DOI: 10.1016/j.cell.2026.07.008

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DOI: 10.1016/j.cell.2026.07.008

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DOI: 10.1016/j.cell.2026.07.008

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DOI: 10.1016/j.cell.2026.07.008

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DOI: 10.1016/j.cell.2026.06.033

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DOI: 10.1016/j.cell.2026.06.033

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DOI: 10.1016/j.cell.2026.06.033

Resource: RRID:Addgene_171588

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DOI: 10.1016/j.cell.2026.06.033

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DOI: 10.1016/j.bioactmat.2026.07.031

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DOI: 10.1016/j.ajhg.2025.12.016

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DOI: 10.1007/s00784-026-07051-y

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DOI: 10.1007/s00784-026-07051-y

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DOI: 10.1007/s00784-026-07051-y

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DOI: 10.1007/s00784-026-07051-y

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DOI: 10.1007/s00018-026-06254-6

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DOI: 10.1002/smmd.70038

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DOI: 10.1002/ptr.70307

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DOI: 10.1002/ptr.70307

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DOI: 10.1002/pro.70746

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DOI: 10.1002/pro.70746

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DOI: 10.1002/mbo3.70370

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DOI: 10.1002/cne.70188

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DOI: 10.1002/cne.70188

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DOI: 10.1002/cne.70188

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DOI: 10.1002/cne.70188

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DOI: 10.1002/cne.70188

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DOI: 10.1002/cne.70188

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DOI: 10.1002/cne.70188

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DOI: 10.1002/cne.70188

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DOI: 10.1002/cne.70188

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DOI: 10.1002/cmdc.70425

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DOI: 10.1002/advs.76824

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DOI: 10.1002/advs.76738

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DOI: 10.1002/advs.202519893

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DOI: 10.1002/adma.74301

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DOI: 10.1002/adma.74301

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DOI: 10.1002/adma.74301

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DOI: 10.1002/2211-5463.70233

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DOI: 10.1002/2211-5463.70233

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What is this?

DOI: 10.1002/1878-0261.70237

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DOI: 10.1002/1878-0261.70237

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DOI: 10.1002/1878-0261.70237

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DOI: 10.1002/1878-0261.70237

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DOI: 10.1038/s41467-026-74702-9

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What is this?

DOI: 10.1093/nar/gkag769

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What is this?

I dont think we need this. delete

delete

what does this mean?

delete

lets get rid of this alltogterj

give me a sanity check in terms of how "ok" it is to use and compare these numbers regardles sof all these caveats. Consider adding a sentence here to this paragraph, that regardles sof these caveats and the "fine print" its largely about the huge gap to everyone else that we have included it, dont say it like this, but whether its 1 mio more or less does not seem to matter so much, its more about the contrats, becuse differences are so huge,

again: change title and get rid of second headline

change teh title of the grapg below to "Germany: from minimum wage to Chancellor"

this "table" tells me exactly the same thing as the graph above. lets cut it

we should probably say at the beginning of this section that we draw on data from the public sector because its freely available. Saying then that "it leaves the public sector entirely" soujd s bit strange, maybe rephrase, because of course we also have lower salaries in the private sector...it s a small annoyance though

delete.

give me an alternative for a better title

no second headline

add that this is base pay only: tax-free expense allowances and supplements, which are substantial in some countries (notably Poland, Romania and Belgium), are excluded everywhere.

delete

see my comments in V2: we need to check: a) whether it is not true that all countries median bledn full time workers and oart time workers. b) check whether there are other countries where parliament ppl only work part time.

While we are at it and checking things: I also want you to fact check the Hungary numbers, the Gemany numbers and the Spain numbes. Give me the exact calculations you did here.

do we not have a table for this section? As in a graph to illustrate this? If so, please insert it before the headline "Parliaments: from below the median to just over four times it"

NOte: i juts found the graph. It is further down and it needs to be moved up

This shoudl go into the methodology.

And the title of the graph above should change according to my feedback throughout when it comes to headlines for graphs

This should be moved into the methodology

no need for this

Different Titel. something shorter, in line with the previous ones.

Good, I would just phrase it a tiny bit more careful to acknowledge that this obviously also has to do with cultural, historical developments and economic strenghts and so on...

For the graph below, make sure you ppick a difefrent title, one that interprets less (I already have that interpretation/insight in the tex). I prefer a more general heading that plays with what this sort of measures: inequality, distance to the top across europe

I dont understand that sentence. What does it mean? Why do euros and price cancel out? It means we do not have to adust for PPS?

again, no second headline

change title: cut the "your", make it more neutrakl in a way, like the equivalent to the previous title " THE TOP 1%"

make this a seperate paragraph

get rid of all of this. Find a new way to introduce the oaragraph below which talks about the geographical "where" the top1 lives. Make sure you add the numbers relevant: "the EU-wide top 10% begins at €46,828 a year and the top 1% of the entire European Union begins at €92,225 a year (€7,685 a month), figures most readers place far too high when asked to guess."

Ok, this is interesting, but needs to be presented better. Rewrite this paragraph and make clear that the prevous oparagraph talks about PERCENTAGE (so 13% of Luxemburgs population is in the top 1%), but when we look at ABSOLUTE NUMBERS the picture looks differently.

We should change the table. Its not easy to read. I would not work with arrows that point "up" and "Down", but literally reshuffle the list with the new hierachy. maybe we can add a red arrow (for downward movement, pointing down) or a green rrow for upward movemnet, pointing up, behind each countries name to indicate whetehr they moved up or down when adjusted for PPS.

Since the previous paragraph moves up, this needs a different intro sentence.

come up with a shorter, better title.

This paragraph needs to go right after the map of Europe

In the chart titled "ten national medians clear Romania's top 1% bar" come up with a better titel. I want something shorter and more general, not interpretative. So something like "Income in Europe: The middle and the top"

not just BUlgaria, right? Should it not be more like "And one of the most striking insights: the median Luxembourger clears the entry bar of 7 East European countries (Bulgaria.....).

combine this paragraph and the new one ask you to create in the previous comment ("Before this sentence put this part which we deleted in the the intro: Entering the top 1% takes €205,420 a year in Luxembourg and €22,715 in Romania, and that Romanian ticket to the very top is almost exactly what the median European lives on (€22,038). Preface it with something along the lines of "there are significant differences of what it takes to be among the top 1%…" and make it its own paragraph.") so that we do not have any redundancy.

Before this sentence put this part which we deleted in the the intro: Entering the top 1% takes €205,420 a year in Luxembourg and €22,715 in Romania, and that Romanian ticket to the very top is almost exactly what the median European lives on (€22,038). Preface it with something along the lines of "there are significant differences of what it takes to be among the top 1%..." and make it its own paragraph.

place the map of Europe before this paragraph

delete

change to: The TOP 1% in Europe

rephrase this to sound less "defending" of the methodology. For example we dont need a sentence like "They are never mixed within a single comparison." A simple "... in order to do this/answer these questions we use three different measures: A B and C, details in the methodology.

can we make this sentnece even shorter and less repetetive of what comes after?

delete this sentence

AI:工业生产出来的物品，其实是人的能力（创造力、智慧、审美、技术、组织能力等）的外在表现；如果只把工业看成赚钱和满足需要的工具，就看不到其中包含的人的本质。

而不只是某种抽象的，纯粹效用的，和社会相异的对象

对象不再是某种异己的，敌对的存在，而是能够反映人的本质力量的存在，能够和人的需要，创造，社会关系联系起来的存在，人能通过自己的对象确认自身

不是从纯粹经济的效用而是从人的效用出发。

不是为了占有而是为了创造，不仅是为了自己更是为了社会

AI:人真正拥有自己的现实，不是靠拥有物品，而是靠发展自己的人的能力。

AI:这里的占有不是简单的所有，拥有。而是人对世界的真实理解和使用。

AI:对象性关系 = 人通过具体对象认识世界、改造世界，同时实现自己的关系。

AI:人通过意识到自己是社会的人，认识到自己的共同人性；而人的这种共同人性，也只有通过这种自觉意识才真正成为现实。人不仅生活在社会中，而且能够理解自己为什么这样生活，并主动创造自己的社会生活。

