for - progress trap - AI - like NAFTA

for - progress trap - NAFTA

for - cosmolocal model - AI is forcing us towards socialism

for - forte - comparison - foreign immigrants Vs AI immigrants - sorry about foreign immigrants - should be more worried about AI immigrants

for - quote - millions of Nobel Prize level digital immigrants

for - social media - progress trap

for - progress trap - AI - narrow boundary

for - AI - Deep Humanity - the sacred

for - AI - immortality project

for - ai tech leaders - immortality projects - denial of death

bonjour, j'ai une preoccupation et elle est la suivante : je suis aller dans cette section de code pen j'ai constaté que les valeurs attribuées à l'attribu class ne sont declarées de la meme maniére dans le css. et j'aimerai comprendre pourquoi s'il vous plait.

aussi j'aimerai comprendre si Box apres l'espace dans le HTML lors de l'affectation des valeurs à l'attribut veut tout simplement dire que l'on aura des valeurs geometriques comme par exemple un carré et donc c'est la raison pour laquelle il ne figure pas dans le CSS. merci d'avance pour votre orientation

Editors Assessment:

Coded and written up as part of the African Society for Bioinformatics and Computational Biology (ASBCB) Omicscodeathons, EMImR is a novel Shiny application for transcriptomic and epigenomic change identification and correlation wrapped up using a combination of Bioconductor and CRAN packages. Case studies are on publicly available GEO data corresponding to sequencing data of human blood cell samples of multiple sclerosis patients to demonstrate how the tool works. And a documentation and videos are provided. Peer review and the study highlighting the usefulness of the developed tool for analyzing transcriptomic and epigenomic data.

This evaluation refers to version 1 of the preprint

This work has been published in GigaByte Journal under a CC-BY 4.0 license (https://doi.org/10.46471/gigabyte.168), and has published the reviews under the same license.

Reviewer 1. Haikuo Li

Is there a clear statement of need explaining what problems the software is designed to solve and who the target audience is? No. Should be made more clear.

Comments: The authors developed EMImR as an R toolkit and open-sourced software for analysis of bulk RNA-seq as well as epigenomic sequencing data including DNA methylation seq and non-coding RNA profiling. This work is very interesting and should be of interest to people interested in transcriptomic and epigenomic data analysis but without computational background. I have two major comments: 1. Results presented in this manuscript were only from microarray datasets and are kind of “old” data. Although these data types and sequencing platforms are still very valuable, I don’t think they are widely used as of today, and therefore, it may be less compelling to the audience. It is suggested to validate EMImR using additional more recently published datasets. 2. The authors studied bulk transcriptomic and epigenomic sequencing data. In fact, single-cell and spatially resolved profiling of these modalities are becoming the mainstream of biomedical research since those methods offer much better resolution and biological insights. The authors are encouraged to discuss some key references of this field (for example, PMIDs: 34062119 and 38513647 for single-cell multiomics; PMID: 40119005 for spatial multiomics sequencing), potentially as the future direction of package development. Re-review: The authors have answered my questions and added new content in the Discussion section as suggested.

Reviewer 2. Weiming He

Dear Editor-in-Chief, The EMImR developed by the author is a Shiny application designed for the identification of transcriptomic and epigenomic changes and data association. This program is mainly targeted at Windows UI users who do not possess extensive computational skills. Its core function is to identify the intersections between genetic and epigenetic modifications

Review Recommendation I recommend that after making appropriate revisions to the current “Minor Revision”, the article can be accepted. However, the author needs to address the following issues.

Major Issue The article does not provide specific information on the resource consumption (memory and time) of the program. This is crucial for new users. Although we assume that the resource consumption is minimal, users need to know the machine configuration required to run the program. Therefore, I suggest adding two columns for “Time” and “Memory” in Table 1.

Minor Issues 1. GitHub Page The Table of Contents on the GitHub page provides a Demonstration Video. However, due to restricted access to YouTube in some regions, it is recommended to also upload a manual in PDF format named “EMImR_manual.pdf” on GitHub. In step 4 of the Installation Guide, it states that “All dependencies will be installed automaticly”. It is advisable to add a step: if the installation fails, prompt the user about the specific error location and guide the user to install the dependent packages manually first to ensure successful installation. Currently, the command “source(‘Dependencies_emimr.R’)” does not return any error messages, which is extremely inconvenient for novice users. The author can provide the maintainer's email address so that users can seek timely solutions when encountering problems

1. R Version The author recommends using R - 4.2.1 (2022), which was released three years ago. The current latest version is R 4.5.1. It is suggested that the author test the program with the latest version to ensure its adaptability to future developments.

2. Flowchart Suggestion It is recommended to add a flowchart to illustrate the sequential relationships among packages such as DESeq2 for differential analysis, clusterProfiler for clustering, enrichplot for plotting, and miRNA - related packages (this is optional).

4.Function Addition Currently, the program seems to lack a button for saving PDFs, as well as functions for batch uploading, saving sessions, and one - click exporting of PDF/PNG files. It is recommended to add the “shinysaver” and “downloadHandler” functions to fulfill these requirements.

1. Personalized Features and Upgrade Plan To attract more users, more personalized features should be added. The author can mention the future upgrade plan in the discussion section. For example, currently, DESeq2 is used for differential analysis, and in future upgrades, more methods such as PossionDis, NOIseq, and EBseq could be provided for users to choose from.

2. Text Polishing Suggestions 6.1 Unify the usage of “down - regulated” and “downregulated”, preferably using the latter. 6.2 “R - studio version” ---》 “RStudio” 6.3 Lumian, ---》 Lumian 6.4 no login wall ---》 does not require user registration 6.5 Rewrite “genes were simultaneously differentially expressed and methylated” as “genes that were both differentially expressed and differentially methylated”. 6.6 Ensure that Latin names of species are in italics 6.7 make corresponding modifications to other sentences to improve the accuracy and professionalism of the language in the article.

The above are my detailed review comments on this article. I hope they can provide a reference for your decision - making.

今後主流になるかは

くらいでいいのでは

以下は冗長なので省略でよさそう

これだと短すぎるので、なんかのリポジトリをまるっと型チェックとかする方がいいかなと思いました

このリンクがわかりにくいので、説明を書いて欲しいかな。

サンドボックスでexample.pyを◯◯した結果

みたいな

nits: 比較する、でいいかなと

VS Codeと書くのが正しいはず https://code.visualstudio.com/

nits: 体言止めと~~するがまざっているのでどっちかに統一がいかな

高速に動作 付ける機能

でよさそう

あとで比較対象にもなっているので、「型チェッカーにはmypy、pyrightなどがありますが、Pyrefryには◯◯な特徴があります」みたいな感じの文章があるといいなと思いました

imho: コマンドの公式ドキュメントへのリンクがあると嬉しいなと思いました

感想です：便利すぎますね

感想です：おおおお！

IMO：Pyreflyの生まれた経緯に少し触れたいです！後半の納得感の味付けにもなりそうかなと思いまして！ ・PyreってのをFacebookが作ってた ・色々限界きた ・IDEを第一に考えた「型チェッカー + 言語サーバ」の設計思想がある

以下の記事にありました！ Why we built Pyrefly https://engineering.fb.com/2025/05/15/developer-tools/introducing-pyrefly-a-new-type-checker-and-ide-experience-for-python/

nits: 名はなくてもよさそうです。（あるいは文章のほうに名をつけるか）

from

/hyperpost/🌐/🧊/0/

Origo Folder - hyperpost web directory on IPFS

https://k51qzi5uqu5div1auuxm59ygav4p7gdg9z4e9iggtu6m43rmc3xw75mczx2b7x.ipns.dweb.link/📝/?isPathWritable=true&path=/♖/hyperpost/🌐/🧊/0/index.html

cut the middle bit out and have access to the document to read and share

📝/?isPathWritable=true&path=

via dweb link

root of the ipfs indy web

Origo Folder - hyperpost web directory on IPFS

哪些年份的

It's raw Mastery

Important steps for a solid introduction

Know your genre when making your concept map

this is a helpful and realistic explanation of the writing process

This section argues that more research is needed to understand effective teaching for historically underserved students, especially studies that include the voices of families and communities. It also encourages teachers to study their own practice, valuing their lived experiences. Overall, it challenges both researchers and educators to rethink what “good teaching” means and to ensure it is accessible to all students.

This text explains that culturally relevant pedagogy goes beyond finding “correct” teaching strategies. Instead, it emphasizes a humanizing approach that values students’ histories, realities, and perspectives. It builds on earlier ideas about pedagogical knowledge (Shulman) and critiques the limits of expert teaching models (Berliner), arguing that teaching must connect deeply to students’ lived experiences.

This text highlights that culturally relevant pedagogy centers students’ lived experiences. Instead of focusing on perfect teaching methods, it emphasizes a humanizing approach that values students’ identities, histories, and perspectives, arguing that meaningful teaching must connect directly to who learners are.

MUST: 結果が書かれていないので追加する

• Companies aggressively push app downloads, especially in places like Taiwan, offering discounts but often installing without full consent, leading to spam and unwanted data collection.
• Avoid handing over your phone to staff and never download apps, as they provide minimal benefits compared to the risks involved.
• Primary risks include surveillance capitalism: apps enable extensive data tracking for targeted ads and "surveillance pricing," where prices vary based on inferred financial status (e.g., charging more after payday).
• This undermines fair pricing, giving corporations power over individual costs beyond market forces.
• Apps enforce binding arbitration clauses in Terms of Service, waiving rights to court, jury trials, or oversight; examples include Disney attempting to force arbitration in a wrongful death case linked to a Disney+ trial.
• Predictions highlight future abuses, like arbitration forced via unrelated services (e.g., Uber Eats leading to self-driving car disputes).
• Recommendation: Use websites or PWAs instead to preserve privacy and rights.

Hacker News Discussion

• Users debate apps vs. websites/PWAs: many praise PWAs (e.g., Mastodon, Photoprism) for performance when implemented well, criticizing poor web apps and noting apps often wrap webviews with extra tracking.
• Privacy concerns dominate: native apps access more device data (contacts, SMS, biometrics, etc.) even with permissions, unlike sandboxed PWAs; tools like NetGuard suggested for blocking app internet access.
• Loyalty discounts viewed as modern coupons by some, saving money despite data sharing, but others warn of surveillance pricing via purchase patterns and arbitration risks.
• Experiences shared: retailers reject Apple Pay to force accounts; global pushiness for apps noted; arbitrage limits price discrimination viability.
• Calls for better OS controls, open-source apps without tracking, and skepticism of app store security.

Then you could move this to below the research sites sections and rewrite this as the short introductory paragraph to your main methods called "Data-processing and analysis" or something similar. Essentially describe your general workflow and then go into detail in the following sections. You could take a similar approach to this paper, although there may be other examples: https://www.mdpi.com/1999-4907/15/6/1043

It would end with your existing sentences

A slightly reworded version of this may be better at the end of your intro as part of an aims/objectives and methodological approach paragraph (without the figure reference at this stage).

Add how you tagged each tree. E.g., did you tag in the centre of each crown, at the base of the trunk, within a set distance from the trunk?

I would probably add a statement about the final accuracy if you have that data, especially if it was much better than 30cm. E.g., "..confirmed accuracy of <30 cm with the final mean location accuracy being XX ± XX cm (SD).

I assume these numbers are just place holders

Maybe add env./weather conditions here and remove the conservation groups unless you need to refer to this later. You can add them all to your acknowledgements. Also maybe add the size of each site.

I think it is important to give an indication/description here of the type of bush you are working in (plant types, size of areas, what the surrounding areas are).

For example, mixed native and give some examples of plants. You could even include an example image/snip of the ortho for each to give people some perspective on the sites. They key message being that it is a complex matrix of different but similar trees, the bush is dense but they relatively small sites nestled in urban areas close to houses. All things you will come back to in your discussion.

For auckland sites, you could use the codes found in the "ecosystem extent" layer on the council GIS and described here: https://knowledgeauckland.org.nz/media/1399/indigenous-terrestrial-and-wetland-ecosystems-of-auckland-web-print-mar-2017.pdf

You would have to look into if there is something equivalent for Hamilton

add: "H1 is unmanaged and the management status of H2 is unknown". If your observations suggest it is also not managed you could add "but assumed to be unmanaged based on field observations."

I would just include this information in the text. If anything, a summary table of the flight parameters etc. per site may be more useful. If this was for a paper, I would probably put the site-based parameters table in an appendix though, so could go either way for the traditional thesis-style

I would split this into two sub-headings "UAV-MSI data capture" and "UAV-LiDAR data capture" or similar names,

Key information to get across: - Drone used - Sensor used (incl. band wavelengths, and maybe the accuracy levels for the LiDAR vertical and horizontal measurements) - Flight parameters for multispec (resolution (height + GSD), overlap, flight speed) - Flight parameters for LiDAR (no. of returns, flight height, speed, overlap), maybe also resolution, Graham might have more thoughts on the LiDAR parameters. LiDAR/MSI pre-processing - You could take the approach of this paper and include the pre-processing steps in these sections too since these steps are not the point of your work - https://www.mdpi.com/1999-4907/15/6/1043

But essentially, you should include anything someone would need to repeat your flights in another location. So maybe also state that all other camera settings were set to default settings. You can always include a summary table in the appendix too if there is too much going on.

Such a phrasing, seem like two independent contradict statements at first but they are just the same thing twice after reading the main text. The RR numbers are not even showed in the main text.

Copied from a previous page

Find the specific name for the chapter, and spell out.

Spell out

Make sure the font size is consistent on this page.

Spell out. Also, find out the precise name for the chapter..

This should be

$$ \alpha = \lambda_1 y_1 v_1 + \cdots + \lambda_m y_m v_m $$

Notice that \(\beta\) can be found of the binding condition in the primal problem for some \(\lambda_i > 0\).

Please spell out

Spell out

The darker background makes it really difficult for me to read...use a lighter background if possible, to increase the contrast with the print color.

Be consistent with font styles, colors, size, etc.

Spell out any acronyms!

Spell out!

К этому моменту Феофан выработал некоторое правило, которым можно опровергать всякую ересь. Нужно попытаться это правило сформулировать.

ууууу, ну настоящая феноменология! самоочевидность!

красиво

code

code

code

sketch code

Longest chain of carbons e.g. H-C-C-C-C-H - parent chain: 4 carbons e.g. H-C-C-C-H - parent chain: 4 carbons C C

CHallenges to brics financing systems

important

domination of the US dollar exposes them to western sanctions - because the moeny is ofrced to go through US systems and they can easily block or snactio them

recreating old systems. Their absence undermines te institutions

BRICS are an informal gorouping of emerging economies that aim to increase their

BRICS main purpose - to challenge western influence in international institutions

it clearly defines both the porpuse and the basic structure of this type of essay

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

Learn more at Review Commons

Reply to the reviewers

Manuscript number: RC -2025-03175

Corresponding author(s): Gernot Längst

[Please use this template only if the submitted manuscript should be considered by the affiliate journal as a full revision in response to the points raised by the reviewers.

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If you wish to submit a preliminary revision with a revision plan, please use our "Revision Plan" template. It is important to use the appropriate template to clearly inform the editors of your intentions.]

1. General Statements [optional]

This section is optional. Insert here any general statements you wish to make about the goal of the study or about the reviews.

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We thank the reviewers for their efforts and detailed evaluation of our manuscript. We think that the comments of the reviewers allowed us to significantly improve the manuscript.

With best regards

The authors of the manuscript

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

Summary: Holzinger et al. present a new automated pipeline, nucDetective, designed to provide accurate nucleosome positioning, fuzziness, and regularity from MNase-seq data. The pipeline is structured around two main workflows-Profiler and Inspector-and can also be applied to time-series datasets. To demonstrate its utility, the authors re-analyzed a Plasmodium falciparum MNase-seq time-series dataset (Kensche et al., 2016), aiming to show that nucDetective can reliably characterize nucleosomes in challenging AT-rich genomes. By integrating additional datasets (ATAC-seq, RNA-seq, ChIP-seq), they argue that the nucleosome positioning results from their pipeline have biological relevance.

Major Comments:

Despite being a useful pipeline, the authors draw conclusions directly from the pipeline's output without integrating necessary quality controls. Some claims either contradict existing literature or rely on misinterpretation or insufficient statistical support. In some instances, the pipeline output does not align with known aspects of Plasmodium biology. I outline below the key concerns and suggested improvements to strengthen the manuscript and validate the pipeline:

Clarification of +1 Nucleosome Positioning in P. falciparum The authors should acknowledge that +1 nucleosomes have been previously reported in P. falciparum. For example, Kensche et al. (2016) used MNase-seq to map ~2,278 TSSs (based on enriched 5′-end RNA data) and found that the +1 nucleosome is positioned directly over the TSS in most genes:

"Analysis of 2278 start sites uncovered positioning of a +1 nucleosome right over the TSS in almost all analysed regions" (Figure 3A).

They also described a nucleosome-depleted region (NDR) upstream of the TSS, which varies in size, while the +1 nucleosome frequently overlaps the TSS. The authors should nuance their claims accordingly. Nevertheless, I do agree that the +1 positioning in P. falciparum may be fuzzier as compared to yeast or mammals. Moreover, the correlation between +1 nucleosome occupancy and gene expression is often weak and that several genes show similar nucleosome profiles regardless of expression level. This raises my question: did the authors observe any of these patterns in their new data?

We appreciate the reviewer’s insightful comment and agree that +1 nucleosomes and nucleosome depleted promoter regions have been previously reported in P. falciparum, notably by the Bartfai and Le Roch groups, including Kensche et al. (PMID: 26578577). Our study advances this understanding by providing, for the first time, a comprehensive view of the entirety of a canonical eukaryotic promoter architecture in P. falciparum—encompassing the NDR, the well-positioned +1 nucleosome, and the downstream phased nucleosome array. This downstream nucleosome array structure has not been characterized before, as prior studies noted a “lack of downstream nucleosomal arrays” (PMID: 26578577) or “relatively random” nucleosome organization within gene bodies (PMID: 24885191). We have revised the manuscript to more clearly acknowledge previous work and highlight our contributions. The changes we applied in the manuscript are highlighted in yellow and shown as well below.

In the Abstract L26-L230: Contrary to the current view of irregular chromatin, we demonstrate for the first time regular phased nucleosome arrays downstream of TSSs, which, together with the established +1 nucleosome and upstream nucleosome-depleted region, reveal a complete canonical eukaryotic promoter architecture in Pf.

Introduction L156-L159: For example, we identify a phased nucleosome array downstream of the TSS. Together with a well-positioned +1 nucleosome and an upstream nucleosome-free region. These findings support a promoter architecture in Pf that resembles classical eukaryotic promoters (Bunnik et al. 2014, Kensche et al. 2016).

Results L181-L183: These new Pf nucleosome maps reveal a nucleosome organisation at transcription start sites (TSS) reminiscent of the general eukaryotic chromatin structure, featuring a reported well-positioned +1 nucleosome , an upstream nucleosome-free region (NFR, Bunnik et al. 2014, Kensche et al. 2016), and shown for the first time in Pf, a phased nucleosome array downstream of the TSS.

Discussion L414-L419: Previous analyses of Pf chromatin have identified +1 nucleosomes and NFRs (Bunnik et al 2014, Kensche et al. 2016). Here we extend this understanding by demonstrating phased nucleosome array structures throughout the genome. This finding provides evidence for a spatial regulation of nucleosome positioning in Pf, challenging the notion that nucleosome positioning is relatively random in gene bodies (Bunnik et al. 2014, Kensche et al. 2016). Consequently our results contribute to the understanding that Pf exhibits a typical eukaryotic chromatin structure, including well-defined nucleosome positioning at the TSS and regularly spaced nucleosome arrays (Schones et al. 2008; Yuan et al. 2005).

Regarding the reviewer’s question on +1 nucleosome dynamics. Our data agrees with the reviewer and other studies (e.g. PMID: 31694866), that the +1 nucleosome position is robust and does not correlate with gene expression strength. In the manuscript we show that dynamic nucleosomes are preferentially detected at the –1 nucleosome position (Figure 2C). In line with that we show that the +1 nucleosome position does not markedly change during transcription initiation of a subset of late transcribed genes (Figure 5A). However, we observe an opening of the NDR and within the gene body increased fuzziness and decreased nucleosome array regularity (Figure S4A). To illustrate the relationship between the +1 nucleosome positioning and expression strength, we have included a heatmap showing nucleosome occupancy at the TSS, ordered according to expression strength (NEW Figure S4C):

We included a sentence describing the relationship of +1 nucleosome position with gene expression in L257-L258: Furthermore, the +1 nucleosome positioning is unaffected by the strength of gene expression (Figure S2C).

__ Lack of Quality Control in the Pipeline __

The authors claim (lines 152-153) that QC is performed at every stage, but this is not supported by the implementation. On the GitHub page (GitHub - uschwartz/nucDetective), QC steps are only marked at the Profiler stage using standard tools (FastQC, MultiQC). The Inspector stage, which is crucial for validating nucleosome detection, lacks QC entirely. The authors should implement additional steps to assess the quality of nucleosome calls. For example, how are false positives managed? ROC curves should be used to evaluate true positive vs. false positive rates when defining dynamic nucleosomes. How sequencing biases are adressed?

The workflow overview chart on GitHub was not properly color coded. Therefore, we changed the graphics and highlighted the QC steps in the overview charts accordingly:

Based on our long standing expertise of analysing MNase-seq data (PMID: 38959309, PMID: 37641864, PMID: 30496478, PMID: 25608606), the best quality metrics to assess the performance of the challenging MNase experiment are the fragment size distributions revealing the typical nucleosomal DNA lengths and the TSS plots showing a positioned +1 nucleosome and regularly phased nucleosome arrays downstream of the +1 nucleosome. Additionally, visual inspection of the nucleosome profiles in a genome browser is advisable. We make those quality metrics easily available in the nucDetective Profiler workflow (Insertsize Histogram, TSS plot and provide nucleosome profile bigwig files). Furthermore, the PC and correlation analysis based on the nucleosome occupancy in the inspector workflow allows to evaluate replicate reproducibility or integrity of time series data, as shown for data evaluated in this manuscript.

The inspector workflow uses the well-established DANPOS toolkit to call nucleosome positions. Based on our experience, this step is particularly robust and well-established in the DANPOS toolkit (PMID: 23193179), so there is no need to reinvent it. Nevertheless, appropriate pre-processing of the data as done in the nucDetective pipeline is crucial to obtain highly resolved nucleosome positions. Using the final nucleosome profiles (bigwig) and the nucleosome reference positions (bed) as output of the Inspector workflow allows visual inspection of the called nucleosomes in a genome viewer. Furthermore, to avoid using false positive nucleosome positions for dynamic nucleosome analysis, we take only the 20% best positioned nucleosomes of each sample, as determined by the fuzziness score.

We understand the value of a gold standard of dynamic nucleosomes to test performance using ROC curves. However, we are not aware that such a gold standard exists in the nucleosome analysis field, especially not when using multi-sample settings, such as time series data. One alternative would be to use simulated data; however, this has several limitations:

• __Lack of biological complexity: __simulated data often fails to capture the full complexity of biological systems including the heterogeneity, variability, and subtle dependencies present in real-world data. Simplifications and omissions in simulation models can result in test datasets that are more tractable but less realistic, causing software to appear robust or accurate under idealized conditions, while underperforming on actual experimental data.
• __Risks of Overfitting: __Software may be tuned to perform well on simulated datasets leading to overfitting and falsely inflated performance metrics. This undermines the predictive or diagnostic value of the results for real biological data

• Poor Model Fidelity and Hidden Assumptions: The authenticity of simulated data is bounded by the fidelity of the underlying models. If those models are inaccurate or make untested assumptions, the generated data may not reflect real experimental or clinical scenarios. This can mask software shortcomings or bias validation toward specific, perhaps irrelevant, scenarios. Therefore, we decided to validate the performance of the pipeline in the biological context of the analyzed data:

• PCA analysis of the individual nucleosome features shows a cyclic structure as expected for the IDC (Fig. 1D-G).

• Nucleosome occupancy changes anti-correlate with chromatin accessibility (Fig. 3B) as expected.
• Dynamic nucleosome features correlate with expression changes (Fig. 5C) We are aware that MNase-seq experiments might have sequence bias caused by the enzyme's endonuclease sequence preference (PMID: 30496478). However, the main aim of the nucDetective pipeline is to identify dynamic nucleosome features genome wide. Therefore, we are comparing the nucleosome features across multiple samples to find the positions in the genome with the highest variability. Comparisons are performed between the same nucleosome positions at the same genomic sites across multiple conditions, so the sequence context is constant and does not confound the analysis. This is like the differential expression analysis of RNA-seq data, where the gene counts are not normalized by gene length. Introducing a sequence normalization step might distort and bias the results of dynamic nucleosomes.

We included a paragraph describing the limitations to the discussion (L447-457):

Depending on the degree of MNase digestion, preferentially nucleosomes from GC rich regions are revealed in MNase-seq experiments (Schwartz et al. 2019). However, no sequence or gDNA normalisation step was included in the nucDetective pipeline. To identify dynamic nucleosomes, comparisons are performed between the same nucleosome positions at the same genomic sites across multiple samples. Hence, the sequence context is constant and does not confound the analysis. Introducing a sequence normalization step might even distort and bias the results. Nevertheless, it is highly advisable to use low MNase concentrations in chromatin digestions to reduce the sequence bias in nucleosome extractions. This turned out to be a crucial condition to obtain a homogenous nucleosome distribution in the AT-rich intergenic regions of eukaryotic genomes and especially in the AT-rich genome of Pf (Schwartz et al. 2019, Kensche et al. 2016).

__ Use of Mono-nucleosomes Only __

The authors re-analyze the Kensche et al. (2016) dataset using only mono-nucleosomes and claim improved nucleosome profiles, including identification of tandem arrays previously unreported in P. falciparum. Two key issues arise: 1. Is the apparent improvement due simply to focusing on mono-nucleosomes (as implied in lines 342-346)?

The default setting in nucDetective is to use fragment sizes of 140 – 200 bp, which corresponds to the main mono-nucleosome fraction in standard MNase-seq experiments. However, the correct selection of fragment sizes may vary depending on the organism and the variations in MNase-seq protocols. Therefore, the pipeline offers the option of changing the cutoff parameter (--minLen; --maxLen), accordingly. Kensche et al thoroughly tested and established the best parameters for the data set. We agree with their selected parameters and used the same cutoffs (75-175 bp) in this manuscript. For this particular data set, the fragment size selection is not the reason why we obtain a better resolution. MNase-seq analysis is a multistep process which is optimized in the nucDetective pipeline. Differences in the analysis to Kensche et al are at the pre-processing stage and alignment step:

Kensche et al. : “Paired-end reads were clipped to 72 bp and all data was mapped with BWA sample (Version 0.6.2-r126)”

nucDetective:

• Trimming using TrimGalore --paired -q 10 --stringency 2
• Mapping using bowtie2 --very-sensitive –dovetail --no-discordant
• MAPQ >= 20 filtering of aligned read-pairs (samtools). The manuscript text L379 was changed to

This is achieved using MNase-seq optimized alignment settings, and proper selection of the fragment sizes corresponding to mono-nucleosomal DNA to obtain high resolution nucleosome profiles.

