associated with a single process.

      45) Throughout, scale bars are stated in the figure legends at the end of the legend. This is a slightly confusing format. The authors should consider stating the scale bar for each sub-legend where a fluorescence image is taken.

      Done.

      ** Referees cross-commenting**

      After reading reviewer 2 and 3's comments, I think there are significant overlaps in the key points raised in terms of questions about fusion proteins and their potential partial mis-localisation, better descripton of results and target selection. Overall I think we agree that the work has potential, but in its current form does not represent a major advance. It would be immensely helpful if the manuscript would be carefully edited for a better flow and linear description of results.

      We now rearranged the manuscript for better flow but would like to highlight that the many requests for smaller experimental issues (and "better description of results") worked somewhat in the opposite way of a more linear description. We hope the rearranged version acceptably balances these two issues. The issues raised in regards to target selection and potential partial mis-localisation are addressed in our responses mainly to this reviewer. Please also see comments on systems used at the end of the rebuttal.

      Reviewer #1 (Significance (Required)):

      The authors set out to test whether other proteins that are in the vicinity of K13 are involved in mediating ART resistance and endocytosis. This is an interesting question. However, other than MCA2 which was already known to be involved in mediating ART resistance (and was not tested for its involvement in endocytosis), none of their candidate proteins seem to be involved in mediating both these functions. The authors show that the other proteins tested appear important for parasite growth, with KIC12 and MyoF involved in mediating endocytosis. While these findings are novel, the KS approach used by the authors casts some doubt over the findings, and would mean that these findings would have to be re-tested with a more reliable approach, such as the GlmS system or generating a conditional knockout using the DiCre system. Despite not advancing our understanding of ART resistance, or identifying further players involved in this process, this manuscripts provides two candidates that are involved in mediating endocytosis and a further candidate that appears to be important for parasite growth. Further work on these proteins will be required to understand their exact roles. As stated above, there is currently limited interest for these results (limited to researchers working on endocytosis in apicomplexan parasites and possibly the wider endocytosis field from an evolutionary perspective), however with further work, this could increase the impact and interest of this work substantially.

      The authors do not describe any novel methods/approaches within this work.

      In the significance statement the reviewer indicates that other systems would have been more reliable for the work here. This is addressed in our response above and in a detailed considerations on the properties of conditional inactivation systems at the end of the rebuttal. The systems used in this work were not only chosen because they permit rapid targeting of many different proteins, but because they have merits that are beneficial for our assays. In fact many of the functional assays in this manuscript are difficult or impossible to carry with the suggested conditional inactivation systems (please note that we have extensive experience with the systems considered preferable:

      • DiCre (Birnbaum et al., 2017; Mesén-Ramírez et al., 2019; Mesén-Ramírez et al., 2021; Wichers et al., 2022; Kimmel et al., 2023)

      • glmS (Wichers et al., 2021c; Wichers et al., 2021a; Wichers et al., 2022; Wichers-Misterek et al., 2023)).

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

      In a previous publication the Spielmann lab identified the molecular mechanism of ART resistance in P. falciparum by connecting reduced levels of the protein K13 to decreased endocytosis (uptake of hemoglobin from the RBC cytosol), which results in reduced ART susceptibility. Using quantitative BioID the authors further identified proteins belonging to a K13 compartment, highlighting an unusual endocytosis mechanism.

      In the present manuscript the authors follow up on this work and closely examine ten more proteins of the K13/Eps15-related "proxiome". They successfully link MCA2 to ART resistance in vitro, while the proteins MyoF and KIC12 are involved in endocytosis but do not confer in vitro ART resistance when impaired. They further characterize one candidate (KIC11) that partially colocalizes with K13 in trophozoites but to a lesser degree in schizonts. Growth assays suggest an important function for KIC11 in late stages of the intraerythrocytic developmental cycle. Five analyzed proteins however do not colocalize with the K13 compartment, while a sixth was refractory to endogenous tagging.

      Using AlphaFold predictions of the KIC protein structures the author identify domains in most constituents of the K13 compartment, highlighting vesicle trafficking-related features that were not identified on primary sequence level before.

      The combination of functional data together with structure predictions leads them to propose a refinement of the K13 compartment as being divided into proteins participating in endocytosis and proteins that have an unknown function.

      We thank the reviewer for the assessment of the manuscript and the constructive comments.

      Major comments:

      1) -Table 1 is missing

      We apologise for this mistake; Table 1 is now included.

      2) -Lines 117-123: Given the total list of uncharacterized candidates encompasses 13 proteins, can the author gives the reason why only the top 10 and not all 13 were characterized in this study?

      A similar point has been raised by Reviewer 1 in major comment #12, please see our response there for an explanation why we chose which targets.

      3) -Line 174: 20% of observed MCA2 foci show no overlap with K13 and 21% only partially overlap, can the author confirm that the observed MCA2 foci in schizonts are the ones that co-localize with K13. (Addition of a schizont stage image in Fig 1C would be sufficient).

      We now extended Figure 4C with images of MCA2-Y1344STOP-GFP+mCherryK13 parasites covering the schizont and merozoite stage, showing that the majority of the MCA2 foci in schizonts are also mCherry-K13 positive.

      4) -The localization and observed phenotype of KIC11 is interesting but unfortunately the authors do not explore it further. Does KIC11 localize with markers of e.g. the secretory organelles (micronemes or rhoptries) in schizonts and could therefore be involved in RBC invasion?

      While we intended to focus mainly on the endocytosis aspect of these proteins, we see the reviewer's point and now generated new cell lines enabling assessment of spatial association of KIC11 with markers for rhoptry (ARO), micronemes (AMA1), and inner membrane complex (IMC1c). This revealed that the KIC11-GFP signal in schizonts does not overlap with apical organelle markers and the signal does not resemble a typical apical localization. In addition, we assessed all three organelle markers after inactivating KIC11 by knock sideways which showed that KIC11 inactivation has no apparent effect on the appearance of these markers, suggesting no major alterations in schizont morphology in respect to apical markers. These results are now presented as Figure S3A and in line 304 of the results.

      5) Can the author distinguish if KIC11 is involved in RBC invasion or in establishment of the ring-stage parasite?

      In order to look into this, we performed egress/invasion assays, quantifying schizont and ring stage parasites in tightly synchronized parasites at two different time points (pre-egress: 38-42 hpi & post-egress: 46-50 hpi). This revealed a significant decrease in newly formed ring stage parasite per ruptured schizont in parasites with inactivated KIC11, while the egress efficacy remained unaffected. This indicated an invasion or very early ring stage development defect (new Figure 2H, Figure S3G). To further determine at which point exactly the phenotype occurs (ie during invasion or early after invasion) would require extensive experimentation that goes beyond the scope of this study (e.g. invasion assays using video microscopy with a representative number of parasites or sophisticated flow based quantification assays). We hope by excluding egress and gross changes of apical organelles as well as no indication for similar number of early rings (indicating it is invasion or a very early ring-establishment phenotype) will sufficiently narrow down the phenotype for labs interested in invasion to more definitely answer this question.

      Minor comments:

      1) Table S1: Please add the criterion for the order of proteins (abundance in "proxiome"?) in the table as a separate column. I would also suggest adding a new column that highlights the 10 proteins investigated in this study as I found the color-coding slightly confusing.

      Done as suggested: we now include the “average log2 Ratio normalized Kelch13” values from the four DiQ-BioID experiments performed with K13 in (Birnbaum et al., 2020), as well as the suggested column to highlight the investigated proteins. Please also see reviewer 1 major point # 12 for additional information on the selection criteria and how this was added to the manuscript.

      2) -154-155: There is a discrepancy between the text and Fig1C regarding the % of partial overlapping and non-overlapping foci.

      We thank the reviewer for pointing this out, this was corrected.

      3) -The y-axis label is missing in Fig 3E

      Done.

      4) -Fig 4I left graph, the superscript 2 is missing in μm2

      We thank the reviewer for pointing this out, this is now changed.

      5) -Did the author colocalize KIC11 in schizonts with other proteins found in the K13 compartment group of proteins not involved in endocytosis/ART resistance? This may help to further subgroup these proteins.

      This is an interesting point but would actually be technically challenging to do. For this we would need to generate a KIC11endo parasite line for each of these KICs and then do co-localisation in schizonts. However, the outcome of this likely would not be very clear. The reason for this is as follows. There are foci of KIC11 that do overlap with K13 in schizonts. One can expect that these foci show KIC11 at the K13 compartment and that the other KICs would overlap with KIC11 in these K13 foci in schizonts. Hence, we would also need to see K13 to find the non-K13 compartment KIC11 foci and see if these contained the KIC of interest. This is technically challenging because it would mean we would need a third fluorescent protein which is not that trivial to do. Due to the difficulty to do this and the large amount of work involved and the already considerable amount of data in this manuscript, we believe this will be better suited for a different study.

      6) -As a general comment: to make the beautiful IFAs more accessible to a broader readership, I would encourage the authors to switch the color-coding to green/magenta/blue or an equivalent color system or add grayscale images.

      This was done as suggested, all fluorescence images are now provided as greyscale images and the overlays are shown in magenta/green.

      Reviewer #2 (Significance (Required)):

      Characterizing the molecular components involved in Plasmodium endocytosis will not only reveal interesting biology in these highly adapted parasites, but will more importantly lead to a better understanding and potentially open new avenues for intervention of ART resistance. The here presented manuscript is a carefully executed follow-up on previous work done in Dr. Spielmann's lab focusing on the K13 compartment. The authors use established assays to characterize novel components and reveal three new players in endocytosis with one mediating ART resistance in vitro. The proposition that parts of the K13 compartment have a function other than endocytosis is interesting, but will have to await more data from future studies. Taken together this manuscript adds significantly to our understanding of endocytosis in P. falciparum.

      This work is of interest for cell and molecular biologists working on Apicomplexa, but especially for the Plasmodium community.

      We thank the reviewer for this positive assessment.

      I am a cell and molecular biologist working on Toxoplasma gondii

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

      Summary: The authors characterized 4 proteins from P. falciparum via cellular (co-)localization, endocytosis, parasite growth, and artemisinin resistance assays. These proteins have been identified as candidates for Kelch13 compartment and a possible role in endocytosis in their previously work with quantitative BioID for potential proximity to K13 and Eps15 (Birnbaum et al. 2020). In the current work, additional 6 proteins were not confirmed as being associated to the K13 compartment. This experimental work was complemented by an in-silico analysis of protein domains based on AlphaFold algorithm. For this protein structure evaluation all proteins were chosen, which were experimentally confirmed to be linked to the K13 compartment in the current publication and previous work. With the work 3 novel proteins linked to artemisinin resistance or endocytosis could be functionally described (KIC12, MCA2, and MyoF) and a number of hypotheses were generated.

      We thank the reviewer for the assessment of the manuscript and the constructive comments.

      Major comments:

      The quality of the presented work is solid, the experimental design is adequate, and methods are presented clearly. The publication contains a lot of results both presented in text and in the figures and it is not always straight forward for the reader to follow the descriptions due to many details presented and a lack of context for some of these experiments.

      We thank the reviewer for this overall positive assessment.

      We now reordered the results section in an attempt to increase the flow of the manuscript. We also made changes to improve the context for the results. Given the further (very valid) requests for data on schizonts and invasion, there was an increased danger for a less linear manuscript that we hope to have acceptably managed with the re-arrange.

      Specific suggestions for consideration by the authors to improve the manuscript. Abstract: 1) R 31: Mention how the 4 proteins were identified as candidates, you need to refer to previous work to clarify this

      To clarify this the sentence was changed to (line 31): "Here we further defined the composition of the K13 compartment by analysing more hits from a previous BioID, showing that MyoF and MCA2 as well as Kelch13 interaction candidate (KIC) 11 and 12 are found at this site."

      2) R38: "Second group of proteins" is confusing - different from the 4 mentioned above? Significance to endocytosis unclear. Please unify terminology in the manuscript, see also comment below on proxiome.

      We changed the wording to clarify the group issue in the abstract as follows line 34: "Functional analyses, tests for ART susceptibility as well as comparisons of structural similarities using AlphaFold2 predictions of these and previously identified proteins showed that canonical vesicle trafficking and endocytosis domains were frequent in proteins involved in resistance or endocytosis (or both), comprising one group of K13 compartment proteins, While this strengthened the link of the K13 compartment to endocytosis, many proteins of this group showed unusual domain combinations and large parasite-specific regions, indicating a high level of taxon-specific adaptation of this process. Another group of K13 compartment proteins did not influence endocytosis or ART susceptibility and lacked detectable vesicle trafficking domains. We here identified the first protein of this group that is important for asexual blood stage development and showed that it likely is involved in invasion.”

      3) Abstract can only be understood after reading the full publication

      We attempted to amend this by expanding the abstract, particularly the changes highlighted in the previous two points.

      Results: 4) Table 1 is missing from the submitted materials

      We apologise for this mistake. Table 1 is now included.

      5) Consider to shorten and stratify the result section to focus on the significant data

      We rearranged the results in an attempt to streamline this section and are now starting with MyoF in the revised manuscript. However, as highlighted by the requests from reviewer 1, many details need to be available to support our conclusions. For instance the fact that GFP-tagging partially inactivated MyoF asked for further data to support our conclusion (HA-tagged version, showing that the location of the GFP-tagged version was consistent with the HA-tagged version, showing to what extent the different constructs affected growth and correlated with number of vesicles and bloating, see new figure 1M) or that KIC12 has two locations. Overall, we are therefore hesitant to remove data or description from the result part.

      6) Unclear how the localization and functionalization assays might be impaired by the fusion proteins Significance of ART resistance assay is not clear, in presence of strong growth effects due to inactivation or truncation of genes/proteins

      As indicated also in the example given in the previous point (this reviewer #5), the use of different cell lines (GFP-tagged live cells and small epitope tag in IFA) for targets with an indication for an effect of the tagging confirm that the location we assigned is reasonable. In the case of MyoF, the HA-tagged line, the partial inactivation due to GFP and the further inactivation in the GFP-tagged line by knock sideways show plausible increase of phenotypes (vesicle accumulation and bloated FV assays). Thereby the GFP-tagged line can be seen as a partial inactivation line that further supports our conclusions and overall this paints a consistent picture of the function of this protein in endocytosis (see new Figure 1M better illustrating this). Please note that the difference in location shown by this line compared to the HA-tagged proteins is only small (see also reviewer 1 major point 23ff). See also general discussion on tags at the end of this rebuttal.

      Significance of ART resistance assay: The ‘ART resistance assay’ is done comparing +/- ART (DHA) in identical parasites (originating from the same culture and the same condition). Hence, any growth effects are cancelled out and effects in reducing ART susceptibility would - if at all - be underestimated (see more detailed response to point 28, reviewer 1 and controls in Birnbaum et al., 2020 where we tested an unrelated essential protein, unrelated chemical insult and rapalog on 3D7 and did not detect any effect on RSA survival).

      MCA 7) Stratify results, order by significance of findings, it appears to be described in chronological order, improve readability/flow, eg ART resistance if mentioned in r138, but only reported in r183ff

      We attempted to stratify, but then the reason for generating the partial MCA2 disruption parasite line becomes very arbitrary and would leave the reader wondering why we at all truncated the protein at two thirds of the protein. Hence, we do not see a way around this chronological reporting. However, this part is now not at the start of the experimental results section anymore, possibly making it overall a bit more palatable.

      MyoF 8) R195 to 197 - consider moving to discussion as it is distracting here

      This was shortened and additional information (asked for by reviewer 1, major point 22) to clarify that MyoF was previously called MyoC, was added (line 147): “The presence of MyosinF (MyoF; PF3D7_1329100 previously also MyoC), in the K13 proxiome could indicate an involvement of actin/myosin in endocytosis in malaria parasites. "

      9) Term proxiome is introduced above, but not used in result section - suggest to unify language, eg r195 uses "K13 compartment DiQ-BioIDs" instead, which is not very convenient for the reader

      We carefully reviewed this and made this more consistent.

      10) What is the enrichment factor? Please provide for this and the following proteins, eg in Table 1

      The enrichment factor is log2 enrichment over control and this is now provided in table S1 (see also detailed answer for Reviewer 1 major point 12).

      11) R225 to 243 - overall significance of the growth experiments with mislocaliser is not clear, consider removing from manuscript or explain relevance more clearly

      See also point 28, reviewer 1: This experiment is actually quite important. It shows that if we conditionally inactivate the GFP-tagged MyoF, the growth is further reduced, as stated in line 208. It might have been confusing that the mislocalisation is only partial, but this is equivalent to a partial knock down and hence is useful. This becomes even more relevant with the specific assays following in the next paragraph: while the tagging of MyoF already resulted in vesicles, conditional inactivation with KS generated even more vesicles, showing that the same phenotype was rapidly increased when MyoF was further inactivated by a different means and this also correlated with growth. Hence, this is actually a very consistent phenotype that despite some shortcomings of the tools available to analyse this protein (due to the partial inactivation by the GFP tag) in our eyes looks very convincing. We now added a graph showing the correlation of growth and phenotypes to illustrate this (Figure 1L).

      We also tried to make this clearer by changing line 200 to: Hence, conditional inactivation of MyoF further reduced growth despite the fact that the tag on MyoF already led to a substantial growth defect, indicating an important role for MyoF during asexual blood stage development.” And line 208 to:“ This was even more pronounced upon conditional inactivation of MyoF by KS (Figure 1H), suggesting this is due to a reduced function of MyoF.”

      12) KIC11/KIC12 Enrichment factor?

      The enrichment (’average log2 Ratio normalized Kelch13 from Birnbaum et al. 2020’) is 1.65 for KIC11 and 1.32 for KIC12, which is now also explicitly shown in column D of Table S1.

      ** Referees cross-commenting**

      I would like to applaud reviewer #1 for a great, very thorough review and lots of detailed suggestions. I agree with the conclusions mentioned in the significance evaluation from reviewer #1 and #2: the work presented does not contain novel methods and the scope is rather narrow with the current results. (I am working on clinical studies with novel antimalarial agents)

      Reviewer #3 (Significance (Required)):

      On the one hand side, the authors have wrapped up some of the remaining protein candidates of the K13 compartment and could verify 4 of 10 proteins. The work is of interest for the scientific community working on endocytosis and malaria drug resistance mechanisms. Overall, the conclusions and findings from the previous work, Birnbaum et al. 2020, could be confirmed and extended mainly using the methods previously described. On the other hand, the authors made use of progress in protein structure predictions and identified domains linking the K13 compartment proteins to putative functions. The overlaid protein folds of the newly identified domains in figure 5 look convincing, but I can't comment on the technical details or cut-off used for this in-silico analysis.

      Extended general remarks on the systems used for this work:

      Mainly reviewer 1 suggest (in the general comments and the significance statement) that other systems would have been better suited to use for this work, namely glmS and diCre and also has concerns about the large tag which is seconded by a comment of reviewer 3. In light of this we here provide some extended considerations on the properties for conditional systems and tagging in regards to the goals of this work.

      We would like to point out that we do have experience with the systems considered better-suited by the reviewer (one of the first authors has extensively used glmS (Wichers et al., 2021c; Wichers et al., 2021a; Wichers et al., 2022; Wichers-Misterek et al., 2023) and our lab was one of the first to adopt the diCre system in P. falciparum parasites and we regularly us it (Birnbaum et al., 2017; Mesén-Ramírez et al., 2019; Kimmel et al., 2023)). Clearly, these methods have a lot of strengths but there are a number of issues to be considered for the assays we use in this work (see the next section on conditional inactivation systems). In a nutshell, we believe diCre would give a more reliable readout of the absolute level of "essentiality" (i.e. importance for growth) but is unsuitable or at least difficult to use for the assays that reveal the function of our interest in this work. GlmS basically combines the drawbacks of diCre and knock sideways and hence for most targets is not expected to give a better readout of level of "essentiality" but is similarly difficult to use for our specific assays. The fact that both of these systems are possible to use without adding a tag to the target may be an advantage but without tag one loses some very important features that can be critical to understand the outcome with a given system (see considerations on the tag further below).

      Conditional inactivation systems:

      1. __ speed of inactivation:__ glms acts on mRNA and diCre on the gene level, which makes them slower than techniques acting directly on the protein such as DD or KS. With diCre, mRNA and protein is still left, even if the gene is very rapidly excised. For instance for Kelch13 it takes 3-4 days after excising the gene until protein levels have waned enough that this manifests in a reduced growth (Birnbaum et al., 2017). While in some instances diCre permits same cycle analyses if the protein has a very rapid turn-over (e.g. Rab5a, (Birnbaum et al., 2017)), control in a few hours is still difficult. For vesicle accumulation and bloated food vacuole assays, which are done over comparably short time frames and with specific stages, it is rather challenging to hit the correct time of induction to have all the cells at the correct stage with suitably (and uniformly, ie all cells) sufficiently reduced target protein levels during the assay time. Slow acting systems are also more prone to secondary effects. The more immediate the inactivation, the closer it is to the core of the affected function. With vesicle trafficking processes this is particularly relevant as all vesicle trafficking in a cell is interconnected and there are always recycling pathways that maintain the membrane and protein homeostasis of individual compartments. Particularly for endocytosis there seem to be compensatory capacities at least in other organisms (see e.g. (Chen and Schmid, 2020)). One reason why knock sideways was developed is that it permitted to avoid compensatory changes when vesicle adaptors are inactivated (Robinson et al., 2010).

      The comparably short time frame for malaria parasites to go through different stages during blood stage development also is an issue relevant for inactivation speed. The advantage of speed and the danger of obscured phenotypes is highlighted by our work on VPS45 which showed that in trophozoites this protein is involved in the transport of hemoglobin to the FV whereas in late stages it also has a role in secretory processes. Both of these functions we were able to specifically assess in the same growth cycle using KS to rapidly inactivate the protein (Bisio et al., 2020) but with a slower system would have been more complicated to dissect.

      Speed of effect with glmS: unless the KS does not work well, glmS is slower acting than KS (it does not target the already synthesised protein which can remain in the cell) and also often suffers from only partial inactivation, hence the benefit of using it here is unclear. The option to have an untagged protein is a plus, however it also is a minus, as assessing efficiency (particularly in live cells e.g. for bloated assays etc a fluorescent tag is the only direct option to assess inactivation of target) is critical to ensure the phenotype manifests at the stage of interest.

      lethality/absolute phenotypic effects are detrimental to some assays to study the functions we are interested in for this work: no RSA can be conducted, if the gene is lost and the parasites die. Again, with diCre, one could attempt to hit the point when the parasites have lost sufficient amounts of the target protein when they are placed under ART but then the parasites need to continue growing for ~3 days, which is not possible if the cKO is lethal except for very slowly turning over proteins. However, in that latter case, the parasites likely still had full functionality of the target protein at the beginning of the RSA, when the drug pulse happens and there would be no effect. Knock sideways solves these problems by permitting knock sideways inactivation only under ART (or with a few hours pre-incubation depending on the inactivation speed) to not yet affect growth in a severe manner but inhibiting the process the protein is involved in. It may be possible to use glmS for RSAs, but the slow speed would complicate it (it would not permit control of target protein levels in a matter of a few hours to inactivate the target protein and then re-install it).

      None-absolute inactivation is also a strength for some functional assays. While we really like using diCre, in the case of EXP1 it made it necessary to complement the exp1 cKO parasites with low levels of EXP1 to be able to do functional assays without killing the parasites (Mesén-Ramírez et al., 2019; Mesén-Ramírez et al., 2021). While the lethality issue does not apply to glmS (like knock sideways, it also can be tuned), it is unclear what would be gained over knock sideways. Knockdown levels with glmS vary from gene to gene and cannot be predicted, it is in most cases considerably slower than KS, it requires glucosamine which becomes toxic at higher concentrations and might introduce off target effects and tracking protein levels during the assay would equally need GFP tagging.

      Integration of properties of conditional systems

      Given the above discussed properties, several factors have to be considered to be able to use a system for a given assay. Stage-specific transcription is one example. For diCre a protein not expressed in e.g. rings permits to remove the gene and the protein is never made in that parasite development cycle. We exploited this for instance for two proteins only expressed from the trophozoite stage onwards (Kimmel et al., 2023). However, if lethal (absolute effect problem), this also means one can also only see the phenotype on onset of expression of the target (e.g. if in mitosis, the first nuclear division in case the protein is absolutely essential for the process). This is just one example of such issues. Expression timing, turnover of the protein and homogeneity of stage-specific loss of protein will all influence how clearly the phenotype can be determined. All this will decide the exact time of loss/inactivation of the target protein to levels generating a phenotype and ideally therefore can be monitored during an assay (see considerations on tagging).

      For these reasons vesicle accumulation or bloated food vacuole assays are difficult with slow systems as ideally the target should rapidly be inactivated at the trophozoite stage and the result monitored before the cells have moved to the schizont stage. For this a well responding knock sideways is ideal as the protein can be rapidly taken away (sometimes within seconds) to visualise the immediate, direct effect in the cell.

      As shown for KIC11, there is also no disadvantage of using KS for proteins with other assays or proteins that result in different phenotypes. It permits stage-specific same cycle inactivation without having to worry about the turnover of mRNA and protein (Fig. 2F,G). Thus, besides the advantages of knock sideways for endocytosis related assays and RSAs, we also see no disadvantage of using knock sideways for the functional study of KIC11 which has a role other than endocytosis. KS also permits to specifically target the K13 pool of KIC12, something impossible or very difficult to do with other systems. Hence, we are of the opinion that the system for inactivation was adequate for most of the proteins analysed in this manuscript.

      Large tag: we agree that GFP-tagging can be a disadvantage but in our opinion its benefits often outweigh the drawbacks because it permits easy and immediate (on individual cell level, if need be) monitoring of the presence/location of the target protein (e.g. after KS, but given the discrepancy of the timing between gene excision and protein loss, it might be even more important for techniques such as diCre). No fixing/permeabilisation (prone to artifacts, prevents immediate view of cells) to detect a target with specific antibodies or via a small tag is needed with GFP. Similarly, the use of Western blots to do this is time consuming and impractical if monitoring of left-over protein in the course of an assay such as a bloated food vacuole assay is needed.

      In many cases, adding GFP has no negative effect. In addition, if the bulky folded structure of GFP is tolerated, it usually also tolerates the 2 to 4 12kDa FKBP domains in our standard tag. We also typically add a linker. This approach has worked for a large number of different proteins, including many essential ones for which we would not otherwise have obtained the integration cell lines (Birnbaum et al., 2017; Jonscher et al., 2019; Hoeijmakers et al., 2019; Birnbaum et al., 2020; Kimmel et al., 2023; Sabitzki et al., 2023). Hence, whenever a cell line is obtained with it, this tag in most cases is not a disadvantage. Admittedly an exception in this is MyoF and to some extent maybe MCA2 (we would like to stress that in the case of MCA2 the reason for not being able to obtain the full length tagged cell line is unclear: the protein can be severely truncated to less than 3% of its amino acid sequence and a GFP-tag is tolerated on the version with 2/3s of the protein left, which gives no good reason why the full length was not obtained; a potential reason could be a dominant negative effect). However, we obtained the full length with a small tag detected by IFA for both, MyoF and MCA2 and the location of these agreed well with the GFP tagged versions, indicating that the GFP-tagged versions are useful to show the location of these proteins in live cells.

      There are also tricks to attempt monitoring the effect of e.g. diCre without tagging the target. For instance, if a fluorescent protein is connected to excision without actually being fused to the target (ie excision of the gene leads to its expression of e.g. GFP), which would avoid adding a tag to the target itself. However, the problem with this is that expression of GFP does only show excision, but mRNA producing the target protein and left over target protein may still be there in the cell. All in all, the GFP-tag on the target, while with some drawbacks, is still our preferred method to control to monitor the target protein in the cell (in principle permitting quantification of ablation efficiency on the individual cell level).

      Conclusion on these considerations for this manuscript

      Based on these considerations we do not see the immediate benefit of changing the system for the conclusions drawn from this study and are unsure if they are indeed better suited for this work as suggested. While a more exact readout of "essentiality" might be possible with the diCre system we are of the opinion this is less important than learning the function of a protein which - as outlined above - we believe to be considerably more difficult with diCre and even more so with glmS considering our target functions. The same applies to target specific cellular pools of a protein as done here for KIC12. Clearly MyoF is one example where the employed systems shows limitations, but with the new Figure part showing consistency in phenotype with degree of inactivation (importantly with two different forms of inactivation) and the clarification that the location of the GFP-tagged and HA-tagged versions are actually quite similar in location, we do not think employing an extra system is warranted for the conclusions of this work. Admittedly, the apparent lack of need in ring stags might give an opening to attack MyoF using diCre (by excision before its major expression peak), but depending on lethality this might preclude extended analyses (possibly vesicle assays, for sure not RSAs).

      In the end the question is, if our approach provides the function of target analysed in this work and based on the data in our manuscript and the arguments in the rebuttal, we are reasonably confident that this is the case. It is not very likely the other mentioned techniques would result in a different conclusion on the function of the here studied proteins. In fact, we expect other commonly used techniques to be less suitable for the key assays in this work.

      References used in our responses to the reviewers’ comments:

      Behrens, H.M., Schmidt, S., Peigney, D., Sabitzki, R., Henshall, I., May, J., et al. (2023) Impact of different mutations on Kelch13 protein levels, ART resistance and fitness cost in Plasmodium falciparum parasites. bioRxiv 2022.05.13.491767.

      Behrens, H.M., Schmidt, S., and Spielmann, T. (2021) The newly discovered role of endocytosis in artemisinin resistance. Med Res Rev med.21848.

      Behrens, H.M., and Spielmann, T. (2023) Identification of domains in Plasmodium falciparum proteins of unknown function using DALI search on Alphafold predictions. bioRxiv 2023.06.05.543710.

      Birnbaum, J., Flemming, S., Reichard, N., Soares, A.B., Mesén-Ramírez, P., Jonscher, E., et al. (2017) A genetic system to study Plasmodium falciparum protein function. Nat Methods 14: 450–456.

      Birnbaum, J., Scharf, S., Schmidt, S., Jonscher, E., Hoeijmakers, W.A.M., Flemming, S., et al. (2020) A Kelch13-defined endocytosis pathway mediates artemisinin resistance in malaria parasites. Science (80- ) 367: 51–59.

      Bisio, H., Chaabene, R. Ben, Sabitzki, R., Maco, B., Baptiste Marq, J., Gilberger, T.W., et al. (2020) The zip code of vesicle trafficking in apicomplexa: Sec1/munc18 and snare proteins. MBio 11: 1–21.

      Blum, M., Chang, H.Y., Chuguransky, S., Grego, T., Kandasaamy, S., Mitchell, A., et al. (2021) The InterPro protein families and domains database: 20 years on. Nucleic Acids Res 49: D344–D354.

      Borrmann, S., Straimer, J., Mwai, L., Abdi, A., Rippert, A., Okombo, J., et al. (2013) Genome-wide screen identifies new candidate genes associated with artemisinin susceptibility in Plasmodium falciparum in Kenya. Sci Rep 3.

      Bozdech, Z., Llinás, M., Pulliam, B.L., Wong, E.D., Zhu, J., and DeRisi, J.L. (2003) The transcriptome of the intraerythrocytic developmental cycle of Plasmodium falciparum. PLoS Biol 1: e5.

      Burnette, W.N. (1981) “Western Blotting”: Electrophoretic transfer of proteins from sodium dodecyl sulfate-polyacrylamide gels to unmodified nitrocellulose and radiographic detection with antibody and radioiodinated protein A. Anal Biochem 112: 195–203.

      Casella, J.F., Flanagan, M.D., and Lin, S. (1981) Cytochalasin D inhibits actin polymerization and induces depolymerization of actin filaments formed during platelet shape change. Nature 293: 302–305.

      Cerqueira, G.C., Cheeseman, I.H., Schaffner, S.F., Nair, S., McDew-White, M., Phyo, A.P., et al. (2017) Longitudinal genomic surveillance of Plasmodium falciparum malaria parasites reveals complex genomic architecture of emerging artemisinin resistance. Genome Biol 18: 78.

      Chen, Z., and Schmid, S.L. (2020) Evolving models for assembling and shaping clathrin-coated pits. J Cell Biol 219.

      Dell’Angelica, E.C., Puertollano, R., Mullins, C., Aguilar, R.C., Vargas, J.D., Hartnell, L.M., and Bonifacino, J.S. (2000) GGAs: A family of ADP ribosylation factor-binding proteins related to adaptors and associated with the Golgi complex. J Cell Biol 149: 81–93.

      Demas, A.R., Sharma, A.I., Wong, W., Early, A.M., Redmond, S., Bopp, S., et al. (2018) Mutations in Plasmodium falciparum actin-binding protein coronin confer reduced artemisinin susceptibility. Proc Natl Acad Sci 201812317.

      Henrici, R.C., Edwards, R.L., Zoltner, M., Schalkwyk, D.A. van, Hart, M.N., Mohring, F., et al. (2020a) The plasmodium falciparum artemisinin susceptibility-associated ap-2 adaptin μ subunit is clathrin independent and essential for schizont maturation. MBio 11.

      Henrici, R.C., Schalkwyk, D.A. van, and Sutherland, C.J. (2020b) Modification of pfap2μ and pfubp1 Markedly Reduces Ring-Stage Susceptibility of Plasmodium falciparum to Artemisinin in Vitro. Antimicrob Agents Chemother 64.

      Henriques, G., Hallett, R.L., Beshir, K.B., Gadalla, N.B., Johnson, R.E., Burrow, R., et al. (2014) Directional selection at the pfmdr1, pfcrt, pfubp1, and pfap2mu loci of Plasmodium falciparum in Kenyan children treated with ACT. J Infect Dis 210: 2001–2008.

      Heredero-Bermejo, I., Varberg, J.M., Charvat, R., Jacobs, K., Garbuz, T., Sullivan, W.J., and Arrizabalaga, G. (2019) TgDrpC, an atypical dynamin-related protein in Toxoplasma gondii, is associated with vesicular transport factors and parasite division. Mol Microbiol 111: 46–64.

      Hirst, J., Lui, W.W.Y., Bright, N.A., Totty, N., Seaman, M.N.J., and Robinson, M.S. (2000) A family of proteins with γ-adaptin and VHS domains that facilitate trafficking between the trans-golgi network and the vacuole/lysosome. J Cell Biol 149: 67–79.

      Hirst, J., and Robinson, M.S. (1998) Clathrin and adaptors. Biochim Biophys Acta - Mol Cell Res 1404: 173–193.

      Hoeijmakers, W.A.M., Miao, J., Schmidt, S., Toenhake, C.G., Shrestha, S., Venhuizen, J., et al. (2019) Epigenetic reader complexes of the human malaria parasite, Plasmodium falciparum. Nucleic Acids Res 47: 11574–11588.

      Jonscher, E., Flemming, S., Schmitt, M., Sabitzki, R., Reichard, N., Birnbaum, J., et al. (2019) PfVPS45 Is Required for Host Cell Cytosol Uptake by Malaria Blood Stage Parasites. Cell Host Microbe 25: 166-173.e5.

      Kimmel, J., Schmitt, M., Sinner, A., Jansen, P.W.T.C., Mainye, S., Ramón-Zamorano, G., et al. (2023) Gene-by-gene screen of the unknown proteins encoded on Plasmodium falciparum chromosome 3. Cell Syst 14: 9-23.e7.

      Koreny, L., Mercado-Saavedra, B.N., Klinger, C.M., Barylyuk, K., Butterworth, S., Hirst, J., et al. (2023) Stable endocytic structures navigate the complex pellicle of apicomplexan parasites. Nat Commun 14: 2167.

      Kumari, V., Singh, A.P., Singh, J., Sharma, R., Akhter, M., Mishra, P.K., et al. (2018) Biochemical characterization of unusual cysteine protease of P. falciparum, metacaspase-2 (MCA-2). Mol Biochem Parasitol 220: 28–41.

