“Then I’ll do it. Because I don’t care about me.”
This line reveals the girl’s emotional surrender. She’s willing to undergo the abortion not out of personal choice but to please the man. Hemingway uses this brief, restrained dialogue to show her emotional pain in their relationship. He’s detached, while she’s sacrificing herself for his comfort.
But if I do it, then it will be nice again if I say things are like white elephants, and you’ll like it?”
The “white elephants” symbolize something unwanted or burdensome, which, in this case, is the pregnancy. The man tries to make light of it, but the girl’s repetition of the phrase shows her deeper emotional conflict and the couple’s inability to communicate honestly.
“Doesn’t it mean anything to you? We could get along.”
Jig’s plea reveals her emotional vulnerability. She’s seeking reassurance and love rather than logic. The phrase “we could get along” shows she associates keeping the baby with saving their relationship. It's a contrast to the man's practical reasoning.
“I know. Could we have another beer?”
The request to drink again is definitely an attempt to avoid the emotional tension. Alcohol becomes a symbol of distraction and denial, emphasizing the couple’s inability to communicate meaningfully about their situation.
The not-for-profit organization Project Implicit (https://www.projectimplicit.net/) has been researching subconscious biases for years and has developed several, free online tests. (https://implicit.harvard.edu/implicit/takeatest.html) The tests can help you understand your proclivities and subconscious biases. Knowing your biases may help you begin to overcome them.
IAT's have been under scrutiny for some time.They are commonly skewed towards perspectives gained from specific demographics and can be manipulated quite easily to reflect personal pejoratives that align with an agency's codes of ethics. this suggestion should be given with caveats.
“We think there’s no normal way to act on a 911 call,” said the lead investigator, Jessica Salerno, a social psychologist at ASU. Given the gamut of human emotion, she explained, anyone claiming to know the right and wrong way to speak during an emergency has seen too much television.
It's nuts that this has to be said.
an instance of how,at particular moments, our socially produced worlds sometimes becomenaturalized into “new” forms of caring
I understand that Reddy is very cautious about making the parallel connection between the heteronormative consanguineal relationship and the mother-daughter ties in the hijra community. This sentence implies a temporal order, that the biological form precedes the other (maybe I am wrong). Nevertheless, the appearance of "newness" reflects the social construction as the basis of our kinship.
Mothers often appeared to have greater affection for daughters thanfor their celas, even though there was no denying the greater significanceand legitimacy of the guru-cela bond over the ma-beti one
Just a random pondering: how would the celas and daughters of one hijra interact with each other? And does this scale of affection also engender another form of hierarchy and evaluation?
When I asked Rajeshwari why they adopted daughters, she told me itwas to extend their kin relations, their sambandam. Daughters would morethan likely be celas of other hijras with whom they could then form analliance, she explained. Such relationships also serve publicly to strengthenties between hijras, through a symbolic ritual enactment. By developingthese bonds, each hijra is able to establish relationships with other hijras,thereby not only widening the kinship network but also cementing ties,as in Pierre Bourdieu’s (1977) notion of “practical kinship.” For instance,among kandra hijras, dudh behans would “exchange” celas, making thesecelas their respective dudh betis
It is interesting to see that though the mother-daughter relationship is founded upon a mutual affection, it still entails a power relation within the larger hijra community as a means of negotiation and alliances. The term "extend" implies the horizontal orientation of the mother-daughter relationship, which supplements the vertical hierarchy of the guru-cela relationship. Also, they can be interchangeable, as the interlocutors showed that the guru would exchange celas. I dont know whether this alliance also creates a friction between the hijras? For instance, if two gurus exchanged their celas as the other's daughter, will one step out to protect her daughter while she was facing mistreatment by the other guru? And what will happen if the cela decides to switch to another guru, will this mother-daughter tie not be obstructed? Overall, this passage clearly demonstrates that the this horizontal mother-daughter love is not the exception of the hijra kinship, but a constituent of the holistic part of what animates it, opening up venues for ambiguity (Reddy will talk about it later!).
he then pours somemilk, using a cup held over her breast, into the mouths of the prospectivebetis, thereby sealing this relationship with “her” milk. To further seal thebond thus forged, each of the prospective dudh behans pricks her fingerand lets a few drops of blood flow into the cup of milk, which is then sharedby all of them, mother and sisters
The emphasis on milk, a substance, is interesting. This ritual contrasts with the guru-cela one, in which the centre is the monetary "offering" and kissing the feet of the guru and nayak. In this ritual, the transmittable liquid—blood and milk—fuses with one another, sealing the bond in a nursing gesture. It is the mother who enacts the act of care to the daughters. These two rituals sort of indicate an opposite relationship dynamic and orientations of care.
Though the treatment of autistic children was markedlymore brutal, both programs shared one vision—to make the children “indistin-guishable” from others
It is about upholding a norm. It is less so about protecting children then it is upholding sociocultural values.
Our access to technology gives us advantages in accessing information that many around the world do not have.
This is true because some places around the world have no internet access at all so they don't know about many things that aren't in books.
The idea that status impacts your access to information is nothing new. What is relatively new is that librarians and others are critically talking about it as it relates to higher education.
I agree with this because information truly is a privilege.
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Since we are at the stage of simply proposing a Revision Plan to an affiliate journal, there is not a revised version of the manuscript yet. But we honestly thank the three reviewers for their important input, which we are taken into consideration very seriously.
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Major Comments:
It is interesting case study but the main problem with the study is the use of an unsuitable tardigrade model species. It was shown in the past that Hypsibius exemplaris is not a good model species to test tardigrade survival under extreme stress. Of course, results of Hypsibius exemplaris can be published but from the entire manuscript all general comments that tardigrades react in this or in different way need to be removed. This is characteristic only to Hypsibius exemplaris species which is a poor model for studies focused on environmental stressTo present general conclusions use few different tardigrade species or at least a correct tardigrade species with confirmed high resilience for different kind of stress like Milnesium, Ramazzottius, Paramacrobiotus or similar must be tested. Based on present study I can only propose to publish this manuscript as a case study for one poorly stress resistant eutardigrade species, without any general conclusions about other tardigrades. See: Poprawa, I., Bartylak, T., Kulpla, A., Erdmann, W., Roszkowska, M., Chajec, Ł., Kaczmarek, Ł., Karachitos, A. & Kmita, H. (2022) Verification of Hypsibius exemplaris Gąsiorek et al., 2018 (Eutardigrada; Hypsibiidae) application in anhydrobiosis research. PLoS ONE 17(3): e0261485.
Minor comments:
Studies described in the manuscript are very interesting for many potential readers, however manuscript need to be modified as case study for one tardigrades species without generalization of the results for all tardigrades. It is very important to not suggest that all tardigrades react in the same way especially that species used is not a good candidate for this type of studies (see my major comments).
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Summary:
This manuscript studies the effects of genotoxic stress using zeocin, a bleomycin-family drug, in the tardigrade species H. exemplaris. In a first experimental set, the authors evaluate the survival of the organisms as well as the levels of DNA damage.
A RT-qPCR analysis of a set of DNA repair genes identified in a previous study by another group (Clark-Hachtel, Courtney M. et al.; Curr Biol, Vol. 34, Issue 9, 1819-1830.e6) and a comet assay reveal the damage observed during treatment.
Experiments on fasting animals show variations in animal size that overlap with those seen in groups of animals treated with the genotoxic drug. Physiological variations are also observed, such as lipid loss and cuticle alteration.
In a subsequent experimental set, the authors indicate that the genotoxic drug blocks DNA replication and activates DNA repair systems in various tissues, particularly the digestive tissue, which appears to be specifically targeted in terms of its replicative capacity following DNA damage caused by the drug. A sensitivity study of tardigrade embryo development then shows that their proliferative capacity, which is highly dependent on replication, mobilizes different sets of DNA repair genes that may be more closely associated with replication than in adults.
Finally, a comparative study of the development of two organisms (C. elegans and planarian) also shows sensitivity to drugs that disrupt the replication process during development.
The authors conclude from all of this work that the cells of the animals' intestines are the main target of the genotoxic stress induced by the drug. The effects of disruption of the normal replication process in intestinal cells are thought to be the cause of the observed loss of tissue homeostasis (loss of lipids and tissue renewal capacity).
Major comments:
Zeocin is a drug derived from bleomycin but has not yet been extensively studied. Could you give examples of the use/validation of zeocin as a radiomimetic in other biological systems?
Similarities in transcriptional responses between UV and dehydration genotoxic stresses have already been observed (Yoshida et al., 2022; BMC Genomics 23, 405) in a tardigrade species closely related to H. exemplaris (R. varieornatus). However, no correlation in transcriptional responses could be observed after treating H. exemplaris with genotoxic stresses such as desiccation and 500 Gy gamma ray irradiation (Clark-Hachtel, Courtney M. et al.; Curr Biol, Vol 34, Issue 9, 1819 - 1830.e6). These results indicate that, depending on the type of genotoxic stress, transcriptomic responses can appear to be very different and sometimes uncorrelated, particularly in the species H. exemplaris. Bleomycin has been studied in previous reports (refs Yoshida Y, et al. Proc Jpn Acad Ser B Phys Biol Sci. 2024 100(7):414-428; Clark-Hachtel, Courtney M. et al.; Curr Biol, Vol 34, Issue 9, 1819 - 1830.e6; Marwan Anoud et al., 2024, eLife 13:RP92621), which used a transcriptomic study to confirm that it behaves as a radiomimetic for the species H. exemplaris.
On the other hand, since zeocin is a bleomycin-family drug, it is possible that its effects may differ slightly from those of bleomycin, exhibiting specific effects as observed by comparison of chemical radiomimetic and radiation treatments.
A control experiment comparing the effects of bleomycin and zeocin using RNAseq would validate that their use is equivalent.
It would be interesting to block replication in embryos and assess whether the same sets of DNA repair genes are induced when compared with treatment with zeocin only. Additionally, it will be interesting to redo the same DNA replication block experiments with additional treatment to compare the induced sets of DNA reparation genes. This will help to understand the true effect that will be directly imputable to zeocin.
Minor comments:
The data are well presented, and the experiments are well described for general understanding. Previous studies in this field have been well referenced. However, the link between DNA damage caused by the drug and its impact on replication needs to be better explained.
Finally, the use of the drug zeocin should be validated in this system by comparison with bleomycin.
This study evaluates the resistance of a species of tardigrades to genotoxic stress. Several previous studies have conducted this type of experiment using the same species with consistent results and using the same type of genotoxic chemical drug : bleomycin. In this study, a new genotoxic drug is evaluated for its effects on DNA damage as well as on the survival of organisms and their embryonic development. Definitive validation experiments of this new genotoxic chemical tool are necessary to determine its similarities with drugs already known for their effects in the literature.
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This manuscript concerns tardigrade sensitivity to genotoxic stress. Using the radiomimetic drug Zeocin to induce DNA breaks, authors show that continuous exposure progressively kills tardigrades, accompanied by striking body shrinkage and lipid depletion. Authors show that germ cells and embryos, with their high proliferation rates, show heightened sensitivity. To resume, their findings pinpoint DNA replication as an Achilles' heel of organismal survival under genotoxic stress.
Major comments:
The claims and conclusions in this article are not sufficiently supported by the data. They require additional experiments or analyses.
The fundamental problem with this paper is the use of a single molecule, Zeocin, as a radiomimetic. It is absolutely essential to compare the results obtained with radiation. In the bibliography, researchers compare a drug with radiation. Bob Goldstein, for example, in his 2024 Current Biology paper uses radiation and bleomycin. The same is true for Concordet in his 2024 elife paper. Zeocin has been used very little on tardigrades. It cannot be used alone to draw conclusions from this study.
Additionally, at the beginning of the paper, the authors tested different concentrations of Zeocin. They showed results at two concentrations : 100ug/ml and 1mg/ml. In the remainder of the paper, only the latter concentration is used. This is not sufficient. The analyses should have been conducted in parallel on several concentrations in order to compare and analyze a potential dose-dependent effect.
Finally, the authors focused on two types of cells that have the particularity of replicating themselves: gut cells and storage cells. It would have been necessary to work on other cell types to compare the results.
The realization of these additional experiences are completely realistic.
The data and methods are presented in a reproducible manner. But experiments sometimes lack independent replicates and need to be reproduced.
The legend to Figure 1, for example, indicates that the experiment was conducted with 3 to 7 biological replicates and 60 to 120 animals. These are still very different numbers. And this can lead to significant bias.
For the other figures, no biological replicates were indicated and the numbers « n » are sometimes very different, as in Figure 4 with n=107 and n=166. A little more homogenization allows for better robustness of the results. And biological replicates are essential.
Sometimes there are some unclear elements in the figures. In Figure 3, if I understand correctly, A and B show the gut cells (adult) and C and D the storage cells (juvenile). The size difference is not very clear in this image. How old is the juvenile compared to this adult?
This study, if confirmed by additional experiments that are absolutely essential to validate these conclusions, will be interesting for the community of researchers working on tardigrades, even if the effects of genotoxic stress on tardigrades are already widely studied.
This study is relatively complete on only one molecule, Zeocin, at a concentration of 1 mg/ml. To be relevant, another genotoxic stress should be included in the study. And the study should also be conducted at the concentration of 100 ug/ml, which did show effects but was abandoned for the rest of the study. Similarly, only storage cells and gut cells were studied given their replication capacity. Other cell types should have been included in the study for comparison.
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We would like to thank all the reviewers for their valuable comments and criticisms. We have thoroughly revised the manuscript and the resource to address all the points raised by the reviewers. Below, we provide a point-by-point response for the sake of clarity.
Reviewer #1
__Evidence, reproducibility and clarity __
Summary: This manuscript, "MAVISp: A Modular Structure-Based Framework for Protein Variant Effects," presents a significant new resource for the scientific community, particularly in the interpretation and characterization of genomic variants. The authors have developed a comprehensive and modular computational framework that integrates various structural and biophysical analyses, alongside existing pathogenicity predictors, to provide crucial mechanistic insights into how variants affect protein structure and function. Importantly, MAVISp is open-source and designed to be extensible, facilitating reuse and adaptation by the broader community.
Major comments: - While the manuscript is formally well-structured (with clear Introduction, Results, Conclusions, and Methods sections), I found it challenging to follow in some parts. In particular, the Introduction is relatively short and lacks a deeper discussion of the state-of-the-art in protein variant effect prediction. Several methods are cited but not sufficiently described, as if prior knowledge were assumed. OPTIONAL: Extend the Introduction to better contextualize existing approaches (e.g., AlphaMissense, EVE, ESM-based predictors) and clarify what MAVISp adds compared to each.
We have expanded the introduction on the state-of-the-art of protein variant effects predictors, explaining how MAVISp departs from them.
- The workflow is summarized in Figure 1(b), which is visually informative. However, the narrative description of the pipeline is somewhat fragmented. It would be helpful to describe in more detail the available modules in MAVISp, and which of them are used in the examples provided. Since different use cases highlight different aspects of the pipeline, it would be useful to emphasize what is done step-by-step in each.
We have added a concise, narrative description of the data flow for MAVISp, as well as improved the description of modules in the main text. We will integrate the results section with a more comprehensive description of the available modules, and then clarify in the case studies which modules were applied to achieve specific results.
OPTIONAL: Consider adding a table or a supplementary figure mapping each use case to the corresponding pipeline steps and modules used.
We have added a supplementary table (Table S2) to guide the reader on the modules and workflows applied for each case study
We also added Table S1 to map the toolkit used by MAVISp to collect the data that are imported and aggregated in the webserver for further guidance.
- The text contains numerous acronyms, some of which are not defined upon first use or are only mentioned in passing. This affects readability. OPTIONAL: Define acronyms upon first appearance, and consider moving less critical technical details (e.g., database names or data formats) to the Methods or Supplementary Information. This would greatly enhance readability.
We revised the usage of acronyms following the reviewer’s directions of defying them at first appearance.
We thank the reviewer for noticing and praising the availability of the tools of MAVISp. Our MAVISp framework utilizes methods and scores that incorporate machine learning features (such as EVE or RaSP), but does not employ machine learning itself. Specifically, we do not use PyTorch and do not utilize features in a machine learning sense. We do extract some information from the AlphaFold2 models that we use (such as the pLDDT score and their secondary structure content, as calculated by DSSP), and those are available in the MAVISp aggregated csv files for each protein entry and detailed in the Documentation section of the MAVISp website.
We have removed this section and included a mention in the conclusions as part of the future directions.
Minor comments: - Most relevant recent works are cited, including EVE, ESM-1v, and AlphaFold-based predictors. However, recent methods like AlphaMissense (Cheng et al., 2023) could be discussed more thoroughly in the comparison.
We have revised the introduction to accommodate the proper space for this comparison.
We have revised Figure 2 and presented only one case study to simplify its readability. We have also changed Figure 3, whereas retained the other previous figures since they seemed less problematic.
We have done a proofreading of the entire article, including the points above
Significance
General assessment: the strongest aspects of the study are the modularity, open-source implementation, and the integration of structural information through graph neural networks. MAVISp appears to be one of the few publicly available frameworks that can easily incorporate AlphaFold2-based features in a flexible way, lowering the barrier for developing custom predictors. Its reproducibility and transparency make it a valuable resource. However, while the technical foundation is solid and the effort substantial, the scientific narrative and presentation could be significantly improved. The manuscript is dense and hard to follow in places, with a heavy use of acronyms and insufficient explanation of key design choices. Improving the descriptive clarity, especially in the early sections, would greatly enhance the impact of this work.
Advance
to the best of my knowledge, this is one of the first modular platforms for protein variant effect prediction that integrates structural data from AlphaFold2 with bioinformatic annotations and even clinical data in an extensible fashion. While similar efforts exist (e.g., ESMfold, AlphaMissense), MAVISp distinguishes itself through openness and design for reusability. The novelty is primarily technical and practical rather than conceptual.
Audience
this study will be of strong interest to researchers in computational biology, structural bioinformatics, and genomics, particularly those developing variant effect predictors or analyzing the impact of mutations in clinical or functional genomics contexts. The audience is primarily specialized, but the open-source nature of the tool may diffuse its use among more applied or translational users, including those working in precision medicine or protein engineering.
Reviewer expertise: my expertise is in computational structural biology, molecular modeling, and (rather weak) machine learning applications in bioinformatics. I am familiar with graph-based representations of proteins, AlphaFold2, and variant effects based on Molecular Dynamics simulations. I do not have any direct expertise in clinical variant annotation pipelines.
Reviewer #2
__Evidence, reproducibility and clarity __
Summary: The authors present a pipeline and platform, MAVISp, for aggregating, displaying and analysis of variant effects with a focus on reclassification of variants of uncertain clinical significance and uncovering the molecular mechanisms underlying the mutations.
Major comments: - On testing the platform, I was unable to look-up a specific variant in ADCK1 (rs200211943, R115Q). I found that despite stating that the mapped refseq ID was NP_001136017 in the HGVSp column, it was actually mapped to the canonical UniProt sequence (Q86TW2-1). NP_001136017 actually maps to Q86TW2-3, which is missing residues 74-148 compared to the -1 isoform. The Uniprot canonical sequence has no exact RefSeq mapping, so the HGVSp column is incorrect in this instance. This mapping issue may also affect other proteins and result in incorrect HGVSp identifiers for variants.
We would like to thank the reviewer for pointing out these inconsistencies. We have revised all the entries and corrected them. If needed, the history of the cases that have been corrected can be found in the closed issues of the GitHub repository that we use for communication between biocurators and data managers (https://github.com/ELELAB/mavisp_data_collection). We have also revised the protocol we follow in this regard and the MAVISp toolkit to include better support for isoform matching in our pipelines for future entries, as well as for the revision/monitoring of existing ones, as detailed in the Method Section. In particular, we introduced a tool, uniprot2refseq, which aids the biocurator in identifying the correct match in terms of sequence length and sequence identity between RefSeq and UniProt. More details are included in the Method Section of the paper. The two relevant scripts for this step are available at: https://github.com/ELELAB/mavisp_accessory_tools/
- The paper lacks a section on how to properly interpret the results of the MAVISp platform (the case-studies are helpful, but don't lay down any global rules for interpreting the results). For example: How should a variant with conflicts between the variant impact predictors be interpreted? Are specific indicators considered more 'reliable' than others?
We have added a section in Results to clarify how to interpret results from MAVISp in the most common use cases.
We thank the reviewer for spotting this inconsistency. This part in the main text was left over from a previous and preliminary version of the pre-print, we have revised the main text. Supplementary Text S4 includes the correct reference for the value in light of the benchmarking therewithin.
We have changed the structure of the webserver in such a way that now the whole website opens as its own separate window, instead of being confined within the size permitted by the website at DTU. This solves the fixed window size issue. Hopefully, this will improve the user experience.
We have refactored the web app by adding filtering functionality, both for the main protein table (that can now be filtered by UniProt AC, gene name or RefSeq ID) and the mutations table. Doing this required a general overhaul of the table infrastructure (we changed the underlying engine that renders the tables).
The table overhauls fixed both of these issues
We clarified the meaning of the reference column in the Documentation on the MAVISp website, as we realized it had confused the reviewer. The reference column is meant to cite the papers where the computationally-generated MAVISp data are used, not external sources. Since we also have the experimental data module in the most recent release, we have also refactored the MAVISp website by adding a “Datasets and metadata” page, which details metadata for key modules. These include references to data from external sources that we include in MAVISp on a case-by-case basis (for example the results of a MAVE experiment). Additionally, we have verified that the papers using MAVISp data are updated in https://elelab.gitbook.io/mavisp/overview/publications-that-used-mavisp-data and in the csv file of the interested proteins.
Here below the current references that have been included in terms of publications using MAVISp data:
SMPD1
ASM variants in the spotlight: A structure-based atlas for unraveling pathogenic mechanisms in lysosomal acid sphingomyelinase
Biochim Biophys Acta Mol Basis Dis
38782304
https://doi.org/10.1016/j.bbadis.2024.167260
TRAP1
Point mutations of the mitochondrial chaperone TRAP1 affect its functions and pro-neoplastic activity
Cell Death & Disease
40074754
https://doi.org/10.1038/s41419-025-07467-6
BRCA2
Saturation genome editing-based clinical classification of BRCA2 variants
Nature
39779848
0.1038/s41586-024-08349-1
TP53, GRIN2A, CBFB, CALR, EGFR
TRAP1 S-nitrosylation as a model of population-shift mechanism to study the effects of nitric oxide on redox-sensitive oncoproteins
Cell Death & Disease
37085483
10.1038/s41419-023-05780-6
KIF5A, CFAP410, PILRA, CYP2R1
Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci
Computational and Structural Biotechnology Journal
38022694
https://doi.org/10.1016/j.csbj.2023.10.031
KRAS
Combining evolution and protein language models for an interpretable cancer driver mutation prediction with D2Deep
Brief Bioinform
39708841
https://doi.org/10.1093/bib/bbae664
OPTN
Decoding phospho-regulation and flanking regions in autophagy-associated short linear motifs
Communications Biology
40835742
10.1038/s42003-025-08399-9
DLG4,GRB2,SMPD1
Deciphering long-range effects of mutations: an integrated approach using elastic network models and protein structure networks
JMB
40738203
doi: 10.1016/j.jmb.2025.169359
Entering multiple mutants in the "mutations to be displayed" window is time-consuming for more than a handful of mutants. Suggestion: Add a box where multiple mutants can be pasted in at once from an external document.
During the table overhaul, we have revised the user interface to add a text box that allows free copy-pasting of mutation lists. While we understand having a single input box would have been ideal, the former selection interface (which is also still available) doesn’t allow copy-paste. This is a known limitation in Streamlit.
Minor comments
We have done proofreading on the final version of the manuscript
Yes, we are aware of this. It is far from trivial to properly import the datasets from multiplex assays. They often need to be treated on a case-by-case basis. We are in the process of carefully compiling locally all the MAVE data before releasing it within the public version of the database, so this is why they are missing. We are giving priorities to the ones that can be correlated with our predictions on changes in structural stability and then we will also cover the rest of the datasets handling them in batches. Having said this, we have checked the dataset for BRCA1, HRAS, and PPARG. We have imported the ones for PPARG and BRCA1 from ProtGym, referring to the studies published in 10.1038/ng.3700 and 10.1038/s41586-018-0461-z, respectively. Whereas for HRAS, checking in details both the available data and literature, while we did identify a suitable dataset (10.7554/eLife.27810), we struggled to understand what a sensible cut-off for discriminating between pathogenic and non-pathogenic variants would be, and so ended up not including it in the MAVISp dataset for now. We will contact the authors to clarify which thresholds to apply before importing the data.
In the KRAS case study presented in MAVISP, we utilized the protein abundance dataset reported in (http://dx.doi.org/10.1038/s41586-023-06954-0) and made available in the ProteinGym repository (specifically referenced at https://github.com/OATML-Markslab/ProteinGym/blob/main/reference_files/DMS_substitutions.csv#L153). We adopted the precalculated thresholds as provided by the ProteinGym authors. In this regard, we are not really sure the reviewer is referring to this dataset or another one on KRAS.
We improved the description of our classification strategies for both modules in the Documentation page of our website. Also, we explained more clearly the possible sources of ‘uncertain’ annotations for the two modules in both the web app (Documentation page) and main text. Briefly, in the STABILITY module, we consider FoldX and either Rosetta or RaSP to achieve a final classification. We first classify one and the other independently, according to the following strategy:
If DDG ≥ 3, the mutation is Destabilizing If DDG ≤ −3, the mutation is Stabilizing If −2 We then compare the classifications obtained by the two methods: if they agree, then that is the final classification, if they disagree, then the final classification is Uncertain. The thresholds were selected based on a previous study, in which variants with changes in stability below 3 kcal/mol were not featuring a markedly different abundance at cellular level [10.1371/journal.pgen.1006739, 10.7554/eLife.49138]
Regarding the LOCAL_INTERACTION module, it works similarly as for the Stability module, in that Rosetta and FoldX are considered independently, and an implicit classification is performed for each, according to the rules (values in kcal/mol)
If DDG > 1, the mutation is Destabilizing. If DDG Each mutation is therefore classified for both methods. If the methods agree (i.e., if they classify the mutation in the same way), their consensus is the final classification for the mutation; if they do not agree, the final classification will be Uncertain.
If a mutation does not have an associated free energy value, the relative solvent accessible area is used to classify it: if SAS > 20%, the mutation is classified as Uncertain, otherwise it is not classified.
Thresholds here were selected according to best practices followed by the tool authors and more in general in the literature, as the reviewer also noticed.
The last of these points is not an application of MAVISp, but rather a way in which external data can help validate MAVISp results. Furthermore, none of the examples given demonstrate an application in benchmarking (what is being benchmarked?).
We have revised the statements to avoid this confusion in the reader.
We have removed this section and included a mention in the conclusions as part of the future directions.
The reviewer’s interpretation on the second legend is correct - it does refer to the ClinVar classification. Nonetheless, we understand the positioning of the legend makes understanding what the legend refers to not obvious. We also revised the captions of the figures in the main text. On the web app, we have changed the location of the figure legend for the ClinVar effect category and added a label to make it clear what the classification refers to.
We have corrected this in the text and the statements related to it.
Significance
Platforms that aggregate predictors of variant effect are not a new concept, for example dbNSFP is a database of SNV predictions from variant effect predictors and conservation predictors over the whole human proteome. Predictors such as CADD and PolyPhen-2 will often provide a summary of other predictions (their features) when using their platforms. MAVISp's unique angle on the problem is in the inclusion of diverse predictors from each of its different moules, giving a much wider perspective on variants and potentially allowing the user to identify the mechanistic cause of pathogenicity. The visualisation aspect of the web app is also a useful addition, although the user interface is somewhat awkward. Potentially the most valuable aspect of this study is the associated gitbook resource containing reports from biocurators for proteins that link relevant literature and analyse ClinVar variants. Unfortunately, these are only currently available for a small minority of the total proteins in the database with such reports. For improvement, I think that the paper should focus more on the precise utility of the web app / gitbook reports and how to interpret the results rather than going into detail about the underlying pipeline.
We appreciate the interest in the gitbook resource that we also see as very valuable and one of the strengths of our work. We have now implemented a new strategy based on a Python script introduced in the mavisp toolkit to generate a template Markdown file of the report that can be further customized and imported into GitBook directly (https://github.com/ELELAB/mavisp_accessory_tools/). This should allow us to streamline the production of more reports. We are currently assigning proteins in batches for reporting to biocurator through the mavisp_data_collection GitHub to expand their coverage. Also, we revised the text and added a section on the interpretation of results from MAVISp. with a focus on the utility of the web-app and reports.
In terms of audience, the fast look-up and visualisation aspects of the web-platform are likely to be of interest to clinicians in the interpretation of variants of unknown clinical significance. The ability to download the fully processed dataset on a per-protein database would be of more interest to researchers focusing on specific proteins or those taking a broader view over multiple proteins (although a facility to download the whole database would be more useful for this final group).
While our website only displays the dataset per protein, the whole dataset, including all the MAVISp entries, is available at our OSF repository (https://osf.io/ufpzm/), which is cited in the paper and linked on the MAVISp website. We have further modified the MAVISp database to add a link to the repository in the modes page, so that it is more visible.
My expertise. - I am a protein bioinformatician with a background in variant effect prediction and large-scale data analysis.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
Evidence, reproducibility and clarity:
Summary:
The authors present MAVISp, a tool for viewing protein variants heavily based on protein structure information. The authors have done a very impressive amount of curation on various protein targets, and should be commended for their efforts. The tool includes a diverse array of experimental, clinical, and computational data sources that provides value to potential users interested in a given target.
Major comments:
Unfortunately I was not able to get the website to work correctly. When selecting a protein target in simple mode, I was greeted with a completely blank page in the app window. In ensemble mode, there was no transition away from the list of targets at all. I'm using Firefox 140.0.2 (64-bit) on Ubuntu 22.04. I would like to explore the data myself and provide feedback on the user experience and utility.
We have tried reproducing the issue mentioned by the reviewer, using the exact same Ubuntu and Firefox versions, but unfortunately failed to produce it. The website worked fine for us under such an environment. The issue experienced by the reviewer may have been due to either a temporary issue with the web server or a problem with the specific browser environment they were working in, which we are unable to reproduce. It would be useful to know the date that this happened to verify if it was a downtime on the DTU IT services side that made the webserver inaccessible.
I have some serious concerns about the sustainability of the project and think that additional clarifications in the text could help. Currently is there a way to easily update a dataset to add, remove, or update a component (for example, if a new predictor is published, an error is found in a predictor dataset, or a predictor is updated)? If it requires a new round of manual curation for each protein to do this, I am worried that this will not scale and will leave the project with many out of date entries. The diversity of software tools (e.g., three different pipeline frameworks) also seems quite challenging to maintain.
We appreciate the reviewer’s concerns about long-term sustainability. It is a fair point that we consider within our steering group, who oversee and plans the activities and meet monthly. Adding entries to MAVISp is moving more and more towards automation as we grow. We aim to minimize the manual work where applicable. Still, an expert-based intervention is really needed in some of the steps, and we do not want to renounce it. We intend to keep working on MAVISp to make the process of adding and updating entries as automated as possible, and to streamline the process when manual intervention is necessary. From the point of view of the biocurators, they have three core workflows to use for the default modules, which also automatically cover the source of annotations. We are currently working to streamline the procedures behind LOCAL_INTERACTION, which is the most challenging one. On the data manager and maintainers' side, we have workflows and protocols that help us in terms of automation, quality control, etc, and we keep working to improve them. Among these, we have workflows to use for the old entries updates. As an example, the update of erroneously attributed RefSeq data (pointed out by reviewer 2) took us only one week overall (from assigning revisions and importing to the database) because we have a reduced version of Snakemake for automation that can act on only the affected modules. Also, another point is that we have streamlined the generation of the templates for the gitbook reports (see also answer to reviewer 2).
The update of old entries is planned and made regularly. We also deposit the old datasets on OSF for transparency, in case someone needs to navigate and explore the changes. We have activities planned between May and August every year to update the old entries in relation to changes of protocols in the modules, updates in the core databases that we interact with (COSMIC, Clinvar etc). In case of major changes, the activities for updates continue in the Fall. Other revisions can happen outside these time windows if an entry is needed or a specific research project and needs updates too.
Furthermore, the community of people contributing to MAVISp as biocurators or developers is growing and we have scientists contributing from other groups in relation to their research interest. We envision that for this resource to scale up, our team cannot be the only one producing data and depositing it to the database. To facilitate this we launched a pilot for a training event online (see Event page on the website) and we will repeat it once per year. We also organize regular meetings with all the active curators and developers to plan the activities in a sustainable manner and address the challenges we encounter.
As stated in the manuscript, currently with the team of people involved, automatization and resources that we have gathered around this initiative we can provide updates to the public database every third month and we have been regularly satisfied with them. Additionally, we are capable of processing from 20 to 40 proteins every month depending also on the needs of revision or expansion of analyses on existing proteins. We also depend on these data for our own research projects and we are fully committed to it.
Additionally, we are planning future activities in these directions to improve scale up and sustainability:
We thank the reviewer for this comment - we are aware of the upcoming EOL of Python 3.9. We tested MAVISp, both software package and web server, using Python 3.10 (which is the minimum supported version going forward) and Python 3.13 (which is the latest stable release at the time of writing) and updated the instructions in the README file on the MAVISp GitHub repository accordingly.
We plan on keeping track of Python and library versions during our testing and updating them when necessary. In the future, we also plan to deploy Continuous Integration with automated testing for our repository, making this process easier and more standardized.
I appreciate that the authors have made their code and data available. These artifacts should also be versioned and archived in a service like Zenodo, so that researchers who rely on or want to refer to specific versions can do so in their own future publications.
Since 2024, we have been reporting all previous versions of the dataset on OSF, the repository linked to the MAVISp website, at https://osf.io/ufpzm/files/osfstorage (folder: previous_releases). We prefer to keep everything under OSF, as we also use it to deposit, for example, the MD trajectory data.
Additionally, in this GitHub page that we use as a space to interact between biocurators, developers, and data managers within the MAVISp community, we also report all the changes in the NEWS space: https://github.com/ELELAB/mavisp_data_collection
Finally, the individual tools are all available in our GitHub repository, where version control is in place (see Table S1, where we now mapped all the resources used in the framework)
In the introduction of the paper, the authors conflate the clinical challenges of variant classification with evidence generation and it's quite muddled together. They should strongly consider splitting the first paragraph into two paragraphs - one about challenges in variant classification/clinical genetics/precision oncology and another about variant effect prediction and experimental methods. The authors should also note that they are many predictors other than AlphaMissense, and may want to cite the ClinGen recommendations (PMID: 36413997) in the intro instead.
We revised the introduction in light of these suggestions. We have split the paragraph as recommended and added a longer second paragraph about VEPs and using structural data in the context of VEPs. We have also added the citation that the reviewer kindly recommended.
Also in the introduction on lines 21-22 the authors assert that "a mechanistic understanding of variant effects is essential knowledge" for a variety of clinical outcomes. While this is nice, it is clearly not the case as we can classify variants according to the ACMG/AMP guidelines without any notion of specific mechanism (for example, by combining population frequency data, in silico predictor data, and functional assay data). The authors should revise the statement so that it's clear that mechanistic understanding is a worthy aspiration rather than a prerequisite.
We revised the statement in light of this comment from the reviewer
In the structural analysis section (page 5, lines 154-155 and elsewhere), the authors define cutoffs with convenient round numbers. Is there a citation for these values or were these arbitrarily chosen by the authors? I would have liked to see some justification that these assignments are reasonable. Also there seems to be an error in the text where values between -2 and -3 kcal/mol are not assigned to a bin (I assume they should also be uncertain). There are other similar seemingly-arbitrary cutoffs later in the section that should also be explained.
We have revised the text making the two intervals explicit, for better clarity.
On page 9, lines 294-298 the authors talk about using the PTEN data from ProteinGym, rather than the actual cutoffs from the paper. They get to the latter later on, but I'm not sure why this isn't first? The ProteinGym cutoffs are somewhat arbitrarily based on the median rather than expert evaluation of the dataset, and I'm not sure why it's even worth mentioning them when proper classifications are available. Regarding PTEN, it would be quite interesting to see a comparison of the VAMP-seq PTEN data and the Mighell phosphatase assay, which is cited on page 9 line 288 but is not actually a VAMP-seq dataset. I think this section could be interesting but it requires some additional attention.
We have included the data from Mighell’s phosphatase assay as provided by MAVEdb in the MAVISp database, within the experimental_data module for PTEN, and we have revised the case study, including them and explaining better the decision of supporting both the ProteinGym and MAVEdb classification in MAVISp (when available). See revised Figure3, Table 1 and corresponding text.
The authors mention "pathogenicity predictors" and otherwise use pathogenicity incorrectly throughout the manuscript. Pathogenicity is a classification for a variant after it has been curated according to a framework like the ACMG/AMP guidelines (Richards 2015 and amendments). A single tool cannot predict or assign pathogenicity - the AlphaMissense paper was wrong to use this nomenclature and these authors should not compound this mistake. These predictors should be referred to as "variant effect predictors" or similar, and they are able to produce evidence towards pathogenicity or benignity but not make pathogenicity calls themselves. For example, in Figure 4e, the terms "pathogenic" and "benign" should only be used here if these are the classifications the authors have derived from ClinVar or a similar source of clinically classified variants.
The reviewer is correct, we have revised the terminology we used in the manuscript and refers to VEPs (Variant Effect Predictors)
Minor comments:
The target selection table on the website needs some kind of text filtering option. It's very tedious to have to find a protein by scrolling through the table rather than typing in the symbol. This will only get worse as more datasets are added.