How does the pipeline perform with di- or tri-nucleosomes, which are also biologically relevant (Kensche et al., 2016 and others)? Furthermore, the limitation to mono-nucleosomes is only mentioned in the methods, not in the results or discussion, which could mislead readers.

The pipeline is optimized for mono-nucleosome analysis. However, the cutoffs for fragment size selection can be adjusted to analyse other fragment populations in MNase-seq data (--minLen; --maxLen). For example we know from previous studies that the settings in the pipeline could be used for sub-nucleosome analysis as well (PMID: 38959309). Di- or Tri-nucleosome analysis we have not explicitly tested. However, in a previous study (PMID: 30496478) we observed that the inherited MNase sequence bias is more pronounced in di-nucleosomes, which are preferentially isolated from GC-rich regions. This is in line with the depletion of di-nucleosomes in AT-rich intergenic regions in Pf, as was already described by Kensche et al.

Changes to the manuscript text: We included a paragraph describing the limitations to the discussion (L428-434):

The nucDetective pipeline has been optimized for the analysis of mono-nucleosomes. However, the selection of fragment sizes can be adjusted manually, enabling the pipeline to be used for other nucleosome categories. The pipeline is suitable to map and annotate sub-nucleosomal particles (

__ Reference Nucleosome Numbers __

The authors identify 49,999 reference nucleosome positions. How does this compare to previous analyses of similar datasets? This should be explicitly addressed.

We thank the reviewer for this suggestion. In order to put our results in perspective, it is important to distinguish between reference nucleosome positions (what we reported in the manuscript) and all detectable nucleosomes. The reference positions are our attempt to build a set of nucleosome positions with strong evidence, allowing confident further analysis across timepoints. The selection of a well positioned subset of nucleosomes for downstream analysis has been done previously (PMID: 26578577) and the merging algorithm we used across timepoints is also used by DANPOS to decide if a MNase-Seq peak is a new nucleosome position or belongs to an existing position (PMID: 23193179).

To be able to address the reviewer suggestion we prepared and added a table to the supplementary data, including the total number of all nucleosomes detected by our pipeline at each timepoint. We adjusted the results to the following (L223-226):

“The pipeline identified a total of 127370 ± 1151 (mean ± SD) nucleosomes at each timepoint (Supplementary Data X). To exclude false positive positions in our analysis, we conservatively selected 49,999 reference nucleosome positions, representing sites with a well-positioned nucleosome at least at one time point (see Methods). Among these 1192 nucleosomes exhibited […]”

Several groups reported nucleosome positioning data for P. falciparum (PMID: 20015349, PMID: 20054063, PMID: 24885191, PMID: 26578577), however only Ponts et al (2010) reported resolved numbers (~45000-90000 nucleosomes depending in development stage) and Bunnik et al reported ~ 75000 nucleosomes in a graph. Although we do not know the reason of why the other studies did not include specific numbers, we speculate that the data quality did not allow them to confidently report a number. In fact, nucleosomal reads are severely depleted in AT-rich intergenic regions in the Ponts and Bunnik datasets. In contrast, Kensche et al (and our analysis) shows that nucleosomes can be identified throughout the genome of Pf. Therefore, the nucleosome numbers reported by Ponts et al and Bunnik et al are very likely underestimated.

We included the following text in the discussion, addressing previously published datasets (L404 – 405):

“For example, our pipeline was able to identify a total of ~127,000 nucleosomes per timepoint (=5.4 per kb) in range with observed nucleosome densities in other eukaryotes (typically 5 to 6 per kb). From these, we extracted 49,999 reference nucleosome positions with strong positioning evidence across all timepoints, which we used to characterize nucleosome dynamics of Pf longitudinally. Previous studies of P. falciparum chromatin organization, did not report a total number of nucleosomes (Westenberger et al. 2009, Kensche et al. 2016), or estimated approximately ~45000-90000 nucleosomes across the genome at different developmental stages (Bunnik et al. 2014, Ponts et al. 2010). However, this value likely represents an underestimation due to the depletion of nucleosomal reads in AT-rich intergenic regions observed in their datasets.”

__ Figure 1B and Nucleosome Spacing __

The authors claim that Figure 1B shows developmental stage-specific variation in nucleosome spacing. However, only T35 shows a visible upstream change at position 0. In A4, A6, and A8 (Figure S4), no major change is apparent. Statistical tests are needed to validate whether the observed differences are significant and should be described in the figure legends and main text.

We would like to thank the reviewer for bringing this issue to our attention. We apologize for an error we made, wrongly labelling the figure numbers. The differences in nucleosome spacing across time are visible in Figure 1C. Figure 1B shows the precise array structure of the Pf nucleosomes, when centered on the +1 nucleosome, and is mentioned before. The mistake is now corrected.

In Figure 1C the mean NRL and 95% confidence interval are depicted, allowing a visual assessment of data significance (non-overlapping 95% CI-Intervals correspond to p Taken together we corrected this mistake and edited the text as follows (L194 – 199):

“With this +1 nucleosome annotation, regularly spaced nucleosome arrays downstream of the TSS were detected, revealing a precise nucleosome organization in Pf (Figure 1B). Due to the high resolution maps of nucleosomes we can now observe significantvariations in nucleosome spacing depending on the developmental stage (Figure 1C, ANOVA on bootstrapped values (3 per timepoint) F₇,₇₂ = 35.10, p

__ Genome-wide Occupancy Claims __

The claim that nucleosomes are "evenly distributed throughout the genome" (Figure S2A) is questionable. Chromosomes 3 and 11 show strong peaks mid-chromosome, and chromosome 14 shows little to no signal at the ends. This should be discussed. Subtelomeric regions, such as those containing var genes, are known to have unique chromatin features. For instance, Lopez-Rubio et al. (2009) show that subtelomeric regions are enriched for H3K9me3 and HP1, correlating with gene silencing. Should these regions not display different nucleosome distributions? Do you expect the Plasmodium genome (or any genome) to have uniform nucleosome distribution?

On global scale (> 10 kb) we would expect a homogenous distribution of nucleosomes genome wide, regardless of euchromatin or heterochromatin. We have shown this in a previous study for human cells (PMID: 30496478), which was later confirmed for drosophila melongaster (PMID: 31519205,PMID: 30496478) and yeast (PMID: 39587299).

However, Figure S2A shows the distribution of the dynamic nucleosome features during the IDC, called with our pipeline. We agree with the reviewer, that there are a few exceptions of the uniform distribution, which we address now in the manuscript.

Furthermore, we agree with the reviewer that the H3K9me3 / HP1 subtelomeric regions are special. Those regions are depleted of dynamic nucleosomes in the IDC as shown in Fig. 2D and now mentioned in L280 - L282.

We included an additional genome browser snapshot in Supplemental Figure S2B and changed the text accordingly (L245-249):

We observed a few exceptions to the even distribution of the nucleosomes in the center of chromosome 3, 11 and 12, where nucleosome occupancy changes accumulated at centromeric regions (Figure S2B). Furthermore, the ends of the chromosomes are rather depleted of dynamic nucleosome features.

Genome browser snapshot illustrating accumulation of nucleosome occupancy changes at a centromeric site. Centered nucleosome coverage tracks (T5-T40 colored coverage tracks), nucleosomes occupancy changes (yellow bar) and annotated centromers (grey bar) taken from (Hoeijmakers et al., 2012)

Dependence on DANPOS

The authors criticize the DANPOS pipeline for its limitations but use it extensively within nucDetective. This contradiction confuses the reader. Is nucDetective an original pipeline, or a wrapper built on existing tools?

One unique feature of the nucDetective pipeline is to identify dynamic nucleosomes (occupancy, fuzziness, regularity, shifts) in complex experimental designs, such as time series data (Inspector workflow). To our knowledge, there is no other tool for MNase-seq data which allows multi-condition/time-series comparisons (PMID: 35061087). For example, DANPOS allows only pair-wise comparisons, which cannot be used for time-series data. For the analysis of dynamic nucleosome features we require nucleosome profiles and positions at high resolution. For this purpose, several tools do already exist (PMID: 35061087). However, researchers without experience in MNase-seq analysis often find the plethora of available tools overwhelming, which makes it challenging to select the most appropriate ones. Here we share our experience and provide the user an automated workflow (Profiler), which builds on existing tools.

In summary the Profiler workflow is a wrapper built on existing tools and the Inspector workflow is partly a wrapper (uses DANPOS to normalize nucleosome profiles and call nucleosome positions) and implements our original algorithm to detect dynamic nucleosome features in multiple conditions / time-series data.

__ Control Data Usage __

The authors should clarify whether gDNA controls were used throughout the analysis, as done in Kensche et al. (2016). Currently, this is mentioned only in the figure legend for Figure 5, not in the methods or results.

We used the gDNA normalisation to optimize the visualization of the nucleosome depleted region upstream of the TSS in Fig 5A. Otherwise, we did not normalize the data by the gDNA control. The reason is the same as we did not include sequence normalization in the pipeline (see comment above)

We included a paragraph describing the limitations to the discussion (L447-457):

Depending on the degree of MNase digestion, preferentially nucleosomes from GC rich regions are revealed in MNase-seq experiments (Schwartz et al. 2019). However, no sequence or gDNA normalisation step was included in the nucDetective pipeline. To identify dynamic nucleosomes, comparisons are performed between the same nucleosome positions at the same genomic sites across multiple samples. Hence, the sequence context is constant and does not confound the analysis. Introducing a sequence normalization step might even distort and bias the results. Nevertheless, it is highly advisable to use low MNase concentrations in chromatin digestions to reduce the sequence bias in nucleosome extractions. This turned out to be a crucial condition to obtain a homogenous nucleosome distribution in the AT-rich intergenic regions of eukaryotic genomes and especially in the AT-rich genome of Pf (Schwartz et al. 2019, Kensche et al. 2016).

We added following statement to the methods part: Additionally, the TSS profile shown in Figure 5A was normalized by the gDNA control for better NDR visualization.

__ Lack of Statistical Power for Time-Series Analyses __

Although the pipeline is presented as suitable for time-series data, it lacks statistical tools to determine whether differences in nucleosome positioning or fuzziness are significant across conditions. Visual interpretation alone is insufficient. Statistical support is essential for any differential analysis.

We understand the value of statistical support in such an analysis. However, in biology we often face the limitations in terms of the appropriate sample sizes needed to accurately estimate the variance parameters required for statistical modeling. As MNase-seq experiments require a large amount of input material and high sequencing depth, the number of samples in most experiments is low, often with only two replicates (PMID: 23193179). Therefore, we decided that the nucDetective pipeline should be rather handled as a screening method to identify nucleosome features with high variance across all conditions. This prevents misuse of p-values. A common misinterpretation we observed is the use of non-significant p-values to conclude that no biological change exists, despite inadequate statistical power to detect such changes. We included a paragraph in the limitations section discussing the limitations of statistical analysis of MNase-Seq data.

Changes to the manuscript text: We included a paragraph describing the limitations to the discussion (L435-446).

As MNase-seq experiments require a large amount of input material and high sequencing depths, most published MNase-seq experiments do not provide the appropriate sample sizes required to accurately estimate the variance parameters necessary for statistical modelling (Chen et al. 2013). Therefore, dynamic nucleosomes are not identified through statistical testing but rather by ranking nucleosome features according to their variance across all samples and applying a variance threshold to distinguish them. This concept is well established to identify super-enhancers (Whyte et al. 2013). In this study we set the variance cutoff to a slope of 3, resulting in a high data confidence. However, other data sets might require further adjustment of the variance cutoff, depending on data quality or sequencing depth. The nucDetective identification of dynamic nucleosomes can be seen as a screening approach to provide a holistic overview of nucleosome dynamics in the system, which provides a basis for further research.

Reproducibility of Methods

The Methods section is not sufficient to reproduce the results. The GitHub repository lacks the necessary code to generate the paper's figures and focuses on an exemplary yeast dataset. The authors should either: o Update the repository with relevant scripts and examples, o Clearly state the repository's purpose, or o Remove the link entirely. Readers must understand that nucDetective is dedicated to assessing nucleosome fuzziness, occupancy, shift, and regularity dynamics-not downstream analyses presented in the paper.

We thank the reviewer for this helpful comment. In addition to the main nucDetective repository, a second GitHub link is provided in the Data Availability section, which contains the scripts used to generate the figures presented in the paper. This separation was intentional to distinguish the general-purpose nucDetective tool from the project-specific analyses performed for this study. We acknowledge that this may not have been sufficiently clear.

To have all resources available at a single citable permanent location we included a link to the corresponding Zenodo repository (https://doi.org/10.5281/zenodo.16779899) in the Data and materials availability statement.

The Zenodo repository contains:

Code (scripts.zip) and annotation of Plasmodium falciparum (Annotation.zip) to reproduce the nucDetective v1.1 (nucDetective-1.1.zip) analysis as done in the research manuscript entitled "Deciphering chromatin architecture and dynamics in Plasmodium falciparum using the nucDetective pipeline".

The folder "output_nucDetective" conains the complete output of the nucDetective analysis pipeline as generated by the "01_nucDetective_profiler.sh" and "02_nucDetective_inspector.sh" scripts.

Nucleosome coverage tracks, annotation of nucleosome positions and dynamic nucleosomes are deposited additonally in the folder "Pf_nucleosome_annotation_of_nucDetective".

To make this clearer we added following text to Material and Methods in ”The nucDetective pipeline” section:

Changes in the manuscript text (L518-519):

The code, software and annotations used to run the nucDetective pipeline along with the output have been deposited on Zenodo (https://doi.org/10.5281/zenodo.16779899).

__ Supplementary Tables __

Including supplementary tables showing pipeline outputs (e.g., nucleosome scores, heatmaps, TSS extraction) would help readers understand the input-output structure and support figure interpretations.

See comments above.

We included a link to the corresponding Zenodo repository (https://doi.org/10.5281/zenodo.16779899) in the Data and materials availability statement.

The repository contains:

Code (scripts.zip) and annotation of Plasmodium falciparum (Annotation.zip) to reproduce the nucDetective v1.1 (nucDetective-1.1.zip) analysis as done in the research manuscript entitled "Deciphering chromatin architecture and dynamics in Plasmodium falciparum using the nucDetective pipeline".

The folder "output_nucDetective" conains the complete output of the nucDetective analysis pipeline as generated by the "01_nucDetective_profiler.sh" and "02_nucDetective_inspector.sh" scripts.

Minor Comments:

The authors should moderate claims such as "no studies have reported a well-positioned +1 nucleosome" in P. falciparum, as this contradicts existing literature. Similarly, avoid statements like "poorly understood chromatin architecture of Pf," which undervalue extensive prior work (e.g., discovery of histone lactylation in Plasmodium, Merrick et al., 2023).

We would like to clarify that we neither wrote that ““no studies have reported a well-positioned +1 nucleosome”” in P. falciparum nor did we intend to imply such thing. However, we acknowledge that our original wording may have been unclear. To address this, we have revised the manuscript to explicitly acknowledge prior studies on chromatin organization and highlight our contribution.

In the Abstract L26-L30: Contrary to the current view of irregular chromatin, we demonstrate for the first time regular phased nucleosome arrays downstream of TSSs, which, together with the established +1 nucleosome and upstream nucleosome-depleted region, reveal a complete canonical eukaryotic promoter architecture in Pf.

Introduction L156-L159: For example, we identify a phased nucleosome array downstream of the TSS. Together with a well-positioned +1 nucleosome and an upstream nucleosome-free region. These findings support a promoter architecture in Pf that resembles classical eukaryotic promoters (Bunnik et al. 2014, Kensche et al. 2016).

Results L180-L183: These new Pf nucleosome maps reveal a nucleosome organisation at transcription start sites (TSS) reminiscent of the general eukaryotic chromatin structure, featuring a reported well-positioned +1 nucleosome , an upstream nucleosome-free region (NFR, Bunnik et al. 2014, Kensche et al. 2016), and shown for the first time in Pf, a phased nucleosome array downstream of the TSS.

Discussion L412-L421: Previous analyses of Pf chromatin have identified +1 nucleosomes and NFRs (Bunnik et al 2014, Kensche et al. 2016). Here we extend this understanding by demonstrating phased nucleosome array structures throughout the genome. This finding provides evidence for a spatial regulation of nucleosome positioning in Pf, challenging the notion that nucleosome positioning is relatively random in gene bodies (Bunnik et al. 2014, Kensche et al. 2016). Consequently our results contribute to the understanding that Pf exhibits a typical eukaryotic chromatin structure, including well-defined nucleosome positioning at the TSS and regularly spaced nucleosome arrays (Schones et al. 2008; Yuan et al. 2005).

The phrase “poorly understood chromatin architecture” has been modified to “underexplored chromatin architecture” in order to more accurately reflect the potential for further analyses and contributions to the field, while avoiding any potential misinterpretation of an attempt to undervalue previous work.

Track labels in figures (e.g., Figure 5B) are too small to be legible.

We made the labels bigger.

Several figures (e.g., Figure 5B, S4B) lack statistical significance tests. Are the differences marked with stars statistically significant or just visually different?

We added statistics to S4B.

Differences in 5B were identified by visual inspection. To clarify this, we exchanged the asterisks to arrows in Fig.5B and changed the text in the legend:

Arrows mark descriptive visual differences in nucleosome occupancy.

Figure S3 includes a small black line on top of the table. Is this an accidental crop?

We checked the figure carefully; however, the black line does not appear in our PDF viewer or on the printed paper

The authors should state the weaknesses and limitations of this pipeline.

We added a limitation section in discussion, see comments above

Reviewer #1 (Significance (Required)):

The proposed pipeline is useful and timely. It can benefit research groups willing to analyse MNase-Seq data of complex genomes such as P. falciparum. The tool requires users to have extensive experience in coding as the authors didn't include any clear and explicit codes on how to start processing the data from raw files. Nevertheless, there are multiple tool that can detect nucleosome occupancy and that are not cited by the authors not mention. I have included for the authors a link where a large list of tools for analysis of nucleosome positioning experiments tools/pipelines were developed for (Software to analyse nucleosome positioning experiments - Gene Regulation - Teif Lab). I think it would be useful for the authors to direct the reference this.

We appreciate the reviewer’s valuable suggestion. We included a citation to the comprehensive database of nucleosome analysis tools curated by the Teif lab (Shtumpf et al., 2022). We chose to reference only selected tools in addition to this resource rather than listing all individual tools to maintain clarity and avoid overloading the manuscript with numerous citations.

Despite valid, I still believe that controlling their pipeline by filtering out false positives and including more QC steps at the Inspector stage is strongly needed. That would boost the significance of this pipeline.

We thank the reviewer for the assessment of our study and for recognizing that our MNase-seq analysis pipeline nucDetective can be a useful tool for the chromatin community utilizing MNase-Seq in complex settings.

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

In this manuscript, Holzinger and colleagues have developed a new pipeline to assess chromatin organization in linear space and time. They used this pipeline to reevaluate nucleosome organization in the malaria parasite, P. falciparum. Their analysis revealed typical arrangement of nucleosomes around the transcriptional start site. Furthermore, it further strengthened and refined the connection between specific nucleosome dynamics and epigenetic marks, transcription factor binding sites or transcriptional activity.

Major comments

• I am wondering what is the main selling point of this manuscript is. If it is the development of the nucDetective pipeline, perhaps it would be best to first benchmark it and directly compare it to existing tools on a dataset where nucleosome fussiness, shifting and regularity has been analyzed before. If on the other hand, new insights into Plasmodium chromatin biology is the primary target validation of some of the novel findings would be advantageous (e.g. refinement of TSS positions, relevance of novel motifs, etc).

NucDetective presents a novel pipeline to identify dynamic nucleosome properties within different datasets, like time series or developmental stages, as analysed for the erythrocytic cycle in this manuscript. As such kind of a pipeline, allowing direct comparisons, does not exist for MNase-Seq data, we used the existing analysis and high quality dataset of Kensche et al., to visualize the strong improvements of this kind of analysis. Accordingly, we combined the pipeline development and the reasearch of chromatin structure analysis, being able to showcase the utility of this new pipeline.

• The authors identify a strong positioning of +1 nucleosome by searching for a positioned nucleosomes in the vicinity of the assigned TSS. Given the ill-defined nature of TSSs, this approach sounds logic at first glance. However, given the rather broad search space from -100 till +300bp, I am wondering whether it is a sort of "self-fulfilling prophecy". Conversely, it would be good to validate that this approach indeed helps to refine TSS positions.

We thank the reviewer for raising this important point. We would like to clarify that we do not claim to redefine or precisely determine TSS positions in our study. Instead, we use annotated TSS coordinates as a reference to identify nucleosomes that correspond to the +1 nucleosome, based on their proximity to the TSS.

We selected the search window from -100 to +300 bp to account for known variability in Pf TSS annotation. For example, dominant transcription start sites identified by 5'UTR-seq tag clusters can differ by several hundred base pairs within a single time point (Chappell et al., 2020). The broad window thus allows us to capture the principal nucleosome positions near a TSS, even when the TSS itself is imprecise or heterogeneous. Based on the TSS centered plots (Figure 2C and Figure S1B), we reasoned that a window of -100 to +300 is sufficient to capture the majority of the +1 nucleosomes, which would have been missed by using smaller window sizes. This strategy aligns with well-established conventions in yeast chromatin biology, where the +1 nucleosome is defined relative to the TSS (Jiang and Pugh, 2009; Zhang et al. 2011) and commonly used as an anchor point to visualize downstream phased nucleosome arrays and upstream nucleosome-depleted regions (Rossi et al., 2021; Oberbeckmann et al., 2019; Krietenstein et al., 2016 and many more). Accordingly, our approach leverages these accepted standards to interpret nucleosome positioning without re-defining TSS annotations.

• Figure 1C: I am wondering how should the reader interpret the changes in nucleosomal repeat length changes throughout the cycle. Is linker DNA on average 10 nucleotides shorter at T30 compared to T5 timepoint? If so how could such "dramatic reorganization" be achieved at the molecular level in absence of a known linker DNA-binding protein. More importantly is this observation supported by additional evidence (e.g. dinucleosomal fragment length) or could it be due to slightly different digestion of the chromatin at the different stages or other technical variables?

We thank the reviewer for this insightful question regarding the interpretation of NRL changes across the cell cycle. The reviewer is right in her or his interpretation – linker DNA is on average ~10 bp shorter at T30 than at T5.

To address concerns about additional evidence and potential MNase digestion variability, we now analyzed MNase-seq fragment sizes by shifting mononucleosome peaks of each time point to the canonical 147 bp length, to correct for MNase digestion differences. After this normalisation, dinucleosome fragment length distributions revealed the shortest linker lengths at T30 and T35, whereas T5 and T10 showed longer DNA linkers. These results confirm our previous NRL measurements based on mononucleosomal read distances while controlling for MNase digestion bias.

The molecular basis of this reorganization, is still unclear. While linker histone H1 is considered absent in Plasmodium falciparum, presence of an uncharacterized linker DNA–binding protein or alternative factors fulfilling a similar role can not be excluded (Gill et al. 2010). However, H1 absence across all developmental stages, fails to explain stage-specific chromatin changes. We hypothesize that Apicomplexans evolved specialized chromatin remodelers to compensate for the missing H1, which may also drive the dynamic NRL changes observed. The low NRL coincides with high transcriptional activity in Pf during trophozoite stage is consistent with previous reports linking elevated transcription to reduced NRL in other eukaryotes (Baldi et al. 2018). In addition, the schizont stage involves multiple rounds of DNA replication requiring large histone supplies being produced during that time. It may well be that a high level of histone synthesis and DNA amplification, results in a short time period with increased nucleosome density and shorter NRL, until the system reaches again equilibrium (Beshnova et al. 2014). Although speculative we suggest a model wherein increased transcription promotes elevated nucleosome turnover and re-assembly by specialized remodeling enzymes, combined with high abundance of histones, resulting in higher nucleosome density and decreased NRL. Unfortunately, absolute quantification of nucleosome levels from this MNase-seq dataset is not possible without spike-in controls, which makes it infeasible to test the hypothesis with the available data set (Chen et al. 2016).

Minor comments

• I am wondering whether fuzziness and occupancy changes are truly independent categories. I am asking as both could lead to reduction of the signal at the nucleosome dyad and because they show markedly similar distribution in relation to the TSS and associate with identical epigenetic features (Figure 2B-D). Figure 2A indicates minimal overlap between them, but this could be due to the fact that the criteria to define these subtypes is defined such to place nucleosomes to one or the other category, but at the end they represent two flavors of the same thing.

Indeed, changes in occupancy and fuzziness can appear related because both features may reduce signal intensity at the nucleosome dyad and both are connected to “poor nucleosome positioning”. However, their definitions and measurements are clearly distinct and technically independent. Occupancy reflects the peak height at the nucleosome dyad, while fuzziness quantifies the spread of reads around the peak, measured as the standard deviation of read positions within each nucleosome peak (Jiang and Pugh, 2009; Chen et al., 2013). Although a reduction in occupancy can contribute to increased fuzziness by diminishing the dyad axis signal, fuzziness primarily arises from increased variability in the flanking regions around the nucleosome position center. While this distinction is established in the field, it is also often confused by the concept of well (high occupancy, low fuzziness) and poorly (high fuzziness, low occupancy) positioned nucleosomes, where both of these features are considered.

• Do the authors detect spatial relationship between fuzzy and repositioned/evicted nucleosomes at the level of individual nucleosomes pairs. With other words, can fuzziness be the consequence of repositioning/eviction of the neighboring nucleosome?

In Figure 2A we analyse the spatial overlap of all features to each other. The analysis clearly shows that fuzziness, occupancy changes and position changes occur mostly at distinct spatial sites (overlaps between 3 and 10%, Fig. 2A). Therefore, we suggest that the features correspond to independent processes. Likewise, we do observe an overlap between occupancy and ATAC-seq peaks, but not nucleosome positioning shifts, clearly discriminating different processes.

• Figure 4: enrichment values and measure of statistical significance for the different motifs are missing. Also have there been any other motifs identified.

This information is present in Supplemental Figure S3. Here we show the top 3 hits in each cluster. In the figure legend of Figure 4 we reference to Fig. S3:

L1054 –1055:

“Additional enriched motifs along with the significance of motif enrichment and the fraction of motifs at the respective nucleosome positions are shown in Figure S3”

• The M&M would benefit from some more details, e.g. settings in the piepline, or which fragment sizes were used to map the MNase-seq data?

We included a link to the corresponding Zenodo repository (https://doi.org/10.5281/zenodo.16779899) in the Data and materials availability statement.