      Lazarus, M.D., Schneider, T.G., and Taraschi, T.F. (2008) A new model for hemoglobin ingestion and transport by the human malaria parasite Plasmodium falciparum. J Cell Sci 121: 1937–1949.

      Lopez-Hernandez, F.J., Ortiz, M.A., Bayon, Y., and Piedrafita, F.J. (2003) Z-FA-fmk inhibits effector caspases but not initiator caspases 8 and 10, and demonstrates that novel anticancer retinoid-related molecules induce apoptosis via the intrinsic pathway. Mol Cancer Ther 2: 255–263.

      Lord, S.J., Velle, K.B., Mullins, R.D., and Fritz-Laylin, L.K. (2020) SuperPlots: Communicating reproducibility and variability in cell biology. J Cell Biol 219.

      MalariaGEN, Ahouidi, A., Ali, M., Almagro-Garcia, J., Amambua-Ngwa, A., Amaratunga, C., et al. (2021) An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples. Wellcome open Res 6: 42.

      Marti, M., Good, R.T., Rug, M., Knuepfer, E., and Cowman, A.F. (2004) Targeting malaria virulence and remodeling proteins to the host erythrocyte. Science 306: 1930–3.

      Mesén-Ramírez, P., Bergmann, B., Elhabiri, M., Zhu, L., Thien, H. von, Castro-Peña, C., et al. (2021) The parasitophorous vacuole nutrient pore is critical for drug access in malaria parasites and modulates the fitness cost of artemisinin resistance. Cell Host Microbe 0: 283.

      Mesén-Ramírez, P., Bergmann, B., Tran, T.T., Garten, M., Stäcker, J., Naranjo-Prado, I., et al. (2019) EXP1 is critical for nutrient uptake across the parasitophorous vacuole membrane of malaria parasites. PLoS Biol 17: e3000473.

      Mukherjee, A., Crochetière, M.-È., Sergerie, A., Amiar, S., Thompson, L.A., Ebrahimzadeh, Z., et al. (2022) A Phosphoinositide-Binding Protein Acts in the Trafficking Pathway of Hemoglobin in the Malaria Parasite Plasmodium falciparum. MBio 13.

      Otto, T.D., Wilinski, D., Assefa, S., Keane, T.M., Sarry, L.R., Böhme, U., et al. (2010) New insights into the blood-stage transcriptome of Plasmodium falciparum using RNA-Seq. Mol Microbiol 76: 12–24.

      Robinson, M.S., Sahlender, D.A., and Foster, S.D. (2010) Rapid Inactivation of Proteins by Rapamycin-Induced Rerouting to Mitochondria. Dev Cell 18: 324–331.

      Sabitzki, R., Schmitt, M., Flemming, S., Jonscher, E., Hoehn, K., Froehlke, U., and Spielmann, T. (2023) Identification of a Rabenosyn-5 like protein and Rab5b in host cell cytosol uptake reveals conservation of endosomal transport in malaria parasites. bioRxiv 2023.04.05.535711.

      Simwela, N. V., Hughes, K.R., Roberts, A.B., Rennie, M.T., Barrett, M.P., and Waters, A.P. (2020) Experimentally engineered mutations in a ubiquitin hydrolase, UBP-1, modulate in vivo susceptibility to artemisinin and chloroquine in plasmodium berghei. Antimicrob Agents Chemother 64.

      Spielmann, T., Gras, S., Sabitzki, R., and Meissner, M. (2020) Endocytosis in Plasmodium and Toxoplasma Parasites. Trends Parasitol 36: 520–532.

      Subudhi, A.K., O’Donnell, A.J., Ramaprasad, A., Abkallo, H.M., Kaushik, A., Ansari, H.R., et al. (2020) Malaria parasites regulate intra-erythrocytic development duration via serpentine receptor 10 to coordinate with host rhythms. Nat Commun 11.

      Traub, L.M., Downs, M.A., Westrich, J.L., and Fremont, D.H. (1999) Crystal structure of the α appendage of AP-2 reveals a recruitment platform for clathrin-coat assembly. Proc Natl Acad Sci U S A 96: 8907–8912.

      Wagner, M.P., Formaglio, P., Gorgette, O., Dziekan, J.M., Huon, C., Berneburg, I., et al. (2022) Human peroxiredoxin 6 is essential for malaria parasites and provides a host-based drug target. Cell Rep 39: 110923.

      Wall, R.J., Zeeshan, M., Katris, N.J., Limenitakis, R., Rea, E., Stock, J., et al. (2019) Systematic analysis of Plasmodium myosins reveals differential expression, localisation, and function in invasive and proliferative parasite stages. Cell Microbiol 21.

      Wan, W., Dong, H., Lai, D.-H., Yang, J., He, K., Tang, X., et al. (2023) The Toxoplasma micropore mediates endocytosis for selective nutrient salvage from host cell compartments. Nat Commun 14: 977.

      Wichers-Misterek, J.S., Binder, A.M., Mesén-Ramírez, P., Dorner, L.P., Safavi, S., Fuchs, G., et al. (2023) A Microtubule-Associated Protein Is Essential for Malaria Parasite Transmission. MBio .

      Wichers, J.S., Gelder, C. van, Fuchs, G., Ruge, J.M., Pietsch, E., Ferreira, J.L., et al. (2021a) Characterization of Apicomplexan Amino Acid Transporters (ApiATs) in the Malaria Parasite Plasmodium falciparum. mSphere 6.

      Wichers, J.S., Mesén-Ramírez, P., Fuchs, G., Yu-Strzelczyk, J., Stäcker, J., Thien, H. von, et al. (2022) PMRT1, a Plasmodium -Specific Parasite Plasma Membrane Transporter, Is Essential for Asexual and Sexual Blood Stage Development. MBio 13.

      Wichers, J.S., Scholz, J.A.M., Strauss, J., Witt, S., Lill, A., Ehnold, L.-I., et al. (2019) Dissecting the Gene Expression, Localization, Membrane Topology, and Function of the Plasmodium falciparum STEVOR Protein Family. MBio 10: e01500-19.

      Wichers, J.S., Tonkin-Hill, G., Thye, T., Krumkamp, R., Kreuels, B., Strauss, J., et al. (2021b) Common virulence gene expression in adult first-time infected malaria patients and severe cases. Elife 10.

      Wichers, J.S., Wunderlich, J., Heincke, D., Pazicky, S., Strauss, J., Schmitt, M., et al. (2021c) Identification of novel inner membrane complex and apical annuli proteins of the malaria parasite Plasmodium falciparum. Cell Microbiol 23: e13341.

  2. Jun 2023
    1. 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

      Reply to the reviewers

      Manuscript number: RC-2023-01932

      Corresponding author(s): Dennis KAPPEI

      We would like to thank all reviewers for their recognition of our approach and the quality of our work as well as their constructive criticism.

      Reviewer #1

      Reviewer #1: The manuscript by Yong et. al. describes a comparison of various chromatin immunoprecipitation-mass spectrometric (ChIP-MS) methods targeting human telomeres in a variety of systems. By comparing antibody-based methods, crosslinkers, dCas9 and sgRNA targeted methods, KO cells and various controls, they provide a useful perspective for readers interested in similar experiments to explore protein-DNA interactions in a locus-specific manner.

      Response: We would like to thank the reviewer for the feedback and the appreciation of our work.

      Reviewer #1: While interesting, I found it somewhat difficult to extract a clear comparison of the methods from the text. It was also difficult to compare as data and findings from each method was discussed in its own context. Perhaps it is not in their interest to single out a specific method and it is indeed true that there are caveats with each of the methods.

      Response: Across our manuscript we have established one single workflow, for which we present some technical comparisons (e.g. using single or double cross-linking in Fig. 2a/b), technical recommendations such as the use of loss-of-function controls (e.g. Fig. 1c v. Fig. 2a and Extended Data Fig. 3g vs. 3i) and an application to unique loci using dCas9 (Fig. 3f). Based on the suggestions below, we believe that we will improve the clarity of communicating our approach.

      Reviewer #1: I think the manuscript would be of interest but I believe that there are remaining questions that need to be addressed before publication. In particular, I found it difficult to reconcile the discrepancy in protein IDs between most experiments vs. the WT/KO experiment in Fig 2. The authors make a big deal about the importance of the KO control but I think the fewer proteins identified there may be experiment-specific and not general to the KO system. I ask that this be investigated more carefully by the authors in their revisions.

      Response: We thank the reviewer for highlighting this point. We do not think that the ChIP-MS comparison between U2OS WT and ZBTB48 KO clones (Fig. 2a) has experiment-specific caveats. Instead the KO controls as well as the dTAGV-1 degron system for MYB ChIP-MS (Extended Data Fig. 3) reveal antibody-specific off-targets, which are indeed false-positives. Please see below for further details.

      Reviewer #1: Ln 57: What is "standard double cross-linking ChIP reactions" in this context? Is it the two different crosslinkers? The two proteins? The reciprocal IPs of one protein, and blotting for another? It's not clear here or from Extended Fig 1A. Upon further reading, it seems to pertain to the two crosslinkers - if so, the authors should briefly describe their workflow to help readers.

      Response: As the reviewer correctly concludes, we indeed intended to highlight the use of two separate crosslinkers (formaldehyde/FA and DSP). This combination is important as illustrated in the side-by-side comparison of Fig. 2a and Fig. 2d. Here, we performed ZBTB48 ChIP-MS in five U2OS WT and five U2OS ZBTB48 KO clones. While in both experiments the bait protein ZBTB48 was abundantly enriched in the samples that were fixed with formaldehyde we lose about half of the telomeric proteins that are known to directly bind to telomeric DNA independent of ZBTB48 and all of their interaction partners. For instance, while the FA+DSP reaction in Fig. 2a enriched all six shelterin complex members, the FA only reaction in Fig. 2d only enriches TERF2. These data suggest that the use of a second cross-linker helps to stabilise protein complexes on chromatin fragments. This is a critical message of our manuscript as ChIP-MS only truly lives up its name if we can enrich proteins that genuinely sit on the same chromatin fragment without protein interactions to the bait protein. We will expand on this in both the text and our schematics in Fig. 1a and 3a to make this clearer for the readers.

      Reviewer #1: Ln 95: It is surprising and quite unclear to me why it is that the WT ZBTB48 U2OS pulldown in Fig 1B shows 83 hits for the WT vs Ig control experiment but 27 hits for the WT vs KO condition in Fig 2A. The two WT experiments have the same design and reagents, shouldn't they be as close as technical replicates and provide very similar hits?

      The authors seem to make the claim that most of the 'extra' proteins in WT vs Ig are abundant and false positives, but if this is so, shouldn't they bind non-specifically to the beads and be enriched equally in Ig control and ZBTB48 WT IPs?

      Response: We again thank the reviewer for raising this point and the need to explain in more detail why we interpret the difference between 83 hits (anti-ZBTB48 antibody vs. IgG; Fig. 1c) and 27 hits (anti-ZBTB48 antibody used in both U2OS WT and ZBTB48 KO cells; Fig. 2a) primarily as false-positives. The KO controls in Fig. 2a allow to keep the ZBTB48 antibody as a constant variable while instead comparing the presence (WT) or absence (KO) of the bait protein. Hence, proteins that were enriched in the IgG comparison in Fig. 1c but that are lost in the WT vs. KO comparison in Fig. 2a are likely directly (or indirectly) recognised by the ZBTB48 antibody, akin to off-targets to this particular reagent. In a Western blot this would be equivalent to seeing multiple bands at different molecular weights with only the band belonging to the protein-of-interest disappearing in KO cells. To illustrate this we would like to refer to Extended Data Fig. 2, in which we have replotted the exact same data from Fig. 2a. However, in addition we have here highlighted proteins that were enriched in the IgG comparison in Fig. 1c. 46 proteins (in pink) are indeed quantified in the WT vs. KO comparison, but these proteins are found below the cut-offs (and most of them with very poor fold changes and p-values). In contrast to the other several hundred proteins common between both experiments that can be considered common background non-specifically bound to the protein G beads, these 46 proteins represent antibody-specific false-positives.

      The above consideration is not unique to ChIP-MS as illustrated by the Western blot example. We also do not claim novelty on the experimental logic, e.g. pre-CRISPR in 2006 Selbach and Mann demonstrated the usefulness of RNAi controls in immunoprecipitations (IPs) (PMID: 17072306). However, our data suggests that ChIP-MS is particularly vulnerable to this type of false-positives given that the approach requires (double-)cross-linking to sufficiently stabilise true-positives on the same chromatin fragment.

      To supplement the WT vs. ZBTB48 KO comparison, we had included a second experiment in the manuscript that illustrates the same point in even more dramatic fashion. First, KO controls are very clean in principle, but they themselves might come with caveats if e.g. the expression levels between WT and KO samples differ greatly. This might create a situation that the reviewer hinted to, i.e. differential expression of abundant proteins that would proportionally to their expression levels stick to the beads, resulting in “fold enrichments”. The resulting false positives could e.g. be controlled by matched expression proteomes. For ZBTB48 we have previously measured this (PMID: 28500257) and demonstrated that only a small number of genes are differentially expressed (~10) and hence we can interpret the WT vs. ZBTB48 KO comparison quite cleanly. However, for other classes of proteins such as transcription factors that regulate a large number of genes, E3 ligases etc. this might present a more serious concern. Therefore, we extended our loss-of-function comparison to such a transcription factor, MYB, by using the dTAGV-1 degron system. Importantly, the MYB antibody has been used in previous work for ChIP-seq applications (e.g. PMID: 25394790). Here, instead of 186 hits in the MYB vs. IgG comparison using the same MYB antibody in control-treated and dTAGV-1-treated cells (upon 30 min of treatment only) we only detect 9 hits. Again, similar to the WT vs. ZBTB48 KO comparison, 180 proteins are quantified in the DMSO vs. dTAGV-1 comparison, but these proteins fall below the cut-offs (Extended Data Fig. 3g vs. 3i). Again, we believe that this quite drastically illustrates how vulnerable ChIP-MS data is to large numbers of false-positives. This is not only a technical consideration as such datasets are frequently used in downstream pathway/gene set enrichment analyses etc. Such large false discovery rates would obviously lead to error-carry-forward and additional (unintended) misinterpretations. We will carefully expand our textual description across the manuscript to make these points much clearer. In addition, we will move the previous Extended Data Fig. 3 into the main manuscript to more clearly highlight this important point.

      Reviewer #1: Volcano plots in Figs 1, 2, and Suppl. Tables etc: Are the plotted points the mean of 5 replicates? Was each run normalized between the replicates in each group, for e.g. by median normalization of the log2 MS intensities? This does not appear to be the case upon inspection of the Suppl Tables. Given the variability in pulldown efficiency, gel digest and peptide recovery, this would certainly be necessary.

      Response: All volcano plots are indeed based on 4-5 biological replicates (most stringently in the WT vs. KO comparisons in Fig. 2 based on each 5 independent WT and ZBTB48 KO single cell clones). The x-axis of each volcano plot represents the ratio of mean MS1-based intensities between both experimental conditions in log2 scale. However, precisely to account for the variation that the reviewer highlighted we did not base our analysis on raw MS1 intensities but we used the MaxLFQ algorithm (PMID: 24942700) as part of the MaxQuant analysis software (PMID: 19029910) for genuine label-free quantitation across experimental conditions and replicates. In this context, we would also like to refer to a related comment by reviewer #2 based on which we will now addd concordance information for each replicate (heatmaps for Pearson correlations and PCA plots). We will improve this both in the text and methods section accordingly.

      Reviewer #1: Ln 125: The authors make the claim that the ChIP-MS experiments are inherently noisy, with examples from WT cells, dTAG system and IgG controls. This is likely the case, yet their experiments with WT vs KO cells do not identify as many proteins overall. I find this inconsistency somewhat unclear and does not seem to match the claim of ChIP-MS experiments and crosslinking adding to non-specificity. Can the authors add the total number of identified proteins in each volcano plot, for easier reference?

      Response: The number of identified proteins does not vary majorly between matched IgG and loss-of-function comparisons and for instance the single cross-linking (FA only) experiment in Fig. 2c has the largest number of quantified proteins among all ZBTB48 IPs. But we will of course add the requested information to all plots.

      Reviewer #1: I think the manuscript is interest as it provides important benchmarks for ChIP-proteomics experiments. I believe that there are remaining questions that need to be addressed before publication. In particular, I found it difficult to reconcile the discrepancy in protein IDs between most experiments vs. the WT/KO experiment in Fig 2. The authors make a big deal about the importance of the KO control but I think the fewer proteins identified there may be experiment-specific and not general to the KO system. I ask that this be investigated more carefully by the authors in their revisions.

      Response: We would like to thank the reviewer for recognising our work as a source for important benchmarks for ChIP-MS experiments. We hope that with a more detailed description and discussion the highlighted aspects will be more clearly communicated. We originally conceived our manuscript as a short report and now realised that some of the information became too condensed and might therefore benefit from more extensive explanations.

      Reviewer #2

      Reviewer #2: Summary: In this manuscript, Yong and colleagues have introduced a optimized technique for studying actors on chromatin in specific regions with a localized approach thanks to revisited ChIP-mass spectrometry (MS) with label-free quantitative (LFQ). The authors exhibited the utility of their approach by demonstrating its effectiveness at telomeres from cell culture (human U2OS cells) to tissue samples (liver, mouse embryonic stem cells). As a proof of concept, this technique was tested by the authors with proteins from complex shelterin specific to telomeres (TERF2 and ZBTB48), transcription factors (MYB), and through dCas9-driven locus-specific enrichment. Notably, the authors created a U2OS dCas9-GFP clone and then introduced sgRNAs to target either telomeric DNA (sgTELO) or an unrelated control (sgGAL4). The cells expressing sgTELO exhibited a significant localization of telomeres and an enriched amount of telomeric DNA in ChIP with dCas9. They also found the proteins previously identified as known to be enriched at telomeres (for example, the 6 shelterin members).

      Moreover, the authors illustrated the importance of double crosslinking (formaldehyde (FA) and dithiobis(succinimidyl propionate) (DSP) in ChIP-MS. Their data demonstrated also that ChIP-MS is inclined towards false-positives, possibly owing to its inherent cross-linking. However, by utilizing loss-of-function conditions specific to the bait, it can be tightly managed.

      • Can you show the concordance between biological replicates for each ChIP with LFQ? (heatmap of Pearson correlation and PCA plot). This will confirm the robustness of the use of LFQ.

      Response: We will add the requested concordance data for all volcano plots both in the form of heatmaps of Pearson correlation and PCA plots. Across our datasets, the replicates from the same experimental condition clearly cluster with each other and replicates have high concordance values of >0.9. As expected replicates for the target/bait samples have slightly higher concordance values compared to the negative controls (IgG or loss-of-function samples). We thank the reviewer for this suggestion as the new Extended Data panel will strengthen the illustration of our robust LFQ data.

      Reviewer #2: You say that your technique is " a simple, robust ChIP-MS workflow based on comparably low input quantities » (line 139). What would be really interesting for a technical paper would be: a schematic and a table illustrating the differences between your method and the previously published methods (amount of material, timeline,...) to really highlight the novelty in your optimized techniques.

      Response: We will add a comparison table with previous publications using ChIP-MS and for reference include some complementary approaches as requested by reviewer #3. On this note, we would like to stress that we are not “only” intending to use less material and to have an easy-to-adopt protocol. A cornerstone of our manuscript is to apply rigorous expectations to ChIP-MS experiments, in particular the ability to enrich proteins that independently bind to the same chromatin fragments as the bait protein (regardless of whether this is an endogenous protein or a exogenous, targeted bait such as dCas9). Otherwise, such experiments risk to be regular protein IPs under cross-linking conditions, which as illustrated by our loss-of-function comparisons are prone to yield particularly large fractions of false-positives.

      Reviewer #2: It would be interesting to perform the dCas9 ChIP experiment in telomeric regions with and without LFQ. Since the novelty lies in this parameter, at no time does the paper show that LFQ really allows to have as many or more proteins identified but in a simpler way and with less material. A table allowing to compare with and without LFQ would be interesting.

      Response: We do not fully understand what the suggestion “without LFQ” refers to exactly. We assume that this reviewer might suggest to use a different quantitative mass spectrometry approach other than LFQ, e.g. SILAC labelling, TMT labelling etc. Please note that we do not claim that LFQ quantification is per se superior to the various quantification methods that had been developed and widely used across the proteomics community especially before instrument setups and analysis pipelines were stable enough for label-free quantification (a name that is strongly owed to this historic order of development). However, a central goal of our workflow is to make robust and rigorous ChIP-MS accessible to the myriad of laboratories using ChIP-qPCR/-seq and that may not be extensively specialised in mass spectrometry. Both metabolic and isobaric labelling come not only at a higher cost but also present an experimental hurdle to non-specialists compared to performing biological replicates without any labelling, essentially the same way as for any ChIP-qPCR etc. experiment. We will further elaborate on these points in the manuscript to more clearly convey these notions.

      In general, with the right effort different quantitative methods should and will likely yield qualitatively similar results. However, comparisons between LFQ approaches (MaxLFQ, iBAQ,…) and labelling approaches (SILAC, TMT, iTRAQ) have already been better explored and verbalised elsewhere (e.g. PMID: 31814417 & 29535314). Therefore, we believe that this will add relatively little value to our manuscript.

      Reviewer #2: Put a sentence to explain "label free quantification". For a reader who is not at all familiar with this technique, it would be interesting to explain it and to quote the advantages compared to PLEX.

      Response: Thanks for highlighting this. In line with the point above as well as a similar comment by reviewer #1 we will improve this both in the main text and manuscript to clearly explain the terminology, the MaxLFQ algorithm (PMID: 24942700) used and to highlight the advantages compared to labelling approaches.

      Reviewer #2: what does the ranking on the right of each volcano plot represent (figure 1 b-e, figure 2a,d,e for example)? top of the most enriched proteins in the mentioned categories? Not very clear when we look on the volcano plot. it must be specified in the legend.

      Response: The numbering these panels is meant to link protein names to the data points on the volcano plots. The order of hits is ranked based on strongest fold enrichment, i.e. from right to center. We will clarify this in the figure legends.

      Reviewer #2: General assessment/Advance: The authors explain in their article that the ChIP exploiting the sequence specificity of nuclease-dead Cas9 (dCas9) to target specific chromatin loci by directly enriching for dCas9 was already published. Here, the novelty of this study lies in the use of LFQ mass spectrometry to optimize the technique and make it easier to handle. Some comparisons with previous papers or data generated by the lab will be interesting to really show the improvement and the advantage to use LFQ and therefore, to highlight better the novelty of the study.

      Response: We thank the reviewer for this assessment and as mentioned above we will include such a comparison table. dCas9 has been used previously in a ChIP-MS approach termed CAPTURE (PMID: 28841410). While this is clearly a landmark paper that illustrated the dCas9 enrichment concept across multiple omics applications (i.e. not limited to proteomics) in their application to telomeres, the authors enriched only 3 out of the 6 shelterin proteins with quite moderate fold enrichments (POT1: 0.99, TERF2: 2.13, TERF2IP: 1.06; in log2 scale). Based on this alone, POT1 and TERF2IP would not have qualified for our cut-off criteria. In addition, while the authors had performed three replicates, detection is only reported in 1-2 out of 3 replicates. While it is difficult to reconstruct statistical values based on the publicly accessible data, it is therefore unlikely that even these 3 proteins would have robustly be considered hits in our datasets. Similarly, using recombinant dCas9 with a sgRNA targeting telomeres that was in vitro reconstituted with sonicated chromatin extracts from 500 million HeLa cells (CLASP; PMID: 29507191) the authors identified only up to 3 shelterin subunits (TERF2, TERF2IP and TPP1/ACD) based on 1 unique peptide each only. For comparison, in our dCas9 ChIP-MS dataset all 6 shelterin subunits are identified with 9-19 unique peptides, contributing to our robust quantification. Even when considering cell line-specific differences (HeLa cells have shorter telomeres and hence provide less biochemical material for enrichment per cell), these comparisons illustrate that prior attempts struggled to robustly replicate even the most abundant telomeric complex members.

      Based on these findings, others had suggested that dCas9 “might exclude some relevant proteins from telomeres in vivo” (PMID: 32152500), implying that dCas9 ChIP-MS might inherently not be feasible including at repetitive regions such as telomeres. Therefore, we believe that our dCas9 ChIP-MS data is a proof-of-concept that the method has the genuine ability to robustly enrich key proteins at individual loci. In concordance with the comment above we will include a comparison table with previous papers and expand on these points in the discussion.

      Reviewer #2: By presenting this technical paper, the authors allow laboratories across different fields to use this technique to gain insights into protein enrichment in specific chromatin regions such as the promoter of a gene of interest or a particular open region in ATACseq in a easier way and with less materials. This paper holds value in enabling researchers to answer many pertinent questions in various fields.

      Response: We again thank the reviewer for this encouraging assessment and we do indeed hope that this manuscript makes a contribution to a much wider use of ChIP-MS approaches as a promising complement to existing genome-wide epigenetics analyses.

      Reviewer #3

      Reviewer #3: Strengths of the study:

      The study is well-structured and provides a robust workflow for the application of ChIP-MS to investigate chromatin composition in various contexts.

      The use of telomeres as a model locus for testing the developed ChIP-MS approach is appropriate due to its well-characterized protein composition.

      The comparison of WT vs KO lines for ZBTB48 is a rigorous way to control for false-positives, providing more confidence in the results.

      The direct comparison of double vs only FA-crosslinking provides valuable insights into the benefit of additional protein-protein crosslinking in ChIP-MS workflows.

      Response: We thank the reviewer for this assessment and we agree that the above are several of the key features of our manuscript.

      Reviewer #3: Areas for improvement: The novelty of the method is more than questionable as both ChIP-MS coupled to LFQ and dCas9 usage for locus-specific proteomics have been previously reported. The fact that the authors directly pulldown dCas9 instead of using a dCas9-fused biotin ligase and subsequent streptavidin pulldown is only a very minor change to previous methods (not even improvement). It would be more accurate for the authors to present their study as an optimization and rigorous validation of existing techniques rather than a novel approach.

      Response: While we appreciate where the reviewer is coming from, it occurs to us that most of the reviewer’s comments equate ChIP approaches with other complementary methods, in particular proximity labelling. The latter is indeed a powerful experimental strategy and in fact we are ourselves avid users. As highlighted to reviewer #1 as well, our manuscript was originally conceived as a shorter report and based on the feedback we will now expand our discussion to more broadly incorporate related approaches.

      However, we would like to stress that dCas9 ChIP-MS and dCas9-biotin ligase fusions are not the same thing and this is not a minor tweak to an existing protocol. While both approaches have converging aims – to identify proteins that associate with individual genomic loci – the experimental workflows differ fundamentally. Biotin ligases use a “tag and run” approach by promiscuously leaving a biotin tag on encountered proteins. Subsequently, cellular proteins are extracted and in fact proteins can even be denatured prior to enrichment with streptavidin beads. While this is an in vivo workflow that (depending on the biotin ligase used) may provide sensitivity advantages, it does not retain complex information. The latter is inherently part of ChIP workflows due to the use of cross-linkers. One obvious future application would be to maintain (= not to reverse as we have done here) the crosslink during the mass spectrometry sample preparation in order to read out cross-linked peptides to gain insights into interactions and structural features. We will now more clearly incorporate such notions into our discussion.

      In addition, we would like to stress that while this reviewer focuses primarily on the dCas9 aspect of our manuscript, we believe that our general ChIP-MS workflow including the combination with label-free quantitation is useful and important already by itself as e.g. recognised by both reviewers #1 and #2.

      Reviewer #3: The authors should more thoroughly discuss previous works using ChIP-MS and dCas9 for locus-specific proteomics. This would give readers a better understanding of how the current work builds on and improves these earlier methods. For a paper that aims on presenting an optimized ChIP-MS workflow it is crucial to showcase in which use cases it outperforms previously published methods.

      E.g., compare locus-specific dCas9 ChIP-MS to CasID (doi.org/10.1080/19491034.2016.1239000) and C-Berst (doi.org/10.1038/s41592- 018-0006-2); how does your method perform in comparison to these?

      Response: Again, while we will now incorporate more extensively comparisons with previous ChIP-MS publications (and the few prior manuscripts that included dCas9) as well as related techniques, we would like to stress that dCas9 ChIP-MS is not the same approach as CasID and C-BERST, which rely on dCas9 fusions to BirA* and APEX2, respectively. dCas9-APEX2 strategies were also published by two additional groups as CASPEX (back-to-back with the C-BERST manuscript; PMID: 29735997) and CAPLOCUS (PMID: 30805613). All of these methods target specific loci with dCas9 and promiscuously biotinylate proteins that are in proximity to the dCas9-biotin ligase fusion protein. As described above, while the application of the BioID principle (PMID: 22412018) to chromatin regions has converging aims with the dCas9 ChIP-MS part of our manuscript, they do not test the same. ChIP carries chromatin complexes through the entire workflow while the CasID approaches are independent of that. This is the same scenario if we were to compare IP-MS reactions (such as the ChIP-MS reactions presented here for endogenous proteins) and BioID-type experiments for proximity partners of the same bait proteins.

      Reviewer #3: Compare likewise the described protein interactomes to previously published interactomes.

      Response: We will add comparisons in form of Venn diagrams with previously published interactomes. However, we would like to stress that a key aspect of our manuscript is the smaller yet rigorous hit lists based on e.g. loss-of-function controls, higher stringencies and specificity. Simply comparing final interactomes remains reductionist relative to the importance of other variables such as experimental design, number of replicates, data analysis etc.

      Reviewer #3: The authors use sgGAL4 as a control for the telomeric targeting of dCas9. The IF results (Fig3b) show that sgGAL4 barely localizes to the nucleus with very faint signals. It would be helpful to use a control with homogenous nuclear localization of dCas9 to further strengthen the author's conclusions.

      Response: dCas9-EGFP in the presence of sgGAL4 localises diffusely to the nucleus as expected. We have here used a very widely used non-targeting sgRNA control that has been originally used for imaging purposes (PMID: 24360272) and has since been used in a variety of studies (e.g. PMID: 26082495, 32540968, 28427715) including a previous dCas9 ChIP-MS attempt (PMID: 28841410). In addition, to the diffuse nuclear, non-telomeric localisation we provide complementary validation of clean enrichment of telomeric DNA specifically in the sgTELO samples. Therefore, we do not see how other non-targeting sgRNAs would provide for better controls or improve our data.

      Reviewer #3: The extrapolation of results from the use of telomeres as a proof-of-concept to other loci is not a given considering the highly repetitive structure of telomeric DNA. The authors should either be more cautious about generalizing the results to other loci or demonstrate that their method can also capture locus-specific interactomes at non-repetitive regions.

      Response: We agree that the adoption of any locus-specific approach to single genomic loci is a steep additional hurdle and warrants rigorous data on well characterised loci with very clear positive controls. We will expand on these challenges in our discussion. However, we would like to stress that we did not make any such statement in our original manuscript apart from simply referring to our telomeric experiment as proof-of-concept evidence that locus-specific approaches are feasible by ChIP.

      Reviewer #3: What are concrete biological insights from this optimized ChIP-MS workflow that previous methods failed to show?

      Response: We explicitly used telomeres as an extensively studied locus with clear positive controls that at the same time allows us to evaluate likely false positives. As such the intention of the manuscript was not to yield concrete biological insights but to develop a new methodological workflow.

      As also highlighted in a response to reviewer #2, based on other prior attempts to enrich telomers in ChIP-like approaches with dCas9 (PMID: 28841410 & 29507191), it had been suggested that dCas9 “might exclude some relevant proteins from telomeres in vivo” (PMID: 32152500), implying that dCas9 ChIP-MS might inherently not be feasible including at repetitive regions such as telomeres. Therefore, recapitulating the set of well-described telomeric proteins was no trivial feat and our ChIP-MS workflow (both targeted and applied to individual proteins) represents a well-validated method to in the future systematically interrogate changes in chromatin composition. As one example at telomeres, this may include chromatin changes upon the induction of telomeric fusions or general DNA damage.

      Reviewer #3: For instance, the authors could compare their mouse and human TERF2 interactomes and discuss similarities and differences between both species.

      Response: We thank the reviewer for this suggestion, but the comparison between mouse and human TERF2 interactomes is not suitable across the datasets that we generated. U2OS is a human osteosarcoma cell line that relies on the Alternative Lengthening of Telomeres (ALT) pathway while our mouse data is based on embryonic stem cells (mESCs) and mouse liver tissue. Even the latter, in contrast to adult human tissue, expresses telomerase. We can certainly still pinpoint (as already done in our original manuscript) individual differences among known factors, e.g. the fact that proteins such as NR2C2 are more abundantly found at ALT telomeres (PMID: 19135898, 23229897, 25723166) vs. the detection of the CST complex as telomerase terminator (PMID: 22763445) in the mouse samples. However, the TERF2 datasets contain hundreds of proteins as “hits” above our cut-offs and a key message of our manuscript is that the majority of them are likely false positives. Here, differences are likely extending to expression differences between U2OS cells, mESCs and liver samples. So while appealing in theory, this cross data set comparison would remain rather superficial and error prone at this point. As a biology focused follow-up study, this would need to be rigorously conceived based on an appropriate choice of human and murine cell line models. In addition, this would likely require the generation of FKBP12-TERF2 knock-in fusion clones to allow for rapid depletion of TERF2 for a clean loss-of-function control since sustained loss of TERF2 leads to chromosomal fusions and eventually cell death in most cell types.

      Reviewer #3: The authors should also describe which interaction partners are novel and try to validate some of these using orthogonal methods.

      Response: We will now highlight more explicitly two proteins, POGZ and UBTF, that are most robustly and reproducibly enriched on telomeric chromatin across datasets, including the U2OS WT vs. ZBTB48 KO comparison (Fig. 2a). However, we would like to abstain from a molecular characterization at this point. As mentioned above, the discovery of novel telomeric proteins is not the focus of this manuscript, which is primarily dedicated to method development. In addition, these type of validations in methods papers are often limited to a few assays (e.g. can 1 or 2 proteins be enriched by ChIP? Do you see some localisation by IF? etc.). However, our research group has a history of publishing in-depth mechanistic papers on the characterisation of novel telomeric proteins (e.g. PMID: 23685356, 28500257, 20639181, doi.org/10.1101/2022.11.30.518500). Therefore, a genuine validation of such factors would require functional insights and clearly warrants independent follow-up work.

      Reviewer #3: Human Terf2 ChIP-MS (Fig1A) seems to be much more specific than the mouse counterpart (Fig1D) (32 TERF2 interactors out of 176 hits in human vs 12 TERF2 interactors out of 500 hits in mouse). Could the authors explain this notable difference?

      Response: As eluded to above, Fig. 1A and 1D cannot be directly compared, starting with the difference in complexity in the input material – cell line vs. tissue. For comparison, the Terf2 ChIP-MS data from mouse embryonic stem cells tallies up to 19 out of 169 hits, which is much closer to the U2OS results. Again, we deem the majority of hits from the TERF2 ChIP-MS data to be false-positives and the more complex input material from mouse livers likely accounts for the difference in these numbers.

      Reviewer #3: The authors used much higher cell numbers than previously published ChIP-MS experiments; while this is understandable for dCas9-based pulldowns, the cell number is expected to be down-scalable for the other IPs (TERF2, ZBTB48, MYB). Since this work primarily describes an optimized Chip-MS workflow, the authors should show that they can reasonably downscale to at least 15 Mio cells per replicate; one way of achieving this could be through digesting on the beads and not in-gel.

      Response: As we will illustrate in the comparison table that was also requested by reviewer 2, our approach does not use higher cell numbers than previous ChIP-MS approaches – quite the contrary. In addition, we would like to highlight that while we state 50 million cells in Fig. 1a, we only inject 50% of our samples for MS analysis to retain a back-up sample in case of technical issues with the instruments. In other words, our workflow is already effectively based on 25 million cells and thereby pretty close to the requested 15 million cells while simultaneously requiring substantially less reagents.