We have revised the website, adding a filtering option. In detail, we have refactored the web app by adding filtering functionality, both for the main protein table (that can now be filtered by UniProt AC, gene name, or RefSeq ID) and the mutations table. Doing this required a general overhaul of the table infrastructure (we changed the underlying engine that renders the tables).
The data sources listed on the data usage section of the website are not concordant with what is in the paper. For example, MaveDB is not listed.
We have revised and updated the data sources on the website, adding a metadata section with relevant information, including MaveDB references where applicable.
Figure 2 is somewhat confusing, as it partially interleaves results from two different proteins. This would be nicer as two separate figures, one on each protein, or just of a single protein.
As suggested by the reviewer, we have now revised the figure and corresponding legends and text, focusing only on one of the two proteins.
Figure 3 panel b is distractingly large and I wonder if the authors could do a little bit more with this visualization.
We have revised Figure 3 to solve these issues and integrating new data from the comparison with the phosphatase assay
Capitalization is inconsistent throughout the manuscript. For example, page 9 line 288 refers to VampSEQ instead of VAMP-seq (although this is correct elsewhere). MaveDB is referred to as MAVEdb or MAVEDB in various places. AlphaMissense is referred to as Alphamissense in the Figure 5 legend. The authors should make a careful pass through the manuscript to address this kind of issues.
We have carefully proofread the paper for these inconsistencies
MaveDB has a more recent paper (PMID: 39838450) that should be cited instead of/in addition to Esposito et al.
We have added the reference that the reviewer recommended
On page 11, lines 338-339 the authors mention some interesting proteins including BLC2, which has base editor data available (PMID: 35288574). Are there plans to incorporate this type of functional assay data into MAVISp?
The assay mentioned in the paper refers to an experimental setup designed to investigate mutations that may confer resistance to the drug venetoclax. We started the first steps to implement a MAVISp module aimed at evaluating the impact of mutations on drug binding using alchemical free energy perturbations (ensemble mode) but we are far from having it complete. We expect to import these data when the module will be finalized since they can be used to benchmark it and BCL2 is one of the proteins that we are using to develop and test the new module.
Reviewer #3 (Significance (Required)):
Significance:
General assessment:
This is a nice resource and the authors have clearly put a lot of effort in. They should be celebrated for their achievments in curating the diverse datasets, and the GitBooks are a nice approach. However, I wasn't able to get the website to work and I have raised several issues with the paper itself that I think should be addressed.
Advance:
New ways to explore and integrate complex data like protein structures and variant effects are always interesting and welcome. I appreciate the effort towards manual curation of datasets. This work is very similar in theme to existing tools like Genomics 2 Proteins portal (PMID: 38260256) and ProtVar (PMID: 38769064). Unfortunately as I wasn't able to use the site I can't comment further on MAVISp's position in the landscape.
We have expanded the conclusions section to add a comparison and cite previously published work, and linked to a review we published last year that frames MAVISp in the context of computational frameworks for the prediction of variant effects. In brief, the Genomics 2 Proteins portal (G2P) includes data from several sources, including some overlapping with MAVISp such as Phosphosite or MAVEdb, as well as features calculated on the protein structure. ProtVar also aggregates mutations from different sources and includes both variant effect predictors and predictions of changes in stability upon mutation, as well as predictions of complex structures. These approaches are only partially overlapping with MAVISp. G2P is primarily focused on structural and other annotations of the effect of a mutation; it doesn’t include features about changes of stability, binding, or long-range effects, and doesn’t attempt to classify the impact of a mutation according to its measurements. It also doesn’t include information on protein dynamics. Similarly, ProtVar does include information on binding free energies, long effects, or dynamical information.
Audience:
MAVISp could appeal to a diverse group of researchers who are interested in the biology or biochemistry of proteins that are included, or are interested in protein variants in general either from a computational/machine learning perspective or from a genetics/genomics perspective.
My expertise:
I am an expert in high-throughput functional genomics experiments and am an experienced computational biologist with software engineering experience.
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Summary:
The authors present MAVISp, a tool for viewing protein variants heavily based on protein structure information. The authors have done a very impressive amount of curation on various protein targets, and should be commended for their efforts. The tool includes a diverse array of experimental, clinical, and computational data sources that provides value to potential users interested in a given target.
Major comments:
Unfortunately I was not able to get the website to work properly. When selecting a protein target in simple mode, I was greeted with a completely blank page in the app window, and in ensemble mode, there was no transition away from the list of targets at all. I'm using Firefox 140.0.2 (64-bit) on Ubuntu 22.04. I would have liked to be able to explore the data myself and provide feedback on the user experience and utility.
I have some serious concerns about the sustainability of the project and think that additional clarifications in the text could help. Currently is there a way to easily update a dataset to add, remove, or update a component (for example, if a new predictor is published, an error is found in a predictor dataset, or a predictor is updated)? If it requires a new round of manual curation for each protein to do this, I am worried that this will not scale and will leave the project with many out of date entries. The diversity of software tools (e.g., three different pipeline frameworks) also seems quite challenging to maintain.
On the same theme, according to the GitHub repository, the program relies on Python 3.9, which reaches end of life in October 2025. It has been tested against Ubuntu 18.04, which left standard support in May 2023. The authors should update the software to more modern versions of Python to promote the long-term health and maintainability of the project.
I appreciate that the authors have made their code and data available. These artifacts should also be versioned and archived in a service like Zenodo, so that researchers who rely on or want to refer to specific versions can do so in their own future publications.
In the introduction of the paper, the authors conflate the clinical challenges of variant classification with evidence generation and it's quite muddled together. The y should strongly consider splitting the first paragraph into two paragraphs - one about challenges in variant classification/clinical genetics/precision oncology and another about variant effect prediction and experimental methods. The authors should also note that they are many predictors other than AlphaMissense, and may want to cite the ClinGen recommendations (PMID: 36413997) in the intro instead.
Also in the introduction on lines 21-22 the authors assert that "a mechanistic understanding of variant effects is essential knowledge" for a variety of clinical outcomes. While this is nice, it is clearly not the case as we are able to classify variants according to the ACMG/AMP guidelines without any notion of specific mechanism (for example, by combining population frequency data, in silico predictor data, and functional assay data). The authors should revise the statement so that it's clear that mechanistic understanding is a worthy aspiration rather than a prerequisite.
In the structural analysis section (page 5, lines 154-155 and elsewhere), the authors define cutoffs with convenient round numbers. Is there a citation for these values or were these arbitrarily chosen by the authors? I would have liked to see some justification that these assignments are reasonable. Also there seems to be an error in the text where values between -2 and -3 kcal/mol are not assigned to a bin (I assume they should also be uncertain). There are other similar seemingly-arbitrary cutoffs later in the section that should also be explained.
On page 9, lines 294-298 the authors talk about using the PTEN data from ProteinGym, rather than the actual cutoffs from the paper. They get to the latter later on, but I'm not sure why this isn't first? The ProteinGym cutoffs are somewhat arbitrarily based on the median rather than expert evaluation of the dataset and I'm not sure why it's even worth mentioning them when proper classifications are available. Regarding PTEN, it would be quite interesting to see a comparison of the VAMP-seq PTEN data and the Mighell phosphatase assay, which is cited on page 9 line 288 but is not actually a VAMP-seq dataset. I think this section could be interesting but it requires some additional attention.
The authors mention "pathogenicity predictors" and otherwise use pathogenicity incorrectly throughout the manuscript. Pathogenicity is a classification for a variant after it has been curated according to a framework like the ACMG/AMP guidelines (Richards 2015 and amendments). A single tool cannot predict or assign pathogenicity - the AlphaMissense paper was wrong to use this nomenclature and these authors should not compound this mistake. These predictors should be referred to as "variant effect predictors" or similar, and they are able to produce evidence towards pathogenicity or benignity but not make pathogenicity calls themselves. For example, in Figure 4e, the terms "pathogenic" and "benign" should only be used here if these are the classifications the authors have derived from ClinVar or a similar source of clinically classified variants.
Minor comments:
The target selection table on the website needs some kind of text filtering option. It's very tedious to have to find a protein by scrolling through the table rather than typing in the symbol. This will only get worse as more datasets are added.
The data sources listed on the data usage section of the website are not concordant with what is in the paper. For example, MaveDB is not listed.
I found Figure 2 to be a bit confusing in that it partially interleaves results from two different proteins. I think this would be nicer as two separate figures, one on each protein, or just of a single protein.
Figure 3 panel b is distractingly large and I wonder if the authors could do a little bit more with this visualization.
Capitalization is inconsistent throughout the manuscript. For example, page 9 line 288 refers to VampSEQ instead of VAMP-seq (although this is correct elsewhere). MaveDB is referred to as MAVEdb or MAVEDB in various places. AlphaMissense is referred to as Alphamissense in the Figure 5 legend. The authors should make a careful pass through the manuscript to address this kind of issues.
MaveDB has a more recent paper (PMID: 39838450) that should be cited instead of/in addition to Esposito et al.
On page 11, lines 338-339 the authors mention some interesting proteins including BLC2, which has base editor data available (PMID: 35288574). Are there plans to incorporate this type of functional assay data into MAVISp?
General assessment:
This is a nice resource and the authors have clearly put a lot of effort in. They should be celebrated for their achievments in curating the diverse datasets, and the GitBooks are a nice approach. However, I wasn't able to get the website to work and I have raised several issues with the paper itself that I think should be addressed.
Advance:
New ways to explore and integrate complex data like protein structures and variant effects are always interesting and welcome. I appreciate the effort towards manual curation of datasets. This work is very similar in theme to existing tools like Genomics 2 Proteins portal (PMID: 38260256) and ProtVar (PMID: 38769064). Unfortunately as I wasn't able to use the site I can't comment further on MAVISp's position in the landscape.
Audience:
MAVISp could appeal to a diverse group of researchers who are interested in the biology or biochemistry of proteins that are included, or are interested in protein variants in general either from a computational/machine learning perspective or from a genetics/genomics perspective.
My expertise:
I am an expert in high-throughput functional genomics experiments and am an experienced computational biologist with software engineering experience.
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Summary:
The authors present a pipeline and platform, MAVISp, for aggregating, displaying and analysis of variant effects with a focus on reclassification of variants of uncertain clinical significance and uncovering the molecular mechanisms underlying the mutations.
Major comments:
Minor comments
The last of these points is not an application of MAVISp, but rather a way in which external data can help validate MAVISp results. Furthermore, none of the examples given demonstrate an application in benchmarking (what is being benchmarked?). - Transcription factors section. This section describes an intended future expansion to MAVISp, not a current feature, and presents no results. As such, it should probably be moved to the conclusions/future directions section. - Figures. The dot-plots generated by the web app, and in Figures 4, 5 and 6 have 2 legends. After looking at a few, it is clear that the lower legend refers to the colour of the variant on the X-axis - most likely referencing the ClinVar effect category. This is not, however, made clear either on the figures or in the app. - "We identified ten variants reported in ClinVar as VUS (E102K, H86D, T29I, V91I, P2R, L44P, L44F, D56G, R11L, and E25Q, Fig.5a)"
E25Q is benign in ClinVar and has had that status since first submitted.
Platforms that aggregate predictors of variant effect are not a new concept, for example dbNSFP is a database of SNV predictions from variant effect predictors and conservation predictors over the whole human proteome. Predictors such as CADD and PolyPhen-2 will often provide a summary of other predictions (their features) when using their platforms. MAVISp's unique angle on the problem is in the inclusion of diverse predictors from each of its different moules, giving a much wider perspective on variants and potentially allowing the user to identify the mechanistic cause of pathogenicity. The visualisation aspect of the web app is also a useful addition, although the user interface is somewhat awkward. Potentially the most valuable aspect of this study is the associated gitbook resource containing reports from biocurators for proteins that link relevant literature and analyse ClinVar variants. Unfortunately, these are only currently available for a small minority of the total proteins in the database with such reports.
For improvement, I think that the paper should focus more on the precise utility of the web app / gitbook reports and how to interpret the results rather than going into detail about the underlying pipeline.
In terms of audience, the fast look-up and visualisation aspects of the web-platform are likely to be of interest to clinicians in the interpretation of variants of unknown clinical significance. The ability to download the fully processed dataset on a per-protein database would be of more interest to researchers focusing on specific proteins or those taking a broader view over multiple proteins (although a facility to download the whole database would be more useful for this final group).
My expertise.
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Summary: This manuscript, "MAVISp: A Modular Structure-Based Framework for Protein Variant Effects," presents a significant new resource for the scientific community, particularly in the interpretation and characterization of genomic variants. The authors have developed a comprehensive and modular computational framework that integrates various structural and biophysical analyses, alongside existing pathogenicity predictors, to provide crucial mechanistic insights into how variants affect protein structure and function. Importantly, MAVISp is open-source and designed to be extensible, facilitating reuse and adaptation by the broader community.
Major comments:
Minor comments:
Page 3, line 46: "MAVISp perform" -> "MAVISp performs"
Page 3, line 56: "automatically as embedded" -> "automatically embedded"
Page 3, line 57: "along with to enhance" -> unclear; please revise
Page 4, line 96: "web app interfaces with the database and present" -> "presents"
Page 6, line 210: "to investigate wheatear" -> "whether"
Page 6, lines 215-216: "We have in queue for processing with MAVISp proteins from datasets relevant to the benchmark of the PTM module." -> unclear sentence; please clarify
Page 15, line 446: "Both the approaches" -> "Both approaches"
Page 20, line 704: "advantage of multi-core system" -> "multi-core systems"
General assessment: the strongest aspects of the study are the modularity, open-source implementation, and the integration of structural information through graph neural networks. MAVISp appears to be one of the few publicly available frameworks that can easily incorporate AlphaFold2-based features in a flexible way, lowering the barrier for developing custom predictors. Its reproducibility and transparency make it a valuable resource. However, while the technical foundation is solid and the effort substantial, the scientific narrative and presentation could be significantly improved. The manuscript is dense and hard to follow in places, with a heavy use of acronyms and insufficient explanation of key design choices. Improving the descriptive clarity, especially in the early sections, would greatly enhance the impact of this work.
Advance: to the best of my knowledge, this is one of the first modular platforms for protein variant effect prediction that integrates structural data from AlphaFold2 with bioinformatic annotations and even clinical data in an extensible fashion. While similar efforts exist (e.g., ESMfold, AlphaMissense), MAVISp distinguishes itself through openness and design for reusability. The novelty is primarily technical and practical rather than conceptual.
Audience: this study will be of strong interest to researchers in computational biology, structural bioinformatics, and genomics, particularly those developing variant effect predictors or analyzing the impact of mutations in clinical or functional genomics contexts. The audience is primarily specialized, but the open-source nature of the tool may diffuse its use among more applied or translational users, including those working in precision medicine or protein engineering.
Reviewer expertise: my expertise is in computational structural biology, molecular modeling, and (rather weak) machine learning applications in bioinformatics. I am familiar with graph-based representations of proteins, AlphaFold2, and variant effects based on Molecular Dynamics simulations. I do not have any direct expertise in clinical variant annotation pipelines.
eLife Assessment
This important study advances our understanding of how cellular quality control machinery influences cystic fibrosis (CF) drug responsiveness by systematically analyzing the effects of the chaperone calnexin on more than two hundreds of CFTR (cystic fibrosis transmembrane regulator) variants. The evidence supporting the conclusions is convincing, with a comprehensive deep mutational scanning methodology and rigorous quantitative analysis. The findings reveal that calnexin is critical for both CFTR protein expression and corrector drug efficacy in a variant-specific manner, providing invaluable insights that could guide the development of personalized CF therapies. This work will be of significant interest to researchers in protein folding, CF drug development, and genetic disease therapeutics.
Reviewer #1 (Public review):
Summary:
This research investigates how the cellular protein quality control machinery influences the effectiveness of cystic fibrosis (CF) treatments across different genetic variants. CF is caused by mutations in the CFTR gene, with over 1,700 known disease-causing variants that primarily work through protein misfolding mechanisms. While corrector drugs like those in Trikafta therapy can stabilize some misfolded CFTR proteins, the reasons why certain variants respond to treatment while others don't remain unclear. The authors hypothesized that the cellular proteostasis network-the machinery that manages protein folding and quality control-plays a crucial role in determining drug responsiveness across different CFTR variants. The researchers focused on calnexin (CANX), a key chaperone protein that recognizes misfolded glycosylated proteins. Using CRISPR-Cas9 gene editing combined with deep mutational scanning, they systematically analyzed how CANX affects the expression and corrector drug response of 234 clinically relevant CF variants in HEK293 cells.
In terms of findings, this study revealed that CANX is generally required for robust plasma membrane expression of CFTR proteins, and CANX disproportionately affects variants with mutations in the C-terminal domains of CFTR and modulates later stages of protein assembly. Without CANX, many variants that would normally respond to corrector drugs lose their therapeutic responsiveness. Furthermore, loss of CANX caused broad changes in how CF variants interact with other cellular proteins, though these effects were largely separate from changes in CFTR channel activity.
This study has some limitations: the research was conducted in HEK293 cells rather than lung epithelial cells, which may not fully reflect the physiological context of CF. Additionally, the study only examined known disease-causing variants and used methodological approaches that could potentially introduce bias in the data analysis.
How cellular quality control mechanisms influence the therapeutic landscape of genetic diseases is an emerging field. Overall, this work provides important cellular context for understanding CF mutation severity and suggests that the proteostasis network significantly shapes how different CFTR variants respond to corrector therapies. The findings could pave the way for more personalized CF treatments tailored to patients' specific genetic variants and cellular contexts.
Strengths:
(1) This work makes an important contribution to the field of variant effect prediction by advancing our understanding of how genetic variants impact protein function.
(2) The study provides valuable cellular context for CFTR mutation severity, which may pave the way for improved CFTR therapies that are customized to patient-specific cellular contexts.
(3) The research provides further insight into the biological mechanisms underlying approved CFTR therapies, enhancing our understanding of how these treatments work.
(4) The authors conducted a comprehensive and quantitative analysis, and they made their raw and processed data as well as analysis scripts publicly available, enabling closer examination and validation by the broader scientific community.
Comments on revisions:
The authors have addressed my concerns. If Document S1 is part of the final published version, this will address one of my previous concerns about potential skew and bias in the read data (Weakness 3, Methodological Choices).
Reviewer #2 (Public review):
In this work, the authors use deep mutational scanning (DMS) to examine the effect of the endogenous chaperone calnexin (CANX) on the plasma membrane expression (PME) and potential pharmacological stabilization cystic fibrosis disease variants. This is important because there are over 1,700 loss-of-function mutations that can lead to the disease Cystic Fibrosis (CF), and some of these variants can be pharmacologically rescued by small-molecule "correctors," which stabilize the CFTR protein and prevent its degradation. This study expands on previous work to specifically identify which mutations affect sensitivity to CFTR modulators, and further develops the work by examining the effect of a known CFTR interactor-CANX-on PME and corrector response.
Overall, this approach provides a useful atlas of CF variants and their downstream effects, both at a basal level as well as in the context of a perturbed proteostasis. Knockout of CANX leads to an overall reduced plasma membrane expression of CFTR with CF variants located at the C-terminal domains of CFTR, which seem to be more affected than the others. This study then repeats their DMS approach, using PME as a readout, to probe the effect of either VX-445 or VX-455 + VX-661-which are two clinically relevant CFTR pharmacological modulators. I found this section particularly interesting for the community because the exact molecular features that confer drug resistance/sensitivity are not clear. When CANX is knocked out, cells that normally respond to VX-445 are no longer able to be rescued, and the DMS data show that these non-responders are CF variants that lie in the VX-445 binding site. Based on computational data, the authors speculate that NBD2 assembly is compromised, but that remains to be experimentally examined. Cells lacking CANX were also resistant to combinatorial treatment of VX-445 + VX-661, showing that these two correctors were unable to compensate for the lack of this critical chaperone.
One major strength of this manuscript is the mass spectrometry data, in which 4 CF variants were profiled in parental and CANX KO cells. This analysis provides some explanatory power to the observation that the delF508 variant is resistant to correctors in CANX KO cells, which is because correctors were found not to affect protein degradation interactions in this context. Findings such as this provide potential insights into intriguing new hypothesis, such as whether addition of an additional proteostasis regulators, such as a proteosome inhibitor, would facilitate a successful rescue. Taken together, the data provided can be generative to researchers in the field and may be useful in rationalizing some of the observed phenotypes conferred by the various CF variants, as well as the impact of CANX on those effects.
To complete their analysis of CF variants in CANX KO cells, the research also attempted to relate their data, primarily based on PME, to functional relevance. They observed that, although CANX KO results in a large reduction in PME (~30% reduction), changes in the actual activation of CFTR (and resultant quenching of their hYFP sensor) were "quite modest." This is an important experiment and caveat to the PME data presented above since changes in CFTR activity does not strictly require changes in PME. In addition, small molecule correctors also do not drastically alter CFTR function in the context of CANX KO. The authors reason that this difference is due to a sort of compensatory mechanism in which the functionally active CFTR molecules that are successfully assembled in an unbalanced proteostasis system (CANX KO) are more active than those that are assembled with the assistance of CANX. While I generally agree with this statement, it is not directly tested and would be challenging to actually test.
The selected model for all the above experiments was HEK293T cells. The authors then demonstrate some of their major findings in Fischer rat thyroid cell monolayers. Specifically, cells lacking CANX are less sensitive to rescue by CFTR modulators than the WT. This highlights the importance of CANX in supporting the maturation of CFTR and the dependence of chemical correctors on the chaperone. Although this is demonstrated specifically for CANX in this manuscript, I imagine a more general claim can be made that chemical correctors depend on a functional/balanced proteostasis system, which is supported by the manuscript data. I am surprised by the discordance between HEK293T PME levels compared to the CTFR activity. The authors offer a reasonable explanation about the increase in specific activity of the mature CFTR protein following CANX loss.
For the conclusions and claims relevant to CANX and CF variant surveying of PME/function, I find the manuscript to provide solid evidence to achieve this aim. The manuscript generates a rich portrait of the influence of CF mutations both in WT and CANX KO cells. While the focus of this study is a specific chaperone, CANX, this manuscript has the potential to impact many researchers in the broad field of proteostasis.
Comments on revisions:
The authors address my concerns. I appreciate seeing that the UPR probably isn't activated, ruling out that less PME is simply due to less CF protein.
Author response:
The following is the authors’ response to the original reviews
Reviewer 1 (Public review):
This research investigates how the cellular protein quality control machinery influences the effectiveness of cystic fibrosis (CF) treatments across different genetic variants. CF is caused by mutations in the CFTR gene, with over 1,700 known disease-causing variants that primarily work through protein misfolding mechanisms. While corrector drugs like those in Trikafta therapy can stabilize some misfolded CFTR proteins, the reasons why certain variants respond to treatment while others don't remain unclear. The authors hypothesized that the cellular proteostasis network-the machinery that manages protein folding and quality control-plays a crucial role in determining drug responsiveness across different CFTR variants. The researchers focused on calnexin (CANX), a key chaperone protein that recognizes misfolded glycosylated proteins. Using CRISPR-Cas9 gene editing combined with deep mutational scanning, they systematically analyzed how CANX affects the expression and corrector drug response of 234 clinically relevant CF variants in HEK293 cells.
In terms of findings, this study revealed that CANX is generally required for robust plasma membrane expression of CFTR proteins, and CANX disproportionately affects variants with mutations in the C-terminal domains of CFTR and modulates later stages of protein assembly. Without CANX, many variants that would normally respond to corrector drugs lose their therapeutic responsiveness. Furthermore, loss of CANX caused broad changes in how CF variants interact with other cellular proteins, though these effects were largely separate from changes in CFTR channel activity.
This study has some limitations: the research was conducted in HEK293 cells rather than lung epithelial cells, which may not fully reflect the physiological context of CF. Additionally, the study only examined known diseasecausing variants and used methodological approaches that could potentially introduce bias in the data analysis.
We agree that the approaches employed here are not fully physiological, though we would remind the reviewer that we previously benchmarked the results generated by this experimental platform against a variety of other published datasets (PMID: 37253358). Regarding the issue of bias, we outline several pieces of evidence suggesting we retain robust and near-uniform sampling of these variants across these experimental conditions. We hope our comments below address all of these concerns. Overall, we believe deep mutational scanning is actually remarkably unbiased relative to other approaches due to the fact that all measurements are taken from a single dish of cells that is processed in parallel. Moreover, we show the trends are highly reproducible across replicates and users (see Figure S1).
How cellular quality control mechanisms influence the therapeutic landscape of genetic diseases is an emerging field. Overall, this work provides important cellular context for understanding CF mutation severity and suggests that the proteostasis network significantly shapes how different CFTR variants respond to corrector therapies. The findings could pave the way for more personalized CF treatments tailored to patients' specific genetic variants and cellular contexts.
Strengths:
(1) This work makes an important contribution to the field of variant effect prediction by advancing our understanding of how genetic variants impact protein function.
(2) The study provides valuable cellular context for CFTR mutation severity, which may pave the way for improved CFTR therapies that are customized to patient-specific cellular contexts.
(3) The research provides further insight into the biological mechanisms underlying approved CFTR therapies, enhancing our understanding of how these treatments work.
(4) The authors conducted a comprehensive and quantitative analysis, and they made their raw and processed data as well as analysis scripts publicly available, enabling closer examination and validation by the broader scientific community.
We are grateful for this broad perspective on the general relevance of this work.
Weaknesses:
(1) The study only considers known disease-causing variants, which limits the scope of findings and may miss important insights from variants of uncertain significance.
We agree with this caveat. A more comprehensive library of CFTR variants will undoubtedly be useful for assigning variants of uncertain significance, though we note that such a large library would involve trade-offs in depth/ coverage that will compromise the sensitivity/ precision of the measurements. This will, in turn, make it challenging to compare the effects of CFTR modulators across the spectrum of clinical variants. For this reason, we believe the current library will remain a useful tool for CF variant theratyping.
(2) The cellular context of HEK293 cells is quite removed from lung epithelia, the primary tissue affected in cystic fibrosis, potentially limiting the clinical relevance of the findings.
We concede this limitation, but note that we did carry out functional measurements in FRT monolayers, which are a prevailing model that closely mimics pharmacological outcomes in the clinic (see Fig. 6).
(3) Methodological choices, such as the expansion of sorted cell populations before genetic analysis, may introduce possible skew or bias in the data that could affect interpretation.
We respectfully disagree with this point. The recombination system we employ in these studies generates millions of recombinant cells per transfection, which corresponds to tens of thousands of clones per variant. Moreover, our sequencing data contain exhaustive coverage of every variant characterized herein within each of the final data sets. Generally, we do not see any evidence to suggest certain variants are lost from the population. We note that, while HEK293T cells are not the most physiological relevant system, they are robust to uniformly express these variants in a manner that provides a precise comparison of their effects and/ or response to CFTR modulators. To address this concern, we added Document S1 to the revised draft, which shows the total number of reads for each variant within each fraction and each experiment.
(4) While the impact on surface trafficking is convincingly demonstrated, how cellular proteostasis affects CFTR function requires further study, likely within a lung-specific cellular context to be more clinically relevant.
We agree with this caveat.
Reviewer 1 (Recommendations for the authors):
Major Issues
Cell Growth Bias? After sorting cell populations into quartiles, cells were expanded before genetic analysis - if CFTR variants affect cell doubling time (e.g., severely misfolded variants causing cellular stress), this could skew variant abundance within sorted quartiles and bias results.
Based on several observations, we do not believe this to be a significant issue. First, we note that we previously benchmarked the quantitative outputs of these experiments against a variety of other investigations and found very good agreement with previous variant classifications and expression levels (PMID: 37253358). If there were significant bias, we believe this would have come up in our efforts to benchmark the assay. Second, we note that we typically create recombinant cell lines that express WT or ΔF508 CFTR only alongside each recombinant cellular library. Importantly, we have never observed any difference in the growth rate of cultures expressing different CFTR variants. Third, even if cells expressing certain variants grow slower, it seems likely this slow growth would consistently occur in the context of each sorted subpopulation. Given that scores are derived from the relative amount of identifications across each subpopulation, we do not suspect this should impact the scoring. Overall, we believe the robustness of this cell line is a key feature that allows us to avoid any such issues related to proteostatic toxicity.
(1) Please add methodological detail. The data analysis pipeline lacks adequate description beyond referencing prior studies - essential details about what the Plasma Membrane Expression (PME) values represent (fold enrichment vs input library) and calculation methods must be provided.
We thank the reviewer for this helpful comment. We have added the text below to the revised manuscript in order to provide more detail to the reader:
“Briefly, low quality reads that likely contain more than one error were first removed from the demultiplexed sequencing data. Unique molecular identifier sequences within the remaining reads were then counted within each sample to track the relative abundance of each variant. To compare read counts across fractions, the collection of reads within each population were then randomly down-sampled to ensure a consistent total read count across each sub-population. The surface immunostaining of each variant was then estimated by calculating the the weighted-average immunostaining intensity for each variant using the following equation:
where ⟨I⟩<sub>variant</sub> is the weighted-average fluorescence intensity of a given variant, ⟨F⟩<sub>i</sub> is the mean fluorescence intensity associated with cells from the ith FACS quartile, and Ni is the number of variant reads in the i<sup>th</sup> FACS quartile. Variant intensities from each replicate were normalized relative to one another using the mean surface immunostaining intensity of the entire recombinant cell population for each experiment to account for small variations in laser power and/ or detector voltage. Finally, to filter out any noisy scores arising from insufficient sampling, we repeated the down-sampling and scoring process then rejected any variant measurements that exhibit more than X% variation in their intensity scores across the two replicate analyses. The reported intensity values represent the average normalized intensity values from two independent down-sampling iterations across three biologicals replicates.”
(3) Add detail on library composition. The distribution of CFTR variants within the parental HEK293T library after landing pad insertion needs documentation, including any variant dropout or overrepresentation issues.
As noted in our previous work (PMID: 37253358), our CF variant library is quite uniform, with each mutant contributing on average, 0.43% of the library with a standard deviation of +/- 0.16%. This corresponds to an average read depth of over 40K reads per variant, per experimental condition in the final analyses. Indeed, the most abundant variant in the pool was ΔF508 (1.67% of total reads). In contrast, the least sampled variant was S549R (1647T>G) was still sampled an average of 3,688 times per replicate, which corresponds to 0.09% of the total reads. See Doc S1.
(4) Documentation of CFTR variant overlap between parental and CANX KO HEK293T libraries is needed, including whether every variant was present at equivalent input abundance in both libraries.
We thank the reviewer for this suggestion. Though there are small deviations in the composition of recombinant parental and knockout cell lines, the relative abundances of individual variants within the recombinant populations only differs by an average of 18.5% between the parental and knockout lines. There are no cases in which we observe a single variant increasing by more than 50% in the knockout line relative to the parent. However, there is a single variant, Y563N, that exhibits a 96% decrease in its abundance in the context of the knockout cell line. Nevertheless, even this variant was sampled over 1,000 times, and it’s final score passed all quality control metrics. In the revised draft, we have provided a complete table containing the total number of reads and percent of total reads for each variant for each cell line and condition (see Doc. S1).
(5) The section reporting CANX impact on functional rescue of CF variants requires clearer logic flow - the conclusion about higher specific activity of CFTR assembled without CANX appears misleading, given later discussion about CANX allowing suboptimally folded CFTR to traffic to the surface.
We apologize for any confusion. We invoked the term “specific activity” in the enzymological sense, which is to say the proportion of active enzyme (i.e. channel) at the plasma membrane differs in the knockout line. The logic is quite simple- if protein levels are lower while ion conductance remains the same in the knockout cells, then a higher proportion of the mature channels must be inactive in the parental cell line. Thus, we suspect fewer of the channels at the plasma membrane are active in the context of the parental cell line containing CANX. We considered modifications to the text in the discussion, but ultimately feel the current text strikes a reasonable balance between nuance and simplicity.
(6) In your discussion, consider that HEK293T cellular context differs significantly from lung epithelia, and the hYFP quenching assay may have insufficient dynamic range or high noise for detecting relevant functional differences.
We modified the following sentence in the discussion to introduce this possibility:
“While these discrepancies could stem from differences in the dynamic range of the functional assays, they may also suggest the stringency of QC is more finely tuned to ion channel biosynthesis in epithelial monolayers.”
Minor Issues
(1) Include immunostaining quartiles as a supplementary figure overlaid on Figure 1A, and clarify whether quartiles were consistent across experiments or adjusted for each sort.
We added a new figure to demonstrate the gating approach in the revised manuscript (see Fig. S10). We have also added the following text to the Methods section:
“Sorting gates for surface immunostaining were independently set for each biological replicate and in each condition to ensure that the population was evenly divided into four equal subpopulations.”
(2) Figure 2C improvements. Flip the figure 180 degrees to position MSD1 and NBD1 on the left, replace the blue-to-red color scale with yellow-to-blue or monochromatic scaling for better intermediate value differentiation.
Respectfully, we prefer not to do this so that our figures can be easily compared across our previous and forthcoming publications. We chose this rendering because this view depicts certain trends in variant response more clearly.
(3) Indicate the location of ECL4 on the protein structure shown in Figure 2C for better reference.
We appreciate the suggestion. However, most of ECL4 is missing from the experimental cryo-EM models of CFTR due to a lack of density. For this reason, we did not modify the figure.
Reviewer 2 (Public review):
In this work, the authors use deep mutational scanning (DMS) to examine the effect of the endogenous chaperone calnexin (CANX) on the plasma membrane expression (PME) and potential pharmacological stabilization cystic fibrosis disease variants. This is important because there are over 1,700 loss-of-function mutations that can lead to the disease Cystic Fibrosis (CF), and some of these variants can be pharmacologically rescued by small-molecule "correctors," which stabilize the CFTR protein and prevent its degradation. This study expands on previous work to specifically identify which mutations affect sensitivity to CFTR modulators, and further develops the work by examining the effect of a known CFTR interactor-CANX-on PME and corrector response.
Overall, this approach provides a useful atlas of CF variants and their downstream effects, both at a basal level as well as in the context of a perturbed proteostasis. Knockout of CANX leads to an overall reduced plasma membrane expression of CFTR with CF variants located at the C-terminal domains of CFTR, which seem to be more affected than the others. This study then repeats their DMS approach, using PME as a readout, to probe the effect of either VX-445 or VX-455 + VX-661-which are two clinically relevant CFTR pharmacological modulators. I found this section particularly interesting for the community because the exact molecular features that confer drug resistance/sensitivity are not clear. When CANX is knocked out, cells that normally respond to VX-445 are no longer able to be rescued, and the DMS data show that these non-responders are CF variants that lie in the VX-445 binding site. Based on computational data, the authors speculate that NBD2 assembly is compromised, but that remains to be experimentally examined. Cells lacking CANX were also resistant to combinatorial treatment of VX-445 + VX-661, showing that these two correctors were unable to compensate for the lack of this critical chaperone.
One major strength of this manuscript is the mass spectrometry data, in which 4 CF variants were profiled in parental and CANX KO cells. This analysis provides some explanatory power to the observation that the delF508 variant is resistant to correctors in CANX KO cells, which is because correctors were found not to affect protein degradation interactions in this context. Findings such as this provide potential insights into intriguing new hypothesis, such as whether addition of an additional proteostasis regulators, such as a proteosome inhibitor, would facilitate a successful rescue. Taken together, the data provided can be generative to researchers in the field and may be useful in rationalizing some of the observed phenotypes conferred by the various CF variants, as well as the impact of CANX on those effects.
To complete their analysis of CF variants in CANX KO cells, the research also attempted to relate their data, primarily based on PME, to functional relevance. They observed that, although CANX KO results in a large reduction in PME (~30% reduction), changes in the actual activation of CFTR (and resultant quenching of their hYFP sensor) were "quite modest." This is an important experiment and caveat to the PME data presented above since changes in CFTR activity does not strictly require changes in PME. In addition, small molecule correctors also do not drastically alter CFTR function in the context of CANX KO. The authors reason that this difference is due to a sort of compensatory mechanism in which the functionally active CFTR molecules that are successfully assembled in an unbalanced proteostasis system (CANX KO) are more active than those that are assembled with the assistance of CANX. While I generally agree with this statement, it is not directly tested and would be challenging to actually test.
The selected model for all the above experiments was HEK293T cells. The authors then demonstrate some of their major findings in Fischer rat thyroid cell monolayers. Specifically, cells lacking CANX are less sensitive to rescue by CFTR modulators than the WT. This highlights the importance of CANX in supporting the maturation of CFTR and the dependence of chemical correctors on the chaperone. Although this is demonstrated specifically for CANX in this manuscript, I imagine a more general claim can be made that chemical correctors depend on a functional/balanced proteostasis system, which is supported by the manuscript data. I am surprised by the discordance between HEK293T PME levels compared to the CTFR activity. The authors offer a reasonable explanation about the increase in specific activity of the mature CFTR protein following CANX loss.
For the conclusions and claims relevant to CANX and CF variant surveying of PME/function, I find the manuscript to provide solid evidence to achieve this aim. The manuscript generates a rich portrait of the influence of CF mutations both in WT and CANX KO cells. While the focus of this study is a specific chaperone, CANX, this manuscript has the potential to impact many researchers in the broad field of proteostasis.
We thank the reviewer for their thoughtful and comprehensive perspectives on the scope and relevance of this work.
Reviewer 2 (Recommendations for the authors):
While I did not identify any major weaknesses in this manuscript, I offer some suggestions below, as well as some conclusions to consider:
(1) Missing period at the end of line 51.