The repository contains:

Code (scripts.zip) and annotation of Plasmodium falciparum (Annotation.zip) to reproduce the nucDetective v1.1 (nucDetective-1.1.zip) analysis as done in the research manuscript entitled "Deciphering chromatin architecture and dynamics in Plasmodium falciparum using the nucDetective pipeline".

The folder "output_nucDetective" conains the complete output of the nucDetective analysis pipeline as generated by the "01_nucDetective_profiler.sh" and "02_nucDetective_inspector.sh" scripts.

Nucleosome coverage tracks, annotation of nucleosome positions and dynamic nucleosomes are deposited additonally in the folder "Pf_nucleosome_annotation_of_nucDetective".

To make this clearer we added following text to Material and Methods in ”The nucDetective pipeline” section:

Changes in the manuscript (L518-519):

The code, software and annotations used to run the nucDetective pipeline along with the output have been deposited on Zenodo (https://doi.org/10.5281/zenodo.16779899).

which fragment sizes were used to map the MNase-seq data?

The default setting in nucDetective is to use fragment sizes of 140 – 200 bp, which corresponds to the main mono-nucleosome fraction in standard MNase-seq experiments. However, the correct selection of fragment sizes may vary depending on the organism and the variations in MNase-seq protocols. Therefore, the pipeline offers the option of changing the cutoff parameter (--minLen; --maxLen), accordingly. Kensche et al thoroughly tested the best selection of the fragment sizes for the data set, which is used in this manuscript. We agree with their selection and used the same cutoffs (75-175 bp).

This is stated in line 535-536:

The fragments are further filtered to mono-nucleosome sized fragments (here we used 75 – 175 bp)

We changed the text:

The fragments are further filtered to mono-nucleosome sized fragments (default setting 140-200 bp; changed in this study to 75 – 175 bp)

We highlighted other parameters used in this study in the material and methods part.

Reviewer #2 (Significance (Required)):

Overall, the manuscript is well written and findings are clearly and elegantly presented. The manuscript describes a new pipeline to map and analyze MNase-seq data across different stages or conditions, though the broader applicability of the pipeline and advancements over existing tools could be better demonstrated. Importantly, the manuscript make use of this pipeline to provide a refined and likely more accurate view on (the dynamics of) nucleosome positioning over the AT-rich genome of P. falciparum. While these observations make sense they remain rather descriptive/associative and lack further experimental validation. Overall, this manuscript could be interest to both researchers working on chromatin biology and Plasmodium gene-regulation.

We thank the reviewer for the assessment of our study and for recognizing that the results of our MNase-seq analysis pipeline nucDetective contribute to a better understanding of Pf chromatin biology.

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

The manuscript "Deciphering chromatin architecture and dynamics in Plasmodium 2 falciparum using the nucDetective pipeline" describes computational analysis of previously published data of P falciparum chromatin. This work corrects the prevailing view that this parasitic organism has an unusually disorganized chromatin organization, which had been attributed to its high genomic AT content, lack of histone H1, and ancient derivation. The authors show that instead P falciparum has a very typical chromatin organization. Part of the refinement is due to aligning data on +1 nucleosome positions instead of TSSs, which have been poorly mapped. The computational tools corral some useful features, for querying epigenomic structure that make visualization straightforward, especially for fuzzy nucleosomes.

Reviewer #3 (Significance (Required)):

As a computational package this is a nice presentation of fairly central questions. The assessment and display of fuzzy nucleosomes is a nice feature.

We thank the reviewer for the assessment of our study and are pleased that the reviewer acknowledges the value and usability of our pipeline.

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

Learn more at Review Commons

Referee #3

Evidence, reproducibility and clarity

The manuscript "Deciphering chromatin architecture and dynamics in Plasmodium 2 falciparum using the nucDetective pipeline" describes computational analysis of previously published data of P falciparum chromatin. This work corrects the prevailing view that this parasitic organism has an unusually disorganized chromatin organization, which had been attributed to its high genomic AT content, lack of histone H1, and ancient derivation. The authors show that instead P falciparum has a very typical chromatin organization. Part of the refinement is due to aligning data on +1 nucleosome positions instead of TSSs, which have been poorly mapped. The computational tools corral some useful features, for querying epigenomic structure that make visualization straightforward, especially for fuzzy nucleosomes.

Significance

As a computational package this is a nice presentation of fairly central questions. The assessment and display of fuzzy nucleosomes is a nice feature.

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

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

In this manuscript, Holzinger and colleagues have developed a new pipeline to assess chromatin organization in linear space and time. They used this pipeline to reevaluate nucleosome organization in the malaria parasite, P. falciparum. Their analysis revealed typical arrangement of nucleosomes around the transcriptional start site. Furthermore, it further strengthened and refined the connection between specific nucleosome dynamics and epigenetic marks, transcription factor binding sites or transcriptional activity.

Major comments

• I am wondering what is the main selling point of this manuscript is. If it is the development of the nucDetective pipeline, perhaps it would be best to first benchmark it and directly compare it to existing tools on a dataset where nucleosome fussiness, shifting and regularity has been analyzed before. If on the other hand, new insights into Plasmodium chromatin biology is the primary target validation of some of the novel findings would be advantageous (e.g. refinement of TSS positions, relevance of novel motifs, etc).
• The authors identify a strong positioning of +1 nucleosome by searching for a positioned nucleosomes in the vicinity of the assigned TSS. Given the ill-defined nature of TSSs, this approach sounds logic at first glance. However, given the rather broad search space from -100 till +300bp, I am wondering whether it is a sort of "self-fulfilling prophecy". Conversely, it would be good to validate that this approach indeed helps to refine TSS positions.
• Figure 1C: I am wondering how should the reader interpret the changes in nucleosomal repeat length changes throughout the cycle. Is linker DNA on average 10 nucleotides shorter at T30 compared to T5 timepoint? If so how could such "dramatic reorganization" be achieved at the molecular level in absence of a known linker DNA-binding protein. More importantly is this observation supported by additional evidence (e.g. dinucleosomal fragment length) or could it be due to slightly different digestion of the chromatin at the different stages or other technical variables?

Minor comments

• I am wondering whether fuzziness and occupancy changes are truly independent categories. I am asking as both could lead to reduction of the signal at the nucleosome dyad and because they show markedly similar distribution in relation to the TSS and associate with identical epigenetic features (Figure 2B-D). Figure 2A indicates minimal overlap between them, but this could be due to the fact that the criteria to define these subtypes is defined such to place nucleosomes to one or the other category, but at the end they represent two flavors of the same thing.
• Do the authors detect spatial relationship between fuzzy and repositioned/evicted nucleosomes at the level of individual nucleosomes pairs. With other words, can fuzziness be the consequence of repositioning/eviction of the neighboring nucleosome?
• Figure 4: enrichment values and measure of statistical significance for the different motifs are missing. Also have there been any other motifs identified.
• The M&M would benefit from some more details, e.g. settings in the piepline, or which fragment sizes were used to map the MNase-seq data?

Significance

Overall, the manuscript is well written and findings are clearly and elegantly presented. The manuscript describes a new pipeline to map and analyze MNase-seq data across different stages or conditions, though the broader applicability of the pipeline and advancements over existing tools could be better demonstrated. Importantly, the manuscript make use of this pipeline to provide a refined and likely more accurate view on (the dynamics of) nucleosome positioning over the AT-rich genome of P. falciparum. While these observations make sense they remain rather descriptive/associative and lack further experimental validation. Overall, this manuscript could be interest to both researchers working on chromatin biology and Plasmodium gene-regulation.

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Referee #1

Evidence, reproducibility and clarity

Summary:

Holzinger et al. present a new automated pipeline, nucDetective, designed to provide accurate nucleosome positioning, fuzziness, and regularity from MNase-seq data. The pipeline is structured around two main workflows-Profiler and Inspector-and can also be applied to time-series datasets. To demonstrate its utility, the authors re-analyzed a Plasmodium falciparum MNase-seq time-series dataset (Kensche et al., 2016), aiming to show that nucDetective can reliably characterize nucleosomes in challenging AT-rich genomes. By integrating additional datasets (ATAC-seq, RNA-seq, ChIP-seq), they argue that the nucleosome positioning results from their pipeline have biological relevance.

Major Comments:

Despite being a useful pipeline, the authors draw conclusions directly from the pipeline's output without integrating necessary quality controls. Some claims either contradict existing literature or rely on misinterpretation or insufficient statistical support. In some instances, the pipeline output does not align with known aspects of Plasmodium biology. I outline below the key concerns and suggested improvements to strengthen the manuscript and validate the pipeline:

• Clarification of +1 Nucleosome Positioning in P. falciparum The authors should acknowledge that +1 nucleosomes have been previously reported in P. falciparum. For example, Kensche et al. (2016) used MNase-seq to map ~2,278 TSSs (based on enriched 5′-end RNA data) and found that the +1 nucleosome is positioned directly over the TSS in most genes: "Analysis of 2278 start sites uncovered positioning of a +1 nucleosome right over the TSS in almost all analysed regions" (Figure 3A). They also described a nucleosome-depleted region (NDR) upstream of the TSS, which varies in size, while the +1 nucleosome frequently overlaps the TSS. The authors should nuance their claims accordingly. Nevertheless, I do agree that the +1 positioning in P. falciparum may be fuzzier as compared to yeast or mammals. Moreover, the correlation between +1 nucleosome occupancy and gene expression is often weak and that several genes show similar nucleosome profiles regardless of expression level. This raises my question: did the authors observe any of these patterns in their new data?
• Lack of Quality Control in the Pipeline The authors claim (lines 152-153) that QC is performed at every stage, but this is not supported by the implementation. On the GitHub page (GitHub - uschwartz/nucDetective), QC steps are only marked at the Profiler stage using standard tools (FastQC, MultiQC). The Inspector stage, which is crucial for validating nucleosome detection, lacks QC entirely. The authors should implement additional steps to assess the quality of nucleosome calls. For example, how are false positives managed? ROC curves should be used to evaluate true positive vs. false positive rates when defining dynamic nucleosomes. How sequencing biases are addressed?
• Use of Mono-nucleosomes Only The authors re-analyze the Kensche et al. (2016) dataset using only mono-nucleosomes and claim improved nucleosome profiles, including identification of tandem arrays previously unreported in P. falciparum. Two key issues arise:
• Is the apparent improvement due simply to focusing on mono-nucleosomes (as implied in lines 342-346)?
• How does the pipeline perform with di- or tri-nucleosomes, which are also biologically relevant (Kensche et al., 2016 and others)? Furthermore, the limitation to mono-nucleosomes is only mentioned in the methods, not in the results or discussion, which could mislead readers.
• Reference Nucleosome Numbers The authors identify 49,999 reference nucleosome positions. How does this compare to previous analyses of similar datasets? This should be explicitly addressed.
• Figure 1B and Nucleosome Spacing The authors claim that Figure 1B shows developmental stage-specific variation in nucleosome spacing. However, only T35 shows a visible upstream change at position 0. In A4, A6, and A8 (Figure S4), no major change is apparent. Statistical tests are needed to validate whether the observed differences are significant and should be described in the figure legends and main text.
• Genome-wide Occupancy Claims The claim that nucleosomes are "evenly distributed throughout the genome" (Figure S2A) is questionable. Chromosomes 3 and 11 show strong peaks mid-chromosome, and chromosome 14 shows little to no signal at the ends. This should be discussed. Subtelomeric regions, such as those containing var genes, are known to have unique chromatin features. For instance, Lopez-Rubio et al. (2009) show that subtelomeric regions are enriched for H3K9me3 and HP1, correlating with gene silencing. Should these regions not display different nucleosome distributions? Do you expect the Plasmodium genome (or any genome) to have uniform nucleosome distribution?
• Dependence on DANPOS The authors criticize the DANPOS pipeline for its limitations but use it extensively within nucDetective. This contradiction confuses the reader. Is nucDetective an original pipeline, or a wrapper built on existing tools?
• Control Data Usage The authors should clarify whether gDNA controls were used throughout the analysis, as done in Kensche et al. (2016). Currently, this is mentioned only in the figure legend for Figure 5, not in the methods or results.
• Lack of Statistical Power for Time-Series Analyses Although the pipeline is presented as suitable for time-series data, it lacks statistical tools to determine whether differences in nucleosome positioning or fuzziness are significant across conditions. Visual interpretation alone is insufficient. Statistical support is essential for any differential analysis.
• Reproducibility of Methods The Methods section is not sufficient to reproduce the results. The GitHub repository lacks the necessary code to generate the paper's figures and focuses on an exemplary yeast dataset. The authors should either:
  • Update the repository with relevant scripts and examples,
  • Clearly state the repository's purpose, or
  • Remove the link entirely. Readers must understand that nucDetective is dedicated to assessing nucleosome fuzziness, occupancy, shift, and regularity dynamics-not downstream analyses presented in the paper.
• Supplementary Tables Including supplementary tables showing pipeline outputs (e.g., nucleosome scores, heatmaps, TSS extraction) would help readers understand the input-output structure and support figure interpretations.

Minor Comments:

• The authors should moderate claims such as "no studies have reported a well-positioned +1 nucleosome" in P. falciparum, as this contradicts existing literature. Similarly, avoid statements like "poorly understood chromatin architecture of Pf," which undervalue extensive prior work (e.g., discovery of histone lactylation in Plasmodium, Merrick et al., 2023).
• Track labels in figures (e.g., Figure 5B) are too small to be legible.
• Several figures (e.g., Figure 5B, S4B) lack statistical significance tests. Are the differences marked with stars statistically significant or just visually different?
• Figure S3 includes a small black line on top of the table. Is this an accidental crop?
• The authors should state the weaknesses and limitations of this pipeline.

Significance

• The proposed pipeline is useful and timely. It can benefit research groups willing to analyse MNase-Seq data of complex genomes such as P. falciparum. The tool requires users to have extensive experience in coding as the authors didn't include any clear and explicit codes on how to start processing the data from raw files. Nevertheless, there are multiple tool that can detect nucleosome occupancy and that are not cited by the authors not mention. I have included for the authors a link where a large list of tools for analysis of nucleosome positioning experiments tools/pipelines were developed for (Software to analyse nucleosome positioning experiments - Gene Regulation - Teif Lab). I think it would be useful for the authors to direct the reference this.
• Despite valid, I still believe that controlling their pipeline by filtering out false positives and including more QC steps at the Inspector stage is strongly needed. That would boost the significance of this pipeline.

just trying it out!

eLife Assessment

This study presents a valuable finding on whether executive resources mediate the impact of language predictability in reading in the context of aging. The evidence is solid in the investigation of prediction in reading, with one caveat that the text materials used could be biased against the aging population. The work will be of interest to cognitive neuroscientists working on reading, language comprehension, and executive control.

Reviewer #1 (Public review):

The authors of this study set out to address a central question in the psycholinguistics literature: does the human brain's ability to predict upcoming language come at a cognitive cost, or is it an automatic, "free" process? To investigate this, they employed a dual-task paradigm where participants read texts word-by-word while simultaneously performing a secondary task (an n-back task on font color) designed to manipulate cognitive load. The study examines how this external cognitive load, along with the effects of aging, modulates the impact of word predictability (measured by surprisal and entropy) on reading times. The central finding is that increased cognitive load diminishes the effects of word predictability, supporting the conclusion that language prediction is a resource-dependent process.

A major strength of the revised manuscript is its comprehensive and parallel analysis of both word surprisal and entropy. The initial submission focused almost exclusively on surprisal, which primarily reflects the cost of integrating a word into its context after it has been perceived. The new analysis now thoroughly investigates entropy as well, which reflects the uncertainty and cognitive effort involved in predicting the next word before it appears. This addition provides a much more complete and theoretically nuanced picture, allowing the authors to address how cognitive load affects both predictive and integrative stages of language processing. This is a significant improvement and substantially increases the paper's contribution to the field.

Furthermore, the authors have commendably addressed the initial concerns regarding the robustness of their replication findings. The first version of the manuscript presented replication results that were inconsistent, particularly for key interaction effects. In the revision, the authors have adopted a more focused and appropriately powered modeling approach for the replication analysis. This revised analysis now demonstrates a consistent effect of cognitive load on the processing of predictable words across both the original and replication datasets. This strengthens the evidence for the paper's primary claim.

The initial review also raised concerns that the results could be explained by general cognitive factors, such as task-switching costs, rather than the specific demands on the language prediction system. While the complexity of cognitive load in a dual-task paradigm remains a challenge, the authors have provided sufficient justification in their revisions and rebuttal to support their interpretation that the observed effects are genuinely tied to the process of language prediction.

Reviewer #2 (Public review):

Summary:

This paper considers the effects of cognitive load (using an n-back task related to font color), predictability, and age on reading times in two experiments. There were main effects of all predictors, but more interesting effects of load and age on predictability. The effect of load is very interesting, but the manipulation of age is problematic, because we don't know what is predictable for different participants (in relation to their age). There are some theoretical concerns about prediction and predictability, and a need to address literature (reading time, visual world, ERP studies).

There is a major concern about the effects of age. See the results (155-190): this depends what is meant by word predictability. It's correct if it means the predictability in the corpus. But it may or may not be correct if it refers to how predictable a word is to an individual participant. The texts are unlikely to be equally predictable to different participants, and in particular to younger vs. older participants, because of their different experience. To put it informally, the newspaper articles may be more geared to the expectations of younger people. But there is also another problem: the LLM may have learned on the basis of language that has largely been produced by young people and so its predictions are based on what young people are likely to say. Both of these possibilities strike me as extremely likely. So it may be that older adults are affected more by words that they find surprising, but it is also possible that the texts are not what they expect, or the LLM predictions from the text are not the ones that they would make. In sum, I am not convinced that the authors can say anything about the effects of age unless they can determine what is predictable for different ages of participants. I suspect that this failure to control is an endemic problem in the literature on aging and language processing and needs to be systematically addressed.

Overall, I think the paper makes enough of a contribution with respect to load to be useful to the literature. But for discussion of age, we would need something like evidence of how younger and older adults would complete these texts (on a word-by-word basis) and that they were equally predictable for different ages. I assume there are ways to get LLMs to emulate different participant groups, but I doubt if we could be confident about their accuracy without a lot of testing. But without something like this, I think making claims about age would be quite misleading.

The authors respond to my summary comment by saying that prediction is individual and that they account for age-related effects in their models. But these aren't my concerns. Rather:

(1) The texts (these edited newspaper articles) could be more predictable for younger than older adults. If so, effects with older adults could simply be because people are less likely to predict less than more predictable words.

(2) The GPT-2 generated surprisal scores may correspond more closely to younger than older adult responses -- that is, its next word predictions may be more younger- than older-adult-like.

In my view, the authors have two choices: they could remove the discussion of age-related effects, or they could try to address BOTH (1) and (2).

As an aside, consider what we would conclude if we drew similar conclusions from a study in which children and adults read the same (children's) texts, but we didn't test what was predictable to each of them separately.

The paper is really strong in other respects and if my concern is not addressed, the conclusions about age might be generally accepted.

Author response:

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

Reviewer #1 (Public review):

This manuscript reports a dual-task experiment intended to test whether language prediction relies on executive resources, using surprisal-based measures of predictability and an n-back task to manipulate cognitive load. While the study addresses a question under debate, the current design and modeling framework fall short of supporting the central claims. Key components of cognitive load, such as task switching, word prediction vs integration, are not adequately modeled. Moreover, the weak consistency in replication undermines the robustness of the reported findings. Below unpacks each point. 

Cognitive load is a broad term. In the present study, it can be at least decomposed into the following components: 

(1)  Working memory (WM) load: news, color, and rank. 

(2)  Task switching load: domain of attention (color vs semantics), sensorimotor rules (c/m vs space).

(3)  Word comprehension load (hypothesized against): prediction, integration. 

The components of task switching load should be directly included in the statistical models. Switching of sensorimotor rules may be captured by the "n-back reaction" (binary) predictor. However, the switching of attended domains and the interaction between domain switching and rule complexity (1-back or 2-back) were not included. The attention control experiment (1) avoided useful statistical variation from the Read Only task, and (2) did not address interactions. More fundamentally, task-switching components should be directly modeled in both performance and full RT models to minimize selection bias. This principle also applies to other confounding factors, such as education level. While missing these important predictors, the current models have an abundance of predictors that are not so well motivated (see later comments). In sum, with the current models, one cannot determine whether the reduced performance or prolonged RT was due to affecting word prediction load (if it exists) or merely affecting the task switching load. 

The entropy and surprisal need to be more clearly interpreted and modeled in the context of the word comprehension process. The entropy concerns the "prediction" part of the word comprehension (before seeing the next word), whereas surprisal concerns the "integration" part as a posterior. This interpretation is similar to the authors writing in the Introduction that "Graded language predictions necessitate the active generation of hypotheses on upcoming words as well as the integration of prediction errors to inform future predictions [1,5]." However, the Results of this study largely ignored entropy (treating it as a fixed effect) and only focus on surprisal without clear justification. 

In Table S3, with original and replicated model fitting results, the only consistent interaction is surprisal x age x cognitive load [2-back vs. Reading Only]. None of the two-way interactions can be replicated. This is puzzling and undermines the robustness of the main claims of this paper. 

Reviewer #2 (Public review):

Summary

This paper considers the effects of cognitive load (using an n-back task related to font color), predictability, and age on reading times in two experiments. There were main effects of all predictors, but more interesting effects of load and age on predictability. The effect of load is very interesting, but the manipulation of age is problematic, because we don't know what is predictable for different participants (in relation to their age). There are some theoretical concerns about prediction and predictability, and a need to address literature (reading time, visual world, ERP studies). 

Strengths/weaknesses 

It is important to be clear that predictability is not the same as prediction. A predictable word is processed faster than an unpredictable word (something that has been known since the 1970/80s), e.g., Rayner, Schwanenfluegel, etc. But this could be due to ease of integration. I think this issue can probably be dealt with by careful writing (see point on line 18 below). To be clear, I do not believe that the effects reported here are due to integration alone (i.e., that nothing happens before the target word), but the evidence for this claim must come from actual demonstrations of prediction. 

The effect of load on the effects of predictability is very interesting (and also, I note that the fairly novel way of assessing load is itself valuable). Assuming that the experiments do measure prediction, it suggests that they are not cost-free, as is sometimes assumed. I think the researchers need to look closely at the visual world literature, most particularly the work of Huettig. (There is an isolated reference to Ito et al., but this is one of a large and highly relevant set of papers.) 

There is a major concern about the effects of age. See the Results (161-5): this depends on what is meant by word predictability. It's correct if it means the predictability in the corpus. But it may or may not be correct if it refers to how predictable a word is to an individual participant. The texts are unlikely to be equally predictable to different participants, and in particular to younger vs. older participants, because of their different experiences. To put it informally, the newspaper articles may be more geared to the expectations of younger people. But there is also another problem: the LLM may have learned on the basis of language that has largely been produced by young people, and so its predictions are based on what young people are likely to say. Both of these possibilities strike me as extremely likely. So it may be that older adults are affected more by words that they find surprising, but it is also possible that the texts are not what they expect, or the LLM predictions from the text are not the ones that they would make. In sum, I am not convinced that the authors can say anything about the effects of age unless they can determine what is predictable for different ages of participants. I suspect that this failure to control is an endemic problem in the literature on aging and language processing and needs to be systematically addressed. 

Overall, I think the paper makes enough of a contribution with respect to load to be useful to the literature. But for discussion of age, we would need something like evidence of how younger and older adults would complete these texts (on a word-by-word basis) and that they were equally predictable for different ages. I assume there are ways to get LLMs to emulate different participant groups, but I doubt that we could be confident about their accuracy without a lot of testing. But without something like this, I think making claims about age would be quite misleading. 

We thank both reviewers for their constructive feedback and for highlighting areas where our theoretical framing and analyses could be clarified and strengthened. We have carefully considered each of the points raised and made substantial additions and revisions.

As a summary, we have directly addressed the concerns raised by the reviewers by incorporating task-switching predictors into the statistical models, paralleling our focus on surprisal with a full analysis and interpretation of entropy, clarifying the robustness (and limitations) of the replicated findings, and addressing potential limitations in our Discussion.

We believe these revisions substantially strengthen the manuscript and improve the reading flow, while also clarifying the scope of our conclusions. We will not illustrate these changes in more detail:

(1) Cognitive load and task-switching components.

We agree that cognitive load is a multifaceted construct, particularly since our secondary task broadly targets executive functioning. In response to Reviewer 1, we therefore examined task-switching demands more closely by adding the interaction term n-back reaction × cognitive load to a model restricted to 1-back and 2-back Dual Task blocks (as there were no n-back reactions in the Reading Only condition). This analysis showed significantly longer reading times in the 2-back than in the 1back condition, both for trials with and without an n-back reaction. Interestingly, the difference between reaction and no-reaction trials was smaller in the 2-back condition (β = -0.132, t(188066.09) = -34.269, p < 0.001), which may simply reflect the general increase in reading time for all trials so that the effect of the button press time decreases in comparison to the 1-back. In that sense, these findings are not unexpected and largely mirror the main effect of cognitive load. Crucially, however, the three-way interaction of cognitive load, age, and surprisal remained robust (β = 0.00004, t(188198.86) = 3.540, p < 0.001), indicating that our effects cannot be explained by differences in taskswitching costs across load conditions. To maintain a streamlined presentation, we opted not to include this supplementary analysis in the manuscript.

(2) Entropy analyses.

Reviewer 1 pointed out that our initial manuscript placed more emphasis on surprisal. In the revised manuscript, we now report a full set of entropy analyses in the supplementary material. In brief, these analyses show that participants generally benefit from lower entropy across cognitive load conditions, with one notable exception: young adults in the Reading Only condition, where higher entropy was associated with faster reading times. We have added these results to the manuscript to provide a more complete picture of the prediction versus integration distinction highlighted in the review (see sections “Control Analysis: Disentangling the Effect of Cognitive Load on Pre- and PostStimulus Predictive Processing” in the Methods and “Disentangling the Effect of Cognitive Load on Pre- and Post-Stimulus Predictive Processing“ in the Results).

(3) Replication consistency.

Reviewer 1 noted that the results of the replication analysis were somewhat puzzling. We take this point seriously and agree that the original model was likely underpowered to detect the effect of interest. To address this, we excluded the higher-level three-way interaction of age, cognitive load, and surprisal, focusing instead on the primary effect examined in this paper: the modulatory influence of cognitive load on surprisal. Using this approach, we observed highly consistent results between the original online subsample and the online replication sample.

(4) Potential age bias in GPT-2.  

We thank Reviewer 2 for their thoughtful and constructive feedback and agree that a potential age bias in GPT-2’s next-token predictions warrants caution. We thus added a section in the Discussion explicitly considering this limitation, and explain why it should not affect the implications of our study.

Reviewer #1 (Recommendations for the authors):

The d-prime model operates at the block level. How many observation goes into the fitting (about 175*8=1050)? How can the degrees of freedom of a certain variable go up to 188435? 