这里强调人既是历史运动的结果也是历史运动的出发点，人和人的关系是社会的，因此社会的性质体现历史运动的性质，因此就像历史，社会产生人一样，人也产生历史和社会

这个对象指的是劳动产品，亦即人创造的劳动产品在属于他自己的同时，是别人认识他，接近他的方式，是别人需要的，体现别人的东西，也是别人通过这个东西对我产生影响的东西，这里的逻辑递进有些弯弯绕绕的，需要多加了理解

这里说明的是在某个抽象的，私有财产被积极扬弃的条件下，人不仅在劳动活动中形成他自己，同时也在塑造别人

在这里，我们需要注意马克思对以下方法的批判： 1.历史上曾经出现过共同所有，所以共产主义是自然的（即原文的“从私有财产相对立的历史形式中寻找证明”）这里的共产主义不等同于过去的某种共同占有形式 2.从历史中挑一个符合自己观点的片段，然后说整个历史都是这样。（即“把历史中的个别环节固定下来”）不是因为原始社会共享财产，就需要回归共产主义，而是在私有制的基础上扬弃形成类似于旧的形式的新的制度。 “如果说它曾经存在过，那么它的过去存在反而反驳了它”：原始社会的共产主义不能代表真正的共产主义而是某一被历史抛弃的社会关系

历史的终结的意味，在这里，一旦人回归了人，那么接下来呢？这种问法也许是荒诞的，无意义的，不合逻辑的，但是，人成为人之后，历史就终结了吗？人难道就要成为“神”了吗？社会就要成为天堂了吗？

人和人的关系是一种社会关系，人作为社会的整体和自然的关系（对自然的占有，改造等等）是受到社会内人和人之间的关系影响的，同时，这种自然也可以理解为一种人天然的，本质的，符合人的东西，譬如性关系，作为一种自然关系，在这里是同社会关系有着强相关的

一个社会如何处理男女关系，反映了这个社会如何处理/理解人的关系

在这里，人的整体中有一部分被贬低到物的地位，因此，这里的关系不是人与人的关系，而是人和物的关系，是一种异化的关系

把人和物看作占有关系，物仍然在支配人

它追求的不是人的解放，而是人的同化，人人占有一样的东西，因而是最彻底的私有财产的表现，绝对地强调占有

在这里，人人都是工人，人人都是劳动者，可是，这里的劳动是异化的，是私有财产的根源，因而这个社会没有摆脱私有财产，而只是扩大化了的

这里应当指的是由老板私人占有变为某种集体的，国家的等等的占有，这种占有没有改变人与劳动的关系（为什么？就是说劳动在这里还是异化的，说的通俗些，就是工人还是在为工资而拼命，劳动产品仍然是作为支配工人的异己于工人的存在而存在，工人不是通过劳动实现自己，而只是通过劳动满足作为动物的需求）中国，苏联等社会主义国家

“自我异化”：人通过自己的活动，把自己的本质力量变成了外在的、敌对的力量。它的扬弃是指：消除劳动成为外在强制力量的状态，使劳动重新成为人的自由活动。这一整句话的大致意思：要解决异化，必须从异化本身产生的现实关系出发。

不再大言不惭地宣称自己代表自由，平等，民主，而是直接承认自己的逐利本质，并拒绝承认改变的方法

提及路德宗教改革，是为建立这样一种比喻，改革前的宗教将宗教权威建立在外在事物（教会，教士，赎罪券）上，而路德将这种宗教转移到人的心中，也就是说宗教是“人的”而不是“物的”，类似的，私有财产的本质不在于外在的工厂，生产资料等等，而在于人和财产的关系，在于人的占有关系和劳动能力，然而这种将私有财产转移到人的做法并没有解决人仍然被财产控制的情况，人的价值仍然被财产关系决定。

eLife Assessment

This important paper describes the role of the Pre-rRNA in meiotic sex chromosome inactivation in mouse spermatocytes. The cytological analyses of nucleolar components and the chemical inhibition of RNA polymerase I for rDNA transcription provided solid evidence, supporting the authors' conclusions. However, the results were not well described or explained in the text, making the logic difficult to follow. This paper will be of interest to researchers in meiotic chromosome structure and the nucleolus.

Reviewer #1 (Public review):

The authors show that during prophase I of male meiosis, nucleoli disassemble and nucleolar components relocalize to the sex chromosome (XY) body. They further demonstrate that this process is regulated by the ATR-dependent signaling pathway that mediates meiotic sex chromosome inactivation (MSCI). Pharmacological disruption of pre-rRNA synthesis using the RNA polymerase I inhibitor BMH-21 leads to the recruitment of RNA polymerase II to the sex chromosomes and ectopic expression of sex chromosome-linked genes. These findings uncover a previously unrecognized role for pre-rRNAs in maintaining transcriptional silencing during meiosis. The study employs a combination of cell biology, genetics, and genomics approaches, and the conclusions are supported by compelling, well-organized data.

Comments:

(1) The current study focuses on transcriptional regulation of the sex chromosomes. It would be interesting to know whether perturbation of pre-rRNA synthesis also affects transcription of autosomal genes.

(2) Is ribosome biogenesis still active during prophase I of male meiosis? Additional discussion of the timing and extent of rRNA synthesis at this stage would help place the findings in a broader biological context.

(3) A recent preprint reports active RNA polymerase II-mediated transcription of Y chromosome genes within nucleolus-like bodies (NLBs) during prophase I of meiosis in Drosophila male germ cells (https://doi.org/10.64898/2026.05.20.726666). These findings suggest that the meiotic nucleolus may have species-specific roles in regulating sex chromosome gene expression. It would be valuable for the authors to discuss how their findings compare with these observations and the potential evolutionary implications.

Reviewer #2 (Public review):

Summary:

The authors showed the localization pattern of nucleolus components, including Pre-rRNA, a precursor of rRNAs, changes during meiotic prophase I, particularly with the localization of these nucleolar components to the X-Y body, which shows inactivation of RNA polymerase II transcription, during pachynema. The localization of Pre-rRNA depends on ATR kinase and gammaH2AX. The chemical inhibition of rRNA transcription disrupts the binding of pre-rRNA to the X-Y body and suppresses the inhibition of the RNA polymerase II-mediated transcription on the sex chromosomes.

Strengths:

The cytological analysis, combined with the chemical inhibition, provided solid evidence to support the idea that, together with the remodeling of the nucleolus structure, pre-rRNA is an essential component of sex chromosome inactivation in male mouse meiosis. The role of pre-rRNA in sex chromosome inactivation in male meiosis helps our understanding of how the X-Y body, which would be a biological condensate, would be formed; e.g. for example, this Pre-rRNA may promote phase separation.