      Importantly, our examples are based on rather lowly expressed bait proteins such as ZBTB48 (not detected within DDA-based proteomes of ~10,000 proteins in U2OS cells). While the workflow can be applied across proteins, exact input numbers might vary depending on the bait protein, e.g. histones and its modifications would likely require less for the same absolute sample enrichment. For instance, PMID 25990348 and 25755260 performed ChIP-MS on common histone modifications but still used 300-800 million cells per replicate. Considering that we worked on substantially less abundant proteins, we here present a workflow with comparably low input samples.

      Reviewer #3: It is not clear from the text or figure what the authors are trying to show in Fig2c. They should either explain this further or take the figure out.

      Response: We are trying to illustrate the following: As in any IP reaction the bait protein is the most enriched protein with very high relative intensities, e.g. TERF2 in the TERF2 ChIP-MS data. Direct protein interaction partners – here the other shelterin members – follow at about 1 order of magnitude lower signal intensities. In contrast, proteins that are enriched via an interaction with the same DNA molecule (i.e. that do not physically interact with the bait protein) such as NR2C2, HMBOX1 and ZBTB48 further trail by at least 1 more order of magnitude. These are information that are not easily visualised within the volcano plots and mainly “buried” within the Supplementary Tables. However, these relative intensities displayed in Fig. 2c clearly illustrate the dynamic range challenge that ChIP-MS poses for proteins that independently bind to the same chromatin fragment. We have now modified our text to make this point more clear.

      Reviewer #3: Was there any benefit in using a Q Exactive HF vs timsTOF flex?

      Response: Yes, measuring the same samples (e.g. the 50% backup mentioned above) on both instruments enriches more telomeric proteins/shelterin proteins in e.g. the dCas9 ChIP-MS data set on the timsTOF fleX. However, given the difference in age of these instruments/technologies between a Q Exactive HF and a timsTOF fleX (in the context of these experiments the equivalent of a timsTOF Pro 2), this is not a fair comparison beyond concluding that a more recent instrument like the timsTOF fleX achieves better coverage and is more sensitive with otherwise comparable measurement parameters. As we did not have the opportunity to run matched samples on e.g. an Exploris 480, we would not want to make claims across vendors. As stated in the discussion we are expecting that even newer generation of mass spectrometers, such as the very recently released Orbitrap Astral or timsTOF Ultra would further improve the sensitivity and/or allow to reduce the amount of input material. Therefore, the main conclusion is that improvements in the mass spec generations improve proteomics data quality and our samples are no exception, i.e. this is not specifically pertinent to our approach.

      Reviewer #3: How did the authors analyze the PTM data? This is not described in the methods section. In addition, it would be important to validate the novel PTMs described for NR2C2.

      Response: We apologise for the oversight and we will add the description of PTMs as variable modifications during our MaxQuant search in the methods section. The originally deposited datasets already include this and we had simply missed this in our methods text.

      While we are not 100% sure to understand the request for validation correctly, we would like to point out that the PTMs on NR2C2 have been previously reported in several high-throughput datasets and for S19 in functional work on NR2C2 (PMID: 16887930). However, the relevance in our data set is as follows: While the PTMs on TERF2 as the bait protein could occur both on telomere-bound TERF2 as well as on nucleoplasmic TERF2, NR2C2 is only enriched in the TERF2 ChIP-MS reactions due to its direct interaction with telomeric DNA. The co-detection of its modifications therefore implies that at least some of the telomere-bound NR2C2 carries these modifications. We showcase this example as an additional angle of how such ChIP-MS datasets can be analysed.

      While the robust, MS2-based detection of these modified peptides in our data set and several other publicly available datasets provides strong evidence that these modifications are genuine, further functional validation would involve rather labour-intensive experiments and resource generation (e.g. phospho-site specific antibodies). We hope that the reviewer agrees with us that this would require an independent follow-up study and that this goes beyond the scope of our current manuscript.

      Reviewer #3: For this kind of methods paper one would expect to see the shearing results of the ChIP-MS experiments since variations in DNA shearing can impact the detection of false-positives in the ChIP-MS experiments

      Response: We will include agarose gel pictures of our sonicates, which we indeed routinely quality controlled prior to ChIP experiments as stated in our methods description.

      Reviewer #3: Overall, the current state of the manuscript neither provides direct evidence that the "optimized" ChIP-MS workflow is better in certain aspects/use cases than previously published methods nor does it provide novel biological insights. At the current state it even cannot be considered as a validation of previously published methods since it does not discuss them.

      Response: We politely disagree with this conclusion. Again, as mentioned above we are under the impression that this reviewer somehow equates our entire manuscript to a comparison with dCas9-biotin ligase fusions.

      Instead, we here provide a workflow for ChIP-MS that incorporates label-free quantification as the experimentally easiest, most intuitive quantification method for non-mass spectrometry experts. This offers a particularly low barrier to entry aimed at making ChIP-MS more widely accessible as a complement to commonly used ChIP-seq applications. Furthermore, we showcase that as a gold standard ChIP-MS – to truly live up to its name – should have the ability to enrich proteins independently binding to the same chromatin fragment. We demonstrated that double cross-linking is critical for these assays and in return illustrate how rigorous loss-of-function controls (both KOs and degron systems) can mitigate prevalent false-positives that are exacerbated due to the cross-linking. Finally, we applied this workflow to different types of endogenous proteins (transcription factors, telomeric proteins) in cell lines and tissue and extend our work to dCas9 ChIP-MS as a targeted method.

  3. May 2023
    1. 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 comments and constructive suggestions to improve the manuscript. We are encouraged to see that both reviewers acknowledge how the results from our manuscript uses state-of-art technologies to advance molecular underpinnings of centriole length, integrity and function regulation. Both reviewers also highlighted that the manuscript is well laid out and presents clear, rigorous, and convincing data. Reviewer#1 described our manuscript of highest experimental quality and broad interest to the field of centrosome and cell biology form a basic research and genetics/clinical point of view. Here, we explain the revisions, additional experimentations and analyses planned to address the points raised by the referees. We will perform most of the experimentations and corrections requested by the reviewers. We have already made several revisions and are currently working on additional experiments.

      Our responses to each reviewer comment in bold are listed below. References mentioned here are listed in the references section included at the of this document.

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

      Summary: __In this manuscript, Arslanhan and colleagues use proximity proteomics to identify CCDC15 as a new centriolar protein that co-localizes and interacts with known inner scaffold proteins in cell culture-based systems. Functional characterization using state-of-the-art expansion microscopy techniques reveals defects in centriole length and integrity. The authors further reveal intriguing aberrations in the recruitment of other centriole inner scaffold proteins, such as POC1B and the SFI1/centrin complex, in CCDC15-deficient cells, and observe defects in primary cilia. __

      We thank the reviewer for the accurate summary of the major conclusions of our manuscript.

      Major points:

      1) The authors present a high-quality manuscript that identifies a novel centriolar protein by elegantly revealing and comparing the proximity proteomes of two known centriolar proteins, which represents an important component for the maintenance of centrioles.

      We thank the reviewer for highlighting that our manuscript is of high quality and presents important advances for the field.

      __2) Data are often presented from two independent experiments (n = 2), which is nice, but also the minimum for experiments in biology. It is strongly recommended to perform at least three independent experiments. __

      We agree with the reviewer that analysis of data form three experimental replicates is ideal for statistical analysis. We performed three replicates for the majority of experiments in the manuscript. However, as the reviewer pointed out, we included analysis from two experiments for the following figures:

      • Fig. 4H: quantification of CCDC15 total cellular levels throughout the cell cycle by western blotting
      • Fig. 5A: CCDC15-positive centrioles in control and CCDC15 siRNA-transfected cells
      • Fig. 6B: % centriolar coverage of POC5, FAM161A, POC1B and Centrin-2 in control and CCDC15 siRNA-transfected cells
      • Fig. 6C, 6E: Centrin-2 or SFI1-positive centrioles in control and CCDC15 siRNA-transfected cells
      • Fig. 6J, K: normalized tubulin length and percentage of defective centrioles in cells depleted for CCDC15 or co-depleted for CCDC15 and POC1B
      • Fig. 7F, H: SMO-positive cilia and basal body IFT88 levels in control and CCDC15 siRNA-transfected cells
      • Fig. S3H: centriole amplification in HU-treated control and CCDC15 siRNA-transfected cells (no)
      • Fig. S3A: centrosomal levels upon CCDC15 depletion There are two reasons for why we performed two experimental replicates for these experiments: 1) results from the two experimental replicates were similar, 2) quantification of data by U-ExM is laborious. To address the reviewer’s comments, we will perform the third experimental replicate for the sets of data that led to major conclusions of our manuscript, which are Figures 4H, 6C, 6E, 6J, 6K, 7F, 7H and S3A.

      3) The protein interaction studies presented in Fig. 3 could be of higher quality. While it is great that the authors compared interactions to the centriolar protein SAS6, which is not expected to interact with CCDC15, the presented data raise many questions.

      __a) In most cases, co-expression of tagged CCDC15 stabilizes the tested interaction partners, such that the overall abundance seems to be higher. The increase in protein abundance is substantial for Flag-FAM161A (Fig. 3D) and GFP-Centrin-2 (Fig. 3E) and is even higher for the non-interactor SAS6 (Fig. 3G), while it cannot be assessed for GFP-POC1B (Fig. 3F). Hence, the higher expression levels under these conditions make it more likely that these proteins are "pulled down" and therefore do not represent appropriate controls. __

      We agree with the reviewer that the differences in protein abundance of the prey proteins upon expression of CCDC15 relative to control might impact the interpretation of the interaction data. To address this concern, we will perform the following experiments:

      • To account of the potential stabilizing effects of CCDC15 expression, we will change the relative ratio of plasmids expressing proteins of interest and assess the expression of bait and prey protein levels. We will then repeat the co-immunoprecipitation experiments in conditions where prey expression levels are similar.
      • To avoid the potential stabilizing effects of CCDC15 overexpression, we will perform immunoprecipitation experiments in cells expressing GFP or V5-tagged inner scaffold proteins and assess their potential physical or proximity interaction by blotting for endogenous CCDC15. __b) All Co-IP experiments are lacking negative controls in the form of proteins that are not pulled down under the presented conditions. __

      For the co-IP experiments, we only included a specificity control for the interaction of the bait protein with the tag of the prey protein (i.e. GBP pulldown of GFP or GFP-CCDC15-expressing cells). As the reviewer suggested, we will also include a specificity control for the interaction of bait with the tag of the prey protein for co-immunoprecipitation experiments (i.e. GFP pulldown of cells expressing GFP-CCDC15 with V5-BirA* or V5-BirA*-FAM161A).

      __c) The amounts of co-precipitation of the tested proteins appears very different. Could this reflect strong or weak interactors, or does it reflect the abundance of the respective proteins in centrioles? __

      We agree with the reviewer that the quantity of the co-precipitated prey proteins might be a proxy for the interaction strength if the abundance of the bait proteins is similar. However, the expression levels of bait and prey proteins in co-transfected cells are different and thus, cannot be used to derive a conclusion on the interaction strength. For the revised manuscript, we will repeat the IP experiments and comment on this in the discussion section.

      __4) The observation that IFT88 is supposedly decreased at the base of cilia in CCDC15-depleted cells requires additional experiments/evidence. Fig. 7G shows the results of n = 2 and more importantly, a similar reduction of gamma-tubulin in siCCDC15. Could the observed reduction in IFT88 be explained by a decrease in accessibility to immunofluorescence microscopy? Would the reduction in IFT88 at the base also be apparent when the signals were normalized to gamma-tubulin signals? __

      To address the reviewer’s concern, we quantified the basal body gamma-tubulin and IFT88 levels in control and CCDC15-depleted cells and plotted the basal body IFT88 levels normalized to gamma-tubulin levels in Fig. 7H. Similar to the reduction in IFT88 levels, gamma-tubulin-normalized IFT88 levels was significantly less relative to control cells. Moreover, the gamma-tubulin basal body levels were similar between control and CCDC15 cells. We revised the gamma-tubulin micrographs in Fig. 7G to represent this. These results indicate that the reduction in basal body IFT88 levels upon CCDC15 depletion in specific.

      __5) The observed Hedgehog signaling defects are described as follows: "CCDC15 depletion significantly decreased the percentage of SMO-positive cells". It is similarly described in the figure legend. If this was true, the simplest explanation would be that it reflects the reduction in ciliation rate (which is in a similar range). If SMO-positive cilia (instead of "cells") were determined, the text needs to be changed accordingly. __

      As the reviewer pointed out, we quantified SMO-positive cilia, but not cells. We are sorry for this typo. We corrected SMO-positive cells as SMO-positive cilia in the manuscript text, Fig. 7 and figure legends.

      __6) OPTIONAL: While expansion microscopy is slowly becoming one of the standard super-resolution microscopy methods, which is particularly well validated for studying centrioles, the authors should consider confirming part of their findings (as a proof of principle, surely not in all instances) by more established techniques. This could serve to convince critical reviewers that may argue that the expansion process may induce architectural defects of destabilized centrioles, as observed after disruptions of components, such as in Fig. 6. Alternatively, the authors could cite additional work that make strong cases about the suitability of expansion microscopy for their studies, ideally with comparisons to other methods. __

      • SIM imaging was previously successfully applied for nanoscale mapping of other centriole proteins including CEP44, MDM1 and PPP1R35 (Atorino et al., 2020; Sydor et al., 2018; Van de Mark et al., 2015). To complement the U-ExM analysis, we have started imaging cells stained for CCDC15 and different centriole markers (i.e. distal appendage, proximal linker, centriole wall) using a recently purchased 3D-SIM superresolution microscope. We already included the SIM imaging data for CCDC15 localization in centrosome fractions purified from HEK293T cells in Fig. S5B. In the revised manuscript, we will replace confocal imaging data in Fig. 3A and 3B with SIM imaging data.
      • As the reviewer noted, expansion microscopy has been successfully used for the analysis of a wide range of cellular structures and scientific questions including nanoscale mapping of cellular structures across different organisms. In particular, U-ExM of previously characterized centrosome proteins various centriole proteins have significantly advanced our understanding of centriole ultrastructure. In our manuscript, we used the U-ExM protocol that was validated for centrioles by comparative analysis of U-ExM and cryo-ET imaging by our co-authors (Gambarotto et al., 2019; Hamel et al., 2017). To clarify these points, we included the following sentence along with the relevant references in the introduction: “Application of the U-ExM method to investigate known centrosome proteins has started to define the composition of the inner scaffold as well as other centriolar sub-compartments (Chen et al., 2015; Gambarotto et al., 2021; Gambarotto et al., 2019; Kong and Loncarek, 2021; Laporte et al., 2022; Mahen, 2022; Mercey et al., 2022; Odabasi et al., 2023; Sahabandu et al., 2019; Schweizer et al., 2021; Steib et al., 2022; Tiryaki et al., 2022; Tsekitsidou et al., 2023).”

      Minor points:

      1) Text, figures, and referencing are clear and accurate, apart from minor exceptions.

      We clarified and corrected the points regarding text, figures and references as suggested by the two reviewers.

      __ 2) The title suggests a regulator role for CCDC15 in centriole integrity and ciliogenesis, which has formally not been shown. __

      We revised the title as “CCDC15 localizes to the centriole inner scaffold and functions in centriole length control and integrity”.

      __3) As the authors observe changes in centriole lengths in the absence of CCDC15, it would be very insightful to compare these phenotypes to other components that affect centriolar length, such as C2CD3, human Augmin complex components (as HAUS6 is identified in Fig. 1) or others. These could be interesting aspects for discussion, additional experiments are OPTIONAL. __

      We agree with the reviewer that comparative analysis of centriole length phenotypes for CCDC15 and other components that regulate centriole length will provide insight into how these components work together at the centriole inner core. To this end, we phenotypically compared CCDC15 loss-of-function phenotypes to that of other components of the inner scaffold (POC5, POC1B, FAM161A) that interact with CCDC15. In agreement with their previously reported functions in U2OS or RPE1 cells, we found that POC5 depletion resulted in a 4% slight but significant increase in centriole length and POC1B depletion resulted in a 15% significant decrease. In contrast, FAM161A depletion did not alter centriole length (siControl: 447.8±59.7 nm, siFAM161A 436.3±64 nm). Together, our analysis of their centriolar localization dependency and regulatory roles during centriole length suggest that CCDC15 and POC1B might form a functional complex as positive regulators of centriole length. In contrast, POC5 functions as a negative regulator and might be part of a different pathway for centriole length regulation. We integrated the following sub-paragraph in the results section and also included discussion of this data in the discussion section:

      “Moreover, we quantified centriole length in control cells and cells depleted for POC5 or POC1B. While POC5 depletion resulted in longer centrioles, POC1B resulted in shorter centrioles (POC5: siControl: 414.1 nm±38.3, siPOC5: 432.7±44.8 nm, POC1B: siControl: 400.6±36.1 nm, siPOC1B: 341.5±44.39 nm,). FAMA161A depletion did not alter centriole length (siControl: 447.8±59.7 nm, siFAM161A 436.3±64 nm). Together, these results suggest that CCDC15 might cooperate with POC1B and compete with POC5 to establish and maintain proper centriole length.”

      __ 4) While the reduced ciliation rate in the absence of CCDC15 is convincing, the authors did not investigate "ciliogenesis", i.e. the formation of cilia, and hence should re-phrase. The sentence in the discussion that "CCDC15 functions during assembly" should be removed. __

      To clarify that we only investigated the role of CCDC15 in the ability of cells to form cilia, we replaced sentences that indicates “CCDC15 functions in cilium assembly” with “CCDC15 is required for the efficiency of cilia formation”.

      __5) The existence of stably associated CCDC15 pools with centrosomes (Fig. 2) requires further evidence. The recovery of fluorescence after photobleaching in FRAP experiments is strongly dependent on experimental setups and is only semi-quantitative. A full recovery is unrealistic, hence, it is ideally compared to a known static or known mobile component. I personally think this experiment -as it is presented now- is of little value to the overall fantastic study. The authors may consider omitting this piece of data. __

      We agree with the reviewer that FRAP data by itself does not prove the existence of stably associated CCDC15 pool. As controls in these experiments, we use FRAP analysis of GFP-CCDC66, which has a 100% immobile pool at the cilia and 50% immobile pool at the centrosomes as assessed by FRAP (Conkar et al., 2019). To address these points, we toned down the conclusions derived from this experiment by revising the sentence as follows:

      Additionally, we note that the following data provides support for the stable association of CCDC15 at the centrioles:

      • About 49.6% (± 3.96) of the centrioles still had CCDC15 fluorescence signal at one of the centrioles upon CCDC15 siRNA treatment (Fig. 5A, 5B). The inefficient depletion of the mature centriole pool of CCDC15 is analogous to what was observed upon depletion of other centriole lumen and inner scaffold proteins including WDR90 and HAUS6 (Schweizer et al., 2021; Steib et al., 2020). __6) The data that CCDC15 is a cell cycle-regulated protein is not very convincing (see Fig. 3H), as the signals area weak and the experiment has been performed only once (n= 1). This piece of data does not appear to be very critical for the main conclusions of the manuscript and may be omitted. Otherwise, this experiment should be repeated to allow for proper statistical analysis. __

      We will perform these experiments two more times, quantify cellular abundance of CCDC15 in synchronized populations from three experimental replicates and plot it with proper statistical analysis.

      __7) Experimental details on how "defective centrioles" are determined are missing. __

      We included the following experimental details to the methods section:

      “Centrioles were considered as defective when the roundness of the centriole was lost or the microtubule walls were broken or incomplete. In the longitudinal views of centrioles, defective centrioles were visualized as heterogenous acetylated signal along the centriole wall or irregularities in the cylindrical organization of the centriole wall (Fig. 5F). We clarified these points in the methods section.

      __ 8) For figures, in which the focus should be on growing centrioles (see Fig. 4), it could be helpful to guide the reader and indicate the respective areas of the micrographs by arrows. __

      We added arrows to point to the respective areas of the micrographs in Fig. 4F.

      __ 9) Page18: "centriole length shortening" could be changed to "centriole shortening". __

      We corrected this description as suggested.

      __10) It is unclear how the authors determine distal from proximal ends of centrioles in presented micrographs (see Fig. 5D). __

      We determined the proximal and distal ends of the centrioles by taking the centriole pairs as a proxy. Even though we only represent a micrograph containing a single centriole in some of the U-ExM figures including Fig. 5D, the uncropped micrographs contain two centrioles, which are oriented orthogonally and tethered to each other at their proximal ends in interphase cells. We added the following sentence to the methods section to clarify this point:

      *“Since centrioles are oriented orthogonally and tethered to each other at their proximal ends in interphase cells, we also used the orientation of the centriole pairs as a proxy to determine the proximal and distal ends of the centrioles.” *

      __11) Fig. 7A is missing scale bars and Fig.7 overall is lacking rectangle indicators of the areas that are shown at higher magnification in the insets. __

      We added scale bar to Fig. 7A and rectangle indicators for zoomed in regions in Fig. A, E, G.

      12) Fig. 7C displays cilia that appear very short, especially when comparing to the micrographs and bar graphs presented. The authors may want to explain this discrepancy.

      We thank the reviewer for the comment. The zoomed in representative cilia is 4.1 µM in control cells and 1.4 µM in CCDC15-depleted cells. Therefore, the representative cilia is in agreement with the quantification of cilia in Fig. 7C.

      Reviewer #1 (Significance (Required)):From a technical point of view the authors use two state-of-the-art technologies, namely proximity labeling combined with proteomics and ultrastructure expansion microscopy, that are both challenging and very well suited to address the main questions of this study. ____ • General assessment: The presented study is of highest experimental quality. Despite being very challenging, the expansion microscopy and proximity proteomics experiments have been designed and performed very well to allow solid interpretation. The results of the central data are consistent and allow strong first conclusions about the putative function of the newly identified centriolar protein CCDC15. The study presents a solid foundation for future hypothesis-driven, mechanistic analysis of CCDC15 and inner scaffold proteins in centriole length control and maintaining centriole integrity. The only limitation of the study is that the technically simpler experiments should be repeated to allow proper statistical assessment, which can be addressed easily. • Advance: This is the first study that identifies CCDC15 as a centriolar protein and localizes it to the inner scaffold. It further describes a function for CCDC15 in centriole length control and shows its importance in maintaining centriole integrity with consequences for stable cilia formation in tissue culture. The study provides further functional insights into the interdependence of inner scaffold proteins and the role of CCDC15 in the recruitment of the SFI1/centrin distal complex. • Audience: The manuscript will be of broad interest to the fields of centrosome and cell biology, both from a basic research and genetics/clinical point of view due to the association with human disorders. The state-of-the-art technologies applied will be of interest to a broader cell and molecular biology readership that studies subcellular compartments and microtubules. • Reviewer's field of expertise: Genetics, imaging, and protein-protein interaction studies with a focus on centrosomes and cilia.

      We thank the reviewer for recognizing the importance of our work and for supportive and insightful comments that will further strengthen the conclusions of our manuscript. Our planned revisions will address the only major technical limitation raised by the reviewer that requires adding one more experimental replicate for analysis of the data detailed in major point#1. Notably, we also thank the reviewer to specifying the experiments that are not essential or will be out of the scope of our manuscript as “optional”.

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

      Summary:

      __In this study, Arslanhan et al. propose CCDC15 as a novel component of the centriole inner scaffold structure with potential roles in centriole length control, stability and the primary cilium formation in cultured epithelial cells. Using proximity labelling they explore the common interactors of Poc5 and Centrin-2, two resident molecules of the centriole inner scaffold, to hunt for novel regulators of this structure. The authors leverage expansion microscopy-based localization and siRNA-dependent loss-of-function experiments to follow up on one such protein they identify, CCDC15, with the aforementioned roles in centriole and cilia biology.

      This study is designed and laid out nicely; however, to be able to support some of the important claims regarding their proximity labelling results and exploration on the roles of CCDC15, there are several major technical and reproducibility concerns that deem major revision. Similarly, the introduction (perhaps inadvertently) omits much of the recent studies on centriole size control that have highlighted the complexity of this biological problem. As such, addressing the following major points will be essential in further considering this work for publication. __

      __We thank the reviewer for recognizing the importance of our work and appreciate the positive reflections on our manuscript and the feedback comments that were well thought-out and articulated and will further strengthen the conclusions of our manuscript. Our planned revisions focus on addressing the reviewer’s comments especially in further supporting our conclusions for proximity-labeling, phenotypic characterization and immunoprecipitation experiments, examining CCDC15 centriole localization in an additional cell line and investigating how CCDC15 works together during centriole length control with known components of the inner scaffold. __

      Major points:

      __1a) The authors use Poc5 and Centrin-2 molecules as joint baits to reveal the interactome of the centriole inner scaffold, however the work lacks appropriate experimental and analytical controls to argue that this is a proximity mapping "at the centriole inner scaffold". In its current state, it is simply an interactome of total Poc5 and Centrin-2, and it might be misleading to call it an interactome at the centriole inner scaffold (the statistical identification of shared interactors cannot do full justice to their biology at the centrosome). Appropriate expression data needed to delineate how large the centrosomal vs. cytoplasmic (or nucleoplasmic) fraction is for either of these molecules, both without and upon the addition of biotin (to see whether the bulk of interaction data stem from the cytoplasm/nucleoplasm or the centrioles themselves). The authors can test this by selectively blotting a lysate fraction containing the centrosomes after centrifugation, and compare them with the simultaneous blot of the supernatant (which were readily used for the blots presented in Fig. 1B). This experiment also becomes very relevant for the case of Centrin-2, as it also heavily localizes to the nucleoplasm as the authors found out (see Fig. 1A and Fig. S1A). __

      __ Additionally, an orthogonal approach should be taken to perform bio-image analysis on their biotin/streptavidin imaging data to demonstrate the exact ratios between the centrosomal vs. cytoplasmic/nucleoplasmic biotin activation with appropriate signal normalization between the biotin/streptavidin images. This is particularly important, as although the authors claim that these cells stably express the V5BirA*, it seems that there is partial clonality to the expression. Some cells in both the Poc5 and Centrin-2 fusion constructs appear to lack the V5/Streptavidin signals upon Biotin addition (such as the two cells in the centre right in Poc5, and again a cell in the centre right for Centrin-2 images). In its current form, Fig. 1A lacks signal quantification and does not report any information about the replicates and distributions of the data. I worry that this may raise concerns on the reproducibility if published in its current form. __a) We agree with the reviewer that the proximity maps of POC5 and

      a) Centrin-2 are not specific to the centriole inner scaffold and thus, do not represent the inner scaffold interactome. The proximity maps identified interactions across different pools of POC5 and Centrin-2 in nucleus, cytoplasm and centrosomes (Fig. 1, S1). To highlight these important points, we already included extensive analysis of the different cellular compartments and biological processes identified by the POC5 and Centrin-2 proximity maps in the results section (pg. 9-10).

      We think that there are two reasons that caused the misinterpretation of the use of these proximity maps as the “inner scaffold interactome”: 1) the way we introduced the motivation for proximity mapping studies, 2) proposing the use of the resulting interactomes as resources for identification of the full repertoire of the inner scaffold proteins. To clarify these points, we revised the manuscript in all relevant parts that might have led to misinterpretation. Following are the specific revisions:

      • To clarify that the proximity maps are not specific to the inner scaffold pools of POC5 and Centrin-2, we revised the title of the results section for Fig. 1 and 2 as follows: “Proximity mapping of POC5 and Centrin-2 identifies new centriolar proteins”.

      • To indicate that POC5 and Centrin-2 localizes to the cytoplasm and/or nucleus in addition to the centrosome, we added the following sentence to the result section: In addition to centrosomes, both fusion proteins also localized to and induced biotinylation diffusely in the cytoplasm and/or nucleus (Fig. 1A).”

      • In the introduction, we revised the following sentence “Here, we used the known inner scaffold proteins as probes to identify the molecular makeup of the inner scaffold in an unbiased way.” as follows: *“Here, we used the known inner scaffold proteins as probes to identify new components of the inner scaffold”. *

      • To highlight the different cellular pools of POC5 and Centrin-2 and identification of their interactors in these pools, we included the following sentence in the results section: “As shown in Fig. S1, Centrin-2 and POC5 proximity interactomes were enriched for GO categories that are relevant for their published functions during centrosomal, cytoplasmic and/or nuclear biological processes and related cellular compartments (Azimzadeh et al., 2009; Dantas et al., 2013; Heydeck et al., 2020; Khouj et al., 2019; Resendes et al., 2008; Salisbury et al., 2002; Steib et al., 2020; Yang et al., 2010; Ying et al., 2019).”

      • We replaced the “interactome” statement with “proximity interaction maps” or “proximity interactors” throughout the manuscript to prevent the conclusion that the proximity maps represent the inner scaffold interactome. b) As the reviewer noted, most centrosome proteins have multiple different cellular pools including the centrosome. For most proteins like gamma-tubulin and centrin, their cytoplasmic/nucleoplasmic pools are more abundant than their centrosomal pools (Moudjou et al., 1996; Paoletti et al., 1996). For the Firat-Karalar et al. Current Biology 2015 paper, I compared the biotinylation levels of centrosomal fractions versus cytoplasmic fractions and confirmed that this is also true in cells expressing myc-BirA* fusions of CDK5RAP2, CEP192, CEP152 and CEP63 (unpublished) (Firat-Karalar et al., 2014). For the revised manuscript, we will compare the biotinylation level of centrosomal, nuclear and cytoplasmic pools of V5Bir*-POC5 and V5BirA*-Centrin-2 using the stable lines. To this end, we will use published centrosome purification protocols. We will include this data in Fig. S1 to highlight that the proximity interactomes represent the different pools of the bait proteins and to show the relative levels of the baits across their different pools.

      c) BioID approach has been successfully used to probe centrosome interactions by my lab and other labs in the field. In fact, proximity interaction maps of over 50 centrosome proteins were published as resource papers by Pelletier&Gingras labs (Gheiratmand et al., 2019; Gupta et al., 2015). Analogous to our strategy in this manuscript, these studies generated proximity maps of centrosome proteins by creating cell lines that stably express BioID-fusions of centrosome proteins followed by streptavidin pulldowns from whole cell extracts and mass spectrometry analysis. Since majority of centrosome proteins also have pools in multiple cellular locations, the published BioID proximity maps for centrosome proteins are not specific to centrosomes. However, the proximity maps included all known centrosome proteins and identified new proteins, which shows that centrosome interactions are represented in pulldowns form whole cell lysates. Moreover, maps form whole cell lysates are also advantageous as they are are unbiased and can be used in future studies as resources for studying the functions and interactions of the bait proteins in different contexts.

      In the Firat-Karalar et al. Current Biology 2015 paper, I combined centrosome purifications with BioID pulldowns to enrich for the centrosomal interactions in the proximity maps of centriole duplication proteins(Firat-Karalar et al., 2014). However, I started the purification with cells transiently transfected with the BioID-fusion constructs, which resulted in high ectopic expression of the fusions in the cytoplasm and/or nucleus. Therefore, centrosome enrichments were useful as an additional step before mass spectrometry. Comparative analysis of the data for proximity maps of 4 centrosome proteins generated from stable lines or centrosome fractions of transiently transfected cells substantially overlap as compared in the Gupta et al. Cell 2015 study and were more comprehensive (Table S2) (Gupta et al., 2015). Therefore, we are confident that the proximity interactomes we generated for POC5 and Centrin-2 include their centrosomal interactions.

      __1b) Similarly, it is not clear whether the expression of Poc5 and Centrin-2 fusion molecules somehow interfere with their endogenous interactions or function. At least some loss-of-function (e.g., RNAi) experiments should be performed where the depletion of endogenous proteins should be attempted to rescue by the fusion constructs. This will help evaluate whether the fusion proteins can rescue the depletion of their endogenous counterparts and behave as expected from a wild-type scenario. __

      The reviewer raises an important concern regarding the physiological relevance of the POC5 and Centrin-2 proximity maps. In the manuscript, we showed and discussed the validation of their proximity interactomes by two lines of evidence, which are: 1) the interactomes identified the previously described cellular compartments, biological processes or interactors of POC5 and Centrin-2, 2) the interactomes led to the identification of CCDC15 as a new inner scaffold protein.

      As the reviewer indicated, stable expression of POC5 and Centrin-2 in the presence of their endogenous pools might affect cellular physiology and thereby the landscape of the interactomes. We plan to address this using the following experiments:

      a) We will perform a set of functional assays to assess whether stable V5BirA*-Centrin-2 and V5BirA*-POC5 cells behaves like control cells in terms of their centrosome number, cell cycle profiles and mitotic progression. We will specifically quantify:

      • centrosome number (immunofluorescence analysis for gamma-tubulin and centrin)
      • their mitotic index (immunofluorescence analysis by DAPI)
      • spindle polarity and percentage of multinucleation (immunofluoerescence analysis for microtubules, gamma-tubulin and DAPI)
      • cell cycle profiles (flow cytometry and immunofluorescence)
      • apoptosis (immunoblotting for caspase 3) Together, results from these experiments indicate that the V5BirA*-POC5 or Centrin-2-expressing stable lines do not exhibit defects associated with their stable expression.

      b) We will perform expansion microscopy in V5BirA*-Centrin-2 and V5BirA*-POC5 cells to assess whether the fusion protein specifically localizes to the centriole inner scaffold, which will provide support for the presence of inner scaffold proteins in their proximity maps. Specifically, we plan to stain the fusion proteins by V5 or BirA antibodies and include the data for the antibody that works for expansion microscopy. This experiment will address whether their stable expression results in specific localization of these proteins at the centriole inner scaffold.

      1c) Overall, as the entire claim around the proximity mapping revolve around its assumption about the centriole inner scaffold, these controls seem imperative to substantiate the ground truth of the biology presented in the manuscript.

      In the revised manuscript, we toned down and made it clear that Centrin-2 and POC5 proximity maps are not specific to the inner scaffold and do not represent the inner scaffold interactome. Since the maps were generated from the whole cell extract, they will provide a resource for future studies aimed at studying functions and mechanisms of POC5 and Centrin-2 across their different cellular pools including the centrosome.

      We would like to also highlight that the proximity maps of POC5 and Centrin-2 are not the major advances of our manuscript. The major advance of our manuscript is the identification of CCDC15 as a new inner scaffold protein that is required for regulation of centriole size and architectural integrity and thereby, for maintaining the ability of centrioles to template the assembly of functional cilia. Importantly, our results identified CCDC15 as the first dual regulator of centriolar recruitment of inner scaffold protein POC1B and the distal end SFI1/Centrin complex and provided important insight into how inner scaffold proteins work together during centriole integrity and size regulation. The new set of experiments we will perform for the revisions of the paper will strengthen these conclusions.

      __2) I am curious about the choices of the cell lines in this work. The proximity mapping to reveal CCDC15 as a candidate protein for centriole inner scaffold was performed in HEK293T cells (human embryonic kidney), however its immunostaining was performed using RPE1 and U2OS cells (human retinal and osteosarcoma epithelial cells respectively). This raises questions regarding the generality of CCDC15 as a centriole inner scaffold protein. Could CCDC15 be simply unique to the centriole inner scaffold of epithelial cells such as RPE1 and U2OS cells? Or could the authors demonstrate any information/data on whether it's similarly localized to the inner scaffold in embryonic kidney cells or other cell types? If not, the claims should be moderated to reflect this fine detail. __

      To test whether CCDC15 localizes to the inner scaffold in other cell types, we performed U-ExM analysis of CCDC15 localization relative to the centriolar microtubules in differentiating multiciliated epithelial cultures (MTEC). As shown in Fig. S3A, CCDC15 localized to the inner scaffold in the centrioles in MTEC ALI+4 cells. Given that the inner scaffold proteins including CCDC15 and previously characterized ones have not been studied in multiciliated epithelia, this result is important and provides support for potential role of the inner scaffold in ensuring centriole integrity during ciliary beating. Additionally, we examined CCDC15 localization by 3D-SIM in centrosomes purified from HEK293T cells, which showed that CCDC15 localizes between the distal centriole markers CEP164 and Centrin-3 and proximal centriole markers gamma-tubulin and rootletin (Fig. S3B).