We thank the reviewer for spotting this issue. Indeed, there was an error in our initial calculations, which we have now corrected in the manuscript. Importantly, the correction does not meaningfully affect the results for the analysis of d-primes or the conclusions of the study (see line 102).  

“A linear mixed-effects model revealed n-back performance declined with cognitive load (β = -1.636, t(173.13) = -26.120, p < 0.001), with more pronounced effects with advancing age (β = -0.014, t(169.77) = -3.931, p > 0.001; Fig. 3b, Table S1)”.

Consider spelling out all the "simple coding schemes" explicitly. 

We thank the reviewer for this helpful suggestion. In the revised manuscript, we have now included the modelled contrasts in brackets after each predictor variable.

“Example from line 527: In both models, we included recording location (online vs. lab), cognitive load (1-back and 2back Dual Task vs. Reading Only as the reference level) and continuously measured age (centred) in both models as well as the interaction of age and cognitive load as fixed effects”.

The relationship between comprehension accuracy and strategies for color judgement is unclear or not intuitive. 

We thank the reviewer for this helpful comment. The n-back task, which required participants to judge colours, was administered at the single-trial level, with colours pseudorandomised to prevent any specific colour - or sequence of colours - from occurring more frequently than others. In contrast, comprehension questions were presented at the end of each block, meaning that trial-level stimulus colour was unrelated to accuracy on the block-level comprehension questions. However, we agree that this distinction may not have been entirely clear, and we have now added a brief clarification in the Methods section to address this point (see line 534):  

“Please note that we did not control for trial-level stimulus colour here. The n-back task, which required participants to judge colours, was administered at the single-trial level, with colours pseudorandomised to prevent any specific colour - or sequence of colours - from occurring more frequently than others. In contrast, comprehension questions were presented at the end of each block, meaning that trial-level stimulus colour was unrelated to accuracy on the blocklevel comprehension questions”.

Could you explain why comprehension accuracy is not modeled in the same way as d-prime, i.e., with a similar set of predictors? 

This is a very good point. After each block, participants answered three comprehension questions that were intentionally designed to be easy: they could all be answered correctly after having read the corresponding text, but not by common knowledge alone. The purpose of these questions was primarily to ensure participants paid attention to the texts and to allow exclusion of participants who failed to understand the material even under minimal cognitive load. As comprehension accuracy was modelled at the block level with 3 questions per block, participants could achieve only discrete scores of 0%, 33.3%, 66.7%, or 100%. Most participants showed uniformly high accuracy across blocks, as expected if the comprehension task fulfilled its purpose. However, this limited variance in performance caused convergence issues when fitting a comprehension-accuracy model at the same level of complexity as the d′ model. To model comprehension accuracy nonetheless, we therefore opted for a reduced model complexity in this analysis.

RT of previous word: The motivations described in the Methods, such as post-error-slowing and sequential modulation effects, lack supporting evidence. The actual scope of what this variable may account for is unclear.  

We are happy to elaborate further regarding the inclusion of this predictor. Reading times, like many sequential behavioral measures, exhibit strong autocorrelation (Schuckart et al., 2025, doi: 10.1101/2025.08.19.670092). That is, the reading time of a given word is partially predictable from the reading time of the previous word(s). Such spillover effects can confound attempts to isolate trialspecific cognitive processes. As our primary goal was to model single-word prediction, we explicitly accounted for this autocorrelation by including the log reading time of the preceding trial as a covariate. This approach removes variance attributable to prior behavior, ensuring that the estimated effects reflect the influence of surprisal and cognitive load on the current word, rather than residual effects of preceding trials. We now added this explanation to the manuscript (see line 553):

“Additionally, it is important to consider that reading times, like many sequential behavioural measures, exhibit strong autocorrelation (Schuckart et al., 2025), meaning that the reading time of a given word is partially predictable from the reading time of the previous word. Such spillover effects can confound attempts to isolate trial-specific cognitive processes. As our primary goal was to model single-word prediction, we explicitly accounted for this autocorrelation by including the reading time of the preceding trial as a covariate”.  

Block-level d-prime: It was shown with the d-prime performance model that block-level d-prime is a function of many of the reading-related variables. Therefore, it is not justified to use them here as "a proxy of each participant's working memory capacity."

We thank the reviewer for their comment. We would like to clarify that the d-prime performance model indeed included only dual-task d-primes (i.e., d-primes obtained while participants were simultaneously performing the reading task). In contrast, the predictor in question is based on singletask d-primes, which are derived from the n-back task performed in isolation. While dual- and singletask d-primes may be correlated, they capture different sources of variance, justifying the use of single-task d-primes here as a measure of each participant’s working memory capacity.

Word frequency is entangled with entropy and surprisal. Suggest removal.

We appreciate the reviewer’s comment. While word frequency is correlated with word surprisal, its inclusion does not affect the interpretation of the other predictors and does not introduce any bias. Moreover, it is a theoretically important control variable in reading research. Since we are interested in the effects of surprisal and entropy beyond potential biases through word length and frequency, we believe these are important control variables in our model. Moreover, checks for collinearity confirmed that word frequency was neither strongly correlated with surprisal nor entropy. In this sense, including it is largely pro forma: it neither harms the model nor materially changes the results, but it ensures that the analysis appropriately accounts for a well-established influence on word processing.

Entropy reflects the cognitive load of word prediction. It should be investigated in parallel and with similar depth as surprisal (which reflects the load of integration).

This is an excellent point that warrants further investigation, especially since the previous literature on the effects of entropy on reading time is scarce and somewhat contradictory. We have thus added additional analyses and now report the effects of cognitive load, entropy, and age on reading time (see sections “Disentangling the Effect of Cognitive Load on Pre- and Post-Stimulus Predictive Processing” in the Results, “Control Analysis: Disentangling the Effect of Cognitive Load on Pre- and Post-Stimulus Predictive Processing” in the Methods as well as Fig. S7 and Table S6 in the Supplements for full results). In brief, we observe a significant three-way interaction among age, cognitive load, and entropy. Specifically, while all participants benefit from low entropy under high cognitive load, reflected by shorter reading times, in the baseline condition this benefit is observed only in older adults. Interestingly, in the baseline condition with minimal cognitive load, younger adults even show a benefit from high entropy. Thus, although the overall pattern for entropy partly mirrors that for surprisal – older adults showing increased reading times when word entropy is high and generally greater sensitivity to entropy variations – the effects differ in one important respect. Unlike for surprisal, the detrimental impact of increased word entropy is more pronounced under high cognitive load across all participants.

Reviewer #2 (Recommendations for the authors):

I agree in relation to prediction/load, but I am concerned (actually very concerned) that prediction needs to be assessed with respect to age. I suspect this is one reason why there is so much inconsistency in the effects of age in prediction and, indeed, comprehension more generally. I think the authors should either deal with it appropriately or drop it from the manuscript.

Thank you for raising this important concern. It is true that prediction is a highly individual, complex process as it depends upon the experiences a person has made with language over their lifespan. As such, one-size-fits-all approaches are not sufficient to model predictive processing. In our study, we thus took particular care to ensure that our analyses captured both age-related and other interindividual variability in predictive processing.

First, in our statistical models, we included age not only as a nuisance regressor, but also assessed age-related effects in the interplay of surprisal and cognitive load. By doing so, we explicitly model potential age-related differences in how individuals of different ages predict language under different levels of cognitive load.

Second, we hypothesised that predictive processing might also be influenced by a range of interindividual factors beyond age, including language exposure, cognitive ability, and more transient states such as fatigue. To capture such variability, all models included by-subject random intercepts and slopes, ensuring that unmodelled individual differences were statistically accommodated.

Together, these steps allow us to account for both systematic age-related differences and residual individual variability in predictive processing. We are therefore confident that our findings are not confounded by unmodelled age-related variability.

Line 18, do not confuse prediction (or pre-activation) with predictability. Predictability effects can be due to integration difficulty. See Pickering and Gambi 2018 for discussion. The discussion then focuses on graded parallel predictions, but there is also a literature concerned with the prediction of one word, typically using the "visual world" paradigm (which is barely cited - Reference 60 is an exception). In the next paragraph, I would recommend discussing the N400 literature (particularly Federmeier). There are a number of reading time studies that investigate whether there is a cost to a disconfirmed prediction - often finding no cost (e.g., Frisson, 2017, JML), though there is some controversy and apparent differences between ERP and eye-tracking studies (e.g., Staub). This literature should be addressed. In general, I appreciate the value of a short introduction, but it does seem too focused on neuroscience rather than the very long tradition of behavioural work on prediction and predictability.

We thank the reviewer for this suggestion. In the revised manuscript, we have clarified the relevant section of the introduction to avoid confusion between predictability and predictive processing, thereby improving conceptual clarity (see line 16).

“Instead, linguistic features are thought to be pre-activated broadly rather than following an all-or-nothing principle, as there is evidence for predictive processing even for moderately- or low-restraint contexts (Boston et al., 2008; Roland et al., 2012; Schmitt et al., 2021; Smith & Levy, 2013)”.  

We also appreciate the reviewer’s comment regarding the introduction. While our study is behavioural, we frame it in a neuroscience context because our findings have direct implications for understanding neural mechanisms of predictive processing and cognitive load. We believe that this framing is important for situating our results within the broader literature and highlighting their relevance for future neuroscience research.

I don't think 2 two-word context is enough to get good indicators of predictability. Obviously, almost anything can follow "in the", but the larger context about parrots presumably gives a lot more information. This seems to me to be a serious concern - or am I misinterpreting what was done? 

This is a very important point and we thank the reviewer for raising it. Our goal was to generate word surprisal scores that closely approximate human language predictions. In the manuscript, we report analyses using a 2-word context window, following recommendations by Kuribayashi et al. (2022).

To evaluate the impact of context length, we also tested longer windows of up to 60 words (not reported). While previous work (Goldstein et al., 2022) shows that GPT-2 predictions can become more human-like with longer context windows, we found that in our stimuli – short newspaper articles of only 300 words – surprisal scores from longer contexts were highly correlated with the 2word context, and the overall pattern of results remained unchanged. To illustrate, surprisal scores generated with a 10-word context window and surprisal scores generated with the 2-word context window we used in our analyses correlated with Spearman’s ρ = 0.976.

Additionally, on a more technical note, using longer context windows reduces the number of analysable trials, since surprisal cannot be computed for the first k words of a text with a k-word context window (e.g., a 50-word context would exclude ~17% of the data).  

Importantly, while a short 2-word context window may introduce additional noise in the surprisal estimates, this would only bias effects toward zero, making our analyses conservative rather than inflating them. Critically, the observed effects remain robust despite this conservative estimate, supporting the validity of our findings.

However, we agree that this is a particularly important and sensitive point, and have now added a discussion of it to the manuscript (see line 476).

“Entropy and surprisal scores were estimated using a two-word context window. While short contexts have been shown to enhance GPT-2’s psychometric alignment with human predictions, making next-word predictions more human-like (Kuribayashi et al., 2022), other work suggests that longer contexts can also increase model–human similarity (Goldstein et al., 2022). To reconcile these findings in our stimuli and guide the choice of context length, we tested longer windows and found surprisal scores were highly correlated with the 2-word context (e.g., 10-word vs. 2-word context: Spearman’s ρ = 0.976), with the overall pattern of results unchanged. Additionally, employing longer context windows would have also reduced the number of analysable trials, since surprisal cannot be computed for the first k words of a text with a k-word context window. Crucially, any additional noise introduced by the short context biases effect estimates toward zero, making our analyses conservative rather than inflating them”.

Line 92, task performance, are there interactions? Interactions would fit with the experimental hypotheses. 

Yes, we did include an interaction term of age and cognitive load and found significant effects on nback task performance (d-primes; b = -0.014, t(169.8) = -3.913, p < 0.001), but not on comprehension question accuracy (see table S1 and Fig. S2 in the supplementary material).

Line 149, what were these values?

We found surprisal values ranged between 3.56 and 72.19. We added this information in the manuscript (see line 143).

huhu

Tiere

Das ist nur ein Test

• Background
• Show off a bit.
• Skills I bring and interests, come and see!

no table with raw number for this

There is no table with this number

where does this number come from? Table 1 does not have it.

Document d'information : Rencontres interprofessionnelles de la Miprof 2025

Résumé Exécutif

Ce document synthétise les analyses, données et stratégies clés présentées lors des Rencontres interprofessionnelles de la Miprof 2025.

La conférence a souligné l'ampleur systémique des violences sexistes et sexuelles en France, tout en dressant un état des lieux des avancées législatives, des défis judiciaires et des nouvelles menaces. Les points saillants sont les suivants :

1. Une ambition d'éradication et un cadre législatif renforcé : L'objectif politique affirmé n'est pas de réduire mais d'éradiquer totalement les violences.

Des avancées législatives majeures ont été réalisées, notamment l'introduction de la notion de non-consentement dans la définition pénale du viol, la reconnaissance du contrôle coercitif et l'allongement des délais de prescription pour les crimes sexuels sur mineurs. Une loi-cadre transpartisane est en préparation pour unifier la réponse institutionnelle.

2. Des données alarmantes confirmant un fléau de masse : Les statistiques pour 2023-2024 révèlent une prévalence massive des violences. Chaque jour, 3,5 femmes sont victimes de féminicide (direct ou indirect) ou de tentative de féminicide par leur partenaire ou ex-partenaire.

Les enfants représentent plus de la moitié des victimes de violences sexistes et sexuelles enregistrées. L'analyse confirme que les femmes sont victimes de manière disproportionnée (85 % des victimes de violences sexuelles) et que les agresseurs, majoritairement des hommes, sont le plus souvent des proches, faisant du foyer le lieu le plus dangereux.

3. L'urgence de la prévention des féminicides et de la protection des enfants co-victimes : L'analyse des homicides conjugaux ("rétex") montre que dans la moitié des cas, des signaux d'alerte préexistaient.

Les experts appellent à un changement de paradigme : se focaliser sur l'auteur, mieux "criticiser" les situations à haut risque en identifiant des marqueurs clés comme la strangulation et les menaces de mort, et utiliser l'ordonnance de protection de manière préventive.

Le "suicide forcé", angle mort des féminicides, représente près de 300 décès de femmes par an. Les enfants exposés aux violences conjugales sont reconnus comme des victimes directes subissant des traumatismes sévères, nécessitant une protection judiciaire coordonnée et des outils de prévention ciblés comme le film "Selma".

4. L'émergence de nouveaux champs de bataille : la cyberviolence et les mouvements masculinistes : Les cyberviolences sexistes et sexuelles touchent massivement les jeunes, avec des conséquences psychologiques graves et un très faible taux de plainte (12 %).

Parallèlement, la montée en puissance de mouvements masculinistes organisés, professionnels et très bien financés (plus d'un milliard de dollars en Europe) constitue une menace directe. Ces mouvements attaquent les dispositifs d'aide comme le 3919, instrumentalisent les droits des enfants pour affaiblir ceux des mères et cherchent à saper les fondements de l'égalité via un lobbying politique et une présence médiatique accrus.

En conclusion, la journée a mis en lumière la nécessité d'une vigilance constante, d'une formation continue de tous les professionnels, d'une meilleure coordination inter-institutionnelle et d'une réponse ferme et structurée face aux nouvelles stratégies des agresseurs et de leurs relais idéologiques.

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1. Vision Politique et Cadre d'Action Stratégique

Les rencontres ont été ouvertes par une intervention de la Ministre de l'égalité entre les femmes et les hommes, qui a fixé un cap clair : l'objectif n'est pas de réduire ou d'atténuer les violences, mais de les éradiquer complètement et définitivement. Cette ambition se traduit par un renforcement de l'arsenal juridique et une adaptation constante des stratégies d'intervention.

1.1. Un Phénomène aux Multiples Visages

La ministre a rappelé la diversité des formes de violences faites aux femmes, qui ne cessent d'évoluer :

• Physiques, sexuelles, psychologiques

• Économiques, numériques, chimiques

• Liées à la traite des êtres humains, souvent dissimulées derrière des façades comme de prétendus salons de massage.

Cette adaptabilité des violences exige une réponse innovante et proactive de la part des pouvoirs publics.

1.2. Avancées Législatives Récentes

L'année 2025 est présentée comme celle du "renforcement et de la clarté", marquée par plusieurs avancées législatives majeures :

• Définition du viol et non-consentement : La proposition de loi introduisant la notion de non-consentement dans la définition pénale du viol est une avancée historique. Elle inscrit dans la loi que "ne pas dire non, ce n'est pas dire oui", mettant fin à une ambiguïté qui protégeait les auteurs. Le silence, la sidération ou la peur ne sont pas des consentements.

• Délais de prescription pour les viols sur mineurs : Une loi a prolongé les délais de prescription, reconnaissant qu'il faut parfois des décennies pour que la parole se libère. L'objectif final reste cependant l'imprescriptibilité des crimes sexuels commis sur les enfants.

• Reconnaissance du contrôle coercitif : Pour la première fois, le droit français reconnaît le contrôle coercitif, un pas décisif pour identifier les violences conjugales avant les coups.

Celles-ci commencent par des actes comme la confiscation du téléphone, l'isolement social, l'installation de la peur, le contrôle des comptes bancaires, l'hypercontrôle et l'humiliation répétée.

1.3. Vers une Loi-Cadre et une Mobilisation Nationale

Pour assurer une vision globale et cohérente, un groupe de travail parlementaire transpartisan a été mis en place pour préparer une loi-cadre contre les violences sexuelles et intrafamiliales.

L'objectif est de bâtir une "nation mobilisée" où la détection, l'écoute, la protection et la coordination deviennent des réflexes pour tous les professionnels et citoyens.

1.4. Vigilance face aux Mouvements Masculinistes

Une alerte a été lancée contre la montée des mouvements masculinistes qui cherchent à relativiser la violence et à banaliser les inégalités.

Leur discours, souvent masqué derrière la "liberté d'expression", vise à faire reculer les droits des femmes.

La réponse doit être ferme : "La liberté d'expression n'a jamais été la liberté de nuire" et l'égalité femmes-hommes est un principe fondateur de la République, non une opinion.

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2. Données Clés 2024 : Une Violence de Masse Systémique et Genrée

La présentation de la Lettre n°25 de l'Observatoire national des violences faites aux femmes a objectivé l'ampleur du phénomène à travers des données multi-sources (Ministères de l'Intérieur et de la Justice, associations).

2.1. Statistiques Générales des Violences

Catégorie de Violence

Donnée Clé

Source

Fréquence

Toutes les 23 secondes, une femme subit du harcèlement, de l'exhibition sexuelle ou un envoi non sollicité de contenu sexuel.

Miprof

Toutes les 2 minutes, une femme est victime de viol, tentative de viol ou agression sexuelle.

Miprof

Violences Sexuelles (Victimation déclarée 2023)

1 809 000 personnes majeures se sont déclarées victimes.

Enquête VRS (SSMSI)

Détail pour les femmes

Harcèlement sexuel : 1 155 000

Enquête VRS (SSMSI)

Exhibition / Envoi contenu sexuel non sollicité : 369 000

Enquête VRS (SSMSI)

Viol ou tentative de viol : 159 000

Enquête VRS (SSMSI)

Agression sexuelle : 222 000

Enquête VRS (SSMSI)

Violences au sein du couple (Victimation déclarée 2023)

376 000 femmes majeures se sont déclarées victimes.

Enquête VRS (SSMSI)

Violences enregistrées par les forces de l'ordre (2024)

Violences sexuelles : 94 900 filles et femmes victimes (52 % de mineures).

Police / Gendarmerie

Violences au sein du couple : 228 000 femmes victimes.

Police / Gendarmerie

2.2. Féminicides et Tentatives (2024)

L'analyse des féminicides inclut désormais les "féminicides indirects", à savoir le harcèlement conduisant au suicide.

• Féminicides directs : 107 femmes tuées.

• Tentatives de féminicides directs : 270 femmes.

• Harcèlement par conjoint/ex ayant conduit au suicide ou à sa tentative : 906 femmes.

• Total combiné : 1 283 femmes que leur partenaire ou ex-partenaire a tuées, tenté de tuer ou poussées au suicide. Cela représente 3,5 femmes par jour.

• Enfants devenus orphelins en 2024 : 94. Depuis 2011, ce chiffre s'élève à 1 473.

2.3. La Réponse Judiciaire et les Dispositifs de Protection

Indicateur

Chiffre 2024 / 2025

Source

Poursuites (Violences sexuelles)

11 200 mis en cause poursuivis (sur 43 700 cas traités).

SDSE (Justice)

Condamnations (Violences sexuelles)

7 000 condamnations définitives.

SDSE (Justice)

Poursuites (Violences au sein du couple)

54 400 mis en cause poursuivis (sur 145 400 cas traités).

SDSE (Justice)

Condamnations (Violences au sein du couple)

42 200 condamnations définitives.

SDSE (Justice)

Accueil en Unité Médico-Judiciaire (UMJ)

74 000 victimes de violences sexistes et sexuelles.

Données administratives

Hébergement et logement dédiés

11 300 places au 31 décembre 2024.

Données administratives

Ordonnances de Protection

4 200 délivrées.

SDSE (Justice)

Téléphones Grave Danger (TGD) actifs

5 400 (début novembre 2025).

Données administratives

Bracelets Anti-Rapprochement (BAR) actifs

660 (début novembre 2025).

Données administratives

Appels traités par le 3919

Plus de 100 000.

FNSF

Signalements traités par le 119 (enfants co-victimes)

5 200.

SNATED

2.4. Analyse : Une Violence Systémique et un Danger Proche

• Dimension genrée : Les femmes représentent 85 % des victimes de violences sexuelles.

Pour 9 victimes sur 10, quel que soit leur sexe, l'agresseur est un homme. 84 % des victimes de violences au sein du couple sont des femmes (98 % pour les violences sexuelles au sein du couple).

• Danger au sein du foyer : Le discours public se focalise souvent sur le danger extérieur, mais les données démontrent le contraire. 46 % des viols enregistrés sur des femmes ont été commis dans le cadre conjugal. 58 % des femmes tuées en 2024 l'ont été par un membre de leur famille ou leur partenaire/ex-partenaire.

• Sous-déclaration massive : La loi du silence reste prégnante. Seules 2 % des femmes victimes de harcèlement sexuel ou d'exhibitionnisme déposent plainte. Ce taux monte à seulement 7 % pour les viols et agressions sexuelles.

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3. Focus : Les Cyberviolences Sexistes et Sexuelles

Une enquête nationale menée par un consortium d'associations (Point de contact, Féministes contre le cyberharcèlement, Stop Fisha) a révélé l'ampleur et les spécificités des violences en ligne.

3.1. Profil des Victimes et Nature des Actes

• Cibles principales : Les femmes et les filles, dont plus de la moitié sont mineures.

• L'image comme arme : Plus d'un quart des victimes ont subi une diffusion non consentie de leurs contenus intimes. Ce chiffre atteint 36 % chez les mineurs.

• Proximité de l'agresseur : Dans 85 % des cas où l'agresseur est connu, il s'agit d'un homme. Deux tiers des victimes connaissaient leur agresseur, qui provenait majoritairement de l'entourage proche (relation de couple pour 52 %, camarades de classe pour un tiers).

3.2. Conséquences Dévastatrices et Faible Recours à la Justice

• Impact psychologique : Les conséquences sont lourdes, même sans contact physique.

◦ Pensées suicidaires : 1 victime sur 10 (cyberviolence seule) ; 1 sur 3 (si les violences se prolongent hors ligne).   

◦ Tentatives de suicide : 7 % (cyberviolence seule) ; 1 sur 4 (si les violences se prolongent hors ligne).

• Taux de plainte : Seulement 12 % des victimes portent plainte (10 % pour les mineurs).

• Freins au dépôt de plainte :

◦ Méconnaissance : Un tiers des mineurs ne savaient pas qu'ils pouvaient porter plainte.  

◦ Sentiment d'inutilité : Un tiers des victimes estiment que la plainte ne les aiderait pas.  

◦ Culpabilisation : Deux tiers des victimes qui ont porté plainte déclarent s'être senties culpabilisées lors du processus.

3.3. Recommandations

• Prévention : Renforcer massivement la prévention, la sensibilisation et la formation en milieu scolaire et auprès du grand public, avec un discours de réduction des risques et de déculpabilisation.

• Formation : Former tous les professionnels (justice, police, santé, éducation) dans une perspective de genre.

• Accompagnement : Créer une plateforme unique et holistique pour les victimes adultes.

• Régulation : Généraliser le retrait préventif des contenus signalés par les plateformes, sans attendre la décision de modération finale.

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4. Focus : La Protection des Françaises Victimes de Violences à l'Étranger

Une table ronde a mis en lumière la situation souvent invisible des femmes françaises victimes de violences à l'étranger, estimées entre 3 et 3,5 millions de personnes.

4.1. Vulnérabilités Spécifiques

Les chiffres officiels (186 situations suivies en 2024) sous-estiment largement la réalité. Les femmes à l'étranger font face à des difficultés supplémentaires :

• Dépendance : Dépendance économique et administrative vis-à-vis du conjoint (le visa est souvent lié).

• Isolement : Barrière linguistique et isolement social, loin du réseau de soutien.

• Risques juridiques : Contexte local où les violences ne sont pas toujours reconnues ou poursuivies, et risque de déplacement illicite d'enfants en cas de départ du pays.

• Stéréotypes : L'image des "expatriés privilégiés" masque la réalité des violences et freine la prise de conscience et l'action.

4.2. Stratégies de Réponse et Initiatives Modèles

• Feuille de route de la diplomatie féministe : Le Ministère de l'Europe et des Affaires étrangères a intégré la protection des Françaises à l'étranger dans sa stratégie, autour de trois axes : mieux informer, mieux protéger, mieux accompagner.

• Le modèle de Singapour : Une initiative pilote a été présentée : une clinique juridique gratuite et bilingue, fruit d'un partenariat entre le Barreau de Paris, la Law Society de Singapour et l'Ambassade de France.

Elle offre un accès au droit sécurisé et anonyme, articule les systèmes juridiques français et local, et oriente vers un réseau de partenaires (hébergement, psychologues).

• Formation du réseau consulaire : Des formations spécifiques, élaborées avec la Miprof, sont en cours de déploiement pour les 186 agents référents dans les consulats.

• Accès aux dispositifs nationaux : La plateforme numérique arretonslesviolences.gouv.fr est désormais accessible depuis l'étranger, mais le 3919 ne l'est pas encore, ce qui constitue un combat prioritaire.

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5. Focus : La Prévention des Féminicides

Une table ronde d'experts (magistrats, médecin légiste, avocate) a analysé les leviers pour mieux prévenir les passages à l'acte.

5.1. Enseignements des "Retours d'Expérience" (Retex)

L'analyse systématique des homicides conjugaux par les parquets a permis d'identifier des axes d'amélioration :

• Dans 50 % des cas, des signaux d'alerte ou des antécédents judiciaires existaient.