Weaknesses:

However, there is limited information on how Pre-rRNA is recruited to only sex chromosomes and how the RNA promotes the inactivation of sex chromosomes. Of course, these will be a target of future study. One major weakness of this paper is a poor description of the results, with fair presentation and interpretation of the data.

mein titel annotation

maybe too broad.

relevant for our purpose?

eLife Assessment

The authors addressed a significant biological question, namely the role of glutamine metabolism in humoral responses, and they obtained solid conclusions. The strength of this study is that the authors used state-of-the-art transgenic mouse models together with in vitro analysis, thereby providing important insights into the question posed. The manuscript has been further substantiated by adding more appropriate experimental controls and describing more in-depth functionality/physiological relevance.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigate the functional requirements for glutamine and glutaminolysis in antibody responses. The authors first demonstrate that the concentrations of glutamine in lymph nodes are substantially lower than in plasma, and that at these levels, glutamine is limiting for plasma cell differentiation in vitro. The authors go on to use genetic mouse models in which B cells are deficient in glutaminase 1 (Gls), the glucose transporter Slc2a1, and/or mitochondrial pyruvate carrier 2 (Mpc2) to test the importance of these pathways in vivo. Interestingly, deficiency of Gls alone showed clear antibody defects when ovalbumin was used as the immunogen, but not the hapten NP. For the latter response, defects in antibody titers and affinity were observed only when both Gls and either Mpc2 or Slc2a1 were deleted. These latter findings form the basis of the synthetic auxotrophy conclusion. The authors go on to test these conclusions further using in vitro differentiations, Seahorse assays, pharmacological inhibitors, and targeted quantification of specific metabolites and amino acids. Finally, the authors document reduced STAT3 and STAT1 phosphorylation in response to IL-21 and interferon (both type 1 and 2), respectively, when both glutaminolysis and mitochondrial pyruvate metabolism are prevented.

Strengths:

(1) The main strength of the manuscript is the overall breadth of experiments performed. Orthogonal experiments are performed using genetic models, pharmacological inhibitors, in vitro assays, and in vivo experiments to support the claims. Multiple antigens are used as test immunogens--this is particularly important given the differing results.

(2) B cell metabolism is an area of interest but understudied relative to other cell types in the immune system.

(3) The importance of metabolic flexibility and caution when interpreting negative results is made clear from this study.

Weaknesses:

(1) All of the in vivo studies were done in the context of boosters at 3 weeks and recall responses 1 week later. Primary responses, including germinal centers, may still be ongoing at 3 weeks after the initial immunization and defects in GCs may contribute to the findings. Nonetheless, the authors do check antibody levels prior to the boost, and it is likely that most of the observed defects in Gls/Mpc2-deficiency are driven by faulty recall responses.

Reviewer #3 (Public review):

Summary:

In their manuscript, the authors investigate how glutaminolysis (GLS) and mitochondrial pyruvate import (MPC2) jointly shape B cell fate and the humoral immune response. Using inducible knockout systems and metabolic inhibitors, they uncover a "synthetic auxotrophy": When GLS activity/glutaminolysis is lost together with either GLUT1-mediated glucose uptake or MPC2, B cells fail to upregulate mitochondrial respiration, IL 21/STAT3 and IFN/STAT1 signaling is impaired, and the plasma cell output and antigen-specific antibody titers drop significantly. This work thus demonstrates the promotion of plasma cell differentiation and cytokine signaling through parallel activation of two metabolic pathways. The dataset is technically comprehensive and conceptually novel, but some aspects leave the in vivo and translational significance uncertain.

Strengths:

(1) Conceptual novelty: the study goes beyond single-enzyme deletions to reveal conditional metabolic vulnerabilities and fate-deciding mechanisms in B cells.

(2) Mechanistic depth: the study uncovers a novel "metabolic bottleneck" that impairs mitochondrial respiration and elevates ROS and directly ties these changes to cytokine-receptor signaling. This is both mechanistically compelling and potentially clinically relevant.

(3) Breadth of models and methods: inducible genetics, pharmacology, metabolomics, seahorse assay, ELISpot/ELISA, RNA-seq, two immunization models.

(4) Potential clinical angle: the synergy of CB839 with UK5099 and/or hydroxychloroquine hints at a druggable pathway targeting autoantibody-driven diseases.

Comments on revised version.

Authors extensively modified the text with great care and provided new data e.g. Fig. 5. Collectively, this is convincing and hence, I have no further comments.

Author response:

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

We thank the referees for noting the substantive revisions and for the praise of the work. While we each have somewhat different weightings of likelihood, we feel the appraisals are fair and reasonable.

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

eLife Assessment

The authors addressed an important biological question, namely the role of glutamine metabolism in humoral responses, and they obtained solid conclusions. The strength of this study is that the authors used state-of-the-art transgenic mouse models together with in vitro analysis, thereby providing significant insights into the question posed. The following would strengthen the manuscript: i) adding more in-depth functionality/physiological relevance in the discussion part, and ii) regarding the experiments, the inclusion of more appropriate controls and a clearer and more accurate description of the methods.

We are grateful for the decision of the Editors to select this submission for in-depth peer review and to the Reviewing Editor and referees for the thoughtful and constructive comments.

We mostly agree with the specific comments and evaluation of strengths of what the work adds as well as with indications of limitations and caveats that apply to the breadth of conclusions. We have edited the text to be more clear and provide more details about certain aspects of the Methods and Legends. In addition, although we try to avoid Discussion sections that are unduly long or have flights of fancy, we will add to the Discussion as well as edit it for directness about potential relevance, basic explorations of mechanisms, and functionality.

The revised manuscript also contains new data, some of it dealing with comments of the referees, other additions representing work done while the manuscript was under review. While we would be inclined to do more, the sad practical problem is one of limits placed by both the absence of any grant funds and the institution's terminations (RIFs) of the two experimenters in the lab.

While we believe the original data interpretable as presented originally, up to a point it nonetheless is good to enhance scope or have even better data and add refinements about some of the technical issues. Ultimately, the question becomes "when is enough enough?"

In the detailed point-by-point response below, we outline changes prompted by the reviewers. We also comment on a few points more expansively that would be suitable for the paper itself, and offer some skepticism or disagreement, (longer and more detailed explanations.

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this manuscript, Cho et al. present a comprehensive and multidimensional analysis of glutamine metabolism in the regulation of B cell differentiation and function during immune responses. They further demonstrate how glutamine metabolism interacts with glucose uptake and utilization to modulate key intracellular processes. The manuscript is clearly written, and the experimental approaches are informative and well-executed. The authors provide a detailed mechanistic understanding through the use of both in vivo and in vitro models. The conclusions are well supported by the data, and the findings are novel and impactful. I have only a few, mostly minor, concerns related to data presentation and the rationale for certain experimental choices.

Detailed Comments:

(1) In Figure 1b, it is unclear whether total B cells or follicular B cells were used in the assay. Additionally, the in vitro class-switch recombination and plasma cell differentiation experiments were conducted without BCR stimulation, which makes the system appear overly artificial and limits physiological relevance. Although the effects of glutamine concentration on the measured parameters are evident, the results cannot be confidently interpreted as true plasma cell generation or IgG1 class switching under these conditions. The authors should moderate these claims or provide stronger justification for the chosen differentiation strategy. Incorporating a parallel assay with anti-BCR stimulation would improve the rigor and interpretability of these findings.

We edited the manuscript to be clear that total splenic B cells were used in this set-up figure and the rest of the paper. In addition, we performed new experiments to improve this "set-up figure (Fig. 1)" and moved the older data using alternative experimental conditions to a supplemental figure, Figure 1 - supplement 1. We also used new conditions that included styles of stimulating proliferation and differentiation - to foster an increased sense of generality. The findings in no way change the supported conclusions of the work. Specifically, we used mitogenic stimulation with anti-IgM ⁺ anti-CD40, all with BAFF, IL-4, and IL-5 in addition to the anti-CD40 stimulation of the original manuscript, bearing in mind excellent work from Aiba et al, Immunity 2006; 24: 259-268, and similar papers. In addition, we added a panel with representative flow cytometric profiles. These new data are presented in Figure 4 - supplement 1 (panels ae).