      3) Discussions and data on the localization of CCDC15 to centriolar satellites appear anecdotal and not fully convincing (Fig. S2D). Given that the authors test the relevance of PCM1 for CCDC15's centriolar localization, it is key to have quantitative data supporting their claim that centriolar satellites can help recruit CCDC15 to the centriole. Could the authors quantify what proportion of CCDC15 localize to the centriolar satellites? One way to do this could be to quantify the colocalization coefficience of CCDC15 and PCM1 signals.

      We only observed co-localization of CCDC15 with the centriolar satellite marker PCM1 in cells transiently transfected with mNG-CCDC15. In Fig. S2E, we included the quantification of the percentage of U2OS and RPE1 cells that exhibit co-localization of PCM1 (100% of U2OS cells, about 80% of RPE1 cells). Like CCDC15, ectopic expression of WDR90 revealed its centriolar satellite localization, suggesting a potential link between centriolar satellites and inner scaffold proteins that can be investigated in future studies (Steib et al., 2020). We now included these results in the discussion section as follows:

      As assessed by co-localization with the centriolar satellite marker PCM1, mNG-CCDC15 localized to centriolar satellites in all U2OS cells and in about 80% of RPE1 cells (Fig. S2C-E). Association of CCDC15 with centriolar satellites is further supported by its identification in the centriolar satellite proteomes(Gheiratmand et al., 2019; Quarantotti et al., 2019).”

      Even though endogenous staining for CCDC15 did not reveal its localization to centriolar satellites, following lines of data support the presence of a dynamic and low abundance pool of CCDC15 at the centriolar satellites: 1) CCDC15 was identified in the centriolar satellite proteome and interactome (Gheiratmand et al., 2019; Quarantotti et al., 2019). 2) CCDC15 centrosomal targeting is in part regulated by PCM1 (Fig. S2F, S2G). For majority of the proteins identified in the centriolar satellite proteome, their satellite pool can only be observed upon ectopic expression. This might be because their centriolar satellite pool is of low abundance and transient as satellite interactions are extensively identified only in proximity mapping studies, but not in traditional pulldowns

      __4) Similar to above (#3), there is no quantitative information on the co-localization or partial co-localization of the signal foci in Fig. 3A and 3B. The authors readily study CCDC15's localization in wonderful detail in their expansion microscopy data, so they could actually consider taking out Fig. 3A and 3B, as the data seem redundant without any quantification. __

      To address the reviewer’s concern, we included plot intensity profile analysis of CCDC15 and different centriole markers along a line drawn at the centrioles in Fig. 3A and 3B, which shows the extent of their overlap. As part of our revision plan, we will replace the confocal imaging data in Fig. 3A and 3B with 3D-SIM imaging data of CCDC15 relative to different centriole markers together with plot profile analysis. We already included 3D-SIM imaging of centrosomes purified form HEK293T cells in Fig. S3B. 3D-SIM imaging data will complement the localization data revealed by U-ExM.

      __5) Do the authors also feel that CCDC15 localize to the core lumen in a somehow helical manner (Fig. 1A, Fig. 1F top and bottom panels, Fig. 5A etc.)? Le Guennec et al. 2020's helical lattice proposal for the inner scaffold further reaffirms that CCDC15 is indeed a likely major component of the inner scaffold. In my view, authors should state this physical similarity explicitly to further support their findings on CCDC15. __

      As the reviewer indicated, cryo–electron tomography and subtomogram averaging of centrioles from four evolutionarily distant species showed that centriolar microtubules are bound together by a helical inner scaffold covering ~70% of the centriole length (Le Guennec et al., 2020). Although U-ExM data do not have enough resolution to show that CCDC15 localizes in a helical manner, we agree with the reviewer that the discussion of this possibility is important and thus we included the following sentence in the results:

      “Longitudinal views suggest potential helical organization of CCDC15 at the inner scaffold, which is consistent with its reported periodic, helical structure (Le Guennec et al., 2020).”

      __6a) The data on the link between the CCDC15 recruitment and the centriole growth (Fig. 4F) or the G2 phase of the cell cycle (Fig. 4H) are not fully convincing without quantitative data. For Fig. 4F, the authors should consider plotting the daughter centriole length vs the daughter CCDC15 intensities against each another, to see whether more elongated daughters truly tend to have more CCDC15. __

      To address the reviewer’s concern, we will plot the daughter centriole length versus CCDC15 intensity at different stages of centriole duplication. In asynchronous cultures that we analyzed with U-ExM, we were not able to find enough cells to perform such quantification. To overcome this limitation, we will perform U-ExM analysis of cells fixed at different points after mitotic shake-off and stained for CCDC15 and tubulin. We will include minimum 10 different representative U-ExM data for different stages of centriole duplication in the revised manuscript along with quantification of length versus signal.

      As detailed in the results section, the goal of these experiments was to determine when CCDC15 is recruited to the procentrioles during centriole duplication, but not to suggest a role for CCDC15 in centriole growth. We clarified this by including the following sentence:

      “To investigate the timing of CCDC15 centriolar recruitment during centriole biogenesis, we examined CCDC15 localization relative to the length of procentrioles that represent cells at different stages of centriole duplication (Fig. 4F).”

      __6b) For Fig. 4H, the argument regarding the cell cycle regulation requires quantification of the bands from several WB repeats, normalized to the expression of GAPDH within each blot (this is particularly relevant, as the bands of CCDC15 do not look dramatically different enough to draw conclusions by eye). __

      We will perform these experiments two more times, quantify cellular abundance of CCDC15 in synchronized populations from three experimental replicates and plot it with proper statistical analysis.

      __7a) The authors find herein that CCDC15 depletion lead to centrioles that are ~10% shorter than the controls. With the depletion of Poc5 and Wdr90 (other proposed components of the inner scaffold), the centrioles end up larger however (Steib et al., 2020). If the role of inner scaffold in promoting centriole elongation is structural, why are these two results the opposite of each other? I realize there is a brief discussion about this at the end of the paper, however, this requires a detailed discussion and speculation on the relevance of these findings. It would be key to clarify whether the inner scaffold as a structure inhibits or promotes centriole growth - or somehow both? If so, how? __

      We agree with the reviewer that comparative analysis of centriole length phenotypes for CCDC15 and other components that regulate centriole length will provide insight into how these components work together at the centriole inner core. To this end, we phenotypically compared CCDC15 loss-of-function phenotypes to that of other components of the inner scaffold (POC5, POC1B, FAM161A) that interact with CCDC15. In agreement with their previously reported functions in U2OS or RPE1 cells, we found that POC5 depletion resulted in a 4% slight but significant increase in centriole length and POC1B depletion resulted in a 15% significant decrease. In contrast, FAM161A depletion did not alter centriole length (siControl: 447.8±59.7 nm, siFAM161A 436.3±64 nm). Together, our analysis of their centriolar localization dependency and regulatory roles during centriole length suggest that CCDC15 and POC1B might form a functional complex as positive regulators of centriole length. In contrast, POC5 functions as a negative regulator and might be part of a different pathway for centriole length regulation. We integrated the following sub-paragraph in the results section in pg. 19 and also included discussion of this data in the discussion section in pg. 23:

      “Moreover, we quantified centriole length in control cells and cells depleted for POC5 or POC1B. While POC5 depletion resulted in longer centrioles, POC1B resulted in shorter centrioles (POC5: siControl: 414.1 nm±38.3, siPOC5: 432.7±44.8 nm, POC1B: siControl: 400.6±36.1 nm, siPOC1B: 341.5±44.39 nm,). FAMA161A depletion did not alter centriole length (siControl: 447.8±59.7 nm, siFAM161A 436.3±64 nm). Together, these results suggest that CCDC15 might cooperate with POC1B and compete with POC5 to establish and maintain proper centriole length.”

      __7b) There might be some intriguing opposing regulatory action of Poc5 and CCDC15 as demonstrated here, where CCDC15 depletion leads to slightly over-recruitment of Poc5, and vice versa. Does this suggest that a tug-of-war going on between different molecules that localize to the inner scaffold? Does this provide some dynamicity to this structure, which might in turn regulate centriole length both positively and negatively? This may be analogous to how opposing forces of dyneins and kinesins provide robust length control for mitotic spindles. I am speculating here, but hopefully these may provide some useful grounds for further discussion in the paper. If the authors deem it interesting experimentally, they can test whether the two molecules indeed regulate centriole length by opposing each other's action, by a double siRNA of CCDC15 and Poc5 to see if this retains the centriole length at its control siRNA size (like how they do a similar test for Poc1's potential co-operativity with CCDC15 in Fig. 6J). __

      We thank the reviewer for proposing excellent ideas on how inner scaffold proteins work together to regulate centriole length. As proposed by the reviewer, different proteins oppose each other analogous to how dynein and kinesin regulate mitotic spindle length. Loss-of-function and localization dependency data support that CCDC15 cooperates with POC1B, which was supported by phenotypic characterization of co-depleted cells (Fig. 6I-K).

      The increase in POC5 levels and coverage at the centrioles upon CCDC15 depletion and vice versa (Fig. 7B, 7G) suggest that CCDC15 and POC5 compete with each other in centriole length regulation. As suggested by the reviewer, we attempted to test this by comparing centriole length in cells co-depleted for CCDC15 and POC5 relative to their individual depletions. Although we tried different depletion workflows, we were not able to co-deplete CCDC15 and POC5. Specifically, we tried transfecting cells with CCDC15 and POC5 siRNAs at the same time or sequentially for 48 h or 96 h. The centrioles in cells that survived co-depletion were positive for both CCDC15 and POC5. This might be because co-depletion of both proteins is toxic to cells. Since CCDC15 and POC5 are likely part of two different pathway in regulation of centrioles and also have other cellular functions, this might have caused cell death. We included the following statement in the discussion to address the excellent model proposed by the reviewer:

      “Taken together, our results suggest that CCDC15 cooperates with POC1B and competes with POC5 during centriole length regulation. Moreover, they also raise the exciting possibility that centriole length can be regulated by opposing activities of inner scaffold proteins. Future studies that explore the relationship among centriole core proteins are required to uncover the precise mechanisms by which they regulate centriole integrity and size.”

      __8) In their introduction section, the authors discuss how relatively little is known about the size control of centrioles, however they fail to mention a series of recent primary literature that uncover striking, new mechanisms and novel molecular players that highlight the complexity of centriole size control. This complexity appears to arise from the existence of multitude of length control mechanisms that influence the cartwheel or the microtubule length individually, or simultaneously via yet-to-be further explored crosstalk mechanisms. a. As such, when the authors talk about the procentriole size control in the introduction, they should discuss and refer to the following studies, in terms of: • How theoretical and experimental work demonstrate that procentriole length may vary dependent on the levels of its building block Sas-6 in animals (Dias Louro et al., 2021 PMID: 33970906; Grzonka and Bazzi, 2022 bioRxiv). • How a homeostatic Polo-like kinase 4 clock regulates centriole size during the cell cycle (Aydogan et al., 2018 JCB PMID: 29500190), and how biochemistry and genetics coupled with mathematical modelling unravel a conserved negative feedback loop between Cep152 and Plk4 that constitutes the oscillations of this clock in flies (Boese et al., 2018 PMID: 30256714; Aydogan et al., 2020 PMID: 32531200) and human cells (Takao et al., 2019 PMID: 31533936). __

      __b. Similarly, when the authors refer to centriole size control induced by microtubule-related proteins, they should highlight the further complexity of this process by referring to: • How a molecule located at the microtubule wall, Cep295/Ana1, can regulate centriole length in flies (Saurya et al., 2016 PMID:27206860) and human cells (Chang et al., 2016 PMID:27185865) - like all the other centriolar MT molecules that the authors discuss in the manuscript. • How a crosstalk between Cep97 and Cep152 influences centriole growth in fly spermatids (Galletta et al., 2016 PMID:27185836). • How a crosstalk between CP110-Cep97 and Plk4 influences centriole growth in flies (Aydogan et al., 2022 PMID:35707992), and this molecular crosstalk is conserved, at least biochemically, in human cells (Lee et al., 2017 PMID:28562169). __

      We thank the reviewer for highlighting the papers that uncovered new mechanisms and players of centriole size and integrity control as well as for the detailed explanation of how different studies led to these discoveries in different organisms. We should have discussed these proteins, functional complexes and mechanisms in our manuscript and cited the relevant literature. We inadvertently focused on literature that uncovered centriole length regulation by MAPs and the inner scaffold. In the introduction section of the revised manuscript where we introduced centriole size regulation in pg. 5, we summarized the major findings on the role of different MAPs, cartwheel and PLK4 homeostatic clock in ensuring formation of centrioles at the correct size in different organisms.

      __Minor points: __

      __1) Introduction section: Literature reference missing for the sentence starting with "Importantly, the stable nature of centrioles enables them to withstand...". __

      We cited research articles that show the importance of centriole motility during ciliary motility and cell division.

      “Importantly, the stable nature of centrioles enables them to withstand mechanical forces during cell division and upon ciliary and flagellar motility (Abal et al., 2005; Bayless et al., 2012; Meehl et al., 2016; Pearson et al., 2009).

      __2) Fig. S1 legend: A typo as follows: CRAPome banalysis should read CRAPome analysis. __

      We corrected this typo.

      __3) Fig. S2: Info on the scale bar in the legend is missing in Fig. S2A. Scale bars for different panels are missing in general in Fig. S2A. __

      We added scale bar information for Fig. S2A and to all other supplementary figure legends that lack scale bar information.

      __4) Fig. 3A and 3B: When displaying the data, coloured cartoon diagrams would be beneficial to guide the reader who are not fully familiar with the spatial orientation of these proteins. __

      As suggested by the reviewer, we will remove the confocal imaging data for CCDC15 localization from Fig. 3A and 3B. For the revised version, we will include 3D-SIM imaging data along with a diagram that represents the spatial orientation of CCDC15 relative to the chosen centriole markers.

      __5) Fig. 3H: No information about the sample number (number of cells or technical repeats examined) reported. __

      We included information on the number of experimental replicates and cells analyzed.

      __6) Fig. S3B legend: A typo as follows: CCD15-depelted RPE1 cells should read CCDC15-depleted RPE1 cells. __

      We corrected this typo.

      __7) Fig. S3B legend: A typo as follows: cellswere fixed with should read cells were fixed with. __

      We corrected this typo.

      __8) There are many spelling mistakes and typos throughout the paper. I have listed a few examples above, but please carefully read through the manuscript to correct all the errors. __

      Thank you for indicating the spelling mistakes we missed to correct for initial submission. In the revised manuscript, we carefully read through the manuscript to correct the mistakes.

      __9) Fig. S3E: The orange columns depicting % of cells with Sas-6 dots look awkward. Why the columns look larger than the mean line? Please correct as appropriate. __

      The total percentage of cells in the two categories (orange and purple) we counted is 100%, which corresponds to the column value at the y-axis. Therefore, the value for each experimental replicate for the orange category is less than 100% and is marked below the 100% line.

      __10) Although authors provide microscopy information for the U-ExM and FRAP experiments, there is no information about the microscopy on regular confocal imaging experiments which should be detailed in Materials and Methods. Also, there is no information about the lenses, laser lines and the filter sets that were used in the imaging experiments. These should be provided as well. __

      In the methods section, we now included detailed information for the microscopes we used and imaging setup (lenses, laser lines, filter sets, detectors, z-stack size, resolution).

      11)

      • __ Fig. 2A: lacks a scale bar. __
      • __ Fig. 2C legend: lacks info on the scale bar length. __
      • __ Fig. 5A legend: lacks info on the scale bar length. __
      • __ Fig. 7A: lacks a scale bar. __
      • __ Fig. 7G legend: lacks info on the scale bar length. __
      • __ Fig. S2C-E: lack scale bars. __
      • __ Fig. S3D, F and H: lack scale bars. (Fig. S4 in the revised manuscript)__
      • __ Fig. S3J legend: lacks info on the scale bar length. (Fig. S4 in the revised manuscript)__
      • __ Fig. S4A, B, D and E: lack scale bars. (Fig. S5 in the revised manuscript)__
      • __ Fig. S4C legend: lacks info on the scale bar length. (Fig. S5 in the revised manuscript)__
      • __ Fig. S4G legend: lacks info on the scale bar length. (Fig. S5 in the revised manuscript)__ We added the scale bars and the size information to the figures and figure legends for the above figures.

      Reviewer #2 (Significance (Required)): __The findings of this study join among the relatively new literature (e.g., Steib et al., 2020 and Le Guennec et al. 2020) on the nature of centriole inner scaffold and its potential roles in centriole formation, integrity and its propensity to form the primary cilium. Therefore, it will be of interest to a group of scientists studying these topics in the field of centrosomes/cilia.

      My expertise is on the biochemistry and genetics of centriole formation in animals.__

      We thank the reviewer for his/her comments and constructive feedback to improve our manuscript. We are encouraged to see that the reviewer acknowledges how the results from our manuscript advances our understanding of centriole length, integrity and function regulation.

      References

      Abal, M., G. Keryer, and M. Bornens. 2005. Centrioles resist forces applied on centrosomes during G2/M transition. Biol Cell. 97:425-434.

      Atorino, E.S., S. Hata, C. Funaya, A. Neuner, and E. Schiebel. 2020. CEP44 ensures the formation of bona fide centriole wall, a requirement for the centriole-to-centrosome conversion. Nat Commun. 11:903.

      Azimzadeh, J., P. Hergert, A. Delouvee, U. Euteneuer, E. Formstecher, A. Khodjakov, and M. Bornens. 2009. hPOC5 is a centrin-binding protein required for assembly of full-length centrioles. J Cell Biol. 185:101-114.

      Bayless, B.A., T.H. Giddings, Jr., M. Winey, and C.G. Pearson. 2012. Bld10/Cep135 stabilizes basal bodies to resist cilia-generated forces. Mol Biol Cell. 23:4820-4832.

      Chen, F., P.W. Tillberg, and E.S. Boyden. 2015. Optical imaging. Expansion microscopy. Science. 347:543-548.

      Conkar, D., H. Bayraktar, and E.N. Firat-Karalar. 2019. Centrosomal and ciliary targeting of CCDC66 requires cooperative action of centriolar satellites, microtubules and molecular motors. Sci Rep. 9:14250.

      Dantas, T.J., O.M. Daly, P.C. Conroy, M. Tomas, Y. Wang, P. Lalor, P. Dockery, E. Ferrando-May, and C.G. Morrison. 2013. Calcium-binding capacity of centrin2 is required for linear POC5 assembly but not for nucleotide excision repair. PLoS One. 8:e68487.

      Firat-Karalar, E.N., N. Rauniyar, J.R. Yates, 3rd, and T. Stearns. 2014. Proximity interactions among centrosome components identify regulators of centriole duplication. Curr Biol. 24:664-670.

      Gambarotto, D., V. Hamel, and P. Guichard. 2021. Ultrastructure expansion microscopy (U-ExM). Methods Cell Biol. 161:57-81.

      Gambarotto, D., F.U. Zwettler, M. Le Guennec, M. Schmidt-Cernohorska, D. Fortun, S. Borgers, J. Heine, J.G. Schloetel, M. Reuss, M. Unser, E.S. Boyden, M. Sauer, V. Hamel, and P. Guichard. 2019. Imaging cellular ultrastructures using expansion microscopy (U-ExM). Nat Methods. 16:71-74.

      Gheiratmand, L., E. Coyaud, G.D. Gupta, E.M. Laurent, M. Hasegan, S.L. Prosser, J. Goncalves, B. Raught, and L. Pelletier. 2019. Spatial and proteomic profiling reveals centrosome-independent features of centriolar satellites. EMBO J.

      Gupta, G.D., E. Coyaud, J. Goncalves, B.A. Mojarad, Y. Liu, Q. Wu, L. Gheiratmand, D. Comartin, J.M. Tkach, S.W. Cheung, M. Bashkurov, M. Hasegan, J.D. Knight, Z.Y. Lin, M. Schueler, F. Hildebrandt, J. Moffat, A.C. Gingras, B. Raught, and L. Pelletier. 2015. A Dynamic Protein Interaction Landscape of the Human Centrosome-Cilium Interface. Cell. 163:1484-1499.

      Hamel, V., E. Steib, R. Hamelin, F. Armand, S. Borgers, I. Fluckiger, C. Busso, N. Olieric, C.O.S. Sorzano, M.O. Steinmetz, P. Guichard, and P. Gonczy. 2017. Identification of Chlamydomonas Central Core Centriolar Proteins Reveals a Role for Human WDR90 in Ciliogenesis. Curr Biol. 27:2486-2498 e2486.

      Heydeck, W., B.A. Bayless, A.J. Stemm-Wolf, E.T. O'Toole, A.S. Fabritius, C. Ozzello, M. Nguyen, and M. Winey. 2020. Tetrahymena Poc5 is a transient basal body component that is important for basal body maturation. J Cell Sci. 133.

      Khouj, E.M., S.L. Prosser, H. Tada, W.M. Chong, J.C. Liao, K. Sugasawa, and C.G. Morrison. 2019. Differential requirements for the EF-hand domains of human centrin 2 in primary ciliogenesis and nucleotide excision repair. J Cell Sci. 132.

      Kong, D., and J. Loncarek. 2021. Analyzing Centrioles and Cilia by Expansion Microscopy. Methods Mol Biol. 2329:249-263.

      Laporte, M.H., I.B. Bouhlel, E. Bertiaux, C.G. Morrison, A. Giroud, S. Borgers, J. Azimzadeh, M. Bornens, P. Guichard, A. Paoletti, and V. Hamel. 2022. Human SFI1 and Centrin form a complex critical for centriole architecture and ciliogenesis. EMBO J. 41:e112107.

      Le Guennec, M., N. Klena, D. Gambarotto, M.H. Laporte, A.M. Tassin, H. van den Hoek, P.S. Erdmann, M. Schaffer, L. Kovacik, S. Borgers, K.N. Goldie, H. Stahlberg, M. Bornens, J. Azimzadeh, B.D. Engel, V. Hamel, and P. Guichard. 2020. A helical inner scaffold provides a structural basis for centriole cohesion. Sci Adv. 6:eaaz4137.

      Mahen, R. 2022. cNap1 bridges centriole contact sites to maintain centrosome cohesion. PLoS Biol. 20:e3001854.

      Meehl, J.B., B.A. Bayless, T.H. Giddings, Jr., C.G. Pearson, and M. Winey. 2016. Tetrahymena Poc1 ensures proper intertriplet microtubule linkages to maintain basal body integrity. Mol Biol Cell. 27:2394-2403.

      Mercey, O., C. Kostic, E. Bertiaux, A. Giroud, Y. Sadian, D.C.A. Gaboriau, C.G. Morrison, N. Chang, Y. Arsenijevic, P. Guichard, and V. Hamel. 2022. The connecting cilium inner scaffold provides a structural foundation that protects against retinal degeneration. PLoS Biol. 20:e3001649.

      Moudjou, M., N. Bordes, M. Paintrand, and M. Bornens. 1996. gamma-Tubulin in mammalian cells: the centrosomal and the cytosolic forms. J Cell Sci. 109 ( Pt 4):875-887.

      Odabasi, E., D. Conkar, J. Deretic, U. Batman, K.M. Frikstad, S. Patzke, and E.N. Firat-Karalar. 2023. CCDC66 regulates primary cilium length and signaling via interactions with transition zone and axonemal proteins. J Cell Sci. 136.

      Paoletti, A., M. Moudjou, M. Paintrand, J.L. Salisbury, and M. Bornens. 1996. Most of centrin in animal cells is not centrosome-associated and centrosomal centrin is confined to the distal lumen of centrioles. J Cell Sci. 109 ( Pt 13):3089-3102.

      Pearson, C.G., D.P. Osborn, T.H. Giddings, Jr., P.L. Beales, and M. Winey. 2009. Basal body stability and ciliogenesis requires the conserved component Poc1. J Cell Biol. 187:905-920.

      Quarantotti, V., J.X. Chen, J. Tischer, C. Gonzalez Tejedo, E.K. Papachristou, C.S. D'Santos, J.V. Kilmartin, M.L. Miller, and F. Gergely. 2019. Centriolar satellites are acentriolar assemblies of centrosomal proteins. EMBO J.

      Resendes, K.K., B.A. Rasala, and D.J. Forbes. 2008. Centrin 2 localizes to the vertebrate nuclear pore and plays a role in mRNA and protein export. Mol Cell Biol. 28:1755-1769.

      Sahabandu, N., D. Kong, V. Magidson, R. Nanjundappa, C. Sullenberger, M.R. Mahjoub, and J. Loncarek. 2019. Expansion microscopy for the analysis of centrioles and cilia. J Microsc. 276:145-159.

      Salisbury, J.L., K.M. Suino, R. Busby, and M. Springett. 2002. Centrin-2 is required for centriole duplication in mammalian cells. Curr Biol. 12:1287-1292.

      Schweizer, N., L. Haren, I. Dutto, R. Viais, C. Lacasa, A. Merdes, and J. Luders. 2021. Sub-centrosomal mapping identifies augmin-gammaTuRC as part of a centriole-stabilizing scaffold. Nat Commun. 12:6042.

      Steib, E., M.H. Laporte, D. Gambarotto, N. O’lieric, C. Zheng, S. Borgers, V. Olieric, M.L. Guennec, F. Koll, A.M. Tassin, M.O. Steinnmetz, P. Guichard, and V. Hamel. 2020. WDR90 is a centriolar microtubule wall protein important for centriole architecture integrity. eLife.

      Steib, E., R. Tetley, R.F. Laine, D.P. Norris, Y. Mao, and J. Vermot. 2022. TissUExM enables quantitative ultrastructural analysis in whole vertebrate embryos by expansion microscopy. Cell Rep Methods. 2:100311.

      Sydor, A.M., E. Coyaud, C. Rovelli, E. Laurent, H. Liu, B. Raught, and V. Mennella. 2018. PPP1R35 is a novel centrosomal protein that regulates centriole length in concert with the microcephaly protein RTTN. Elife. 7.

      Tiryaki, F., J. Deretic, and E.N. Firat-Karalar. 2022. ENKD1 is a centrosomal and ciliary microtubule-associated protein important for primary cilium content regulation. FEBS J. 289:3789-3812.

      Tsekitsidou, E., C.J. Wong, I. Ulengin-Talkish, A.I.M. Barth, T. Stearns, A.C. Gingras, J.T. Wang, and M.S. Cyert. 2023. Calcineurin associates with centrosomes and regulates cilia length maintenance. J Cell Sci. 136.

      Van de Mark, D., D. Kong, J. Loncarek, and T. Stearns. 2015. MDM1 is a microtubule-binding protein that negatively regulates centriole duplication. Mol Biol Cell. 26:3788-3802.

      Yang, C.H., C. Kasbek, S. Majumder, A.M. Yusof, and H.A. Fisk. 2010. Mps1 phosphorylation sites regulate the function of centrin 2 in centriole assembly. Mol Biol Cell. 21:4361-4372.

      Ying, G., J.M. Frederick, and W. Baehr. 2019. Deletion of both centrin 2 (CETN2) and CETN3 destabilizes the distal connecting cilium of mouse photoreceptors. J Biol Chem. 294:3957-3973.

  4. Aug 2022
    1. 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

      Reply to the reviewers

      1. General Statements

      It is the common view of all three reviewers that we have not utilized adequate in vitro/biochemical evidence to support the idea that SATB1 protein undergoes liquid-liquid phase separation. We do agree with the reviewers that our manuscript lacks biochemical evidence to support such notion. Though we find it quite interesting and we would like to suggest for the first time in the field of chromatin organization and function, based upon the action of SATB1, that this protein does exist in at least two polypeptide isoforms (764 and 795 amino acids long) which display different phase separation propensity and therefore confer different actions in regulating the (patho)physiological properties of a murine T cell.

      Every single research group that works on SATB1, considered so far only a single protein isoform, that is, the shorter isoform of 764 amino acids and no tools, such as isoform-specific antibodies have been developed to discriminate the two isoforms and thus being able to assign unique functions to each isoform. We do understand that such a report, suggesting the presence of two protein isoforms, with potentially quite diverse functions, would question (not necessarily by the authors of this manuscript, since no such comment is included in our manuscript) the conclusions drawn in the literature assigning all biochemical properties to a single, short isoform of SATB1. Moreover, all the genetically modified mice that have been analyzed so far (including our group), deleted both Satb1 isoforms. Our future research approaches should, from now on, consider unraveling the isoform-specific functions of SATB1 and their involvement in physiology and disease. This could also deem useful to explain the quite diverse, both positive and negative effects of SATB1 in transcription regulation. Another major objection of the reviewers was that we should provide cumulative supporting evidence for the existence of the long SATB1 isoform, or at least evaluate the specificity of our custom-made antibody.

      Taking under consideration the aforementioned constructive criticism of the three reviewers we would like to perform (most of the suggested experiments have already been performed) additional experiments to support our claims in the manuscript. These experiments are described below as a point-by-point reply to each point raised by the reviewers.

      In line with the aforementioned rationale, we propose the title of our manuscript to change into “Two SATB1 isoforms display different phase separation propensity”, if our manuscript is considered for publication.

      1. Description of the planned revisions

      **Reviewer #1**:

      4) Lack of in vitro reconstitution experiments with purified long and short SATB1

      **PLANNED EXPERIMENT #1**

      We do realize this shortcoming of our work. We have to note that purifying recombinant SATB1 protein is quite a challenging task, yet we 1. cloned both Satb1 cDNAs for the long and short isoforms, 2. we successfully expressed both proteins in great quantity and quality and we are willing to perform these experiments if our work is considered for publication.

      This proposed experiment has also been requested by Reviewers #2 and #3.

      **Reviewer #2**:

      1. Moreover, an important and direct experiment would be to clone the long isoform in a suitable vector and overexpress in the cell line (as done for the canonical isoform in Supp Fig 1a). This would unequivocally show the efficacy of the antibody and thus the following usage of the same for various assays.

      **PLANNED EXPERIMENT #2**

      This is a great suggestion. We have cloned the long and short Satb1 cDNAs in pEGFP-C1 vector. We will transfect these plasmids in NIH 3T3 fibroblasts and we will perform Western blot analysis, utilizing the antibody raised against the extra 31 amino acids long peptide present only in the long SATB1 isoform, for the following samples: 1. NIH-3T3 whole cell protein extracts, 2. protein extracts from NIH 3T3 fibroblasts transiently transfected with the pEGFP-C1 plasmid, 3. protein extracts from NIH 3T3 fibroblasts transiently transfected with the pEGFP-long_Satb1_ plasmid and 4. protein extracts from NIH 3T3 fibroblasts transiently transfected with the pEGFP-short_Satb1_ plasmid.

      This experiment will consist another proof regarding the specificity of the antibody raised against the extra 31 amino acids long peptide present only in the long SATB1 isoform.

      **Minor comments:**

      1. On pg 6, related to Figure 1, the authors mention 'It should also be noted that when investigating the SATB1 protein levels, we have to bear in mind that the antibodies targeting the N-terminus of SATB1 protein cannot discriminate between the short and long isoforms'. The authors reason that their sizes are too close. It is indeed possible, and widely studied in biochemistry to assess various factors on protein migration (such as PTMs). The authors should validate this aspect (as it is important as per their premise) and perform separation based on charge as well and also use a commercial antibody to validate the same.

      (Experiments already performed)

      We have adapted the text so that it does not imply that the two isoforms cannot be separated by size. This part in lines 102-107 then reads: “It should also be noted that when investigating the SATB1 protein levels, we have to bear in mind that the antibodies targeting the N-terminus of SATB1 protein cannot discriminate between the short and long isoforms, thus we can only compare the amount of the long SATB1 isoform to the total SATB1 protein levels in vivo conditions. To overcome this limitation and to specifically validate the presence of the long SATB1 protein isoform in primary murine T cells, we designed a serial immunodepletion-based experiment (Fig. 1e, Supplementary Fig. 1a).”

      Moreover, in the revised version of the manuscript we now provide a number of additional proofs supporting the presence of the long isoform and also the specificity of the long isoform-specific antibody. As evident in the text cited above, in the revised Fig. 1e,f and revised Supplementary Fig. 1a,b; we present two immunodepletion experiments which should alone address the Reviewer’s concerns. Moreover, we added Supplementary Fig. 1c; demonstrating that the long isoform-specific antibody does not detect any protein in cells with conditionally depleted SATB1 (Satb1_fl/fl_Cd4-Cre+), supporting its specificity. The custom-made and publicly available antibodies targeting all SATB1 isoforms were also verified in Supplementary Fig. 1d. Moreover, the long isoform and all isoform antibodies display similar localization in the nucleus (Supplementary Fig. 1e; their co-localization based on super-resolution microscopy is also quantified in Supplementary Fig. 5a).

      In our accompanying revised manuscript Zelenka et al., 2022 (https://doi.org/10.1101/2021.07.09.451769), we will provide yet another piece of evidence, consisting of bacterially expressed short and long SATB1 protein isoforms detected by western blot using either the long isoform-specific or the non-selective all SATB1 isoform antibodies.

      **PLANNED EXPERIMENT #3**

      Although we think that in the revised version of the manuscript, we have provided enough proof about the existence of the long isoform in primary murine thymocytes we would like to try the following approach as suggested by this Reviewer.

      The pI of the two SATB1 isoform is quite similar. The pI of the short SATB1 isoform is 6.09 and for the long SATB1 isoform is 6.18. We will perform 2D PAGE coupled to Western blotting utilizing the antibodies detecting the long and all SATB1 isoforms. Given the fact that both isoforms are post-translationally modified to a various degree, it will be extremely difficult to discriminate between the long and short unmodified versus the long and short post-translationally modified proteins especially in the absence of a specific antibody only for the short isoform.

      **Reviewer #3**

      1. Hexanediol is another assay frequently used in phase-separation studies. However, hexanediol has many deleterious effects on the cell, even at a fraction of the concentration normally used in phase-separation studies. Authors should show controls of cell viability, control proteins that do not phase-separate, etc. See https://www.jbc.org/article/S0021-9258(21)00027-2/fulltext.

      Secondly, hexanediol treatment should cause phase-separated protein aggregates to disperse. It is difficult to determine from the images whether or not the aggregates actually disperse or there is just less protein. In any case, small aggregates remain even after treatment, and this appears different from most other hexanediol experiments reported in the literature where the signals become more dispersed and uniform. This is likely because the samples are fixed.

      One of the main features of using hexanediol in phase-separation is to show that upon washout, LLPS aggregates can reform. Because the cells are fixed, the critical aspect of this assay is not performed. A washout and LLPS recovery would control for cell viability issues described above and would provide the opportunity to show that total SATB1 protein levels did not change, but its distribution did, which is the essence of this assay in the context of LLPS. This review from the Tjian group is very informative and may be a good resource:

      http://genesdev.cshlp.org/content/33/23-24/1619

      In line with our reply to point #1 of this Reviewer (page 26 of this document), we should again emphasize that we utilized the hexanediol treatment in primary murine developing T cells as this is the only way to investigate the properties of SATB1 speckles under physiological conditions. This also explains why some small insoluble structure remains after the hexanediol treatment. Note that under physiological conditions, there is a contribution of several protein variants (such as differential PTMs) out of which some will tend to form more stable structures while others could undergo LLPS. It is not clear how the washout experiment could be applied in the primary cell conditions that include cell fixation as the heterogeneity and big variation among cells would make such data analysis highly unreliable.