• Les failles se situent souvent au niveau du traitement des premiers signalements, de la communication entre acteurs judiciaires et de l'évaluation du danger.

5.2. Vers un Changement de Paradigme Judiciaire

• Focalisation sur l'auteur : La magistrate Gwnola Joly-Coz a insisté sur la nécessité de déplacer le regard de la victime vers l'auteur et ses stratégies, notamment via la notion de contrôle coercitif.

• "Criticiser" les situations : Les magistrats doivent identifier les situations de "très haute intensité" en se basant sur des critères objectifs et prédictifs.

• Marqueurs de danger imminent :

1. La strangulation : Un acte "sexo-spécifique" visant à faire taire et à arrêter la respiration, qui doit être considéré comme un critère de gravité absolue.  

2. Les menaces de mort : Elles ne doivent jamais être euphémisées ou minimisées, car elles manifestent une intention criminelle.

5.3. Le Rôle Clé de l'Ordonnance de Protection et du Repérage des Suicides Forcés

• Ordonnance de Protection : Ernestine Ronai a rappelé que cet outil (4 200 délivrées en France contre 33 000 en Espagne) est sous-utilisé et intervient trop tard.

Il doit devenir une première marche de protection accessible avant le dépôt de plainte, dès que des violences sont "vraisemblables".

• Suicide forcé : Yael Mellul a souligné que cet "angle mort" représente environ 300 féminicides par an.

La loi existe mais est très peu appliquée. Elle préconise une "autopsie psychologique" systématique en cas de suicide pour rechercher un contexte de harcèlement et de violences.

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6. Focus : Les Enfants Co-victimes

Les enfants exposés aux violences conjugales sont désormais reconnus comme des victimes directes, mais leur protection reste un défi majeur.

6.1. L'Impact Traumatique

• Les enfants sont profondément affectés, même sans subir de coups directs. 60 % présentent un diagnostic de trouble de stress post-traumatique.

• L'enfant est souvent utilisé comme une arme dans le cadre du contrôle coercitif exercé sur la mère.

6.2. Les Défis de la Protection

• Silos institutionnels : La complexité du système judiciaire (Juge aux Affaires Familiales, Juge des Enfants, juge pénal) peut conduire à des décisions contradictoires et à une vision parcellaire de la situation familiale.

Des initiatives comme les "chambres des VIF" en cour d'appel visent à décloisonner en jugeant le civil et le pénal de manière coordonnée.

• Exercice de l'autorité parentale : C'est un enjeu central, car elle est un levier majeur du contrôle coercitif post-séparation.

La loi a évolué pour permettre sa suspension ou son retrait, mais son application reste complexe.

• Rôle des services de protection de l'enfance (ASE) : Les professionnels doivent être formés à ne pas symétriser les violences et à toujours recentrer l'analyse sur le contexte de violence, même lorsque l'intervention porte sur les symptômes de l'enfant.

6.3. Le Film "Selma" : Un Outil de Prévention

• Objectif : Un court-métrage de fiction commandé par la Direction de la Jeunesse (DJEPVA) et réalisé par Johanna Benaïnous pour sensibiliser les animateurs et directeurs d'accueils collectifs de mineurs.

• Thématiques : Le film aborde la difficulté de signaler pour un jeune professionnel, la stratégie de l'agresseur pour déstabiliser et inverser la culpabilité, et un modèle d'accueil bienveillant par les forces de l'ordre.

• Déploiement : Il s'accompagne d'un livret de formation et sera déployé nationalement pour former les formateurs et les acteurs de terrain, en insistant sur le contrôle d'honorabilité, l'obligation de signalement et l'éducation au consentement.

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7. Focus : La Montée des Mouvements Masculinistes

La dernière table ronde a alerté sur la structuration et la professionnalisation des mouvements masculinistes, qui représentent une contre-offensive organisée face aux avancées féministes.

7.1. Idéologie et Stratégie

• Postulat de base : Le féminisme serait allé trop loin et les hommes seraient désormais les principales victimes, menacés d'éradication par un "complot" féministe.

• Tactique : Ils se présentent comme des "groupes de soutien" pour des hommes en souffrance, en leur offrant un bouc émissaire (les femmes, les féministes) et des solutions simplistes à des problèmes complexes (confiance en soi, relations).

• Recrutement : Ils ciblent particulièrement les jeunes hommes en quête identitaire via des influenceurs sur les réseaux sociaux, capitalisant financièrement et politiquement sur leur mal-être.

7.2. Une Offensive Financée et Professionnalisée

• Financement : Le rapport "La Nouvelle Vague" révèle qu'au moins 1,2 milliard de dollars ont financé les mouvements anti-genre en Europe entre 2019 et 2023.

Les fonds proviennent des États-Unis (droite chrétienne), de la Russie, mais sont majoritairement européens.

• Professionnalisation : Cet argent a permis de créer une infrastructure de lobbying à haut niveau, un écosystème de think tanks, une forte présence médiatique et la création de "services anti-genre" (ex: centres de "crise de grossesse" pour dissuader de l'IVG).

7.3. Manifestations et Impacts Concrets

• Attaques contre les dispositifs d'aide : La FNSF a témoigné des attaques ciblées contre le 3919 : tentatives de saturation de la ligne, harcèlement des professionnelles, et lobbying politique pour "ouvrir la ligne aux hommes" dans une logique de fausse symétrie qui nie la nature systémique des violences.

• Instrumentalisation des droits des enfants : Des propositions de loi (comme la PPL 819 sur la résidence alternée de principe) sont portées par des groupes masculinistes sous couvert de "défense des enfants", alors que leur objectif est de renforcer les droits des pères, y compris violents, au détriment de la sécurité des mères et des enfants.

• Infiltration politique : Ces mouvements ne sont plus marginaux. Ils sont "en costard-cravate" et obtiennent des rendez-vous dans les ministères et les parlements, faisant sauter les "digues républicaines".

7.4. Pistes de Réponse

• Médias : Traiter le masculinisme comme un fait et une menace terroriste, non comme une "opinion".

• Prévention : Renforcer l'éducation à l'égalité dès le plus jeune âge en s'appuyant sur les acteurs de terrain.

• Régulation : Contraindre légalement les plateformes numériques à modérer ces contenus haineux.

• Écoute des associations : Prendre au sérieux les alertes lancées par les associations féministes sur la banalisation des discours de haine et la revictimisation des femmes dans le système judiciaire (ex: contre-plaintes, stages pour auteurs imposés aux victimes).

'~듯이' 직유법을 반복해서 사용함으로써 모두 동등하다라는 의미를 생성한다. 화자가 나열한 대상들은 다 작고 여리지만 순수한 존재들인데 화자는 자신과 이들을 동일시하면서 자신의 가난과 외로움이 순수함의 증거라고 말하고 있다.

위에 언급한 것과 같은 맥락이다

슬픔으로 가득 차는 것은 소망을 이루지 못하는 상태 때문일 것이다

위의 차갑고 시퍼러둥둥하다는 심상과 대비된다. 차갑고 시퍼러둥둥하다는 것은 현실이고 따뜻한 것은 소망이라고 앞서 언급했으니 굳이 따지자면 화자의 소망을 얘기한다는 것을 알 수 있다.

접속 어미 '-고'를 통해 앞 뒤 단어들을 대등하게 연결한다. 즉, 화자는 가난함을 높음이라는 가치와 동등한 위계로 인식하고 있음을 알 수 있다. 이를 통해 화자는 단순히 가난을 궁핍함으로 생각하는 것이 아니라 세속적 탐욕이 없는 청빈함으로 인식하고 있다. 또한 외로움을 고립이 아니라 자신을 성찰하기 위한 고독으로 얘기를 하고 있다.

어여쁜 사람은 여럿이서 밥을 먹고 있는데 화자는 혼자서 생각을 하고 있다. 이 1 대 다수의 대조를 통해 외로움을 부각한다.

화자는 벽을 보며 생각만 하고 정적인 상태에 있는 반면 이 사람들은 국을 끓이고 저녁을 먹는 것과 같이 행동이 동적이다. 이 대조를 통해 화자의 외로움을 더욱 부각시킨다.

어여쁜 사람은 혼자가 아니다

위의 따끈뜬한이라는 촉각적 심상과 대비가 된다. 차가운 현실과 따뜻한 소망을 대조시켜 화자의 결핍과 궁핍한 현실을 강조한다

어머니가 가난하다고 말함으로써 화자가 궁핍한 현실을 말해준다

화자의 소망을 나타낸다

이것 또한 물체를 쉬게 할 수 없으므로 감정이 이입되어 있음을 알 수 있다

불빛이 지칠 수는 없으므로 화자는 자신의 감정을 사물에 이입하고 있다

쓸쓸한 것이라는 감정은 눈에 보이지 않지만, 화자는 이것이 벽 위를 지난다라고 말함으로써 추상적 감정을 물리적 실체로 바꿔 말했다. 이를 통해 화자는 자신의 내면세계를 벽 위에 투영하고 있음을 알 수 있다

만약 벽이 화려한 벽지였거나 어두운 색이었다면, '희미한 십오촉 전등'이나 '그림자', '지나가는 글자'들을 시각적으로 선명하게 포착해낼 수 없을 것이다.

가나다

Is energy consumption the best way to measure compute power? What about things like flops per second?

eLife Assessment

M proteins are essential group A streptococci virulence factors that bind to numerous human proteins; a small subset of M proteins, such as M3, have been reported to bind collagen, which is thought to promote tissue adherence. In this important paper, the authors provide a solid characterization of M3 interactions with collagen. The work raises significant questions regarding the specificity of the structure and its interactions with different collagens, with implications for the variable actions of M protein collagen interactions on biofilm formation.

Reviewer #1 (Public review):

Summary:

Wojnowska et al. report structural and functional studies of the interaction of Streptococcus pyogenes M3 protein with collagen. They show through X-ray crystallographic studies that the N-terminal hypervariable region of M3 protein forms a T-like structure, and that the T-like structure binds a three-stranded collagen-mimetic peptide. They indicate that the T-like structure is predicted by AlphaFold3 with moderate confidence level in other M proteins that have sequence similarity to M3 protein and M-like proteins from group C and G streptococci. For some, but not all, of these related M and M-like proteins, AlphaFold3 predicts, with moderate confidence level, complexes similar to the one observed for M3-collagen. Functionally, the authors show that emm3 strains form biofilms with more mass when surfaces are coated with collagen, and this effect can be blocked by an M3 protein fragment that contains the T-structure. They also show the co-occurrence of emm3 strains and collagen in patient biopsies and a skin tissue organoid. Puzzlingly, M1 protein has been reported to bind collagen, but collagen inhibits biofilm in a particular emm1 strain but that same emm1 strain colocalizes with collagen in a patient biopsy sample. The implications of the variable actions of collagen on biofilm formation are not clear.

Strengths:

The paper is well written and the results are presented in a logical fashion.

Weaknesses:

A major limitation of the paper is that it is almost entirely observational and lacks detailed molecular investigation. Insufficient details or controls are provided to establish the robustness of the data.

Comments on revisions:

The authors' response to this reviewer's Major issue #1 is inadequate. Their argument is essentially that if they denature the protein, then there is no activity. This does not address the specificity of the structure or its interactions.

They went only part way to addressing this reviewer's Major issue #2. While Figure 8 - supplement 3 shows 1D NMR spectra for M3 protein (what temperature?), it does not establish that stability is unaltered (to a significant degree).

This reviewer's Major issue #3 is one of the major reasons for considering this study to be observational. This reviewer agrees that structural biology is by its nature observational, but modern standards require validation of structural observations. The authors' response is that a mechanistic investigation involving mutant bacterial strains and validation involving mutated proteins is beyond their scope. Therefore, the study remains observational.

Major issue 4 was addressed suitably, but brings up the problematic point that the emm1 2006 strain colocalizes quite well with collagen in a patient biopsy sample but not in other assays. This calls into question the overall interpretability of the patient biopsy data.

The authors have not provided a point-by-point response. Issues that were indicated to be minor previously were deemed to be minor because this reviewer thought that they could easily be addressed in a revision. It appears that the authors have ignored many of these comments, and these issues are therefore now considered to be major issues. For example, no errors are given for Kd measurements, Table 2 is sloppy and lacks the requested information, negative controls are missing (Figure 10 - figure supplement 1), and there is no indication of how many independent times each experiment was done.

And "C4-binding protein" should be corrected to "C4b-binding protein."

Reviewer #2 (Public review):

Streptococcus pyogenes, or group A streptococci (GAS) can cause diseases ranging skin and mucosal infections, plasma invasion, and post-infection autoimmune syndromes. M proteins are essential GAS virulence factors that include an N-terminal hypervariable region (HVR). M proteins are known to bind to numerous human proteins; a small subset of M proteins were reported to bind collagen, which is thought to promote tissue adherence. In this paper, authors characterize M3 interactions with collagen and its role in biofilm formation. Specifically, they screened different collagen type II and III variants for full-length M3 protein binding using an ELISA-like method, detecting anti-GST antibody signal. By statistical analysis, hydrophobic amino acids and hydroxyproline found to positively support binding, whereas acidic residues and proline negatively impacted binding. The authors applied X-ray crystallography to determine the structure of the N-terminal domain (42-151 amino acids) of M3 protein (M3-NTD). M3-NTD dimmer (PDB 8P6K) forms a T-shaped structure with three helices (H1, H2, H3), which are stabilized by a hydrophobic core, inter-chain salt bridges and hydrogen bonds on H1, H2 helices, and H3 coiled coil. The conserved Gly113 serves as the turning point between H2 and H3. The M3-NTD is co-crystalized with a 24-residue peptide, JDM238, to determine the structure of M3-collagen binding. The structure (PDB 8P6J) shows that two copies of collagen in parallel bind to H1 and H2 of M3-NTD. Among the residues involved binding, conserved Try96 is shown to play a critical role supported by structure and isothermal titration calorimetry (ITC). The authors also apply a crystal-violet assay and fluorescence microscopy to determine that M3 is involved in collagen type I binding, but not M1 or M28. Tissue biopsy staining indicates that M3 strains co-localize with collagen IV-containing tissue, while M1 strains do not. The authors provide generally compelling evidence to show that GAS M3 protein binds to collagen, and plays a critical role in forming biofilms, which contribute to disease pathology. This is a very well-executed study and a well-written report relevant to understanding GAS pathogenesis and approaches to combatting disease; data are also applicable to emerging human pathogen Streptococcus dysgalactiae. One caveat that was not entirely resolved is if/how different collagen types might impact M3 binding and function. Due to the technical constrains, the in vitro structure and other binding assays use type II collagen whereas in vivo, biofilm formation assays and tissue biopsy staining use type I and IV collagen; it was unclear if this difference is significant. One possibility is that M3 has an unbiased binding to all types of collagens, only the distribution of collagens leads to the finding that M3 binds to type IV (basement membrane) and type I (varies of tissue including skin), rather than type II (cartilage).

Comments on revisions:

We are glad to see that the authors addressed our prior comments on M3 binding to different types of collagens in discussion section; adding a prediction of M3 binding to type I collagen (Figure 8-figure supplement 1B and 1C) is helpful to fill in the gap. Although it would be nice to experimentally fill in the gap by putting all types of collagens into one experiment (For example, like Figure 9A, use different types of human collagens to test biofilm formation; or Figure 10, use different types of human collagens to compete for biofilm formation), this appears to be beyond the scope of this paper. Meanwhile, the changes they have made are constructive.

The authors have addressed the majority of our prior comments.

Author response:

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

We thank the reviewers for their comments on the initial submission, which helped us improve and extend the paper. We would like to respond specifically to reviewer #1.

We disagree with the broad criticism of this study as being “almost entirely observational” and lacking “detailed molecular investigation”. We report structures and binding data, show mechanistic detail, identify critical residues and structural features underlying biological activity, and present biologically meaningful data demonstrating a role of the interaction of the M3 protein with collagens. We disagree that insufficient details or controls are included. We agree that our report has limitations, such as an understanding of potential emm1 strain binding to collagen, which might play a role in host tissue colonization, but not in biofilm.

In response to issues raised in the initial review, we conducted several new experiments for the revised manuscript. We believe these strengthen what we report. Firstly, as the reviewer suggested, we conducted a binding experiment where the tertiary fold of M3-NTD was disrupted to confirm the T-shaped fold is indeed required for binding to collagen, as might be expected based on the crystal structure of the complex. To achieve this, we did not, as the reviewer states, use denatured protein in the ITC binding experiment. Instead, we used a monomeric form of M3-NTD, which does not adopt a well-defined tertiary structure, but retains all residues in the context of alpha helices. Secondly, we added more evidence for the importance of structural features (amino acid side chains defining the collagen binding site) by analysing the role of Trp103. Together, we provide clear evidence for the specific role of the T-shaped fold of M3-NTD for collagen binding.

Responding to a constructive criticism by reviewer #1 we characterised M3-NTD mutants to demonstrate conservation of overall structure. NMR is an exquisite tool for this as it is highly sensitive to structural changes. It is not clear why the reviewer suggested we should have measured the stability of the proteins, which is irrelevant here. What matters is that the fold is conserved between mutated variants at the chosen experimental temperature (now added to the Methods section), which NMR demonstrates.

We added errors for the ITC-derived dissociation constants.

In the submitted versions of the paper we did not include the negative control requested by reviewer #1 for experiments shown in Figure 10 - figure supplement 1B. In our view this does not add information supporting our findings. However, we have now added two negative controls, staining of emm1 and emm28 strains. As expected, no reactivity was found with the type-specific M3 HVR antiserum while the M3 BCW antiserum showed weak reactivity, in line with some sequence similarity of the C-terminal regions of M proteins.

Table 2 contains essential information, in line with what generally is shown in crystallographic tables in this journal. All other information can be found in the depositions of our data at the PDB. The structures have been scrutinised and checked by the PDB and passed all quality tests.

We stated how many times experiments were done where appropriate. We now added this information for CLC assays (as given in the previously published protocol, refs. 45, 47). ITC was carried out more than once for optimization but the results of single experiments are shown (as is common practice).

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

Many thanks for assessing our submission. We are grateful for the reviews that have informed a revised version of the paper, which includes additional data and modified text to take into account the reviewers’ comments. 

We addressed the major limitation identified by Reviewer #1 by including data to demonstrate that collagen binding is indeed dependent on the T-shaped fold (major issue 1). Reviewer #1 suggested this needs to be done through extensive mutational work. This in our view was neither feasible nor necessary. Instead, we used ITC to measure collagen peptide binding using a monomeric form of M3, which preserves all residues including the ones involved in binding, but cannot form the T-shaped structure. This achieves the same as unravelling the T fold through mutations, but without the risk of aJecting binding through altering residues that are involved in both binding and definition of the T fold. The experiment shows a very weak interaction, confirming the fold of the M3-NTD is required for binding activity.

Reviewer #1 finds the study limited for being “almost entirely observational”. Structural biology is by its nature observational, which is not a limitation but the very purpose of this approach. Our study goes beyond observing structures. In the first version of our paper, we identified a critical residue within a previously mapped binding site, and demonstrated through mutagenesis a causal link between presence of this residue on a tertiary fold and collagen binding activity. However, we agree this analysis could have been strengthened by additional mutagenesis, which we carried out and describe in the revised manuscript. This identifies a second residue that is critical for collagen binding. We firmed up these mutational experiments with a characterisation of mutated forms of M3 by NMR spectroscopy to confirm that these mutations did not aJect the overall fold, addressing major issue no. 2 of reviewer #1. We further demonstrate that the interaction between M3 and collagen is the cause of greatly enhanced biofilm formation as observed in patient biopsies and a tissue model of infection. We show that other streptococci that do not possess a surface protein presenting collagen binding sites like M3 do not form collagen-dependent biofilm. We therefore do not think that criticising our study for being almost entirely observational is valid. 

Major issue 3:

We agree with the reviewer that it would be useful to carry out experiments with k.o. and complemented strains. Such experiments go beyond the scope of our study, but might be carried out by us or others in the future. We disagree that emm1 is used “as a negative”. Instead, we established that, in contrast to emm3 strains, emm1 strain biofilm formation is not enhanced by collagen. 

We addressed major issue 4 by quantifying colocalizations in the patient biopsies and 3D tissue model experiments.

We thank Reviewer #2 for the thorough analysis of our reported findings. The main criticism here (issue 1) concerns the question of whether binding of emm3 streptococci would diJer to diJerent types of collagen. Our collagen peptide binding assays together with the structural data identify the collagen triple helix as the binding site for M3. While collagen types diJer in their distribution, functions and morphology in diJerent tissues, they all have in common triple-helical (COL) regions with high sequence similarity that are non-specifically recognised by M3. Therefore, our data in conjunction with the body of published work showing binding to M3 to collagens I, II, III and IV suggest it is highly likely that emm3 streptococci will indeed bind to all types of collagen in the same manner. We added a statement to the manuscript to make this point more clearly. We also added a prediction of a complex between M3 and a collagen I triple-helical peptide, which supports the idea of conserved binding mechanism for all collagen types. Whether this means all collagen types in the various tissues where they occur are targeted by emm3 streptococci is a very interesting question, however one that goes beyond the scope of our study.

Minor issues identified by the reviewers were addressed through changes in the text and addition of figures.

Summary of changes:

(1) Two new authors have been added due to inclusion of additional data and analysis.

(2) New experimental data included in section "M3-NTD harbors the collagen binding site".

(3) Figure 3 panels A and B assigned and swapped.

(4) Figure 4 changed to include new data and move mutant M3-NTD ITC graphs to supplement.

(5) Table 2 corrected and amended.

(6) AlphaFold3 quality parameters ipTM and pTM added to all figures showing predicted structures.

(7) New supplementary figure added showing crystal packing of M3-NTD/collagen peptide complex.

(8) Figure supplement of predicted M-protein/collagen peptide complexes includes new panel for a type I collagen peptide bound to M3.

(9) New figure supplement showing mutant M3-NTD ITC data.

(10) New figure supplement showing 1D ¹H NMR spectra of M3-NTD mutants.

(11) Included data for additional M3-NTD mutants assessing role of Trp103 in collagen binding. Text extended to describe and place into context findings from ITC binding studies using these mutants.

(12) Added quantitative analysis of biopsy and tissue model data (Mander's overlap coeJicient).

(13) Corrected and extended table 3 to take into account new primers.

(14) Added experimental details for new NMR and ITC experiments as well as new quantitative image analysis.

(15) Minor adjustments to the text to improve clarity and correct errors.

• Zorin OS 18 has surpassed 1 million downloads in just over five weeks since its release.
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• New "Prima" eye implant is a breakthrough for the blind – allows regaining the ability to read.
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• Of 32 people implanted, 27 could read using central vision; after a year, they improved by 5 lines on the vision test chart.
• 70-year-old patient Sheila Irvine, who lost her sight over 30 years ago and has had the implant for 3 years, now solves crosswords.
• Rights to PRIMA acquired in 2024 by U.S. company Science Corporation. (video in source)

• Article warns about AI hallucinations spreading disinformation in journalism, law, and business, spotlighting Polish journalist Karolina Opolska's book with likely AI-generated fake sources and errors.
• Opolska incident reached 4 million potential contacts (1.6M traditional media, 2.4M social) from Nov 5-19, 2025, impacting 1 in 8 Poles aged 15+; social reaction mostly negative, debating trust in journalists and AI.
• Polish Exdrog firm lost road tender due to AI-fabricated tax interpretations (1.3M reach, Oct 26-Nov 10, 2025).
• Global cases include lawyers citing invented precedents and media promoting nonexistent books; BBC/EBU study shows 45% error rate in tools like ChatGPT, Copilot, Gemini, Perplexity.
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• IMM analyses from Polish media/social coverage for both cases.

LET OP: alleen toetsen aan 3:88 wanneer er sprake is van beschikkingsonbevoegdheid. Als er tekort word gekomen aan een andere/meerdere voorwaarden van art. 3:84 BW hoef je hier niet aan te toetsen

LET OP: alleen toetsen aan 3:86 wanneer er sprake is van beschikkingsonbevoegdheid. Als er tekort word gekomen aan een andere/meerdere voorwaarden van art. 3:84 BW hoef je hier niet aan te toetsen.

art. 3:86 BW

art. 3:88 BW

Is this really valuable to me?

eLife Assessment

This important study introduces the Life Identification Number (LIN) coding system as a powerful and versatile approach for classifying Neisseria gonorrhoeae lineages. The authors show that LIN codes capture both previously defined lineages and their relationships in a way that aligns with the species' phylogenetic structure. The compelling evidence presented, together with its integration into the PubMLST platform, underscores its strong potential to enhance epidemiological surveillance and advance our understanding of gonococcal population biology.

Reviewer #3 (Public review):

Summary:

In this well-written manuscript, Unitt and colleagues propose a new, hierarchical nomenclature system for the pathogen Neisseria gonorrhoeae. The proposed nomenclature addresses a longstanding problem in N. gonorrhoeae genomics, namely that the highly recombinant population complicates typing schemes based on only a few loci and that previous typing systems, even those based on the core genome, group strains at only one level of genomic divergence without a system for clustering sequence types together. In this work, the authors have revised the core genome MLST scheme for N. gonorrhoeae and devised life identification numbers (LIN) codes to describe the N. gonorrhoeae population structure.

Strengths:

The LIN codes proposed in this manuscript are congruent with previous typing methods for Neisseria gonorrhoeae like cgMLST groups, Ng-STAR, and NG-MAST. Importantly, they improve upon many of these methods as the LIN codes are also congruent with the phylogeny and represent monophyletic lineages/sublineages. Additionally, LIN code cluster assignment is fixed, and clusters are not fused as is common in other typing schemes.

The LIN code assignment has been implemented in PubMLST allowing other researchers to assign LIN codes to new assemblies and put genomes of interest in context with global datasets, including in private datasets.

Weaknesses:

The authors have defined higher resolution thresholds for the LIN code scheme. However, they do not investigate how these levels correspond to previously identified transmission clusters from genomic epidemiology studies. This will be an important focus of future work, but it may be beyond the scope of the current manuscript.

Comments on revisions:

The authors have addressed my previous comments. I have no additional recommendations.

Author response:

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

Reviewer #1 (Public review):

Summary:

Bacterial species that frequently undergo horizontal gene transfer events tend to have genomes that approach linkage equilibrium, making it challenging to analyze population structure and establish the relationships between isolates. To overcome this problem, researchers have established several effective schemes for analyzing N. gonorrhoeae isolates, including MLST and NG-STAR. This report shows that Life Identification Number (LIN) Codes provide for a robust and improved discrimination between different N. gonorrhoeae isolates.

Strengths:

The description of the system is clear, the analysis is convincing, and the comparisons to other methods show the improvements offered by LIN Codes.

Weaknesses:

No major weaknesses were identified by this reviewer.

We thank the reviewer for their assessment of our paper.

Reviewer #2 (Public review):

Summary:

This paper describes a new approach for analyzing genome sequences.