To be transparent and add to a more open public discussion (using the virtues of this forum), the senior author and colleagues would caution about whether any in vitro conditions exist that warrant complete confidence. That is the reason for proceeding to immunization experiments in vivo. That is not said to cast doubt on our own in vitro data - there are some experiments (such as those of Fig. 1a-c and associated Fig 1 - supplement 1) that only can be done in vitro or are better done that way (e.g., because of rapid uptake of early apoptotic B cells in vivo).

For instance: Well-respected papers use the CD40LB and NB21.2D9 systems to activate B cells and generate plasma cells. Those appear to be BCR-independent and yet continue in common use. [We found that these cellular systems (CD40LB; NB21.2D9) cannot be used in experiments with a.a. deprivation or the inhibitors due to effects on the engineered stroma-like cells.] In considering BCR engagement, Reth has published salient points about signaling and concentrations of the Ab, the upshot being that this means of activating mitogenesis and plasma cell differentiation (when the B cells are costimulated via CD40 or TLR (4 or 7/8) is also artificial. Moreover, although Aiba et al, Immunity 2006; 24: 259-268 is a laudable exception, one rarely finds papers using BAFF despite the strong evidence it is an essential part of the equation of B cell regulation in vivo and a cytokine that modulates BCR signaling - in the cultures.

(2) In Figure 1c, the DMK alone condition is not presented. This hinders readers' ability to properly asses the glutaminolysis dependency of the cells for the measured readouts. Also, CD138⁺ in developing PCs goes hand in hand with decreased B220 expression. A representative FACS plot showing the gating strategy for the in vitro PCs should be added as a supplementary figure. Similarly, division number (going all the way to #7) may be tricky to gate and interpret. A representative FACS plot showing the separation of B cells according to their division numbers and a subsequent gating of CD138 or IgG1 in these gates would be ideal for demonstrating the authors' ability to distinguish these populations effectively.

In the revised manuscript, we have added new experimental data (Figure 1).

We agree that exact placement of divisions and deconvolution by FlowJow is more fraught than might be thought from presentations in many or most papers. We include the data shown to the right as representative FACS plot(s) with old and new data that illustrate the gating on CTV fluorescence. With the representative examples pasted in here and presented in Fig 1 - supplement 1f, g of the revised manuscript, we will aver that using divisions 0-6, and ≥7 was and is entirely reasonable.

Ditto for DMK with normal glutamine. However, in the spirit of eLife transparency lacking in many other journals, this comparison is more fraught than the referee comment would make things seem. The concentration tolerated by cells is highly dependent on the medium and glutamine concentration, and perhaps on rates of glutaminolysis (due to its generation of ammonia). In practice, DMK becomes more toxic to B cells unless glutamine is low or glutaminolysis is restricted. Thus, the concentration of DMK that is tolerated and used in Fig. 1b, c can become toxic to the B cells when using the higher levels of glutamine in typical culture media (2 mM or more) - at which point the "normal conditions ⁺ DMK" "control" involves the surviving cells in conditions with far greater cell death and less population expansion than the "low glutamine ⁺ DMK". condition.

(3) A brief explanation should be provided for the exclusive use of IgG1 as the readout in classswitching assays, given that naïve B cells are capable of switching to multiple isotypes. Clarifying why IgG1 was preferentially selected would aid in the interpretation of the results.

On lines ~112-3 and ~182-5, we edited the text in light of the referee's suggestion that we focus the presentation of serologic data on IgG1 in the immunization experiments. We also rearranged figures and panels to be more explicit and harmonize. That said, and [Brief explanation - IgG1 provides the strongest signal and hence better signal/noise both in vitro and with the alum-based immunizations that are avatars for the adjuvant used in the majority of protein-based vaccines for humans. Perhaps for this reason, the majority of papers on molecular mechanisms seem only to analyze IgG1. Nonetheless, since molecular regulation can differ according to isotype, and the more pro-inflammatory mouse IgG2c is more pertinent to some forms of anti-pathogen immunity and some auto-immune disease models, we believe it valuable to retain these data in supplements to the related Figures.]

(4) The immunization experiments presented in Figures 1 and 2 are well designed, and the data are comprehensively presented. However, to prevent potential misinterpretation, it should be clarified that the observed differences between NP and OVA immunizations cannot be attributed solely to the chemical nature of the antigens - hapten versus protein. A more significant distinction lies in the route of administration (intraperitoneal vs. intranasal) and the resulting anatomical compartment of the immune response (systemic vs. lung-restricted). This context should be explicitly stated to avoid overinterpretation of the comparative findings.

We appreciate the positive assessment, and agree with the referee that it is possible the conditions of immune challenge or re-exposure may contribute to the observed differences. We edited the text of the revised manuscript accordingly [lines ~152-153; ~159-160]. Certainly, the difference in how the anti-ova response is elicited compared to the anti-NP response in the same mice or with a bit different an immunization regimen might be another factor - or the major factor - explaining why glutaminolysis was important after ovalbumin inhalations (used because emergence of anti-ova Ab / ASCs is suppressed by the NP hapten after NP-ova immunization) but not needed for the anti-NP response unless Slc2a1 or Mpc2 also was inactivated. Thank you prompting addition of this important caveat!

Nevertheless, it seems fair to note that in Figures 1 and 2, the ASCs and Ab are being analyzed for NP and ova in the same mice, albeit with the NP-specific components not being driven by the inhalations of ovalbumin. With that in mind, when one compares the IgG1 anti-NP ASC and Ab to those for IgG1 anti-ovalbumin (ASC in bone marrow; Ab), the ovalbumin-specific response was reduced whereas the anti-NP response was not. [lines ~171-172]

(5) NP immunization is known to be an inducer of an IgG1-dominant Th2-type immune response in mice. IgG2c is not a major player unless a nanoparticle delivery system is used. However, the authors arbitrarily included IgG2c in their assays in Figures 2 and 3. This may be confusing for the readers. The authors should either justify the IgG2c-mediated analyses or remove them from the main figures. (It can be added as supplemental information with proper justification).

We rearranged the Figure panels to move IgM and IgG2c data to Supplemental Figures (Figure 3 - supplements 1, 2, 4, 5 in the eLife system).

For purposes of public discourse, we note first that in contrast to the premise about weak IgG2c responses, the data [previously, Figure 3(c, g); now in the supplements] show substantial levels of NP-specific IgG2c. The referee is quite right that the class switching and in vitro ASC generation were done with IL-4 / IgG1-promoting conditions.

To assist readers, the revised manuscript takes note of the important role of IgG2c (mouse - IgG1 in humans) in controlling or clearing various pathogens as well as in autoimmunity [lines ~182-5]. Moreover, we continue to think that these measurements add substantial value both from the standpoint of providing a better sense of generality to the loss-of-function effects, and in considering potential ways of translating the findings to B cell-dependent autoimmune conditions such as systemic lupus erythematosus.

[As a scientific aside, we speculate that a greater or lesser IgG2c anti-NP response may arise due to different preparations of NP-carrier obtained from the vendor (Biosearch) having different amounts of TLR (e.g., TLR4) ligand. In any case, the points of presenting the IgG2c (and IgM) data were to push against the limiting boundaries of convention (which risks perpetuating a narrow view of potential outcomes) and make the breadth of results more apparent to readers.

(6) Similarly, in affinity maturation analyses, including IgM is somewhat uncommon. I do not see any point in showing high affinity (NP2/NP20) IgMs (Figure 3d), since that data probably does not mean much.

As noted in the reply immediately preceding this one, we appreciate this suggestion from the reviewer and moved the IgM and IgG2c to supplemental status.

Nonetheless, in collegial discourse we disagree a bit with the referee in light of our data as well as of work that (to our minds) leads one to question why inclusion of affinity maturation of IgM is so uncommon - as the referee accurately notes. Of course a defect in the capacity to class-switch is highly deleterious in patients but that is not the same as concluding that recall IgM or its affinity is of little consequence.