      **PLANNED EXPERIMENT #1**

      As we answered to point #4 of Reviewer 1 (page 2), we propose the following experiment. Although the purification of recombinant SATB1 protein is quite a challenging task, yet we 1. cloned both Satb1 cDNAs for the long and short isoforms, 2. we successfully expressed both proteins in great quantity and quality and we are willing to perform in vitro reconstitution experiments if our work is considered for publication.

      1. The major difference between the long and short isoform of SATB1 is the 31aa segment within the IDR. However the authors find that neither the long or short isoform SATB1 forms LLPS aggregates, and the IDR alone forms aggregates in the cytoplasm (Fig5) but they do not respond to Cry2 light activation. When forced to localize to the nucleus, it does not form aggregates as well (Fig6). The short isoform also did not form any aggregates. These results seem to argue against any isoform specific phase-separation. This experiment seems critical for the story, yet it does not support their overall conclusions. The authors might consider using a different cell line or perhaps do an in vitro assay using purified protein.

      I am not certain what to make of the cytoplasmic aggregation, which appears to not form upon localization to the nucleus. Because of this, it is difficult to place weight on the significance of the S635A mutation and the role that a phosphorylation of SATB1 contributes to phase-separation, let alone function There are many additional points of concern, but the ones listed above are perhaps the most significant in terms of the overall conclusions of the paper.

      In Fig. 5c we show that the full length long SATB1 isoform often aggregates unlike the short isoform. These data are accompanied with the results for the IDR region, where the situation is even more obvious (Fig. 5f,g). However, in the latter, we have to bear in mind the absence of the multivalent N-terminal part of the protein which seems to be essential for the overall phase behavior of the protein as indicated in Fig. 4b,c.

      **PLANNED EXPERIMENT #1**

      To further support LLPS of SATB1, we are considering performing the following in vitro experiment, as we answered to point #4 of Reviewer 1 (page 2). Although the purification of recombinant SATB1 protein is quite a challenging task, yet we 1. cloned both Satb1 cDNAs for the long and short isoforms, 2. we successfully expressed both proteins in great quantity and quality and we are willing to perform in vitro reconstitution experiments if our work is considered for publication.

      1. Description of the revisions that have already been incorporated in the transferred manuscript

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

      This paper looks at an important nuclear matrix protein SATB1, which is a well known global chromatin organizer and help chromatin loop attach to the nuclear matrix. The paper starts with identification of novel short and long form of SATB1. Both the isoform consist of a prion like low complexity domains, but the long isoform additionally contain an extra EPF domain next the Prion like low complexity domain. The paper reports that in murine cells the long isoform is 3-4 fold more abundant than the short isoform. By using STED microscopy they show SATB1 foci lie next to transcription sites in the nucleus. They conclude by looking at the spherical shape of the SATB1 foci and the susceptibility of SATB1 staining after 1,6 hexanediol treatment that SATB1 forms the small foci in the nucleus due to LLPS. The authors also use RAMAN spectroscopy to conclude a change in nuclear chemical space in absence of SATB1 but without much explanation about which chemical bond or nuclear sub structure change correspond to the change in principal component analysis from Raman spectroscopy. The authors use the light inducible aggregation cry2 tag with the PrD domain of SATB1 and compare it with the Cry2-FUS-LC domain to conclude that the SATB1 LC domain can undergo LLPS. The authors hint at involvement of RNA and also DNA in the LLPS of the SATB1 but without going into any detail. Reviewer: The paper reports that in murine cells the long isoform is 3-4 fold more abundant than the short isoform.

      Actually, in page 5 (lines 94-96) of the manuscript we write: “We confirmed that in murine thymocytes the steady state mRNA levels of the short Satb1 transcripts were about 3-5 fold more abundant compared to the steady state mRNA levels of the long Satb1 transcripts (Fig. 1d).” Although the steady state mRNA levels of the long isoform are less abundant compared to the shorter isoforms, the long isoform protein levels are almost comparable to the short isoform as deduced based on immunofluorescence experiments. Moreover, Using our two immunodepletion experiments we quantified the difference, estimating the long isoform being 1.5× to 2.62× less abundant than the short isoform (Fig. 1f and Supplementary Fig. 1b; compare lanes 2 & 3 at the lower panel). • Regarding the RAMAN spectroscopy experiments please see Minor Comment #1 of this Reviewer (page 10).

      The key conclusions of the paper are- A) SATB1 undergoes LLPS. But this conclusion is drawn after correlative experiments as detailed below-

      This conclusion is indeed made based on correlative experiments only for the primary murine T cells, which do not allow for any targeted experiments. However, the use of in vitro cell lines allowed us to validate these findings using the optogenetic approaches, utilizing additional experimentation.

      1) observation of spherical punctae by STED-which could also seem spherical due to their small size. The resolution limit achieved by the STED microscopy used in this paper is not determined or mentioned clearly.

      In the revised version of the manuscript, we have specified the resolution of our systems, for STED in Lines 745-746: ”This system enables super-resolution imaging with 35 nm lateral and 130 nm axial resolution.” and for SIM in Lines 759-761: “Images were acquired over the majority of the cell volume in z-dimension with 15 raw images per plane (five phases, three angles), providing ~120-135 nm lateral and ~340-350 nm axial resolution for 488/568 nm lasers, respectively.” The size of the observed speckles is thus above the resolution limit with sizes ranging between 40-80 nm.

      The resolution of our systems is routinely verified by the following methods: The resolution of our OMX (SIM-3D) system was tested using ARGO-SIM slide containing a pattern of 36 µm long lines with gradually increasing spacing ranging from (left to right) 0 to 390 nm, with a step of 30 nm (Fig. 1 below). Our SIM system was able to clearly resolve two lines separated by 120 nm.

      2) No live cell FRAP experiment with fluorescent SATB1 long or short isoform to show that these foci are liquid like

      We did perform FRAP experiments for the SATB1 N-terminus optogenetic construct as demonstrated in Fig. 4f. We did not perform FRAP in the primary murine T cells as this is not technically feasible without creating a new mouse line with fluorescently labeled protein. In the revised version of the manuscript, we additionally performed FRAP experiments for the full length short and long isoform of SATB1 labeled with EGFP and transfected into the NIH-3T3 cell line (Supplementary Figure 6f).

      5) LLPS is strongly coupled to the cellular concentration of the proteins. Authors should quantify the cellular concentration of the long and short isoform in the cells.

      We did consider protein concentration in our analyses of optogenetic constructs in Fig. 4b,d,e and Supplementary Fig. 6a,b,c. Quantifying the physiological cellular concentration of short and long SATB1 protein isoforms in primary T cells is impossible due to the inherent inability to discriminate between the isoforms by two antibodies, in the absence of Satb1 isoform-specific knockout mice.

      However, an approximation of the cellular concentration can be obtained from our immunodepletion experiments. On top of the original immunodepletion experiment that we now present in Supplementary Fig. 1a,b; in the revised version of the manuscript we have repeated the experiment in Fig. 1e,f. Comparison of the two bands for the long and short SATB1 isoforms in the lower panel of the western blot figures suggest that the long SATB1 isoform protein levels are 1.5× to 2.62× less abundant than the short isoform, according to the original and new immunodepletion experiment, respectively. This is now also included in the main text in Lines 110-116: “This experiment can also be used for approximation of the cellular protein levels of SATB1 isoforms in primary murine thymocytes. Comparison of the two bands for long (lane 2) and short SATB1 (lane 3) isoform in the lower panel of Fig. 1f and Supplementary Fig. 1b, suggests that the long SATB1 isoform protein levels may be about 1.5× to 2.62× less abundant than the short isoform, according to the two replicates of our immunodepletion experiment, respectively.”

      Major conclusion B)- SATB1 regulates transcription and splicing.

      This was also shown previously and in this paper they show the close proximity of the transcription site and SATB1 foci by microscopy. Hexanediol treatment which lead to loss of colocalization between FU foci and SATB1 is also taken as an evidence in regulation of transcription is not right as the transcription foci itself can be dissolved using 1,6 Hexanediol. Although the rate of transcription is not measured quantitatively.

      As mentioned in comment #3 (page 29) of this Reviewer, unfortunately there is no better tool to investigate these questions in primary cells than using microscopy approaches in conjunction with hexanediol treatment. However, we should also note that there is an accompanying manuscript from our group that is currently being under revision in another journal (preprint available: Zelenka et al., 2021; https://doi.org/10.1101/2021.07.09.451769). In the preprint manuscript, we showed that: 1. the long SATB1 isoform binding sites have increased chromatin accessibility than what expected by chance (Fig. 3b), 2. there is a drop in chromatin accessibility at SATB1 binding sites in Satb1 cKO mouse (Fig. 3c) and 3. this drop in chromatin accessibility is especially evident at the transcription start sites of genes (Supplementary Fig. 1i)

      We believe that, together these data suggest a direct involvement of SATB1 in transcription regulation. Also note the vast transcriptional deregulation that occurs in Satb1 cKO T cells, affecting the expression of nearly 2000 genes (Fig. 2f, this revised manuscript). That is why we believe that the co-localization analysis, using super-resolution microscopy, presented in Fig. 2c and quantified in Fig. 3g, represents a nice additional support to our claims. Moreover, in the revised version of the manuscript we now present a positive correlation between SATB1 binding and deregulation of splicing (Supplementary Fig. 4d) which also supports its direct involvement in the regulation of transcriptional and co-transcriptional processes.

      In the revised version of the manuscript we have made this clear in Lines 182-194: “Satb1 cKO animals display severely impaired T cell development associated with largely deregulated transcriptional programs as previously documented19,37,38. In our accompanying manuscript19, we have demonstrated that long SATB1 isoform-specific binding sites (GSE17344619) were associated with increased chromatin accessibility compared to randomly shuffled binding sites (i.e. what expected by chance), with a visible drop in chromatin accessibility in Satb1 cKO. Moreover, the drop in chromatin accessibility was especially evident at the transcription start site of genes, suggesting that the long SATB1 isoform is directly involved in transcriptional regulation. Consistent with these findings and with SATB1’s nuclear localization at sites of active transcription, we identified a vast transcriptional deregulation in Satb1 cKO with 1,641 (922 down-regulated, 719 up-regulated) differentially expressed genes (Fig. 2f). Specific examples of transcriptionally deregulated genes underlying SATB1-dependent regulation are provided in our accompanying manuscript19. Additionally, there were 2,014 genes with altered splicing efficiency (Supplementary Fig. 4d-e; Supplementary File 3-4). We should also note that the extent of splicing deregulation was directly correlated with long SATB1 isoform binding (Supplementary Fig. 4d).”

      Major conclusion C)-Post transcriptional modification is important for SATB1 function.

      This point is just barely touched upon in the last figure of the paper

      We would not call the identification of the novel phosphorylation site as a main conclusion of our manuscript. Though, it is already known that posttranslational modifications of SATB1 are important for its function as they can function as a molecular switch rendering SATB1 into either an activator or a repressor (Kumar et al., 2006; https://doi.org/10.1016/j.molcel.2006.03.010).

      In the revised manuscript, we support the effect of serine phosphorylation on the DNA binding capacity of SATB1 by another experiment. We have performed DNA affinity purification experiments utilizing primary thymocyte nuclear extracts treated with phosphatase (Supplementary Fig. 7b). We found that SATB1’s capacity to bind DNA (RHS6 hypersensitive site of the TH2 LCR) is lost upon treatment with phosphatase (Supplementary Fig. 7c). These results are in line with the data presented in Supplementary Fig. 7d, indicating the lost ability of SATB1 to bind DNA upon mutating the discovered phosphorylation site S635. Given the importance of posttranslational modifications of proteins on LLPS, we found it relevant to include it in our manuscript. Even more so, when we identified SATB1 aggregation, upon mutation of this phospho site (Fig. 6d).

      Overall I find that the major conclusion-point A and B, is based on very indirect experiments and needs much more convincing data and the role of SATB1 LLPS in cells should be demonstrated more rigorously. And conclusion C is barely described and needs a lot more cell biological and genetic evidence.

      One of the major assets of our work is that most of our data are based on the analysis of primary murine T cells and thus investigating the biological roles of the endogenous SATB1 protein, under physiological conditions. We apologize that we did not make it clear to this Reviewer, that our system has certain inherent limitations due to the utilization of primary cells.

      I do not recommend publishing the paper in current state. The story needs much more experiment to convincingly prove the major conclusions. Further, the MS needs more careful thinking and presentation to make it streamlined.

      We hope that in the revised version we have significantly improved the quality of our manuscript by implementing the suggested changes.

      Minor comments: One of the major flaw of the paper is the use too many techniques without proper explanation. E.g. use of STED and RAMAN microscopy need controls and explanation on what is being quantified. The use of Raman microscopy to quantify the nuclear environment of nucleus is not related to the chromatin organization or LLPS of SATB1 at all. And no information is provided at all which aspect of nuclear organization is being measured in Raman and what it means for the LLPS of SATB1.

      We do provide quite a thorough explanation of Raman spectroscopy and the underlying quantification in Lines 224-231: “we employed Raman spectroscopy, a non-invasive label-free approach, which is able to detect changes in chemical bonding. Raman spectroscopy was already used in many biological studies, such as to predict global transcriptomic profiles from living cells42, and also in research of protein LLPS and aggregation43–47. Thus we reasoned that it may also be used to study phase separation in primary T cells. We measured Raman spectra in primary thymocytes derived from both WT and Satb1 cKO animals and compared them with spectra from cells upon 1,6-hexanediol treatment. Principal component analysis of the resulting Raman spectra clustered the treated and non-treated Satb1 cKO cells together, while the WT cells clustered separately (Fig. 3h).” We also do provide controls as the method was performed on both treated and untreated WT and Satb1 cKO cells.

      Regarding the RAMAN spectroscopy experiments we now provide more information on the changes of chemical bonds altered between wild type and Satb1 cKO thymocytes. Following principal component analysis, we have extracted the two main principal components that were used for the clustering of our data. The differences are presented in Supplementary Fig. 5d.

      We do realize that RAMAN spectroscopy, although a quite novel approach utilized to study LLPS, has not been used to study LLPS in live cells. If deemed proper we are willing to avoid presenting these results in this manuscript.

      Similarly for Hexanediol treatment, duration of treatment is missing. Hexanediol can also dissolve the liquid like transcription foci. And hence a decrease in correlation between SATB1 foci and FU foci cannot be taken as a measure of SATB1 foci connection to transcription alone

      The duration of hexanediol treatment was 5 minutes as presented in Line 724 and in the revised version of the manuscript also in Lines 1206-1207. We should also note that additionally, we performed experiments with different hexanediol concentrations and timing varying from 1 minute to 10 minutes with results consistent with the data presented.

      It is not very clear how many times the STED or Raman microscopy is done on how many samples and biological replicates. Similarly for RNA sequencing number of samples and description of controls are missing. Also if the sequencing data is made publicly available is not clear.

      Data availability is clearly stated in Lines 506-509: “RNA-seq experiments and SATB1 binding sites are deposited in Gene Expression Omnibus database under accession number GSE173470 and GSE173446, respectively. The other datasets generated and/or analyzed during the current study are available upon request.”

      The Reviewer’s token is “wjwtmeeeppovzqx”.

      RNA sequencing was performed in a biological triplicate for each genotype as stated in the GEO repository and now also in Line 566 of the revised manuscript.

      In Lines 180-181, we also state that it was performed on Satb1 cKO animals and WT mice as a control: “we performed stranded-total-RNA-seq experiments in wild type (WT) and Satb1fl/flCd4-Cre+ (Satb1 cKO) murine thymocytes”.

      In Lines 739-740, we now also state that all imaging approaches were performed on at least two biological replicates (different mice) and please also note the fact that all findings were based on data from both STED and 3D-SIM methods, allowing to minimize detection of artifacts. In the Raman spectroscopy figure, each point represents measurements from an individual cell and for each condition we used 2-5 biological replicates (Lines 831-832 & Line 1169).

      Similarly, in Lines 129-132 we provided a quite detailed description of differences between STED and 3D-SIM, even though these techniques are not that rare as Raman spectroscopy in biology research.

      Additional control is needed to report the resolution limit of Superresolution techniques-STED and 3D-SIM systems used by them.

      We have already provided this information in our reply to comment #1 of this Reviewer (pages 6-7): In the revised version of the manuscript, we have specified the resolution of our systems, for STED in Lines 745-746: ”This system enables super-resolution imaging with 35 nm lateral and 130 nm axial resolution.” and for SIM in Lines 759-761: “Images were acquired over the majority of the cell volume in z-dimension with 15 raw images per plane (five phases, three angles), providing ~120-135 nm lateral and ~340-350 nm axial resolution for 488/568 nm lasers, respectively.” The resolution of our systems is routinely verified by the following methods: The resolution of our OMX (SIM-3D) system was tested using ARGO-SIM slide containing a pattern of 36 µm long lines with gradually increasing spacing ranging from (left to right) 0 to 390 nm, with a step of 30 nm (Fig. 1 below). Our SIM system was able to clearly resolve two lines separated by 120 nm.

      Would be very helpful if the zonation was plotted for the FluoroUridine (FU) also to show that Zone1 (heterochromatin) is completely depleted of FU, and is present in other regions.

      In the revised version of the manuscript, we performed the suggested analysis and in Supplementary Fig. 3a we now show that indeed FU is significantly less localized to Zone 1 (heterochromatin) and has the most abundant localization in Zones 3 and 4, similar to the localization of SATB1 protein, as demonstrated in Fig. 2b.

      Scale bar needed figure 3d

      In the revised version of the manuscript, we included scale bars which are both 0.5 µm (line 1213).

      Perfectly rounded SATB1 foci- this does not mean LLPS. For LLPs measurement, protein condensate dynamics measurement by FRAP or fusion experiments is required. What is the size of condensates? and cellular concentration of SATB1? Will SATB1 undergo LLPS in vitro at similar concentrations? does SATB1 interact with DNA or RNA to undergo LLPS ?

      We toned down this sentence which now reads: “Here we demonstrated its connection to transcription and found that it forms spherical speckles (Fig. 1g), markedly resembling phase separated transcriptional condensates. (Lines 200-202)”.

      Moreover, as explained in earlier replies to comments of this Reviewer, we cannot perform FRAP on primary murine T cells without generating a new mouse line. We did, however, use FRAP and other in vitro approaches including visualization of droplet fusion in ex vivo experiments utilizing cell lines. Moreover, we are willing to demonstrate the LLPS properties of SATB1 on in vitro purified SATB1 protein as indicated in the suggested experiment of Point#4 (page 2).

      After careful reading of the MS I conclude that the main conclusions of the paper are very preliminary and need much more detailed experiments. So does not qualify to get published at all at this stage.

      **Reviewer #1 (Significance)**:

      The present manuscript tries to connect the phase separation of SATB1 to understanding the mechanism of SATB1 function in cells. One of the major hallmarks of phase separation is dynamic, liquid-like behaviour and in absence of these measurements, it is very difficult to say that the current manuscript has made any contribution to showing that SATB1 can phase separate.

      The presence of 2 isoforms of SATB1 is a novel finding and the paper could have focused more on this. E.g. elucidate expression of the isoform during thymocyte development and maturation.

      As a reviewer my expertise are cell biology experiments, microscopy, in vitro reconstitution assays, RNA binding proteins, RNA and RBP condensate formation. And I feel that the reconstitution experiments are an important tool for understanding phase behaviour of proteins and also to gauge if this behaviour can occur or not in cellular concentration and conditions.

      I do not have sufficient expertise in Raman microscopy and hence the information provided in the MS on this part was not enough to understand the experiment and conclusions drawn from it.

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

      The authors have reported the existence of a 'long' SATB1 isoform which also undergoes LLPS. The authors tried to draw multiple comparisons and pointed out distinction between phase properties of SATB1 isoforms. The authors also touch upon two functional roles of SATB1. Although a wide array of assays are used, the data presented and hence the manuscript makes multiple transitions into disparate hypotheses without diving deep into a single hypothesis. As a result, the connections drawn are unclear, and do not converge at best. The authors have used number of techniques, however, the results do not support their conclusions and they appear hastily drawn. It is not clear why the authors jump from one context to the other, discussing LLPS first, then transcription, splicing, post-translational modification and finally cancer. The link between all of these isn't clear and not fully supported by data. It appears that the authors wish to focus on Satb1's physiological role in development, hence the data on breast cancer is confusing. Thus, this work suffers from multiple pitfalls. Specific comments are given below:

      Major comments 1. Importantly, in Fig 1d, there is no statistics shown. There is no mention of number of replicates as well in the legends. Proper statistical evaluation is critical for interpreting this result.

      Please note that Fig. 1d only serves as a control to the sequencing experiment in Fig. 1b. In Line 566, we now state that for the RNA-seq: “A biological triplicate was used for each genotype.” To validate these data, we further designed a RT-qPCR experiment which was performed on three technical replicates from a male and female mouse. We now state this in Line 636. For the low number of samples, statistical tests are not accurate but we still added t test into the figure Fig. 1d and specified it also in the figure legend in Line 1169-1170.

      1. Figure 1f presents one of the weakest evidences in the manuscript. There are a number of corrections needed. Firstly, being their major and only validation figure for their custom antibody, the immunoblot is not clean, bands are fuzzy. Importantly, as the authors claim that the antibody is highly specific to 'long' SATB1, after the IP there should be only a single band (like input) of Satb1 long. But that does not seem to be the case, rather an array of bands are visible below (lane 2 top panel). This could easily mean that the shorter isoforms or non-specific protein bands are also pulled down with the 'long' form specific antibody. Therefore, raising a critical concern regarding the specificity of the antibody.

      • The long antibody was raised in mice inoculated with the extra peptide present in the long isoform only. Therefore, the capacity of this antibody precipitating the shorter isoforms, which do not express the sequence of the extra peptide (EP, Figure 1a) in not possible. • We have repeated the immunodepletion experiment and we now provide the results in Fig. 1f and Supplementary Fig. 1b. The western blot in Fig. 1f is now cleaner and supports quite convincingly the presence of a long SATB1 isoform. Given the lack of isoform-specific knockouts which we could utilize to immunoprecipitate or detect the different isoforms in a single cell (or cell population), the utilized approach of immunodepletion and subsequent western blotting is the approach we thought of implementing. • As shown in Fig. 1f and Supplementary Figure 1b, the long isoform SATB1 antibody has the capacity to recognize the long isoform in murine thymocyte protein extracts but not the short SATB1 isoform (please compare lane 3 in the two western blots utilizing either the antibody for the long isoform -top panel - or the antibody that detects both isoforms (lower panel). • We have performed Immunofluorescence experiments utilizing the antibody detecting the long SATB1 isoform in thymocytes isolated from either C57BL/6 or Satb1 cKO mice. The antibody is specific to the SATB1 protein since there is no signal in immunofluorescence experiments utilizing the knockout cells (Supplementary Figure 1c). • We have performed Immunofluorescence experiments utilizing thymocytes and the antibody detecting the long SATB1 or a commercially available antibody detecting all SATB1 isoforms. The pattern of SATB1 subnuclear localization is similar for both antibodies (Supplementary Figure 1e). • In our accompanying revised manuscript Zelenka et al., 2022 (https://doi.org/10.1101/2021.07.09.451769), we provide yet another piece of evidence, consisting of bacterially expressed short and long SATB1 protein isoforms detected by western blot using either the long isoform-specific or the non-selective all SATB1 isoforms antibodies. • Regarding the additional bands detected in the immunoprecipitation experiment presented in the original Supplementary Figure 1b (lane 2), it is not surprising that additional bands appear in a sample of protein extracts that is used for several hours for the immunoprecipitation experiments, while the “input” sample simply denotes protein extract that is frozen at -80oC right after the preparation of protein extracts until use. It is well-established that SATB1 is the target of proteases which might as well be active during the immunoprecipitation steps (2 consecutive immunoprecipitation steps take place). Therefore, the immunoprecipitated material cannot necessarily be a copy of the input material displaying a single protein band even if protease inhibitors are included in the buffers.

      Taken together the experiments described here we showed that the antibody raised against the extra 31 aa long peptide, present only in the long SATB1 isoform, is specific for this isoform.

      1. Related to Fig. 2 a, the authors state on Pg 5, '....the euchromatin and interchromatin regions (zones 3 & 4, Fig. 2a, b).' Although the DAPI correlation seems clear, there is no mention on how they reached the above said correlation. They should at least show a parallel speckle staining for HP1 or signature modification such as H3K4me9 STEDs for making supporting such a claim. DAPI alone is not sufficient. The authors should rectify the text thoroughly for many such interpretations without validation/reference or provide relevant data.

      This is a great suggestion we have again taken under consideration and we added the following experiments and the appropriate changes in the revised version of our manuscript. • We modified the text and added a reference to Miron et al., 2020 (https://doi.org/10.1126/sciadv.aba8811) supporting our claims regarding SATB1 localization in relation to DAPI staining. • We have also added new microscopy images for HP1, H3K4me3 and fibrillarin staining and quantified the localization of FU-stained sites of active transcription in nuclear zones, to further support our claims. • This whole modified part in Lines 139-167 then reads: “ “The quantification of SATB1 speckles in four nuclear zones, derived based on the relative intensity of DAPI staining, highlighted the localization of SATB1 mainly to the regions with medium to low DAPI staining (zones 3 & 4, Fig. 2a, b). A similar distribution of the SATB1 signal could also be seen from the fluorocytogram of the pixel-based colocalization analysis between the SATB1 and DAPI signals (Supplementary Fig. 2a). SATB1’s preference to localize outside heterochromatin regions was supported by its negative correlation with HP1β staining (Supplementary Fig. 2b). Localization of SATB1 speckles detected by antibodies targeting all SATB1 isoforms and/or only the long SATB1 isoform, revealed a significant difference in the heterochromatin areas (zone 1, Fig. 2b), where the long isoform was less frequently present (see also Fig. 2a and Fig. 3c). Although, this could indicate a potential difference in localization between the two isoforms, due to the inherent difficulty to distinguish the two based on antibody staining, we refrain to draw any conclusions. The prevailing localization of SATB1 corresponded with the localization of RNA-associated and nuclear scaffold factors, architectural proteins such as CTCF and cohesin, and generally features associated with euchromatin and active transcription32. This was also supported by colocalization of SATB1 with H3K4me3 histone mark (Supplementary Fig. 2c), which is known to be associated with transcriptionally active/poised chromatin. Given the localization of SATB1 to the nuclear zones with estimated transcriptional activity32 (Fig. 2b, zone 3), we investigated the potential association between SATB1 and transcription. We unraveled the localization of SATB1 isoforms and the sites of active transcription labeled with 5-fluorouridine. Sites of active transcription displayed a significant enrichment in the nuclear zones 3 & 4 (Supplementary Fig. 3a), similar to SATB1. As detected by fibrillarin staining, SATB1 also colocalized with nucleoli which are associated with active transcription and RNA presence (Supplementary Fig. 3b). Moreover, we found that the SATB1 signal was found in close proximity to nascent transcripts as detected by the STED microscopy (Fig. 2c). Similarly, the 3D-SIM approach indicated that even SATB1 speckles that appeared not to be in proximity with FU-labeled sites in one z-stack, were found in proximity in another z-stack (Supplementary Fig. 3c). Additionally, a pixel-based colocalization of SATB1 and sites of active transcription is quantified later in the text in Fig. 3g, supporting their colocalization.”

      1. The authors mention, '...of the different SATB1 isoforms, uncovered by the use of the two different antibodies, relied in the heterochromatin areas (zone 1), where the long isoform was less frequently...' There is no supporting figure number mentioned. The authors need to show a zone-by-zone comparison images for 'all iso' vs 'long' iso of SATB1. Just to reiterate, there is a need for a heterochromatin mark to unambiguously call out the distinction.

      We should remind that there is an inherent difficulty to accurately compare localization of short and long SATB1 isoforms in primary cells, especially due to the lack of Satb1 isoform-specific knockout mice. There is no way to detect only the short isoform in these primary cells as there are only antibodies targeting the long or all SATB1 isoforms. Therefore, we cannot set up additional experiments probing these questions.

      In line with this, in the revised version of the manuscript, we toned down our statements regarding the differential localization of the two isoforms in primary cells. We only refer to it as an indication and we support it by adding references to the relevant figures. This part now reads: “Localization of SATB1 speckles detected by antibodies targeting all SATB1 isoforms and/or only the long SATB1 isoform, revealed a significant difference in the heterochromatin areas (zone 1, Fig. 2b), where the long isoform was less frequently present (see also Fig. 2a and Fig. 3c). Although, this could indicate a potential difference in localization between the two isoforms, due to the inherent difficulty to distinguish the two based on antibody staining, we refrain to draw any conclusions. (Lines 145-150)”

      1. On the same lines, '....Given the localization of SATB1 to the nuclear zones with estimated transcriptional activity (Fig. 2b, zone 3)....' How was the region labelled as transcriptionally active? For the statistical analysis of speckle count for the two antibodies' staining, the claim posited is a bit bigger. This could simply be true for that cell. The authors thus need to statistically analyse the speckle counts for multiple cells. This needs to be done for all imaging statistics done in multiple figures throughout the manuscript.

      As mentioned in our reply to the two previous comments of this Reviewer, transcriptional activity in relation to the nuclear zonation is well established in the literature. To make this clear, we have now added the reference to Miron et al., 2020 (https://doi.org/10.1126/sciadv.aba8811) supporting our claims and additionally we have also included HP1, H3K4me3 and fibrillarin staining and quantification of FU signal in the nuclear zones. Moreover, it is not clear to which particular cell the comment refers to. The presented dots in Fig. 2b represent individual cells and the relative proportions of speckles in each nuclear zone are plotted on the y axis. In the revised version of the manuscript, we added into the figure the number of cells scored and we adapted the figure legend so that it is absolutely clear that we have analyzed multiple cells:

      “Nuclei of primary murine thymocytes were categorized into four zones based on the intensity of DAPI staining and SATB1 speckles in each zone were counted. Images used represented a middle z-stack from the 3D-SIM experiments. The graph depicts the differences between the long and all SATB1 isoforms’ zonal localization in nuclei of primary murine thymocytes. (Lines 1189-1193)”

      1. For figure 2c. the authors have used 5 Fluorouridine for nascent RNA speckles. 5FU is known to have a spread signal type (with strong association to nucleolus as well). This is not the case for the image presented 2c. The authors should resolve this by showing different sets of images.

      Developing and naive T cells are very unique in terms of their metabolic features and thus they should not be directly compared with other cell types. Therefore, we would not expect to see such a spread FU pattern as previously shown for other cell types. Having said that, we could not find any reference publication that utilized super-resolution microscopy to detect localization of FU-stained sites of active transcription in developing primary T cells. However, we performed additional immunofluorescence experiments to demonstrate the colocalization or its lack between SATB1 and HP1 (Supplementary Fig. 2b), H3K4me3 (Supplementary Fig. 2c) and fibrillarin (Supplementary Fig. 3b). Moreover, we provide additional regions of SATB1 and FU staining in Supplementary Fig. 3c. The modified text reads:

      “We unraveled the localization of SATB1 isoforms and the sites of active transcription labeled with 5-fluorouridine. Sites of active transcription displayed a significant enrichment in the nuclear zones 3 & 4 (Supplementary Fig. 3a), similar to SATB1. As detected by fibrillarin staining, SATB1 also colocalized with nucleoli which are associated with active transcription and RNA presence (Supplementary Fig. 3b). Moreover, we found that the SATB1 signal was found in close proximity to nascent transcripts as detected by the STED microscopy (Fig. 2c). Similarly, the 3D-SIM approach indicated that even SATB1 speckles that appeared not to be in proximity with FU-labeled sites in one z-stack, were found in proximity in another z-stack (Supplementary Fig. 3c). Additionally, a pixel-based colocalization of SATB1 and sites of active transcription is quantified later in the text in Fig. 3g, supporting their colocalization. (Lines 157-167)”

      1. Fig 2 d., the authors have suddenly jumped solely to 'all iso' Satb1 here for IP MS. Is there a reason for that? The authors either need to do this with 'long iso' antibody or remove the analysis from the manuscript as it does not add to their primary aim of the manuscript. Also, the authors have only selectively talked about two clusters? What about chromatin related proteins? It is quite intuitive to have highest enrichment of these given previous literature and even IP MS data by other groups. Thus, it is necessary to revise this thoroughly or remove it.

      We appreciate the acknowledgment by the Reviewer that our IP-MS data identified anticipated factors. In the revised version of the manuscript we modified the underlying text to accommodate references to these former findings revealing interactions between SATB1 and chromatin modifying complexes: “Apart from subunits of chromatin modifying complexes that were also detected in previous reports25,33–36, unbiased k-means clustering of the significantly enriched SATB1 interactors revealed two major clusters consisting mostly of proteins involved in transcription (blue cluster 1; Fig. 2d and Supplementary Fig. 4c) and splicing (yellow cluster 2; Fig. 2d and Supplementary Fig. 4c). (Lines 170-174)”

      Please note that many subunits of chromatin modifying and chromatin-related complexes are in fact characterized as transcription-related factors, therefore our statements are not in disagreement with the former findings. Note also that we provide Supplementary File 1 & 2 with comprehensive description of our IP-MS data for the readers’ convenience. Please also note that we are the first group to report on the existence of the long isoform. Therefore, we find it absolutely reasonable to perform IP-MS experiment for all SATB1 isoforms which can then be used for a comparison with other publicly available datasets. We believe that there is no contradiction in this experimental setup in relation to the rest of the manuscript. We discuss the two major clusters simply because they are the two major clusters identified as indicated in Fig. 2d. Additionally, in Supplementary Fig. 4c, we provide a comprehensive description of all significantly enriched interactors including their cluster annotation and thus anyone can investigate the data if needed.

      1. In relation to Fig. 2f, the authors have not mentioned any of the previously published work on Satb1 CD4 specific KO, not even the RNA seq studies the other groups have reported under the same condition. Only an unpublished reference of their own (preprint) is cited. It is imperative to show how much their data corroborates with other published studies. Additionally, what is the binding site status of dysregulated genes?

      In the revised version of the manuscript, we have included the references to other studies using the same Satb1 conditional knockout. Moreover, we have clarified the relationship between SATB1 binding and gene transcription. The modified part in Lines 182-194 now reads: “Satb1 cKO animals display severely impaired T cell development associated with largely deregulated transcriptional programs as previously documented19,37,38. In our accompanying manuscript19, we have demonstrated that long SATB1 isoform specific binding sites (GSE17344619) were associated with increased chromatin accessibility compared to randomly shuffled binding sites (i.e. what expected by chance), with a visible drop in chromatin accessibility in Satb1 cKO. Moreover, the drop in chromatin accessibility was especially evident at the transcription start site of genes, suggesting that the long SATB1 isoform is directly involved in transcriptional regulation. Consistent with these findings and with SATB1’s nuclear localization at sites of active transcription, we identified a vast transcriptional deregulation in Satb1 cKO with 1,641 (922 down-regulated, 719 up-regulated) differentially expressed genes (Fig. 2f). Specific examples of transcriptionally deregulated genes underlying SATB1-dependent regulation are provided in our accompanying manuscript19. Additionally, there were 2,014 genes with altered splicing efficiency (Supplementary Fig. 4d-e; Supplementary File 3-4). We should also note that the extent of splicing deregulation was directly correlated with long SATB1 isoform binding (Supplementary Fig. 4d).”

      1. In context of Figure 3a and b, the authors write .'...The long SATB1 isoform speckles evinced such sensitivity as demonstrated by a titration series with increasing concentrations of 1,6-hexanediol treatment followed...' Whereas it is apparent from the image at least that overall numbers of individual speckles are instead increased at both 2 and 5%. There is although a clear spreading of restricted speckles compared to the controls. The authors should revise their figures to substantiate the associated text. Furthermore, there needs to be 'all iso' SATB1 3D SIM imaging and not just quantitation for comparison. This is also true for panel c in order to demonstrate the effect.