Strengths:

The work was performed with great rigor and provides much greater insights than earlier classification systems.

Weaknesses:

A minor weakness is that the clinical application of LIN coding could be articulated in a more in-depth way. The LIN coding system is very impressive and is certainly superior to other protocols. My recommendation, although not necessary for this paper, is that the authors expand their analysis to noncoding sequences, especially those upstream of open reading frames. In this respect, important cis-acting regulatory mutations that might help to further distinguish strains could be identified.

We thank the reviewer for their comments. LIN code could be applied clinically, for example in the analysis of antibiotic resistant isolates, or to investigate outbreaks associated with a particular lineage. We have updated the text to note this, starting at line 432.

In regards to non-coding sequences: unfortunately, intergenic regions are generally unsuitable for use in typing systems as (i) they are subject to phase variation, which can occlude relationships based on descent; (ii) they are inherently difficult to assemble and therefore can introduce variation due to the sequencing procedure rather than biology. For the type of variant typing that LIN code represents, which aims to replicate phylogenetic clustering, protein encoding sequences are the best choice for convenience, stability, and accuracy. This is not to say that it is not a valid object to base a nomenclature on intergenic regions, which might be especially suitable for predicting some phenotypic characters, but this will still be subject to problem (ii), depending on the sequencing technology used.  Such a nomenclature system should stand beside, rather than be combined with or used in place of, phylogenetic typing. However, we could certainly investigate the relationship between an isolates LIN code and regulatory mutations in the future.

Reviewer #3 (Public review):

Summary:

In this well-written manuscript, Unitt and colleagues propose a new, hierarchical nomenclature system for the pathogen Neisseria gonorrhoeae. The proposed nomenclature addresses a longstanding problem in N. gonorrhoeae genomics, namely that the highly recombinant population complicates typing schemes based on only a few loci and that previous typing systems, even those based on the core genome, group strains at only one level of genomic divergence without a system for clustering sequence types together. In this work, the authors have revised the core genome MLST scheme for N. gonorrhoeae and devised life identification numbers (LIN) codes to describe the N. gonorrhoeae population structure.

Strengths:

The LIN codes proposed in this manuscript are congruent with previous typing methods for Neisseria gonorrhea, like cgMLST groups, Ng-STAR, and NG-MAST. Importantly, they improve upon many of these methods as the LIN codes are also congruent with the phylogeny and represent monophyletic lineages/sublineages.

The LIN code assignment has been implemented in PubMLST, allowing other researchers to assign LIN codes to new assemblies and put genomes of interest in context with global datasets.

Weaknesses:

The authors correctly highlight that cgMLST-based clusters can be fused due n to "intermediate isolates" generated through processes like horizontal gene transfer. However, the LIN codes proposed here are also based on single linkage clustering of cgMLST at multiple levels. It is unclear if future recombination or sequencing of previously unsampled diversity within N. gonorrhoeae merges together higher-level clusters, and if so, how this will impact the stability of the nomenclature.

The authors have defined higher resolution thresholds for the LIN code scheme. However, they do not investigate how these levels correspond to previously identified transmission clusters from genomic epidemiology studies. It would be useful for future users of the scheme to know the relevant LIN code thresholds for these investigations.

We thank the reviewer for their insightful comments. LIN codes do use multi-level single linkage clustering to define the cluster number of isolates. However, unlike previous applications of simple single linkage clustering such as N. gonorrhoeae core genome groups (Harrison et al., 2020), once assigned in LIN code, these cluster numbers are fixed within an unchanging barcode assigned to each isolate. Therefore, the nomenclature is stable, as the addition of new isolates cannot change previously established LIN codes.

Cluster stability was considered during the selection of allelic mismatch thresholds. By choosing thresholds based on natural breaks in population structure (Figure 3), applying clustering statistics such as the silhouette score, and by assessing where cluster stability has been maintained within the previous core genome groups nomenclature, we can have confidence that the thresholds which we have selected will form stable clusters. For example, with core genome groups there has been significant group fusion with clusters formed at a threshold of 400 allelic differences, while clustering at a threshold of 300 allelic differences has remained cohesive over time (supported by a high silhouette score) and so was selected as an important threshold in the gonococcal LIN code. LIN codes have now been applied to >27000 isolates in PubMLST, and the nomenclature has remained effective despite the continual addition of new isolates to this collection. The manuscript emphasises these points at line 96 and 346.

Work is in progress to explore what LIN code thresholds are generally associated with transmission chains. These will likely be the last 7 thresholds (25, 10, 7, 5, 3, 1, and 0 allelic differences), as previous work has suggested that isolates linked by transmission within one year are associated with <14 single nucleotide polymorphism differences (De Silva et al., 2016). The results of this analysis will be described in a future article, currently in preparation.

Harrison, O.B., et al. Neisseria gonorrhoeae Population Genomics: Use of the Gonococcal Core Genome to Improve Surveillance of Antimicrobial Resistance. The Journal of Infectious Diseases 2020.

De Silva, D., et al. Whole-genome sequencing to determine transmission of Neisseria gonorrhoeae: an observational study. The Lancet Infectious Diseases 2016;16(11):1295-1303.

Reviewer #3 (Recommendations for the authors):

(1) Data/code availability: While the genomic data and LIN codes are available in PubMLST and new isolates uploaded to PubMLST can be assigned a LIN code, it is also important to have software version numbers reported in the methods section and code/commands associated with the analysis in this manuscript (e.g. generation of core genome, statistical analysis, comparison with other typing methods) documented in a repository like GitHub.

Software version numbers have been added to the manuscript. Scripts used to run the software have been compiled and documented on protocols.io, DOI: dx.doi.org/10.17504/protocols.io.4r3l21beqg1y/v1

(2) Line 37: Missing "a" before "multi-drug resistant pathogen".

This has been corrected in the text.

(3) Line 60: Typo in geoBURST.

The text refers to a tool called goeBURST (global optimal eBURST) as described in Francisco, A.P. et al., 2009. DOI: 10.1186/1471-2105-10-152. Therefore, “geoBURST” would be incorrect.

(4) Line 136-138: It might be helpful to discuss how premature stop codons are treated in this scheme. Often in isolates with alleles containing early premature stop codons, annotation software like prokka will annotate two separate ORFs, which are then clustered with pangenome software like PIRATE. How does the cgMLST scheme proposed here treat premature stop codons? Are sequences truncated at the first stop codon, or is the nucleotide sequence for the entire gene used even if it is out of frame?

In PubMLST, alleles with premature stop codons are flagged, but otherwise annotated from the typical start to the usual stop codon, if still present. This also applies to frameshift mutations – a new unique allele will be annotated, but flagged as frameshift. In both cases, each new allele with a premature stop codon or frameshift will require human curator involvement to be assigned, to ensure rigorous allele assignment. As the Ng cgMLST v2 scheme prioritised readily auto-annotated genes, loci which are prone to internal stop codons or frameshifts with inconsistent start/end codons are excluded from the scheme. The text has been updated at line 128 to mention this.

(5) Line 213-214: What were the versions of software and parameters used for phylogenetic tree construction?

Version numbers have been added to the text between lines 214-219. Parameters have been included with the scripts documented at protocols.io DOI: dx.doi.org/10.17504/protocols.io.4r3l21beqg1y/v1

(6) Line 249: K. pneumoniae may also be a more diverse/older species than N. gonorrhoeae.

The text has been updated at line 252-253 to emphasize the difference in diversity. The age of N. gonorrhoeae as a species is a matter of scientific debate, and out of the scope of this paper to discuss.

(7) Line 278-279: Were some isolates unable to be typed, or have they just been added since the LIN code assignment occurred?

Some genomes cannot be assigned a LIN code due to poor genome quality. A minimum of 1405/1430 core genes must have an allele designated for a LIN code to be assigned. Genomes with large numbers of contigs may not meet this requirement. LIN code assignment is an ongoing process that occurs on a weekly basis in PubMLST, performed in batches starting at 23:00 (UK local time) on Sundays. The text has been updated to describe this at lines 196 and 282-283.

(8) Line 314-315: Was BAPS rerun on the dataset used in this manuscript, or is this based on previously assigned BAPS groups?

This was based on previously assigned BAPs groups, as described between lines 315-320.

(9) Line 421-423: Are there options for assigning LIN codes that do not require uploading genomes to PubMLST? I can imagine that there may be situations where researchers or public health institutions cannot share genomic data prior to publication.

Isolate data does not need to be shared to be uploaded and assigned a LIN code in PubMLST. data owners can create a private dataset within PubMLST viewable only to them, on which automated assignment will be performed. LIN code requires a central repository of genomes for new codes to be assigned in relation to. The text has been updated to emphasize this at line 197 and 427.

(10) Figure 6: How is this tree rooted? Additionally, do isolates that have unannotated LIN codes represent uncommon LIN codes or were those isolates not typed?

The tree has been left unrooted, as it is being used to visualise the relationships between the isolates rather than to explore ancestry. Detail on what LIN codes have been annotated can be found in the figure legend, which describes that the 21 most common LIN code lineages in this 1000 isolate dataset have been labelled. All 1000 isolates used in the tree had a LIN code assigned, but to ensure good legibility not all lineages were annotated on the tree. The legend has been updated to improve clarity.

meta title can it be updated to avoid search confusion

Last Mile Delivery Solutions | GFS

Amend the meta description to the condensed 150 characters

GFS simplifies last-mile delivery with smart tech, proactive support and multi-carrier choice, giving retailers seamless, scalable UK and international delivery.

We would add a section that relates directly to the technology as there is lots of search keywords about last mile software, solutions, platforms

We would advise a section after here that speaks directly to what the services are (this is very common on the top ranking pages)

It may mean we want to split this section into what you do and why choose you

This would be good if you could cite the customer name and company as text below the quote

We would move this below the benefits section

Can we highlights a couple of the blogs or resources related to this page to stay consistent with the rest of the website landing pages

The word count on this page is very low (under 400) - we would advise looking to double that word count

Internal links - very important for this page in particular * https://gfsdeliver.com/gfs-in-the-press/in-the-press-how-does-last-mile-delivery-affect-your-ecommerce-brand/ * https://gfsdeliver.com/blog/bringing-it-home-expert-tips-for-last-mile-delivery-in-the-homeware-industry/ * https://gfsdeliver.com/blog/final-mile-delivery-tracking-in-multi-carrier-shipping-to-handle-high-order-volumes/

eLife Assessment

This valuable study uses zebrafish as a model to reveal a role for the cell cycle protein kinase CDK2 as a negative regulator of type I interferon signaling. The evidence supporting the authors' claims is convincing, including both in vivo and in vitro investigative approaches that corroborate a role for CDK2 in regulating TBK1 degradation. In this latest version, the authors included data addressing a concern raised by the reviewer in the previous peer review round. This work will interest cell biologists, immunologists, and virologists.

Reviewer #1 (Public review):

Summary:

The authors set out to evaluate the regulation of interferon (IFN) gene expression in fish, using mainly zebrafish as a model system. Similar to more widely characterized mammalian systems, fish IFN is induced during viral infection through the action of the transcription factor IRF3 which is activated by phosphorylation by the kinase TBK1. It has been previously shown in many systems that TBK1 is subjected to both positive and negative regulation to control IFN production. In this work, the authors find that the cell cycle kinase CDK2 functions as a TBK1 inhibitor by decreasing its abundance through recruitment of the ubiquitinylation ligase, Dtx4, which has been similarly implicated in the regulation of mammalian TBK1. Experimental data are presented showing that CDK2 interacts with both TBK1 and Dtx4, leading to TBK1 K48 ubiqutinylation on K567 and its subsequent degradation by the proteasome.

Strengths:

The strengths of this manuscript are its novel demonstration of the involvement of CDK2 in a process in fish that is controlled by different factors in other vertebrates and its clear and supportive experimental data.

Weaknesses:

The weaknesses of the study include the following. 1) It remains unclear how CDK is regulated during viral infection and how it specifically recruits E3 ligase to TBK1. The authors find that its abundance increases during viral infection, an unusual finding given that CDK2 levels are often found to be stable. How this change in abundance might affect cell cycle control was not explored. 2) The implications and mechanisms for a relationship between the cell cycle and IFN production will be a fascinating topic for future studies. In particular, it will be critical to determine if CDK2 catalytic activity is required. An experiment with an inhibitor suggests that this novel action of CDK2 is kinase independent, but the lack of controls showing the efficacy of the inhibitor prevents a firm conclusion. It will also be critical to determine if there is a role for cyclins in this process or if there is competition for binding between TBK1 and cyclin and, if so, if this has an impact on the cell cycle. Likewise, an impact of CDK2 induction by virus infection on normal cell cycling will be important to investigate.

Reviewer #2 (Public review):

Summary:

In this paper, the authors describe a novel function involving the cell cycle protein kinase CDK2, which binds to TBK1 (an essential component of the innate immune response) leading to its degradation in a ubiquitin/proteasome-dependent manner. Moreover, the E3 ubiquitin ligase, Dtx4, is implicated in the process by which CDK2 increases the K48-linked ubiquitination of TBK1. This paper presents intriguing findings on the function of CDK2 in lower vertebrates, particularly its regulation of IFN expression and antiviral immunity.

Strengths:

(1) The research employs a variety of experimental approaches to address a single question. The data are largely convincing and appear to be well executed.

(2) The evidence is strong and includes a combination of in vivo and in vitro experiments, including knockout models, protein interaction studies, and ubiquitination analyses.

(3) This study significantly impacts the field of immunology and virology, particularly concerning the antiviral mechanisms in lower vertebrates. The findings provide new insights into the regulation of IFN expression and the broader role of CDK2 in immune responses. The methods and data presented in this paper are highly valuable for the scientific community, offering new avenues for research into antiviral strategies and the development of therapeutic interventions targeting CDK2 and its associated pathways.

Author response:

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

Reviewer #1 (Public Review):

The weaknesses of the study include the following.

(1)  It remains unclear how CDK is regulated during viral infection and how it specifically recruits E3 ligase to TBK1.

We would like to express our gratitude to the reviewer for highlighting this significant issue. The present study demonstrates that CDK2 expression is significantly upregulated upon SVCV infection in multiple fish tissues and cell lines (see Fig. 1C-F), thus suggesting that viral infection triggers CDK2 induction. However, the precise upstream signaling pathways that regulate CDK2 during viral infection remain to be fully elucidated. It is hypothesized that viral RNA sensors may activate transcription factors that bind to the cdk2 promoter; however, further investigation is required to confirm this. We have added a sentence in the Discussion (Lines 409-412) acknowledging this as a limitation and a focus for future work, suggesting potential involvement of viral sensor pathways.

With regard to the mechanism by which CDK2 recruits the E3 ligase Dtx4 to TBK1, evidence is provided that CDK2 directly interacts with both TBK1 (via its kinase domain) and Dtx4 (see Fig. 4F-I, 6A-C). Furthermore, evidence is presented demonstrating that CDK2 enhances the interaction between Dtx4 and TBK1 (Fig. 6D), thus suggesting that CDK2 functions as a scaffold protein to facilitate the formation of a ternary complex. However, further study is required to ascertain the precise structural basis of this interaction, including whether CDK2's kinase activity is required. We have added a note in the Discussion (Lines 417-421) acknowledging this limitation and proposing future structural studies to elucidate the precise binding interfaces.

(2) The implications and mechanisms for a relationship between the cell cycle and IFN production will be a fascinating topic for future studies.

We concur with the reviewer's assertion that the interplay between cell cycle progression and innate immunity constitutes a promising and under-explored research domain. Whilst the present study concentrates on the function of CDK2 in antiviral signaling, independent of its cell cycle functions, it is acknowledged that CDK2's activity is cell cycle-dependent. It is hypothesized that CDK2 may function as a molecular link between cell proliferation and immune responses, particularly in light of the observation that viral infections frequently modify host cell cycle progression. In the Discussion (lines 387-391), we now briefly propose a model wherein CDK2 activity during the S phase may suppress TBK1-mediated IFN production to allow viral replication, while CDK2 inhibition (e.g., in G1) may enhance IFN responses. This hypothesis will be the subject of our future work, including cell cycle synchronization experiments and time-course analyses of CDK2 activity and IFN output during infection.

Reviewer #1 (Recommendations for the authors):

(1) A control showing that the CDK2 inhibitor blocked kinase activity would be appropriate.

We thank the reviewer for this suggestion. We have performed experiments using the CDK2-specific inhibitor SNS-032. As shown in the Author response image 1, the treatment of EPC cells with SNS-032 (2 µM) still affect TBK1 expression. However, the selection of this inhibitor was based on literature references (ref. 1 and 2), and it is uncertain whether it directly inhibits the kinase activity of CDK2. However, our result demonstrated that CDK2 retains the capacity to degrade TBK1 even in the absence of its kinase domain (Fig. 6I), yielding outcomes that are consistent with this inhibitor.

Author response image 1.

References:

(1) Mechanism of action of SNS-032, a novel cyclin-dependent kinase inhibitor, in chronic lymphocytic leukemia. Blood. 2009 May 7;113(19):4637-45.

(2) SNS-032 is a potent and selective CDK 2, 7 and 9 inhibitor that drives target modulation in patient samples. Cancer Chemother Pharmacol. 2009 Sep;64(4):723-32.

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 valuable to the field and the strength of evidence to support the findings is solid.

Reviewer #1 (Public review):

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.

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.

Author response:

The following is the authors’ response to the previous reviews

Reviewers 1:

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.

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.

We thank the reviewer for this insightful and critical comment regarding the quality control of our analytical data and the assessment of biological variability. We agree that this is essential for validating the reliability of our findings. We have now provided the requested CV data and clarified this point in the revised manuscript as detailed below.

"This dual-replicate strategy enabled a comprehensive evaluation of both biological heterogeneity and assay precision, and the coefficient of variation for samples were below 16%." Please see the Materials and Methods (Page 16, lines 360-362, and Author response table 1).

Author response table 1.

Comparative analysis of serum biomarker concentrations in acute and convalescent phase cohorts.

Reviewers 2:

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.

The verb "accelerated" in the title implies that the glycosylation state of IgG was a direct driver of recovery, rather than something that correlated with recovery. Thus, a more neutral word/phrase would be ideal.

We sincerely thank the reviewer for this insightful suggestion. We agree that the use of "accelerated" might overstate the potential role of IgG glycosylation, which has not been clearly clarified by our current findings. As reported in results (particularly in Figure 2), partial glycosylation exhibits statistically significant variations between seropositive and seronegative statuses, before and after seroconversion, and across different HTNV- NP specific antibody titers. Therefore, we have replaced "accelerated" with "contribute to" in the Title: "Glycosylated IgG antibodies contribute to the recovery of haemorrhagic fever with renal syndrome patients".

eLife Assessment

This study presents a useful overview of the taxonomic composition of the microbiome associated with Dactylorhiza traunsteineri, a widely distributed orchid species in Central Europe. The evidence supporting the claims of the authors is incomplete, especially when it comes to the (secondary) metabolic pathways found in the metagenome assembled genomes, and requires more substantial analysis to be able to claim that these pathways play a key role in microbiome-orchid symbiosis.

Reviewer #1 (Public review):

Summary:

The microbiota of Dactylorhiza traunsteineri, an endangered marsh orchid, forms complex root associations that support plant health. Using 16S rRNA sequencing, we identified dominant bacterial phyla in its rhizosphere, including Proteobacteria, Actinobacteria, and Bacteroidota. Deep shotgun metagenomics revealed high-quality MAGs with rich metabolic and biosynthetic potential. This study provides key insights into root-associated bacteria and highlights the rhizosphere as a promising source of bioactive compounds, supporting both microbial ecology research and orchid conservation.

Strengths:

The manuscript presents an investigation of the bacterial communities in the rhizosphere of D. traunsteineri using advanced metagenomic approaches. The topic is relevant, and the techniques are up-to-date; however, the study has several critical weaknesses.

Weaknesses:

(1) Title: The current title is misleading. Given that fungi are the primary symbionts in orchids and were not analyzed in this study (nor were they included among other microbial groups), the use of the term "microbiome" is not appropriate. I recommend replacing it with "bacteriome" to better reflect the scope of the work.

(2) Line 124: The phrase "D. traunsteineri individuals were isolated" seems misleading. A more accurate description would be "individuals were collected", as also mentioned in line 128.

(3) Experimental design: The major limitation of this study lies in its experimental design. The number of plant individuals and soil samples analyzed is unclear, making it difficult to assess the statistical robustness of the findings. It is also not well explained why the orchids were collected two years before the rhizosphere soil samples. Was the rhizosphere soil collected from the same site and from remnants of the previously sampled individuals in 2018? This temporal gap raises serious concerns about the validity of the biological associations being inferred.

(4) Low sample size: In lines 249-251 (Results section), the authors mention that only one plant individual was used for identifying rhizosphere bacteria. This is insufficient to produce scientifically robust or generalizable conclusions.

(5) Contextual limitations: Numerous studies have shown that plant-microbe interactions are influenced by external biotic and abiotic factors, as well as by plant age and population structure. These elements are not discussed or controlled for in the manuscript. Furthermore, the ecological and environmental conditions of the site where the plants and soil were collected are poorly described. The number of biological and technical replicates is also not clearly stated.

(6) Terminology: Throughout the manuscript, the authors refer to the "microbiome," though only bacterial communities were analyzed. This terminology is inaccurate and should be corrected consistently.

Considering the issues addressed, particularly regarding experimental design and data interpretation, significant improvements to the study are needed.

Reviewer #2 (Public review):

Summary:

The authors aim to provide an overview of the D. traunsteineri rhizosphere microbiome on a taxonomic and functional level, through 16S rRNA amplicon analysis and shotgun metagenome analysis. The amplicon sequencing shows that the major phyla present in the microbiome belong to phyla with members previously found to be enriched in rhizospheres and bulk soils. Their shotgun metagenome analysis focused on producing metagenome assembled genomes (MAGs), of which one satisfies the MIMAG quality criteria for high-quality MAGs and three those for medium-quality MAGs. These MAGs were subjected to functional annotations focusing on metabolic pathway enrichment and secondary metabolic pathway biosynthetic gene cluster analysis. They find 1741 BGCs of various categories in the MAGs that were analyzed, with the high-quality MAG being claimed to contain 181 SM BGCs. The authors provide a useful, albeit superficial, overview of the taxonomic composition of the microbiome, and their dataset can be used for further analysis.

The conclusions of this paper are not well-supported by the data, as the paper only superficially discusses the results, and the functional interpretation based on taxonomic evidence or generic functional annotations does not allow drawing any conclusions on the functional roles of the orchid microbiota.

Weaknesses:

The authors only used one individual plant to take samples. This makes it hard to generalize about the natural orchid microbiome.

The authors use both 16S amplicon sequencing and shotgun metagenomics to analyse the microbiome. However, the authors barely discuss the similarities and differences between the results of these two methods, even though comparing these results may be able to provide further insights into the conclusions of the authors. For example, the relative abundance of the ASVs from the amplicon analysis is not linked to the relative abundances of the MAGs.

Furthermore, the authors discuss that phyla present in the orchid microbiome are also found in other microbiomes and are linked to important ecological functions. However, their results reach further than the phylum level, and a discussion of genera or even species is lacking. The phyla that were found have very large within-phylum functional variability, and reliable functional conclusions cannot be drawn based on taxonomic assignment at this level, or even the genus level (Yan et al. 2017).

Additionally, although the authors mention their techniques used, their method section is sometimes not clear about how samples or replicates were defined. There are also inconsistencies between the methods and the results section, for example, regarding the prediction of secondary metabolite biosynthetic gene clusters (BGCs).

The BGC prediction was done with several tools, and the unusually high number of found BGCs (181 in their high-quality MAG) is likely due to false positives or fragmented BGCs. The numbers are much higher than any numbers ever reported in literature supported by functional evidence (Amos et al, 2017), even in a prolific genus like Streptomyces (Belknap et al., 2020). This caveat is not discussed by the authors.

The authors have generated one high-quality MAG and three medium-quality MAGs. In the discussion, they present all four of these as high-quality, which could be misleading. The authors discuss what was found in the literature about the role of the bacterial genera/phyla linked to these MAGs in plant rhizospheres, but they do not sufficiently link their own analysis results (metabolic pathway enrichment and biosynthetic gene cluster prediction) to this discussion. The results of these analyses are only presented in tables without further explanation in either the results section or the discussion, even though there may be interesting findings. For example, the authors only discuss the class of the BGCs that were found, but don't search for experimentally verified homologs in databases, which could shed more light on the possible functional roles of BGCs in this microbiome.

In the conclusions, the authors state: "These analyses uncovered potential metabolic capabilities and biosynthetic potentials that are integral to the rhizosphere's ecological dynamics." I don't see any support for this. Mentioning that certain classes of BGCs are present is not enough to make this claim, in my opinion. Any BGC is likely important for the ecological niche the bacteria live in. The fact that rhizosphere bacteria harbour BGCs is not surprising, and it doesn't tell us more than is already known.

References:

Belknap, Kaitlyn C., et al. "Genome mining of biosynthetic and chemotherapeutic gene clusters in Streptomyces bacteria." Scientific reports 10.1 (2020): 2003

Amos GCA, Awakawa T, Tuttle RN, Letzel AC, Kim MC, Kudo Y, Fenical W, Moore BS, Jensen PR. Comparative transcriptomics as a guide to natural product discovery and biosynthetic gene cluster functionality. Proc Natl Acad Sci U S A. 2017 Dec 26;114(52):E11121-E11130.

References:

Belknap, Kaitlyn C., et al. "Genome mining of biosynthetic and chemotherapeutic gene clusters in Streptomyces bacteria." Scientific reports 10.1 (2020): 2003

Amos GCA, Awakawa T, Tuttle RN, Letzel AC, Kim MC, Kudo Y, Fenical W, Moore BS, Jensen PR. Comparative transcriptomics as a guide to natural product discovery and biosynthetic gene cluster functionality. Proc Natl Acad Sci U S A. 2017 Dec 26;114(52):E11121-E11130.

Yan Yan, Eiko E Kuramae, Mattias de Hollander, Peter G L Klinkhamer, Johannes A van Veen, Functional traits dominate the diversity-related selection of bacterial communities in the rhizosphere, The ISME Journal, Volume 11, Issue 1, January 2017, Pages 56-66

Author response:

Reviewer #1 (Public review):

The microbiota of Dactylorhiza traunsteineri, an endangered marsh orchid, forms complex root associations that support plant health. Using 16S rRNA sequencing, we identified dominant bacterial phyla in its rhizosphere, including Proteobacteria, Actinobacteria, and Bacteroidota. Deep shotgun metagenomics revealed high-quality MAGs with rich metabolic and biosynthetic potential. This study provides key insights into root-associated bacteria and highlights the rhizosphere as a promising source of bioactive compounds, supporting both microbial ecology research and orchid conservation.  

The manuscript presents an investigation of the bacterial communities in the rhizosphere of D. traunsteineri using advanced metagenomic approaches. The topic is relevant, and the techniques are up-to-date; however, the study has several critical weaknesses.  