In some of the pioneering work back in the 1980's, Bothwell showed that NP- carrier immunization generated hybridomas producing IgM Ab with extensive SHM (~11% of the 18 lineages; ~ 1/3 of the IgM hybridomas) [PMID: 8487778], IgM B cells appear to move into GC, and there is at least a reasonable published basis for the view that there are GC-derived IgM (unswitched) memory B cells (MBC) that would be more likely, upon recall activation, to differentiate into ASCs. [As an example, albeit with the Jenkins lab anti-rPE response, Taylor, Pape, and Jenkins generated quantitative estimates of the numbers of Ag-specific IgM⁺ vs switched MBC that were GC-derived (or not). [PMID: 22370719]. While they emphasized that ~90% of IgM⁺ MBC appeared to be GC-independent, their data also indicated that ~1/2 of all GC-derived MBC were IgM⁺ rather than switched (their Fig. 8, B vs C; also 8E, which includes alum-PE). And while we immensely respect the referee, we are perhaps less confident that IgM or high-affinity Ag-specific IgM doesn't mean that much, if only because of evidence that localized Ab compete for Ag and may thus influence selective processes [PMCID: PMC2747358; PMID: 15953185; PMID: 23420879; PMID: 27270306].

(7) Following on my comment for the PC generation in Figure 1 (see above), in Figure 4, a strategy that relies solely on CD40L stimulation is performed. This is highly artificial for the PC generation and needs to be justified, or more physiologically relevant PC generation strategies involving anti-BCR, CD40L, and various cytokines should be shown.

In line with our response to point (1), we tested BCR-stimulated B cells (anti-CD40 plus anti-IgM with BAFF, IL-4, and IL-5, parallel to the analyses with anti-CD40 but no BCR engagement). These results align with and reinforce the utility of the data with anti-CD40 as the sole mitogen.

(8) The effects of CB839 and UK5099 on cell viability are not shown. Including viability data under these treatment conditions would be a valuable addition to the supplementary materials, as it would help readers more accurately interpret the functional outcomes observed in the study.

We added presentation of data that provide cues as to relative viability / cxmsurvival under the experimental conditions used.

[FSC X SSC as well as 7AAD or Ghost dye panels; we also generated new data that in[ further experiments scoring annexin V staining (see Fig 4 - supplement 1d, e, and Fig 5 - supplement 1e, f)].

(9) It is not clear how the RNA seq analysis in Figure 4h was generated. The experimental strategy and the setup need to be better explained.

Including text added at lines ~291-293 and ~582-585, the revised manuscript provides more information in the Results, Methods and Legend for Fig 4j-l. We agree entirely with the concern and apologize that in this and a few other instances we inadvertently sacrificed sufficiency of detail on the altar of attempting brevity.

[As a synopsis: In three temporally and biologically independent experiments, cultures were harvested 3.5 days after splenic B cells were purified and cultured as in the experiments of Fig. 4a-e. Total cellular RNA was prepared from the twelve samples (three replicates for each of four conditions - DMSO vehicle control, CB839, UK5099, and CB839 ⁺ UK5099), then analyzed by RNA-seq. RNA-seq data were initially processed using the pipeline described in the Methods. For panels g & h of Fig 4, DESeq2 was used to quantify and compare read counts in the three CB839 ⁺ UK5099 samples relative to the three independent vehicle controls and identify all genes for which variances yielded P<0.05. In Fig 4g, all such genes for which the difference was 'statistically significant' (i.e., P<0.05) were entered into the indicated Immgen tool and thereby mapped to the B lineage subsets shown in the figure panels (i.e., g, h). In (g), these are displayed using one format, whereas (h) uses the 'heatmap' tool in MyGeneSet.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigate the functional requirements for glutamine and glutaminolysis in antibody responses. The authors first demonstrate that the concentrations of glutamine in lymph nodes are substantially lower than in plasma, and that at these levels, glutamine is limiting for plasma cell differentiation in vitro. The authors go on to use genetic mouse models in which B cells are deficient in glutaminase 1 (Gls), the glucose transporter Slc2a1, and/or mitochondrial pyruvate carrier 2 (Mpc2) to test the importance of these pathways in vivo.

Interestingly, deficiency of Gls alone showed clear antibody defects when ovalbumin was used as the immunogen, but not the hapten NP. For the latter response, defects in antibody titers and affinity were observed only when both Gls and either Mpc2 or Slc2a1 were deleted. These latter findings form the basis of the synthetic auxotrophy conclusion. The authors go on to test these conclusions further using in vitro differentiations, Seahorse assays, pharmacological inhibitors, and targeted quantification of specific metabolites and amino acids. Finally, the authors document reduced STAT3 and STAT1 phosphorylation in response to IL-21 and interferon (both type 1 and 2), respectively, when both glutaminolysis and mitochondrial pyruvate metabolism are prevented.

Strengths:

(1) The main strength of the manuscript is the overall breadth of experiments performed. Orthogonal experiments are performed using genetic models, pharmacological inhibitors, in vitro assays, and in vivo experiments to support the claims. Multiple antigens are used as test immunogens--this is particularly important given the differing results.

(2) B cell metabolism is an area of interest but understudied relative to other cell types in the immune system.

(3) The importance of metabolic flexibility and caution when interpreting negative results is made clear from this study.

Weaknesses:

(1) All of the in vivo studies were done in the context of boosters at 3 weeks and recall responses 1 week later. This makes specific results difficult to interpret. Primary responses, including germinal centers, are still ongoing at 3 weeks after the initial immunization. Thus, untangling what proportion of the defects are due to problems in the primary vs. memory response is difficult.

We performed new experiments and added the data on differences prior to a boost [see below; new Fig 3d, e; etc].

(2) Along these lines, the defects shown in Figure 3h-i may not be due to the authors' interpretation that Gls and Mpc2 are required for efficient plasma cell differentiation from memory B cells. This interpretation would only be correct if the absence of Gls/Mpc2 leads to preferential recruitment of low-affinity memory B cells into secondary plasma cells. The more likely interpretation is that ongoing primary germinal centers are negatively impacted by Gls and Mpc2 deficiency, and this, in turn, leads to reduced affinities of serum antibodies.

We have edited the wording of the conclusion to add a possibility we consider unlikely and downplay a conclusion that MBCs bearing switched BCRs are affected once reactivated. [see lines ~221-230] We also have added citations pertaining to the topic, including work from the Victora lab which seems to put the point succinctly: "Recall GCs in mice consist almost entirely of naïve B cells, whereas recall antibodies derive overwhelmingly from memory B cells." [emphasis added] [PMID: 38838672; new ref #83]. While unclear as to the reasoning - as one looks at the data - and skeptical as to the accuracy of the referee's point (2), it suggests that the matter is open to reasonable doubt. In line with the point and the edits, we also have added citation of a bioRxiv preprint from the Victora lab, which touches on the concept of what one could call boost-induced reinvigoration of a pre-existing GC [new ref #82].

Beyond the textual changes, we performed a new series of experiments to investigate partially, and present the results in Fig 3d, e as well as Fig 3 - supplement 1d, e. Unfortunately, time before lab closure was an enemy both for the period between primary and recall immunizations in performance and multiple replication of work to extend that presented in Figure 3, panels g & h, and the related Supplemental Data (Fig 3 - supplements 4d, 5a-g). Unfortunately, it was not possible to do a longer-term memory experiment with recall immunization out at 8 weeks.