We thank the reviewer for catching this grammatical error and have added proper punctuation.
(2)Figure S1 "repre-sent"??
We have corrected this punctuation error.
(3) Figure S2 missing parentheses A)
We have corrected the punctuation error.
(4) Figure S5, "B) The total ΔRMSD of the active conformation of NBD2 is shown for variants bound to VX-445. Red bars show increasing deviations from the native NBD2 conformation in the mutant models, and blue bars show how much VX-445 suppresses these conformational defects in NBD2."
VX-445 should not bind/stabilize the G85E from the calculations in Figure S5A. As a confirmation, it would be nice to see the calculated hypothetical effect of VX-445 in the G85E variant as performed for L1077P and N1303K. I also want to point out that G58E is referred to as being non-responsive in S5A, but then in S5D, N103K is referred to as non-responsive, but this variant falls pretty far below the stabilized region calculated in S5A, right?
We agree that it would be insightful to examine the RMSD changes in a non-responsive variant such as G85E. We added the G85E NBD2 ∆RMSD to Supplemental Figure S5B and a G85E ∆RMSD structure map as an additional subpanel at Supplemental Figure S5C. As the reviewer expected, VX-445 fails to confer any stability to G85E as shown by a lack of significant change in NBD2 ∆RMSD or any visible ∆RMSD throughout the structure. Finally, we acknowledge that N1303K falls below the stabilized region as calculated in S5A. However, we note that the binding energy only suggests it is likely to interact with the protein- this does not to necessarily mean that binding will allosterically suppress conformational defects in NBD2. Moreover, this is simply an in silico calculation, that does not necessarily capture all of the nuanced interactions in the cell (or lack thereof). We have corrected this in the Figure S5 caption, which reads as follows:
“Maps of the change in RMSD between N1303K modeled with and without VX-445 shows that few structural regions are stabilized by VX-445 for N1303K, which responds poorly to VX-445 in vitro.”
(5) "stan-dard" standard?
We have corrected this punctuation error.
(6) Line 270, "these variants" is written twice
We have corrected this typographical error.
(7) Figure 6 B. What is being compared? The text writes "there are prominent differences in the activity of these variants [those with CANX] (two-way ANOVA, p = 3.8 x 10-27." Does this mean WT vs. delF508, P5L, V232D, T1036N, and I1366N combined? I have not seen a set of 5 variables compared to a single variable. Usually, it would be WT vs. DelF508, WT vs. P5L, WT vs. V232D...right? Maybe this is normal in this specific field. The same goes for the CANX knockout comparison "(two-way ANOVA, p = 0.06).".
In this instance, the two-way ANOVA test is evaluating whether there are differences in the half-lives of individual variants and/ or systematic differences across the variant measurements in the knockout line relative to the parental cells. The test gives independent p-values for these two variables (variant and cell line). We chose this test because it makes it clear that, when you consider the trends together, one variable has a significant effect while the other does not.
(8) Why don't the CFTR modulators rescue CFTR activity in the WT FRT monolayers?
We thank the reviewer for this inquiry. Please note that compared to DMSO, VX-661 does significantly enhance the forskolin-mediated response of WT-CFTR (red asterisk). Treatments with VX-445 alone, VX-661+VX-445, or VX-661+VX-445+VX-770 showed no significant forskolin stimulation of WT-CFTR. These observations could be attributable to the brief period in which WT-CFTR cDNA is transiently transfected. However, it is not necessarily anticipated that modulators would enhance WT-CFTR function. Correctors and potentiators are designed to rescue processing and gating abnormalities, respectively. WT-CFTR channels do not exhibit such defects.
In both constitutive overexpression systems and primary human airway epithelia, published literature demonstrates that prolonged exposure to CFTR modulators has resulted in variable consequences on WT-CFTR activity. For example, forskolin-mediated responsiveness of WT-CFTR is not altered by chronic application of VX-445 (PMID: 34615919) nor VX-770 (PMID: 28575328, 27402691, 37014818). In contrast, short-circuit current measurements show that forskolin stimulation of WT-CFTR is augmented by chronic treatment with VX-809 (PMID: 28575328), an analog of VX-661. Thus, our findings are congruent with observations reported by other groups.
(9) General comment: As someone not familiar with the field, it would be nice to see the structures of VX-445 and VX-661 somewhere in the figures or at least in the SI.
We appreciate this suggestion, but do not feel that we include enough structural analyses to justify a stand-alone figure for these purposes. The structures of these compounds are easily referenced on a variety of internetbased resources.
(10) Weakness: As an ensemble, the data points CANX as required for plasma membrane expression, particularly those that lie in the C-terminal domain, but when considering individual CF variants, there is no clear trend. Similarly, when looking at the effect of the pharmacological correctors on PME, no variant strays from the linear trend.
We generally agree that the predominant trend is a uniform decrease in CFTR PME across all variants and that individual variant effects are hard to generalize. Indeed, this latter point has been widely appreciated in the CF community for several decades. Our approach exposes this variability in detail, but we concede that we cannot yet fully interpret the full complexity of the trends.
(11) Something to consider: Knockout of calnexin, a central ER chaperone, is going to set off the UPR, which in turn will activate the ISR and attenuate translation. From what I can tell, in general, all CF variant PME is decreased. Is this simply because less CF protein is being synthesized?
The reviewer raises an excellent point. However, to investigate this possibility further, we compared whole-cell proteomic data for the parental and knockout cell lines. Our analysis suggests there is no significant upregulation of proteins associated with UPR activation, as is shown in the graphic to the right. In fact, only proteins associated with the PERK branch of the UPR exhibit any statistically significant changes between these two cell lines across three biological replicates. Based on this consideration, we suspect any wider changes in ER proteostasis must be relatively subtle.
Author response image 1.
What you’re doing: Turning one-off prompts into reusable systems.Once you’ve perfected a workflow, you have a proven recipe. Now you can decide how to operationalise it. There are three options:Create a Prompt Template when you want to use it regularly for personal reuse onlyBuild a Custom GPT or Bot when you want to share a task-specific workflow with a team for cross-team quality and efficiency gains Create an Automated Agent when you want to trigger the workflow automatically in certain conditions
How to create reusable systems
File format matters. Here’s the reliability ranking for how well AI reads different formats:.txt / .md — Minimal noise, clear structure (best)JSON / CSV — Great for structured dataDOCX — Fine if formatting is simpleDigital PDFs — Extraction can mix headers, footers, columnsPPTX — Text order can be unpredictableScanned PDFs / images — Worst; requires OCR, highly error-prone
How AI reads file formats and what they are good for
TLDR: When working with LLMs, the risks for the L&D workflow and its impact on substantive learning are real:Hallucination — LLMs invent plausible-sounding facts that aren’t trueDrift — LLM outputs wander from your brief without clear constraintsGeneric-ness — LLMs surface that which is most common, leading to homogenisation and standardisation of “mediocre”Mixed pedagogical quality — LLMs do not produce outputs which are guaranteed to follow evidence-based practiceMis-calibrated trust — LLMs invite us to read guesswork as dependable, factual knowledge These aren’t edge cases or occasional glitches—they’re inherent to how AI / all LLMs function. Prediction machines can’t verify truth. Pattern-matching can’t guarantee validity. Statistical likelihood doesn’t equal quality.
Real inherent issue using AI for learning.
Google’s LearnLM: an LLM built specifically to “fix” the pedagogical shortcomings of general LLMs and optimise AI’s performance in learning and education-related tasks (try it for yourself in Google’s AI Studio, here).
Google Learn LM
AI’s instructional design “expertise” is essentially a statistical blend of everything ever written about learning—expert and amateur, evidence-based and anecdotal, current and outdated. Without a structured approach, you’re gambling on which patterns the model draws from, with no guarantee of pedagogical validity or factual accuracy.
Issue with applying general LLMs to instructional design
quality of AI’s predictions depends ultimately on the data it’s been trained on -- i.e. the resources it’s been fed by those who built it.
Training data sets are critical to good results
Violet's Country Cottage
Lady Penelope and I spent time baking gingerbread biscuits in the kitchen today. Brains wanted to help, but questioned in advance the difference between gingerbread 'men' and gingerbread 'boys' and how boys actually become men through puberty in the process.
Introduction
Quick test
d Dynamic Balance
What is the definition of dynamic balance?
Stocks are the accumulations in a system, like the water in a pond, the money in a savings account, or the number of trained staff in an organization.
This could be more effective if we're focused on weaving the example we introduced above throughout (intentionally). ie, take out pond analogy, for example, Stocks are,..
Other examples of stocks include...
and Dynamic Balance
Do we need this second part of the title? the term Dynamic balance isn't used.
Let’s begin with a natural example: a pond.
This is conversational and uses an analogy. As someone 'learning' this, this is easy to understand and the visual adds to the learning experience here.
good tone, good analogy, good use of an image
What Makes a System Tick?
Consider not using headings for the intro/overview unless intro or overview?
Musikanski, L., Phillips, R., Bradbury, J, DeGraaf, J. & Bliss, C. L. (2021).
Remove authors and and publisher. Simple include the text title and the chapter number and title. When only one chapter, don't use a subbullet. Place title and chapter in main bullet. Chapter first?
For the exmplar, remove the text (stocks and flows) from the image. In general, we want to avoid this and this particular definition is phrased different from the one in the lesson.
one or more of these principles?
what principles does this refer to? Above the diagrams-there is reference to elements- below the diagram it talks about tools- the first paragraph talks about foundational concepts- so which is it?
analyzing supply chain emissions
go back to the pond. In order for this to follow through- it should use the same analogy every time.
the money in a savings account
it might make sense to just stick to the pond example and not add more to it.
The color line is a metaphor used to explain the assumptions people make about Black people. They think Black people do negative things because its a part of their nature.
Identity exists in the context of race, social class, gender, sexual orientation, language, culture, geography, physical ability, religion, and so much more
Disinterestedness – Scientists should focus on truth, not personal gain. That means putting curiosity and honesty above fame or money.
This is something that society struggles with as a whole so its no surprise science is affected by it. People are often motivated by the money or fame they can get rather than making decisions that not just benefit themselves or their company but also society. The idea of bettering for society instead of just for money is becoming a more popular idea again so hopefully we will soon see that reflected in the science industry.
What gets studied, how it’s studied, and whose voices are heard all depend on the world around us.
A great example of this is the space race. The world was competing to be the first on the moon. Many scientists joined the race while the people where helping to fund the tests and experiments. Because the world was focus on space so was science and because science was studying space the people wanted to help fund the science.
How do social values and beliefs shape the kind of research that gets done?
This is a very important question to be asking, and taking a look at history shows us why. During time periods where religion was the government science was viewed in a very poor light and thus little to no research was done. The more positive the society's view grew the more research was being done. Society and its view point on science greatly influence the scientific worlds ability to conduct research.
Global Prediction Summaries
For the platform, there are also other headers in this wireframe:https://suntheticsml.quarto.pub/platform_redesign_wireframe/modeling/explore-predictive-space.html
I don't have all the graphs from the platform, and some won't be shown for the automated report, so it is good to review these as well.
There are: Global Prediction Summaries, Single-Variable Exploration, Multi-Variable Exploration, and Interactive Predictions.
One of my favorite examples in the book is how temporal landmarks distort judgment. This is how we relate to time and how we use time to structure days, weeks, months, and years.
!
they help us make shortcuts in our decision-making processes that serve us well most of the time.
*
but details and the big picture aren’t always congruent.
We tend to downplay anything that seems distant, be it a future event or something happening to a stranger, and ignore its significance in our decision-making process.
Your decisionscape is the mental equivalent; it’s what you put into consideration, how you foreground and background things, and where you put the focus of your attention.
!
Artists use distance and diminution to draw big things in the foreground and small things in the background
? I don't know what diminution is and how it applies to the situation.
A decisionscape is the cognizant equivalent of an artist’s canvas.
*!
I set out to bring together insights from the arts that could help sharpen our understanding of why and how people make decisions, what they value, and how decision making manifests in our society.
*
oduction
this one is good overall- it feels more concise than the other 2 and to the point. I can confidently answer the 3 questions at the end and I don't even have to do any reading. :)
Lesson Reading
How do we feel about placement of the assigned reading associated with a lesson? In some courses, I see the reading listed at the top of the lesson, asking students to "Read Chap. XX to prepare for this lesson." Or does placement in the middle of lesson content work just as well?
Data scientists spend 60% of their time cleaning data instead of analyzing it.
Appreciate the callout boxes for these meta-cognitive prompts (e.g. real world examples, questions for thought, etc.). They set off this content nicely.
The Family Reunion
I LOVE this very basic, common analogy that everyone can understand. It really sets up the learner for success in comprehending rather technical, abstract "data quality" topics
Industry insight
this could be worded differently- and even expanded into a great example of a system. Pesticides are used- these consequences are happening plus more- if we add harm to bee populations and take that further to those consequences, it expands into a giant web of a system. This could tighten up the lesson a bit- but I think it does depend on if the focus is on sustainability or on systems thinking.
key concept is lag time
put this with the key concepts bulleted list of terms and definitions.
Sustainability
this could be removed- 2nd para-is also covered below in the section- why systems thinking matters…. this would include the disclaimer statement.
ystems?
What is the goal of this lesson? Is it about systems or is it about sustainability? I think it could be condensed a bit.
Disclaimer Statement All socio-political or company examples mentioned throughout this course should be considered appropriate illustrations of the associated points when this course was initially designed in mid-2025. Companies, institutions, and/or political entities that are the subject of these examples may or may not have continued the illustrated practices after that time period.
I wonder if this disclaimer statement should be included in all courses that reference real-world examples/events? Leah really liked it, and wanted it placed in both courses I was working on during Summer 2025
visualizing
In theory I like the idea of an actual visual for the concept, but I wouldn't use this one because the fine print is too small to be legible (to me, on my large monitor).
What happens when a large, powerful country like the United States backs out?
I've run into several instances when I wonder if content is too "political". How should we handle this, as a team?
Solution
There is mistake in the calculation of Kp for the net reaction. The calculation \(4.5\times 10^{15} / 0.28 \) gives \(1.6\times 10^{16}\)
Downloads Map
Not sure we need this page specifically for Downloads Map. Can we repurpose it? Maybe to be the page where "Share your Work in Purdue e-Pubs" links to? The map can be embedded at the bottom of that page. OR, we need a separate page for information about depositing works in Purdue e-Pubs.
muggles
I'm closer to being a mugle then being a high priest of a low cult. I have Software is practical magic you do not need to be a wizard. In fact nor being one is a distinct advantage. You can Prevents one to be dazzled by their own brilliance distracting seeing the true light of the adjacent impossible that cries out to be rendered inevitable
exploration
Exlprimence
Explore experiment Write to think to formulate the vision as you make The Indy Learning Commons Experience
Jisc open policy finder (formerly Sherpa services): Search this database for open end sharing. Search by publisher name or journal title. Addendum to Publication Agreements for BTAA Authors: This recommended addendum, created by the Big Ten Academic Alliance, allows authors to retain enough rights to their work to share the work on their institution’s repository after a period of six (6) months from the date of publication. Purdue Author Addendum Letter for Author Accepted Manuscript (AAM): This form letter to publishers requests permission to deposit the author accepted manuscript (AAM) before the article has been published. Even if you have already signed an author agreement, you still may be able to share your work. We can help determine if your work can be shared: send the author accepted manuscript and the citation of your work to epubs@purdue.edu. Purdue Author Addendum Letter Requesting Deposit of Author Accepted Manuscript (AAM): This form letter to publishers requests permission to deposit the author accepted manuscript (AAM) after the article has been published if the publisher does not allow sharing based upon SHERPA/RoMEO.
Would it be reasonable to put this information in a table? Left side = before publishing, Right side = after publishing. Before publishing = first three bullet points. After publishing = lower bullet point and Publication Eligibility Review Service (link to same page as "post your works to Purdue e-Pubs" link): Free service to Purdue community. Send a list of publications to epubs@purdue.edu, requesting a review. Staff review publisher sharing policies, check for eligible versions, create metadata records and post your works to Purdue e-Pubs.
Search this database for open end sharing.
Find author sharing policies for your target journal. Search by publisher name, journal title, or ISSN to discover details. Learn where your work can be shared and which version of the work can be shared.
Without due caution, authors can easily sign away valuable rights and significantly limit the accessibility of their works.
Publishing companies often require authors to assign all copyright of their works to the publisher as a requirement for publication. This is not always necessary. There are ways to negotiate retention of some author rights. Most publishers support author sharing policies. This allows faculty to retain certain rights to their works, such as sharing their works openly on an institutional repositiory, like Purdue e-Pubs. For more information on copyrights, visit the Purdue University Copyright Office (https://lib.purdue.edu/uco/).
Het plan van de Europese Unie ter waarde van 20 miljard euro om AI-gigafabrieken op te richten voor het opleiden van toonaangevende AI-modellen wordt geconfronteerd met aanzienlijke kritiek van branchegroepen met betrekking tot het doel en de financiële levensvatbaarheid ervan .
Hoewel de EU ernaar streeft haar AI-capaciteiten te versterken door middel van gigafabrieken, vragen belanghebbenden uit de sector over het algemeen om een meer gedefinieerde strategie, duidelijkere businesscases en meer overleg om het succes en de financiële levensvatbaarheid van het initiatief op lange termijn te waarborgen in een snel evoluerend en concurrerend wereldwijd AI-landschap.
eLife Assessment
This important study uses data from OpenAlex on more than 50 million journal articles in over 50,000 research journals to examine the dynamics of interdisciplinarity and international collaboration in research journals. The data analytics used to quantify disciplinary and national diversity are convincing, and support the claims that journals have become more diverse in both aspects. The revisions made by the authors have addressed the small number of concerns the reviewers had about the original version.
Reviewer #1 (Public review):
(1) Summary
The authors aim to explore how interdisciplinarity and internationalization-two increasingly prominent characteristics of scientific publishing-have evolved over the past century. By constructing entropy-based indices from a large-scale bibliometric dataset (OpenAlex), they examine both long-term trends and recent dynamics in these two dimensions across a selection of leading disciplinary and multidisciplinary journals. Their goal is to identify field-specific patterns and structural shifts that can inform our understanding of how science has become more globally collaborative and intellectually integrated.
(2) Strengths
The primary strengths of the paper remain its comprehensive temporal scope and use of a rich, openly available dataset covering over 56 million articles. The interdisciplinary and internationalization indices are well-founded and allow meaningful comparisons across fields and time. The revised manuscript has substantially improved in several aspects. In particular, the authors have clarified the methodology of trend estimation with a concrete example and justification of the 5-year window, making their approach much more transparent. They have also expanded the discussion of potential disparities in data coverage across disciplines and time, acknowledging limitations and implementing safeguards in their analysis. Furthermore, the manuscript has been carefully revised for grammar, clarity, and style, which improves its overall polish. While a sensitivity analysis might still further strengthen the robustness of findings, the revisions satisfactorily address the main methodological concerns raised in the initial review.
(3) Evaluation of Findings
The findings, such as the sharp rise in internationalization in fields like Physics and Biology, and the divergence in interdisciplinarity trends across disciplines, are clearly presented and better substantiated in the revised version. The authors now provide more discipline-specific discussion (e.g., medicine, biology, social sciences), which adds valuable nuance to the interpretation of internationalization dynamics. The improved methodological clarity and acknowledgment of data limitations enhance the credibility of the results and their generalizability.
(4) Impact and Relevance
This study continues to make a timely and meaningful contribution to scientometrics, sociology of science, and science policy. Its combination of scale, historical depth, and field-level comparison offers a useful framework for understanding changes in scientific publishing practices. The entropy-based indicators remain a simple yet flexible tool, and the expanded discussion of their appropriateness strengthens the methodological foundation. The use of open bibliometric data enhances reproducibility and accessibility for future research. Policymakers, journal editors, and researchers interested in publication dynamics will likely find this work informative, and its methods could be applied or extended to other structural dimensions of scholarly communication.
Reviewer #2 (Public review):
Summary:
This paper uses large-scale publication data to examine the dynamics of interdisciplinarity and international collaborations in research journals. The main finding is that interdisciplinarity and internationalism have been increasing over the past decades, especially in prestigious general science journals.
Strengths:
The paper uses a state-of-the-art large-scale publication database to examine the dynamics of interdisciplinarity and internationalism. The analyses span over a century and in major scientific fields in natural sciences, engineering, and social sciences. The study is well designed and has provided a range of robustness tests to enhance the main findings. The writing is clear and well organized.
Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public review):
However, some methodological choices, such as the use of a 5-year sliding window to compute trend values, are insufficiently justified and under-explained. The paper also does not fully address disparities in data coverage across disciplines and time, which may affect the reliability of historical comparisons. Finally, minor issues in grammar and clarity reduce the overall polish of the manuscript.
We thank the reviewer for pointing out the weakness of the manuscript. We addressed these comments in our response to Recommendations A and B. Minor grammar and clarity issues have also been addressed.
Reviewer #2 (Public review):
The first thing that comes to mind is the epistemic mechanism of the study. Why should there be a joint discussion combining internationalism and interdisciplinarity? While internationalism is the tendency to form multinational research teams to work on research projects, interdisciplinarity refers to the scope and focus of papers that draw inspiration from multiple fields. These concepts may both fall into the realm of diversity, but it remains unclear if there is any conceptual interplay that underlies the dynamics of their increase in research journals.
We thank the reviewer for pointing out the lack of clarity in our decision to conduct a joint discussion of interdisciplinarity and internationalization.
It is a well-known fact that team science has increased in importance over time. An important question then is whether teams have only grown in size and frequency or whether they have changed in other aspects. Interdisciplinarity and internationalization are two aspects in which teams could have changed.
We revised the Introduction (Lines 68–70 of the revised manuscript) to address this matter.
It is also unclear why internationalization is increasing. Although the authors have provided a few prominent examples in physics, such as CERN and LAGO, which are complex and expensive experimental facilities that demand collective efforts and investments from the global scientific community, whether some similar concerns or factors drive the growth of internationalism in other fields remains unknown. I can imagine that these concerns do not always apply in many fields, and the authors need to come up with some case studies in diverse fields with some sociological theory to support their empirical findings.
We thank the reviewer for requesting further evidence concerning why our findings may be correct. Physics is an area where the need for extraordinary resources has naturally led to large international collaborative efforts. As we discuss in line 255 of the revised manuscript, this is actually also the case for biology. The Human Genome Project and subsequent projects have also required massive investments, leading to further internationalization.
We believe that the drive toward internationalization for medicine has to do with the need for establishment of robust results that are not specific to a single country or medical system. Additionally, the impact of global epidemics — Acquired immunodeficiency Syndrome (AIDS), Severe Acute Respiratory Syndrome (SARS) — has also increased the needs to involve researchers from around the world.
The case for increased internationalization in the social sciences is, we believe, related to the desire to identify phenomena that extend beyond the Western, educated, industrialized, rich and democratic (WEIRD) societies.
We have expanded the discussion around these points in lines 274–283 of the revised manuscript.
The authors use Shannon entropy as a measure of diversity for both internationalism and interdisciplinarity. However, entropy may fail to account for the uneven correlations between fields, and the range of value chances when the number of categories changes. The science of science and scientometrics community has proposed a range of diversity indicators, such as the RaoStirling index and its derivatives. One obvious advantage of the RS index is that it explicitly accounts for the heterogeneous connections between fields, and the value ranges from 0 to 1. Using more state-of-the-art metrics to quantify interdisciplinarity may help strengthen the data analytics.
We thank the reviewer for pointing the need to provide a deeper discussion of the impact of different metrics on how disciplinary diversity is calculated. We chose Shannon’s entropy because it accounts for both richness (the number of distinct fields) and evenness (the balance of representation across fields). While measures such as the Rao-Stirling index can be very useful when considering disciplines at different levels of aggregation, since to consider only level 0 Field-of-Study (FoS) tags, that problem is not as much a concern for our analysis.
We have added a further clarification in lines 145–151 of the revised manuscript.
Reviewer #1 (Recommendations for the authors)
Ambiguity in the Trend Calculation Methodology in Figure 4 and 5
The manuscript uses a 5-year sliding window to calculate recent trends in interdisciplinarity (I<sub>d</sub>) and internationalization (I<sub>n</sub>), but the method is not clearly described. Could the authors clarify whether the trend is calculated by (1) performing linear regression on the index values over the past 5 years, (2) using the regression slope as the trend value, and (3) interpreting the sign and magnitude of the slope to indicate increasing, decreasing, or stable trends? Additionally, the rationale for choosing a 5-year window over other durations (e.g., 10 or 15 years) is not discussed. Given that different time windows could yield different insights, a brief justification or sensitivity check would strengthen the methodological transparency.
Thank you for pointing the lack of clarity in our description. In an attempt to increase clarity, we added a specific case study to illustrate the use of 5-year trend in the Supplementary Information: Estimation of tendency of the revised manuscript (Lines 691–704 of the revised manuscript).
Specifically, imagine we want to calculate the trend of the Interdisciplinarity Index for 2010 for Annalen der Physik. We would perform an ordinary least squares linear fit to the 6 data points for the Index in years 2005–2010.
The reason to focus on a 5-year window is two-fold. First, a longer time period would — as suggested by the data on Figure S10 — likely aggregate over multiple trends. Second, a shorter time period would result in too great an uncertainty in the estimation of the trend.
This is the reason why we did not implement a sensitivity analysis. Reasonable time windows that consider the two reasons expressed above would be too narrow to provide a worthwhile analysis.
Lack of Discussion on Temporal Coverage Disparities Across Disciplines
The study spans publications from 1900 to 2021, but the completeness and representativeness of the data-especially in earlier decades-may differ significantly across disciplines. For instance, OpenAlex has limited coverage for publications before the mid-20th century, and disciplines such as Medicine and Political Science may have adopted journal-based publishing at different historical periods compared to Physics or Chemistry. These temporal disparities could bias cross-disciplinary comparisons of long-term trends in interdisciplinarity and internationalization. I recommend that the authors briefly discuss this limitation and, if possible, report when coverage becomes reliable for each discipline. A sensitivity analysis starting from a common baseline year (e.g., 1950 or 1970) could also help assess whether the observed disciplinary differences are driven in part by unequal temporal data availability.
We thank the reviewer for the requesting further clarification on this matter. We completely agree that “completeness and representativeness of the data – especially in earlier decades-may differ significantly across disciplines”. That is exactly the reason why we made the analyses choices described in the manuscript.
Indeed, we consider only three journals for the analysis of the entire 1900–2021 period. Those 3 journals, Nature, PNAS and Science are ones that we know to be well recorded.
When conducting the disciplinary analysis, we focus on the period 1960–2021. While we know that the coverage for the social sciences is less robust until the 1990s, we address this concern by implementing several safeguards:
Manual selection of representative journals in each discipline to ensured that their publications are well represented in OpenAlex.
Decade by decade analysis of interdisciplinarity and internationalization so that changes over time can be identified and potential issues with data coverage are restricted to only some aspects of the analysis.
We also acknowledge the potential coverage disparities in earlier years of the data source (Lines 319-326 of the revised manuscript).
The authors use both interdisciplinarity and multidisciplinarity. While these concepts offer similar definitions of diversity, it may help the reader if there is some explanation to clarify their subtle differences. (Reviewer #2)
It is a well-known fact that team science has increased in importance over time. An important question then is whether teams have only grown in size and frequency or whether they have changed in other aspects. Interdisciplinarity and internationalization are two aspects in which teams could have changed.
We revised the Introduction (Lines 68–70 of the revised manuscript) to address this matter.
Minor Comments
Several sentences
(1) Line 11: The phrase “authors form multiple countries” contains a typographical error. The word “form” should be corrected to “from” so that the sentence reads: “authors from multiple countries.”
tences and phrases throughout the manuscript could be improved for grammatical accuracy, clarity, and stylistic appropriateness:
(2) Line 63: The clause “these expansion is well described by a logistic model” contains a subject-verb agreement error. “These” should be replaced by the singular demonstrative pronoun “this”, resulting in: “This expansion is well described by a logistic model.”
(3) Line 89: The phrase “were quickly overcame” misuses the verb form. “Overcame” is a past tense form and should be replaced with the past participle “overcome” to match the passive construction. Suggested revision: “were quickly overcome.”
(4) Line 106: The verb “refered” is misspelled. It should be corrected to “referred” for proper past tense. The corrected phrase should read: “we referred to...”
(5) Line 127: The phrase “sing discipline papers” contains a typographical error. “Sing” should be “single”, yielding: “single discipline papers.”
(6) Lines 238–239: The sentence “An exception to this pattern are the two mega open-access journals: PLOS One and Scientific Reports, which have internationalization indices as high the the most internationalized Physics journals.” contains multiple grammatical issues.
First, the subject “An exception” is singular, but the verb “are” is plural; this results in a subject-verb agreement error.
Second, the phrase “the the” includes a typographical repetition.
Third, the comparative construction is incomplete; “as high the the...” is ungrammatical and should use “as high as.”
Suggested revision: “An exception to this pattern is the pair of mega open-access journals— PLOS One and Scientific Reports—which have internationalization indices as high as those of the most internationalized Physics journals.”
(7) Line 254: The sentence “biological research been revolutionized...” lacks an auxiliary verb. To be grammatically correct, it should read: “biological research has been revolutionized...”
(8) Line 258: The phrase “need global spread of...” is syntactically awkward. Depending on the intended meaning, it could be revised to either “the global spread of...” or “the global need for the spread of...” for clarity.
(9) Figure S2 Caption: The term “Microsofe Academic Graph” is a typographical error and should be corrected to “Microsoft Academic Graph.”
(10) Reference [40]: The link “ttps://doi.org/10.1038/nature02168” is missing the “h” in “https.” The corrected version is: “https://doi.org/10.1038/nature02168.”
We appreciate your comments on the grammar and clarity of the manuscript. We have thoroughly reviewed and corrected these issues to improve the overall clarity of the text.
Line 11: We changed the typo “form” to “from”.
Line 63: We changed the sentence to “There has been a significant expansion in the number of countries where scientists are publishing in selective journals”.
Line 89 (Line 93 of the revised manuscript): We revised the sentence as suggested, and the revised sentence becomes “Even the significant impacts on publication rates of the two World Wars were quickly overcome, and exponential growth resumed. ”
Line 106 (Line 110 of the revised manuscript): We changed the typo “refered” to “referred”.
Line 127 (Line 131 of the revised manuscript): We changed the typo “Sing” to “single”.
Lines 238-239 (Lines 245-247 of the revised manuscript): We thank the issues pointed out by the reviewer, and we took the reviewer’s suggested version and changed the original sentence to “An exception to this pattern is the pair of mega open-access journals — PLOS One and Scientific Reports — which have internationalization indices as high as those of the most internationalized Physics journals”.
Line 254 (Line 262 of the revised manuscript): We added the auxiliary verb to the sentence, and the sentence now becomes “biological research has been revolutionized”
Line 258 (Line 266 of the revised manuscript): We changed the phrase to “the global need for the spread of”.
Figure S2 Caption: We corrected the typo of “Microsoft Academic Graph”.
Reference [40]: We corrected the URL of the reference.
Reviewer #2 (Recommendations for author):
Some typos:
(1) Page 2: On page 2, “contributions from a multiple disciplines” and ”these expansion is well described”.
(2) Page 4: “World Wars were quickly overcame”.
(3) Page 5: “to quantify the the internationalization of a journal”.
(4) Page 10: “indices as high the the most internationalized Physics journals”
(5) Page 10: The sentence “indices as high the the most internationalized Physics journals” contains multiple issues. The phrase “the the” is a typographical error, and the comparative construction is incomplete. It should be revised to: “indices as high as those of the most internationalized Physics journals.”
We revised those typographical errors on page 2, 4, 5, and 10 pointed out by the reviewer. We truly thank the reviewer’s critical examination on the syntax of the manuscript.
Page 2: We removed “a” so now the sentence reads: “contributions from multiple disciplines.”
Page 2: We changed the sentence to “There has been a significant expansion in the number of countries where scientists are publishing in selective journals”.
Page 4: We replaced “overcame” with the past participle “overcome” , resulting in: “World Wars were quickly overcome.”
Page 5: The phrase “to quantify the the internationalization of a journal” contains a typographical repetition. We changed it to: “to quantify the internationalization of a journal.”
Page 10: For the sentence “indices as high the the most internationalized Physics journals”, we removed duplicated “the” as a typographical error. We revised the sentence into: “indices as high as those of the most internationalized Physics journals.”
The clear hidden wink and nudge is “clearly this means she’s obviously 100% a plant from that side!” What else was said in that speech? Maybe show a whole 3-4 minutes? But that would be boring and you can’t do the whole show a fast snip and then wink wink at your audience about “aha but we all know what this really means don’t we folks!
/u/Choperollo describes something for which we have no name and would not be accurately described as a dogwhistle but still shares some similarities and is now common/prevalent enough that we would perhaps benefit from being able to refer to it by name to discuss it.
Benjamin explains that the sociotechnical imaginary is not just about revealing “how the technical andsocial components of design are intertwined, but also imagines how they might be configureddifferently.”
Design is also practice, it's a step in-between theory and application. It's about understanding logistics from the inside without causing real havoc or backfire. It's about learning to predict, to see the holes and gaps that may arise before they do. Design, at the end, is about bridging the theory-application divide. It helps solidfy theories while seeing their limitations in a safe space, dispelling the myth of sudden talent (from an illusion of explanatory depth), and warning against creeping normality by remaining revisionist (iterating) through the practice.
eLife Assessment
The authors investigated the potential role of IgG N-glycosylation in Haemorrhagic Fever with Renal Syndrome (HFRS), which may offer significant insights for understanding molecular mechanisms and for the development of therapeutic strategies for this infectious disease. The findings are thought to be valuable to the field and the strength of evidence to support the findings is solid.
Reviewer #1 (Public review):
Summary:
The authors investigated the potential role of IgG N-glycosylation in Haemorrhagic Fever with Renal Syndrome (HFRS), which may offer significant insights for understanding molecular mechanisms and for the development of therapeutic strategies for this infectious disease.
Comments on revisions:
While the majority of the issues have been addressed, a few minor points still remain unresolved.
Quality control should be conducted prior to the analysis of clinical samples. However, the coefficient of variation (CV) value was not provided for the paired acute and convalescent-phase samples from 65 confirmed HFRS patients, which were analyzed to assess inter-individual biological variability. It is important to note that biological replication should be evaluated using general samples, such as standard serum.
Reviewer #2 (Public review):
This work sought to explore antibody responses in the context of hemorrhagic fever with renal syndrome (HFRS) - a severe disease caused by Hantaan virus infection. Little is known about the characteristics or functional relevance of IgG Fc glycosylation in HFRS. To address this gap, the authors analyzed samples from 65 patients with HFRS spanning the acute and convalescent phases of disease via IgG Fc glycan analysis, scRNAseq, and flow cytometry. The authors observed changes in Fc glycosylation (increased fucosylation and decreased bisection) coinciding with a 4-fold or greater increased in Haantan virus-specific antibody titer. The study also includes exploratory analyses linking IgG glycan profiles to glycosylation-related gene expression in distinct B cell subsets, using single-cell transcriptomics. Overall, this is an interesting study that combines serological profiling with transcriptomic data to shed light on humoral immune responses in an underexplored infectious disease. The integration of Fc glycosylation data with single-cell transcriptomic data is a strength.
The authors have addressed the major concerns from the initial review. However, one point to emphasize is that the data are correlative. While the associations between Fc glycosylation changes and recovery are intriguing, the evidence does not establish causation. This is not a weakness, as correlative studies can still be highly valuable and informative. However, the manuscript would be strengthened by making this distinction clear, particularly in the title.
Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public review):
(1) The authors should provide a detailed description of the pathogenesis of Haemorrhagic Fever with Renal Syndrome (HFRS) and elaborate on the crucial role of IgG proteins in the disease's progression (line 65).
As suggested, we have now provided a detailed description of the pathogenesis of HFRS and elaborated on the crucial role of IgG proteins in the disease's progression:
"Hantaviruses are tri-segmented, single-stranded, negative-sense RNA viruses, whose genomes consist of three regions: large (L), medium (M), and small (S). The glycoproteins Gn and Gc, encoded by the M segment, can infect target cells - primarily vascular endothelial cells - via β3 integrin receptors (Pizarro et al., 2019). Simultaneously, they could also infect other cell types, such as mononuclear macrophages and dendritic cells, leading to systemic viral infection. Although hantavirus replication is thought to occur primarily in the vascular endothelium without direct cytopathic effects, a plethora of innate immune cells mediate host antiviral defenses. These include natural killer cells, neutrophils, monocytes, and macrophages, together with pattern recognition receptors (PRRs), interferons (IFNs), antiviral proteins, and complement activation, e.g., via the pentraxin 3 (PTX3) pathway, which can exacerbate HFRS disease progression leading to immunopathological damage through cytokine/chemokine production, cytoskeletal rearrangements in endothelial cells, ultimately amplifying vascular dysfunction (Tariq & Kim, 2022). Rapid and effective humoral immune responses, however, such as neutralizing antibody responses targeting the glycoproteins Gn/Gc, contribute to rapid recovery from HFRS and are critical for protection from severe disease (Engdahl & Crowe, 2020; Li et al., 2020)." Please see the Introduction (Page 4, lines 65-81).
(2) An additional discussion on the significance of glycosylation, particularly IgG N-glycosylation, in viral infections should be included in the Introduction section.
Thank you for the suggestion and we have added an additional discussion on the significance of glycosylation in viral infections in the revised Introduction section.