      In the revised Fig. 3a we provide new images which better reflect the underlying data analysis. Moreover, in Fig. 3c and Fig. 3d we provide an additional comparison between SATB1 all isoforms and long isoform staining and their changes upon hexanediol treatment, detected by both the 3D-SIM and STED approaches. It is true that upon treatment, there tend to be more speckles, however these are much smaller as they are gradually being dissolved. Depending on the treatment duration, the cells are swollen which is reflected in increased spreading of speckles. Nevertheless, the nuclear size was considered in all the quantification analyses. We believe that the new images provide better evidence of SATB1’s sensitivity to hexanediol treatment.

      1. Fig. 3 d also does not clearly demonstrate what the authors have claimed '...hexanediol treatment highly decreased colocalization between...' The figure shows at best decreased signal intensity for both SATB1 and FU. We suggest that the authors should give a statistical analysis as well for the colocalization points between the two using multiple source images. Lastly, the two images shown (control and treated), there seems to be a clearly visible magnification difference. The authors should clarify this.

      • In the revised version of the manuscript in Figure 3d, we have provided scale bars, which are both 0.5 µm (line 1213). The difference observed by this Reviewer is actually the main reason why we provided this image. Figure 3d demonstrates that upon hexanediol treatment, the speckles are mostly missing or significantly reduced in size, for both FU and SATB1 staining. • Moreover, the suggested statistical analysis is also provided – in Figure 3e. In Figure 3e, we performed pixel-based colocalization analysis which is a method that allows both quantification and statistical comparison of colocalization between two factors and between different conditions. Please note especially the decreased colocalization between long SATB1 isoform and FU-stained sites of active transcription in the left graph, which is in agreement with our claims in the manuscript. • Moreover, our data are compared to a negative control, i.e. 90 degrees rotated samples, which is a common method in colocalization experiments as described for example in Dunn et al., 2011 (https://doi.org/10.1152/ajpcell.00462.2010). • Additionally, we provide Costes’ P values which are based on randomly scrambling the blocks of pixels (instead of individual pixels, because each pixel’s intensity is correlated with its neighboring pixels) in one image, and then measuring the correlation of this image with the other (unscrambled) image. Please see Costes et al., 2004 (https://doi.org/10.1529%2Fbiophysj.103.038422) for more details.

      1. Figure 3f. The authors show the PC plot for Raman spectroscopy for phase behaviour due to Satb1. The experiment and its related text seems misinterpreted; the authors write...' ese bonds were probably enriched for weak interactions responsible for LLPS that are susceptible to hexanediol treatment. This shifted the cluster of WT treated cells towards the Satb1 cKO cells. However, the remaining covalent bonds differentiated the WT samples from Satb1 cKO cells......' whereas the clusters are clearly far away in 3D for both WT and KO while being closer to their respective treatments. Which is also intuitive given the sensitivity of Raman spectroscopy. Thus, it is more likely to be treatment effect and KO effect as separate. Treatment of WT leads to KO like spectra is far-fetched. Thus, the authors need to show separate PCs and modify their text thoroughly.

      We do not present any 3D graph hence it is not clear what the Reviewer refers to. Please also note that as stated in Lines 817-818, we used a customized Raman Spectrometer. Therefore, this approach allowed us to measure Raman spectra at cellular and even sub-cellular levels. For example, solely by utilizing Raman spectroscopy, we can now distinguish euchromatin and heterochromatin, methylated and unmethylated DNA and RNA, etc. This, together with other reports, such as Kobayashi-Kirschvink et al., 2018 (https://doi.org/10.1016/j.cels.2018.05.015) and Kobayashi-Kirschvink et al., 2022 (https://doi.org/10.1101/2021.11.30.470655), indicate a potential use of Raman in biological research. In our manuscript, we used this method as a supplementary approach, however we do find it noteworthy. We should also emphasize that in the revised Raman spectroscopy Fig. 3h, each point represents measurements from an individual cell and for each condition we used 2-5 biological replicates (Lines 831-832 & Lines 1225-1226). We specifically refer to the principal component 1 (PC1) that differentiates the samples. Therefore, there are certain spectra (representing certain chemical bonding) that allowed us to differentiate between WT and Satb1 cKO. The same type of bonding was then affected when WT samples were treated with hexanediol and we also had controls to rule out the impact of hexanediol on the resulting spectra.

      1. In Fig 4. b, The authors have shown the propensity of SATB1 N terminus to phase separate using different optodroplet constructs. Although the imaging is clear, why are the regions selected not uniform when comparing various constructs?

      We have selected images that would best represent each category. Please note that this was live cell imaging of photo-responsive constructs, thus there are many limitations regarding the area selection. Very often, even the brief time of bright light exposure to localize cells may trigger protein clustering. Upon disassembly, every new light exposure of the same cell then triggers much faster assembly which skews the overall results. It is therefore desired to work fast, while neglecting selection of equally sized cells. Moreover, it is not clear how would the proposed change improve the quality of our manuscript.

      1. Figure 5a, the disassembly should be shown for 'long' SATB1 as well. On pg 13, the authors write '....cytoplasmic protein aggregation has been previously described for proteins containing poly-Q domains and PrLDs..' no reference given.

      • In the revised version of the manuscript, we present the assembly and disassembly for both short and long full length SATB1 optogenetic constructs. To increase clarity, we present the behavior of the short and long isoforms as two separate images in Figure 5a and Figure 5b, respectively. • Moreover, we provided references to the statement regarding aggregation of PrLD and poly-Q-containing proteins in Lines 305-309, which now reads: ”Since protein aggregation has been previously described for proteins containing poly-Q domains and PrLDs8,11,38,39, we next generated truncated SATB1 constructs encoding two of its IDR regions, the PrLD and poly-Q domain and in the case of the long SATB1 isoform also the extra peptide neighboring the poly-Q domain (Fig. 1a and 4a).”

      1. Fig. 5d, Is there an amino-acid specific reasoning to support the authors claim of the phase behaviour due to extra peptide? They need to show a proper control with equal extra (unrelated) peptide to show the specificity. Are the shorter isoform aggregates responsive to light?

      • We have referred to the amino acid composition bias in Fig. 5c. In the revised version of the manuscript, we made this clear by showing the composition bias in the new revised Fig. 5e. The related part of the main text then reads: “Computational analysis, using the algorithm catGRANULE37, of the protein sequence for both murine SATB1 isoforms indicated a higher propensity of the long SATB1 isoform to undergo LLPS with a propensity score of 0.390, compared to 0.379 for the short isoform (Fig. 5d). This difference was dependent on the extra peptide of the long isoform. Out of the 31 amino acids comprising the murine extra peptide, there are six prolines, five serines and three glycines – all of which contribute to the low complexity of the peptide region3 (Fig. 5e).” (Lines 298-304) • Moreover, we should note that the low complexity extra peptide of the long SATB1 isoform directly extends the PrLD and IDR regions as indicated in Fig. 4a and which we now directly state in Lines 304-305: “Moreover, the extra peptide of the long SATB1 isoform directly extends the PrLD and IDR regions as indicated in the Fig. 4a.” • We show in Fig. 4, that the N terminus of SATB1 undergoes LLPS. Since this part of SATB1 is shared by both isoforms, it is reasonable to assume that both isoforms would undergo LLPS. This is also in line with the observed photo-responsiveness of both short and long full length SATB1 isoforms in CRY2 optogenetic constructs in revised Fig. 5a,b, and similar FRAP results for both short and long full length SATB1 isoform constructs transiently transfected in NIH-3T3 cells in the revised Supplementary Fig. 6f. However, the main reason why we think that the difference in LLPS propensity between the isoforms is important is because the long isoform is more prone to aggregate compared to the short isoform, as documented in Fig 5c,f,g and Supplementary Fig. 5f.

      1. Fig 6c., It is important that authors show the data for NLS+short iso data as well to prove their hypothesis.

      As shown in original Figure 5d, the long SATB1 isoform undergoes cytoplasmic aggregation, unlike the short SATB1 isoform (as shown in the same Figure). Therefore, an image of the NLS + short isoform would not be related to our hypothesis. Actually, we wanted to reverse the long SATB1 isoform’s relocation, from the aggregated form in the cytoplasm into the nucleus. Nevertheless, to show the complete picture, in the revised version of the manuscript in Figure 6c, we now provide data for both short and long SATB1 isoforms.

      1. Fig 6d., The authors claim that mutating a specific P site changes the phase behaviour of the 'short iso'. Does it also increase for the long isoform? The authors need to confirm this in order to verify the effect of a single P site outside of oligomerization domain. ...' phosphorylation status; when phosphorylated it remains diffused, whereas unphosphorylated SATB1 is localized to PML bodies....' This being an important premise, thus should be moved to the results text.

      In the revised version of the manuscript, we moved the part regarding PML in the results section, as suggested by the Reviewer. Moreover, we included additional experiments probing the impact of association between PML and two SATB1 full length isoforms on their dynamics. The modified section in Lines 357-368 now reads: “In relation to this, a functional association between SATB1 and PML bodies was already described in Jurkat cells64. We should note that PML bodies represent an example of phase separated nuclear bodies65 associated with SATB1. Targeting of SATB1 into PML bodies depends on its phosphorylation status; when phosphorylated it remains diffused, whereas unphosphorylated SATB1 is localized to PML bodies66. This is in line with the phase separation model as well as with our results from S635A mutated SATB1, which has a phosphorylation blockade promoting its phase transitions and inducing aggregation. To further test whether SATB1 dynamics are affected by its association with PML, we co-transfected short and long full length SATB1 isoforms with PML isoform IV. The dynamics of long SATB1 isoform was affected more dramatically by the association with PML than the short isoform (Supplementary Fig. 7e), which again supports a differential behavior of the two SATB1 isoforms.”

      Moreover, given the localization of the discussed phosphorylation site in the DNA binding region of SATB1 we did test its impact on DNA binding as documented in the revised Supplementary Fig. 7d. Additionally, as we have noted in our answer in Major Comment C of this reviewer, to further support the effect of serine phosphorylation on the DNA binding capacity of SATB1 we have performed DNA affinity purification experiments utilizing primary thymocyte nuclear extracts treated with phosphatase (Supplementary Fig. 7b) We found that SATB1’s capacity to bind DNA (RHS6 hypersensitive site of the TH2 LCR) is lost upon treatment with phosphatase (Supplementary Fig. 7c).

      1. Pg 16,. The authors have tried to explain multiple things (concepts of self-regulation, accessibility) which is quite tangential. There is no inference to Fig 6f., which is showing the opposite to what the authors had postulated. This portion should either be removed or explained with a rationale. The writing also needs to be revised thoroughly in this section. Similarly, the discussion should also be modified.

      The rationale for the original Fig. 6f (revised Fig. 6g) was described in great detail in Lines 330-343 of the original manuscript. It is not clear why the Reviewer assumes that it shows the opposite to our hypothesis. As we explained, the increased accessibility allows faster read-through by RNA polymerase, and thus the exon with higher accessibility is more likely to be skipped. The exact relationship is shown in the revised Fig. 6g where the increased accessibility is associated with the expression of the short isoform, whereas the long isoform expression needs lower chromatin accessibility which allows the splicing machinery to act on the specific exon to be included. We reason that these findings are important and relevant because: 1) we suggest a potential regulatory mechanism for the SATB1 isoforms production. This is highly relevant to this manuscript given the fact that this is the first report on the existence of the long SATB1 isoform, and 2) the differential production of the long/short SATB1 isoforms has a potential relevance to breast cancer prognosis. In the revised version of the manuscript we added Fig. 6f, which now indicates the differential chromatin accessibility in human breast cancer patients and accordingly the expression of the long SATB1 isoform are associated with worse patient prognosis as indicated in Fig. 6h and Supplementary Fig. 8a,b. In the revised version of the manuscript, we substantially modified the text in Lines 374-408, to make the relevance of all these conclusions clear. The modified text now reads: “Therefore, we reasoned that a more plausible hypothesis would be based on the regulation of alternative splicing. In our accompanying manuscript19, we have reported that the long SATB1 isoform DNA binding sites display increased chromatin accessibility than what expected by chance (Fig. 3b in 19), and chromatin accessibility at long SATB1 isoform binding sites is reduced in Satb1 cKO (Fig. 3c in 19), collectively indicating that long SATB1 isoform binding promotes increased chromatin accessibility. We identified a binding site specific to the long SATB1 isoform19 right at the extra exon of the long isoform (Fig. 6e). Moreover, the study of alternative splicing based on our RNA-seq analysis revealed a deregulation in the usage of the extra exon of the long Satb1 isoform (the only Satb1 exon affected) in Satb1 cKO cells (deltaPsi = 0.12, probability = 0.974; Supplementary File 4). These data suggest that SATB1 itself is able to control the levels of the short and long Satb1 isoforms. A possible mechanism controlling the alternative splicing of Satb1 gene is based on its kinetic coupling with transcription. Several studies indicated how histone acetylation and generally increased chromatin accessibility may lead to exon skipping, due to enhanced RNA polymerase II elongation48,49. Thus the increased chromatin accessibility promoted by long SATB1 isoform binding at the extra exon of the long isoform, would increase RNA polymerase II read-through leading to decreased time available to splice-in the extra exon and thus favoring the production of the short SATB1 isoform in a negative feedback loop manner. This potential regulatory mechanism of SATB1 isoform production is supported by the increased usage of the extra exon in the absence of SATB1 in Satb1 cKO (Supplementary File 4). To further address this, we utilized the TCGA breast cancer dataset (BRCA) as a cell type expressing SATB150. ATAC-seq experiments for a series of human patients with aggressive breast cancer51 revealed differences in chromatin accessibility at the extra exon of the SATB1 gene (Fig. 6f). In line with the “kinetic coupling” model of alternative splicing, the increased chromatin accessibility at the extra exon (allowing faster read-through by RNA polymerase) was positively correlated with the expression of the short SATB1 isoform and slightly negatively correlated with the expression of the long SATB1 isoform (Fig. 6f). Moreover, we investigated whether the differential expression of SATB1 isoforms was associated with poor disease prognosis. Worse pathological stages of breast cancer and expression of SATB1 isoforms displayed a positive correlation for the long isoform but not for the short isoform (Fig. 6g and Supplementary Fig. 6c). This was further supported by worse survival of patients with increased levels of long SATB1 isoform and low levels of estrogen receptor (Supplementary Fig. 6d). Overall, these observations not only supported the existence of the long SATB1 isoform in humans, but they also shed light at the potential link between the regulation of SATB1 isoforms production and their involvement in pathological conditions.”

      1. The authors should not draw conclusions based on any data which is not shown '....ed differences in chromatin accessibility at the extra exon of the SATB1 gene (data not shown), suggesting its potential involvement in alternative splicing regulation according to the "kinetic coupling" model...'. This has led to overspeculation and needs correction.

      In the revised version of the manuscript, we included the ATAC-seq data from human breast cancer patients in the revised Fig. 6f. The legend of this figure now reads: “Human TCGA breast cancer (BRCA) patient-specific ATAC-seq peaks51 span the extra exon (EE: extra exon; labeled in green) of the long SATB1 isoform. Note the differential chromatin accessibility in seven selected patients, emphasizing the heterogeneity of SATB1 chromatin accessibility in cancer. Chromatin accessibility at the promoter of the housekeeping gene DNMT1 is shown as a control. (Lines 1281-1285)” Accordingly, we have also modified the main text: “ATAC-seq experiments for a series of human patients with aggressive breast cancer68 revealed differences in chromatin accessibility at the extra exon of the SATB1 gene (Fig. 6f). In line with the “kinetic coupling” model of alternative splicing, the increased chromatin accessibility at the extra exon (allowing faster read-through by RNA polymerase) was positively correlated with the expression of the short SATB1 isoform and slightly negatively correlated with expression of the long SATB1 isoform (Fig. 6g).” (Lines 395-339)”

      Minor comments: 1. On pg 4, the authors state 'Here, we utilized primary murine T cells, in which we have identified two full-length SATB1 protein isoforms.' Whereas only one 'long' isoform is identified and the other is the canonical version. The authors should correct the statement.

      In the revised version of the manuscript, we modified this statement as follows: ”In this work, we utilized primary developing murine T cells, in which we have identified a novel full-length long SATB1 isoform and compared it to the canonical “short” SATB1 isoform.” (Lines 64-66)”

      1. Fig. 1 a , Is there a specific reason to generate a custom-made antibody for 'all' SATB1, using similar regions that are already commercially available. This becomes redundant otherwise, because there is no apparent difference in detection compared to the commercial one (Suppl. Fig 1a). Antibody generation strategy (1a) should be moved to supplementary. Additionally, authors have obtained the custom antibodies from a commercial source, therefore, the text should reflect the same alongside relevant details.

      The custom-made SATB1 antibody targeting the amino-terminal region of the protein has been developed in order to be utilized for detecting the native form of the protein. Unlike commercially available antibodies raised against either short peptides or denatured forms of the protein we have utilized the native form of the amino-terminal part of the protein for raising this antibody. To be honest, this antibody has been raised in order to be utilized in ChIP-seq experiments since no commercially available antibody is of high quality for this approach. Moreover, the original Figure 1a was utilized in order to provide an overview of the SATB1 protein structure which is highly relevant to understand its biophysical properties and not for presenting the strategy for raising a custom-made antibody for SATB1.

      1. Fig 3e: what is the control used here? In their Pearson correlation analysis, there seem to be significant reduction in control sets as well upon treatment. This needs to be clarified.

      We used scans rotated by 90° which served as a negative control, as stated in Line 769: “SATB1 scans rotated by 90° served as a negative control for the colocalization with FU.” Note that this is a commonly used control in colocalization experiments as described for example in Dunn et al., 2011 (https://doi.org/10.1152/ajpcell.00462.2010).

      Additionally, we provide Costes’ P values which are based on randomly scrambling the blocks of pixels (instead of individual pixels, because each pixel’s intensity is correlated with its neighboring pixels) in one image, and then measuring the correlation of this image with the other (unscrambled) image. Please see Costes et al., 2004 (https://doi.org/10.1529%2Fbiophysj.103.038422) for more details. Moreover, it was actually anticipated to see a decrease in colocalization upon hexanediol treatment even in the negative control, as hexanediol significantly reduces both SATB1 and FU speckles as established in Fig. 3a-d.

      1. Pg 10, the authors claim that '..., thus we reasoned that it may also be used to study phase separation...' But there have been numerous reports starting from 2018, which have utilized this technique in corelation to phase behaviour (albeit individual proteins). The authors should include proper citations as they are extending an idea from the same field to their specific need.

      In the revised version of the manuscript, we included relevant citations to support the use of Raman spectroscopy in LLPS research: “Raman spectroscopy was already used in many biological studies, such as to predict global transcriptomic profiles from living cells42, and also in research of protein LLPS and aggregation43–47. Thus we reasoned that it may also be used to study phase separation in primary T cells.” (Lines 225-228)”

      1. For Fig 5b, there should be a comparative image for 'short' isoform.

      In the revised Figure 5c we have included a comparative image for the short SATB1 isoform.

      1. In the context of Figure 5c, the authors claim ...' Note also the higher LLPS propensity of the human long SATB1 isoform compared to the murine SATB1...' Why suddenly human and mouse comparisons are drawn? This figure should be moved to supplementary.

      The comparison between the human and mouse SATB1 isoforms has been implemented because it is relevant for our claims regarding the increased SATB1 aggregation in human cells in relation to the revised Fig. 6f,g,h and Supplementary Fig. 6c,d. This is also discussed in Lines 479-482, which read: “This is particularly important given the higher LLPS propensity of the human long SATB1 isoform compared to the murine SATB1 (Fig. 5d). Therefore, human cells could be more susceptible to the formation of aggregated SATB1 structures which could be associated with physiological defects.”

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

      Zelenka et al., focus on a T cell genome-organizing protein, SATB1, to show that SATB1 undergoes liquid liquid phase-separation (LLPS), and distinct isoforms confer different LLPS-related biophysical properties. They generate a long-isoform specific antibody and conduct several experiments to test for LLPS and compare LLPS properties between the long-isoform relative to the whole SATB1 protein population. Given that SATB1 plays important roles in T cell development and in cancer, interrogating SATB1 biophysical properties is an important question. However, there are multiple problems with the experimental setup and data that weaken their support of the conclusions. I will detail some of the major issues below:

      Regarding phase-separation There are several assays to determine whether a protein undergoes LLPS. 1. One of the first the authors address is the spherocity or roundness. Indeed, formation of spherical droplets is one evidence of the liquid nature of a protein. However, the authors use fixed preparations (which can introduce artifacts), not free-floating protein, and determine roundness by showing a 2D image. Roundness should take into account the diffraction-limits of fluorescent imaging, as many structures can be imaged to appear round by the detector. There are quantifiable measurements that can be taken on 3D images to show roundness. This would best be shown using non-fixed protein.

      • We thank this Reviewer for several insightful comments. Although, we agree with most of them, we should highlight the main goal of our manuscript, i.e. to investigate the SATB1 protein with an emphasis on its physiological roles in primary developing murine T cells. We highlight this already in the introduction in Line 64 “In this work, we utilized primary developing murine T cells,...” and mainly also in the respective part of the result section: “To probe differences in phase separation in mouse primary cells, without any intervention to SATB1 structure and expression, we first utilized 1,6-hexanediol treatment, which was previously shown to dissolve the liquid-like droplets34.(Lines 203-205)”

      • We believe that this is a very important aspect of our study that should not be overlooked. The majority of proteins perhaps behave differently under physiological and in vitro conditions. However, due to the extensive post-translational modifications affecting the properties of SATB1, its completely different localization patterns between primary developing T cells and other cell types but especially cell lines and many other aspects, it was of utmost importance to focus our research on primary T cells. Unfortunately, this was accompanied with multiple difficulties, such as that we have to use fixed cells as this is the only way to visualize SATB1 in these cells. Alternatively, one could create a new mouse line expressing a fluorescently tagged SATB1 protein, but this is beyond the scope of our work.

      • However, we should also note that many LLPS-related studies do not pay any focus on primary physiological functions of proteins and they simply focus on the investigation of protein’s artificial behavior in in vitro conditions. Having said that, we too extended our experiments in primary cells to the ex vivo studies in cell lines to further support our claims. In these experiments, we utilized live cell imaging in Fig. 4-6, quantified the spherocity in Supplementary Fig. 6, showed the ability of speckles to coalesce in Fig. 4c and also used FRAP in Fig. 4f and also in the revised version of the manuscript in Supplementary Figure 6f. Moreover, we should note that most of these experiments were designed and performed during 2017 and 2018 conforming with the standards. We are well aware of the progress in the field and impact of fixation on LLPS, as described in Irgen-Gioro et al., 2022 (https://doi.org/10.1101/2022.05.06.490956), but after over seven months of review process in another journal we also believe that these aspects should be considered not to delay further progress of the SATB1 field.

      Regarding the isoform specificity of SATB1 biophysical properties 1. The authors generate a long isoform-specific antibody. However, the western blot is not convincing that this is indeed specific to the long isoform as there is a rather large smear. Can this be improved with antibody preabsorption? Since this is a key reagent for the manuscript, improvement in antibody quality is essential.

      The custom-made antibody for the long isoform has been raised against the unique 31 amino acids long peptide present in the long SATB1 isoform. The polyclonal serum has undergone affinity chromatography utilizing the immobilized peptide (antigen) to purify the antibody. In the revised version of the manuscript we have included another immunodepletion experiment with cleaner bands (Fig. 1f). Moreover, please read our answer to Major comment #2 of Reviewer 1 that follows: • The long antibody was raised in mice inoculated with the extra peptide present in the long isoform only. Therefore, the capacity of this antibody precipitating the shorter isoforms, which do not express the sequence of the extra peptide (EP, Figure 1a) in not possible.

      • We have repeated the immunodepletion experiment and we now provide the results in Fig. 1f and Supplementary Fig. 1b. The western blot in Fig. 1f is now cleaner and supports quite convincingly the presence of a long SATB1 isoform. Given the lack of isoform-specific knockouts which we could utilize to immunoprecipitate or detect the different isoforms in a single cell (or cell population), the utilized approach of immunodepletion and subsequent western blotting is the approach we thought of implementing.

      • As shown in Fig. 1f and Supplementary Figure 1b, the long isoform SATB1 antibody has the capacity to recognize the long isoform in murine thymocyte protein extracts but not the short SATB1 isoform (please compare lane 3 in the two western blots utilizing either the antibody for the long isoform -top panel - or the antibody that detects both isoforms (lower panel).

      • We have performed Immunofluorescence experiments utilizing the antibody detecting the long SATB1 isoform in thymocytes isolated from either C57BL/6 or Satb1 cKO mice. The antibody is specific to the SATB1 protein since there is no signal in immunofluorescence experiments utilizing the knockout cells (Supplementary Figure 1c).

      • We have performed Immunofluorescence experiments utilizing thymocytes and the antibody detecting the long SATB1 or a commercially available antibody detecting all SATB1 isoforms. The pattern of SATB1 subnuclear localization is similar for both antibodies (Supplementary Figure 1e).

      • In our accompanying revised manuscript Zelenka et al., 2022 (https://doi.org/10.1101/2021.07.09.451769), we provide yet another piece of evidence, consisting of bacterially expressed short and long SATB1 protein isoforms detected by western blot using either the long isoform-specific or the non-selective all SATB1 isoforms antibodies.

      • Regarding the additional bands detected in the immunoprecipitation experiment presented in the original Supplementary Figure 1b (lane 2), it is not surprising that additional bands appear in a sample of protein extracts that is used for several hours for the immunoprecipitation experiments, while the “input” sample simply denotes protein extract that is frozen at -80oC right after the preparation of protein extracts until use. It is well-established that SATB1 is the target of proteases which might as well be active during the immunoprecipitation steps (2 consecutive immunoprecipitation steps take place). Therefore, the immunoprecipitated material cannot necessarily be a copy of the input material displaying a single protein band even if protease inhibitors are included in the buffers.

      Taken together the experiments described here we showed that the antibody raised against the extra 31 aa long peptide, present only in the long SATB1 isoform, is specific for this isoform.

      1. Fig 4 Optodroplet experiment appears to show that the N-terminus of SATB1 can undergo LLPS. The results of this assay show that SATB1 has a domain that can undergo phase-separation in isolation, but it does not show that the protein itself is a phase-separating protein. The FRAP assay methods are not provided by the authors, but this is important, as continued light activation means proteins are continuously forming aggregates, and the bleaching for FRAP should be balanced with the levels of Cry2 activation. A very good description of the methods is described in the original Optodroplet paper: https://www.sciencedirect.com/science/article/pii/S009286741631666X?via%3Dihub#sec4

      We should note that we did follow the FRAP protocol provided by the recommended study Shin et al., 2017 (https://doi.org/10.1016/j.cell.2016.11.054). Indeed, these experiments are very tricky to perform and interpret, as every cell expresses slightly different amounts of protein which is directly associated with the different speed of optoDroplet formation, and thus its propensity to aggregate upon overactivation. On the other hand, there need to be continuous activation during the FRAP experiment as the lack of activation laser would result in fast disassembly of the optoDroplets, counteracting the FRAP results. Moreover, the optoDroplets actively move around the cell in all dimensions which makes the accurate measurement of signal intensity really challenging, even with an adjusted pinhole. Therefore, we do not think that FRAP is the best approach to examine the behavior of optoDroplets.

      Either way, we have now described the detailed FRAP protocol in Lines 889-898, which read: “For the FRAP experiments, cells were first globally activated by 488 nm Argon laser illumination (alongside with DPSS 561 nm laser illumination for mCherry detection) every 2 s for 180 s to reach a desirable supersaturation depth. Immediately after termination of the activation phase, light-induced clusters were bleached with a spot of ∼1.5 μm in diameter. The scanning speed was set to 1,000 Hz, bidirectionally (0.54 s / scan) and every time a selected point was photobleached for 300 ms. Fluorescence recovery was monitored in a series of 180 images while maintaining identical activation conditions used to induce clustering. Bleach point mean values were background subtracted and corrected for fluorescence loss using the intensity values from the entire cell. The data were then normalized to mean pre-bleach intensity and fitted with exponential recovery curve in Fiji or in frapplot package in R.”

      1. Description of analyses that authors prefer not to carry out

      **Reviewer #1**:

      Can they use the all and long isoform antibodies together, then subtract the signal from long isoform to conclude about the localization of the shorth isoform ?

      We thank the Reviewer for the suggestion, though given the differential efficiency of antibodies and other limitations of imaging experiments, we do not find the suggested experiment to have a potential to improve the quality of our manuscript. However, we should note that we have performed a pixel-based colocalization experiment between the signal detected by all isoform and long isoform SATB1 antibodies. Fluorocytogram of the pixel-based colocalization, based on 3D-SIM data is provided on the left, with quantified colocalization on the right of the revised Supplementary Fig. 5a.

      3) Lack of better staining with antibody against the long and short SATB1 isoforms after treatment with 1,6 Hexanediol. 1,6 Hexanediol treatment can change many other chromatin associated proteins to which SATB1 can be bound to indirectly. This experiment can

      We do understand the controversy and difficulties of experiments using 1,6-hexanediol treatment. However, we have to note that there is no better approach available for the investigation of LLPS in our primary murine T cells. We did use alternative approaches in ex vivo experiments, utilizing cell lines to validate our hypothesis without the involvement of 1,6-hexanediol.

      **Reviewer #2**:

      1. The authors mention, '...of the different SATB1 isoforms, uncovered by the use of the two different antibodies, relied in the heterochromatin areas (zone 1), where the long isoform was less frequently...' There is no supporting figure number mentioned. The authors need to show a zone-by-zone comparison images for 'all iso' vs 'long' iso of SATB1. Just to reiterate, there is a need for a heterochromatin mark to unambiguously call out the distinction.

      We should remind that there is an inherent difficulty to accurately compare localization of short and long SATB1 isoforms in primary cells, especially due to the lack of Satb1 isoform-specific knockout mice. There is no way to detect only the short isoform in these primary cells as there are only antibodies targeting the long or all SATB1 isoforms. Therefore, we cannot set up additional experiments probing these questions.

      In line with this, in the revised version of the manuscript, we toned down our statements regarding the differential localization of the two isoforms in primary cells. We only refer to it as an indication and we support it by adding references to the relevant figures. This part now reads: “Localization of SATB1 speckles detected by antibodies targeting all SATB1 isoforms and/or only the long SATB1 isoform, revealed a significant difference in the heterochromatin areas (zone 1, Fig. 2b), where the long isoform was less frequently present (see also Fig. 2a and Fig. 3c). Although, this could indicate a potential difference in localization between the two isoforms, due to the inherent difficulty to distinguish the two based on antibody staining, we refrain to draw any conclusions. (Lines 145-150)”

      1. Fig. 6a, The authors wished to see the effect of RNA on Satb1 nuclear localization. This is not related to the main theme of the paper, thus should be moved to supplementary (true for b as well). Importantly, the experiments should be performed with total cells to show the divergence of localization (like the paper the authors referred to) instead of matrix for clarity.

      • We did not wish to see the effect of RNA on SATB1 localization. In fact, there is a long history of SATB1 research that is inherently linked with the concept of nuclear matrix, a putative nuclear structure which is highly associated with nuclear RNAs. SATB1 was described many times as a nuclear matrix protein (https://doi.org/10.1016/0092-8674(92)90432-c; https://doi.org/10.1128/mcb.14.3.1852-1860.1994; https://doi.org/10.1074/jbc.272.17.11463; https://doi.org/10.1128/mcb.17.9.5275; https://doi.org/10.1021/bi971444j; https://doi.org/10.1083/jcb.141.2.335; https://doi.org/10.1101/gad.14.5.521; https://doi.org/10.1038/ng1146).

      • Moreover, our data discussed in comments 4-7 of this Reviewer, such as i. the localization of SATB1 to the nuclear zones associated with RNA and nuclear scaffold factors (Fig. 2b, Supplementary Fig. 1c), ii. colocalization of SATB1 with actively transcribed RNAs (Fig. 2c, Fig. 3g, Supplementary Fig. 2a, Supplementary Fig. 2c), iii. including its association with nucleoli (Supplementary Fig. 3b), and also iv. its computationally predicted interaction with Xist lncRNA (Agostini et al., 2013; https://doi.org/10.1093/nar/gks968) as a notable factor of nuclear matrix, all suggest that the interaction between RNA and SATB1 is plausible and potentially relevant for its function and/or at least its subnuclear localization. It is relevant even more so, when considering numerous reports on the ability of RNA-binding, poly-Q and PrLD-containing proteins to undergo LLPS https://doi.org/10.1016/j.molcel.2015.08.018; https://doi.org/10.1042/bcj20160499; https://doi.org/10.1016/j.cell.2018.03.002; https://doi.org/10.1016/j.cell.2018.06.006; https://doi.org/10.1093/nar/gkaa681), including RNAs specifically regulating LLPS behavior, especially for poly-Q and PrLD-containing proteins, such as SATB1 (https://doi.org/10.1126/science.aar7366; https://doi.org/10.1126/science.aar7432; https://doi.org/10.1016/j.ceb.2019.03.007; https://doi.org/10.1038/s41598-020-57994-9; https://doi.org/10.1016/j.molcel.2015.09.017; https://doi.org/10.1038/s41598-019-48883-x; https://doi.org/10.1038/s41467-019-11241-6).

      • It should also be noted that SAF and various hnRNPs, as the most prominent proteins of nuclear matrix were many times reported to phase separate (https://doi.org/10.1016/j.molcel.2019.10.001; https://doi.org/10.1074/jbc.ra118.005120; https://doi.org/10.1016/j.celrep.2019.12.080; https://doi.org/10.1038/s41467-019-09902-7; https://doi.org/10.1016/j.molcel.2017.12.022; https://doi.org/10.1074/jbc.tm118.001189). All these aspects show that the relation between nuclear matrix, SATB1 and RNA are quite relevant to our manuscript.

      • Moreover, in light of the aforementioned information, we believe that it is much clearer to follow the protocol we did – i.e. to remove soluble proteins by CSK treatment and then, upon RNase treatment, extract the released proteins using ammonium sulfate. In an experiment utilizing whole cells, one would need to microinject RNase A into the nucleus, which 1. is very challenging for primary T cells having a radius of 3-5 micrometers, 2. is of low throughput, 3. would not allow for released protein removal which would thus make the results hard to interpret. Please note that in the reference paper, the authors used cell lines overexpressing heterologous GFP-tagged proteins, which is not related to our setup.

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

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  5. Sep 2021
    1. Author response


      September 9, 2021

      We would like to thank ASAPbio for selecting our preprint for review! We are excited to contribute to this new process and hope others will find it as helpful as we have. The comments generated by the “crowd” were detailed and thoughtful. Below we respond to the major discussion points and if there were specific reviewer comments relevant to the discussion point, we also included that statement. We also responded to each specific comment. We would love to continue this discussion, so we invite further feedback and responses! Thanks so much for your time.

      -Chelsea Kidwell, Joey Casalini, and Minna Roh-Johnson


      Major Discussion Point #1:One of the most important claims is that mitochondria are the organelles responsible for the activation of the signals of cell proliferation. However, a previous report by the last author reported that macrophages transfer cytoplasm to recipient cells. It cannot be excluded that other organelles or cellular fragments are transferred as well and contribute to the observed effects (ERK activity). Perhaps a good way to solve this would be the use of macrophages that are devoid of mitochondria. At least, this aspect should be discussed in the manuscript.