The intriguing concerns and questions of points 1 & 2 provide a springboard for consideration of generalizations and simplifications. Germinal center durability is not at all monolithic, and instead is quite variable**. It is true that in the literature (especially with the substantially different approach of transferring BCR-transgenic / knock-in versions of an NP-biased BCR) there may be meaningful pools of IgG1 and IgG2c GC B cells. The premise (cognitive bias, perhaps?) in our interpretation is that in our previous work we measured few if any GC B cells - NP-APC-binding or otherwise - above the background (non-immunized controls) three weeks after immunization with NP-ovalbumin in alum. While recognizing that the immunogen can matter, we note for the readers and referee that Fig. 1 of the Taylor, Pape, & Jenkins paper considered above [PMID: 22370719] reported 10-fold more Ag-specific MBCs than GC B cells at day 29 post-immunization (the point at which the boost/recall challenge was performed in our Figure 3g, h. [That work did not use NP-carrier in alum to immunize, or measure the anti-NP response.]

Viewing Fig. 3i from that perspective, the surmise of the comment is that a major contribution to the differences in both all-affinity and high-affinity anti-NP IgG1 (whose production requires differentiation into plasma cells) derived from the immunization at 4 wk stimulating persistent GC B cells as opposed to memory B cells.

The issue and question also relate to rates of output of plasma cells or rises in the serum concentrations of class-switched Ab. To this point, our prior experiences agree with the long-published data of the Kurosaki lab in Figure 3c of the Aiba et al paper noted above (Immunity, 2006) (and other such time courses). Readers can note that the IgG1 anti-NP response (alum adjuvant, as in our work) hits its plateau at 2 wk, and did not increase further from 2 to 3 wk. The most likely interpretation is that GC are on the decline and Ab production has reached its plateau by the time of the 2nd immunization in Fig. 3h.

Assuming we understand the comment and line of reasoning correctly, we also lean towards disagreeing with the statement " This interpretation would only be correct if the absence of Gls/Mpc2 leads to preferential recruitment of low-affinity memory B cells into secondary plasma cells. Our evidence shows that both low-affinity as well as high-affinity anti-NP Ab (IgG1) were reduced due to combined gene-inactivation after the peak primary response (Fig. 3h; also, see the new data in Fig 3 and Fig 3 - supplement 1). Recent papers show that affinity maturation is attributable to greater proliferation of plasmablasts with high-affinity BCR. Accordingly, the findings with loss of GLS and MPC function are quite consistent with the interpretation that much of the response after the second immunization draws on MBC differentiation into plasmablasts and then plasma cells, where the proliferative advantage of high-affinity cells is blunted by the impaired metabolism. Notwithstanding these issues, the revised manuscript includes the alternative, if less likely, interpretation proposed by the review [lines ~221-230].

**In some contexts, of course, especially certain viral infections or vaccination with lipid nanoparticles carrying modified mRNA, germinal centres are far more persistent; also, in humans even the seasonal flu vaccine

(3) The gating strategies for germinal centers and memory B cells in Supplemental Figure 2 are problematic, especially given that these data are used to claim only modest and/or statistically insignificant differences in these populations when Gls and Mpc2 are ablated. Neither strategy shows distinct flow cytometric populations, and it does not seem that the quantification focuses on antigen-specific cells.

The revised manuscript improves these aspects of the presentation, using old and new data. See Fig 3 - supplement 3a, c; Fig 3 - supplement 4a. We note for readers that many other papers in the best journals show plots in which the separation of, say, GC-Tfh from overall Tfh is based on cut-off within what essentially is a continuous spectrum of emission as adjusted or compensated by the cytometer (spectral or conventional).

The revised manuscript presents results from new experiments that deal with the subset of GC B cells whose BCRs bind NP-APC with enough affinity to retain a positive signal after washing. These new data are presented in Fig 3 - supplement 3c & 3e. In practice, the new findings suggest that the metabolic requirement applied more to the NP-binding B cells than the overall GC B cell population.

(4) Along these lines, the conclusions in Figure 6a-d may need to be tempered if the analysis was done on polyclonal, rather than antigen-specific cells. Alum induces a heavily type 2-biased response and is not known to induce much of an interferon signature. The authors' observations might be explained by the inclusion of other ongoing GCs unrelated to the immunization.

We apologize for ambiguity or insufficient clarity and, as noted above, have edited the text to be more clear that the in vitro experiments do not represent GC B cells and that the RNA-seq data were from experiments that did not involve alum and were not an Ag (SRBC)-specific subset.

New text in the Results, an expanded Legend, and tweaking the Methods make it more readily clear that the RNA-seq data (and hence the GSEA) involved immunizations with SRBC (not the alum / NP system. That said, we note that the hapten-carrier experiments in which the immunogen was adjuvantized with alum actually generated a robust IgG2c (type 1-driven) response along with the type 2-enhanced IgG1 response, in line with what has been reported by others with alum-adjuvanted vaccination.

Reviewer #3 (Public review):

Summary:

In their manuscript, the authors investigate how glutaminolysis (GLS) and mitochondrial pyruvate import (MPC2) jointly shape B cell fate and the humoral immune response. Using inducible knockout systems and metabolic inhibitors, they uncover a "synthetic auxotrophy": When GLS activity/glutaminolysis is lost together with either GLUT1-mediated glucose uptake or MPC2, B cells fail to upregulate mitochondrial respiration, IL 21/STAT3 and IFN/STAT1 signaling is impaired, and the plasma cell output and antigen-specific antibody titers drop significantly. This work thus demonstrates the promotion of plasma cell differentiation and cytokine signaling through parallel activation of two metabolic pathways. The dataset is technically comprehensive and conceptually novel, but some aspects leave the in vivo and translational significance uncertain.

Strengths:

(1) Conceptual novelty: the study goes beyond single-enzyme deletions to reveal conditional metabolic vulnerabilities and fate-deciding mechanisms in B cells.

(2) Mechanistic depth: the study uncovers a novel "metabolic bottleneck" that impairs mitochondrial respiration and elevates ROS, and directly ties these changes to cytokinereceptor signaling. This is both mechanistically compelling and potentially clinically relevant.

(3) Breadth of models and methods: inducible genetics, pharmacology, metabolomics, seahorse assay, ELISpot/ELISA, RNA-seq, two immunization models.

(4) Potential clinical angle: the synergy of CB839 with UK5099 and/or hydroxychloroquine hints at a druggable pathway targeting autoantibody-driven diseases.

We agree and thank the referee for the positive comments and this succinct summary of what we view as contributions of the paper.

Weaknesses:

(1) Physiological relevance of "synthetic auxotrophy"

The manuscript demonstrates that GLS loss is only crippling when glucose influx or mitochondrial pyruvate import is concurrently reduced, which the authors name "synthetic auxotrophy". I think it would help readers to clarify the terminology more and add a concise definition of "synthetic auxotrophy" versus "synthetic lethality" early in the manuscript and justify its relevance for B cells.

We edited the Abstract, Introduction, and Discussion to try to do better on this score. Conscious of how expansive the prose and data are even in the original submission, we appear to have taken some shortcuts that we will try to rectify or at least mitigate. Thank you for highlighting this need to improve on key concepts !!

Specifically, the revised text expands a bit on the notion that synthetic auxotrophy represents effects on differentiation that go beyond additional mechanisms of reducing division efficiency and a modest impact on selective death. [see the 10th - 11th lines in Abstract and lines ~84-85, Introduction] Even though decreased population expansion is observed and new evidence supports a model in which the altered metabolism contributes to enhanced death in vivo, at equal division numbers the frequency of CD138⁺ progeny is lower once glutaminolysis and mitochondrial pyruvate are reduced by either genetic or pharmacological means.

This comment of the review raises interesting semantic questions about what represents "physiological relevance". The fundamental point is to explore a basic science question - what, if any, are limits to metabolic flexibility? In principle, shouldn't B cells be able to use fatty acid metabolism to generate enough ATP and provide the backbones for biosynthesis during growth? Put a different way, the point is that a basic curiosity to understand why decreasing glucose influx did not have an even more profound effect than what was observed, combined with curiosity as to why glutaminolysis was dispensable in relatively standard vaccine-like models of immunize/boost, provided a springboard to identification of new vulnerabilities. The manuscript shows one physiological limitation (and hence vulnerability). Be that as it may, the revised text of the Discussion section more clearly addresses this issue (lines ~531-549 at the end of the Discussion).