"Immunoglobulin G (IgG) N-linked glycosylation mediates critical functions modulating antiviral immunity during viral infection. Changes in the conserved N-linked glycan Asn297 in the Fc region of IgG typically by fucosylation, galactosylation, or sialylation can alter antibody effector function. A reduction in core fucosylation decreases IgG binding to NK cell FcγRIIIa promotes antibody-dependent cellular cytotoxicity (ADCC) necessary for clearance of viruses, including SARS-CoV-2, dengue and HIV-1 whereas sialylation can attenuate immune responses resulting in immune evasion (Ash et al., 2022; Haslund-Gourley et al., 2024; Hou et al., 2021; Wang et al., 2017). Changes in IgG and other protein N-linked glycosylation profiles therefore shape virus-host interactions and disease progression." (Page 4, lines 82-91).
(3) In the abstract section, the authors state that HTNV-specific IgG antibody titers were detected and IgG N-glycosylation was analyzed. However, the analysis of plasma IgG N-glycans is described in the Methods section. Therefore, the authors should clarify the glycome analysis process. Was the specific IgG glycome profile similar to the total IgG N-glycome? Given the biological relevance of specific IgG in immunological diseases, characterizing the specific IgG N-glycome profile would be more significant than analyzing the total plasma IgG.
We are grateful to the reviewer for the comments. Previous studies on viral infections have revealed that the pattern of virus-specific IgG N-glycans may be similar to that of total IgG N-glycome, and we therefore analyzed the total plasma IgG glycosylation profiling in the HFRS patients. However, we have discussed this in the Discussion section.
"Despite establishing a well-characterized patient cohort and performing systematic IgG glycosylation profiling based on HTNV NP antibody status, this study has several noteworthy limitations. Most notably, while preliminary comparisons suggested similar patterns between virus-specific and total IgG N-glycome, our total plasma IgG analysis may have introduced confounding factors in the observed associations. This methodological constraint could potentially affect the interpretation of certain disease-specific glycosylation signatures." Please see the Discussion (Page 12, lines 274-280).
References
(1) Mads Delbo Larsen, Erik L de Graaf, Myrthe E Sonneveld, et al. Afucosylated IgG characterizes enveloped viral responses and correlates with COVID-19 severity. Science . 2021 Feb 26;371(6532):eabc8378.
(2) Chakraborty S, Gonzalez J, Edwards K, et al. Proinflammatory IgG Fc structures in patients with severe COVID-19. Nat Immunol. 2021 Jan;22(1):67-73.
(3) Tea Petrović, Amrita Vijay, Frano Vučković, et al. IgG N-glycome changes during the course of severe COVID-19: An observational study. EBioMedicine. 2022 Jul ;81: 104101.
(4) Hou H, Yang H, Liu P, et al. Profile of Immunoglobulin G N-Glycome in COVID-19 Patients: A Case-Control Study. Front Immunol. 2021 Sep 23;12:748566.
(4) Further details regarding the N-glycome analysis should be provided, including the quantity of IgG protein used and the methodology employed for analyzing IgG N-glycans (lines 286-287).
As suggested, we have provided further details regarding the N-glycome analysis in the Method section.
"Briefly, the diluted plasma samples were transferred onto a 96-well protein G monolithic plate (BIA Separations, Slovenia) for the isolation of IgG. The isolated IgG was eluted with 1 mL of 0.1 M formic acid and was immediately neutralized with 170 µL of 1M ammonium bicarbonate.
The released N-glycans were labelled with 2-aminobenzamide (2-AB) and were then purified from a mixture of 100% acetonitrile and ultrapure water in a 1:1 ratio (v/v). This was then analyzed by hydrophilic interaction liquid chromatography using ultra-performance liquid chromatography (HILIC-UPLC; Walters Corporation, Milford, MA) (Hou et al., 2019). As previously reported, the chromatograms were separated into 24 IgG glycan peaks (GPs) (Menni et al., 2018)." Please see the Method section (Page 15, lines 346-355).
(5) Additional statistical analyses should be performed, including multiple comparisons with p-value adjustment, false discovery rate (FDR) control, and Pearson correlation (line 291).
As suggested, we have performed additional statistical analyses and mentioned the results in the revised manuscript.
"Positive correlations were observed between the ASM subsets and both galactosylation (p=0.017, r<sub>s</sub>=0.418) and sialylation (p=0.008, r<sub>s</sub>=0.458) in the antibody Fc region, as well as between the PB subsets and sialylation (p=0.036, r<sub>s</sub>=0.372) (Figure 4A-C). (Page 8, lines 180-183)"
"The Benjamini - Hochberg (BH) method was used to adjust the raw p-values from DEG analysis, controlling the false discovery rate (FDR)." Please see the Materials and Methods (Page 16, lines 369-371).
(6) Quality control should be conducted prior to the IgG N-glycome analysis. Additionally, both biological and technical replicates are essential to assess the reproducibility and robustness of the methods.
Thank you for the suggestion. We have added descriptions on the biological and technical replicates in the Method section.
"Our study incorporated both biological and technical replicates to ensure a robust glycomic profiling analysis. Specifically, we analyzed paired acute/convalescent-phase samples from 65 confirmed HFRS patients to assess inter-individual biological variability, while technical reproducibility was validated through comparison with standard chromatographic peak plots (Vučković et al., 2016). This dual-replicate strategy enabled a comprehensive evaluation of both biological heterogeneity and assay precision." (Page 15, lines 356-362).
(7) Multiple regression analysis should be conducted to evaluate the influence of genetic and environmental factors on the IgG N-glycome.
As suggested, we have conducted multiple regression analysis to evaluate the influence of genetic and environmental factors on the IgG N-glycome. These results have been provided in the revised Result section.
"Multivariate linear regression was employed to mitigate potential confounding by genetic and environmental factors in the glycomics analysis. While no significant associations were observed for most glycan models (fucosylation, p=0.526; bisecting GlcNAc, p=0.069; and sialylation, p=0.058), we discovered sex showed a potentially influential effect on galactosylation (p=0.001) (Supplementary files 5-8). These results suggest that while most glycan features appear unaffected by the examined covariates, galactosylation may be subject to sex-specific biological regulation." (Page 7, lines 153-160).
(8) Line 196. Additional discussions should be included, focusing on the underlying correlation between the differential expression of B-cell glycogenes and the dysregulated IgG N-glycome profile, as well as the potential molecular mechanisms of IgG N-glycosylation in the development of HFRS.
Thank you for your suggestions. We have added these contents in the Discussion section.
"Antibody-related glycogenes are significantly activated following Hantaan virus infection. We noted that ribophorin I and II (RPN1 and RPN2) were significantly upregulated in the ASM/IM/PB/RM subsets after Hantaan virus infection, which linked the high mannose oligosaccharides with asparagine residues found in the Asn-X-Ser/Thr consensus motif (Hwang et al., 2025). We speculate that they continuously attach the synthesized glycan chains to the constant region of antibodies during antibody synthesis. Similarly, fucosyltransferase 8 (FUT8) in the ASM subset, catalyzing the alpha1-2, alpha1-3, and alpha1-4 fucose addition (Wang & Ravetch, 2019; Yang et al., 2015), was downregulated in the mRNA translation, and the levels of fucosylated antibodies were naturally lower in the acute HFRS patients. Meanwhile, the beta-1,4-galactosyltransferase (beta4GalT) gene expression was significantly elevated in the ASM subpopulation during the acute phase, which also correlated with increased levels of galactosylated antibodies in serum (Wang & Ravetch, 2019). However, we did not observe significant upward changes in sialyltransferase mRNA expression in the acute HFRS patients, similar with the finding from severe COVID-19 cohorts (Haslund-Gourley et al., 2024). The neuraminidase 1 (NEU1) gene is strikingly upregulated and may potentially explain the decreased sialylation on the secreted HTNV-specific IgG antibodies during convalescence. Overall, the glycosylation of immunoglobulin G is regulated by a large network of B-cell glycogenes during HTNV infection." Please see the Discussion (Page 11, lines 254-273).
Reviewer #2 (Public review):
(1) While it is great to reference prior publications in the Materials and Methods section, the current level of detail is insufficient to clearly understand the study design and experimental procedures performed. Readers should not be expected to consult multiple previous papers to grasp the core methodological aspects of the present paper. For instance, the categorization of HFRS patients into different clinical subtypes/ courses, and the methods for measuring Fc glycosylation should be explicitly described in the Materials and Methods section of this manuscript.
Many thanks for your comments. We have added more details regarding the study design and experimental procedures in the Materials and Methods section. "Clinical specimens were collected from HFRS patients who were hospitalized in Baoji Central Hospital between October 2019 and January 2022. Patients were categorized into four clinical subtypes (mild, moderate, severe, and critical) based on the diagnostic criteria for HFRS issued by the Ministry of Health (Ma et al., 2015). This study was approved by the ethics committee of the Shandong First Medical University & Shandong Academy of Medical Sciences (R201937). Written informed consent was obtained from each participant or their guardians.
The clinical course of HFRS is grouped into acute (febrile, hypotensive, and oliguric stages) and convalescent (diuretic and convalescent stages) phases. The acute phase was defined as within 12 days of illness onset, and the convalescent phase was defined as a period of illness lasting 13 days or longer (Tang et al., 2019; Zhang et al., 2022). The earliest sample was selected if there were multiple blood samples available in the acute phase and the last available sample before discharge was selected if there were multiple blood samples in the convalescent phase.
Briefly, the diluted plasma samples were transferred onto a 96-well protein G monolithic plate (BIA Separations, Slovenia) for the isolation of IgG. The isolated IgG was eluted with 1 mL of 0.1 M formic acid and was immediately neutralized with 170 µL of 1M ammonium bicarbonate.
The released N-glycans were labelled with 2-aminobenzamide (2-AB) and were then purified from a mixture of 100% acetonitrile and ultrapure water in a 1:1 ratio (v/v). This was then analyzed by hydrophilic interaction liquid chromatography using ultra-performance liquid chromatography (HILIC-UPLC; Walters Corporation, Milford, MA) (Hou et al., 2019). As previously reported, the chromatograms were separated into 24 IgG glycan peaks (GPs) (Menni et al., 2018)." Please see the Materials and Methods (Page 13, lines 290-303, and Page 15, lines 346-355).
(2) The authors should explain the nature of their cohort in a bit more detail. While it appears that HFRS cases were identified based on IgM ELISA and/or PCR, these are indicators of the Haantan virus infection. My understanding is that not all Haantan virus infections progress to HFRS. Thus, it is unclear whether all patients in the HFRS group actually had hemorrhagic fever. This distinction is critical for interpreting how the results observed relate to disease severity.
We are sincerely grateful for this valuable suggestion. We have carefully revised Figure 1 and the texts (Page 5, lines 104-107) in the revised manuscript.
"To characterize the humoral immune profiles in HFRS patients, we enrolled 166 suspected HTNV-infected patients who were admitted to Baoji Central Hospital in Shaanxi Province, China, between October 2019 and January 2022. Among them, 65 met the inclusion criteria and were included in the study (Figure 1)."
(3) The authors state that: "A 4-fold or greater increase in HTNV-NP-specific antibody titers usually indicates a protective humoral immune response during the acute phase", but they do not cite any references or provide any context that supports this claim. Given that in their own words, one of the most significant findings in the study is changes in glycosylation coinciding with this 4-fold increase, it is important to ground this claim in evidence. Without this, the use of a 4-fold threshold appears arbitrary and weakens the rationale for using this immune state as a proxy for protective immunity.
Thank you for the suggestion and we have provided relevant references in the Results section (Page 8, lines 171-173).
According to the Expert Consensus on Prevention and Treatment of Hemorrhagic Fever with Renal Syndrome (HFRS) (https://ts-cms.jundaodsj.com/file/163823638693909.pdf), a confirmed diagnosis requires, based on a suspected or clinical diagnosis, one of the following: positive serum-specific IgM antibodies, detection of Hantavirus RNA in patient specimens, a four-fold or greater rise in titer of serum-specific IgG antibodies in the convalescent phase compared to the acute phase, or isolation of Hantavirus from patient specimens. A four-fold or greater rise in titer of convalescent serum-specific IgG antibodies compared to the acute phase not only suggests a recent Hantaan virus infection, but also the production of antibodies helping to combat the viral infection. In addition, the antibody glycosylation modifications may thus play a significant role in the antiviral immune response.
(4) The authors also claim that changes in Fc glycosylation influence recovery from HFRS - a point even emphasized in the manuscript title. However, this conclusion is not well supported by the data for two main reasons. First, the authors appear to measure bulk IgG Fc glycans, not Fc glycans of Hantaan virus-specific antibodies. While reasonable, this is something that should be communicated in the manuscript. Hantaan virus-specific antibodies are likely a very small fraction of total circulating IgG antibodies (perhaps ~1%), even during acute infection. As a result, changes in bulk Fc glycosylation may (or may not) accurately reflect the glycosylation state of Hantaan virus-specific antibodies. Second, even if the bulk Fc glycan shifts do mirror those of Hantaan virus-specific antibodies, it remains unclear whether these changes causally drive recovery or are merely a consequence of the infection being resolved. Thus, while the differences in Fc glycosylation observed are interesting - and it is tempting to speculate on their functional significance - the manuscript treats the observed correlations as causal mechanistic insight without sufficient data or justification.
Thank you for your valuable comments. This study measured bulk IgG Fc glycans, not Fc glycans of Hantaan virus-specific antibodies. We have described this limitation in the Discussion section (Page 12, lines 274-280). As reported in previous studies (references provided below), the changed pattern of virus-specific IgG N-glycans may reflect the total IgG N-glycome. Nevertheless, more studies are clearly needed to directly measure virus-specific IgGs and to clarify the causal mechanistic insights.
References
(1) Mads Delbo Larsen, Erik L de Graaf, Myrthe E Sonneveld, et al. Afucosylated IgG characterizes enveloped viral responses and correlates with COVID-19 severity. Science. 2021 Feb 26;371(6532): eabc8378.
(2) Chakraborty S, Gonzalez J, Edwards K, et al. Proinflammatory IgG Fc structures in patients with severe COVID-19. Nat Immunol. 2021 Jan;22(1):67-73.
(3) Tea Petrović, Amrita Vijay, Frano Vučković, et al. IgG N-glycome changes during the course of severe COVID-19: An observational study. EBioMedicine. 2022 Jul ;81: 104101.
(4) Hou H, Yang H, Liu P, et al. Profile of Immunoglobulin G N-Glycome in COVID-19 Patients: A Case-Control Study. Front Immunol. 2021 Sep 23;12: 748566.
(5) Fc glycosylation is known to be influenced by covariates such as age and sex. While it is helpful that the authors stratified the patients by age group and looked for significant differences in glycosylation across them, a more robust approach would be to directly control for these covariates in the statistical analysis - such as by using a linear mixed effects model, in which disease state (e.g., acute vs. convalescent), age, and sex are treated as fixed effects, and subject ID is included as a random effect to account for repeated measures. This would allow the authors to assess whether observed differences in Fc glycosylation remain significant after accounting for potential confounders. This could be important given that some of the reported differences are quite small, for example, 94.29% vs. 94.89% fucosylation.
Thank you for your valuable suggestion. As suggested, we have conducted multiple regression analysis to evaluate the influence of genetic and environmental factors on the IgG N-glycome, and have provided these results in the revised Result section.
"Multivariate linear regression was employed to mitigate potential confounding by genetic and environmental factors in the glycomics analysis. While no significant associations were observed for most glycan models (fucosylation, p=0.526; bisecting GlcNAc, p=0.069; and sialylation, p=0.058), we discovered sex showed a potentially influential effect on galactosylation (p=0.001) (Supplementary files 5-8). These results suggest that while most glycan features appear unaffected by the examined covariates, galactosylation may be subject to sex-specific biological regulation." (Page 7, lines 153-160).
(6) The manuscript states that there are limited studies on antibody glycosylation in the context of HFRS, but does not cite any relevant literature. If prior work exists, it should be cited to contextualize the current study. If no prior studies have been conducted/reported, to the author's knowledge, that should be stated explicitly to show the novelty of the work.
Thank you for your suggestion. To our knowledge, there has been no prior reports regarding the regulation of IgG glycosylation in HFRS, particularly in relation to seroconversion. We have reworded this sentence in the revised manuscript. "Importantly, there have not been prior studies specifically examining plasma IgG N-glycome profiles derived from chromatographic peak data in HFRS patients, particularly in relation to seroconversion status. This gap in our knowledge motivated our systematic investigation of both total and virus-specific IgG glycosylation dynamics during acute infection." Please see the Introduction (Page 5, lines 92-96).
Reviewer #2 (Recommendations for the authors):
Minor points:
(1) Line 47, 78: The use of the word 'However' appears to be an incorrect expression.
We have made this correction.
(2) Line 127: The term 'glycome' should be replaced with 'N-glycome,' and all relevant expressions should be corrected accordingly, such as 'N-glycosylation.
We have made this correction.
(3) Line 84-87: The sentence 'A total of 166 HFRS patients...' contains a grammatical error.
We have made tis correction (Page 5, lines 99-101).
o the topic and as a brief,
change
"I think, therefore I am
will 100% be on the test
eLife Assessment
This study addresses an important question in liver biology: how zonal hepatocytes balance survival and proliferation following injury; using spatial transcriptomics, mechanistic perturbations, and functional assays, the authors propose that a mid-zone Atf4-Chop axis to Btg2 program temporarily suppresses proliferation to promote survival during APAP-induced hepatotoxicity. The idea that distinct intrahepatic zones mount tailored stress responses is conceptually significant and has implications for regeneration and toxicology. The dataset is rich and the methodology modern, but several conclusions rely on assumptions about zonation under injury, limited injury models, and incomplete functional validation of the Atf4-Chop-Btg2 axis. With targeted revisions and additional experiments, the work has the potential to provide strong mechanistic insights into liver zonation and injury responses.
Reviewer #1 (Public review):
Summary:
The authors present evidence that during acetaminophen (APAP)-induced liver injury, mid-zone hepatocytes activate an integrated stress response (ISR) program via Atf4 and Chop, leading to induction of Btg2. This program suppresses proliferation in the early phase of injury, prioritizing hepatocyte survival before regeneration begins. The study uses spatial transcriptomics, immunohistochemistry, CUT&RUN, and AAV overexpression to support this model.
Strengths:
(1) Innovative use of spatial transcriptomics to capture zonal differences in hepatocyte stress responses.
(2) Identification of a mid-zone specific ISR signature and candidate downstream regulator Btg2.
(3) Functional experiments with Atf4-Chop-Btg2 modulation provide causal evidence linking ISR activation to proliferation inhibition.
(4) Conceptually significant model that hepatocytes actively balance survival and regeneration dynamically in a zone-specific manner.
Weaknesses:
(1) Zonation definition under injury has been shown to be sustained broadly, but is not sufficiently validated and quantified, especially considering the resolution of the 10x Visium system and the potential variation of outcomes based on how to define zones.
(2) The model is built entirely in APAP injury, which specifically targets pericentral hepatocytes. It remains unclear whether the proposed mechanism applies to other liver injuries (e.g., partial hepatectomy, CCl4).
(3) Baseline proliferation appears higher than expected in homeostasis (Figure 1B), and fold change analysis (not absolute counts) may be needed to assess zonal proliferation suppression (Figure 1D).
(4) AAV-based overexpression raises potential confounds (altered CYP activity before injury) and shows incomplete penetrance that is not quantified. (Figure 5 - Figure 6).
(5) The functional link between proliferation suppression and improved survival is inferred, but direct survival /injury readouts are limited.
Reviewer #2 (Public review):
The manuscript reports protection of midlobular hepatocytes from APAP toxicity by activation of Atf4-CHOP (Ddit3)-mediated cell cycle arrest and stress response. The authors acknowledge that their finding is unexpected because CHOP typically induces cell death. Therefore, they functionally validate several aspects of the proposed Atf4-CHOP mechanism. Along these lines, the mitigation of APAP toxicity by AAV expression of Atf4 or Btg2, the latter identified as CHOP effector, is impressive. Whether Atf4 indeed acts through CHOP and whether midlobular hepatocytes are protected because of cell cycle arrest is less clear. These and other criticisms are described in the following.
Major points:
(1) Starting with the basics, one wonders why midlobular hepatocytes manage to mount a defensive response to APAP but pericentral hepatocytes don't. Is this because midlobular hepatocytes express the relevant Cyps (2e1, but also 1a2 and 3a11) at lower levels, which mitigates toxicity and buys them time? This would be supported by F2A but not by F3B, at least not for the most important Cyp2e1. A moderate difference is shown for Cyp1a2 expression in F3D, but is that enough to explain the different fates? Or are additional post-transcriptional effects on these Cyps at work?
(2) The evidence presented in support of cell cycle arrest of midlobular hepatocytes is not fully convincing: there is no overt difference in S and G2/M gene scores in F2F; the marker genes used for S phase and G1 to S progression in F2G are unusual. Along these lines, one wonders if spatial transcriptomics confirmed the Ki67 immunostaining results in F1 also for specific zones, not only overall, as shown in F2E?
(3) The authors conclude in line 364 that halting of proliferation by Btg2 favors survival, which raises the question of whether Btg2 knockout causes death in midlobular hepatocytes in F6K. Data addressing this question, that is, the localization and extent of tissue necrosis and ALT levels after APAP, are missing. The efficiency of the knockout of Btg2 is also not given.
(4) Related to the previous question, the BTG2 immunostaining in F6F is not convincing when compared to F6D. One also wonders if it is necessary to apply APAP to find induction of BTG2 by AAV-Ddit3?
(5) Related to the previous question, the proposed Atf4-Ddit3 axis is challenged by the lack of midlobular induction of Atf4 in the APAP scRNA-seq data published by another group, presented in S4F and G. Further analysis of AAV-Atf4 samples generated for F5 could address whether it is really Atf4 that acts on Ddit3 in APAP toxicity.
(6) Related to the previous question, the ATF4 immunostaining in F5A doesn't look convincing, with many brown pigments appearing to be outside of the nucleus.
(7) It is not ruled out that AAV expression of Atf4 or Btg2 reduces hepatocyte sensitivity to APAP by affecting the expression of the Cyps needed for activation. In other words, does AAV-Atf4 or AAV-Btg2 change the expression of any of the Cyps relevant to APAP in the 3 weeks before APAP application (F5B)?
(8) It is laudable that the authors tried to extend their findings to humans by using snRNA-seq data from a published study (line 391), but it is unclear why they didn't analyze all 10 patients in that study but instead focused on 2 and stated that this small sample number prevented drawing definitive conclusions and could therefore only be mentioned in the discussion.
Reviewer #3 (Public review):
Summary:
This paper by Zhu et al explores zonal gene expression changes and stress responses in the liver after APAP injury. 3-6 hours after APAP, zone 2 hepatocytes demonstrate important gene expression changes. There is an increase in stress response/cell survival genes such as Hmox1, Hspa8, Atf3, and protein degradation/autophagy genes such as Ubb, Ubc, and Sqstm1. This is hypothesized to be a "stress adaption" which happens during the initial phases of acute liver injury. Furthermore, there is a spatial redistribution of Cyp450 expression that then establishes the Mid-zone as the primary site of APAP metabolism during early AILI. This particular finding was identified previously by other groups in several single-cell papers. Ddit3 (Chop) expression also increases in zone 2. The authors focused mostly on the Atf4-Ddit3 axis in stress adaptation. Importantly, they probe the functionality of this axis by overexpressing either ATF4 or DDIT3 using AAV tools, and they show that these manipulations block APAP-induced injury and necrosis. This is somewhat convincing evidence that these stress response proteins are probably important during injury and regeneration.
Strengths:
Overall, I think this is a useful study, showing that the Mid-lobular zone 2 hepatocytes turn on a stress-responsive gene program that suppresses proliferation, and that this is functionally important for efficient, long-term regeneration and homeostasis. This adds to the body of literature showing the importance of zone 2 cells in hepatic regeneration, and also provides an additional mechanism that tells us how they are better at surviving chemical injuries.
Weaknesses:
The main concern is that the overexpression of ATF4 and DDIT3 is causing reduced cell death and damage by APAP. This makes it harder to understand if these genes are truly increasing survival or if they are just reducing the injury caused by APAP. It may be better to perform overexpression immediately after, or at the same time as APAP delivery. Alternatively, loss-of-function experiments using AAV-shRNAs against these targets could be useful.
eLife Assessment
This study presents an important finding by identifying OPG as a novel stromal checkpoint influencing T-cell anti-tumor responses, thereby shedding new light on the complex interplay between the tumor microenvironment and immune regulation. The data are robust and the experimental approaches are sound, providing solid support for the study's conclusions; however, there are a number of additional questions raised by the data. Of particular note are the questions raised on the mechanistic effects of TRAIL versus RANKL. In addition, it would broaden the interest in this study to include more translational human data to complement the work presented.
Reviewer #1 (Public review):
Summary:
Wang et al. present a compelling study investigating a novel immunosuppressive mechanism within the tumor microenvironment (TME) mediated by a subset of cancer-associated fibroblasts (CAFs)-specifically, inflammatory CAFs (iCAFs) that secrete osteoprotegerin (OPG). Utilizing both genetic and antibody-mediated OPG inhibition in murine breast and pancreatic cancer models, the authors demonstrate that blocking OPG enhances infiltration and effector function of cytotoxic T cells, which leads to significant tumor regression. Their data further show that OPG blockade induces a population of IFN-licensed CAFs characterized by increased expression of antigen presentation genes and immunomodulatory properties that favour T cell infiltration. The manuscript proposes that OPG functions as a "stromal immune checkpoint" and could represent a promising therapeutic target to convert "cold" tumors into "hot," immunotherapy-responsive tumours.
Strengths:
(1) Novel role for OPG+ CAF as T-cell immune suppressors:<br /> This study introduces a novel role for OPG+ iCAFs as active suppressors of T cell function and highlights stromal OPG as a critical negative regulator of antitumor immunity.
(2) Methodological Rigor:<br /> The manuscript is underpinned by a thorough and systematic experimental design, combining genetic mouse models, antibody interventions, in vitro functional assays, single-cell RNA-seq, and human RAN-seq datasets analyses.
(3) Translational Relevance:<br /> By identifying OPG as a stromal immune checkpoint, the study opens exciting opportunities for developing new immunotherapeutic strategies in stromatogenic tumors.
(4) Clear and Comprehensive Data Presentation:<br /> The use of high-dimensional single-cell technologies and logical, detailed data presentation supports the study's reproducibility and transparency.
Weaknesses:
(1) The manuscript lacks definitive data identifying the cellular origin of OPG, particularly establishing iCAFs as the exclusive functional source.
(2) There is a paucity of translational evidence directly correlating OPG+ iCAFs with T cell exclusion in human tumors.
(3) The scope is limited by the reliance on two murine models, including a subcutaneous pancreatic cancer model, which may not fully recapitulate native tumor microenvironments.
(4) Long-term outcomes and durability of response following OPG blockade, including possible effects on bone homeostasis, are not addressed.
(5) Mechanistic experiments related to the blockade of TRAIL and RANKL remain incomplete, and alternative pathways are not thoroughly explored.
Reviewer #2 (Public review):
Summary:
The work identified a protein called OPD secreted by a particular subtype of cancer-associated fibroblasts and found that it regulated T cell function in the tumor microenvironment. They showed that an antibody that targeted this protein could induce infiltration of immune cells into the tumour and could convert a cold tumor lacking tumour infiltration to a hot tumour with an immune-rich tumour microenvironment. They have supported the conclusion with the data in animal work as well as human tissue data. The authors also stated that it remains unclear whether the IFN-stimulated CAF subset after antibody treatment of OPG is due to reprogramming of existing iCAFs or arises de novo from progenitor populations. Despite their preclinical data suggesting the latter, they rightly suggested that in vivo lineage tracing is needed to further prove the origin and fate of these CAF populations. Overall, this is a well-designed and important study that would benefit from further mechanistic clarification and minor revision.
Strengths:
The strength of their data is that they utilized an immunocompetent orthotopic breast cancer model using the GFP-labelled tumor cell line EO771 in C57BL/6J mice, a well-established model for interrogating the role of stromal-immune interactions in carcinogenesis and tumor growth. They also performed scRNA-seq of the sorted stromal cells of the implanted EO771 cells as well as stromal cells from human esophageal carcinoma using tumor samples and matched adjacent non-malignant tissues from patients.
Weaknesses:
The key mechanistic aspects remain unclear, in particular the relative contributions of the TRAIL versus RANKL pathways to immunosuppression. The dual inhibition of TRAIL and RANKL by OPG is proposed, but the contribution of each axis to immune suppression was not clearly dissected. It would strengthen the paper to evaluate the effects of TRAIL versus RANKL signalling (e.g., with selective ligands or antagonists), which warrants deeper mechanistic exploration. Moreover, while CD4⁺ T cell cytotoxicity was observed, its functional role was underexplored.
Once a group is singled out in one contrast, it cannot appear in another. Each contrast compares only two “chunks” of variance. If you have a control group, the first contrast usually compares the control against all experimental groups.
dus bepaalde constraten, eerst word de contrast groep vergeleken met alle experimentele groepen en als je iets uit het conntrast haalt kan het niet terugkomen
Both and are sums, so their size depends on the number of scores. To eliminate this inequality we calculate an average sum of squares, the so-called mean squares
mean squeres vermindereen de afhankelijkheid van de grote van de aantal nummers op de totale optelsommen. Mean squares zijn een manier om de som van kwadraten te normaliseren door de vrijheidsgraden (degrees of freedom, df). Dit maakt het mogelijk om de variatie per eenheid te vergelijken, ongeacht de steekproefgrootte. dit zijn deze vormen mean square for the model, residuals en total. deze standaardiseren variatie zodat de variatie per eenheid kan worden vergeleden want de sommen zijn afhankelijk van n. mean of squares zijn dus onafhankelijk
The model sum of squares
hoeveel van de verschillende scores voorkomen door de verschillende behandelingscondities
between each observed data point and the grand mean.
verschil elk geobserveerd punt zowel goed als error en de grand mean vervolgens kwadradeer je dit. je moet het zien als een waargenomen datapunt min de mean en dit in het kwadraad
efficients, the greater the deviation between the model and the null.
parameters bepalen de vorm van het model hoe groter de coefficienten hoe groter de afwijking tussen het nulmodel en het model
ncrease the number of dummy
meerdere dummys als je meerdere groepsgemiddelden wil vergelijken
p-value for significance, the mean difference for direction, the effect size for magnitude, and the confidence intervals for precision
wat rapoteer je als het gaat om de repeated t/test. effectsize, mean differences, en de p waarde en confidence intervals
the effect size in a repeated-measures design is large, and the confidence interval is narrower than in the inde
als effect size groter is dan de confidence interval dan heeft er een nauwkirge schatting van het effect weergegeven
If the confidence interval around the mean difference excludes zero,
als 0 niet in het confidence interval is benoemd versterkt dit de conclsuie dat er een effect is
Effect sizes, such as Cohen’s d, quantify how different the groups are in practical terms. Confidence intervals around these estimates further help us understand the possible range of the true effect,
effect sizes geven hoeveel groepen verschillen en confidence intevals geven de range
If the observed difference is larger than the standard error:
wanneer de geobserveerde verschillen in gemiddelen groter zijn dan de standaard error dan kan er of geen effect zijn of wel omdat het twee verschillende populaties zijn. dit zijn de twee opties maar stel het verschil tussen de geobserveerde verschillen en de se is heel groot dan is de kans dat het om t2 gaat veel groter
The liver, while playing important roles in whole body metabolism, is usually considered a part of the gastrointestinal system for two main reasons. First, it provides for excretion from the body of lipid-soluble waste products that cannot enter the urine. Second, the blood flow draining the intestine is arranged such that substances that are absorbed pass first through the liver, allowing for the removal and metabolism of any toxins that have been taken up, as well as clearance of particulates, such as small numbers of enteric bacteria.
Testing
I put on the body-armor of black rubber the absurd flippers the grave and awkward mask.
I think it’s interesting how the ordinary diving equipment becomes symbolic, like “black rubber body armor” and “awkward mask,” suggesting emotional or psychological protection.
rdfs:Literal (typed as as xsd:decimal).
We have bytes here the cannot be 0.5
DCAT v3
Range: rdfs:Literal typically typed as xsd:nonNegativeInteger.
https://www.w3.org/TR/vocab-dcat-3/#Property:distribution_size
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Reviewer #1
Summary:
Miyamoto et al. report that importin α1 is highly enriched in a subfraction of micronuclei (about 40%), which exhibit defective nuclear envelopes and compromised accessibility of factors essential for the damage response associated with homologous recombination DNA repair. The authors suggest that the unequal localization and abnormal distribution of importin α1 within these micronuclei contribute to the genomic instability observed in cancer.
Major comments:
1.) It is crucial to quantitatively assess the localization of importin α1 in micronuclei (MN) across non-transformed MCM10A cells compared to transformed cell lines (MC7, HeLa, and MDA-MB-231). This analysis would help determine whether the localization of importin α1 in MN correlates with genomic stability in human cancer cells
We appreciate the reviewer's thoughtful suggestion to compare non-transformed and transformed cell lines to evaluate importin α1 localization in MN. Given that HeLa cells are derived from cervical cancer rather than the mammary epithelium, we considered it inappropriate to directly compare them with non-transformed mammary epithelial MCF10A cells. Therefore, HeLa cells were analyzed separately to assess the effects of reversine treatment on importin α1 localization. The results indicated no significant difference between the treated and untreated HeLa cells. (Supplemental Fig. S2F in the revised manuscript). Regarding the comparison between MCF10A and the two cancer cell lines, MCF7 and MDA-MB-231, the proportion of importin α1-positive MN did not significantly differ across the cell lines, regardless of reversine treatment (Supplemental Fig. S3B, Untreated: p = 0.9850 and 0.5533; Reversine: p = 0.2218 and 0.9392). These results suggest that there is no clear difference in the localization of importin α1 in MN between the transformed and non-transformed cell lines tested. However, we acknowledge that this does not exclude the possibility that importin α1 localization to MN is linked to genomic instability under specific conditions.
2.) While the authors provide some evidence indicating partial disruption of nuclear envelopes in MN (Figures 3 and S4), it is noteworthy that this phenomenon also occurs in importin α1-negative MN. Furthermore, according to the figure legends, the data presented in both figures stem from a single experiment. Current literature suggests that compromised nuclear envelope integrity is one of the major contributors to genomic instability, mediated through mechanisms such as chromothripsis and cGAS-STING-mediated inflammation arising from MN. Therefore, a more comprehensive quantification of nuclear envelope integrity-ideally comparing non-transformed MCM10A cells with transformed cell lines (MC7, HeLa, and MDA-MB-231)-is necessary to substantiate the connection between aberrant importin α1 behavior in MN and chromothripsis processes, as well as regulation of the cGAS-STING pathway linked to genomic instability in cancer cells.
We thank the reviewer for the constructive suggestion to quantify nuclear envelope integrity more comprehensively. In response, we compared laminB1 localization at the MN membrane between importin α1-positive and -negative MN in MCF10A, MCF7, MDA-MB-231, and HeLa cells, and included these results in the revised manuscript (Fig. 4C). For each cell, the laminB1 intensity in the MN was normalized to that of the primary nucleus (PN). This analysis showed that laminB1 intensity was significantly lower in importin α1-positive MN across all cell lines, including non-transformed MCF10A cells. These findings support a close association between aberrant importin α1 accumulation and compromised nuclear envelope integrity, a key factor potentially linking MN to chromothripsis and cGAS-STING-mediated genomic instability.
3.) The schematic illustration presented in Figure 8 does not adequately summarize all findings from this study nor does it clarify how the localization of importin α1 within MN might hypothetically influence genome stability. Although it is reasonable to propose that "importin α can serve as a molecular marker for characterizing the dynamics of MN" (Line 344), the authors assert (Line 325) that their findings, along with others, have "potential implications for the induction of chromothripsis processes and regulation of the cGAS-STING pathway in cancer cells." However, they fail to provide a clear or even hypothetical explanation regarding how their findings contribute to these molecular events. To address this gap, it would be essential for them to contextualize their results within existing literature that explores and links structural integrity deficits or aberrant DNA replication/damage responses in MN with chromothripsis and inflammation (e.g., PMID: 32601372; PMID: 32494070; PMID: 27918550; PMID: 28738408; PMID: 28759889).
We agree that the previous schematic illustration (former Fig. 8) did not adequately summarize our findings and may have overstated our conclusions. Accordingly, we have removed this figure from the revised manuscript.
To address the reviewer's concern, we performed additional analyses and included the results in the new Figure 8. These data show that, in addition to RAD51, both RPA2 and cGAS display mutually exclusive localization with importin α1 in MN. RPA2, a single-stranded DNA-binding protein, stabilizes damaged DNA and enables RAD51 filament assembly during homologous recombination repair. Previous studies have demonstrated that RPA2 accumulates in ruptured MN in a CHMP4B-dependent manner (PMID: 32601372). Likewise, cGAS is a cytosolic DNA sensor that localizes to ruptured MN and activates innate immune signaling through the cGAS-STING pathway, as widely reported (PMID: 28738408; 28759889; see also PMID: 32494070; 27918550).
Our findings suggest an alternative scenario: even when nuclear envelope rupture occurs, importin α1-positive MN may remain inaccessible to DNA repair and sensing factors such as RPA2 and cGAS. This supports the view that importin α1 defines a distinct MN subset, separate from those characterized by the canonical DNA damage response or innate immune signaling factors. Furthermore, our overexpression experiments with EGFP-importin α1 (Fig. 7G, 7H) raises the possibility that importin α1 enrichment may impede the recruitment of DNA-binding proteins.