We thank the reviewer for their careful reading of our manuscript and for the constructive comments. We will revise the manuscript substantially. Our responses to the specific points are below:

(1) Title: The current title is misleading. Given that fungi are the primary symbionts in orchids and were not analyzed in this study (nor were they included among other microbial groups), the use of the term "microbiome" is not appropriate. I recommend replacing it with "bacteriome" to better reflect the scope of the work.

In the revised manuscript, we will expand the Results (shotgun sequencing) and Discussion to also include fungal taxa. With these additions, the use of the term microbiome will accurately reflect the inclusion of both bacterial and fungal components.

(2) Line 124: The phrase "D. traunsteineri individuals were isolated" seems misleading. A more accurate description would be "individuals were collected", as also mentioned in line 128.

This ambiguity will be corrected in the revised manuscript.

(3) Experimental design: The major limitation of this study lies in its experimental design. The number of plant individuals and soil samples analyzed is unclear, making it difficult to assess the statistical robustness of the findings. It is also not well explained why the orchids were collected two years before the rhizosphere soil samples. Was the rhizosphere soil collected from the same site and from remnants of the previously sampled individuals in 2018? This temporal gap raises serious concerns about the validity of the biological associations being inferred.

In the revised manuscript, we will explicitly state the number of individuals and soil samples included in the study, and we will more clearly describe the sequence of sampling events. We will also add a dedicated statement in the Discussion addressing the temporal gap between plant sampling and rhizosphere soil collection, acknowledging that this is a limitation of the study.

(4) Low sample size: In lines 249-251 (Results section), the authors mention that only one plant individual was used for identifying rhizosphere bacteria. This is insufficient to produce scientifically robust or generalizable conclusions.

In the revised manuscript, we will clearly state that only one rhizosphere sample was available and will frame the study as exploratory in nature. We will explicitly acknowledge this limitation in both the Methods and Discussion, and we will temper our conclusions accordingly.

(5) Contextual limitations: Numerous studies have shown that plant-microbe interactions are influenced by external biotic and abiotic factors, as well as by plant age and population structure. These elements are not discussed or controlled for in the manuscript. Furthermore, the ecological and environmental conditions of the site where the plants and soil were collected are poorly described. The number of biological and technical replicates is also not clearly stated.

In the revised manuscript, we will expand the description of the collection site and environmental conditions to the extent supported by our records. We will also clearly state the number of biological and technical replicates used for each analysis. In the Discussion, we will explicitly acknowledge that plant age, environmental variables, and other biotic/abiotic factors may influence plant–microbe interactions and were not directly assessed in this study.

(6) Terminology: Throughout the manuscript, the authors refer to the "microbiome," though only bacterial communities were analyzed. This terminology is inaccurate and should be corrected consistently.

As noted in our response to point (1), we will revise terminology throughout the manuscript to ensure consistency and to accurately reflect the expanded bacterial and fungal coverage in the revised version.

Reviewer #2 (Public review):

The authors aim to provide an overview of the D. traunsteineri rhizosphere microbiome on a taxonomic and functional level, through 16S rRNA amplicon analysis and shotgun metagenome analysis. The amplicon sequencing shows that the major phyla present in the microbiome belong to phyla with members previously found to be enriched in rhizospheres and bulk soils. Their shotgun metagenome analysis focused on producing metagenome assembled genomes (MAGs), of which one satisfies the MIMAG quality criteria for high-quality MAGs and three those for medium-quality MAGs. These MAGs were subjected to functional annotations focusing on metabolic pathway enrichment and secondary metabolic pathway biosynthetic gene cluster analysis. They find 1741 BGCs of various categories in the MAGs that were analyzed, with the high-quality MAG being claimed to contain 181 SM BGCs. The authors provide a useful, albeit superficial, overview of the taxonomic composition of the microbiome, and their dataset can be used for further analysis.

The conclusions of this paper are not well-supported by the data, as the paper only superficially discusses the results, and the functional interpretation based on taxonomic evidence or generic functional annotations does not allow drawing any conclusions on the functional roles of the orchid microbiota.  

We thank the reviewer for their thoughtful and constructive assessment of our manuscript. The comments have been very helpful in identifying areas where the clarity, structure, and interpretation of our work can be improved. Our responses to the specific points are below:

(1) The authors only used one individual plant to take samples. This makes it hard to generalize about the natural orchid microbiome.

We agree with the reviewer that the limited number of plant individuals restricts the generality of the conclusions. In the revised manuscript, we will clearly state that only one rhizosphere sample was available for analysis and will frame the study as exploratory. We will also explicitly acknowledge this limitation in the Discussion and ensure that our interpretations and conclusions remain appropriately cautious.

(2) The authors use both 16S amplicon sequencing and shotgun metagenomics to analyse the microbiome. However, the authors barely discuss the similarities and differences between the results of these two methods, even though comparing these results may be able to provide further insights into the conclusions of the authors. For example, the relative abundance of the ASVs from the amplicon analysis is not linked to the relative abundances of the MAGs.

In the revised manuscript, we will expand the Results and Discussion to include a clearer comparison between the taxonomic profiles derived from 16S amplicon sequencing and those obtained from shotgun metagenomic binning.

(3) Furthermore, the authors discuss that phyla present in the orchid microbiome are also found in other microbiomes and are linked to important ecological functions. However, their results reach further than the phylum level, and a discussion of genera or even species is lacking. The phyla that were found have very large within-phylum functional variability, and reliable functional conclusions cannot be drawn based on taxonomic assignment at this level, or even the genus level (Yan et al. 2017).

In the revised manuscript, we will incorporate taxonomic discussion at finer resolution where reliable assignments are available. We will also revise the Discussion to avoid overinterpreting phylum-level taxonomy in terms of ecological function.

(4) Additionally, although the authors mention their techniques used, their method section is sometimes not clear about how samples or replicates were defined. There are also inconsistencies between the methods and the results section, for example, regarding the prediction of secondary metabolite biosynthetic gene clusters (BGCs).

In the revised Methods section, we will clearly define the number and type of samples included in each analysis, specify the number of replicates and how they were handled, and provide a clearer description of the biosynthetic gene cluster (BGC) prediction workflow, including the tools used and how results were interpreted. 

(5) The BGC prediction was done with several tools, and the unusually high number of found BGCs (181 in their high-quality MAG) is likely due to false positives or fragmented BGCs. The numbers are much higher than any numbers ever reported in literature supported by functional evidence (Amos et al, 2017), even in a prolific genus like Streptomyces (Belknap et al., 2020). This caveat is not discussed by the authors.

We thank the reviewer for this important point. Our original intention was to present the BGC predictions as a resource for future exploration, which is why multiple tools were used. However, we understand how this approach may lead to confusion, particularly regarding the confidence level of the predicted clusters and the potential inflation of counts due to assembly fragmentation or tool sensitivity. In the revised manuscript, we will thoroughly revise this section to clearly distinguish highconfidence predictions from more exploratory findings. We will focus on results supported by stronger evidence, explicitly qualify lower-confidence predictions as putative, and temper any functional interpretations accordingly.

(6) The authors have generated one high-quality MAG and three medium-quality MAGs. In the discussion, they present all four of these as high-quality, which could be misleading. The authors discuss what was found in the literature about the role of the bacterial genera/phyla linked to these MAGs in plant rhizospheres, but they do not sufficiently link their own analysis results (metabolic pathway enrichment and biosynthetic gene cluster prediction) to this discussion. The results of these analyses are only presented in tables without further explanation in either the results section or the discussion, even though there may be interesting findings. For example, the authors only discuss the class of the BGCs that were found, but don't search for experimentally verified homologs in databases, which could shed more light on the possible functional roles of BGCs in this microbiome.

In the revised manuscript, we will ensure that MAG quality is described accurately and consistently throughout, distinguishing clearly between high-quality and medium-quality bins according to accepted standards.

(7) In the conclusions, the authors state: "These analyses uncovered potential metabolic capabilities and biosynthetic potentials that are integral to the rhizosphere's ecological dynamics." I don't see any support for this. Mentioning that certain classes of BGCs are present is not enough to make this claim, in my opinion. Any BGC is likely important for the ecological niche the bacteria live in. The fact that rhizosphere bacteria harbour BGCs is not surprising, and it doesn't tell us more than is already known.

In the revised manuscript, we will rewrite the conclusion to reflect a more cautious interpretation, focusing on the potential metabolic and biosynthetic capabilities suggested by the data without asserting ecological roles that cannot be directly supported. These capabilities will be presented as hypotheses for future investigation rather than established ecological features.

eLife Assessment

This manuscript makes a valuable contribution to the concept of fragility of meta-analyses via the so-called 'ellipse of insignificance for meta-analyses' (EOIMETA). The strength of evidence is solid, supported primarily by an example of the fragility of meta-analyses in the association between Vitamin D supplementation and cancer mortality, but the approach could be applied in other meta-analytic contexts. The significance of the work could be enhanced with a more thorough assessment of the impact of between-study heterogeneity, additional case studies, and improved contextualization of the proposed approach in relation to other methods.

Reviewer #1 (Public review):

Summary:

This manuscript addresses an important methodological issue - the fragility of meta-analytic findings - by extending fragility concepts beyond trial-level analysis. The proposed EOIMETA framework provides a generalizable and analytically tractable approach that complements existing methods such as the traditional Fragility Index and Atal et al.'s algorithm. The findings are significant in showing that even large meta-analyses can be highly fragile, with results overturned by very small numbers of event recodings or additions. The evidence is clearly presented, supported by applications to vitamin D supplementation trials, and contributes meaningfully to ongoing debates about the robustness of meta-analytic evidence. Overall, the strength of evidence is moderate to strong, though some clarifications would further enhance interpretability.

Strengths:

(1) The manuscript tackles a highly relevant methodological question on the robustness of meta-analytic evidence.

(2) EOIMETA represents an innovative extension of fragility concepts from single trials to meta-analyses.

(3) The applications are clearly presented and highlight the potential importance of fragility considerations for evidence synthesis.

Weaknesses:

(1) The rationale and mathematical details behind the proposed EOI and ROAR methods are insufficiently explained. Readers are asked to rely on external sources (Grimes, 2022; 2024b) without adequate exposition here. At a minimum, the definitions, intuition, and key formulas should be summarized in the manuscript to ensure comprehensibility.

(2) EOIMETA is described as being applicable when heterogeneity is low, but guidance is missing on how to interpret results when heterogeneity is high (e.g., large I²). Clarification in the Results/Discussion is needed, and ideally, a simulation or illustrative example could be added.

(3) The manuscript would benefit from side-by-side comparisons between the traditional FI at the trial level and EOIMETA at the meta-analytic level. This would contextualize the proposed approach and underscore the added value of EOIMETA.

(4) Scope of FI: The statement that FI applies only to binary outcomes is inaccurate. While originally developed for dichotomous endpoints, extensions exist (e.g., Continuous Fragility Index, CFI). The manuscript should clarify that EOIMETA focuses on binary outcomes, but FI, as a concept, has been generalized.

Reviewer #2 (Public review):

Summary:

The study expands existing analytical tools originally developed for randomized controlled trials with dichotomous outcomes to assess the potential impact of missing data, adapting them for meta-analytical contexts. These tools evaluate how missing data may influence meta-analyses where p-value distributions cluster around significance thresholds, often leading to conflicting meta-analyses addressing the same research question. The approach quantifies the number of recodings (adding events to the experimental group and/or removing events from the control group) required for a meta-analysis to lose or gain statistical significance. The author developed an R package to perform fragility and redaction analyses and to compare these methods with a previously established approach by Atal et al. (2019), also integrated into the package. Overall, the study provides valuable insights by applying existing analytical tools from randomized controlled trials to meta-analytical contexts.

Strengths:

The author's results support his claims. Analyzing the fragility of a given meta-analysis could be a valuable approach for identifying early signs of fragility within a specific topic or body of evidence. If fragility is detected alongside results that hover around the significance threshold, adjusting the significance cutoff as a function of sample size should be considered before making any binary decision regarding statistical significance for that body of evidence. Although the primary goal of meta-analysis is effect estimation, conclusions often still rely on threshold-based interpretations, which is understandable. In some of the examples presented by Atal et al. (2019), the event recoding required to shift a meta-analysis from significant to non-significant (or vice versa) produced only minimal changes in the effect size estimation. Therefore, in bodies of evidence where meta-analyses are fragile or where results cluster near the null, it may be appropriate to adjust the cutoff. Conducting such analyses-identifying fragility early and adapting thresholds accordingly-could help flag fragile bodies of evidence and prevent future conflicting meta-analyses on the same question, thereby reducing research waste and improving reproducibility.

Weaknesses:

It would be valuable to include additional bodies of conflicting literature in which meta-analyses have demonstrated fragility. This would allow for a more thorough assessment of the consistency of these analytical tools, their differences, and whether this particular body of literature favored one methodology over another. The method proposed by Atal et al. was applied to numerous meta-analyses and demonstrated consistent performance. I believe there is room for improvement, as both the EOI and ROAR appear to be very promising tools for identifying fragility in meta-analytical contexts.

I believe the manuscript should be improved in terms of reporting, with clearer statements of the study's and methods' limitations, and by incorporating additional bodies of evidence to strengthen its claims.

Reviewer #3 (Public review):

Summary and strengths:

In this manuscript, Grimes presents an extension of the Ellipse of Insignificant (EOI) and Region of Attainable Redaction (ROAR) metrics to the meta-analysis setting as metrics for fragility and robustness evaluation of meta-analysis. The author applies these metrics to three meta-analyses of Vitamin D and cancer mortality, finding substantial fragility in their conclusions. Overall, I think extension/adaptation is a conceptually valuable addition to meta-analysis evaluation, and the manuscript is generally well-written.

Specific comments:

(1) The manuscript would benefit from a clearer explanation of in what sense EOIMETA is generalizable. The author mentions this several times, but without a clear explanation of what they mean here.

(2) The authors mentioned the proposed tools assume low between-study heterogeneity. Could the author illustrate mathematically in the paper how the between-study heterogeneity would influence the proposed measures? Moreover, the between-study heterogeneity is high in Zhang et al's 2022 study. It would be a good place to comment on the influence of such high heterogeneity on the results, and specifying a practical heterogeneity cutoff would better guide future users.

(3) I think clarifying the concepts of "small effect", "fragile result", and "unreliable result" would be helpful for preventing misinterpretation by future users. I am concerned that the audience may be confusing these concepts. A small effect may be related to a fragile meta-analysis result. A fragile meta-analysis doesn't necessarily mean wrong/untrustworthy results. A fragile but precise estimate can still reflect a true effect, but whether that size of true effect is clinically meaningful is another question. Clarifying the effect magnitude, fragility, and reliability in the discussion would be helpful.

eLife Assessment

In the gram-positive model organism Bacillus subtilis, the membrane associated ParA family member MinD, concentrates the division inhibitor MinC at cell poles where it prevents aberrant division events. This important study presents compelling data suggesting that polar localization of MinCD is largely due to differences in diffusion rates between monomeric and dimeric MinD. This finding is exciting as it negates the necessity for a third, localization determinant, in this system as has been proposed by previous investigations.

Reviewer #1 (Public review):

The authors used fluorescence microscopy, image analysis, and mathematical modeling to study the effects of membrane affinity and diffusion rates of MinD monomer and dimer states on MinD gradient formation in B. subtilis. To test these effects, the authors experimentally examined MinD mutants that lock the protein in specific states, including Apo monomer (K16A), ATP-bound monomer (G12V) and ATP-bound dimer (D40A, hydrolysis defective), and compared to wild-type MinD. Overall, the experimental results support the conclusions that reversible membrane binding of MinD is critical for the formation of the MinD gradient, but the binding affinities between monomers and dimers are similar.

The modeling part is a new attempt to use the Monte Carlo method to test the conditions for the formation of the MinD gradient in B. subtilis. The modeling results provide good support for the observations and find that the MinD gradient is sensitive to different diffusion rates between monomers and dimers. This simulation is based on several assumptions and predictions, which raises new questions that need to be addressed experimentally in the future.

Reviewer #3 (Public review):

This important study by Bohorquez et al examines the determinants necessary for concentrating the spatial modulator of cell division, MinD, at the future site of division and the cell poles. Proper localization of MinD is necessary to bring the division inhibitor, MinC, in proximity to the cell membrane and cell poles where it prevents aberrant assembly of the division machinery. In contrast to E. coli, in which MinD oscillates from pole-to-pole courtesy of a third protein MinE, how MinD localization is achieved in B. subtilis-which does not encode a MinE analog-has remained largely a mystery. The authors present compelling data indicating that MinD dimerization is dispensable for membrane localization but required for concentration at the cell poles. Dimerization is also important for interactions between MinD and MinC, leading to the formation of large protein complexes. Computational modeling, specifically a Monte Carlo simulation, supports a model in which differences in diffusion rates between MinD monomers and dimers lead to concentration of MinD at cell poles. Once there, interaction with MinC increases the size of the complex, further reinforcing diffusion differences. Notably, interactions with MinJ-which has previously been implicated in MinCD localization, are dispensable for concentrating MinD at cell poles although MinJ may help stabilize the MinCD complex at those locations.

Comments on revisions:

I believe the authors put respectable effort into revisions and addressing reviewer comments, particularly those that focused on the strengths of the original conclusions. The language in the current version of the manuscript is more precise and the overall product is stronger.

Author response:

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

Reviewer #1 (Public review):

The authors used fluorescence microscopy, image analysis, and mathematical modeling to study the effects of membrane affinity and diffusion rates of MinD monomer and dimer states on MinD gradient formation in B. subtilis. To test these effects, the authors experimentally examined MinD mutants that lock the protein in specific states, including Apo monomer (K16A), ATP-bound monomer (G12V), and ATPbound dimer (D40A, hydrolysis defective), and compared to wild-type MinD. Overall, the experimental results support the conclusion that reversible membrane binding of MinD is critical for the formation of the MinD gradient, but that the binding affinities between monomers and dimers are similar.  

The modeling part is a new attempt to use the Monte Carlo method to test the conditions for the formation of the MinD gradient in B. subtilis. The modeling results provide good support for the observations and find that the MinD gradient is sensitive to different diffusion rates between monomers and dimers. This simulation is based on several assumptions and predictions, which raises new questions that need to be addressed experimentally in the future. However, the current story is sufficient without testing these assumptions or predictions.

Reviewer #2 (Public review): 

Summary:  

Bohorquez et al. investigate the molecular determinants of intracellular gradient formation in the B. subtilis Min system. To this end, they generate B. subtilis strains that express MinD mutants that are locked in the monomeric or dimeric states, and also MinD mutants with amphipathic helices of varying membrane affinity. They then assess the mutants' ability to bind to the membrane and form gradients using fluorescence microscopy in different genetic backgrounds. They find that, unlike in the E. coli Min system, the monomeric form of MinD is already capable of membrane binding. They also show that MinJ is not required for MinD membrane binding and only interacts with the dimeric form of MinD. Using kinetic

Monte Carlo simulations, the authors then test different models for gradient formation, and find that a MinD gradient along the cell axis is only formed when the polarly localized protein MinJ stimulates dimerization of MinD, and when the diffusion rate of monomeric and dimeric MinD differs. They also show that differences in the membrane affinity of MinD monomers and dimers are not required for gradient formation.  

Strengths:  

The paper offers a comprehensive collection of the subcellular localization and gradient formation of various MinD mutants in different genetic backgrounds. In particular, the comparison of the localization of these mutants in a delta MinC and MinJ background offers valuable additional insights. For example, they find that only dimeric MinD can interact with MinJ. They also provide evidence that MinD locked in a dimer state may co-polymerize with MinC, resulting in a speckled appearance.  

The authors introduce and verify a useful measure of membrane affinity in vivo.  

The modulation of the membrane affinity by using distinct amphipathic helices highlights the robustness of the B. subtilis MinD system, which can form gradients even when the membrane affinity of MinD is increased or decreased.  

Weaknesses:  

The main claim of the paper, that differences in the membrane affinity between MinD monomers and dimers are not required for gradient formation, does not seem to be supported by the data. The only measure of membrane affinity presented is extracted from the transverse fluorescence intensity profile of cells expressing the mGFP-tagged MinD mutants. The authors measure the valley-to-peak ratio of the profile, which is lower than 1 for proteins binding to the membrane and higher than 1 for cytosolic proteins. To verify this measure of membrane affinity, they use a membrane dye and a soluble GFP, which results in values of ~0.75 and ~1.25, respectively. They then show that all MinD mutants have a value - roughly in the range of 0.8-0.9 - and they use this to claim that there are no differences in membrane affinity between monomeric and dimeric versions.  

While this way to measure membrane affinity is useful to distinguish between binders and non-binders, it is unclear how sensitive this assay is, and whether it can resolve more subtle differences in membrane affinity, beyond the classification into binders and non-binders. A dimer with two amphipathic helices should have a higher membrane affinity than a monomer with only one such copy. Thus, the data does not seem to support the claim that "the different monomeric mutants have the same membrane affinity as the wildtype MinD". The data only supports the claim that B. subtilis MinD monomers already have a measurable membrane affinity, which is indeed a difference from the E. coli Min system.  

While their data does show that a stark difference between monomer and dimer membrane affinity may not be required for gradient formation in the B. subtilis case, it is also not prevented if the monomer is unable to bind to the membrane. They show this by replacing the native MinD amphipathic helix with the weak amphipathic helix NS4AB-AH. According to their membrane affinity assay, NS4AB-AH does not bind to the membrane as a monomer (Figure 4D), but when this helix is fused to MinD, MinD is still capable of forming a gradient (albeit a weaker one). Since the authors make a direct comparison to the E. coli MinDE systems, they could have used the E. coli MinD MTS instead or in addition to the NS4AB-AH amphipathic helix. The reviewer suspects that a fusion of the E. coli MinD MTS to B. subtilis MinD may also support gradient formation.  

The paper contains insufficient data to support the many claims about cell filamentation and minicell formation. In many cases, statements like "did not result in cell filamentation" or "restored cell division" are only supported by a single fluorescence image instead of a quantitative analysis of cell length distribution and minicell frequency, as the one reported for a subset of the data in Figure 5.  

The paper would also benefit from a quantitative measure of gradient formation of the distinct MinD mutants, instead of relying on individual fluorescent intensity profiles.  

The authors compare their experimental results with the oscillating E. coli MinDE system and use it to define some of the rules of their Monte Carlo simulation. However, the description of the E. coli Min system is sometimes misleading or based on outdated findings.

The Monte Carlo simulation of the gradient formation in B. subtilis could benefit from a more comprehensive approach:

(1) While most of the initial rules underlying the simulation are well justified, the authors do not implement or test two key conditions:

(a) Cooperative membrane binding, which is a key component of mathematical models for the oscillating E. coli Min system. This cooperative membrane binding has recently been attributed to MinD or MinCD oligomerization on the membrane and has been experimentally observed in various instances; in fact, the authors themselves show data supporting the formation of MinCD copolymers.  

(2) Local stimulation of the ATPase activity of MinD which triggers the dimer-to-monomer transition; E. coli MinD ATP hydrolysis is stimulated by the membrane and by MinE, so B. subtilis MinD may also be stimulated by the membrane and/or other components like MinJ. Instead, the authors claim that (a) would only increase differences in diffusion between the monomer and different oligomeric species, and that a 2-fold increase in dimerization on the membrane could not induce gradient formation in their simulation, in the absence of MinJ stimulating gradient formation. However, a 2-fold increase in dimerization is likely way too low to explain any cooperative membrane binding observed for the E. coli Min system. Regarding (b), they also claim that implementing stimulation of ATP hydrolysis on the membrane (dimer-to-monomer transition) would not change the outcome, but no simulation result for this condition is actually shown.  

(3) To generate any gradient formation, the authors claim that they would need to implement stimulation of dimer formation by MinJ, but they themselves acknowledge the lack of any experimental evidence for this assertion. They then test all other conditions (e.g., differences in membrane affinity, diffusion, etc.) in addition to the requirement that MinJ stimulates dimer formation. It is unclear whether the authors tested all other conditions independently of the "MinJ induces dimerization" condition, and whether either of those alone or in combination could also lead to gradient formation. This would be an important test to establish the validity of their claims.

Reviewer #3 (Public review): 

This important study by Bohorquez et al examines the determinants necessary for concentrating the spatial modulator of cell division, MinD, at the future site of division and the cell poles. Proper localization of MinD is necessary to bring the division inhibitor, MinC, in proximity to the cell membrane and cell poles where it prevents aberrant assembly of the division machinery. In contrast to E. coli, in which MinD oscillates from pole to pole courtesy of a third protein MinE, how MinD localization is achieved in B. subtilis - which does not encode a MinE analog - has remained largely a mystery. The authors present compelling data indicating that MinD dimerization is dispensable for membrane localization but required for concentration at the cell poles. Dimerization is also important for interactions between MinD and MinC, leading to the formation of large protein complexes. Computational modeling, specifically a Monte Carlo simulation, supports a model in which differences in diffusion rates between MinD monomers and dimers lead to the concentration of MinD at cell poles. Once there, interaction with MinC increases the size of the complex, further reinforcing diffusion differences. Notably, interactions with MinJ-which has previously been implicated in MinCD localization, are dispensable for concentrating MinD at cell poles although MinJ may help stabilize the MinCD complex at those locations.  

Reviewer #1 (Recommendations for the authors):  

(1) The title could be modified to better reflect the emphasis on MinD monomer and dimer diffusion rather than the fact that membrane affinity is not important in MinD gradient formation. In addition, because membrane association requires affinity for the membrane, this title seems inconsistent with statements in the main text, such as Lines 246-247: a reversible membrane association is important for the formation of a MinD gradient along the cell axis.

We agree with the reviewer that the title can be more accurate, and we have now changed it to “Membrane affinity difference between MinD monomer and dimer is not crucial to MinD gradient formation in Bacillus subtilis”

(2) This paper reports that the difference in diffusion rates between MinD monomers and dimers is an important factor in the formation of Bs MinD gradients. However, one can argue for the importance of MinD monomers in the cellular context. Since the abundance of ATP in cells often far exceeds the abundance of MinD protein molecules under experimental conditions, MinD can easily form dimers in the cytoplasm. How does the author address this problem?  

It is a good point that ATP concentration in the cell likely favours dimers in the cytoplasm. However, what is important in our model is that there is cycling between monomer and dimer, rather than where exactly this happen. In fact, the gradients works essentially equally well if dimers can become monomers only whilst they are at the membrane, as we have mentioned in the manuscript (lines 324-326 in the original manuscript). However, in the original manuscript this simulation was not shown, and now we have included this in the new Fig. 8D & E.