While the overall findings, especially the subset specificity and the clinical implications, are generally interesting, the "synthetic auxotrophy" condition feels a little engineered.

CAR-T cells are 'a little engineered' (or more than a little) and yet they do seem to have had an impact on understanding the centrality of B cells in various autoimmune conditions as well as in the direction of cancer therapy research. So it is a matter of balancing this perspective of the referee against the strengths they highlight in points 1, 2, and 4. In editing the revision, we try to expand and be more explicit about this in the Discussion of the revised manuscript.

In brief, even were the money not all gone, we would not believe that expanding the heft of this already rather large manuscript and set of data would be appropriate. As matters stand, a basic new insight about metabolic flexibility and its limits leads to evidence of a way to reduce generation of Ab and a novel impairment of STAT transcription factor induction by several cytokine receptors. The vulnerability that could be tested in later work on B cell-dependent autoimmunity includes the capacity to test a compound that already has been to or through FDA phase II in patients together with an FDA-approved standard-of-care agent.

Therefore, the findings strongly raise the question of the likelihood of such a "double hit" in vivo and whether there are conditions, disease states, or drug regimens that would realistically generate such a "bottleneck".

Hence, the authors should document or at least discuss whether GC or inflamed niches naturally show simultaneous downregulation/lack of glutamine and/or pyruvate. The authors should also aim to provide evidence that infections (e.g., influenza), hypoxia, treatments (e.g., rapamycin), or inflammatory diseases like lupus co-limit these pathways.

Again, we appreciate some 'licensing' to be more expansive and explicit, and will try to balance editing in such points against undue tedium or tendentiously speculative length in the Discussion. In particular, we will note that a clear, simple implication of the work is to highlight an imperative to test CB839 in lupus patients already on hydroxychloroquine as standard-of-care, and to suggest development of UK5099 (already tested many times in mouse models of cancer) to complement glutaminase inhibition.

As backdrop, we note that the failure to advance imaging mass spectrometry to the capacity to quantify relative or absolute (via nano-DESI) concentrations of nutrients in localized interstitia is a critical gap in the entire field. Techniques that sample the interstitial fluid of tumour masses or in our case LN as a work-around have yielded evidence that there can be meaningful limitations of glucose and glutamine, but it needs to be acknowledged that such findings may be very model-specific and, as can be the case with cutting-edge science, are not without controversy. That said, yes, we had found that hypoxia reduced glutamine uptake but given the norms of focused, tidy packages only reported on leucine in an earlier paper [PMID27501247; PMCID5161594].

Beyond all that, another impetus to and inspiration for these experiments stems from quite data that we generated in a model of short-term protein-restricted diet (loosely akin to kwashiorkor in humans), based on an excellent publication showing that such a regimen quickly led to lower circulating glutamine and mTORC1 activity (**). In brief, we found that a low-protein diet did, in our experiments, preferentially lower glutamine but - importantly - led to reduced Ab responses (which would match what we have modeled here). The findings were not a well-enough connected evidentiary component to include in the "story" but I'll append slides with the relevant data to this Response to Reviews for the referee's perusal (and anyone else who reads this online discourse).

It would hence also be beneficial to test the CB839 + UK5099/HCQ combinations in a short, proof-of-concept treatment in vivo, e.g., shortly before and after the booster immunization or in an autoimmune model. Likewise, it may also be insightful to discuss potential effects of existing treatments (especially CB839, HCQ) on human memory B cell or PC pools.

We certainly agree that the suggestions offered in this comment are important next steps and the right approach to test if the findings reported here translate toward the treatment of autoimmune diseases that involve B cells, interferons, and pathophysiology mediated by auto-Ab. As practical points, performance and replication of such studies would take more time than the year allotted for return of a revised manuscript to eLife and in any case neither funds nor a lab remain to do these important studies.

Concrete evidence for our concurrence was embodied in a grant application to NIH that was essential for keeping a lab and doing any such studies. [We note, as a suggestion to others, that an essential component of such studies would be to test the effects of these compounds on B cells from patients and mice with autoimmunity]. Perhaps unfortunately for SLE patients, the review panelists did not agree about the importance of such studies. However, it can be hoped that the patent-holder of CB839 (and perhaps other companies developing glutaminase inhibitors) will see this peer-reviewed preprint and the public dialogue, and recognize how positive results might open a valuable contribution to mitigation of diseases such as SLE.

(2) Cell survival versus differentiation phenotype

Claims that the phenotypes (e.g., reduced PC numbers) are "independent of death" and are not merely the result of artificial cell stress would benefit from Annexin-V/active-caspase 3 analyses of GC B cells and plasmablasts. Please also show viability curves for inhibitor-treated cells.

This comment leads us to see that the wording on this point may have been overly terse in the interests of brevity, and thereby open to some odd misunderstanding. The CD138⁺ events are scored among VIABLE CELLS, so a decrease in the %CD138⁺ at similar division number represents an effect independent from (or beyond) survival and division-counting. Accordingly, we expanded the text of the Abstract and elsewhere in the manuscript, to be more clear. In addition, we added data from new experiments addressing death in vitro and among GC-phenotype B cells in vivo. To clarify in this public context, it is not that an increase in death (along with the reported decrease in cell cycling) can be or is excluded. The point is that beyond any such increase, and taking into account division number (since there is evidence that PC differentiation and output numbers involve a 'division-counting' mechanism), the frequencies of CD138⁺ cells and of ASCs among the viable cells are lower, as is the level of Prdm1-encoded mRNA even before the big increase in CD138⁺ cells in the population.

(3) Subset specificity of the metabolic phenotype

Could the metabolic differences, mitochondrial ROS, and membrane-potential changes shown for activated pan-B cells (Figure 5) also be demonstrated ex vivo for KO mouse-derived GC B cells and plasma cells? This would also be insightful to investigate following NP-immunization (e.g., NP+ GC B cells 10 days after NP-OVA immunization).

We performed a series of new experiments to have enough biologically independent replications for meaningful and statistical analyses. The new results, added in as Fig 5 - supplement 1, showed that the combined pathway interruption by loss-of-function increased ROS, mtROS, and death (annexin V / 7AAD) upon analyzing GCphenotype B cells immediately upon harvest. The findings align well with the data in Fig 5 (cultured B cells).

(4) Memory B cell gating strategy

I am not fully convinced that the memory-B-cell gate in Supplementary Figure 2d is appropriate. The legend implies the population is defined simply as CD19+GL7-CD38+ (or CD19+CD38++?), with no further restriction to NP-binding cells. Such a gate could also capture naïve or recently activated B cells. From the descriptions in the figure and the figure legend, it is hard to verify that the events plotted truly represent memory B cells. Please clarify the full gating hierarchy and, ideally, restrict the MBC gate to NP+CD19+GL7-CD38+ B cells (or add additional markers such as CD80 and CD273). Generally, the manuscript would benefit from a more transparent presentation of gating strategies.

In considering the referee's viewpoint, we further expanded the supplemental data displays to include more of the gating and analytic schemes, which we believe should mitigate one concern noted here. In addition, we now include flow data from the non-immunized control mice that had been analyzed concurrently in the experiments.

Third and finally, we performed new experiments and analyses in which the focus was the frequencies of memory-phenotype (IgD^neg GL7^neg CD38⁺ / CD38^hi aka CD38⁺⁺) NPbinding B cells after immunization. While this time, as opposed to previously, the NP-APC staining met our standard for interpretability, the gist of the findings was that the two independent repeat experiments yielded a split decision and a degree of variability. With time being up due to the funds running out, we have elected to delete the issue and the data panel in question.