Taken together, these results support the conclusion that importin α1 marks a unique MN state and provides a molecular framework for distinguishing between different MN environments. At the reviewer's suggestion, we have cited all the recommended references (PMID: 32601372, 32494070, 27918550, 28738408, and 28759889) in the revised manuscript to better contextualize our findings. We are grateful for the reviewer's thoughtful suggestions and literature recommendations, which helped us clarify the implications of our findings within the broader context of chromothripsis and cGAS-STING-mediated genomic instability.
4.) Fig. 4D does not support the idea that importin α1 is euchromatin enriched: H3K9me3, H3K4me3 and H3K37me3 seem to be all deeply blue.
We sincerely thank the reviewer for pointing out the important limitations of the original version of Fig. 4D, as also raised in minor comment #5. As the reviewer correctly noted, this figure was intended to demonstrate that importin-α1 preferentially localizes to euchromatin regions (H3K4me3 and H3K36me3) rather than heterochromatin (H3K9me3 and H3K27me3). However, we acknowledge that in the original figure, the predominantly blue tone of the heatmap made this interpretation unclear and that the Spearman's correlation coefficient for H3K36me3 was missing. In response, we have substantially revised the figure (now shown as Fig. 5E in the revised manuscript). Specifically, we improved the color scale for better visual distinction, added the missing Spearman's coefficients for H3K36me3, and strengthened the analysis by incorporating ChIP-seq data obtained with two independent antibodies against importin α1 (Ab1 and Ab2). We believe that these revisions provide a clear and more accurate representation of euchromatin enrichment of importin-α1, as originally intended.
Indeed, the data presented by the authors do not adequately support a direct link between the presence of importin α1 in MN and genomic instability in human cancer cells. While the experimental correlations provided may not substantiate this connection definitively, they do lay a foundation for a grounded hypothesis and suggest the need for further research to explore this topic in greater depth. Additionally, it is worth noting that the evidence contributes to the growing list of nuclear proteins exhibiting abnormal behavior in micronuclei (MN). This highlights the significance of studying such proteins to understand their roles in genomic stability and cancer progression.
Following the reviewer's suggestion, we carefully revised the manuscript to ensure that our statements are consistent with the scope of the data and do not overstate our conclusions. As part of this effort, we removed the schematic illustration (former Fig. 8), which might have overstated our findings, and refined the relevant text to prevent overinterpretation.
To our knowledge, this study is the first to report the specific accumulation of importin α in MN. Our results suggest a previously unrecognized function of importin α beyond its canonical transport role and add to the growing list of nuclear proteins that exhibit abnormal behavior in MN. We hope that these findings will provide a conceptual and experimental basis for future studies aimed at clarifying the biological significance of MN heterogeneity and quality control in cancer biology.
Additional experiments are necessary to quantitatively assess the localization of importin α1 in micronuclei (MN) across non-transformed MCM10A cells and transformed cell lines (MC7, HeLa, MDA-MB-231). This analysis would help determine whether the localization of importin α1 in MN correlates with genomic stability in human cancer cells.
As part of our response to Major Comment 1, we conducted additional experiments to quantitatively compare importin α1 localization in MN between non-transformed MCF10A cells, breast cancer cell lines (MCF7 and MDA-MB-231), and HeLa cells. These results have been included in the revised manuscript (Supplemental Fig. S2F and Fig. S3B). The analyses showed no significant differences in the proportion of importin α1-positive MN among these cell lines, consistent with the reviewer's request for a more comprehensive evaluation.
The authors claim that importin α1 preferentially localizes to euchromatic areas rather than heterochromatic regions within MN. While this assertion is supported by the immunofluorescence (IF) images presented in Figures 4A/B and S5A/B, it remains less clear for Figure S5C/B. To strengthen this claim, providing averages of IF distributions from multiple cells across independent experiments would be beneficial to draw more robust conclusions.
We have quantified the co-localization of importin α1 with the euchromatin marker H3K4me3 and the heterochromatin marker H3K9me3 in micronuclei (MN) across four human cell lines (MCF10A, MCF7, MDA-MB-231, and HeLa). The results of this statistical analysis are included in the revised manuscript in Fig. 5C. These data provide quantitative evidence from independent experiments showing that importin α1 preferentially localizes to euchromatic regions within the MN, thereby supporting our initial observation.
Furthermore, ChIP-seq data are presented to support the idea that importin α1 preferentially distributes over euchromatin areas in MN. However, as described, the epigenetic chromatin status indicated by these ChIP-seq experiments reflects that of the principal nucleus (PN), not specifically the status within MN in MCF7 cells. Given that MN represent only a small fraction of the cell population under normal culture conditions-likely less than 5% for HeLa cells as shown in Figure S2D-the relevance of this data is limited. Additionally, according to data presented in Figure 1B, importin α1 does not localize or distribute within the PN as it does in MN in MCF7 cells. Therefore, further experiments should be conducted to substantiate that importin α1 preferentially targets euchromatin areas within MN and to compare this distribution with that observed in the principal nucleus. Such studies could reveal potential abnormalities regarding the correlation between epigenetic chromatin status and importin α distribution in MN.
As noted, these experiments were performed on whole-cell populations of MCF7 cells and therefore reflect the overall chromatin landscape, not specifically that of the MN. We fully acknowledge that MN constitute only a small fraction of the cell population under standard culture conditions (Supplemental Fig. S2D), and thus, the relevance of ChIP-seq data to MN must be interpreted with caution.
Nevertheless, our intention in presenting these data was to illustrate that importin α1 preferentially associates with euchromatin regions marked by H3K4me3. To examine this more directly, we analyzed importin α1 localization in MN using immunofluorescence with histone modification markers across multiple cell lines. These analyses, together with the quantitative results now included in the revised manuscript (Fig. 5C), confirming that importin α1 preferentially localizes to euchromatic regions within MN.
Taken together, although the ChIP-seq data were derived from whole-cell populations, the combined results from IF imaging and quantitative analysis support our interpretation that importin α1 retains its euchromatin-associating property within MN. We hope that these additional data will address the reviewer's concerns.
To support the hypothesis that importin α1 inhibits RAD51 accessibility within MN, Figures 7D and E should be supplemented with thorough quantification and statistical analysis based on at least three independent experiments. This additional data would enhance confidence in their findings regarding RAD51 accessibility inhibition by importin α1.
Following the reviewer's suggestion, we have added a new graph (Fig. 7F) in the revised manuscript. This figure presents the quantified frequency of RAD51-positive MN among importin α1-negative and importin α1-positive MN, analyzed across six microscopy fields (n = 6) from three independent experiments.
To improve clarity and consistency, we reorganized the panels: representative RAD51 images are now shown in Fig. 7B, and the Cell #1 (low RAD51) vs. Cell #2 (high RAD51) classification with etoposide responsiveness is summarized in Fig. 7C. As illustrated in Figs. 7D and 7E, importin α1 and RAD51 exhibit mutually exclusive localization in MN. Fig. 7F provides a unified statistical summary at the population level.
The results showed that the proportion of RAD51-positive MN was significantly lower among importin α1-positive MN than among importin α1-negative MN, providing robust quantitative support for the proposed mutual exclusivity between importin α1 localization and RAD51 accessibility in MN.
We are grateful to the reviewer for this constructive suggestion, which helped us clarify and better support the central message of our study.
The additional experiments proposed are controls and direct comparisons using the same techniques and experimental designs used by the authors, so it is reasonable that the authors can carry them out within a realistic timeframe.
We appreciate the reviewer's thoughtful consideration of the feasibility of the additional experiments.
Given the importance of reproducibility and the need to evaluate results based on imaging and quantitation, I strongly recommend that the authors include a detailed description of the optical microscopy procedures utilized in their study. This should encompass imaging conditions, acquisition settings, and the specific equipment used. Providing this information will enhance transparency and facilitate reproducibility. For reference, some valuable guidance on essential parameters for reproducibility can be found in Heddleston et al. (2021) (doi:10.1242/jcs.254144). Incorporating these details will not only strengthen the manuscript but also support other researchers in reproducing the findings accurately.
Following the reviewer's suggestion, we have substantially revised the Materials and Methods sections in the main and supplemental manuscripts to provide detailed descriptions of the optical microscopy procedures, including the specifications of the imaging equipment, acquisition settings, and image processing parameters. These revisions follow the best practices recommended by Heddleston et al. (2021, J. Cell Sci., doi:10.1242/jcs.254144).
We have also expanded the description of our quantitative image analysis using ImageJ, providing details on the parameters for MN identification and the measurement of colocalization rates between importin α and histone modifications. These additions ensured reproducibility and clarity.
We believe that these modifications will enhance the reproducibility of our results and increase the value of our study for the research community. We sincerely appreciate the reviewer's helpful suggestions.
Many of the plots and values in the manuscript lack appropriate statistical analysis, including p-values, which are not detailed in the figures or their legends. Furthermore, the Statistical Analysis section does not provide adequate information regarding the specific statistical tests employed or the criteria used to determine which analyses were applied in each case. To enhance the rigor and clarity of the study, it is essential that these issues be addressed prior to publication. A comprehensive presentation of statistical analysis will improve the reliability of the findings and allow readers to better understand the significance of the results. I recommend that the authors revise this section to include detailed explanations of all statistical methods used, along with corresponding p-values for all relevant comparisons.
We sincerely appreciate the reviewer's constructive comments highlighting the importance of transparent and rigorous statistical analyses. In response, we have carefully revised all figure panels, figure legends, and the Materials and Methods (Statistical Analysis) section in both the main and the supplementary manuscripts.
In the revised figure legends, we now provide the number of independent experiments and sample sizes (n), statistical tests applied (e.g., unpaired or paired two-tailed t-test, one-way ANOVA with Tukey's post-hoc test, two-way ANOVA with Sidak's multiple comparisons), data presentation format (mean {plus minus} SD), and corresponding p-values or significance indicators (*, **, ***). The Statistical Analysis section was also expanded to explain the rationale for selecting each statistical test, the criteria for significance, and the reporting of the replicates. These revisions ensure clarity, reproducibility, and transparency throughout the manuscript, directly addressing the reviewers' concerns. We are grateful for this valuable suggestion, which has significantly improved the rigor of our study.
Minor comments:
The authors claim that importin α1 exhibits remarkably low mobility in the micronuclei (MN) compared to its mobility in the principal nucleus (PN), as illustrated in Figure 1. However, based on the experimental design, this conclusion may not be appropriate. In the current setup, the FRAP experiment conducted in the PN measures the mobility of importin α1 molecules within the cell nucleus, where the influence of nuclear transport is likely negligible. Conversely, in the MN experiments shown, all molecules of importin α1 are bleached within a given MN. Consequently, what is being measured here primarily reflects the effects of nuclear transport rather than intrinsic molecular mobility. To accurately compare kinetics of nuclear transport, it would be essential to completely bleach the entire PN. If measuring molecular mobility between MN and PN is desired, only a small fraction of either MN or PN area/volume should be bleached during FRAP analysis. Additionally, it would be beneficial to include measurements of mobility for other canonical nuclear transport factors (e.g., RAN, CAS, RCC1) for comparative purposes. This broader context would allow for a more comprehensive understanding of importin α1 behavior relative to other factors involved in nuclear transport. Finally, utilizing cells that exhibit importin α1 signals in both PN and MN could further strengthen comparisons and provide more robust conclusions regarding its mobility dynamics.
We thank the reviewer for their constructive suggestions regarding our FRAP analysis. To address the concern that the original comparison between PN and the micronuclei (MN) might have been biased by differences in bleaching areas, we performed new experiments in which both PN and MN were fully bleached within the same cells (Fig. 3A, and 3C). This approach allowed for a more direct comparison of importin α1 dynamics under equivalent conditions.
These experiments revealed a markedly slower fluorescence recovery in MN than in PN, indicating reduced nuclear import and/or recycling efficiency of importin α1 in MN. In addition, we retained our original analysis to further characterize the heterogeneous mobility patterns of importin α1 in MN, identifying three distinct mobility classes: high, intermediate, and low (Fig. 3B, and 3D). Together, these results support our observation that importin α1 mobility is restricted in MN, likely due to altered nuclear transport dynamics.
As suggested by the reviewer, we attempted partial bleaching of MN to assess intranuclear mobility. However, owing to the small size of MN, partial bleaching is technically challenging and inconsistent, with some MN recovering even during the bleaching process. Therefore, reliable quantification was not possible. For transparency, these data are provided as a Reviewer-only Figure but were not included in the revised manuscript.
Finally, while we agree that examining other nuclear transport factors (e.g., RAN, CAS, RCC1) would be informative, our study focused on importin α1 dynamics. We consider these additional factors to be important directions for future investigations.
Prior studies are referenced appropriately in general, but the authors missed some references (PMID: 32601372; PMID: 32494070; PMID: 27918550; PMID: 28738408; PMID: 28759889) that I consider key to put the present findings in frame with previous works which link the lack of structural integrity and/or aberrant DNA replication/damage responses in MN with Cchromothripsis and inflammation.
We thank the reviewer for carefully pointing out the key references that are highly relevant to framing our findings in the context of previous studies on micronuclear instability, chromothripsis and inflammation. We fully agree with this suggestion.
In the revised manuscript, we have cited these studies in both the Introduction and Discussion sections. Specifically, we incorporated these studies when discussing the structural fragility of MN, aberrant DNA replication, and the exposure of micronuclear DNA to cytoplasmic sensors, which mechanistically link MN rupture to chromothripsis and cGAS-STING-mediated immune activation. For example, we now refer to the study demonstrating RPA2 recruitment to ruptured MN in a CHMP4B-dependent manner (PMID: 32601372), reports showing defective replication and DNA damage responses in MN (PMID: 32494070; 27918550), and seminal studies establishing cGAS localization to ruptured MN and activation of innate immune signaling (PMID: 28738408; 28759889).
By incorporating these references, we more clearly position our findings that importin α1 defines a distinct subset of MN lacking access to DNA repair and sensing factors such as RAD51, RPA2, and cGAS. This contextualization emphasizes that our data add to and extend the established view that compromised MN integrity underlies chromothripsis and inflammation by identifying importin α1 as a novel marker of an alternative MN microenvironment. We are grateful for this constructive recommendation, which has allowed us to strengthen the framing of our study in the existing literature.
The figures presented in the manuscript are clear; however, where plots are included, they require appropriate statistical analysis. It is essential to display p-values on the plots or within their legends to provide readers with information regarding the significance of the results. Including this statistical information will enhance the interpretability of the data and strengthen the overall findings of the study. I recommend that the authors revise these sections accordingly before publication.
In response, we have revised the relevant figure panels and their legends to clearly display the statistical significance, including p-values, where appropriate. Specifically, we added statistical annotations (p-values or significance markers such as asterisks) directly on the plots or in the corresponding legends, and clarified the number of replicates, statistical tests used, and definitions of error bars (mean {plus minus} SD). We believe that these revisions improve the interpretability and transparency of our results and strengthen the overall presentation of the data.
__ 1.) In lines 134-135, it is stated that "up to 40% of the MN showed importin α1 accumulation under both standard culture conditions and the reversine treatment (Fig. S2F)." However, Figure S2F only displays percentages for reversine-treated cells, and there is no mention in the text or figures regarding the percentage of importin α1-positive MN determined by immunofluorescence (IF) under standard culture conditions. This discrepancy should be addressed.__
Following the reviewer's comments, we revised Supplemental Fig. S2F shows a direct comparison of the proportion of importin α1-positive MN between untreated and reversine-treated HeLa cells based on indirect IF analysis. The Results section was updated accordingly (page 8, Lines 148-150): "We then examined whether reversine treatment affected the proportion of importin α1-positive MN. The results revealed that the MN formation rate for either untreated or treated cells was 36.2% {plus minus} 7.8 or 38.3% {plus minus} 8.8, respectively, with no significant difference (Fig. S2F). "
We believe that this revision addresses the reviewer's concern by providing relevant quantitative data for the untreated condition.
2.) In line 170, the authors state that "Cells in which overexpressed EGFP-importin α1 localized only in PN were excluded from the analysis (see Fig. 1E, top panels)." It is unclear why this exclusion was made. The authors should clarify whether they are referring to all constructs or only to the wild-type (WT) construct when mentioning EGFP-importin α1 localization solely in PN. This clarification is important as it may affect the results highlighted in line 173.
In this section, we aimed to clarify that the quantitative analysis focused exclusively on cells harboring MN, as the purpose of the analysis was to compare the localization of EGFP-importin α1 between MN and PN. We excluded cells that contained no MN and showed EGFP-importin α1 localization only in the PN. This criterion was consistently applied to both wild-type and mutant constructs. To avoid confusion, we have removed the sentence "Cells in which overexpressed EGFP-importin α1 localized only in PN were excluded from the analysis (see Fig. 1E, top panels)." from the revised manuscript.
3.) The statement in line 191 ("However, this antibody could not be further used in this context due to cross-reactivity with highly concentrated importin α1 in MN (Fig. S4)") is somewhat misleading. While it hints at a technical issue, it does not provide additional relevant information for understanding its implications for the rationale of the research. Moreover, Figure S4 is referenced but appears to refer specifically to panels S4D and E, which are not mentioned in the text. I recommend clarifying this point or removing it altogether.
We agree with the reviewer that the statement "However, this antibody could not be further used in this context due to cross-reactivity with highly concentrated importin α1 in MN (Fig. S4)" was not essential for understanding the rationale of our study and could be misleading. In response, we have removed this sentence from the revised manuscript, along with the corresponding Supplementary Fig. S4.
4.) Lines 197-199 contain a sentence that could be misleading and would benefit from clearer explanation. Although Figure 3D provides some clarity on this matter, no statistical analysis is included-only a bar plot is presented. A proper statistical analysis should be provided here to enhance understanding.
In the revised manuscript, we performed one-way ANOVA followed by Holm-Sidak's multiple comparisons test to evaluate the MN localization ratio of EGFP-NES between Imp-α1-negative and Imp-α1-positive MN. This analysis revealed a statistically significant difference (**p
5.) In lines 218-221, it states that importin α1 associates with euchromatin regions characterized by H3K4me3 and H3K36me3; however, Figure 4D lacks the Spearman's correlation coefficient value for H3K36me3 within the matrix. This omission needs correction.
We thank the reviewer for this insightful comment. As addressed in response to Major comment #4, we have substantially revised Fig. 5 and added the missing Spearman's correlation coefficient value for H3K36me3 (now shown in Fig. 5E). These revisions, together with the overall improvements to the figure, more clearly illustrate the euchromatin enrichment of importin-α1.
6.) For consistency in the experimental design aimed at identifying potential importin α1-interacting proteins, it would be more appropriate for Figures 5C/D to show IF data from MCF7 cells rather than HeLa cells.
We sincerely apologize for the misstatements in the legends of the original Fig. 5C. The correct description is that this experiment was performed using MCF7 cells, and we have revised the legend accordingly in the revised manuscript (now Fig. 6C). In addition, because the original data in Fig. 5D were obtained from HeLa cells, we repeated this experiment using MCF7 cells and replaced the panel with new data (now Fig. 6D).
7.) To substantiate claims that importin α1 inhibits RAD51 accessibility within MN, Figures 7D and E should include thorough quantitation and statistical analysis based on at least three independent experiments.
As described above, we addressed this point by adding a new quantification and statistical analysis in Fig. 7F, based on six microscopy fields across three independent experiments. This analysis directly supports our claim that importin α1 inhibits RAD51 accessibility in the MN.
We would also like to clarify that although the reviewer referred to Figs 7D and 7E, these two panels were designed to illustrate the same phenomenon-the mutually exclusive localization of importin α1 and RAD51 to distinct MN-shown in different contexts. Specifically, Fig. 7D presents examples from separate cells, each with MN containing either importin α1 or RAD51, while Fig. 7E shows a single cell containing two distinct MN, one enriched with importin α1 and the other with RAD51. Because both panels serve as illustrative examples of the same phenomenon, it would not be meaningful to quantify them independently as parallel datasets. Instead, we integrated the statistical analysis into a unified graph (Fig. 7F), which summarizes the frequency of RAD51-positive MN in relation to importin α1 status across the cell population, thereby supporting our interpretation that importin α1-positive MN represent a distinct subset that is less accessible to RAD51.
8.) The meaning of lines 336-338-"Therefore, the enrichment of importin α1 in MN, along with its interaction with chromatin, may regulate the accessibility of RAD51 to DNA/chromatin fibers in MN and protect its activity"-is unclear. I suggest rephrasing this sentence for improved clarity and comprehension.
We appreciate the reviewer's comment regarding the clarity of our statement in the Discussion (former lines 336-338). We agree that the original phrasing is ambiguous. To improve clarity and align with our results, we revised this section to emphasize that importin α1-positive MN represent a restricted environment from which DNA repair and sensing factors are excluded. Specifically, RAD51, RPA2, and cGAS showed mutually exclusive localization with importin α1, indicating that these MN are largely inaccessible to DNA-binding proteins (pages 20-21). This rephrasing removes the unclear phrase "protect its activity" and directly reflects our experimental findings, presenting a clearer interpretation that is consistent with the Results.
9.) Fig. 1D: Numbers on the y-axis are missing, x-axis labeling is too small
We appreciate the reviewer's careful examination of the figure. In the revised manuscript, we added numerical tick labels to both the x- and y-axes and increased the label font size to ensure clear readability, as shown in Fig. 1D. We also applied the same improvements to other fluorescence intensity plots, including Figs. 4A, 4B, 5A, 5B, 7H, and Supplemental Fig. S4C and S5A-S5F to ensure consistency in readability across the manuscript. We thank the reviewer for helping us improve the clarity and accuracy of our figure presentations.
10.) Fig. 1F: As the PN/MN values of the three experiments are seemingly identical (third column) the distribution of the three individual data of the PN (first column) should mirror the distribution of the three individual data of the MN (second column). The authors might want to check why this is not the case.
Upon re-examination of the source data, we identified and corrected a minor calculation error in one subset and regenerated the panel. After correction, the three independent PN/MN ratios were 3.1%, 2.9%, and 2.6%, rather than being identical. These corrected values were proportional to the corresponding PN and MN measurements and preserved the expected relationship between their distributions. Although the numerical differences were small, they demonstrated high reproducibility across independent experiments. These corrections do not alter the interpretation of Fig. 1F, and the distribution of PN/MN values is now consistent with the paired PN and MN data presented in the revised manuscript.
Significance Micronuclei (MN) primarily arise from defects in mitotic progression and chromatin segregation, often associated with chromatin bridges and/or lagging chromosomes. MN frequently exhibit DNA replication defects and possess a rupture-prone nuclear envelope, which has been linked to genomic instability. The nuclear envelope of MN is notably deficient in crucial factors such as lamin B and nuclear pore complexes (NPCs). This deficiency may be attributed to the influence of microtubules and the gradient of Aurora B activity at the mitotic midzone, which inhibits the recruitment of proper nuclear envelope components. Additionally, several other factors may contribute to this process: for instance, PLK1 controls the assembly of NPC components onto lagging chromosomes; chromosome size and gene density positively correlate with the membrane stability of MN; and abnormal accumulation of the ESCRT complex on MN exacerbates DNA damage within these structures, triggering pro-inflammatory pathways.
The work presented by Dr. Miyamoto and colleagues reveals the abnormal behavior of importin α1 in MN during interphase. According to their findings, it is reasonable to consider importin α1 as a molecular marker for characterizing MN dynamics. Furthermore, it could serve as a potential clinical marker if the authors provide additional experiments demonstrating significantly different localization patterns of importin α1 in transformed cells (e.g., MC7, HeLa, MDA-MB-231) compared to non-transformed cells (e.g., MCM10A).
While the authors present some evidence indicating partial disruption of nuclear envelopes in MN (Figures 3 and S4), it is noteworthy that this phenomenon also occurs in importin α1-negative MN. Moreover, according to the figure legends, data for both figures originate from a single experiment. As such, convincing evidence linking the aberrant behavior of importin α1 in MN with chromothripsis processes or regulation of the cGAS-STING pathway-and its implications for genomic instability in cancer cells-remains lacking.
Overall, it is not entirely clear what significance this advance holds for the field; while there are conceptual contributions made by this work, they do not appear sufficiently robust at this time. Further research is needed to clarify these connections and strengthen their conclusions regarding importin α1's role in MN dynamics and genomic instability.
We sincerely appreciate the reviewer's thoughtful and constructive evaluation of the significance of our study. We agree that in the original submission, the conceptual contribution was not fully supported by sufficient evidence. In the revised manuscript, we have substantially strengthened our findings by incorporating new data on RPA2 and cGAS, in addition to RAD51. These results consistently show that importin α1-positive MN are largely inaccessible to multiple DNA-recognizing proteins-including DNA repair factors (RAD51 and RPA2) and the innate immune sensor cGAS-whereas importin α1-negative MN readily recruit these proteins. This broader dataset reinforces the concept that importin α defines a distinct and restricted MN subset, extending beyond our initial observation of RAD51 exclusion.
By framing importin α as a molecular marker that discriminates between functionally distinct MN environments, our study conceptually advances the understanding of MN heterogeneity. This adds to the prior literature showing that defective nuclear envelope integrity underlies chromothripsis and cGAS-STING activation and positions importin α as a new marker for identifying MN that are refractory to these DNA repair and sensing pathways. While we agree that further work is necessary to directly link importin α enrichment to downstream genomic instability or inflammation in cancer, we believe that our revised data now provide a robust foundation for future investigations.
Taken together, the revised manuscript presents a clearer and more comprehensive conceptual advance: importin α-positive MN represents a previously unrecognized molecular environment distinct from MN characterized by canonical DNA repair or sensing factors. We are grateful to the reviewer, whose constructive comments greatly improved the clarity, robustness, and overall impact of our study. We believe that these findings will be of particular interest to researchers studying the mechanisms of genomic instability, chromothripsis, and cancer biology.
Reviewer #2
Summary:
The authors have shown that Importin α1, a nuclear transport factor, is enriched in subsets of micronuclei (MN) of cancer cells (MCF7 and HeLa) and, using FRAP, has an altered dynamics in MN. Moreover, the authors have shown that these levels of Importin α1 in the MN are likely not due to its traditional role for signal-dependent protein transport, as suggested by immunofluorescence of other factors important for this function. Additionally, cargo dynamics carrying NLS or NES signals were disrupted in Importin α1-positive micronuclei. Importin α1-positive micronuclei also appear to have a disrupted nuclear envelope, potentially explaining some of these cargo disruptions. The authors also demonstrated that Importin α colocalizes with proteins important for DNA replication, and p53 signaling using RIME, followed by immunofluorescence. Lastly, the authors show that Importin α and RAD51 have mutual exclusivity in the micronuclei.
Major comments:
1) A key issue is there are very few statistical tests used in this study. It is crucial to the interpretation of the data. We strongly urge the authors to re-analyze the data using appropriate statistical analyses. Along those lines, in many figures 1 or 2 images are shown without stating how many biological or technical replicates this is representative of or showing quantification of the anlyses. In general, the authors' statements would be strengthened by showing more examples and/or stating "N" in the figure legends or supplement.
We sincerely thank the reviewer for emphasizing the importance of including sufficient statistical analyses and replication information. As noted in our response to Reviewer #1, we have carefully revised the manuscript to enhance statistical rigor and transparency throughout. Specifically, we expanded the Statistical Analysis section in the Materials and Methods section to provide a clear description of the statistical approaches used. In addition, all figure legends have been revised to explicitly state the number of biological replicates, sample sizes, statistical tests applied, and corresponding p-values or significance indicators. Representative images are consistently accompanied by quantitative analyses derived from multiple independent experiments.
We believe that these comprehensive revisions directly address the reviewer's concerns and substantially improve the rigor, clarity, and interpretability of our manuscript.
2) Using RIME and immunofluorescence, the authors identify factors that co-localize with Importin α1 in subsets of micronuclei (Figure 5), which is interesting, but there is no functional data associated with this result. Are the authors stating that these differences account for altered DNA damage or replication? It is unclear what the conclusion is beyond "some MN are different than others." Could the authors knockdown/knockout these factors to determine if they recruit Importin α1 into MN or the reciprocal? For many of these factors, they appear to be broadly present throughout the entire primary nucleus as well, indicating there is nothing unique about their MN localization.
We agree that our original RIME and indirect IF analyses were primarily descriptive and lacked functional validation. To strengthen this aspect, we added new IF and quantification data (now presented in Fig. 8) showing that importin α1-positive MN are largely mutually exclusive with DNA repair and sensing factors such as RAD51, RPA2, and cGAS, whereas importin α1 frequently co-localizes with chromatin regulators identified by RIME, such as PARP1 and SUPT16H/FACT. These findings indicate that importin α1-positive MN define a distinct molecular environment enriched in replication- and chromatin-associated regulators but inaccessible to canonical DNA repair and sensing proteins.
This combination of mutual exclusivity with DNA repair/sensing factors and frequent co-localization with chromatin regulators underscores the biological significance of importin α1 localization in MN, as it may contribute to localized chromatin stabilization through association with chromatin regulators while simultaneously restricting access to DNA repair and sensing factors. Thus, importin α1-positive MN represent a restricted subset with potential implications for genome stability and immune signaling, going beyond the descriptive notion that "some MN are different than others."
Moreover, many chromatin regulators identified by RIME contain classical nuclear localization signals (NLSs), raising the possibility that importin α1 interacts with these proteins via their NLS sequences. We fully agree with the reviewer that knockdown or knockout experiments would be highly valuable to clarify whether such interactions actively recruit importin α1 into MN or occur reciprocally, and we regard this as an important direction for future investigations.
3) In line 274, the authors state that MN highly enriched for Importin α1 inhibits RAD51 accessibility but this is an overstatement of the data. Instead, the authors show that RAD51 and importin α1 do not colocalize in micronuclei, albeit without quantification which weakens their argument. Also, the consequence of this "mutual exclusivity" is unclear. Can the authors inhibit or knockdown Importin α1 and show that RAD51 goes to all micronuclei? And how is this different than the data shown for factors in Figure 5? Some of those show colocalization with Importin α1-positive micronuclei and others do not. Could you perform live imaging of labeled Importin a1 and RAD51 and show that as Importin α1 accumulates in MN that RAD51 or other DNA repair factors are exported? An alternative experiment would be to show that the C-mutant, which is defective in nuclear export, now colocalizes with RAD51 in MN. Please reconcile this or show experiments to prove the statement above.
We agree that our original wording "inhibits RAD51 accessibility" was not sufficiently supported by direct evidence, as it was based solely on the immunofluorescence data. Therefore, we have removed this statement from the Results section of the revised manuscript. To strengthen this point, we added a quantitative analysis (Fig. 7F) showing that RAD51 signals were significantly reduced in importin α1-enriched MN.
Regarding the suggestion to perform knockdown experiments, we note that the depletion of KPNA2 (gene name of importin α1) has been reported to cause severe cell-cycle arrest (Martinez-Olivera et al, 2018; Wang et al, 2012). Consistent with these reports, we also found that siRNA-mediated knockdown of KPNA2 in our system strongly reduced MN induction upon reversine treatment, making it technically unfeasible to analyze RAD51 localization under these conditions. We also sincerely thank the reviewer for suggesting the live imaging experiments. We fully agree that such experiments would provide valuable mechanistic insights, and we regard this as an important direction for future research.
In addition, to address the reviewer's concern about other DNA repair factors, we added new data (Fig. 8) showing that importin α1-positive MN are mutually exclusive with RPA2 and cGAS. RPA2 is a canonical single-strand DNA (ssDNA)-binding protein that stabilizes exposed ssDNA and facilitates RAD51 recruitment. It has been reported to accumulate in ruptured MN in a CHMP4B-dependent manner (Vietri et al, 2020). cGAS is a cytosolic DNA sensor that detects ruptured MN and activates innate immune signaling via the cGAS-STING pathway. Together with our RAD51 results, these data show that importin α1-positive MN are consistently segregated from multiple DNA-recognizing factors, including RAD51. Simultaneously, importin α1 co-localizes with chromatin regulators identified by RIME, such as PARP1 and SUPT16H/FACT. These findings support the view that importin α1-positive MN define a distinct molecular environment enriched in chromatin regulators but largely inaccessible to DNA repair and sensing factors. While the precise mechanism remains unclear, one possibility is that importin α1-associated chromatin interactions limit the access of DNA repair and sensing proteins. However, this interpretation is speculative and requires further investigation.
4) In the Discussion, line 343-344 states that "importin α1 is uniquely distributed and alters the nuclear/chromatin status when enriched in MN," however this is not currently supported by the present data. The data presented shows correlation (albeit weak) between euchromatic modifications and Importin α1, and it does not definitively show that importin α1 is sufficient to alter the nuclear-chromatin status when enriched in the MN. More substantial experiments would be required to show whether Importin α1 plays an active role in these modifications.
Following the reviewer's suggestion, in the revised manuscript, we removed this overstatement and rephrased the relevant sections of the Discussion. Rather than implying a causal role, we now describe the mutually exclusive localization of importin α1 with DNA repair and sensing factors (RAD51, RPA2, and cGAS), emphasize its preferential association with euchromatin regions marked by H3K4me3, and note its frequent co-localization with chromatin regulators identified by RIME, such as PARP1 and SUPT16H/FACT. These findings suggest that importin α1-positive MN define a distinct subset characterized by limited accessibility to DNA repair and sensing proteins, whereas cGAS-positive ruptured MN exemplify a state in which these proteins can accumulate.
We also added a concluding statement that frames importin α1 as defining a previously unrecognized MN subset that is distinct from conventional ruptured MN. This revision provides a more accurate and appropriately cautious interpretation of our data while underscoring the conceptual advance of our study by clarifying how importin α1 localization reveals MN heterogeneity.
Minor Comments
1) Summary statement (page 3 Line 40): The use of "their" is confusing. Whose microenvironment are you referring to?
We have rephrased the sentence as follows: The accumulation of importin α in micronuclei, followed by modulation of the microenvironment of the micronuclei, suggests the non-canonical function of importin α in genomic instability and cancer development. Thank you for this useful suggestion.
2) In Abstract and introduction (page 4, Line 44 and page 5, line 59) it states that MN are membrane enclosed structures, but this is not always the case (see https://doi.org/10.1038/nature23449 as one example).
While MN are typically surrounded by a nuclear envelope at the time of their formation during mitosis, we agree that this envelope can later rupture or fail to assemble completely, thereby exposing micronuclear DNA to the cytoplasm. To clarify this point, we revised the Introduction to explicitly acknowledge that MN may lose nuclear envelope integrity, which can have important consequences for genomic instability and immune activation inflammation. Specifically, we have added the following sentence to the Introduction (page 4, lines 77-80): "The nuclear envelope of MN can be partially or completely disrupted, allowing cytoplasmic DNA sensors, such as cyclic GMP-AMP synthase (cGAS), to access micronuclear DNA and trigger innate immune responses via the cGAS-STING pathway (Harding et al, 2017; Li & Chen, 2018; Mackenzie et al, 2017). "
We hope this addition appropriately addresses the concerns raised by Reviewer #2 while incorporating the valuable suggestions from Reviewer #1 without altering the overall structure and flow of the manuscript.
3) Given the fact that the RIME result identified proteins involved in DNA replication to be enriched with Importin α1, are these MN enriched in factors described in Fig. 5 simply localizing to MN that are in S phase, as described previously (doi: 10.1038/nature10802)?
We sincerely thank the reviewer for raising this constructive perspective regarding the potential relationship between importin α1 enrichment in micronuclei (MN) and the S phase. Our RIME analysis identified chromatin-associated proteins, such as PARP1 and SUPT16H/FACT, which are often activated during replication stress and frequently function in the S phase. However, importin α1-positive MN were not exclusively associated with S-phase-specific molecules, and our data do not indicate that these MN are restricted to the S phase.
Previous studies [e.g., (Crasta et al, 2012)] have established that MN are prone to replication defects and represent hotspots of genomic instability. The recovery of replication stress-responsive molecules, such as PARP1 and FACT, by RIME is therefore consistent with the biology of MN. Based on this valuable suggestion, we have revised the Discussion (page 19) to explicitly mention the potential involvement of replication-related proteins in importin α1-positive MN, as well as the possibility that importin α1 accumulation may contribute to replication defects in these structures. We are grateful to the reviewer for raising this important perspective, which has enabled us to place our findings in a broader mechanistic context.
We are grateful to the reviewer for this important comment, which has allowed us to place our findings in a broader mechanistic context and outline directions for future research, including testing the relationship between importin α1-positive MN and established S-phase markers such as PCNA.
4) The FRAP data is not very compelling. While it is clear there are differences between the PN and MN dynamics, what is driving these differences? Are these differences meaningful to the biology of the MN or PN? It is unclear what this data is contributing to the conclusions of the paper. Also, if the mobility of the MN is plotted on the same graph as the PN, the differences in MN mobility might not look as compelling.
We respectfully emphasize that FRAP analysis is a key component of our study, as it provides important insights into the distinct dynamics of importin α1 in MN compared to PN.
In the revised manuscript, we included new experiments (now shown in Fig. 3A and 3C) that directly compare the recovery kinetics of importin α1 in PN and MN in the same cells. By plotting the PN and MN recovery curves side by side, we aimed to improve clarity and provide a direct visualization of the pronounced differences in importin α1 dynamics between these compartments.
Our FRAP results showed that importin α1 accumulated in both PN and MN but exhibited markedly reduced mobility in MN. These findings suggest that, unlike in the PN, canonical nucleocytoplasmic recycling of importin α1 is impaired in MN. Furthermore, the reduced mobility indicates that importin α1 is stably associated with chromatin or chromatin-associated factors in MN, consistent with our additional biochemical and imaging data showing preferential association with euchromatin (e.g., H3K4me3) and chromatin regulators.