      🡪 We had first considered two approaches to test the requirement and sufficiency of macrophage mitochondria in cancer cell proliferation. The first was to generate rho-zero macrophages (mtDNA-deficient), as you mention in your comment, such that the macrophages did not have functional mitochondria. However, we use primary human macrophages for all of our studies, and these cells would not survive long enough to generate rho-zero cells (which requires that the cells be treated with low levels of ethidium bromide for weeks). The second is to biochemically purify mitochondria from macrophages and directly inject these mitochondrial preps into breast cancer cells. We actually did this experiment, and cancer cells injected with purified mitochondrial preps exhibited higher proliferation (by live timelapse microscopy) compared to control cells. However, we also found that the mitochondrial purifications were not clean, and contained other membranous components in the cytoplasm. We tried centrifugation-centric approaches, as well as IP-ing against a mitochondrially-localized tag, but in all cases, the mitochondrial preparations contained other cytoplasmic components. Therefore, we did not feel that this approach was an adequate way to test effects of specifically the mitochondria. We certainly wanted to discuss this aspect in the manuscript, but unfortunately, we were limited due to space. If folks have suggestions on how to best purify mitochondria, we’d love to know, so please reach out.

      However, in terms of the bigger question of whether the induced proliferation in cancer cells is specifically due to ROS accumulation in transferred macrophage mitochondria, we tried to address this question with the mito-KillerRed experiments, where we generate ROS using optogenetics, and ask whether this accumulation is sufficient to induce cancer cell proliferation (which we showed it was). We also showed that this same approach could induce Erk activity, and then in separate experiments, we show that macrophage mitochondrial transfer results in accumulation of ROS and increased Erk activity. We feel that these experiments support our conclusions, however, we’d love for a way to link it all together. Unfortunately, we are not convinced that such experiments are possible at this time.

      Major Discussion Point #2: Most of the positive examples of transferred mitochondria discussed appeared in a small clump. However, there also appears to be another population that was more diffuse and co-localizes with host mitochondria (e.g., Fig2B, bottom right panels). It would be helpful to show results of these sibling mitochondria for assays performed on their clumpy siblings. If they behave differently, it would be helpful to provide some explanation.

      Specific Comment: Figure 2 Majority (57%) of donated mitochondria do not colocalize with LysoTracker signal (N=24 cells, 4 donors) - Here the paper implies that some transferred mitochondria do co-localize with lysoTracker signal. More importantly, they co-localize with host mitochondria. It raises the question of whether they signal through ROS and ERK like their clumpy siblings who are in the limelight of most figures.

      🡪Yes, you are correct. There does appear to be a diffuse population of macrophage mitochondria. The majority of these mitochondria co-localize with lysotracker, suggesting that they are being actively degraded. We can’t say that they tend to co-localize with endogenous cancer cell mitochondria, however, it’s possible that this diffuse population is comprised of both mitochondria that are being degraded and mitochondria that are fusing with the endogenous network. We do not know if this population has a different effect on cancer cell behavior because we did not follow this population (mostly because once the mitochondria are degraded or fuse with the network, we can no longer follow those mitochondria!). However, we did follow cancer cells that contained punctate macrophage mitochondria. Often times this was the only population we could observe in the cell at that time, and this is the population in which we observe accumulated ROS.

      Major Discussion Point #3:The effects that are attributed to the transferred mitochondria are highly variable (figures 1F, 3A,E) and often due to a subpopulation of samples that show a few extreme values (e.g. figures 2D, 3E, S4B, S4D). This might be expected from effects that are caused by a single mitochondria (which has a small volume) that is transferred to a complete cell. This complicates the study of the transfer process and effects and should be discussed. Also, do the authors have ideas how to improve the system, to make it more robust and easier to study the effects?

      🡪The variability in the assays likely reflects the heterogeneity within the biology - Each experiment contains macrophages derived from primary monocytes that are harvested from different human blood donors! Due to the primary nature of these cells, we do expect a range of phenotypes as each donor would have a different genetic background and the monocytes were likely exposed to different environmental stimuli. In fact, even though working on this study was a giant pain due to the variability, we felt more confident about our findings because despite the heterogeneity in the system, we still observed consistent phenotypes. Below we indicate where we took a sample set and removed “outliers”, and ran the statistical tests again. The differences were still statistically significantly different, further suggesting robustness of our findings.

      However, we are always on the lookout for ways to make the system easier to study. One way that we will follow up on is using M2-like macrophages since they transfer mitochondria at a higher rate than unstimulated macrophages.

      Major Discussion Point #4: The authors conclude that the transfer of dysfunctional mitochondria generated a signal mediated by ROS that activates cell proliferation signals. The statement that "transferred mitochondria act as a signaling source that promotes cancer cell proliferation" is too strong. There is increased ROS production from mitochondria, yes, but an experiment in which ROS are decreased would be needed to properly sustain that conclusion. The title and abstract could be changed to better reflect the data.

      Specific Comment: ‘Furthermore, treatment with an ERK inhibitor (ERKi) was sufficient to inhibit ERK activity ‘- curious as to whether antioxidant treatment would reverse any proliferative phenotypes?

      🡪We wish we could quench the ROS at macrophage mitochondria. We really tried. We used a combination of ROS quenchers (NAC, mitoTempo, Tempo) and ROS readouts (mitoSOX, CellRox, DCFDA, and the 2 biosensors used in our study: Grx and Orp1), and treated cells for various amounts of time, and no matter what we tried, we could not reliably detect reduction of ROS levels in the host network or the transferred mitochondria (without killing the cells, that is). Another issue that we faced was that any pharmacological treatment would have a global effect on the mitochondrial network in the recipient cells and therefore it would not be possible to distinguish effects from global inhibition of ROS versus specifically at the site of the transferred mitochondria, and we certainly observed cell death upon treatment of ROS quenchers because of this fact. We talked to a couple of ROS experts, and they indicated that this issue is not unique to us, although we unfortunately did not have viable solutions, so if people have ideas or suggestions, please let us know!!

      However, despite our failed attempts at quenching ROS, the comment that "transferred mitochondria act as a signaling source that promotes cancer cell proliferation" is too strong of a statement… well, we don’t entirely agree given that we do perform sufficiency experiments in which weinduce ROS and observe both proliferation and ERK signaling, so we do feel reasonably justified to provide the title that we did. However, we will continue to mull over this comment. Thanks for sharing your thoughts.

      Major Discussion Point #5:The study may benefit from more direct evidence to support its conclusion of increased proliferation after mitochondrial transfer. While the RNA-seq, flow cytometry, counting of completion of cytokinesis and dry mass measurements provided in the present study do lend some support to the proliferation hypothesis, they all seem indirect. With the biomarkers labeling the mitochondria of donor and potential recipient cells, high content imaging and tracking of cells could be used to monitor cell division. A comparison of cell division rates of transfer-positive cells and transfer-negative cells will provide a more pertinent test of whether mitochondrial transfer promotes recipient cell proliferation.

      🡪We should probably do a better job at describing the dry mass measurements (QPI, quantitative phase imaging) because we view this quantification as one of the most direct measurement to monitor cell growth/division. The approach measures the changes in dry mass as the cells prepares for cell division. So not only do we get the final readout of division (complete cytokinesis), but we also get a measure of that growth rate (the cell getting ready to divide) before cytokinesis. This is why we are so tickled to collaborate with Tom Zangle’s lab because we could finally get a direct proliferation readout in real-time. We could also use this approach to follow thousands of cells at a time, a very critical aspect since mitochondrial transfer is rare event, and therefore, we need to follow many cells to have enough statistical power to quantify the growth rates. Check out some of the Zangle lab’s other papers (PMC5866559; PMC6917840; PMC4274116), and please let us know if you disagree with us!

      Major Discussion Point #6: The authors have used such a tracking-based approach on a very small scale (n=5) to measure daughter cell growth rate. However, the data do not show a statistically significant difference between the growth rates of daughters that inherited transferred mitochondria and those who did not (Fig S3). Increasing the case number via high content imaging would help obtain sufficient data points for a reliable statistical test. In addition, as suggested above, an accounting of the daughter cells' division rate for transfer positive and negative cells would provide another line of evidence to either prove or disprove the increased proliferation rate hypothesis. The same suggestion goes to the optically induced ERK activation experiments shown in Fig3F. It is also helpful to include references that studied how ERK signaling promotes proliferation and compare the evidence here with evidence or assays used in those studies as a benchmark.

      Specific Comment:Figure S3 - There is no statistical test to check for ‘increase in their rate of change of dry mass over time versus sister cells that did not inherit macrophage mitochondria’. What are the colours indicative of in S3B? Can this be reported in the figure legend.

      🡪You are right – the tracking-based approach on daughter cells is based on a small ‘n’. However, the tracking itself is performed on 1000s of cells. It’s just that in order to capture daughter cell data, we have to find a cancer cell with macrophage mitochondria (which is only ~1% of the population), and then follow that cell until it divides, and then follow BOTH daughter cells. So, even with the 1000s of cells that we followed, we could only capture a small number of daughter cells. The colors in S3B represent each individual triads – parent and 2 daughters. We will make this info clearer in the legend.

      In terms of the optically-induced ERK activation experiments, yes, it would be great to have a higher sampling. These experiments were performed at 63x so we could reliably draw small ROIs to mimic the size of a macrophage mitochondria. While we switched to lower magnification to follow cell division, we still were limited to only a few cells for the actual photoactivation. The technical aspects of this experiment were the reason for the low sampling. Despite these limitations though, we still observed increased cell division upon mito-killerred photoactivation, which we were honestly pretty surprised (and stoked) about.

      Other specific comments:

      -Figure S1A - The authors could perhaps use a more aggressive gating strategy here, clipping closer to the 231 population described in Fig S1A - picking only the center of the cluster in the upper left of the RFP vs CD11b plot would likely not affect results but make them more convincing by unequivocally excluding macrophages.

      -Figure 1D - Not sure about the 0.2% baseline assigned for the monoculture of cancer cells (that does not have the macrophages with the Emerald mitochondria). It is determined with cytometry - I am no expert on that topic, so maybe I missed something - but it looks weird to see some cells with transfer when there is a monoculture.

      🡪Due to the variable nature of the mito-mEm signal in the recipient cancer cells (i.e. transfer of one mitochondrion vs transfer of three), we found that an overlap of 0.2% set on a fully stained monoculture control was the most accurate way to gate for the recipient cancer cells. The final gating strategies used in our study were determined by FACS-isolating populations of interest based on several different gating strategies, and directly visualizing cancer cells with macrophage mitochondria without capturing macrophages or cancer cell/macrophage fusions (which is cool, but not what we wanted). To further clarify, there is no transfer occurring in the monoculture – the overlap of mEmerald signal into the transfer gate in that control sample is likely reflective of normally occurring autofluorescence. This is a very important point, so we will make this aspect clearer in the Methods section.

      -Figure S1B - Could perhaps be an interesting follow-up question for future works re: differences between cell lines and propensities to transfer mitochondria. Did the authors attempt to use other cell lines (ie, MDCK, HeLa, iPSCs, etc)?

      🡪Great question and something that we have also been thinking about. To date the only recipient cells we have used are 231, MCF10A, and PDxO cells. This would be a great avenue for future studies.

      -Figure S1B - Did the authors see an increase in growth rate in MCF10A line despite the lower growth rate?

      🡪We have not measured the growth rate in MCF10a recipient cells but something that would be great to follow up on in future studies.

      -‘physically separated from macrophages by a 0.4μM trans-well insert’ - should this read 0.4 micrometer?

      🡪Yes, great catch.

      -Figure S1F - The authors wrote that they used a two-way ANOVA analysis, could you report the factors used for that analysis in the Figure legend.

      🡪Noted!

      -Figure 1B - It is difficult to see the arrowheads in 1B, suggest moving them so they are not covering the magenta fluorescence, have them point from a different angle, and make them more brightly colored. Insets here would help the reader. A negative control image from a monoculture would also be helpful, to ensure the GFP signal is not an artifact of culture conditions.

      🡪Thank you for your feedback – we will take note of this.

      -Figure 1F - For graphs that do not show zero (as in 1F), the bar should be omitted. In these cases the length of the bar does not reflect the average of the data (as it does in 1D).

      -Figure 3C - Please omit bar, see comment on panel 1F.

      🡪 In the case of Fig 1F, we modified the y-axis to eliminate empty space. The bar is representative of mean of the data displayed in both 1D as well as 1F, but we can add a broken y-axis to help make this point.

      -Figure 1 - Given that these data are fractions of a population (ie. can be described via a contingency table), isn't something like a Fisher's exact test a better measure of significance here?

      🡪We think you are referring to Figure 1D? If so, we thought that we could not use Fisher’s exact test because that test assumed parametric distributions (which we do not observe). We have been working with a biostatistician for our statistics, but please do let us know if we have it wrong.

      -Single cell RNA- sequencing - In the methods section the authors mention doing a differential analysis between the cells that received the mitochondria and the cells that didn’t. It might be worth introducing a figure (a heatmap or a U-MAP) relating to this analysis. Single cell sequencing would not only affirm the heterogeneity between these two populations but also help in highlighting the novel cell surface markers associated with the two populations.

      🡪Yeah, good point – we can add a UMAP.

      -‘mito-mEm+ mitochondria remained distinct from the recipient host mitochondrial network, with no detectable loss of the fluorescent signal for over 15 hours’- It is surprising that the transferred mitochondria do (or cannot) fuse with the host 231 mitochondria.

      🡪We were also initially surprised to find that the transferred mitochondria do not fuse with the host 231 network! We think that the lack of fusion is due to the fact that the transferred mitochondria do not exhibit membrane potential (which is required for mitochondrial fusion). We also think that these results open interesting lines of questioning: Why are these depolarized mitochondria not degraded? Is this an active avoidance of the mitophagy pathway? How dynamic are these punctae? Many fun and interesting questions regarding the long-lived nature of these transferred mitochondria.

      -It is unclear in these images, but the 231 mitochondria appear fragmented too. Is it possible that the mitochondrial fusion machinery (Opa1 or Mfn1/2) are inactive?

      🡪231 cells are capable of fission and fusion (PMC7275541, PMC3911914, and in our own timelapse recordings), so we think that the machinery is functional. However, we don’t know whether the 231 mitochondrial machinery changes after receipt of macrophage mitochondria. Interestingly, the references above both investigate how mitochondrial dynamics promote tumor metastasis. A fascinating future direction could include an investigation to how macrophage mitochondrial transfer influences tumor cell mitochondrial dynamics.

      -Figure 2B - What does the MTDR staining of the macrophage mitochondria prior to transfer look like? Important to check this to confirm that only the transferred mitochondria had lower membrane potential.

      -‘significantly higher ratios of oxidized:reduced protein were associated with the transferred mitochondria versus the host network’-Here too, it would be important to check the mito-Grx1-roGFP2 readout of macrophage mitochondria prior to transfer.

      🡪The way that these comments are written is as if we already know that the mitochondria are dysfunctionalbefore transfer to cancer cells. But we actually do not know if that is the case. It’s also possible that macrophage mitochondria become dysfunctional once they are in the cancer cell, which would be equally cool. So, we are actively investigating this biology.

      -Figure 2A, 2BB and S1D - How were the colocalizations assessed? Was it just a visual assessment? Given the importance of these experiments for the whole story, having a quantification of the level of colocalization with each dye would be important.

      🡪This is a good point and it should be straightforward to include a Pearsons coefficient for these markers.

      -Figure S1D - The paper makes an argument about mitochondria transferred from Macrophages (marked green) having positive DNA stain (gray), but appearing depolarized (negative TMRM stain). The image in FigS1D is peculiar, as the majority of the 231 cells' mitochondria appear to not have any DNA stain but maintain membrane potential (positive in TMRM), while some (just above the green macrophage mitochondria) do have both DNA stain and membrane potential. The authors might want to clarify whether this is a typical scenario, and if so perhaps offer an explanation as to why the 231 mitochondria exhibit such heterogeneity.

      🡪The images in S1D are of a single z-plane image therefore the DNA signal in the endogenous network is more readily visible in planes that are not shown.

      -‘we confirmed that 91% of transferred mitochondria were not encapsulated by a membranous structure, thus excluding sequestration as a mechanism for explaining the lack of degradation or interaction with the endogenous mitochondrial network’ - This is based on co-staining with MemBrite 640/660, which is a dye that "covalently labels the surface of live cells", thus there is a concern as to whether this approach allows to study whether the mitochondrium is encapsulated by an endomembrane.

      🡪Thank you for your feedback. We actually do think that Membrite can label endomembrane in addition to the plasma membrane. This is from the published Membrite protocol: “MemBrite™ Fix dyes are designed to be fixed shortly after staining, when they primarily localize to the plasma membrane/cell surface. Cells also can be returned to growth medium and cultured after staining, however, dye localization in live cells changes over time. Labeled membranes become internalized, so staining gradually changes from cell surface to intracellular vesicles, usually becoming mostly intracellular after about 24 hours. Internalized MemBrite™ Fix dye is usually detectable for up to 48 hours after staining, though this may vary by cell type”.

      In our hands, we found that the dye started to become internalized and labeled vesicles within the cell within a few hours of staining. The images in the panels that you refer to came from time-lapse imaging experiments of between 10-15 hours, therefore the cells have internalized the MemBrite signal allowing for the visualization of internal vesicles. Also, in other studies not in the preprint, we perfused purified mitochondrial preparations onto 231 cells. The 231 cells took up the mitochondria from the environment, and all of these engulfed mitochondria were surrounded by a MemBrite positive membrane! These results further suggest that if the transferred mitochondria were encapsulated by a membrane, we would be able to visualize it.

      _-‘macrophage mitochondria are depolarized but remain in the recipient cancer cell’ -_Did the authors examine the extent of cancer cell death in their co-culture system (due to the activation of apoptosis by the depolarized mitochondria)?

      🡪We do not find any evidence of abnormal levels of cell death by both flow cytometry assays as well through our QPI image analysis.

      -Figure 2C–D - Like in Fig 2B, in the bottom left of panel of Fig 2C there are a lot of donor mitochondria not in highly oxidized state and the growth/proliferation phenotypes apply mostly to donor mitochondria that appear 'clumpy'.

      -Perhaps it is worth commenting on whether there is a link between donor mitochondrial morphology and the suspected proliferation-enhancing phenotype.

      🡪The images in Fig. 2C are of the same cell – a single recipient cancer cell which is expressing the Grx biosensor. The donor mitochondria are labeled with an arrowhead, the rest of the yellow/green signal (bottom right) is from the endogenous host network and therefore we do not expect it to be in a highly oxidized state (ie. more yellow than green).

      Regarding the mito morphology and proliferation – great question, and one that we are actively working on!

      -‘At 24 hours, we observed a similar trend, but no statistically significant difference (Fig. S4D). These results indicate ROS accumulates at the site of transferred mitochondria in recipient cancer cells’ - if a specific sensor fails to show a significant oxidation at 24 hours compared mito-Grx1-roGFP2 which reports on mitochondrial glutathione redox state, does that mean there are ROS independent ways to oxidize Glutathione? The authors did see cell growth phenotype both in 24 and 48 hours which suggests that something is happening in 24 hours despite no significant difference in ROS H2O2 sensor.

      🡪The additional biosensor that we used – mito-Orp1-roGFP2 - has been engineered to be a readout of one type of ROS – H2O2. The Grx probe is a surrogate for ROS of any type, of which there are many! To us, it is not completely unexpected that they would behave differently over time since they are readout for two separate things, and it generates an interesting possibility that different types of ROS accumulate over time. Given that the Grx probe shows an increase at 24 hours, which is when we observe the proliferation phenotype, we think we are on the right track. If you have ideas on robust ways to directly observe specific types of ROS, we would love to know!

      -The differences in ratio for the two sensors used are not very convincing. In Fig 2D and Fig S4B and D the “host” and “transfer” populations are very similar. The difference seems only due to the presence of a few outliers in the “transfer” populations. More importantly, sometimes it seems that these outliers come mostly from one donor rather than being present in all 3 donors. It could be good to show histograms of the two populations for each replicate/donor and maybe redo the stats excluding these outliers.

      🡪We think that the heterogeneity that is observed is due to the biology in the system – we are using primary macrophages derived from blood donors. However, for the data represented in Fig 2D, just as a test case, we took out the top four “outliers” in that data set and re-ran the Wilcoxon matched-pairs signed rank test and the p-value was 0.0010 (***), further suggesting that the ROS biosensors are revealing consistent and robust results.

      -Figure S5C - it seems like the percentage of cells that divided is the same for unstimulated cells and cells with stimulated mito-KillerRed. Isn't this contrary to the expectation? The figure shows that photobleaching cytoplasm decreased % cell division, which is puzzling.

      🡪The mean percent of cells that divided in unstimulated and mito bleach are very similar and was not significantly different. One point to be made that may not be well illustrated in our graphical representation is that if you look at the matched data (points connected are averaged per FOV for each condition in the same experiment) the trend shows that the mito bleach does seem to have an increase in cell division which is washed out with the average bar overlay. We should note that this experiment is very “noisy” and therefore we needed a lot of N to be able to detect significant changes. We are currently thinking about other ways to demonstrate sufficiency as it relates to cell proliferation – any experimental suggestions would be very welcome! Thanks for the feedback.

      -Figure 3A - In the 'cyto' condition 6 out of 13 fields have no cells that divide. Is that expected? What is the percentage of dividing cells for cells that were not illuminated at all (a control that is lacking)? There is large variation, ranging from 0% to 22%. The evidence that illumination of KillerRed leads to increased proliferation is rather weak. Also, since Cyto and Mito are different cells, is a "paired" statistical test the right kind of test to use here?

      🡪Additional data pertaining to Fig. 3A can be found in Fig. S5C, which includes the control for cells not illuminated at all. Having no cells that divide in a field of view is not surprising to us – the doubling time for these cells is ~35 hours, and we imaged for 18 hours. Also, for each field of view, our ‘n’ for each field of view was often 6-8 cells because we performed these experiments at 63X to allow for accurately drawn regions of interest for photoactivation. We also internally controlled every experiment (each experiment consisted of fields of view that had either mito activation, cyto activation, or no-activation controls, all of which were imaged overnight with multiple x/y positions). Cells that left the field of view over the 18 hours of imaging could not be quantified. It’s this sampling that caused the large variation in the graph. But again, as with many of our experiments, despite this variability, we still observe a significant difference in our experimental conditions over control cyto bleach. As for the statistical test, our understanding is that given each experiment is internally controlled, and we compare within each experiment, a paired statistical test is appropriate here. We will consult with our biostatistician to confirm, though.

      -‘ROS induces several downstream signaling pathways’ - We would not expect the authors to investigate every signaling pathway, but wonder if the PI3K pathway was explored? It seems to be the other major cancer/proliferative pathway induced by ROS.

      🡪Yes, this is a very good point! We actually assessed three different pathways at first – ERK, PI3K-AKT, and NLRP3/inflammasome. While analyzing these 3 pathways simultaneously, we discovered that ERK inhibitors resulted in decreased proliferation in cancer cells with macrophage mitochondria. As a result, we then focused on the ERK pathway. We still do not know if PI3K-AKT or NLRP3/inflammasome pathways play a role in this biology because we have not gone back and revisited these experiments yet, however in figure 3F, ERKi treated recipient cells exhibit a partial ‘rescue’ of baseline proliferation. This suggests that other pathways may indeed be involved and we plan to investigate this possibility.

      -‘Recipient 231 cells had significantly higher cytoplasmic to nuclear (C/N) ERK-KTR ratios compared to cells that did not receive transfer’-Since two different quantification styles with opposite fraction values were used, is it possible to please specify which one was used here.

      🡪Will do!

      -Figure 3B - Please show the outlines of the nuclei and that of the cell.

      🡪That would be helpful, wouldn’t it? Will do!

      -Figure 3D - it is peculiar that ERK-KTR in Fig 3D is so strongly cytosolic while in Fig 3B it is almost exclusively nuclear. If this sensor behaves differently in different situations, the authors may want to comment on how that would affect their conclusions.

      🡪The panels in Fig. 3B were taken with the ImageStream flow cytometer which takes a lower resolution image of a single plane of a cell in suspension in the flow stream. In Fig. 3D, those images are from confocal spinning disk microscopy which allows for higher resolution, z-stack images of adherent cells on glass. Therefore, we think the differences that you point out are likely due to the fact that the two images come from very different imaging systems.

      -Figure 3E - The effect of 'opto-induced' ERK activity is weak. The initial ERK-KTR is 1 at time point zero (as the data is normalized to this timepoint) and around 1 for both the cyto and mito condition. A statistical difference is observed, but the effect is minor and it is unclear whether it is biologically meaningful. The 'cyto' condition shows an average below 1 and the mito condition remains 1, suggesting that ERK activity remains constant when ROS are produced in the mitochondria.

      -Also from S8C and 3E it appears cyto actually shows a decrease rather than mito showing an increase, could the authors comment on this?

      🡪We have a few thoughts on this. The first is that we don’t expect a dramatic change in ERK signaling because the ROS accumulation is localized to a small region in the recipient cell. This is not a situation where we would expect a large-scale change because we are adding a growth factor. We can understand that the change in ERK activity may appear to be minor, but our data suggest that these subtle changes in kinase signaling translate into significant changes in downstream behavior – proliferation. The way that we interpret differences as “biological meaningful” is whether they exhibit a functional response, and in our study, we show that inhibiting the induction of ERK activity in cancer cells with macrophage mitos inhibits proliferation. What is most interesting to us is that cancer cells that do not have macrophage mitochondria have an unchanged fraction of cells in G2/M phase of the cell cycle in response to the concentration of ERK inhibitor we used, suggesting that the ERK inhibition specifically blocks macrophage mitochondria-induced proliferation.

      In Fig. S8C, bleaching a region of cytoplasm does seem to cause a decrease in ERK activity over time. We really can’t explain this result. However, we do think that ERK activity is higher in mito-bleached cells because mt-ROS is generating an increase in ERK activity which compensates for the decrease in activity that occurs when the cytoplasmic region of interest is photobleached. It’s still a head scratcher, though, but we did perform internal controls for every experiment (as we describe above), and the mito-bleach, cyto-bleach, and no-bleach conditions were run side-by-side such that we can make apples-to-apples comparisons.

      -‘patient-derived xenografts (PDxOs)’ - As a control it would be relevant to include a normal mammary organoid model perhaps from the same patient to demonstrate that the transfer of mitochondria specifically to the cancer cells is more beneficial.

      🡪Using a normal mammary organoid cells as a control to compare efficiency of transfer and downstream phenotypes would be very interesting. Due to the fact that these are patient-derived organoids, we are unable to acquire non-malignant cells from the same patient. Expanding our studies in the MCF10A cell line that we utilized in this paper would be an alternative to what you propose and would also expand our understanding of general biology underlying mitochondrial transfer.

      -‘macrophages to both HCI-037 and HCI-038 PDxO cells (Fig. 4G)’ - Why is M0 able to transfer efficiently to HCL-037 tumour when its mitochondrial network is less fragmented as M2?

      🡪These results really stood out to us. It was quite surprising that in HCI-037, both M0 and M2 macrophages were able to transfer their mitochondria at similar efficiencies, but in HCI-038, M2 macrophages were more efficient at transfer. HCI-037 is a primary tumor, and HCI-038 is a metastases from the same patient, so there are some exciting avenues of study to examine how macrophage mitochondria transfer differs at the primary versus metastatic site. There is still very little known about how donor cell dynamics influence mitochondrial transfer!

      -Are mito transfer from M0 depolarised and accumulate ROS or show increased ERK activity or increased cell proliferation?

      🡪Yes – all studies, except studies pertinent to fig 4 (where we assessed macrophage differentiation states), were done with M0 macrophages.

      -‘M2-like macrophages preferentially transferred mitochondria to the bone metastasis PDxO cells (HCI-038) when compared to primary breast tumor PDxO cells (HCI-037)’ -The authors may want to check this statement here as it is in consistent with their data plot. In Fig. 4G, M2/PDxO transfer percentages for HCI-037 and HCI-038 are about the same, unless the authors provide statistical tests to prove otherwise. Instead, M0 appears to transfer mitochondria to HCI-037 much more efficiently than it does HCI-038.

      🡪Upon re-reading our sentence again, we now realize that it’s actually quite poorly written, so we can understand the confusion! What we meant to articulate is that M2-like macrophages are better at transferring mitochondria to HCI-038 than M0 macrophages. Whereas in HCI-037, we do not observe the same preferential transfer (ie. M0 and M2 can transfer at the same efficiency). We will certainly clarify this language in the manuscript.

      -‘M2-like macrophages exhibit mitochondrial fragmentation’ - Is there a correlation between the status of the mitochondrial network in the donor and the % of transfer to the recipient? If so, this would be a correlation that would support the conclusions.

      🡪Yes, please see Fig. 4C for transfer rates with different donor subtypes and Fig. 4H for a general working model on how we think these data fit into the larger picture.

      -‘accumulate ROS, leading to increased ERK activity’ - Did the authors obtain similar results with the PDXOs? It would be an interesting observation if the primary samples also exhibit a mechanism similar to established cell lines wherein there are more accumulated genetic changes.

      🡪Our main limitation with PDxOs is overcoming the technical hurdles related to our downstream assays. These include introducing relevant reporters and generating stable lines in the PDxOs, and imaging at high-resolution when the PDxOs are cultured in 3D. However, we are very interested in this question as well, and are actively thinking about ways to overcome these hurdles.

      -It would also be interesting to examine whether there is any difference in the ROS-ERK mechanism for primary and metastatic tumour.

      🡪We agree and this is an active avenue of investigation for us. We agree and are currently pursing models to understand how our findings fit into the larger picture of tumorigenesis and metastatic potential. We had spent months pursuing anin vivo approach using a murine Cre/LoxP system to genetically label mouse macrophage mitochondria with GFP. We crossed mice which express Cre under a monocyte-specific promoter (Jax, SN: 004781) and mice with germline expression of Lox-Stop-Lox-3xHA-EGFP-OMP25 (Jax, SN: 032290) with the expectation of seeing Cre-based excision of the stop cassette – thus resulting in offspring with macrophages expressing mitochondrial-localized GFP. However, the macrophages of the resulting offspring do not express GFP (by flow cytometry, imaging, and western blot analysis), despite the PCR-verified presence of both transgenes and the excision of the stop cassette. Needless to say, this was quite frustrating! We are currently in the process of developing a newly available MitoTag model which has been optimized for visualization purposes (Jax, SN: 032675). If you have any suggestions or advice on this matter we would much appreciate your thoughts!

      -‘in cancer cells that receive exogenous mitochondria’ - Since these macrophages also transfer mitochondria to non-malignant cells, such as MCF10A cells shown in Fig S1B, perhaps the authors could comment on whether this is part of a physiological process that would also promote normal cell growth?

      🡪 There are so many questions regarding when and why macrophages might transfer mitochondria. In general, mitochondrial transfer is observed in stressed cells. Our data suggest that transfer happens to MCF10A cells although at a much lower rate than their malignant counterparts, 231 cells, but we do not know whether similar downstream mechanisms and phenotypes are also occurring in the non-malignant cells. Thanks for your feedback – more to come here!

  6. Jul 2021
    1. 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

      Dear reviewers,

      We thank all reviewers for and their appreciation of our work and even more so for their constructive comments and suggestions, which will significantly improve the quality of the manuscript. We were able to complete the revision and address all reviewer comments. Aside a more stringent discussion of the literature, and rewording of certain paragraphs for clarity, we also generated additional experimental data.

      More importantly, to address the concern that we did not provide a positive marker for the intranuclear compartment, we present new images. We attempted to label gamma-Tubulin by generating new antibodies, GFP-tagged strains, and trying multiple commercial antibodies since the beginning of the project. Only recently we found an antibody providing a more specific signal at the expected location, although with some likely cross-reactivity with alpha- and beta-tubulin, and now show these data in the supplements. Additionally, we generated expansion microscopy samples stained with a fluorophore-coupled NHS-Ester, a bulk protein label. These data show that the centrosome contains an exceptionally protein dense hourglass-shaped region, which spans from the extranuclear to the intranuclear compartment, as revealed by centrin and tubulin co-staining. This fortifies our claims about the distinct nature of the intranuclear centrosome compartment containing the microtubule nucleation sites.

      Further, we add images of 5-SiR-Hoechst, SPY555-Tubulin, Centrin1-GFP triple labelling live cells to demonstrate the specificity of the microtubule dye and to underline that we are indeed acquiring the dynamics from the first nuclear division on.

      In terms of formatting we added line numbers and uploaded high quality figures separately. Due to the added data and panels we needed to split Fig. 1 into two separate figures, rewrote the figure legends and moved them to the end of the document.

      Please find below a point-by-point response to the comments.

      Best regards,

      Julien Guizetti

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

      The manuscript by Simon and collaborators addresses the dynamic changes of spindle and hemi-spindle microtubules occurring along schizogony in Plasmodium falciparum. The work explores the temporal correlation of the changes observed in intranuclear spindles with changes at the level of the centriolar plaque; the nuclear microtubule organizing center of these parasites, using centrin as a bona fide marker of the structure. The study shows that spindle microtubules organize from an intranuclear region, devoid of chromatin, distinct from the centrin region which had not been observed or described before. It further shows that centrin does not localize at the nuclear envelope, but it is actually extranuclear.

      This work significantly expands on previous knowledge regarding the functional and spatial organization of the nucleus in P. falciparum, and the structure once defined as "an electron dense mass on the nuclear envelope." It uses state of the art microscopy approaches such as STED, UExM and CLEM, in combination with immunolabeling, dyes and parasites over expressing fluorescent protein fusions, to address these questions.

      **Major comments:**

      • Are the key conclusions convincing?

      I find the manuscript successfully addresses the posed questions. The data presented supports the conclusions.

      • Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

      • Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

      No

      • Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

      N/A

      • Are the data and the methods presented in such a way that they can be reproduced?

      Yes

      • Are the experiments adequately replicated and statistical analysis adequate?

      Yes

      **Minor comments:**

      • Specific experimental issues that are easily addressable.

      On the data shown in Figure 1, it is unclear to me what elements are taken into account to define "anaphase." Anaphase could be defined by using chromatin markers - such as CenH3- which have been identified in Plasmodium and the authors make use of in Figure 1F.

      We acknowledge that the term anaphase is ill-defined here. Further it suggests a mitotic morphology analogous to the one observed in “classical” models (prophase, metaphase, anaphase,…), which is not fully appropriate. In line with the comments by Reviewer 3 we, therefore, decided to use the term “extended spindle” instead (Fig. 1 & 2). This better reflects the morphological criterion on which we based the stage definition.

      • Are prior studies referenced appropriately?

      The authors state that "with the exception of centrins and gamma tubulins" few canonical centrosome components are conserved in Plasmodium. These parasites are in fact able to assemble a more or less canonical centriole for microgamete basal body formation. Widely conserved centriolar components such as Sas6 are coded by the malaria genome, and have been characterized previously. This work is neither referenced nor discussed in the manuscript.

      The reviewer is right to point out this omission. We were too much focussed on the blood stage centriolar plaques while writing this section, where centrioles are not observed. Of course centriole-like structures are relevant in other life cycle stages, such as microgametes, and should be discussed (line 104). Some previous attempts to endogenously tag Sas6 to verify its localization in blood stages were unfortunately not successful.

      • Are the text and figures clear and accurate?

      I find the timings shown in Figure 1A, with respect to the schematic quantification shown in Figure 1B, confusing. Shown as it is, one naturally correlates the images on Fig1A above with the cell cycle progression timing shown on Fig1B, below. However, by time 260min, for example, two somewhat adjacent centrin signals can be observed. Though this is defined as anaphase- by an unspecified criterium- this could very well be representative of metaphase. Nonetheless, the timing shown on Figure 1B for "anaphase" onset is 170min, which is inconsistent with the images above. I suggest that either, the quantification is shown in a different format (ex. bar plots) which could then better reflect the cell to cell variations observed (by use of error bars, for example) or that the figure explanation in the results section clarifies this issue.