(3)The claim "This oscillating gradient requires cycling of MinD between a monomeric cytosolic and a dimeric membrane attached state." (Lines 46, 47) is not well supported by most current studies and needs to be revised since to my knowledge, most proposed models do not consider the monomer state. The basic reaction steps of Ec Min oscillations include ATP-bound MinD dimers attaching to the membrane that subsequently recruit more MinD dimers and MinE dimers to the membrane; MinE interactions stimulate ATP hydrolysis in MinD, leading to dissociation of ADP-bound MinD dimers from the membrane; nucleotide exchange occurs in the cytoplasm.  

Here the reviewer refers to a sentence in a short “Importance” abstract that we have added. In fact, such abstract is not necessary, so we have removed it. Of note, the E. coli MinD oscillation, including the role of MinE, is described in detail in the Introduction. 

A recent reference is a paper by Heermann et al. (2020; doi: 10.1016/j.jmb.2020.03.012), which considers the MinD monomer state, which is not mentioned in this work. How do their observations compare to this work?  

The Heermann paper mentions that MinD bound to the membrane displays an interface for multimerization, and that this contributes to the local self-enhancement of MinD at the membrane. In our Discussion, we do mention that E. coli MinD can form polymers in vitro and that any multimerization of MinD dimers will further increase the diffusion difference between monomer and dimer, and might contribute to the formation of a protein gradient (lines 459-467). We have now included a reference to the Heermann paper (line 461).

(4) Throughout the manuscript, errors in citing references were found in several places.                 

We have corrected this where suggested.

(5) The introduction may be somewhat misleading due to mixed information from experimental cellular results, in vitro reconstructions, and theoretical models in cells or in vitro environments. Some models consider space constraints, while others do not. Modifications are recommended to clarify differences.  

See below for responses 

(6) The citation for MinD monomers:

The paper by Hu and Lutkenhaus (2003, doi: 10.1046/j.1365-2958.2003.03321.x.) contains experimental evidence showing monomer-dimer transition using purified proteins. Another paper by the same laboratory (Park et al. 2012, doi: 10.1111/j.1365-2958.2012.08110.x.) explained how ATP-induced dimerization, but this paper is not cited.  

The Park et al. 2012 paper focusses at the asymmetric activation of MinD ATPase by MinE, which goes beyond the scope of our work. However, we have cited several other papers from the Lutkenhaus lab, including the Wu et al. 2011 paper describing the structure of the MinD-ATP complex.

Other evidence comes from structural studies of Archaea Pyrococcus furiosus (1G3R) and Pyrococcus horikoshii (1ION), and thermophilic Aquifex aeolicus (4V01, 4V02, 4V03). As they may function differently from Ec MinD, they are less relevant to this manuscript.

We agree. 

(7) Lines 65, 66: Using the term 'a reaction-diffusion couple' to describe the biochemical facts by citing references of Hu and Lutkenhaus (1999) and Raskin and de Boer (1999) is not appropriate. The idea that the Min system behaves as a reaction-diffusion system was started by Howard et al. (2001), Meinhardt and de Boer (2001), and Huang et al. (2003) et al. In addition, references for MinE oscillation are missing. 

We have now corrected this (line 52).

(8) Lines 77-79: Citations are incorrect.

ATP-induced dimerization: Hu and Lutkenhaus (2003, DOI: 10.1046/j.1365-2958.2003.03321.x), Park et al. (2012). C-terminal amphipathic helix formation: Szeto et al. (2003), Hu and Lutkenhaus (2003, DOI: 10.1046/j.1365-2958.2003.03321.x).

Citations have been corrected.

(9) Line 78: The C-terminal amphipathic helix is not pre-formed and then exposed upon conformational change induced by ATP-binding. This alpha-helical structure is an induced fold upon interaction with membranes as experimentally demonstrated by Szeto et al. (2003).  

We have adjusted the text to correct this (lines 64-66).

(10) Line 102: 'cycles between membrane association and dissociation of MinD' also requires MinE in addition to ATP.

We believe that in the context of this sentence and following paragraph it is not necessary to again mention MinE, since it is focused on parallels between the E. coli and B. subtilis MinD membrane binding cycles.

(11) In the introduction, could the author briefly explain to a general audience the difference between Monte Carlo and reaction-diffusion methods? How do different algorithms affect the results?

The main difference between the kinetic Monte Carlo and typical reaction-diffusion methods which is relevant to our work is that the first is particle-based, and naturally includes statistical fluctuations (noise), whereas the second is field-based, and is in the normal implementation deterministic, so does not include noise. Whilst it should be noted that one can in principle include noise in the field-based reactiondiffusion methods, this is done rarely. Additionally, although we do not do this here, the kinetic MonteCarlo can also account, in principle, for particle shape (sphere versus rod), or for localized interactions (as sticky patches on the surface): therefore the kinetic Monte Carlo is more microscopic in nature. We have now shortly described the difference in lines 102-105.

(12)  Lines 126-128: The second part of the sentence uses the protein structure of Pyrococcus furiosus MinD (Ref 37) to support a protein sequence comparison between Ec and Bs MinD. However, the structure of the dimeric E. coli MinD-ATP complex (3Q9L) is available, which is Reference 38 that is more suited for direct comparison.

To discuss monomeric MinD from P. furiosus, it will be useful to include it in the primary sequence alignment in Figure S1.

We do not think that this detailed information is necessary to add to Figure S1, since the mutants have been described before (appropriate citations present in the text).

(13) Lines 127, 166: Where Figure S1 is discussed, a structural model of MinD will be useful alongside with the primary sequence alignment.

We do not think that this detailed information is necessary to understand the experiments since the mutants have been described before.

(14) Lines 131-132: Reference is missing for the sentence of " the conserved..."; Reference 38.  In Reference 38, there is no experimental evidence on G12 but inferred from structure analysis. Reference 26 discusses ATP and MinE regulation on the interactions between MinD and phospholipid bilyers; not about MinD dimerization.

We have corrected this and added the proper references. 

For easy reading, the mutant MinD phenotypes can be indicated here instead of in the figure legends, including K16A (apo monomer), MinD G12V (ATP-bound monomer), and MinD D40A (ATP-bound dimer, ATP hydrolysis deficient).  

We have added the suggested descriptions of the mutants in the main text.

(15) Lines 150-151: Unlike Ec MinD, which forms a clear gradient in one half of the cell, Bs MinD (wild type) mainly accumulates at the hemispheric poles. What percentage of a cell (or cell length) can be covered by the Bs MinD gradient? How does the shaded area in the longitudinal FIP compare to the area of the bacterial hemispherical pole? If possible, it might be interesting to compare with the range of nucleoid occlusion mechanisms that occur.

Part of the MinD gradient covers the nucleoid area, since the fluorescence signal is still visible along the cell lengths, yet there is no sudden drop in fluorescence, suggesting that nucleoid exclusion does not play a role.

(16)  Line 160: In addition to summarizing the membrane-binding affinity, descriptions of the differences in the gradient distribution or formation will be useful.  

We have done this in lines 155-156 of the original manuscript: “The monomeric ATP binding G12V variant shows the same absence of a protein gradient as the K16A variant”.

(17) Line 262: 'distribution' is not shown.  

We do not understand this remark. This information is shown in Fig. 5B (now Fig. 6B).

(18)  Line 287: Wrong citation for reference 31.

Reference has been corrected.

(19)  Line 288 and lines 596 regarding the Monte Carlo simulation:

(a)  An illustration showing the reaction steps for MinD gradient formation will help understand the rationale and assumptions behind this simulation.

We have added an illustration depicting the different modelling steps in the new Fig. 8.

(b)  Equations are missing.

(c)   A table summarizing the parameters used in the simulation and their values.

(d)  For general readers, it will be helpful to convert the simulation units to real units.

(e)  Indicate real experimental data with a citation or the reason for any speculative value.

The Methods section provides a discussion of all parameters used in the potentials on which our kinetic Monte-Carlo algorithm is based. We have now also provided a Table in the SI (Table S1) with typical parameter values in both simulation units and real units. The experimental data and reasoning behind the values chosen are discussed in the Methods section (see “Kinetic Monte Carlo simulation”).

(20)  Lines 320-321: Reference missing.

The interaction between MinJ and the dimer form of MinD is based on our findings shown in the original Fig. S4, and this information has not been published before. We have rephrased the sentence to make it more clear. Of note, Fig. S4 has been moved to the main manuscript, at the request of reviewer #2, and is now new Fig. 2. 

(21)  Lines 355-359: Is the statement specifically made for the Bs Min system? Is there any reference for the statement? Isn't the differences in diffusion rates between molecules 'at different locations' in the system more important than reducing their diffusion rates alone? It is unclear about the meaning of the statement "the Min system uses attachment to the membrane to slow down diffusion". Is this an assumption in the simulation?

The statement is generic, however the reviewer has a good point and we have made this statement more clear by changing “considerably reduced diffusion rate” to “locally reduced diffusion rate” (line 359).

(22) Line 403: Citation format.

We have corrected the text and citation.

(23) Lines 442-444: The parameters are not defined anywhere in the manuscript.

Discussed in the M&M and in the new Table S1.

(24) Lines 464-465: Regarding the final sentence, what does 'this prediction' refer to? Hasn't the author started with experimental observations, predicted possible factors of membrane affinity and diffusion rates, and used the simulation approach to disapprove or support the prediction?

We have changed “prediction” to “suggestion”, to make it clear that it is related to the suggestion in the previous sentence that  “our modelling suggests that stimulation of MinD-dimerization at cell poles and cell division sites is needed.” (line 471).

(25) Materials and Methods: Statistical methods for data analyses are missing.

Added to “Microscopy” section.

(26) References: References 34, 40, 51 are incomplete.

References 34 and 40 have been corrected. Reference 51 is a book.

(27)  Figures: The legends (Figures 1-7) can be shortened by removing redundant details in Material and Methods. Make sure statistical information is provided. The specific mutant MinD states, including Apo monomer, ATP-bound dimer, ATP hydrolysis deficient, and non-membrane binding etc can be specified in the main text. They are repeated in the legends of Figures 1 and 2.

We have removed redundant details from the legends and provided statistical information.

(28)  Supporting information:

Table S1: Content of the acknowledgment statement may be moved to materials and methods and the acknowledgment section. Make sure statistical information is provided in the supporting figure legends.

We are not sure what the reviewer means with the content acknowledgement in Table S1 (now Table S2). Statistical information has been added.

Figure S1. Adding a MinD structure model will be useful.

We do not think that a structural model will enlighten our results since our work is not focused at structural mutagenesis. The mutants that we use have been described in other papers that we have cited.

Reviewer #2 (Recommendations for the authors):  

The authors should cite and relate their data to the preprint by Feddersen & Bramkamp, BioRxiv 2024. ATPase activity of B. subtilis MinD is activated solely by membrane binding.

We have now discussed this paper in relation to our data in lines 407-409. 

I am not convinced the authors are able to make the statement in lines 160-161 based on their assay: "This confirmed that the different monomeric mutants have the same membrane affinity as wild-type MinD". It is unclear if measuring valley-to-peak ratios in their longitudinal profiles can resolve small differences in membrane affinity. Wildtype MinD should at least be dimeric, or (as the authors also note elsewhere) may even be present in higher-order structures and as such have a higher membrane affinity than a monomeric MinD mutant. The authors should rephrase the corresponding sections in the manuscript to state that the MinD monomer already has detectable membrane affinity, instead of stating that the monomer and dimer membrane affinity are the same.

We agree that “the same affinity” is too strongly worded, and we have now rephrased this by saying that the different monomeric mutants have a comparable membrane affinity as wild type MinD (line 152).

According to the authors' analysis, MinD-NS4B would not bind to the membrane as it has a valley-to-peak ratio higher than 1, similar to the soluble GFP. However, the protein is clearly forming a gradient, and as such probably binding to the membrane. The authors should discuss this as a limitation of their membrane binding measure.

The ratio value of 1 is not a cutoff for membrane binding. As shown in Fig. 1F, GFP has a valley-topeak ratio close to 1.25, whereas the FM5-95 membrane dye has a ratio close to 0.75. In Fig. 3C (now Fig. 4C) we have shown that GFP fused with the NS4B membrane anchor has a lower ratio than free GFP, and we have shown the same in Fig. 4D (now Fig. 5D) for GFP-MinD-NS4B. The difference are small but clear, and not similar to GFP.

The observation that MinD dimers are localized by MinJ is interesting and key to the rule of the Monte Carlo simulation that dimers attach to MinJ. However, the data is hidden in the supplementary information and is not analysed as comprehensively, e.g., it lacks the analysis of the membrane binding. The paper would benefit from moving the fluorescence images and accompanying analysis into the main text.  

We have moved this figure to the main text and added an analysis of the fluorescence intensities (new Fig. 2).

The authors should show the data for cell length and minicell formation, not only for the MinDamphipathic helix versions (Fig. 5), but also for the GFP-MinD, and all the MinD mutants. They do refer to some of this data in lines 145-148 but do not show it anywhere. They also refer to "did not result in cell filamentation" in line 213 and to "resulted in highly filamentous cells" and "Introduction of a minC deletion restored cell division" in lines 167-160 without showing the cell length and minicell data, but instead refer to the fluorescence image of the respective strain. I would suggest the authors include this data either in a subpanel in the respective figure or in the supplementary information.

The effect of uncontrolled MinC activity is very apparent and leads to long filamentous cells. Also the occurrence of minicells is apparent. Cell lengths distribution of wild type cells is shown in Fig. 6B, and minicell formation is negligibly small in wild type cells.

The transverse fluorescence intensity profiles used as a measure for membrane binding are an average profile from ~30 cells. In the case of the longitudinal profiles that display the gradient, only individual profiles are displayed. I understand that because of distinct cell length, the longitudinal profiles cannot simply be averaged. However, it is possible to project the profiles onto a unit length for averaging (see for example the projection of profiles in McNamara. et al., BioRxiv (2023)). It would be more convincing to average these profiles, which would allow the authors to also quantify the gradients in more detail. If that is impossible, the authors may at least quantify individual valley-to-peak ratios of the longitudinal fluorescence profiles as a measure of the gradient.

We agree that in future work it would be better to average the profiles as suggested. However, due to limited time and resources, we cannot do this for the current manuscript.

Regarding the rules and parameters used for the Monte Carlo simulation (see also the corresponding sections in the public review):

(1) The authors mention that they have not included multimerization of MinD in their simulation but argue in the discussion that it would only strengthen the differences in the diffusion between monomers and multimers. This is correct, but it may also change the membrane residence time and membrane affinity drastically.

Simulation of multimerization is difficult, but we have now included a simulation whereby MinD dimers can also form tetramers (lines 341-348), shown in the new Fig. 8K. This did not alter the MinD gradient much. 

(2) The authors implement a dimer-to-monomer transition rate that they equate with the stochastic ATP hydrolysis rate occurring with a half-life of approximately 1/s (line 305). They claim that this rate is based on information from E. coli and cite Huang and Wingreen. However, the Huang paper only mentions the nucleotide exchange rate from ADP to ATP at 1/s. Later that paper cites their use of an ATP hydrolysis rate of 0.7/s to match the E. coli MinDE oscillation rate of 40s. From the authors' statement, it is unclear to me whether they refer to the actual ATP hydrolysis rate in Huang and Wingreen or something else. For E. coli MinD, both the membrane and MinE stimulate ATPase activity. Even if B. subtilis lacks MinE, ATP hydrolysis may still be stimulated by the membrane, which has also been reported in another preprint (Feddersen & Bramkamp, BioRxiv 2024). It may also be stimulated by other components of the Min system like MinJ. The authors should include in the manuscript the Monte Carlo simulation implementing dimer to monomer transition on the membrane only, which is currently referred to only as "(data not shown)". 

The exact value of the ATP hydrolysis rate is not so important here, so 1/s only gives the order of magnitude (in line with 0.7/s above), which we have now clarified in lines 631-632. We have now also added the “(data not shown” results to Fig. 8, i.e. simulations where dimer to monomer transitions (i.e. ATPase activity) only occurs at the membrane (Fig. 8D & E, and lines 319-322).

(3) How long did the authors simulate for? How many steps? What timesteps does the average pictured in Figure 7 correspond to?

We simulated 10^7time steps (corresponding to 100 s in real time). We have checked that the simulation steps for which we average are in steady state. Typical snapshots are recorded after 10^610^7time steps, when the system is in steady state. We have added this information in lines 299-300.

There are several misconceptions about the (oscillating E. coli) Min system in the main text:

(1) Lines 77-78: "In case of the E. coli MinD, ATP binding leads to dimerization of MinD, which induces a conformational change in the C-terminal region, thereby exposing an amphiathic helix that functions as a membrane binding domain" and "This shows a clear difference with the E. coli situation, where dimerization of MinD causes a conformational change of the C-terminal region enabling the amphipathic helix to insert into the lipid bilayer" in lines 400-403 are incorrect. There is no evidence that the amphipathic helix at the C-terminus of MinD changes conformation upon ATP binding; several studies have shown instead that a single copy of the amphipathic helix is too weak to confer efficient membrane binding but that the dimerization confers increased membrane binding as now two amphipathic helices are present leading to an avidity effect in membrane binding. Please refer to the following papers (Szeto et al., JBC (2003); Wu et al., Mol Microbiol (2011); Park et al., Cell (2011); Heermann et al., JMB (2020); Loose et al., Nat Struct Mol Biol (2011); Kretschmer et al., ACS Syn Biol (2021); Ramm et al., Nat Commun (2018) or for a better overview the following reviews on the topic of the E. coli Min system Wettmann and Kruse, Philos Trans R Soc B Biol (2018), Ramm et al., Cell and Mol Life Sci (2019); Halatek et al., Philos Trans R SocB Biol Sci (2018).

This is indeed incorrectly formulated, and we have now amended this in lines 64-66 and lines 403406. Key papers are cited in the text.

(2) The authors mention that E. coli MinD may multimerize, citing a study where purified MinD was found to polymerize, and then suggest that this is unlikely to be the case in B. subtilis as FRAP recovery of MinD is quick. However, cooperativity in membrane binding is essential to the mathematical models reproducing E. coli Min oscillations, and there is more recent experimental evidence that E. coli MinD forms smaller oligomers that differ in their membrane residence time and diffusion (e.g., Heermann et al., Nat Methods (2023); Heermann et al., JMB (2020);) I would suggest the authors revise the corresponding text sections and test the multimerization in their simulation (see above).

As mentioned above, simulating oligomerization is difficult, but in order to approximate related cooperative effects, we have simulated a situation whereby MinD dimers can form tetramers. This simulation did not show a large change in MinD gradient formation. We have added the result of this simulation to Fig. 8 (Fig. 8K), and discuss this further in lines 341-348 and 459-467.

(3) Lines 75-76 and lines 79-80: The sentences "MinC ... and needs to bind to the Walker A-type ATPase MinD for its activity" and "The MinD dimer recruits MinC ... and stimulates its activity" are misleading. MinC is localized by MinD, but MinD does not alter MinC activity, as MinC mislocalization or overexpression also prevents FtsZ ring formation leading to minicell or filamentous cells, as also later described by the authors (line 98). There is also no biochemical evidence that the presence of MinD somehow alters MinC activity towards FtsZ other than a local enrichment on the membrane. I would rephrase the sentence to emphasize that MinD is only localizing MinC but does not alter its activity.   

We have rephrased this sentence to prevent misinterpretation (lines 66-67).

Minor points:  

(1)  I am not quite sure what the experiment with the CCCP shows. The authors explain that MinD binding via the amphipathic helix requires the presence of membrane potential and that the addition of CCCP disturbs binding. They then show that the MinD with two amphipathic helices is not affected by CCCP but the wildtype MinD is. What is the conclusion of this experiment? Would that mean that the MinD with two amphipathic helices binds more strongly, very differently, perhaps non-physiologically?  

This experiment was “To confirm that the tandem amphipathic helix increased the membrane affinity of MinD”, as mentioned in the beginning of the paragraph (line 224).  

(2) Lines 456-457: Please cite the FRAP experiment that shows a quick recovery rate of MinD.

Reference has been added. 

(3) Figure 4D: It is unclear to me to which condition the p-value brackets point.

This is related to a statistical t-test. We have added this information to the legend of the figure.

(4) Line 111, "in the membrane affinity of the MinD". I think that the "the" before MinD should be removed.  

Corrected

(5) Typo in line 199 "indicting" instead of indicating.

Corrected

(6) Typo in line 220 "reversable" instead of reversible.

Corrected

(7) Lines 279, 284, 905: "Monte-Carlo" should read Monte Carlo.

Corrected

Reviewer #3 (Recommendations for the authors):  

Introduction: As written, the introduction does not provide sufficient background for the uninitiated reader to understand the function of the MinCD complex in the context of assembly and activation of cell division in B. subtilis. The introduction is also quite long and would benefit from condensing the description of the Min oscillation mechanism in E. coli to one or two sentences. While highlighting the role of MinE in this system is important for understanding how it works, it is only needed as a counterpoint to the situation in B. subtilis.

Since the Min system of E. coli is by far the best understood Min system, we feel that it is important to provide detailed information on this system. However, we have added an introductory sentence to explain the key function of the Min system (line 46-48).

Line 248: Increasing MinD membrane affinity increases the frequency of minicells - however it is unclear if cells are dividing too much or if it is just a Min mutant (i.e. occasionally dividing at the cell pole vs the middle)? Cell length measurements should be included to clarify this point (Figures 4 and 5).

This information is presented in Fig. 5B (Cell length distribution), which is now Fig. 6B, indicating that the average cell length increases in the tandem alpha helix mutant, a phenotype that is comparable to a MinD knockout. 

Figure 5: I am a bit confused as to whether increasing MinD affinity doesn't lead to a general block in division by MinCD rather than phenocopying a minD null mutant.

Although the tandem alpha helix mutant has a cell length distribution comparable to a minD knockout, the tandem mutant produces much less minicells then the minD knockout, indicating that there is still some cell division regulation.

Change the H2s to H3s

Achieving an average performance level of 99.3% across delivery

GFS Logistics Brochure

Remove the h tag

Take the pressure off and grow your business faster with scalable logistics and fulfilment services

Change to H4

Change H2s for the four boxes to H3s

remove H2

Can we update the meta description so it discusses the specifics of operations

Suggestion Discover how the GFS Operations team ensures seamless, dependable logistics with the expertise and support retailers need to keep shipments on track.

After the video can we add a section that expands on logistics and fulfilment

I know they are not huge focus areas for the business but it seems to be part of the user journey that they would want to know about all logistics (fulfilment and logistics)

Can we add in a section above the video that relates to Operations in relation to 30 words each eCommerce International Multi-Carrier Delivery Management GFS Enterprise Carrier Management Software

And link to those pages

Is there a page we could link to with a CTA? especially if we do one line of boxes - where do we want the user to go next?

Can we offer any power to our main pages?

We would suggest a intro section of 50 words to give a broad arching introduction to operations

Take some details from the boxes below maybe as this would be better if the 4 boxes were all on the same line and the stand out parts of each section

Meta title change - Current title is mixed with ecommerce intent and carrier management

Carrier Management Operations| GFS

Internal links from the below pages to this one

• https://gfsdeliver.com/blog/everything-you-need-to-know-for-parcel-returns-management/
• https://gfsdeliver.com/blog/beyond-the-box-how-health-and-beauty-ecommerce-brands-can-optimise-returns-management/
• https://gfsdeliver.com/blog/how-to-use-post-peak-ecommerce-returns-to-build-customer-loyalty/
• https://gfsdeliver.com/infographics/why-returns-matter/
• https://gfsdeliver.com/blog/resetting-customer-expectations-the-state-of-ecommerce-returns-in-2022/

Please can we change the H2s to H3s

Above the final section (Complete the circle) there is an opportunity to add a section in about GFS in relation to your USPs, brand and customer service?

Didnt feel that there was that explicit message here

Remove H3's and just a

Hoping Sambi provides some more copy to go between the H2 and the below boxes

Can we update this to Business Benefits to Returns Management Solution?

If not then H3 please

remove the h tags just

H3 please

Remove header tags just

please

Can we make this a H3

If Sambi provides another section of content with a kw header that should be the H2

The page has a total word count of 562 - we would want that much closer to 800 words

The page in search terms just feels like it misses context and the full story - its more the bulleted highlights

Can we expand this section out - we want the context around why you need to get it right and what is wrong with it (or could be) wrong with it

Can these two sit side by side rather than on top of each other

can we tweak the content here to increase the relevance around the keywords - returns platform, software etc

Can we ad returns in the middle

Can we include a CTA link to the main ECM page as a next step

This is a hugely important section for SEO especially for mobile. We need a 50-100 word section introducing the returns softare and services.

Thinking about AI tech we want the crawlers to get this page and go yep this is what it is aboiut

Meta description can be slightly longer

examples Fast, affordable returns management software that simplifies ecommerce returns with Global Returns Pro, improving efficiency and customer experience.

Streamline ecommerce returns with fast, affordable returns management software. Global Returns Pro simplifies processes and boosts customer satisfaction.

Fast, affordable returns management software to simplify ecommerce returns. Global Returns Pro improves efficiency, visibility, and customer satisfaction.

Can we extend this section to 20-50 words that can expand on exactly what this page is about and think about the keywords. This sort of area is great for adding micro summaries for ai tech

"Our Global returns management solution offers businesses the opportunity to reduce returns with one simple platform"

Meta Title to be changed as over optimised and Google has changed it to your H1

Return Management Software | GFS Global Returns Pro

The page is doing ok in search but it needs to look at the content to add the following words software, solution and platform in the context as it being returns software,platform etc

The use of these keywords is not specific to returns as other serps results

I find this passage very interessting as Orsino notices Cesario's feminine aspect yet do not describes them in a bad light. Actually, he describes Cesario's lips and voice rather positively (comparing him to a Goddess) which is in a way, direct characterization for Viola but also some kind of inside joke between Shakespear and the audiance who knows that Cesario is a woman. Orsino's description seems to be a forshadowing that he will fall for Viola as he already finds her (or at least her lips) beautiful when she pretends to be a man.

Référence à corriger

Je ne comprend pas la formulation. Peut-être pourrait-on formuler les choses en disant qu'on part d'une conversion éthique à partir de laquelle un nouveau rapport à soi, à autrui et au monde se construit.

Je ne comprends pas la formulation. Le terme de charisme devrait être plus introduit, même s'il est par ailleurs commun en management.

Qualifier une telle praxis ainsi, n'est-ce pas d'emblée la figer dans un rapport pratico-inerte?

Guest Editor:

Thank you for your submission to PLOS Global Public Health. I appreciate the time and effort invested in conducting the study and preparing the submission.

After careful review and evaluation of the manuscript, we are sorry to report that we are unable to accept your manuscript for publication in PLOS Global Public Health, in its current form. While a few considerations factored this decision, our concern were the lack of novelty and too preliminary of results to guide clinical practice.

We recognize the importance of your work and its contribution to the field and feel that substantial revision of the above stated concerns might aid in curating the manuscript to meet the editorial scope of PLOS journals.

We sincerely appreciate your interest and hope that you will consider submitting your future works to PLOS Global Public Health.

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