Taken together, the FRAP data provide functional evidence that complements our structural and molecular analyses, supporting our central conclusion that importin α1 accumulation in MN defines a restricted chromatin environment that influences the accessibility of DNA repair and sensing factors.
5) In Results (line 117), you state that "the cytoplasm of those cell lines emitted quite strong signals" for Importin α1, but that phrasing is a little confusing. Yes, Importin α1 is in present the cytoplasm in most cells, but it appears you are referring to the enrichment in MN. I would recommend re-phrasing this statement to make your intent clearer.
As the reviewer rightly noted, the original phrasing, "the cytoplasm of those cell lines emitted quite strong signals," was misleading, as it could suggest a broad cytoplasmic distribution of importin α1. Our observations showed that importin α1 accumulated specifically in MN located within the cytoplasm, but not in the cytoplasmic regions. To clarify this, we revised the Results section (page 7, lines 125-127) to read: " Next, we performed indirect immunofluorescence (IF) analysis on human cancer cell lines, including MCF7 and HeLa cells. Notably, we found that importin α1 accumulated prominently in MN located within the cytoplasm (MCF7 cells, Fig. 1B; HeLa cells, Fig. 1C; yellow arrowhead). " .
We believe that this revised wording more accurately reflects our findings and addresses the reviewer's concerns.
6) In Results (line 135, Figure S2E,F), the ratio of high, low or no Importin α1 intensity is confusing. Is this percentage relative to the total number of MN? It Is unclear what is meant by "whole number" of MN. Is Importin α1 intensity quantified or is it subjective?
We apologize for the confusing terminology used in the original manuscript for Supplemental Fig. S2 and thank the reviewer for pointing it out. Although the reviewer did not specifically comment on the classification of importin α1 signal intensity as "high" or "low," we recognized that this approach relied on subjective visual assessment and lacked clearly defined thresholds. To improve clarity and objectivity, we have removed this classification and now analyze importin α1 localization in MN as simply positive or negative (revised Supplemental Fig. S2E). The previous graph (original Fig. S2F) was deleted. In addition, the frequency of Importin α1-positive MN has been reported in the Results section of the main text (page 8). We believe that these revisions have improved the clarity and reproducibility of our data presentation.
7) Figure 2C is confusing. Are you counting MN with co-localization of Importin α1 and these factors? Please clarify.
Figure 2C shows the percentage of importin α1-positive MN that displayed localization of importin β1, CAS, or Ran based on IF analysis. In other words, it represents the co-localization rates of these transport factors specifically within the subset of MN positive for importin α1. To improve clarity, we revised the y-axis label in Fig. 2C to "Localization in Impα1-positive MN (%)" and modified the figure legend accordingly. We have clarified this point in the Results section (page 9). We believe that these revisions resolve the confusion and clarify the scope of the analysis.
8) Figure S3D quantification is very confusing and unclear. Also, how is this normalized? Are you controlling for total signal in each cell? And can the results of this experiment give you any mechanistic insight as to what is regulating MN localization beyond the interpretation of "MN localization is distinct from PN localization"? The "C-mutant" appears quite a bit different than the others. What might that indicate about the role of CAS/CSE1L in MN enrichment?
We apologize for the confusion caused by the quantification in the Supplemental Fig. S3D (now revised as Fig. S4D). This figure shows the relative enrichment of EGFP-importin α1 in MN compared with that in PN for wild-type and mutant constructs. To control for nuclear size, fluorescence intensity was measured using a fixed circular ROI (1.5-2.0 µm in diameter) placed in both the MN and PN of the same cell, and MN/PN intensity ratios were directly plotted for individual cells (n = 8 per condition). This procedure is described in detail in the Results section (page 10).
Regarding the C-mutant, the reduced MN/PN ratio primarily reflects increased importin α1 accumulation in the PN rather than a reduced retention in the MN. As discussed in the revised manuscript (page 18), this suggests that CAS/CSE1L-mediated nuclear export is active in the PN but may be impaired or uncoupled in the MN, possibly due to differences in nuclear envelope integrity or chromatin context. We believe that this clarification addresses the reviewer's concerns and highlights the mechanistic implications of the C-mutant phenotype.
9) For Figures 3A,B and S4, are these images of single z-slices or projections? It would be helpful to clarify for your interpretations as to whether they are truly partial or diffuse or the membrane is in another z-plane. Also, how does the localization of Importin α1 different or similar to other factors that localize to MN with a compromised nuclear envelope, such as cGAS? If it is based on epigenetic marks, it should be different than cGAS, which primarily binds non-chromatinized DNA.
We thank the reviewer for this valuable suggestion. All images shown in Figs 3A, 3B, and S4 in the original manuscript (now revised as Fig. 4A and 4B, with the original Fig. S4 omitted) were derived from single optical sections rather than projections. We would like to emphasize that similar discontinuities in signals for lamin proteins (including laminB1 and laminA/C) were consistently observed across multiple cells and independent experiments, indicating that these observations are not due to an artifact of image acquisition or a missing z-plane, but rather reflect a genuine partial loss of the MN membrane.
In contrast to cGAS, which predominantly binds non-chromatinized DNA in ruptured MN, our data indicate that importin α1 preferentially localizes to MN regions enriched in euchromatin-associated histone modifications, such as H3K4me3. The new data presented in Fig. 8 further strengthen this point by directly comparing importin α1 with DNA-recognizing proteins such as cGAS and RPA2, which preferentially localize to MN lacking importin α1. Together, these results highlight that importin α1-positive MN constitute a distinct subset characterized by chromatin-associated localization and reduced accessibility to DNA repair and sensing proteins.
10) In Results, it is unclear how Fig. 7B was calculated. Are the authors qualitatively assessing if RAD51 is there or looking for MN enrichment relative to PN? Additionally, in Fig. 7C, RAD51 localization is diffuse. It should be enriched in foci. I would recommend the authors repeat this experiment using pre-extraction then quantify RAD51 foci number and/or intensity.
For the quantification shown in Fig. 7B of the original manuscript, we acquired images containing approximately 15-50 cells per condition and counted all the micronuclei (MN) in those fields. The percentage of RAD51-positive MN relative to the total MN was calculated. In the revised manuscript, we further refined this analysis by classifying RAD51-positive MN into two categories based on signal intensity: weak (Cell #1 type) and strong (Cell #2 type). For each condition, nine independent fields were analyzed (302 MN in untreated cells and 213 MN in etoposide-treated cells). This quantification revealed that etoposide treatment preferentially increased the proportion of MN with strong RAD51 accumulation (Fig. 7C, right panels), indicating enhanced DNA damage in MN. Thus, our analysis was quantitative rather than qualitative, based on systematic counting across multiple fields.
Regarding the reviewer's suggestion of pre-extraction, we believe that this approach is technically difficult because MN are structurally fragile. Importantly, in the subset of MN with strong RAD51 accumulation, RAD51 was clearly present in foci rather than diffuse signals, as shown in the high-magnification images (Fig. 7E).
Finally, in response to Reviewer #1, we performed a new quantitative analysis (Fig. 7F) focusing on the frequency of strongly RAD51-positive MN in relation to importin α1 status. This analysis confirmed the mutually exclusive relationship between RAD51 and importin α1 in MN and further strengthened our conclusions.
11) In line 264, "notably" is misspelled.
Thank you for pointing this out. We have corrected the spelling.
12) In line 303, "scenarios" should be changed to the singular form.
Thank you for this confirmation. We have corrected this to "scenario".
13) In Figure legend, line 571-582, H3K27me3 is shown in Figure 4D, but the written legend does not mention this mark.
We have added the marks in the legend for Fig. 5E.
Significance: Overall, this paper shows compelling evidence for micronuclear localization of regulators of nuclear export, notably Importin α1. Of note, this occurs in subsets of MN that lack an intact nuclear envelope. And while it has been appreciated that compromised micronuclear envelopes lead to genomic instability, this is one of the first that demonstrate alteration in the nuclear envelope may disrupt import or export of nuclear proteins into micronuclei.
A limitation of the study is that much of the work is based on immunofluorescence and lacks mechanism. While there is much correlative data showing that Importin α1 localizes to micronuclei with compromised envelopes, it is unclear whether Importin α1 drives micronuclear collapse or it is downstream of this process. Additionally, Importin α1 micronuclear localization anti-correlates with RAD51 but does colocalize with other DNA replication factors, yet it is unclear whether their localization is dependent on Importin α1 or its role in nuclear export. Currently, the audience for this manuscript would be focused to those interested in micronuclei. If these concerns about an active role for Importin α1 in micronuclear export are resolved, it would greatly increase the impact of this manuscript to those interested more broadly in genomic instability, DNA repair, and cancer.
We thank the reviewer for positively evaluating our study and highlighting the importance of defining the biological significance of our findings. In the revised manuscript, we incorporated new data (Fig. 8) demonstrating that importin α1-positive MN are mutually exclusive not only with RAD51 but also with RPA2 and cGAS. These results clearly establish importin α1-positive MN as a distinct subset, defined by the enrichment of chromatin-associated proteins, while being largely inaccessible to canonical DNA repair and DNA-sensing factors.
Consistent with this, our FRAP experiments and analysis of the CAS/CSE1L-binding mutant (C-mut) further indicated that the recycling dynamics of importin α1 were altered in MN compared to PN. In addition, importin α1 was enriched in lamin-deficient areas of MN, where electron microscopy revealed a fragile nuclear envelope morphology. Together with prior evidence, as discussed in the revised manuscript that recombinant importin α can inhibit nuclear envelope assembly in Xenopus egg extracts (Hachet et al, 2004), these findings raise the possibility that high local concentrations of importin α1 may actively contribute to impaired nuclear envelope formation or stability in MN.
Such a distinct MN state may have important biological consequences. By limiting the access of DNA repair and DNA-sensing proteins, importin α1 accumulation may influence chromothripsis and immune activation, which, in turn, could play a role in tumor progression and genome instability. We believe that the identification of importin α1 as a marker defining such a restricted MN environment represents a conceptual advance that extends the relevance of our study beyond the MN field to the broader areas of genome instability, DNA repair, and cancer biology. We are grateful to the reviewer for encouraging us to strengthen the framing of our work, which has helped us clarify the novelty and impact of our findings.
Reviewer #3
Summary:
This study reports that importin alpha isoforms enrich strongly in a subset of micronuclei in cancer cells and uses mutagenesis and immunostaining to define how this localization relates to importin alpha's nuclear transport function. This enrichment occurs even though importin-alpha-positive micronuclei also contain Ran and the importin alpha export factor CSE1L, indicating that importin a enrichment is not simply a consequence of the absence of components of the nuclear transport machinery that control its localization. Mutagenesis of importin a indicates that Mn enrichment persists even when the importin beta binding and NLS binding capacities of imp a are impaired. Potential importin alpha interacting proteins are identified by proteomics, although the relationship of these potential binding partners to micronucleus localization is unclear.
In Figure S3, the authors show that mutagenesis of importin alpha's CSE1L binding domain decreases the ratiometric enrichment in Mn vs. Pn. However, is this effect occurring because th CSE1L binding mutant decreases Mn enrichment, or increases Pn enrichment? It seems that the latter is possible based on the images shown. If the Pn specifically becomes brighter on average in cells expressing the C-mut, while Mn remain similar in fluorescence intensity, that might suggest that CSE1L has less of an effect on importin alpha export in Mn compared to Pn.
We appreciate the reviewer's insightful observations. In the revised analysis (now presented in Supplemental Fig. S4D), we quantified EGFP-importin α1 intensities in both PN and MN using fixed circular regions of interest. This revealed that the reduced MN/PN ratio observed in the CSE1L-binding mutant (C-mut) was mainly due to an increase in the PN signal rather than a decrease in the MN signal. These results are consistent with the reviewer's suggestion and indicate that CSE1L-mediated nuclear export is functional in PN but has a limited impact on MN.
Importantly, this interpretation is supported by our FRAP experiments (Fig. 3), which show that importin α1 recycles normally in the PN but exhibits markedly reduced mobility in the MN. Together with our proteomic and colocalization analyses (Fig. 6), which identified importin α1 association with chromatin regulators such as PARP1 and SUPT16H/FACT, these findings suggest that importin α1 accumulates in MN not only because the recycling machinery is uncoupled but also because it forms stable interactions with chromatin-associated proteins. As discussed in the revised manuscript, this dual mechanism provides a plausible explanation for the persistent retention of importin α1 in MN and its role in defining a distinct MN environment.
It is unclear from the text or the methods whether RIME identification of importin-alpha binding partners is performed in reversine-treated cells, which would increase the proportion of importin alpha in Mn, or in untreated cells. In either case, it seems likely that the majority of interactors identified would be cargoes that rely on importin alpha for import into the Pn. The rationale for linking these potential interactions to the Mn is unclear. While some of these factors are indeed shown enriched in Mn in Figure 5, the significance of this is also unclear. These points should be clarified.
We thank the reviewer for raising this important point. The RIME assay was performed using whole-cell extracts from untreated wild-type MCF7 cells, which primarily identified importin α1-associated nuclear cargo proteins. To assess their potential relevance to MN, we screened the RIME candidates using immunofluorescence data provided by the Human Protein Atlas database and experimentally validated those showing clear MN localization by colocalization with importin α1. This two-step approach enabled us to highlight importin α1 interactors that are functionally relevant to MN biology rather than general nuclear cargoes.
In response to the reviewer's concerns, we revised the Results section to clarify this rationale. Specifically, we added the explanation that "As importin α1 interactors are typically nuclear proteins, it is plausible that they reside not only in the primary nucleus but also in the MN. To test this possibility, we screened the identified candidates for MN localization using immunofluorescence images provided by the Human Protein Atlas (HPA) database (Pontén et al, 2008; Thul et al, 2017)." (page 14, lines 294-297).
This is consistent with the idea that a wide range of nuclear proteins carrying NLS motifs can recruit importin α1 into the micronuclei, where they reside. This protein-driven enrichment of importin α1 may create a restricted microenvironment in which canonical DNA repair and sensing proteins, including RAD51, RPA2, and cGAS, are excluded, thereby defining a distinct subset of micronuclei with limited genome surveillance capacity.
In Figure 6, the authors perform FRAP of importin alpha in Mn and show that it recovers much more slowly in Mn than in Pn. However, it appears from the images shown that the entire Mn was photobleached in each FRAP experiment. It thus is unclear whether the slow FRAP recovery is limited by slow diffusion of importin alpha within Mn/on Mn chromatin or impaired trafficking of importin alpha into and out of Mn. These distinct outcomes have distinct implications: either importin alpha is immobilized on Mn (eu)chromatin, or alternatively importin alpha is poorly transported into / out of Mn. This ambiguity could be resolved by bleaching a portion of a Mn and testing whether importin alpha diffuses within a single Mn.
We thank the reviewer for this insightful comment regarding the interpretation of FRAP data. As the reviewer rightly pointed out, the original FRAP design-where the entire MN was photobleached-does not allow for a clear discrimination between the intranuclear immobilization of importin α1 and impaired trafficking into or out of the MN.
In line with a similar suggestion from Reviewer #1, we attempted partial photobleaching of MN to evaluate whether importin α1 can diffuse within MN independently of nucleocytoplasmic transport. However, due to the small size of MN, precise targeting is technically challenging and recovery is often unreliable, with some MN even exhibiting partial recovery during the bleaching process itself. These data were not included in the revised figures; however, we provide representative examples as reviewer-only figures to illustrate these technical limitations.
To further clarify the nuclear transport dynamics of importin α1, we redesigned our FRAP experiments to fully photobleach both the PN and MN within the same cells under identical conditions. These results, presented in revised Fig. 3A and 3C, demonstrate a markedly slower recovery of importin α1 in MN compared to PN, strongly suggesting that nucleocytoplasmic recycling of importin α1 is impaired in MN. Moreover, the reduced mobility of importin α1 in the MN is consistent with stable chromatin binding, limiting its ability to diffuse freely within the nuclear space.
We believe that this additional analysis, prompted by the reviewer's comment, significantly strengthens the mechanistic interpretation of our FRAP data.
References
Crasta K, Ganem NJ, Dagher R, Lantermann AB, Ivanova EV, Pan Y, Nezi L, Protopopov A, Chowdhury D, Pellman D (2012) DNA breaks and chromosome pulverization from errors in mitosis. Nature 482: 53-58
Hachet V, Kocher T, Wilm M, Mattaj IW (2004) Importin α associates with membranes and participates in nuclear envelope assembly in vitro. EMBO J 23: 1526-1535
Martinez-Olivera R, Datsi A, Stallkamp M, Köller M, Kohtz I, Pintea B, Gousias K (2018) Silencing of the nucleocytoplasmic shuttling protein karyopherin a2 promotes cell-cycle arrest and apoptosis in glioblastoma multiforme. Oncotarget 9: 33471-33481
Vietri M, Schultz SW, Bellanger A, Jones CM, Petersen LI, Raiborg C, Skarpen E, Pedurupillay CRJ, Kjos I, Kip E, Timmer R, Jain A, Collas P, Knorr RL, Grellscheid SN, Kusumaatmaja H, Brech A, Micci F, Stenmark H, Campsteijn C (2020) Unrestrained ESCRT-III drives micronuclear catastrophe and chromosome fragmentation. Nat Cell Biol 22: 856-867
Wang CI, Chien KY, Wang CL, Liu HP, Cheng CC, Chang YS, Yu JS, Yu CJ (2012) Quantitative proteomics reveals regulation of karyopherin subunit alpha-2 (KPNA2) and its potential novel cargo proteins in nonsmall cell lung cancer. Mol Cell Proteomics 11: 1105-1122
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
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This study reports that importin alpha isoforms enrich strongly in a subset of micronuclei in cancer cells and uses mutagenesis and immunostaining to define how this localization relates to importin alpha's nuclear transport function. This enrichment occurs even though importin-alpha-positive micronuclei also contain Ran and the importin alpha export factor CSE1L, indicating that importin a enrichment is not simply a consequence of the absence of components of the nuclear transport machinery that control its localization. Mutagenesis of importin a indicates that Mn enrichment persists even when the importin beta binding and NLS binding capacities of imp a are impaired. Potential importin alpha interacting proteins are identified by proteomics, although the relationship of these potential binding partners to micronucleus localization is unclear.
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
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Summary:
The authors have shown that Importin α1, a nuclear transport factor, is enriched in subsets of micronuclei (MN) of cancer cells (MCF7 and HeLa) and, using FRAP, has an altered dynamics in MN. Moreover, the authors have shown that these levels of Importin α1 in the MN are likely not due to its traditional role for signal-dependent protein transport, as suggested by immunofluorescence of other factors important for this function. Additionally, cargo dynamics carrying NLS or NES signals were disrupted in Importin α1-positive micronuclei. Importin α1-positive micronuclei also appear to have a disrupted nuclear envelope, potentially explaining some of these cargo disruptions. The authors also demonstrated that Importin α colocalizes with proteins important for DNA replication, and p53 signaling using RIME, followed by immunofluorescence. Lastly, the authors show that Importin α and RAD51 have mutual exclusivity in the micronuclei.
Major comments:
Minor Comments
Overall, this paper shows compelling evidence for micronuclear localization of regulators of nuclear export, notably Importin α1. Of note, this occurs in subsets of MN that lack an intact nuclear envelope. And while it has been appreciated that compromised micronuclear envelopes lead to genomic instability, this is one of the first that demonstrate alteration in the nuclear envelope may disrupt import or export of nuclear proteins into micronuclei.
A limitation of the study is that much of the work is based on immunofluorescence and lacks mechanism. While there is much correlative data showing that Importin α1 localizes to micronuclei with compromised envelopes, it is unclear whether Importin α1 drives micronuclear collapse or it is downstream of this process. Additionally, Importin α1 micronuclear localization anti-correlates with RAD51 but does colocalize with other DNA replication factors, yet it is unclear whether their localization is dependent on Importin α1 or its role in nuclear export. Currently, the audience for this manuscript would be focused to those interested in micronuclei. If these concerns about an active role for Importin α1 in micronuclear export are resolved, it would greatly increase the impact of this manuscript to those interested more broadly in genomic instability, DNA repair, and cancer.
Reviewer's areas of expertise: Genomic instability, cancer epigenetics, and mitosis
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Summary:
Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate). Miyamoto et al. report that importin α1 is highly enriched in a subfraction of micronuclei (about 40%), which exhibit defective nuclear envelopes and compromised accessibility of factors essential for the damage response associated with homologous recombination DNA repair. The authors suggest that the unequal localization and abnormal distribution of importin α1 within these micronuclei contribute to the genomic instability observed in cancer.
Major comments:
Are the key conclusions convincing?
The conclusions drawn by the authors would benefit from additional supportive experiments and a more detailed explanation. 1. It is crucial to quantitatively assess the localization of importin α1 in micronuclei (MN) across non-transformed MCM10A cells compared to transformed cell lines (MC7, HeLa, and MDA-MB-231). This analysis would help determine whether the localization of importin α1 in MN correlates with genomic stability in human cancer cells 2. While the authors provide some evidence indicating partial disruption of nuclear envelopes in MN (Figures 3 and S4), it is noteworthy that this phenomenon also occurs in importin α1-negative MN. Furthermore, according to the figure legends, the data presented in both figures stem from a single experiment. Current literature suggests that compromised nuclear envelope integrity is one of the major contributors to genomic instability, mediated through mechanisms such as chromothripsis and cGAS-STING-mediated inflammation arising from MN. Therefore, a more comprehensive quantification of nuclear envelope integrity-ideally comparing non-transformed MCM10A cells with transformed cell lines (MC7, HeLa, and MDA-MB-231)-is necessary to substantiate the connection between aberrant importin α1 behavior in MN and chromothripsis processes, as well as regulation of the cGAS-STING pathway linked to genomic instability in cancer cells. 3. The schematic illustration presented in Figure 8 does not adequately summarize all findings from this study nor does it clarify how the localization of importin α1 within MN might hypothetically influence genome stability. Although it is reasonable to propose that "importin α can serve as a molecular marker for characterizing the dynamics of MN" (Line 344), the authors assert (Line 325) that their findings, along with others, have "potential implications for the induction of chromothripsis processes and regulation of the cGAS-STING pathway in cancer cells." However, they fail to provide a clear or even hypothetical explanation regarding how their findings contribute to these molecular events. To address this gap, it would be essential for them to contextualize their results within existing literature that explores and links structural integrity deficits or aberrant DNA replication/damage responses in MN with chromothripsis and inflammation (e.g., PMID: 32601372; PMID: 32494070; PMID: 27918550; PMID: 28738408; PMID: 28759889). 4. Fig. 4D does not support the idea that importin α1 is euchromatin enriched: H3K9me3, H3K4me3 and H3K37me3 seem to be all deeply blue.
Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?
Indeed, the data presented by the authors do not adequately support a direct link between the presence of importin α1 in MN and genomic instability in human cancer cells. While the experimental correlations provided may not substantiate this connection definitively, they do lay a foundation for a grounded hypothesis and suggest the need for further research to explore this topic in greater depth. Additionally, it is worth noting that the evidence contributes to the growing list of nuclear proteins exhibiting abnormal behavior in micronuclei (MN). This highlights the significance of studying such proteins to understand their roles in genomic stability and cancer progression.
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.
Additional experiments are necessary to quantitatively assess the localization of importin α1 in micronuclei (MN) across non-transformed MCM10A cells and transformed cell lines (MC7, HeLa, MDA-MB-231). This analysis would help determine whether the localization of importin α1 in MN correlates with genomic stability in human cancer cells. The authors claim that importin α1 preferentially localizes to euchromatic areas rather than heterochromatic regions within MN. While this assertion is supported by the immunofluorescence (IF) images presented in Figures 4A/B and S5A/B, it remains less clear for Figure S5C/B. To strengthen this claim, providing averages of IF distributions from multiple cells across independent experiments would be beneficial to draw more robust conclusions.
Furthermore, ChIP-seq data are presented to support the idea that importin α1 preferentially distributes over euchromatin areas in MN. However, as described, the epigenetic chromatin status indicated by these ChIP-seq experiments reflects that of the principal nucleus (PN), not specifically the status within MN in MCF7 cells. Given that MN represent only a small fraction of the cell population under normal culture conditions-likely less than 5% for HeLa cells as shown in Figure S2D-the relevance of this data is limited. Additionally, according to data presented in Figure 1B, importin α1 does not localize or distribute within the PN as it does in MN in MCF7 cells. Therefore, further experiments should be conducted to substantiate that importin α1 preferentially targets euchromatin areas within MN and to compare this distribution with that observed in the principal nucleus. Such studies could reveal potential abnormalities regarding the correlation between epigenetic chromatin status and importin α distribution in MN. To support the hypothesis that importin α1 inhibits RAD51 accessibility within MN, Figures 7D and E should be supplemented with thorough quantification and statistical analysis based on at least three independent experiments. This additional data would enhance confidence in their findings regarding RAD51 accessibility inhibition by importin α1.
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.
The additional experiments proposed are controls and direct comparisons using the same techniques and experimental designs used by the authors, so it is reasonable that the authors can carry them out within a realistic timeframe.
Are the data and the methods presented in such a way that they can be reproduced?
Given the importance of reproducibility and the need to evaluate results based on imaging and quantitation, I strongly recommend that the authors include a detailed description of the optical microscopy procedures utilized in their study. This should encompass imaging conditions, acquisition settings, and the specific equipment used. Providing this information will enhance transparency and facilitate reproducibility. For reference, some valuable guidance on essential parameters for reproducibility can be found in Heddleston et al. (2021) (doi:10.1242/jcs.254144). Incorporating these details will not only strengthen the manuscript but also support other researchers in reproducing the findings accurately.
Are the experiments adequately replicated and statistical analysis adequate?
Many of the plots and values in the manuscript lack appropriate statistical analysis, including p-values, which are not detailed in the figures or their legends. Furthermore, the Statistical Analysis section does not provide adequate information regarding the specific statistical tests employed or the criteria used to determine which analyses were applied in each case. To enhance the rigor and clarity of the study, it is essential that these issues be addressed prior to publication. A comprehensive presentation of statistical analysis will improve the reliability of the findings and allow readers to better understand the significance of the results. I recommend that the authors revise this section to include detailed explanations of all statistical methods used, along with corresponding p-values for all relevant comparisons.
Minor comments:
Specific experimental issues that are easily addressable.
The authors claim that importin α1 exhibits remarkably low mobility in the micronuclei (MN) compared to its mobility in the principal nucleus (PN), as illustrated in Figure 1. However, based on the experimental design, this conclusion may not be appropriate. In the current setup, the FRAP experiment conducted in the PN measures the mobility of importin α1 molecules within the cell nucleus, where the influence of nuclear transport is likely negligible. Conversely, in the MN experiments shown, all molecules of importin α1 are bleached within a given MN. Consequently, what is being measured here primarily reflects the effects of nuclear transport rather than intrinsic molecular mobility. To accurately compare kinetics of nuclear transport, it would be essential to completely bleach the entire PN. If measuring molecular mobility between MN and PN is desired, only a small fraction of either MN or PN area/volume should be bleached during FRAP analysis. Additionally, it would be beneficial to include measurements of mobility for other canonical nuclear transport factors (e.g., RAN, CAS, RCC1) for comparative purposes. This broader context would allow for a more comprehensive understanding of importin α1 behavior relative to other factors involved in nuclear transport. Finally, utilizing cells that exhibit importin α1 signals in both PN and MN could further strengthen comparisons and provide more robust conclusions regarding its mobility dynamics.
Are prior studies referenced appropriately?
Prior studies are referenced appropriately in general, but the authors missed some references (PMID: 32601372; PMID: 32494070; PMID: 27918550; PMID: 28738408; PMID: 28759889) that I consider key to put the present findings in frame with previous works which link the lack of structural integrity and/or aberrant DNA replication/damage responses in MN with Cchromothripsis and inflammation.
Are the text and figures clear and accurate?
The figures presented in the manuscript are clear; however, where plots are included, they require appropriate statistical analysis. It is essential to display p-values on the plots or within their legends to provide readers with information regarding the significance of the results. Including this statistical information will enhance the interpretability of the data and strengthen the overall findings of the study. I recommend that the authors revise these sections accordingly before publication.
Do you have suggestions that would help the authors improve the presentation of their data and conclusions?
Micronuclei (MN) primarily arise from defects in mitotic progression and chromatin segregation, often associated with chromatin bridges and/or lagging chromosomes. MN frequently exhibit DNA replication defects and possess a rupture-prone nuclear envelope, which has been linked to genomic instability. The nuclear envelope of MN is notably deficient in crucial factors such as lamin B and nuclear pore complexes (NPCs). This deficiency may be attributed to the influence of microtubules and the gradient of Aurora B activity at the mitotic midzone, which inhibits the recruitment of proper nuclear envelope components. Additionally, several other factors may contribute to this process: for instance, PLK1 controls the assembly of NPC components onto lagging chromosomes; chromosome size and gene density positively correlate with the membrane stability of MN; and abnormal accumulation of the ESCRT complex on MN exacerbates DNA damage within these structures, triggering pro-inflammatory pathways. The work presented by Dr. Miyamoto and colleagues reveals the abnormal behavior of importin α1 in MN during interphase. According to their findings, it is reasonable to consider importin α1 as a molecular marker for characterizing MN dynamics. Furthermore, it could serve as a potential clinical marker if the authors provide additional experiments demonstrating significantly different localization patterns of importin α1 in transformed cells (e.g., MC7, HeLa, MDA-MB-231) compared to non-transformed cells (e.g., MCM10A). While the authors present some evidence indicating partial disruption of nuclear envelopes in MN (Figures 3 and S4), it is noteworthy that this phenomenon also occurs in importin α1-negative MN. Moreover, according to the figure legends, data for both figures originate from a single experiment. As such, convincing evidence linking the aberrant behavior of importin α1 in MN with chromothripsis processes or regulation of the cGAS-STING pathway-and its implications for genomic instability in cancer cells-remains lacking. Overall, it is not entirely clear what significance this advance holds for the field; while there are conceptual contributions made by this work, they do not appear sufficiently robust at this time. Further research is needed to clarify these connections and strengthen their conclusions regarding importin α1's role in MN dynamics and genomic instability. - State what audience might be interested in and influenced by the reported findings.
Scientist and health care professionals that research on mechanism of genomic instability and cancer - 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.
Mitosis, mitotic chromatin decondensation, nuclear reformation, hematopoietic cancers, light microscopy, image analysis.
Why can't I use Artificial Intelligence tools to generate answers? - Help Center. 2023. URL: https://stackoverflow.com/help/ai-policy (visited on 2023-12-08).
This link allows readers to understand certain policies about the general use of ai. It mentions how certain social media platforms or general apps (ex: stack overflow) are banning the overall use of ai because they believe one's original work is a reflection of themselves, and that you have to earn your freedom to have an opinion. It then begins to list certain types of ai tools that are seen as forbidden; it also mentions that ai has a limit, and there are ways for their programmers to know if what is shown is ai or not.
Christie Aschwanden. Science Isn’t Broken. FiveThirtyEight, August 2015. URL: https://fivethirtyeight.com/features/science-isnt-broken/ (visited on 2023-12-05).
The article shows how it is much harder than it seems to correctly access data over a large scale. It is almost impossible to assume that two pieces of data correlate with each other. There have been examples that I was given when I was learning about this concept in Stats class where the consumption of margarine almost identically followed the rate of divorce in Maine. Clearly there is no true correlation between the two but it is a good reminder that it is really difficult to find true evidence of data correlation.
Are you surprised by any of the things that can be done with data mining? Do you think there is information that could be discovered through data mining that social media companies shouldn’t seek out (e.g., social media companies could use it for bad purposes, or they might get hacked and others could find it)?
I am not really surprised by most of the things that can be done with data mining because we live in an advanced society to a point where there's ai and programs that allow companies thrive. One thing I am surprised about data mining is how people can use it to track trends in terms of stocks or the general economy because at what point are they cheating the system? I think information that shouldn't be available for companies to seek in terms of social media are looking for popular individuals to use for campaigns or for leveraging marketing.
I will not link to the photo here. Allow me my parental illusions of protection. I reprint it here on social media only in doctored form. I didn’t know what to use to cover her eyes.
Responsible parenting
Kinship requires both an understanding of the self-in-relation andthe ability to project, to position, oneself as part of an extended networkof relatives. We know our relations by virtue of our lived experiences, aswe understand those experiences in the context of cultural and historicalparadigms that give them substance. In this, relations expand beyond thematerial and toward the unknown—they are not just of this world, but ofthe beyond as well. They exist in the present, and toward iterative becom-ings that are neither past nor future, but both simul taneously. Relations area form of reckoning with time, space, and what vibrates between bodies—love, fear, joy, hope. Relations open pathways to thinking and being inreciprocity
This is how I envision someone who uses the future imaginary as a theoretical framework to define a relationship from an indigenous perspective. Viewing relationships as a form of kinship with a reciprocal balance, where time is cyclical, is very "futuristic" in a sense. Yet, the grounding of indigenous culture and history anchors kinship to the here and now, making it relevant.
In academia, we scholars are often taught to distance ourselves from our research
I find it frustrating that academia teaches scholars to distance themselves from their research subject. Research becomes extractive and stagnant if a scholar is only looking to write a paper and talk about something, instead of really being immersed and have genuine care for what they are researching, or even having it be related to our own communtiities and lived experiences. When we separate our studies from the real world it becomes isolated and pointless.
ublic intervention is also necessary when a womandelivers her child, whether by the hands of a doctor, midwife, ordoul
public
when designers seek to make devices more 'user-friendly' and in the process disguise their mode of operation, it becomes all the more important to investigate the role of cognitive artefacts within archaeology and the relationships and dependencies that exist within the digital ecosystem we are creating.
GIS interfaces are designed to simplify complex modeling decision behind neat buttons and sliders. My documentation resists that "user-friendly opacity" by explaining the slope factor, water barrier weight, and clusteering radius so that others could interpret or replicate the Silk Road model on their critical grounds.
As survey instrumentation becomes digital and increasingly automated, so the level of human engagement changes: the cognitive load is transferred to the digital device
In my Silk Road project, this interpretive workload is divided between terrain-cost and clustering algorithms. The model “thinks” through slope resistance and caravanserai density, freeing me to consider problems of historical interpretation rather than raw computation. The shift represents another key aspect of Huggett’s cognition migrating into the tool.
Understanding the landscape of competitors not only helps inform your design decisions but it also helps inform the overall product strategy. A UX competitive analysis uncovers valuable opportunities to create a superior product and stand out from the competition.
I agree with this conclusion and find it highly practical, especially given how saturated the modern market is. In most industries today, there are already countless products and services competing for users’ attention, so understanding what others are doing is essential before proposing something new. Conducting a competitive analysis helps designers identify what works, what doesn’t, and where the gaps or pain points exist that could make users choose your design over existing ones. I also think this approach is efficient because learning from similar products is a low-stakes but high-value way to begin the design process. It allows you to avoid repeating mistakes that competitors have already made while also inspiring better, differentiated solutions.
Individualisation considers the level of adjustment or customisation available to the agent. At one extreme, this may tailor the device to the individual agent such that it becomes difficult for another to use it, or to adapt it for another task. On the other hand, a device may be easy to pick up, use and understand with little scope or need for improved efficiency or effectiveness, and hence it is not especially individualised. Furthermore, agent and artefact may both be adapted together in what Heersmink calls entrenchment, where the cognitive artefact is individualised according to the user's needs, and in turn the user's behaviour and cognition are adapted by the device in a manner reminiscent of the McLuhanite 'We shape our tools and thereafter our tools shape us' (Culkin 1968, 60). (Heersmink 2012, 52-3; 2015, 590-1).
Cost-surface weights and clustering hyperparameters reflect my priors (slope, water gaps, caravanserai spacing). I’ll publish a config file and run ablations to avoid over-entrenching my personal settings.
Trust – we tend to trust the devices we employ (why would we use them otherwise?) but what is this trust based upon?
I have heard stories of AI programs being incorrect about things and this definitely makes me more cautious when using applications - I try to use them as a secondary source, something to use after information has already been gathered.
I'm curious to see if my trust in AI changes after being on the other side of things (not just a consumer), while trying to prove my hypothesis with a LLM trained by me.
Information flow between agent and artefact, including one-way flow (from artefact to agent, where we simply look at the artefact to extract the information we require), two-way flow (typically where we store information on the artefact and subsequently retrieve it); reciprocal flow (a two-way flow that is incremental, additive, and cyclical, so there is a continuous information exchange); and system flow (where there are multiple agents and multiple artefacts cooperating in the exchange) (Heersmink 2012, 49-50; 2015, 583-6).
This specifically correlates to the hypothesis I will feed to the LLM relating to my topic - I want the LLM to analyze two historical artefacts and compare their relation to each other in order to figure out if one was influenced by the other. Information will be given to me from the LLM - if i train a program to search for this information, I will need to feed the program training/information to achieve an outcome.
They ignore the songs of other species.
How?