      We understand how this representation is misleading and have adjusted the figure and text accordingly. We modified the time stamps in Fig. 1A (now Fig. 1C) to the scale used in Fig. 1B (now Fig. 1D) i.e. collapse of the hemispindle is t=0 and explain this in the text (line 158). Since we feel that Fig. 1B (now Fig. 1D) is a good and compact visual representation of progression through the first division we kept the bar plots in the supplements (Fig. S1), but added a title clarifying that average duration between multiple movies are shown.

      As presented, the data in Figure 1C is rather uninformative. A pattern could be more immediately extracted if dots corresponding to subsequent appearance of centrin dots in the same nucleus were connected to each other.

      Concerning the appearance of the centrin signals we adopted the good suggestion by the reviewer and connected “paired” centrin signals by lines (Fig. 1E).

      • Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

      There are a number of edits required on the text. Row numbers would have been helpful in pointing these out. I point some edits below, but thorough revision of the manuscript for grammatical and synthetic errors would be beneficial.

      • Cytokinetic segmeter - please replace with "segmented"

      • Please refer to Figure 1D when appropriate - there is quite an extensive paragraph describing the results shown on this figure, but it is only referenced at the start.

      • "..., as did the and the number of branches per nucleus,..." please rewrite as appropriate.

      We apologize for not providing line numbers, but have corrected the addressed points and applied a grammatical check throughout the manuscript. We have added additional references to Figure 1D (now Fig. 2A) in the text.

      Reviewer #1 (Significance (Required)):

      This manuscript could be interested to a wide audience interested in cell cycle, cell division, cell organization and organelle positioning, infectious diseases and microscopy. However, the introduction assumes that readers are somewhat experts in the malaria field. I suggest the authors include a brief introduction of the malaria life cycle, and a schematic representation of the division mode. This will help non-experts follow the narrative more easily.

      We are happy to read that the reviewer sees value of this study for a broader audience. Following the suggestion, we added a small schematic (Fig. 1A, lines 54, 62) highlighting the relevant steps of schizogony and expanded the introduction of the life cycle (line 46).

      This work rectifies long-standing inconsistencies observed by different experimental approaches in the nuclear organization of malaria parasites during schizogony. However, what the functional consequences of the alternative modes of spindle organization in malaria could be, are not clearly stated or discussed. In this respect, as it stands, the manuscript is rather descriptive and lacks mechanistic insight. Nonetheless, the data presented are of superb quality, and the manuscript represents a tremendous leap in structural insight and imaging resolution for the field of malaria. I find the data is suitable for publication albeit minor adjustments are made (specially to Figure 1 and/or the description of the results shown in Figure 1, for consistency).

      We agree that the value of this manuscript lies in the clarification of conflicting data, unprecedented structural insight, and providing a useful working model for the malaria parasite centrosome. Although this study is ultimately descriptive it forms the indispensable basis to generate more meaningful functional insight about centrosome biology and nuclear division. Some of the functional consequences worth considering are: i) The (at least) bipartite composition indicating that centrosome functionality is spatially spread throughout the nucleoplasm/cytoplasm boundary. ii) The delayed appearance of the centrin signal after tubulin signal allows the prediction that centrosome assembly is a staged process occurring over an elongated period of time. iii) The generally amorphous structure of the compartment predicts the involvement of yet to be uncovered matrix-like proteins harbouring microtubule nucleation sites. iv) Lastly, our model has important implications for the mechanism of centrosome duplication. In a centrosome containing centrioles (like in vertebrates), the duplication event can easily be explained by physical separation of the daughter and mother centrioles. Spindle pole body duplication in yeasts is achieved by de novo formation of a new one, which remains connected by a half bridge until it is split. The centriolar plaque organization revealed here suggests that we need an entirely new model of centrosome duplication (or splitting) to describe and understand this process in malaria parasites. We now address those points more explicitly in the discussion section (e.g. lines 375, 443, 467).

      **Referee Cross-commenting**

      I agree with all the other reviewer's comments. I'm glad the reviewers seem to be experts in the field of malaria cell division and have pointed out previous studies which were not appropriately referenced. I second those comments.


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

      **Summary:**

      The manuscript by Simon et al have used advance cell biology technology like STED, expansion and live cell imaging to decipher the configuration of microtubules, centrin and nuclear pore during unconventional cell division process in malaria parasite. They have shown the dynamics of centrin and its localisation with respect to centriolar plaque that is characteristic of these parasite cell during schizogony> They also implicate from their studies that there is extended intranuclear compartment which is devoid of chromatin

      **Major Comments**

      • Are the key conclusions convincing? Yes to some extent

      • Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

      *Some part are preliminary and speculative as there is no solid data supporting it. Please see below

      • Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

      *Yes to substantiate their claim

      • Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

      *They can do these quite quickly less than a month

      • Are the data and the methods presented in such a way that they can be reproduced?

      *Yes

      • Are the experiments adequately replicated and statistical analysis adequate?

      *Yes

      The authors present beautiful imaging and some in depth structure using tomography and CLEM to show the location of centrin which is generally considered the marker for centrosome or Microtubule organising centre in malaria parasite. These approaches are still not been applied in Plasmodium and hence very informative. Though they present some advance microscopy but a lot of these concept for hemispindle were shown earlier in many light and super resolution microscopy studies. Authors claim that they are first to show that there is space between centrin and nucleus but it has been show previously in centrin studies in Plasmodium berghei using super resolution microscopy (Roques et al 2019 Fig1 and supplementary videos1&2) as well as expansion microscopy recently by group of Brochet etal 2021.

      We thank the reviewer for the appreciation of our work. We are, indeed, not the first to describe the gap between centrin and tubulin or the nucleus. We just aimed to reiterate this finding, also visible in our data, in order to transition to the analysis of nuclear pore positioning to clarify whether centrin is actually extranuclear. Nevertheless, we should have cited the Roques and Bertiaux et al. studies again in this context, which we have now rectified (line 252).

      In addition the microtubule dynamics was also recently shown with Kinesin5 live cell imaging for schizogony in Plasmodium berghei (PMID: 33154955) which author have omitted in their manuscript.

      We thank the reviewer for pointing out the Kinesin-5 study by Zeeshan et al., which we failed to cite and discuss. We now state the findings of this publication and put it into the context of our work (see also answer to next point). Microtubule associated proteins, such as the microtubule plus end tracking EB1 and the aforementioned Kinesin-5, are indeed useful markers to investigate microtubule dynamics leading to the interesting results shown by Zeeshan et al. Nevertheless, we want to point out that labelling microtubule associated proteins (MAPs) remains an approximation of the underlying microtubule organization. As the authors in Zeeshan et al. indicate by themselves, Kinesin-5 does not decorate axonemal microtubules or the membrane-associated microtubule structure formed during cytokinesis in very late schizont stages. Further, colocalization between alpha-tubulin and kinesin-5 in schizont-stage parasites is not complete indicating a preferential decoration of certain sections of the microtubule structures (possibly the microtubule ends), which could only be resolved by super-resolution microscopy. Using a live cell dye, such as SPY555-tubulin, which directly binds to microtubules will provide a uniform labelling of any microtubule species and hopefully prove useful to the field in the future. Lastly, we present time-lapse microscopy analysis of blood stage cells, contrary to single time point images of live cells, providing a quantified chronology of microtubule reorganization at single cell level (with time stamps). Therefore, we feel that our claim, although it should be relativized, is formally speaking accurate.

      It is also important that authors give valid discussion about previous studies on hemispindle, microtubule dynamics with respect to schizogony (PMID: 18693242; PMID: 11606229; PMID: 33154955) rather than giving the impression that they have given this concept first time on hemispindle dynamics and centrin location during schizogony.

      We agree that those studies should be discussed in more detail. We are grateful to the reviewer for pointing out the Fowler et al. 2001 (PMID: 11606229) study. They use an antibody against gamma-tubulin to demonstrate its presence at the apical pole of subpellicular microtubules (f-MAST) in the merozoite and cytokinetic stages (line 102). However, we were unable to reveal a specific gamma-tubulin staining using the antibody used by them in the preceding schizont stage. After trying many different commercial gamma-tubulin antibodies and attempting to generate our own we now finally observe a gamma tubulin localization at the poles of intranuclear spindles in schizont stage, although the only successful antibody still displays some background staining, possibly including cross-reactivity with alpha or beta-tubulin (Fig. S4, line 237).

      The highly insightful study by Mahajan et al. 2008 (PMID: 18693242) indeed suggests that centrin localizes away from the DNA and demonstrate the distinct localization from tubulin. They, however, likely due to the resolution limit of their microscopy techniques, speculate that the centrin signal is embedded in the membrane, while we could show by super-resolution and nuclear pore staining that centrin is distinct from the membrane (now Fig. 2A; line 257). The work done by Zeeshan et al. 2020 (PMID: 33154955) nicely shows dynamics of kinesin-5 in nuclear division. In schizont stages Kinesin-5 signal elongates and splits alongside the mitotic spindle with which it overlaps for the most part. Colocalization with centrin is less strong although the authors note some overlap. Our data suggest that centrin and tubulin are clearly distinct. In male gametes the authors show nicely time-resolved data of kinesin spreading along the elongating spindle, although hemispindles are not observed at this stage. We introduce and discuss these findings (lines 123, 432).

      The concept of bipartite centrosome is already been discussed in Toxoplasma and the claim by authors in Plasmodium presented here is not substantiated experimentally. They showed that centrin is part of outer region while they do not show with any marker for the inner region. It will be very helpful if the authors use gamma tubulin or MORN1 to show the location with respect to centrin and microtubule. In the absence of this localisation the claims are preliminary and speculative. If the centrosomal protein complex is not involved in microtubule nucleation, then how the nucleation is happening. What are the molecules present in this amorphous matrix? It will be great to check the location of gamma-tubulin or some inner centrosome molecules described in Toxoplasma that is deemed to be MTOC.

      We share the opinion that our Plasmodium data should be compared to Toxoplasma, while still being assessed independently. Despite Toxoplasma belonging to the apicomplexan the conclusion that their centrosomes should be organized in a similar fashion is by no means self-evident considering for example their significant evolutionary distance. Actually, several noteworthy morphological differences have already been well documented. i) Toxoplasma MTOC does contain centrioles in the outer core which is coherent with the centrin and gamma-tubulin localization in this region. ii) Toxoplasma MTOC contains an additional nuclear membrane protrusion enclosing the inner core. iii) mitotic microtubules in Toxoplasma are thought to penetrate the nuclear membrane to connect to centromeres. iv) the inner and the outer core are both extranuclear and therefore not to be equated with the intranuclear compartments. We now expand a bit on the discussion of the aforementioned differences (line 382). Nevertheless, we thank the reviewer for making us realize that the term “bipartite” is a poor choice to describe the centriolar plaque organization in this context. Therefore, we replaced it in the abstract (line 29) and the main text (line 375).

      We acknowledge the fact that it would be desirable to show a marker localizing to the intranuclear compartment, and not only through visualizing the microtubule nucleation complex (Fig. 4A-B) and the positioning of the microtubule ends in this region (Fig. 3A). Concerning MORN1 we found no indication in the published localization data that it is, like in Toxoplasma, associated with the nucleus in Plasmodium species, where it is only found associated with the budding complex (and we are currently unable to procure an antibody) (line 422). We have attempted gamma-tubulin visualization on many occasions throughout the project (transgenic parasite lines, commercial antibodies, self-made antibodies) and only recently found an antibody revealing some specific signal. Indeed, we found localization at the poles of the spindles i.e. the intranuclear compartment (line 237). Unfortunately, this “best-possible staining” still showed some unspecific spindle staining likely resulting from cross-reactivity with alpha- or beta-tubulin causing us to put these data into the supplements (Fig. S4).

      We had more luck with attempting a “new” type of staining, recently used in Plasmodium (Bertiaux & Balestra et al. 2021) using a fluorophore-coupled NHS-Ester in expanded samples. This chemical unspecifically stains proteins and revealed that the centrosomal region contains an exceptionally protein dense “hourglass-shaped” structure (Fig. 3F-H). Since the outer part of this structure colocalizes with centrin and the inner part overlaps with microtubules we assume that the centrosomal complex stretches throughout the nucleo-cytoplasmic boundary and fills part of the intranuclear compartment (line 320). Especially the highly protein dense region at the neck of the “hourglass” seems very coherent with the nuclear membrane embedded electron dense region which can be seen in electron microscopy (e.g. Fig. 3E & 4B). We feel that this staining strongly supports the presence of this novel intranuclear compartment.

      The expansion microscopy is very nice and some of it presented in supplementary can be moved to main section.

      Thanks for sharing our enthusiasm about this imaging technique. We have now selected a representative image of a hemispindle and mitotic spindle stage nucleus imaged by U-ExM and added it to the main section (Fig. 2B, line 231).

      The localisation CenH3 is bit puzzling as it has been shown that centromere/ kinetochore cluster and are present during early and mid schizogony. The various foci with respect to nuclei are not what has been seen previously. Please discuss the difference in these two findings.

      The localization pattern can easily be explained by the increased resolution of STED nanoscopy used in this study. Previous studies (e.g. Hoeijmakers et al. 2012 and Zeeshan et al. 2020) used classical confocal microscopy. Under those imaging conditions the individual foci seen here can´t be resolved and would, in accordance with the other studies, appear as one cluster. We slightly modified the text for more clarity (line 247).

      Reviewer #2 (Significance (Required)):

      • Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

      * This is more technical advancement on the subject of centrin by using STED, tomography and CLEM.

      • Place the work in the context of the existing literature (provide references, where appropriate).

      * This work has relevance relation to cell division during schizogony in asexual stages in par with Toxoplasma or in Apicomplexa in general

      • State what audience might be interested in and influenced by the reported findings.

      Working with Apicomplexa, Protist, cell division and mitosis.

      • 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.

      Working on Cell division in Plasmodium.

      **Referee Cross-commenting**

      I agree with the reviewers and some of the experiment suggested and the minor details have to be addressed. There are some loose ends and these suggestions will enhance clarity of the data. It is a very nice study and some of the comments suggested by reviewers will improve the manuscript. __

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

      **Summary:**

      The centrosome is the primary microtubule-organizing center (MTOC) in eukaryotic cells that nucleate spindle microtubules necessary for chromosome segregation. In most eukaryotic cells, the canonical centrosome is composed of centrioles surrounded by an electron-dense proteinaceous matrix named the pericentriolar matrix (PCM) competent for microtubule nucleation mitotic spindle assembly. Following the breakdown of the nuclear envelope breakdowns, the mitotic spindle microtubules gain access to the kinetochores of the condensed mitotic chromosomes. Once the mitotic spindle is fully developed, centrosomes are at opposite poles of the cells, and chromosomes are pulled toward opposite poles. Cell division completes with cytokinesis resulting in the active formation of two nuclei within two daughter cells. Interestingly, during its asexual replication cycle, the malaria parasite Plasmodium falciparum undergoes multiple asynchronous rounds of mitosis with segregation of uncondensed chromosomes followed by nuclear division within an intact nuclear envelope. The multi-nucleated cell is then subjected to a single round of cytokinesis that produces dozen of daughter cells. We know about the Plasmodium centrosome is that it is made of an acentriolar structure embedded in the nuclear envelope and serves as MTOC during cell division. However, the biogenesis and regulation of the Plasmodium centrosome are poorly understood. Given the peculiarity of the cell division in Plasmodium parasites, understanding the molecular mechanisms that drive and regulate MTOC duplication and maturation could unveil novel targets for the treatment of malaria. In this study, Simon et al. successfully applied challenging and cutting-edge microscopy techniques to monitor the dynamic formation of the spindle microtubules and MTOC during Plasmodium intraerythrocytic mitosis. In addition, they remarkably combined stimulated emission depletion (STED) with ultrastructure expansion microscopy to define an uncharacterized intranuclear compartment devoid of chromatin as the nucleation site of nuclear microtubules. And lastly, the authors adapted an in-resin correlative light and electron microscopy (CLEM) approach to define the centriolar plaque position in a novel intranuclear compartment with centrosomal function.

      **Major comments:**

      1. In the methods section, it is stated that across this study, three different anti-tubulin antibodies (alpha-tubulin B-5-1-2, alpha-tubulin TAT1, beta-tubulin KMX1) were used, and two anti-centrin antibodies (TgCentrin1 and PfCentrin3) were used, one of which seems to have been generated in this study (anti-PfCentrin3). It is unclear in the figures or results section when each of these antibodies was used, and the authors should give a rationale for using multiple antibodies in combination.

      To label microtubules we used the mouse anti-alpha-tubulin B-5-1-2 (Sigma, T5168) antibody throughout the study. Except for U-ExM were we added two additional primary antibodies against tubulin. Due to the expansion of the samples the antibody binding epitopes are stretched out in space. This causes a significant reduction of local epitope concentration (expansion factor 4.5 in all directions results in ~ 80-fold increase in the volume), which can reduce the signal intensity. Adding multiple antibodies binding different epitopes of tubulin can compensate for this dilution effect to some degree, as has been shown before by Gao et al. 2018. At the same time the expansion contributes to the accessibility of the usually densely packed tubulin epitopes within the microtubule polymer, which certainly adds to the success of U-ExM. What the respective contributions of those effects are is not clear, but we found superior signal-to-noise ratios when combining three tubulin antibodies instead of using one. The TgCentrin1 antibody was only used in Fig. 2C (now Fig. 3B) and validated the localization pattern of our new PfCentrin3 antibody we used in the other pictures. We now provide clearer description of antibody usage in the methods section and a new supplemental table.

      The anti-PfCentrin3 antibody seems to have been generated for this study. If this is the case, the authors should provide evidence that this antibody binds to the recombinant PfCentrin3 it was raised against and binds PfCentrin3 in parasite lysates.

      The anti-PfCentrin3 antibody was, indeed, produced for this study and we should have provided our western blot data right away. We now show the requested blot, which shows bands at the appropriate size in parasite lysate as well as for the recombinant protein, in the supplements (Fig. S2, line 178).

      In the first paragraph of the Results section, the authors' remark of centrin foci that they are "...only detectable later (Mov. S2) or sometimes not at all." In Figure 1 A-C, it is implied that the first observed division is the first nuclear division of that parasite. Given that some nuclei do not have a visible centrin focus, it cannot be concluded with certainty that these parasites only contain a single nucleus and that this is their first division. The authors would need to include a quantifiable DNA stain to show this unequivocally to show a single nucleus. It has undergone DNA replication, similar to Klaus et al., 2021 BioRxiv paper. In the absence of a DNA stain, the authors should reword to clarify that this is the first observed division and speculate that it is the first division of that nucleus, but the authors should draw no firm conclusions about the first division.

      Indeed the variability in protein levels that can result from exogenous expression can lead to some cells not showing clear Centrin1-GFP foci. Although this is a rare event we wanted to acknowledge this observation. The live cell microtubule staining using Spy555-Tubulin we use is, however, highly specific and sensitive and would stain any nucleus undergoing division including the first one. If there would be more than one nucleus in the observed cell it would unequivocally show two clearly separated tubulin signals (hemispindle or mitotic spindle). To illustrate this we added Fig. 1B (line 148) showing two live parasites stained with SPY555-Tubulin plus a Hoechst-based dye showing one or two nuclei alongside the corresponding tubulin signal. We modified the text to clarify how we stage the parasite for time-lapse acquisition (line 154). We already extensively experimented with state of the art fluorogenic live cell DNA dyes (e.g. from Spirochrome and the Johnsson group) to visualize the nuclei directly in time lapse microscopy, but even at minimal concentrations they all significantly inhibit mitotic progression. We also add this information in the main text (line 150).

      In the first paragraph of the Results section, the authors write: " We quantified the duration of hemispindle, accumulation and anaphase stages ...." Anaphase spindle fibers means that the sister chromatids are separated. In the absence of a centromeric marker like NDC80, it doesn't seem easy to claim the anaphase stage. The authors should write " extended spindle." The authors might also consider using the term collapsed spindle instead of accumulation to reflect the dynamic of the intranuclear microtubules during the blood-stage replication. The same modification should be made for Figure 1B, so we read " hemispindle, collapsed spindle and extended spindle."

      We thank the reviewer for this suggestion, which is very much in line with a comment by Reviewer 1 on the definition of anaphase. We acknowledge that the term is ill-defined here. Further, it suggest a mitotic morphology analogous to the one observed in “classical” models (prophase, metaphase, anaphase,…), which is not fully appropriate. Consequently, we decided to adapt the suggested terminology in Fig. 1 (and also new Fig. 2) and in the text (line 160).

      Based on the evidence in this study, it cannot be stated unequivocally that the centrosome is entirely extranuclear, at least not as it is implied in Figure 3C. In Supplementary Figure 4, the microtubules appear to be extruding from a circular structure that may either be intranuclear or span the nuclear envelope. In Supplementary Figure 6, the structure pointed to as the centrosome appears to be embedded within the nuclear membrane with a top structure on the cytosolic side of the nuclear envelope. Thus, the best support for an extranuclear centrosome comes from the CLEM images. Still, it is noteworthy that the double membrane of the nuclear envelope is not visible on this slice in the region where the centrin fluorescence is found. Considering some of the fluorescence pixels for centrin are outside the parasite plasma membrane, and some of the Hoechst pixels are outside the nuclear envelope, this data does not show unequivocally that centrosomes are entirely extranuclear. However, this argument would be strengthened if the authors performed a proteinase K protection assay (or something similar) to determine if Centrin1 and Centrin3 are exposed to the cytosol. However, in the absence of that or further evidence, the authors should dampen their claims about the centrosome being exclusively extranuclear, as represented in the schematic in figure 3C.

      We thank the reviewer for this comment, which highlights an issue in our communication of our working model of the centriolar plaque. At no point we intended to claim that the centrosome is exclusively extranuclear. Rather, centrins, which are currently the only reliable marker proteins, localize to a subcompartment of the extranuclear region of the centriolar plaque. Additionally, the centrosome clearly contains an intranuclear region. The composition of this intranuclear compartment is elusive, except that it harbors microtubule nucleation sites. Indeed, our model in Fig. 3C (now Fig. 4C) is misleading and not well annotated. The newly added NHS-Ester staining fortifies this claim (Fig. 3F-H. Consequently, we corrected our working model by adding an explicit figure labelling (now Fig. 4C).

      We apologize for the misleading labelling in Fig. S6 (now Fig. S7). The green arrow was intended to point out the electron dense region associated with the nuclear membrane, which has been seen in previous studies, and was not intended to represent the entire extended centriolar plaque. If anything, this smaller region might provide the link between the intra and extranuclear compartments that the reviewer also identified in Suppl. Fig. 4 (now Fig. 2D). We modified the annotation of the Fig. S7 and Fig. 4A-B accordingly, labelling it the “electron dense region”. More importantly, we hope that our newly added data using NHS-Ester staining of protein dense regions (Fig. 3F-H) highlights the spread of the centrosome across the nucleo-/cytoplasmic boundary more clearly.

      Considering whether centrin is actually extranuclear, we feel that the data shown in Fig. 2A (now 3A) is convincing. We have, however, added two panels of the relevant regions showing centrin localization respective to the nuclear pore and adjusted the contrast as we acknowledge the limited “visibility” within the unadjusted panels. The fact, that the centrin signal slightly overlaps with the nuclear envelope in CLEM images can be explained by the relatively poor resolution of the widefield microscope we had to use to image the sections. From the other super-resolution images in the manuscript, we know that the perimeter of the better resolved centrin signal is significantly smaller. Otherwise one had to assume from the CLEM data that centrin is also in the cytosol of the red blood cell and that DNA is localized outside the nucleus. On a similar note the fluorescence image is, contrary to the tomography image, a single slice since the thickness of the sample section (about 200nm) is significantly below the z-resolution (about 500nm) of a fluorescence microscope.

      Throughout the study, the level of biological replication is unclear. The authors rigorously include all the data points for each of their graphs and the total number of images/videos quantified. And what needs to be added, in either the figure legends or a methods section, is the number of biological replicates for each of these measures came from.

      We have added the number of replicas in the figure legends.

      **Minor comments:**

      STED is present as an acronym in the abstract and should be spelled out in full and clarified that it is a super-resolution microscopy technique.

      We opted to remove STED from the abstract (leaving it at super-resolution, which includes expansion microscopy) to avoid disrupting the “flow” of the abstract and now spell out the acronym at the first mention in the introduction (line 127).

      The second paragraph of the Results section states that ring and early trophozoite stage parasites do not express tubulin or centrin. Still, only an early trophozoite is shown in Supplementary Figure 2. Therefore, the authors should either include a similar image of a ring-stage parasite or remove ring-stage parasites from that statement.

      We have removed the ring stages from the statement.

      The second paragraph of the Results section contains the sentence, "At which point tubulin is reorganized into the bipolar microtubule array, which then forms the mitotic spindle cannot be resolved here." The authors are implying that the point at which tubulin is reorganized into the microtubule array, which goes on to form the mitotic spindle, cannot be resolved here. This is not particularly clear, though, and this sentence could be reworded for clarity.

      We reformulated the sentence to clarify the point we failed to make with the previous wording (line 188).

      The second paragraph of the Results section contains some statements about the results without referencing the figures that these statements come from. The authors should clarify this to make clear which figures each statement refers to.

      We added more references to the appropriate figure throughout the paragraph (lines 188, 219, 223).

      In the third paragraph of the introduction section, the authors write, " Centriolar plaques seem partially embedded in the nuclear membrane, but their positioning relative to the nuclear pore-like "fenestra" remains unclear." Unfortunately, the lack of reference did not allow me to understand if the authors state literature or comment on past published results.

      We added the reference which was incorrectly positioned before the sentence instead of at the end (line 82).

      the authors could add some references:

      • Second section of the introduction: " the 8-28 nuclei are packaged into individual daughter cells, called merozoites ( Rudlaff et al. 2019 PMID: 31097714)

      • Third section of the introduction: " The centrosome of P.falciparum is called centriolar plaque" ( Arnot et al. 2011, Sinden 1991a); " the nuclear pore-like "fenestra" remains unclear (Wall et al. 2018; Zeeshan et al. 2020).

      • Fourth section of the introduction: " tubulin antibody staining are extensive structures measuring around 2-4um ( Ref?)

      • When the authors introduce subpellicular microtubules of segmented schizonts, a reference to a study that shows these structures should be included.

      • A previous study that shows the distinct structure of microtubule minus ends should be cited when this structure is described.

      • Third section of the results, the authors should cite Bertiaux et al. 2021 with the Gambarotto et al. 2019 paper regarding U-ExM.

      We apologize for missing some important references or putting them in the wrong position. We now added all the references or cite them again at the appropriate locations throughout the text.

      Figure 1E shows hemispindle and mitotic spindle lengths of U-ExM expanded parasites, but the position within the figure and figure legend implies that these lengths were determined unexpanded parasites. Therefore, it should be stated in the figure legend that these measurements come from U-ExM expanded parasites. Moreover, I encourage the authors to include U-ExM images in the main figures. The images are beautiful, represent a significant technical achievement, and directly relate to Figure 1E. To the best of my knowledge, this is only the second study to perform expansion microscopy on Plasmodium and the first to use PFA-fixed parasites and a nuclear stain. It would be valuable for the Plasmodium and ExM communities to see this technical advancement represented in the main text.

      We thank the reviewer for the appreciation of our ExM data and added it to Fig. 2B before the quantification of the microtubule length and number and added the information to the legend.

      In the second paragraph of the Results section, the authors write, " but clearly display the microtubule cytoskeleton associated with the inner membrane complex." It would bring clarity to define in few words what the IMC is.

      We included a short definition of the IMC (line 223).

      The methods section details that the length of microtubules was determined by dividing the observed values by an expansion factor of 4.5. If the authors recorded the expansion factors of their gels, this data should be included, and how it was recorded should be stated in the methods. If not, the authors should include the rationale of using an expansion factor of 4.5 as this is slightly different from the previously published expansion factor of P. falciparum of 4.3.

      We recorded the expansion factor by measuring the gel size pre and post expansion with a ruler and found a factor of 4.5 on average. We added this information in the methods (line 688).

      There are several parasite lines used in this study, and some figures are not clear what parasite line was used. Could the authors please include the parasite lines in the figure legends of Figure 1 D-F, Figure 3, Supplementary Figures 1-2, and Supplementary Figures 4-7?

      We added the parasite line information in the legends as requested.

      Nuclear pore complexes, of which Nup313 is a component, can have cytoplasmic, integral, and nuclear-facing components. If it has been shown previously that PfNup313 is the homolog of Nup214 in vertebrates present on the cytosolic side of NPC, this should be stated. If not, then it should be clarified that it is unknown whether Nup313 faces the cytoplasm, nucleus, or is embedded in the NE, as this has implications for the colocalization of Nup313 and Centrin.

      Nuclear pore proteins are very poorly conserved in P. falciparum and Nup313 has only been recently identified as such (Kehrer et al. 2018) mainly by the presence of FG-repeats (as for all the other newly defined proteins). The only related ortholog that can be found through BLAST search against humans, yeasts, and Arabidopsis is Nup100 from S. cerevisiae. ScNup100 is a central pore localizing protein but the sequence similarity to Nup313 is low. We are not aware of any findings showing relatedness to vertebrate Nup214, while sequence analysis rather indicates the absence of orthology. To clearly demonstrate the individual positioning of the few known Nups within the parasite´s nuclear pore complex would require a dedicated long-term project. However, due to the presence of FG-repeats one can assume that it is part of the central FG-Nups layer rather than of the intranuclear basket or the cytoplasmic filaments (line 255). Therefore it would localize more closely to the nuclear envelope than the latter. Either way, a clear gap between centrin and Nup313 signal can be identified and colocalization has not been observed. These data indicate that the exact position of Nup313 on the cytoplasmic, integral or nuclear-facing site is not decisive for the conclusions made in this study and our observations preclude scenarios where centrin is not extranuclear.

      It seems from the image in Figure 2C that DRAQ5 and Hoechst have at least visually indistinguishable localizations. Have the authors taken any STED deconvolved images of nuclei stained with both Hoechst and DRAQ5? Considering the striking increase in detail of the Hoechst signal in STED deconvolved images, it may be informative both to this study and to people who work on chromatin organization what the chromatin staining looks like in the absence of bias towards chromatin state.

      It would, indeed, be interesting to analyse chromatin organization by those means, but DRAQ5 is not a STED compatible dye, highly prone to bleaching, and therefore not suitable for such analysis. Being an infrared dye DRAQ5 is compared to the UV excited Hoechst also yielding a reduced spatial resolution, which is limited by the emitted wave length.

      For the tomography and TEM images, the centrosome is indicated with an arrow, but it isn't entirely clear what that arrow is pointing to for some images. It would be clearer if the centrosome were outlined in green, like the NE, rather than just an arrow. This is particularly important for Supplementary Figure 4, where to my eye, it appears that the microtubules inside the chromatin-free region are coming directly out of a circular structure, which could be interpreted as the centriolar plaque.

      The reviewer is right to point out the use of arrows for centrosome annotation. It was intended for orientation of readers to indicate the “likely position of the centriolar plaque” since a clear boundary around the centrosome can´t be defined. It would have been more precise to indicate that the arrow is pointing at the electron dense region associated with the nuclear membrane, which is of course only one of the sub-regions of the centrosome. This is particularly important since we want to emphasize the extended dimensions of the centrosome. Consequently, we modified the annotation to “electron dense region” in all concerned figures and corresponding legends.

      The ordering of Figure 2A-C seems to imply that the DNA-free region was measured in the STED deconvolved images, but the methods imply that it was in the confocal images. The authors should clarify this in the figure legend or by rearranging B and C's order.

      Hoechst signal was indeed acquired and measured in confocal mode and to avoid confusion we have changed the order of the figures (now Fig. 3B-C) as suggested.

      The authors should provide some more detail on how the DNA-free zone was measured. For example, was it measured on single slices or maximum intensity projections? Was it measured from the middle, far, or near side of the centrin focus? Etc.

      The measurement was carried out in the slice where the DNA-free zone was in focus. Depth was measured from below the centrin signal until the “bottom” of the DNA-free zone. We hoped that the little schematic above the figure would clarify this question, but acknowledge the need to more clearly explain the measurement method, which we now do in the corresponding figure legend (Fig. 3C).

      The methods state that the mCherry signal in figure 2C was detected using a mCherry nanobody. This should be clarified in the figure legends as it currently seems as if we see endogenous mCherry fluorescence.

      The visible signal is certainly a combination of the mCherry plus the “boosting” effect from the Atto594-coupled nanobody that we added. Clearly, this should be mentioned in the figure legend, which we now do.

      The data in Supplementary Figure 4 seems vital to the interpretation of the study. Therefore, for clarity, I encourage the authors to include Supplementary Figure 4 in Figure 2.

      We share the reviewers view on these data and moved them to the main figures (now Fig. 3D).

      In the last sentence of the discussion, it is unclear what the authors mean by how the nuclear compartment "splits," could they please clarify?

      We were referring to the event of centrosome duplication, which has to occur during nuclear division. In a structure without centrioles or a spindle pole body structure forming a half bridge we therefore need a new model to explain how the two poles of the spindle are formed. Potential modes are splitting or de novo assembly. This aspect, as also pointed out by other reviewer, warrants a bit more explanation, which can now be found in the discussion (line 468).

      If the pArl-PfCentrin3-GFP plasmid or pDC2-cam-coCas9-U6.2-hDHFR have been published previously, the respective studies should be cited. If not, the study where the vector backbones were first established should be cited.

      We have now cited the original studies publishing the vector backbones for the first time in the methods (lines 490, 501).

      From the current text, it is not clear that the Nup313 tagged parasites also had a GlmS ribozyme. It is shown in Supplementary Figure 3, but the authors should clarify either in the text of the results, or figure legends, that this parasite line was Nup313_3xHA_GlmS

      The Nup313-tagged line indeed has a glms ribozyme after the HA-tag, which we now mention in the figure legends.

      In the plasmid constructs section of the methods, the authors list several primers by number but not by sequence. Instead, the authors should include the sequence and orientation of each of the primers mentioned in a table as supplementary data.

      This is a good suggestion. We have generated a table at the end of the supplementary data file and on this occasion we also added tables of all the antibodies and dyes used in this study.

      The authors should cite the study where the TgCentrin1 antibody was generated and provide the Rat anti-HA 3F10 antibody catalog number, as catalog numbers are provided for other commercial primary antibodies.

      We now provide the missing catalog numbers in the supplemental data table.

      There is an issue with the formatting of the journal-title in the Kukulski et al. reference.

      Thank you for noticing this error, which we now corrected.

      Reviewer #3 (Significance (Required)):

      The genome of P. falciparum is fully sequenced; however, over 50% of encoded proteins are of unknown function, with many of these proteins unique to Plasmodium parasites. By identifying and characterizing essential biological processes, especially those divergent from human host cell processes, we will formulate ways to interfere with them by developing novel antimalarial drugs. The process of Plasmodium cell division differs from the classical cell cycle of its human host. In the study led by Caroline Simon, authors successfully utilized recent developments of super-resolution microscopies on expanded parasites to identify novel features of cell division machinery of the malaria blood-stage parasite.

      Simon et al.'s work highlight the growing interest in the diversity of cell division mode of Apicomplexan parasites, which will likely contribute to a deeper understanding of the origin and functional role of the centrosome in eukaryotic life. In 2020, the Open Biology journal published a unique article collection named Focus on Centrosome Biology showcasing research that advanced our knowledge on centrosome function, evolution and abnormalities. In addition, the reported findings will interest research groups studying cell cycle regulation and evolution beyond the field of parasitology.

      Our lab studies the peculiar cell cycle of Plasmodium falciparum to gain a functional understanding of mechanistic principles of nuclear envelope assembly and integrity during the cell division of the human malaria parasite.

      **Referee Cross-commenting**

      It is a wonderful study, and once all reviewer's comments are addressed, the manuscript should be in excellent shape for publication.

  7. Oct 2016