Overview Andreas, age 22, was completing his final year in college and was majoring in computer science. He had worked hard in order to prepare himself for a career in information technology, getting good grades with the hope of landing a job in a top company after graduation. He was the only son of a wealthy family. His father was a well-known lawyer in their average-size hometown and his mother was a cardiologist. Andreas had always received lots of attention from his parents, and they ensured that he got a good education and had everything he wanted. Andreas described his parents as being very strict and critical, requiring that he work hard and receive good grades in order to increase his chances of doing something valuable with his life. What triggered Andreas' s depression was an event that took place at the beginning of the semester. At the end of summer holidays, a renowned multinational information technology company launched a contest inviting all students in their final year of computer science to submit a project on an emerging topic. The prize for this contest was a well-paid 6-month internship with the company, which for Andreas would have been the perfect start to a fabulous career. Twenty internships were awarded among more than 200 students who submitted projects, and Andreas was not among them. This made him feel terrible, especially because he had told his parents about this opportunity because he was confident he would be selected. When he received the news about not having been accepted, he initially did not tell his parents about it or about the fact that he was so depressed, lying to them about not receiving the results each time they asked about it. As a result of being rejected for the award and lying to his parents, Andreas developed strong feelings of shame, guilt, and hopelessness, thinking that he would never be as he had been before. He saw himself as a failure both to himself and to his parents. He had tried to prove his worth by winning the internship, and now that opportunity was gone. Andreas came to therapy after what he described as the worst period of his life in which he felt deeply depressed and experienced suicidal ideation. However, he did not intend to commit suicide and did not make any attempt, stating that he was very afraid of these thoughts. When he came to therapy he had not been to class for more than 3 weeks, and in the previous month he had only gone from time to time in his better moments. In the past 3 weeks, however, the depression had gotten so intense that he barely got out of house. He spent his time sleeping, playing video games, and thinking intensely about his situation and the fact that he would not be able to complete his graduation thesis. In the initial session Andreas was introduced to the CBT model and behavioral activation, and in subsequent sessions he learned how to identify and dispute dysfunctional negative automatic thoughts. After the third session, Andreas started attending classes again and was able to study for winter exams, although he was very stressed about them. He also got up the courage to tell his parents that he had not received the award. He said that they were critical but did not dwell on it. In this fourth session the focus was on his deeper cognitions—the intermediate and core beliefs. I used Andreas' s thought records from the previous week to initiate further exploration of his thoughts using the downward arrow technique to access deeper beliefs. At the end of the session we developed a behavioral experiment to test the functionality of these beliefs. What follows is the transcript of the fourth session.
Both Andreas and Allison received CBT to challenge negative self beliefs, but Andreas’s therapy focused on perfectionism and conditional self-worth after losing an internship, while Allison’s addressed low self esteem and peer bullying. Andreas’s therapist targeted deep core beliefs, whereas Allison’s therapist used simpler thought challenging and behavior practice. Both learned to replace self criticism with healthier thinking and actions.
A crucial operational maxim is to "be stubborn on the vision and flexible on the details," acknowledging that this flexibility is necessary because the world is changing [1].
Important
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TEXT- This poster encourages people to focus less on the material aspect like tinsel and lights and instead welcoming others and showing compassion. This poster through the use of "holy" and "prayers" shows Christian values, reminding others that the true spirit of Christmas is love, connection not materials. The font is bond and overall makes someone focus on the text.
IMAGE- The background is diagonal gradient lines with yellow and sometimes orange, all coming together, symbolistic to people coming together. Lastly, there is a gradient of all the colors combined with the text "less tinsel more love" in cursive. This Overall the color usage gives off peace and more significance to the text.
The appetite for video podcasts is enormous. According to a recent study by Cumulus Media, 72 percent of podcast listeners say they prefer shows with video.
I think that this especially applies to my generation. It can be hard for us to just sit and listen to something without loosing focus. Our attention span is much greater when we can actually watch and see what's going on. That's what I think is so great about having this choice now to either just listen on Spotify or watch on Netflix.
“With video podcasts on the rise, our partnership with Spotify ensures we bring the full video versions of these top shows to Netflix and Spotify,” Lauren Smith, a vice president at Netflix, said in a statement. She added: “This offers more choice to creators and unlocks a completely new distribution opportunity.”
I didn't think about this at first how big of an opportunity this is for the creators of the podcasts being able to have their videos on Netflix. It really opens up a whole new audience for them considering the millions of people subscribed to Netflix. I think it's really cool that this not only is a great opportunity for Netflix but also the podcast creators.
The streaming giant announced a partnership with the audio company Spotify on Tuesday that would bring numerous video podcasts on sports, culture, entertainment and true crime to Netflix early next year.
As soon as I saw this article title I immediately was interested considering I use both Netflix and Spotify very often. I think this is actually super smart. Podcasts have increasingly became more and more popular, especially video versions where people can actually watch the podcast, so I imagine this will bring in a lot of money for the companies.
DA
In the final lines of the part (and the poem), we finally hear from the divine. I have established, throughout this part of the poem, an equality and symbiosis between the divine and the natural, whether that is the wind and the chapel or the thunder or the “third walking beside you.” With this in mind, the words from the Thunder, “DA,” stand out as a calling from the divine, perhaps a respite or a sign of holiness, in a waste land, where the lack or disappearance of a god has been repeatedly referenced. These words, from the Thunder to the readers and inhabitants of The Waste Land, perhaps signify an end to the perilous conditions that they have been living under, a savoir, at last, from the human-induced nightmare we have all been living in.
Ira’s reading of the line “DA” stuck out to me during tonight’s reading. In the narrative of the poem, we are presented with the lines “Then spoke the thunder/DA,” suggesting that this is, finally, “What the Thunder Said.” Interestingly, Ira’s reading of this line splits the term “DA” into the prefix for the three proceeding words, “datta,” “dayahadvam,” and “damyata.” All of which were meant to represent the interpretations of the thunder’s words to the different groups – gods, humans, and demons. What interested me the most about her annotation, however, was the question that she indirectly asks in the second paragraph, do we care more about the interpretations of the thunder’s words than the true words themselves? She further asks “what if “da” were intended to encompass all three meanings?”
With this in mind, it makes me wonder: To what degree do the Thunder’s words matter at all? Clearly, they acted as a stem, a savoir for the datta,” “dayahadvam,” and “damyatal;” however, the meanings and suffixes of these words were all human creations. Perhaps what Eliot is suggesting is that we don’t need to look for guidance or a savoir from our action-induced reality, perhaps we have the answers within ourselves, though they may seem to be too divine or grand for human creation and understanding. Do we need to look outward to find the solution to The Waste Land?
There is the empty chapel, only the wind’s home.
This line with an “empty chapel” is a direct reference back to Weston’s chapter on the Perilous Chapel. In some of the Grail legends, Gawain (or Perceval) stumble upon the empty chapel on their way to the Grail Castle. In Gawain’s legend, he finds himself stuck at a crossroads, deciding to take shelter in the chapel. Once inside, he sees a large hand and hears a voice from underneath the building. When he leaves, the night is clear. Perceval’s story is largely similar, however, in his version, there is a dead knight on the altar, slain by a Black Hand, which is actually the Devil, whom he fights to save the enchantment upon the chapel. This line, from Eliot’s poem, makes reference to these wandering knights, looking for shelter amid the storm, only to find further chaos inside.
This chapel, in the narrative of “What the Thunder Said,” acts as a supposed refuge for the wasted land outside – a world of rock and no water, unfit for human habitation. This chapel (an obvious religious reference) acts as one's connection to divinity and religion in the harsh environment. As a result of this connection, the wording of an “empty chapel” denies the existence of an omnipresent god among us (perhaps contradicting the “other one” who walks on the other side of the speaker’s partner). As a reference to the Grail Legend as well, this empty, God-less chapel also aligns well with the Devil’s presence in the Perilous Chapel. In both tales, the narrative follows a protagonist seeking refuge from their environment, only to face the wrath of divinity (or lack thereof). This contrast, between the natural forces and divine, begs the question of which is stronger? In the Grail legend, the two are at odds, with the knight forced to choose between the storm or death at the hand of the Black Hand. In the Waste Land, though, the force or presence of God is completely diminished, with “only wind’s home.” This suggests that the natural world, in all of its rocky and thunderous glory, holds power over the divine.
Furthermore, the second part of the phrase “only the wind’s home” provides two contrasting perceptions of the “empty chapel.” As it is written, Eliot marks the word “wind” with a possessive “‘s,” noting that the “empty chapel” is the home of the wind. While this reading suggests ownership of the chapel by the wind, another reading could be a conjunction between the “wind” and perhaps the word “is,” with the apostrophe used as a placeholder for the “i,” leading to a “wind’s home” that means the “wind is home.” While I am unsure what this could be suggesting, I think that it is cool to think about, especially given my contribution to the website on punctuation.
Conversely, Scholar Anthony Hu took this notion of an empty chapel as a continuation of the “collapse of towers – and of the ‘Unreal City.’” He said that “since churches only survive as witnesses of the replacement of divinity with human industrial progress, their destruction is reminiscent of the ruination of the gargantuan Tower of Babel, where the collective hubris of humans is met with devastating consequences.” I think these two opposing views of the Chapel – one rooted in civilization and industrialization, while the other harks back to tales from the 12th century – showcase the multiplicity and repetition of civilization, a cycle continually touched on by Eliot throughout The Waste Land. In his reading, the chapel stays as a religious figure, standing the test of time through its connection with God. In the Weston reference, though, the chapel is stripped of its religious significance–aligning more closely with the wind and surrounding forest than the “unreal cities.”
Datta: what have we given? My friend, blood shaking my heart The awful daring of a moment’s surrender Which an age of prudence can never retract By this, and this only, we have existed Which is not to be found in our obituaries Or in memories draped by the beneficent spider
This is quite a confusing section. Upon reading it, I was both captivated and extremely perplexed, however, I will try my best to unpack the significance of these lines. 1. Datta. A Hindu custom, "Datta" most nearly translates to "give", an act performed without the intention of receiving transactional reward. In TWL, the narrator asks, "what have we given?" (402). The question is rhetorical, for both the reader and the speaker know the answer: nothing at all. Humanity, as the narrator suggests, has grown incapable of generosity or surrendering selfishness. In doing so, they have strayed way from the ideals of religion or morality (in this case, Hindu customs), and have become estranged from both divine grace and one another. 2. However, the narrator also introduces a sort of hope for humanity's redemption. While acknowledging the depth of human selfishness, he exhibits a brief instance of grace: "The awful daring of a moment's surrender / Which an age of prudence can never retract" (405-6). In the selfless act of "a moment's surrender", human life finally achieves meaning, as existence, for Eliot, is not defined by the literal act of living, meaningless achievement, or worldly possessions, but in the moments in which people choose to open their hearts to others and offer genuine love and compassion Of course, this essential element of humanity remains invisible to history: it cannot be expressed in obituaries or in other physical elements of our legacy that we leave behind. However, what transcends history, what endures silently and often unnoticed, is what is actually the true essence of human existence: the act of giving and/or surrender. That is where the narrator locates the opportunity for redemption for a morally corrupt and disjunct mankind.
Damyata: The boat responded
Datta means "give," dayadhvam means "be compassionate," and damyata means "be self-controlling." Eliot's footnote cites these three Sanskrit words from the Brihadaranyaka Upanishad, where the thunder speaks "DA DA DA" to gods, humans, and demon. The reference to a boat in the damyata section (lines 418-422) deliberately contrasts with earlier water imagery. As Scholar Marisin observes, “Earlier references to 'death by water' and 'drowned sailors' immediately fills the mind with dread at the mere implication of the liquid, yet here the ‘sea was calm” and the hand is an “expert with sail and oar.” This shift from threatening to tranquil water happens because a prophetic voice can finally appear in the Wasteland. When the thunder speaks, it represents authentic divine revelation rather than Madame Sosostris's fraudulent fortune-telling. The spiritual chaos that has defined the poem momentarily stills, just like the sea. The fortune of the sailor takes on new meaning here. Madame Sosostris warned "Fear death by water" (line 55), and we saw Phlebas the Phoenician drowned in Part IV. But the damyata section reframes water entirely. The boat "responded / Gaily" to "controlling hands" (lines 418, 422). This isn't about technological mastery over nature but rather the heart "beating obedient" (line 421) to spiritual discipline. Damyata as self-control leads to harmony rather than drowning.
Ganga was sunken, and the limp leaves Waited for rain, while the black clouds Gathered far distant, over Himavant. The jungle crouched, humped in silence.
The first lines of the stanza stuck out to me, as a contrast from the final lines of the previous stanza where there is “a damp gust bringing rain.” Imagery of water abounds here, a break from the water/rock section found earlier, where the word “water” is hyper-present, but water itself is missing, creating a desert, or a waste land. In this passage the wind is “damp” and brings “rain,” water seeping into the imagery of the poem in reality. The imagery appears to continue in this passage, with the language of “sunken” and the mention of “Ganga,” another word for the river Ganges. However, upon closer inspection, the images here evoke the barren land of before, with rain clouds “distant,” leaves still “limp,” a landscape “waiting for rain.” The storm is on the horizon, anticipation plaguing the landscape, “the jungle crouched” waiting to pounce, to soak up the water that has not appeared yet, but is closer than ever. In her annotation on this section, specifically the line “bringing rain,” Jeannie argues “The irony of waiting (p)ages for something so abrupt simulates the imbalanced power dynamic between gods and men.” The gods, in her interpretation, are in control of the rain, refusing that the water be distributed in the hands of the men, until finally they break the dam and the rain flows. The gods toy with the humans to an even greater degree, explaining the discontinuous nature of the timeline. They give rain, then take it away, leaving a landscape “sunken” and “limp,” still in the state of anticipation. I find an interesting connection between this and the Anniversary Papers, where Kittredge writes “the Brahmans are never wear of inculcating the duty of free-handedness, and deem it more blessed to give than to receive.” In TWL, that attitude remains, the people and the land giving all they have, waiting to receive water. The gods don’t give rain, allowing the land to wait, anticipation building, blessing them, as they are giving and not receiving. This implies a double standard, where the land and the people must follow the rules of the gods, but the gods are not held to those same standards, a potential reflection of the elitism that destroyed the waste land as a public space.
We might want a conversation or action that happens in one context not to be shared in another (context collapse)
This is an interesting case of wanting to keep privacy. It depends on how dire the situation goes in order for a site to have to step in. Imagine if two people were planning a crime using the direct messaging system, would it be ethical for the site to step in? Discussing sensitive content should be private but it depends if the conversation can cause direct harm to others. But this brings up another issue in bullying and harassment which is frankly commonplace in sites like these.
Rosie Hopegood. The perils of ‘sharenting’: The parents who share too much. Al Jazeera, October 2020. URL: https://www.aljazeera.com/features/2020/10/11/facing-the-music-the-parents-who-share-too-much (visited on 2023-12-06).
This is a really interesting debate. When it comes to parents sharing photos of their kids, it could be seen as sensitive information. It’s a question on if social media can be seen as a trusted way to communicate with friends and family rather than people who might want to use your information for themselves. I’ve seen certain internet personalities share photos of their children which seems strange since with their large followings, it will attract unwanted attention to the kid who doesn’t even know they are being posted to the internet.
The goal of this assignment is to get you to think more deeply about how we are consuming information.
I think that this sentence means that however your brain understands how to remember information really connects more deeply to yourself.
emotional family functions did not holdthe greatest significance for the youngest generation, and the analysis did not reveal an increasein the instability of extended family bonds across generations
The study proved that while it's true family roles are shifting and individual choice is increasing, it's not causing instability in extended family bonds. (the case is against intergenerational change associated w individualization)
Characteristics of individuals (both of the participants and theirextended family members), their (nuclear) families, the living environment, and the specificsociohistorical context were perceived by participants as highly influential, sometimes evendetermining their extended family bonds.
Thye study showed that characteristics, nuclear family, living environment, and social and historical context influenced their extended family bonds
intergenerational transmission of kinship norms could actas a counterbalance to changes in extended family bonds associated with individualization
The reason that there isnt the change associated with individualization that theorists expected, is because there are factors being passed through generations are working against it.
Moreover, the continuing impor-tance of traditional family contact, the shared intergenerational experience of declining familycontact in youth, and the transmission of kinship norms across generations, argue for inter-generational continuity rather than change associated with individualization.
continuing importance of traditional family contact. Shared experience of declining family contact at a certain age over generations and passing down norms/ideas about family argue that there isn't change associated with individualization. rather the family dynamic stays the same throughout generations
intergenerational transmission of family normsmay inhibit intergenerational changes in extended family bonds, such as those associated withindividualization, thereby acting as a counterbalance to the individualization of these bonds.
family norms being passed through generations may prevent changes in extended family bonds. counterbalancing the idea that people will choose their extended family bonds
A few participants explicitlyattributed this difference to the nature of youth as a life phase, during which they grew moreindependent from their families in general.
Instability wasn't found by generations over time, but by the age when children grew more independent
In general, individual choice with whom to have a family bond seemed to play a moreimportant role in the extended family narratives of the youngest generation. This could bederived from the finding that the youngest participants more often explained their family con-tacts in a more detailed and elaborate manner compared to participants from the two oldestgenerations.
Younger generations where more detailed and elaborate than older generations when describing the bonds of extended family. (Because younger generations chose which bonds where important to them and wanted to keep.)
intergenerational transmission
intergenerational transmission- the process of values, beliefs, behaviors, and characteristics being passed down through generations
The three generations were similar regarding gender distribution, religion, andliving environment during their youth
not a very diverse group of people, could be missing factors in the results
However, the iterative process of cod-ing, refining codes names and relationships, and theory development continued until no newtheoretical insights emerged, indicating theoretical saturation (Charmaz, 2014; Flick, 2019)
This entire process is how they ended up with 14 families that explored most or all possible info and theories
he use of sensitiz-ing concepts in the initial coding phase
being aware and sensitive to nuances and complexities in data. They started this way so that other themes could still be revealed
This approach allowed emerging questions and provi-sional theories—such as the impact of specific personal characteristics—to guide the selectionof the next family to be analyzed.
They had a software program perform coding to pick which interviews would be analyzed based off the amount of info given related to the topic, emerging questions from people analyzing data, and provisional theories
All of the participants were interviewed in per-son, most of them in their own home. B
probably to make them feel more comfortable, since this subject can be sensitive
The participants were selected using a convenience sampling approach
not the most reliable method, could be more randomized
The use of preexisting datameant that the data had to be sorted and special consideration had to be given to the selectionof the interviews, as the scope of the primary study for which the data were collected extendedbeyond the focus of the present study (Heaton, 2004: Long-Sutehall et al., 2011).
The interviews had to be carefully picked and studies because the original study at the time of the interviews had a wider focus than this study
2Department of Pedagogy and EducationalSciences, Faculty of Behavioural and SocialSciences, University of Groningen, Groningen,The Netherlands
work in applied sciences (including behavioral and social sciences) they took data from people who live near them (nonwestern data, but still applies to how western families work)
May 2024 Revised: 12 January 2025
Recent article, later found out their data was from 2015, meaning not much research about the individualization theory was done between then and now, so we can still use this to deepen our limited knowledge
using grounded theory techniques indata analysis, specifically from constructivist grounded theory (Charmaz, 2014), we allowed unex-pected themes to emerge alongside the main themes from our research question.
Grounded theory techniques- qualitative research methods used to develop theories directly from data (you don't start with a hypothesis)
Constructivist grounded theory- generating theories by gathering data from participants instead of using preexisting theories (useful when little or no theories exist for a topic)
gathered data this way so they can find unexpected themes
Although De Beer did not find strong evidence for individualization inthe Netherlands as a combination of detraditionalization, heterogenization, and emancipation(De Beer, 2007; De Beer & Koster, 2009), social psychologist Hofstede (1991) identified theNetherlands as one of the most individualistic countries in the world
That's why they interviewed families in the Netherlands
due to modernization processes from the end of the 19thcentury and throughout the 20th century, individuals were no longer dependent on extendedfamily for their livelihood (Beck-Gernsheim, 1998). This caused the nuclear family to turn itsgaze inward and focus on relationships within the nuclear family home; a process also describedas “family individualization”
Before the 19th century, extended family lived together and depended on each other. Then during the modernization process individuals stopped being dependent on extended family to live and people started focusing more on spouses and children (Nuclear family)
This process refers to the“gradual loss of individuals’ attachment to traditional institutions” (De Beer & Koster, 2009,p. 55), such as the church, trade unions, political parties, and the family.
Detraditionalization- the process of individuals gradual detachment to traditional institutions (Church, trade unions, political parties, and family)
Adding to the complexity, various social trends, such as deinstitutionalization, emancipa-tion, and heterogenization, are grouped under the umbrella of individualization (De Beer &Koster, 2009). Alongside industrialization and globalization, these macro-social processes areoften viewed as having contributed to the modernization of Western societies
Individualization has become an umbrella term, making it harder to define
The findings of this study suggest that the individualization of extended family bonds, asoutlined by sociologist Beck-Gernsheim (Beck-Gernsheim, 1998; Beck & Beck-Gernsheim, 2002), is only partially supported
There is change, but not for the reasons theorized???
The studyfocuses on three successive generations—a young person around 18 years old, one of their par-ents, and one of their grandparents—in 14 families (N = 42).
Method: They interviewed 14 families and analyzed the narratives from 3 generations. (this included narratives from children) (42 people total)
Filter bubbles are outside forces that affect the information we take in. But, there's also a lot of stuff going on in our own brains that influences the way we take in and interpret information. This is called confirmation bias.
Our brains filter things and information that we want to hear if it doesn't interest our brains then we just ignore whatever is going on.
If, as some experts believe, AI skills are critical for the future of work, the question becomes how to deliver these skills equitably across academic programs
Heavy reliance on AI can negatively impact important critical thinking skills and stunt intellectual betterment. Although experts think AI skills are important for future jobs, it should be highlighted that there should be a blend of knowledge of AI use and genuine intelligence that will be valued.
“I am afraid to be flagged, so I refrain from utilizing it at all,” a junior from Florida Gulf Coast University wrote in the Student Voice survey.
Ai makes it difficult even for those who don't use it to pass their classes.
60% of the world's population is offline
I think this sentence means that not everyone gets the same life and not everything is handed down to them. Although some poeple don't have phones and electronics that is actually a bonus for their mental health.
dentify protein ‘cocktails’essential for developing normal immune function
This ending feels like we’re still guessing at nature’s perfect recipe or secret formula for balance. Maybe it’s not about finding the perfect “cocktail” but about preserving natural variety so we never have to recreate it in a lab...
polyfloral diets enhanced someimmune functions
The polyfloral effect might reveal a deeper evolutionary truth. And that is that specialization (monoculture feeding) is efficient but fragile while diversity creates resilience. That principle applies to ecosystems and even social systems sometimes
polyfloral diets induced ahigher GOX activity
This data point could be the quiet headline of the whole paper in my opinion. Its that diversity literally scales up collective protection. It’s almost evolutionary logic: diversity strengthens the hive’s social fabric
polyfloral diets that had the same amount of protein as monofloraldiets (table 1).
Controlling for total protein was clever. It isolates diversity as its own variable. But it also exposes how easily research on nutrition can oversimplify. equal protein doesn’t mean equal nutrition if amino acid profiles differ. Bees like us, probably need balance not bulk.
So, we also analysed glucose oxidase (GOX)activity as a parameter of social immunity
The idea of “social immunity” is so underrated. Instead of focusing only on the individual bee’s health the study treats the colony like a single organism with shared defenses. That could reshape how we think about disease prevention in other social species.. even humans
honeybee populations have been decliningover the last year
The authors subtly connect diet to colony collapse but it makes me think... are we looking at nutrition as a cause or as a symptom?? Maybe poor floral diversity reflects an already imbalanced ecosystem that’s failing on multiple levels.
THIS IS IT!
Can you add a short section above this final invite to join that touches on the promise on the course? 'This course will take you from x to y/ This program will help you.../ Imagine being having all the resources and guicance to confidenctly ...
what will this workshop be like? If you've never tried a Zoom workshop before, you're in for a treat! how it works: When the course begins, you’ll have instant access to all the Mixed Media Art tutorials.
This is really hard to read, and I'm actually not sure it adds anything. So possibly remove it?
I'm Delight Rogers,I will be y
I would move this section with the logos up right underneath the other 'about' section
New
Ongoing access to the
upon request
Is this within your community? Possibly reword it then and touch on the community they get ongoing access to
Lisette - Personal Portraits Student Said:
Move this section up with the one above
imagine a creative process where playfulness reigns &
I would move this section right underneath the header to set the scene
Repent$500.003 in stock
Repent:
TEXT: The poster Repent references belief that America has failed Jesus through it's language. While the text references Jesus many times, to me it seems available to many different audiences because of how broad the religious language is. Whether it be Christianity, a major religion in the US and Tacoma, or people who don't view themselves as religious or people of other religions involving the figure of Jesus such as Islam, I would argue that most people can interpret the posters text as long as they're familiar with the figure of Jesus and the US current/past social and political standings.
COLOR: The colors of the poster Repent contribute to the religious messages. The poster uses orange, yellow, and blue as the colors of the print with a white background. The use of yellow and orange, both warm colors which represent humanity, color the image's sun and heart, which can be interpreted as symbols of Jesus. The blue is used as the color of the text, language which speak about a need to repent for wrong doings. Blue, a color associated with sorrow and cleanliness, represents the texts message.
Despite supportive parents who expressed concern about her situa-tion, Terri said she was a "very depressed child." Her father would have conversations with her "about being Black and beautiful" and about "the union of people of color that had always existed that I needed to find. And the pride." However, her parents did not have a network of Black friends to help support her.
This is extremely worrisome to me. As someone who aspires to work with children in emotional and behavioral contexts, hearing that there are children who become depressed because of societal circumstances and not personal events makes me wonder what protections and reforms should happen in education in order to keep vulnerable populations from being exposed to hate at school.
As has been rhe case historically, these parents of color see college education as the ticket to their children's life chances, yet too often their children's aca-demic performance lags behind that of their White counterparts.
This is a statement that resonates with me. As a Hispanic student myself, the message that in order to succeed in life, you must obtain a college degree is encouraged and repeated to us as motivation. The fact that White parents don't push this onto their children makes me wonder if it is because academically, their schools have always been better in terms of opportunity, and has given them the option to see college as "just another option" and not their ticket to success.
In the context of predominantly White schools, however, Black boys may enjoy a degree of social success, particularly if they are athletically talented. The culture has embraced the Black athlete, and the young man who can fulfill that role is often pursued by Black girls and White girls alike.
I think even this is a stereotype that can be harmful to Black students. Why should we only celebrate a Black student if they are bringing their high school football team to state championships? It creates an expectation or pressure on Black students to be good at something for the approval of their white peers.
moral education of patriotism
to be a patriot is to be in favor of the country even when the country is unjust, at least when its taught in many cases
moral education of loyalty--but to what?
Thus, Tier Two sources can provide quality information that is more accessible to non-academics. There are three main categories. First, official reports from government agencies or major international institutions like the World Bank or the United Nations; these institutions generally have research departments staffed with qualified experts who seek to provide rigorous, even-handed information to decision-makers. Second, feature articles from major newspapers and magazines like the New York Times, Wall Street Journal, London Times, or The Economist are based on original reporting by experienced journalists (not press releases) and are typically 1500+ words in length. Third, there are some great books from non-academic presses that cite their sources; they’re often written by journalists. All three of these sources are generally well researched descriptions of an event or state of the world, undertaken by credentialed experts who generally seek to be even-handed.
Teir Two Sources: official reports from government agencies or major institutions; studies that submit statistics within communities? Magazines, books from non-academic presses that cite their sources written bb y journalists
Scholarly articles appear in academic journals, which are published multiple times a year in order to share the latest research findings with scholars in the field
similar to state legislative updates that are published annually for the courts/attorney's (reference to my own paper)
The Informative Research Report is a report that relays the results of a central research question in an organized manner through more formal sources. These resources could include Google Scholar, library catalogs and academic article databases, websites of relevant agencies, and Google searches using
based off research question through formal resources
Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.
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__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __
This study explores chromatin organization around trans-splicing acceptor sites (TASs) in the trypanosomatid parasites Trypanosoma cruzi, T. brucei and Leishmania major. By systematically re-analyzing MNase-seq and MNase-ChIP-seq datasets, the authors conclude that TASs are protected by an MNase-sensitive complex that is, at least in part, histone-based, and that single-copy and multi-copy genes display differential chromatin accessibility. Altogether, the data suggest a common chromatin landscape at TASs and imply that chromatin may modulate transcript maturation, adding a new regulatory layer to an unusual gene-expression system.
I value integrative studies of this kind and appreciate the careful, consistent data analysis the authors implemented to extract novel insights. That said, several aspects require clarification or revision before the conclusions can be robustly supported. My main concerns are listed below, organized by topic/result section.
TAS prediction * Why were TAS predictions derived only from insect-stage RNA-seq data? Restricting TAS calls to one life stage risks biasing predictions toward transcripts that are highly expressed in that stage and may reduce annotation accuracy for lowly expressed or stage-specific genes. Please justify this choice and, if possible, evaluate TAS robustness using additional transcriptomes or explicitly state the limitation.
TAS predictions derived only from insect-stage RNA-seq data because in a previous study it was shown that there are no significant differences between stages in the 5’UTR procesing in T. cruzi life stages (https://doi.org/10.3389/fgene.2020.00166) We are not testing an additional transcriptome here, because the robustness of the software was already probed in the original article were UTRme was described (Radio S, 2018 doi:10.3389/fgene.2018.00671).
Results - "There is a distinctive average nucleosome arrangement at the TASs in TriTryps": * You state that "In the case of L. major the samples are less digested." However, Supplementary Fig. S1 suggests that replicate 1 of L. major is less digested than the T. brucei samples, while replicate 2 of L. major looks similarly digested. Please clarify which replicates you reference and correct the statement if needed.
The reviewer has a good point. We made our statement based on the value of the maximum peak of the sequenced DNA molecules, which in general is a good indicative of the extension of the digestion achieved by the sample (Cole H, NAR, 2011).
As the reviewer correctly points, we should have also considered the length of the DNA molecules in each percentile. However, in this case both, T. brucei’s and L major’s samples were gel purified before sequencing and it is hard to know exactly what fragments were left behind in each case. Therefore, it is better not to over conclude on that regard.
We have now comment on this in the main manuscript, and we have clarified in the figure legends which data set we used in each case.
* It appears you plot one replicate in Fig. 1b and the other in Suppl. Fig. S2. Please indicate explicitly which replicate is in each plot. For T. brucei, the NDR upstream of the TAS is clearer in Suppl. Fig. S2 while the TAS protection is less prominent; based on your digestion argument, this should correspond to the more-digested replicate. Please confirm.
The replicates used for the construction of each figure are explicitly indicated in Table S1. Although we have detailed in the table the original publication, the project and accession number for each data set, the reviewer is correct that in this case it was still not completely clear to which length distribution heatmap was each sample associated with. To avoid this confusion, we have now added the accession number for each data set to the figure legends and also clarified in Table S1. Regarding the reviewer’s comment on the correspondence between the observed TAS protection and the extent of samples digestion, he/she is correct that for a more digested sample we would expect a clearer NDR. In this case, the difference in the extent of digestion between these two samples is minor, as observed the length of the main peak in the length distribution histogram for sequenced DNA molecules is the same. These two samples GSM5363006, represented in Fig1 b, and GSM5363007, represented in S2, belong to the same original paper (Maree et al 2017), and both were gel purified before sequencing. Therefore, any difference between them could not only be the result of a minor difference in the digestion level achieved in each experiment but could be also biased by the fragments included or not during gel purification. Therefore, I would not over conclude about TAS protection from this comparison. We have now included a brief comment on this, in the figure discussion
* The protected region around the TAS appears centered on the TAS in T. brucei but upstream in L. major. This is an interesting difference. If it is technical (different digestion or TAS prediction offset), explain why; if likely biological, discuss possible mechanisms and implications.
We appreciate the reviewer suggestion. We cannot assure if it is due to technical or biological reasons, but there is evidence that L. major ‘s genome has a different dinucleotide content and it might have an impact on nucleosome assembly. We have now added a comment about this observation in the final discussion of the manuscript.
Results - "An MNase sensitive complex occupies the TASs in T. brucei": * The definition of "MNase activity" and the ordering of samples into Low/Intermediate/High digestion are unclear. Did you infer digestion levels from fragment distributions rather than from controlled experimental timepoints? In Suppl. Fig. S3a it is not obvious how "Low digestion" was defined; that sample's fragment distribution appears intermediate. Please provide objective metrics (e.g., median fragment length, fraction 120-180 bp) used to classify digestion levels.
As the reviewer suggests, the ideal experiment would be to perform a time course of MNase reaction with all the samples in parallel, or to work with a fixed time point adding increasing amounts of MNase. However, even when making controlled experimental timepoints, you need to check the length distribution histogram of sequenced DNA molecules to be sure which level of digestion you have achieved.
In this particular case, we used public available data sets to make this analysis. We made an arbitrary definition of low, intermediate and high level of digestion, not as an absolute level of digestion, but as a comparative output among the tested samples. We based our definition on the comparison of __the main peak in length distribution heatmaps because this parameter is the best metric to estimate the level of digestion of a given sample. It represents the percentage of the total DNA sequenced that contains the predominant length in the sample tested. __Hence, we considered:
low digestion: when the main peak is longer than the expected protection for a nucleosome (longer than 150 bp). We expect this sample to contain additional longer bands that correspond to less digested material.
intermediate digestion, when the main peak is the expected for the nucleosome core-protection (˜146-150bp).
high digestion, when the main peak is shorter than that (shorter than 146 bp). This case, is normally accompanied by a bigger dispersion in fragment sizes.
To do this analysis, we chose samples that render different MNase protection of the TAS when plotting all the sequenced DNA molecules relative to this point and we used this protection as a predictor of the extent of sample digestion (Figure 2). To corroborate our hypothesis, that the degree of TAS protection was indeed related to the extent of the MNase digestion of a given sample, we looked at the length distribution histogram of the sequenced DNA molecules in each case. It is the best measurement of the extent of the digestion achieved, especially, when sequencing the whole sample without any gel purification and representing all the reads in the analysis as we did. The only caveat is with the sample called “intermediate digestion 1” that belongs to the original work of Mareé 2017, since only this data set was gel purified.
Whether the sample used in Figure 1 (from Mareé 2017) is also from the same lab and is an MNase-seq. Strictly speaking, there is no methodological difference between MNase-seq and the input of a native MNase-ChIP-seq, since the input does not undergo the IP.
* Several fragment distributions show a sharp cutoff at ~100-125 bp. Was this due to gel purification or bioinformatic filtering? State this clearly in Methods. If gel purification occurred, that can explain why some datasets preserve the MNase-sensitive region.
The sharp cutoff is neither due to gel purification or bioinformatic filtering, it is just due to the length of the paired-end read used in each case. In earlier works the most common was to sequence only 50bp, with the improvement of technologies it went up to 75,100 or 125 bp. We have now clarified in Table S1 the length of the paired-reads used in each case when possible.
* Please reconcile cases where samples labeled as more-digested contain a larger proportion of >200 bp fragments than supposedly less-digested samples; this ordering affects the inference that digestion level determines the loss/preservation of TAS protection. Based on the distributions I see, "Intermediate digestion 1" appears most consistent with an expected MNase curve - please confirm and correct the manuscript accordingly.
As explained above, it's a common observation in MNase digestion of chromatin that more extensive digestion can still result in a broad range of fragment sizes, including some longer fragments. This seemingly counter-intuitive result is primarily due to the non-uniform accessibility of chromatin and the sequence preference of the MNase enzyme, which has a preference for AT reach sequences.
The rationale of this is as follows: when you digest chromatin with MNase and the objective is to map nucleosomes genome-wide, the ideal situation would be to get the whole material contained in the mononucleosome band. Given that MNase is less efficient to digest protected DNA but, if the reaction proceeds further, it always ends up destroying part of it, the result is always far from perfect. The better situation we can get, is to obtain samples were ˜80% of the material is contained in the mononucloesome band. __And here comes the main point: __even in the best scenario, you always get some additional longer bands, such as those for di or tri nucleosomes. If you keep digesting, you will get less than 80 % in the nucleosome band and, those remaining DNA fragments that use to contain di and tri nucleosomes start getting digested as well, originating a bigger dispersion in fragments sizes. How do we explain persistence of Long Fragments? The longest fragments (di-, tri-nucleosomes) that persist in a highly digested sample are the ones that were originally most highly protected by proteins or higher-order structure, or by containing a poor AT sequence content, making their linker DNA extremely resistant to initial cleavage. Once the majority of the genome is fragmented, these few resistant longer fragments become a more visible component of the remaining population, contributing to a broader size dispersion. Hence, you end up observing a bigger dispersion in length distributions in the final material. Bottom line, it is not a good practice to work with under or over digested samples. Our main point, is to emphasize that especially when comparing samples, it important to compare those with comparable levels of digestion. Otherwise, a different sampling of the genome will be represented in the remaining sequenced DNA.
Results - "The MNase sensitive complexes protecting the TASs in T. brucei and T. cruzi are at least partly composed of histones": * The evidence that histones are part of the MNase-sensitive complex relies on H3 MNase-ChIP signal in subnucleosomal fragment bins. This seems to conflict with the observation (Fig. 1) that fragments protecting TASs are often nucleosome-sized. Please reconcile these points: are H3 signals confined to subnucleosomal fragments flanking the TAS while the TAS itself is depleted of H3? Provide plots that compare MNase-seq and H3 ChIP signals stratified by consistent fragment-size bins to clarify this.
What we learned from other eukaryotic organisms that were deeply studied, such as yeast, is that NDRs are normally generated at regulatory points in the genome. In this sense, yeast tRNA genes have a complex with a bootprint smaller than a nucleosome formed by TFIIIC-TFIIB (Nagarajavel, doi: 10.1093/nar/gkt611). On the other hand, many promotor regions have an MNase-sensitive complex with a nucleosome-size footprint, but it does not contain histones (Chereji, et al 2017, doi:10.1016/j.molcel.2016.12.009). The reviewer is right that from Figure 1 and S2 we could observe that the footprint of whatever occupies the TAS region, especially in T. brucei, is nucleosome-size. However, it only shows the size, but it doesn’t prove the nature of its components. Nevertheless, those are only MNase-seq data sets. Since it does not include a precipitation with specific antibodies, we cannot confirm the protecting complex is made up by histones. In parallel, a complementary study by Wedel 2017, from Siegel’s lab, shows that using a properly digested sample and further immunoprecipitating with a-H3 antibody, the TAS is not protected by nucleosomes at least not when analyzing nucleosome size-DNA molecules. Besides, Briggs et. al 2018 (doi: 10.1093/nar/gky928) showed that at least at intergenic regions H3 occupancy goes down while R-loops accumulation increases. We have now added a supplemental figure associated to Figure 3 (new Suplemental 5) replotting R-loops and MNase-ChIP-seq for H3 relative to our predicted TAS showing this anti-correlation and how it partly correlates with MNase protection as well. As a control we show that Rpb9 trends resembles H3 as Siegel’s lab have shown in Wedel 2018.
* Please indicate which datasets are used for each panel in Suppl. Fig. S4 (e.g., Wedel et al., Maree et al.), and avoid calling data from different labs "replicates" unless they are true replicates.
In most of our analysis we used real replicated experiments. Such is the case MNase-seq data used in Figure 1, with the corresponding replicate experiments used in Figure S2; T. cruzi MNase-ChIP-seq data used in Figure 3b and 4a with the respective replicate used in Figures S4 and S5 (now S6 in the revised manuscript). The only case in which we used experiments coming from two different laboratories, is in the case of MNase-ChIP-seq for H3 from T. brucei. Unfortunately, there are only two public data sets coming each of them from different laboratories. The samples used in Fig 3 (from Siegel’s lab) whether the IP from H3 represented in S4 and S5 (S6 n the updated version) comes from another lab (Patterton’s). To be more rigorous, we now call them data 1 and 2 when comparing these particular case.
The reviewer is right that in this particular case one is native chromatin (Pattertons’) while the other one is crosslinked (Siegel’s). We have now clarified it in the main text that unfortunately we do not count on a replicate but even under both condition the result remains the same, and this is compatible with my own experience, were crosslinking does not affect the global nucleosome patterns (compared nucleosome organization from crosslinked chromatin MNAse-seq inputs Chereji, Mol Cell, 2017 doi: 10.1016/j.molcel.2016.12.009 and native MNase-seq from Ocampo, NAR, 2016 doi: 10.1093/nar/gkw068).
* Several datasets show a sharp lower bound on fragment size in the subnucleosomal range (e.g., ~80-100 bp). Is this a filtering artifact or a gel-size selection? Clarify in Methods and, if this is an artifact, consider replotting after removing the cutoff.
We have only filtered adapter dimmer or overrepresented sequences when needed. In Figures 2 and S3 we represented all the sequenced reads. In other figures when we sort fragments sizes in silico, such as nucleosome range, dinucleosome or subnucleosome size, we make a note in the figure legends. What the reviewer points is related to the length of the sequence DNA fragment in each experiment. As we explained above, the older data-sets were performed with 50 bp paired-end reads, the newer ones are 75, 100 or 125bp. This is information is now clarified in Table S1.
__Results - "The TASs of single and multi-copy genes are differentially protected by nucleosomes": __
__ __* Please include T. brucei RNA-seq data in Suppl. Fig. S5b as you did for T. cruzi.
We have shown chromatin organization for T. brucei in S5b to show that there is a similar trend. Unfortunately, we did not get a robust list of multi-copy genes for T. brucei as we did get for T. cruzi, therefore we do not want to over conclude showing the RNA-seq for these subsets of genes. The limitation is related to the fact that UTRme restrict the search and is extremely strict when calling sites at repetitive regions.
* Discuss how low or absent expression of multigene families affects TAS annotation (which relies on RNA-seq) and whether annotation inaccuracies could bias the observed chromatin differences.
The mapping of occurrence and annotations that belong to repetitive regions has great complexity. UTRme is specially designed to avoid overcalling those sites. In other words, there is a chance that we could be underestimating the number of predicted TASs at multi-copy genes. Regarding the impact on chromatin analysis, we cannot rule out that it might have an impact, but the observation favors our conclusion, since even when some TASs at multi-copy genes can remain elusive, we observe more nucleosome density at those places.
* The statement that multi-copy genes show an "oscillation" between AT and GC dinucleotides is not clearly supported: the multi-copy average appears noisier and is based on fewer loci. Please tone down this claim or provide statistical support that the pattern is periodic rather than noisy.
We have fixed this now in the preliminary revised version
* How were multi-copy genes defined in T. brucei? Include the classification method in Methods.
This classification was done the same way it was explained for T. cruzi
Genomes and annotations: * If transcriptomic data for the Y strain was used for T. cruzi, please explain why a Y strain genome was not used (e.g., Wang et al. 2021 GCA_015033655.1), or justify the choice. For T. brucei, consider the more recent Lister 427 assembly (Tb427_2018) from TriTrypDB. Use strain-matched genomes and transcriptomes when possible, or discuss limitations.
The most appropriate way to analyze high throughput data, is to aline it to the same genome were the experiments were conducted. This was clearly illustrated in a previous publication from our group were we explained how should be analyzed data from the hybrid CL Brener strain. A common practice in the past was to use only Esmeraldo-like genome for simplicity, but this resulted in output artifacts. Therefore, we aligned it to CL Brener genome, and then focused the main analysis on the Esmeraldo haplotype (Beati Plos ONE, 2023). Ideally, we should have counted on transcriptomic data for the same strain (CL Brener or Esmeraldo). Since this was not the case at that moment, we used data from Y strain that belongs to the same DTU with Esmeraldo.
In the case of T. brucei, when we started our analysis and the software code for UTRme was written, the previous version of the genome was available. Upon 2018 version came up, we checked chromatin parameters and observed that it did not change the main observations. Therefore, we continue working with our previous setups.
Reproducibility and broader integration: * Please share the full analysis pipeline (ideally on GitHub/Zenodo) so the results are reproducible from raw reads to plots.
We are preparing a full pipeline in GitHub. We will make it available before manuscript full revision
* As an optional but helpful expansion, consider including additional datasets (other life stages, BSF MNase-seq, ATAC-seq, DRIP-seq) where available to strengthen comparative claims.
We are now including a new suplemental figure including DRIP-seq and Rp9 ChIP-seq (revised S5). Additionally, we added a new panel c to figure 4, representing FAIRE-seq data for T. cruzi fore single and multi-copy genes
We are working on ATAC-seq analysis and BSF MNase-seq
Optional analyses that would strengthen the study: * Stratify single-copy genes by expression (high / medium / low) and examine average nucleosome occupancy at TASs for each group; a correlation between expression and NDR depth would strengthen the functional link to maturation.
We have now included a panel in suplemental figure 5 (now revised S6), showing the concordance for chromatin organization of stratified genes by RNA-seq levels relative to TAS.
__Minor / editorial comments: __ * In the Introduction, the sentence "transcription is initiated from dispersed promoters and in general they coincide with divergent strand switch regions" should be qualified: such initiation sites also include single transcription start regions.
We have clarified this in the preliminary revised version
* Define the dotted line in length distribution plots (if it is not the median, please clarify) and consider placing it at 147 bp across plots to ease comparison.
The dotted line is just to indicate where the maximum peak is located. It is now clarified in figure legends.
* In Suppl. Fig. 4b "Replicate2" the x-axis ticks are misaligned with labels - please fix.
We have now fixed the figure. Thanks for noticing this mistake.
* Typo in the Introduction: "remodellingremodeling" → "remodeling
Thanks for noticing this mistake, it is fixed in the current version of the manuscript
**Referee cross-commenting** Comment 1: I think Reviewer #2 and Reviewer #3 missed that they authors of this manuscript do cite and consider the results from Wedel at al. 2017. They even re-analysed their data (e.g. Figure 3a). I second Reviewer #2 comment indicating that the inclusion of a schematic figure to help readers visualize and better understand the findings would be an important addition.
Comment 2: I agree with Reviewer #3 that the use of different MNase digestion procedures in the different datasets have to be considered. On the other hand, I don't think there is a problem with figure 1 showing an MNase-protected TAS for T. brucei as it is based on MNase-seq data and reproduces the reported results (Maree et al. 2017). What the Siegel lab did in Wedel et al. 2017 was MNase-ChIPseq of H3 showing nucleosome depletion at TAS, but both results are not necessary contradictory: There could still be something else (which does not contain H3) sitting on the TAS protecting it from MNase digestion.
Reviewer #1 (Significance (Required)):
This study provides a systematic comparative analysis of chromatin landscapes at trans-splicing acceptor sites (TASs) in trypanosomatids, an area that has been relatively underexplored. By re-analyzing and harmonizing existing MNase-seq and MNase-ChIP-seq datasets, the authors highlight conserved and divergent features of nucleosome occupancy around TASs and propose that chromatin contributes to the fidelity of transcript maturation. The significance lies in three aspects: 1. Conceptual advance: It broadens our understanding of gene regulation in organisms where transcription initiation is unusual and largely constitutive, suggesting that chromatin can still modulate post-transcriptional processes such as trans-splicing. 2. Integrative perspective: Bringing together data from T. cruzi, T. brucei and L. major provides a comparative framework that may inspire further mechanistic studies across kinetoplastids. 3. Hypothesis generation: The findings open testable avenues about the role of chromatin in coordinating transcript maturation, the contribution of DNA sequence composition, and potential interactions with R-loops or RNA-binding proteins. Researchers in parasitology, chromatin biology, and RNA processing will find it a useful resource and a stimulus for targeted experimental follow-up.
My expertise is in gene regulation in eukaryotic parasites, with a focus on bioinformatic analysis of high-throughput sequencing data
__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __
Siri et al. perform a comparative analysis using publicly available MNase-seq data from three trypanosomatids (T. brucei, T. cruzi, and Leishmania), showing that a similar chromatin profile is observed at TAS (trans-splicing acceptor site) regions. The original studies had already demonstrated that the nucleosome profile at TAS differs from the rest of the genome; however, this work fills an important gap in the literature by providing the most reliable cross-species comparison of nucleosome profiles among the tritryps. To achieve this, the authors applied the same computational analysis pipeline and carefully evaluated MNase digestion levels, which are known to influence nucleosome profiling outcomes.
In my view, the main conclusion is that the profiles are indeed similar-even when comparing T. brucei and T. cruzi. This was not clear in previous studies (and even appeared contradictory, reporting nucleosome depletion versus enrichment) largely due to differences in chromatin digestion across these organisms. The manuscript could be improved with some clarifications and adjustments:
- The authors state from the beginning that available MNase data indicate altered nucleosome occupancy around the TAS. However, they could also emphasize that the conclusions across the different trypanosomatids are inconsistent and even contradictory: NDR in T. cruzi versus protection-in different locations-in T. brucei and Leishmania.
We start our manuscript by referring to the first MNase-seq data sets publicly available for each TriTryp and we point that one of the main observations, in each of them, is the occurrence of a change in nucleosome density or occupancy at intergenic regions. In T. cruzi, in a previous publication from our group, we stablished that this intergenic drop in nucleosome density occurs near the trans-splicing acceptor site. In this work, we extend our study to the other members of TriTryps: T. brucei and L. major.
In T. brucei the papers from Patterton’s lab and Siegel’s lab came out almost simultaneously in 2017. Hence, they do not comment on each other’s work. The first one claims the presence of a well-positioned nucleosome at the TAS by using MNase-seq, while the second one, shows an NDR at the TAS by using MNase-ChIP-seq. However, we do not think they are contradictory, or they have inconsistency. We brought them together along the manuscript because we think these works can provide complementary information.
On one hand, we infer data from Pattertons lab is slightly less digested than the sample from Siegel’s lab. Therefore, we discuss that this moderate digestion must be the reason why they managed to detect an MNase protecting complex sitting at the TAS (Figure 1). On the other hand, Sigel’s lab includes an additional step by performing MNase-ChIP-seq, showing that when analyzing nucleosome size fragments, histones are not detected at the TAS. Here, we go further in this analysis on figure 3, showing that only when looking at subnucleosome-size fragments, we are able to detect histone H3. And this is also true for T. cruzi.
By integrating every analysis in this work and the previous ones, we propose that TASs are protected by an MNase-sensitive complex (probed in Figure 2). This complex most likely is only partly formed by histones, since only when analyzing sub-nucleosomes size DNA molecules we can detect histone H3 (Figure 3). To be absolutely sure that the complex is not entirely made up by histones, future studies should perform an MNse-ChIP-seq with less digested samples. However, it was previously shown that R-loops are enriched at those intergenic NDRs (Briggs, 2018 doi: 10.1093/nar/gky928) and that R-loops have plenty of interacting proteins (Girasol, 2023 10.1093/nar/gkad836). Therefore, most likely, this MNase-sensitive complexed have a hybrid nature made up by H3 and some other regulatory molecules, possibly involved in trans-splicing. We have now added a new figure S5 showing R-loop co-localization with the NDR.
Regarding the comparison between different organisms, after explaining the sensitivity to MNase of the TAS protecting complex, we discuss that when comparing equally digested samples T. cruzi and T. brucei display a similar chromatin landscape with a mild NDR at the TAS (See T. cruzi represented in Figure 1 compared to T. brucei represented in Intermediate digestion 2 in Figure 2, intermediate digestion in the revised manuscript). Unfortunately, we cannot make a good comparison with L. major, since we do not count on a similar level of digestion.
Another point that requires clarification concerns what the authors mean in the introduction and discussion when they write that trypanosomes have "...poorly organized chromatin with nucleosomes that are not strikingly positioned or phased." On the other hand, they also cite evidence of organization: "...well-positioned nucleosome at the spliced-out region.. in Leishmania (ref 34)"; "...a well-positioned nucleosome at the TASs for internal genes (ref37)"; "...a nucleosome depletion was observed upstream of every gene (ref 35)." Aren't these examples of organized chromatin with at least a few phased nucleosomes? In addition, in ref 37, figure 4 shows at least two (possibly three to four) nucleosomes that appear phased. In my opinion, the authors should first define more precisely what they mean by "poorly organized chromatin" and clarify that this interpretation does not contradict the findings highlighted in the cited literature.
For a better understanding of nucleosome positioning and phasing I recommend the review: Clark 2010 doi:10.1080/073911010010524945, Figure 4. Briefly, in a cell population there are different alternative positions that a given nucleosome can adopt. However, some are more favorable. When talking about favorable positions, we refer to the coordinates in the genome that are most likely covered by a nucleosome and are predominant in the cell population. Additionally, nucleosomes could be phased or not. This refers not only the position in the genome, but to the distance relative to a given point. In yeast, or in highly transcribed genes of more complex eukaryotes, nucleosomes are regularly spaced and phased relative to the transcription start site (TSS) or to the +1 nucleosome (Ocampo, NAR, 2016, doi:10.1093/nar/gkw068). In trypanosomes, nucleosomes have some regular distribution when making a browser inspection but, given that they are not properly phased with respect to any point, it is almost impossible to make a spacing estimation from paired-end data. This is also consistent with a chromatin that is transcribed in an almost constitutive manner.
As the reviewer mention, we do site evidence of organization. We think the original observations are correct, but we do not fully agree with some of the original statements. In this manuscript our aim is to take the best we learned from their original works and to make a constructive contribution adding to the original discussions. In this regard, in trypanosomes there are some conserved patterns in the chromatin landscape, but their nucleosomes are far from being well-positioned or phased. For a better understanding, compare the variations observed in the y axis when representing av. nucleosome occupancy in yeast with those observed in trypanosomes and you will see that the troughs and peaks are much more prominent in yeast than the ones observed in any TryTryp member.
Following the reviewer’s suggestion we have now clarified this in the main text
The paper would also benefit from the inclusion of a schematic figure to help readers visualize and better understand the findings. What is the biological impact of having nucleosomes, di-nucleosomes, or sub-nucleosomes at TAS? This is not obvious to readers outside the chromatin field. For example, the following statement is not intuitive: "We observed that, when analyzing nucleosome-size (120-180 bp) DNA molecules or longer fragments (180-300 bp), the TASs of either T. cruzi or T. brucei are mostly nucleosome-depleted. However, when representing fragments smaller than a nucleosome-size (50-120 bp) some histone protection is unmasked (Fig. 3 and Fig. S4). This observation suggests that the MNase sensitive complex sitting at the TASs is at least partly composed of histones." Please clarify.
We appreciate the reviewer’s suggestion to make a schematic figure. We are working on this and will be added to the manuscript upon final revision.
Regarding the biological impact of having mono, di or subnucleosome fragments, it is important to unveil the fragment size of the protected DNA to infer the nature of the protecting complex. In the case of tRNA genes in yeast, at pol III promoters they found footprints smaller than a nucleosome size that ended up being TFIIB-TFIIC (Nagarajavel, doi: 10.1093/nar/gkt611). Therefore, detecting something smaller than a nucleosome might suggest the binding of trans-acting factors different than histones or involving histones in a mixed complex. These mixed complexes are also observed, and that is the case of the centromeric nucleosome which has a very peculiar composition (Ocampo and Clark, Cells Reports, 2015). On the other hand, if instead we detect bigger fragments, it could be indicative of the presence of bigger protecting molecules or that those regions are part of higher order chromatin organization still inaccessible for MNase linker digestions.
Here we show on 2Dplots, that complex or components protecting the TAS have nucleosome size, but we cannot assure they are entirely made up by histones, since, only when looking at subnucleosome-size fragments, we are able to detect histone H3. We have now added part of this explanation to the discussion.
By integrating every analysis in this work and the previous ones, we propose that the TAS is protected by an MNase-sensitive complex (Figure 2). This complex most likely is only partly formed by histones, since only when analyzing sub-nucleosomes size DNA molecules we can detect histone H3 (Figure 3). As explained above, to be absolutely sure that the complex is not entirely made up by histones, future studies should perform an MNse-ChIP-seq with less digested samples. However, it was previously shown that R-loops are enriched at those intergenic NDRs (Briggs 2018) and that R-loops have plenty of interacting proteins (Girasol, 2023). Therefore, most likely, this MNase-sensitive complexed have a hybrid nature made up by H3 and some other regulatory molecules. We have now added a new S5 figure showing R-loop co-localization.
Some references are missing or incorrect:
we will make a thorough revision
"In trypanosomes, there are no canonical promoter regions." - please check Cordon-Obras et al. (Navarro's group). Thank you for the appropiate suggestion.
We have now added this reference
Please, cite the study by Wedel et al. (Siegel's group), which also performed MNase-seq analysis in T. brucei.
We understand that reviewer number 2# missed that we cited this reference and that we did used the raw data from the manuscript of Wedel et. al 2017 form Siegel’s group. We used the MNase-ChIP-seq data set of histone H3 in our analysis for Figures 3, S4b and S5b (S6c in the revised version), also detailed in table S1. To be even more explicit we have now included the accession number of each data set in the figure legend.
Figure-specific comments: Fig. S3: Why does the number of larger fragments increase with greater MNase digestion? Shouldn't the opposite be expected?
This a good observation. As we also explained to reviewer#1:
It's a common observation in MNase digestion of chromatin that more extensive digestion can still result in a broad range of fragment sizes, including some longer fragments. This seemingly counter-intuitive result is primarily due to the non-uniform accessibility of chromatin and the sequence preference of the MNase enzyme.
The rationale of this is as follows: when you digest chromatin with MNase and the objective is to map nucleosomes genome-wide, the ideal situation would to get the whole material contained in the mononucleosome band. Given that MNase is less efficient to digest protected DNA but, if the reaction proceeds further, it always ends up destroying part of it, the result is always far from perfect. The better situation we can get, is to obtain samples were ˜80% of the material is contained in the mononucloesome band. __And here comes the main point: __even in the best scenario, you always have some additional longer bands, such as those for di or tri nucleosomes. If you keep digesting, you will get less than 80 % in the nucleosome band and, those remaining DNA fragments that use to contain di and tri nucleosomes start getting digested as well originating a bigger dispersion in fragments sizes. How do we explain persistence of Long Fragments? The longest fragments (di-, tri-nucleosomes) that persist in a highly digested sample are the ones that were originally most highly protected by proteins or higher-order structure, making their linker DNA extremely resistant to initial cleavage. Once the majority of the genome is fragmented, these few resistant longer fragments become a more visible component of the remaining population, contributing to a broader size dispersion. Hence, there you end up having a bigger dispersion in length distributions in the final material. Bottom line, it is not a good practice to work with under or overdigested samples. Our main point is to emphasize that especially when comparing samples, it important to compare those with comparable levels of digestion. Otherwise, a different sampling of the genome will be represented in the remaining sequenced DNA Fig. S5B: Why not use MNase conditions under which T. cruzi and T. brucei display comparable profiles at TAS? This would facilitate interpretation.
The reviewer made a reasonable observation. The reason why we used MNase-ChIP_seq instead of just MNase to test occupancy at TAS at the subsets of genes, is because we intended to be more certain if we were talking about the presence of histones or something else. By using IP for histone H3 we can see that at multi-copy genes this protein is present when looking at nucleosome-size fragments. Additionally, as shown in figure S4b, length distribution histograms are also similar for the compared IPs.
Minor points:
There are several typos throughout the manuscript.
Thanks for the observation. We will check carefully.
Methods: "Dinucelotide frecuency calculation."
We will add a code in GitHub
Reviewer #2 (Significance (Required)):
In my view, the main conclusion is that the profiles are indeed similar-even when comparing T. brucei and T. cruzi. This was not clear in previous studies (and even appeared contradictory, reporting nucleosome depletion versus enrichment) largely due to differences in chromatin digestion across these organisms. Audience: basic science and specialized readers.
Expertise: epigenetics and gene expression in trypanosomatids.
__Reviewer #3 (Evidence, reproducibility and clarity (Required)): __
The authors analysed publicly accessible MNase-seq data in TriTryps parasites, focusing on the chromatin structure around trans-splicing acceptor sites (TASs), which are vital for processing gene transcripts. They describe a mild nucleosome depletion at the TAS of T. cruzi and L. major, whereas a histone-containing complex protects the TASs of T. brucei. In the subsequent analysis of T. brucei, they suggest that a Mnase-sensitive complex is localised at the TASs. For single-copy versus multi-copy genes, the authors show different di-nucleotide patterns and chromatin structures. Accordingly, they propose this difference could be a novel mechanism to ensure the accuracy of trans-splicing in these parasites.
Before providing an in- depth review of the manuscript, I note that some missing information would have helped in assessing the study more thoroughly; however, in the light of the available information, I provide the following comments for consideration.
The numbering of the figures, including the figure legends, is missing in the PDF file. This is essential for assessing the provided information.
We apologized for not including the figure numbers in the main text, although they are located in the right place when called in the text. The omission was unwillingly made when figure legends were moved to the bottom of the main text. This is now fixed in the updated version of the manuscript.
The publicly available Mnase- seq data are manyfold, with multiple datasets available for T. cruzi, for example. It is unclear from the manuscript which dataset was used for which figure. This must be clarified.
This was detailed in Table S1. We have now replaced the table by an improved version, and we have also included the accession number of each data set used in the figure legends.
Why do the authors start in figure 1 with the description of an MNase- protected TAS for T.brucei, given that it has been clearly shown by the Siegel lab that there is a nucleosome depletion similar to other parasites?
We did not want to ignore the paper from Patterton’s lab because it was the first one to map nucleosomes genome-wide in T. brucei and the main finding of that paper claimed the existence of a well-positioned nucleosome at intergenic regions, what we though constitutes a point worth to be discussed. While Patterton’s work use MNase-seq from gel-purified samples and provides replicated experiments sequenced in really good depth; Siegel’s lab uses MNase-ChIP-seq of histone H3 but performs only one experiment and its input was not sequenced. So, each work has its own caveats and provides different information that together contributes to make a more comprehensive study. We think that bringing up both data sets to the discussion, as we have done in Figures 1 and 3, helps us and the community working in the field to enrich the discussion.
If the authors re- analyse the data, they should compare their pipeline to those used in the other studies, highlighting differences and potential improvements.
We are working on this point. We will provide a more detail description in the final revision.
Since many figures resemble those in already published studies, there seems little reason to repeat and compare without a detailed comparison of the pipelines and their differences.
Following the reviewer advice, we are now working on highlighting the main differences that justify analyzing the data the way we did and will be added in the finally revised method section.
At a first glance, some of the figures might look similar when looking at the original manuscripts comparing with ours. However, with a careful and detailed reading of our manuscripts you can notice that we have added several analyses that allow to unveil information that was not disclosed before.
First, we perform a systematic comparison analyzing every data set the same way from beginning to end, being the main difference with previous studies the thorough and precise prediction of TAS for the three organisms. Second, we represent the average chromatin organization relative to those predicted TASs for TriTryps and discuss their global patterns. Third, by representing the average chromatin into heatmaps, we show for the very first time, that those average nucleosome landscape are not just an average, they keep a similar organization in most of the genome. These was not done in any of the previous manuscripts except for our own (Beati, PLOS One 2023). Additionally, we introduce the discussion of how the extension of MNase reaction can affect the output of these experiments and we show 2D-plots and length distribution heatmaps to discuss this point (a point completely ignored in all the chromatin literature for trypanosomes). Furthermore, we made a far-reaching analysis by considering the contributions of each publish work even when addressed by different techniques. Finally, we discuss our findings in the context of a topic of current interest in the field, such as TriTryp’s genome compartmentalization.
Several previous Mnase- seq analysis studies addressing chromatin accessibility emphasized the importance of using varying degrees of chromatin digestion, from low to high digestion (30496478, 38959309, 27151365).
The reviewer is correct, and this point is exactly what we intended to illustrate in figure number 2. We appreciate he/she suggests these references that we are now citing in the final discussion. Just to clarify, using varying degrees of chromatin digestion is useful to make conclusions about a given organism but when comparing samples, strains, histone marks, etc. It is extremely important to do it upon selection of similar digested samples.
No information on the extent of DNA hydrolysis is provided in the original Mnase- seq studies. This key information can not be inferred from the length distribution of the sequenced reads.
The reviewer is correct that “No information on the extent of DNA hydrolysis is provided in the original Mnase-seq studies” and this is another reason why our analysis is so important to be published and discussed by the scientific community working in trypanosomes. We disagree with the reviewer in the second statement, since the level of digestion of a sequenced sample is actually tested by representing the length distribution of the total DNA sequenced. It is true that before sequencing you can, and should, check the level of digestion of the purified samples in an agarose gel and/or in a bioanalyzer. It could be also tested after library preparation, but before sequencing, expecting to observe the samples sizes incremented in size by the addition of the library adapters. But, the final test of success when working with MNase digested samples is to analyze length of DNA molecules by representing the histograms with length distribution of the sequenced DNA molecules. Remarkably, on occasions different samples might look very similar when run in a gel, but they render different length distribution histograms and this is because the nucleosome core could be intact but they might have suffered a differential trimming of the linker DNA associated to it or even be chewed inside (see Cole Hope 2011, section 5.2, doi: 10.1016/B978-0-12-391938-0.00006-9, for a detailed explanation).
As the input material are selected, in part gel- purified mono- nucleosomal DNA bands. Furthermore the datasets are not directly comparable, as some use native MNase, while others employ MNase after crosslinking; some involve short digestion times at 37 {degree sign} C, while others involve longer digestion at lower temperatures. Combining these datasets to support the idea of an MNase- sensitive complex at the TAS of T. brucei therefore may not be appropriate, and additional experiments using consistent methodologies would strengthen the study's conclusions.
In my opinion, describing an MNase- sensitive complex based solely on these data is not feasible. It requires specifically designed experiments using a consistent method and well- defined MNase digestion kinetics.
As the reviewer suggests, the ideal experiment would be to perform a time course of MNase reaction with all the samples in parallel, or to work with a fix time point adding increasing amounts of MNase. However, the information obtained from the detail analysis of the length distribution histogram of sequenced DNA molecules the best test of the real outcome. In fact, those samples with different digestion levels were probably not generated on purpose.
The only data sets that were gel purified are those from Mareé 2017 (Patterton’s lab), used in Figures 1, S1 and S2 and those from L. major shown in Fig 1. It was a common practice during those years, then we learned that is not necessary to gel purify, since we can sort fragment sizes later in silico when needed.
As we explained to reviewer #1, to avoid this conflict, we decided to remove this data from figures 2 and S3. In summary, the 3 remaining samples comes from the same lab, and belong to the same publication (Mareé 2022). These sample are the inputs of native MNase ChIp-seq, obtain the same way, totally comparable among each other.
Reviewer #3 (Significance (Required)):
Due to the lack of controlled MNase digestion, use of heterogeneous datasets, and absence of benchmarking against previous studies, the conclusions regarding MNase-sensitive complexes and their functional significance remain speculative. With standardized MNase digestion and clearly annotated datasets, this study could provide a valuable contribution to understanding chromatin regulation in TriTryps parasites.
As we have explained in the previous point our conclusions are valid since we do not compare in any figure samples coming from different treatments. The only exception to this comment could be in figure 3 when talking about MNase-ChIP-seq. We have now added a clear and explicit comment in the section and the discussion that despite having subtle differences in experimental procedures we arrive to the same results. This is the case for T. cruzi IP, run from crosslinked chromatin, compared to T. brucei’s IP, run from native chromatin.
Along the years it was observed in the chromatin field that nucleosomes are so tightly bound to DNA that crosslinking is not necessary. However, it is still a common practice specially when performing IPs. In our own hands, we did not observe any difference at the global level neither in T. cruzi or in my previous work with yeast.
...
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The authors analysed publicly accessible MNase-seq data in TriTryps parasites, focusing on the chromatin structure around trans-splicing acceptor sites (TASs), which are vital for processing gene transcripts. They describe a mild nucleosome depletion at the TAS of T. cruzi and L. major, whereas a histone-containing complex protects the TASs of T. brucei. In the subsequent analysis of T. brucei, they suggest that a Mnase-sensitive complex is localised at the TASs. For single-copy versus multi-copy genes, the authors show different di-nucleotide patterns and chromatin structures. Accordingly, they propose this difference could be a novel mechanism to ensure the accuracy of trans-splicing in these parasites.
Before providing an in- depth review of the manuscript, I note that some missing information would have helped in assessing the study more thoroughly; however, in the light of the available information, I provide the following comments for consideration.
The numbering of the figures, including the figure legends, is missing in the PDF file. This is essential for assessing the provided information. The publicly available Mnase- seq data are manyfold, with multiple datasets available for T. cruzi, for example. It is unclear from the manuscript which dataset was used for which figure. This must be clarified. Why do the authors start in figure 1 with the description of an MNase- protected TAS for T.brucei, given that it has been clearly shown by the Siegel lab that there is a nucleosome depletion similar to other parasites? If the authors re- analyse the data, they should compare their pipeline to those used in the other studies, highlighting differences and potential improvements. Since many figures resemble those in already published studies, there seems little reason to repeat and compare without a detailed comparison of the pipelines and their differences. Several previous Mnase- seq analysis studies addressing chromatin accessibility emphasised the importance of using varying degrees of chromatin digestion, from low to high digestion (30496478, 38959309, 27151365). No information on the extent of DNA hydrolysis is provided in the original Mnase- seq studies. This key information can not be inferred from the length distribution of the sequenced reads. As the input material are selected, in part gel- purified mono- nucleosomal DNA bands. Furthermore the datasets are not directly comparable, as some use native MNase, while others employ MNase after crosslinking; some involve short digestion times at 37 {degree sign} C, while others involve longer digestion at lower temperatures. Combining these datasets to support the idea of an MNase- sensitive complex at the TAS of T. brucei therefore may not be appropriate, and additional experiments using consistent methodologies would strengthen the study's conclusions. In my opinion, describing an MNase- sensitive complex based solely on these data is not feasible. It requires specifically designed experiments using a consistent method and well- defined MNase digestion kinetics.
Due to the lack of controlled MNase digestion, use of heterogeneous datasets, and absence of benchmarking against previous studies, the conclusions regarding MNase-sensitive complexes and their functional significance remain speculative. With standardized MNase digestion and clearly annotated datasets, this study could provide a valuable contribution to understanding chromatin regulation in TriTryps parasites.
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Siri et al. perform a comparative analysis using publicly available MNase-seq data from three trypanosomatids (T. brucei, T. cruzi, and Leishmania), showing that a similar chromatin profile is observed at TAS (trans-splicing acceptor site) regions. The original studies had already demonstrated that the nucleosome profile at TAS differs from the rest of the genome; however, this work fills an important gap in the literature by providing the most reliable cross-species comparison of nucleosome profiles among the tritryps. To achieve this, the authors applied the same computational analysis pipeline and carefully evaluated MNase digestion levels, which are known to influence nucleosome profiling outcomes.
In my view, the main conclusion is that the profiles are indeed similar-even when comparing T. brucei and T. cruzi. This was not clear in previous studies (and even appeared contradictory, reporting nucleosome depletion versus enrichment) largely due to differences in chromatin digestion across these organisms. The manuscript could be improved with some clarifications and adjustments:
"In trypanosomes, there are no canonical promoter regions." - please check Cordon-Obras et al. (Navarro's group).
Please, cite the study by Wedel et al. (Siegel's group), which also performed MNase-seq analysis in T. brucei.
Figure-specific comments:
Fig. S3: Why does the number of larger fragments increase with greater MNase digestion? Shouldn't the opposite be expected?
Fig. S5B: Why not use MNase conditions under which T. cruzi and T. brucei display comparable profiles at TAS? This would facilitate interpretation.
Minor points:
There are several typos throughout the manuscript.
Methods: "Dinucelotide frecuency calculation."
In my view, the main conclusion is that the profiles are indeed similar-even when comparing T. brucei and T. cruzi. This was not clear in previous studies (and even appeared contradictory, reporting nucleosome depletion versus enrichment) largely due to differences in chromatin digestion across these organisms.
Audience: basic science and specialized readers.
Expertise: epigenetics and gene expression in trypanosomatids.
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This study explores chromatin organization around trans-splicing acceptor sites (TASs) in the trypanosomatid parasites Trypanosoma cruzi, T. brucei and Leishmania major. By systematically re-analyzing MNase-seq and MNase-ChIP-seq datasets, the authors conclude that TASs are protected by an MNase-sensitive complex that is, at least in part, histone-based, and that single-copy and multi-copy genes display differential chromatin accessibility. Altogether, the data suggest a common chromatin landscape at TASs and imply that chromatin may modulate transcript maturation, adding a new regulatory layer to an unusual gene-expression system.
I value integrative studies of this kind and appreciate the careful, consistent data analysis the authors implemented to extract novel insights. That said, several aspects require clarification or revision before the conclusions can be robustly supported. My main concerns are listed below, organized by topic/result section.
TAS prediction:
Results
Results
Genomes and annotations:
Reproducibility and broader integration:
Minor / editorial comments:
Referee cross-commenting
Comment 1: I think Reviewer #2 and Reviewer #3 missed that they authors of this manuscript do cite and consider the results from Wedel at al. 2017. They even re-analysed their data (e.g. Figure 3a). I second Reviewer #2 comment indicating that the inclusion of a schematic figure to help readers visualize and better understand the findings would be an important addition.
Comment 2: I agree with Reviewer #3 that the use of different MNase digestion procedures in the different datasets have to be considered. On the other hand, I don't think there is a problem with figure 1 showing an MNase-protected TAS for T. brucei as it is based on MNase-seq data and reproduces the reported results (Maree et al. 2017). What the Siegel lab did in Wedel et al. 2017 was MNase-ChIPseq of H3 showing nucleosome depletion at TAS, but both results are not necessary contradictory: There could still be something else (which does not contain H3) sitting on the TAS protecting it from MNase digestion.
This study provides a systematic comparative analysis of chromatin landscapes at trans-splicing acceptor sites (TASs) in trypanosomatids, an area that has been relatively underexplored. By re-analyzing and harmonizing existing MNase-seq and MNase-ChIP-seq datasets, the authors highlight conserved and divergent features of nucleosome occupancy around TASs and propose that chromatin contributes to the fidelity of transcript maturation.
The significance lies in three aspects:
My expertise is in gene regulation in eukaryotic parasites, with a focus on bioinformatic analysis of high-throughput sequencing data
What good man would prefer a country covered with forests and ranged by a fewthousand savages to our extensive Republic, studded with cities, towns, andprosperous farms embellished with all the improvements which art can devise orindustry execute, occupied by more than 12,000,000 happy people, and filled withall the blessings of liberty, civilization and religion?
Honestly this is a very interesting argument. We can all sit here hundreds of years later and say that this was all wrong but then the world we know would not exist. This brings up so many unanswerable questions about morality, history, and philosophy. What is even the point of discussing such things? The only reason I see for judging the morality of historical actions is so that we can make better decisions in the present. So yes, the vast majority of Americans benefit from this genocide, but that does not make criticism of it irrelevant. What it does mean is that we should take no satisfaction or moral victory from criticizing history. As for Jackson's point in his own time, it isn't really asking this question. The point is actually to argue that this genocide has been and will continue to be worth it. Jackson is saying that if he was sent back 150 years he would do the same thing as the forefathers. It is worth noting that this argument reframes the conflict, shifting attention from the possibility of better treatment in the future to justifying past sins. It thus implicitly argues that destroying the natives is fine.
Dickie Delacroix
Sounds like a french name
boisterous
noisy, energetic, and cheerful; rowdy
Tessie Hutchinson was in the center of a cleared space by now, and she held her hands out desperately as the villagers moved in on her. “It isn’t fair,” she said. A stone hit her on the side of the head.
Tessie was chosen to get stoned by the lottery