That said, it bears noting that in the previous figure panel, the labeling indicated that the gating included the important criterion that cells be IgD^neg, which excludes the vast majority of naive B cells but measures memory-phenotype B cells independent from consideration of whether or not they were NP-binding.

[In principle marginal zone (MZ) B cells might fall within this gate. However, the MZ B population is unlikely to explain the differences shown.

(5) Deletion efficiency - [The] mRNA data show residual GLS/MPC2 transcripts (Supplementary Figure 8). Please quantify deletion efficiency in GC B cells and plasmablasts.

Even were there resources to do this, the degree of reduction in target mRNA (Gls; Mpc2) renders this question superfluous. To the best of our understanding, the proteins (for which there might be some phenotypic lag) are translated from RNA. Might there be a small subpopulation of B cells (or their PC progeny) with only one, or even neither, allele converted from fl to D? Yes, but they would be a minor subset in light of the magnitude of mRNA reduction, in contrast to our published observations with Slc2a1. As to plasmablasts and plasma cells, the pre-existing populations make such an analysis misleading, while the scarcity of such cells recoverable with antigen capture techniques is so low as to make both RNA and genomic DNA analyses questionable. We also refer readers to the supplemental figure that presents the results of experiments testing the issue one might infer from the question about extents of deletion in PC (i.e., how much counter-selection might have occurred by the PC stage).

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eLife Assessment

This interesting study adapts machine learning tools to analyze movements of a chromatin locus in living cells in response to serum starvation. The machine learning approach developed is useful, the experiments are well controlled, and the data are solid. The study will benefit from future work testing predictions by perturbation experiments. This work will be of interest to those studying chromosome biology and gene expression patterns.

Reviewer #1 (Public review):

Summary:

Redchuk et al. explore the dynamic properties of chromatin upon serum starvation using machine learning approaches. They use CRISPR-tagging to visualize a region on chromosome 1 in human cells and show that in their system, chromosome 1, but not the previously reported chromosomes 10, 13, and X, undergo a change in radial position upon serum starvation. Live cell imaging showed a position change towards the periphery after serum starvation. They then apply a machine learning algorithm for the analysis of the imaging data, which reveals changes in nuclear area during serum starvation and longer displacements of the chromosome 1 locus near the nuclear periphery. Differential behavior of homologues is also reported.

Strengths:

(1) The study of chromatin dynamics is an interesting and important area of research.

(2) The use of machine learning approaches to analyze live cell imaging data is timely.

(3) With serum starvation, the authors use a simple, well-controllable model system.

Weaknesses:

(1) This study provides limited new insight into chromatin dynamics.

(2) It was not immediately evident what the use of machine learning approaches added to this study. It appears that the main conclusions could have been reached by conventional analysis.

Comments on revised version:

The authors have added some technical information, but have not made any major efforts to clarify some of the major points or to strengthen the paper. The degree of advance remains limited and several conclusions are not convincingly supported by the presented data.

Reviewer #2 (Public review):

Summary:

The study demonstrates that CRISPR-Sirius provides a powerful approach to investigating chromosome dynamics in living cells during environmental stress. By focusing on serum starvation, the authors show that this process induces global nuclear changes, including a reduction in nuclear area and increased morphological dynamism, while at the same time driving specific reorganization of chromosome 1. Chromosome 1 relocates toward the nuclear periphery and displays distinctive patterns of motion, maintaining overall motility but punctuated by occasional long-distance displacements, particularly near the nuclear envelope. Importantly, the analysis reveals that homologous copies of chromosome 1 do not behave uniformly: peripheral loci become more mobile and responsive to starvation, whereas central homologs remain comparatively stable, often associated with nucleolar subcompartments. By integrating live imaging with machine learning and explainable AI analysis, the study highlights the complexity of nuclear organization and provides valuable insights into how chromosome-specific and locus-specific responses to stress are orchestrated within the three-dimensional nuclear landscape.

Strengths:

The study uses live-cell imaging to investigate the dynamics of loci during starvation. Live-cell tracking and data interpretation are carried out using machine learning and AI models, which is a major strength.

Weaknesses:

The manuscript is at times difficult to follow, partly because the methodological descriptions are highly specialized, especially for non-expert biologists. In addition, the observations are not tested for a mechanistic basis. Experiments that could provide deeper insights are missing, for example, why chromosome 1 moves, why the peripheral homologue dislocates, or why a "long jump" is observed at the periphery even though the speed of the loci does not change. It is also unclear whether a displacement of 0.5 μm is functionally meaningful.

Comments on revised version:

The authors have added some technical information and provided a better discussion of the data, but beyond that, they have not strengthened the conclusions. The observations are not supported by any perturbation assays.

Author response:

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

eLife Assessment

This interesting study adapts machine learning tools to analyze movements of a chromatin locus in living cells in response to serum starvation. The machine learning approach developed is useful, the experiments are well controlled, and the data are solid. The study would be greatly strengthened by testing key predictions made using perturbation experiments. This work will be of interest to those studying chromosome biology and gene expression patterns.

We thank eLife for this nice assessment. We indeed believe that the presented machine learning approach will be useful for many types of research questions, and this was the main aim of this manuscript.

Public Reviews:

Reviewer #1 (Public review):

Summary:

Redchuk et al. explore the dynamic properties of chromatin upon serum starvation using machine learning approaches. They use CRISPR-tagging to visualize a region on chromosome 1 in human cells and show that in their system, chromosome 1, but not the previously reported chromosomes 10, 13, and X, undergo a change in radial position upon serum starvation. Live cell imaging showed a position change towards the periphery after serum starvation. They then apply a machine learning algorithm for the analysis of the imaging data, which reveals changes in nuclear area during serum starvation and longer displacements of the chromosome 1 locus near the nuclear periphery. Differential behavior of homologues is also reported.

Strengths:

(1) The study of chromatin dynamics is an interesting and important area of research.

(2) The use of machine learning approaches to analyze live cell imaging data is timely.

(3) With serum starvation, the authors use a simple, well-controllable model system.

Weaknesses:

(1) This study only provides limited new insight into chromatin dynamics.

We respectfully disagree with this conclusion. To the best of our knowledge, our study is the first to provide any insights into chromatin dynamics upon serum starvation. Previous studies are solely based on studies in fixed cells, and the dynamics have remained unexplored. Moreover, for example the notion that homologous chromosomes show differential dynamic behavior is novel and will likely have implications and relevance to many chromatin-based processes beyond the example studied here.

(2) It was not immediately evident what the use of machine learning approaches added to this study. It appears that the main conclusions could have been reached by conventional analysis.

First, we would like to point out that the other reviewer found our machine learning analysis pipeline a major strength of our manuscript. Indeed, analyzing single features and assessing their impact on the studied phenomenon could have been achieved relatively easily by conventional analysis. However, this analysis would have ignored the interactions (some of which were not intuitively obvious) between different features and thereby limited the knowledge gain from the experiment.

Unbiased analysis of the interactions between the different features would have been already very difficult and time-consuming with conventional approaches. We believe that our analysis pipeline, especially with the Shapley values, addresses the key issue of combinatorial explosion prominent to multiparametric data, such as imaging data, and helps the researcher to navigate complex datasets.

(3) There are several specific technical points:

(a) It was not clear what the CRISRP-Sirius probes actually labelled. The chromosome 1 sgRNA sequence is provided, but I could not find information as to which region(s) of the chromosome are actually labelled (size, location, etc.).

We have added a schematic as Supplementary Figure 1A to show the region of the chromosome that is labelled. In addition, the target sequence, together with the relevant references can be found in the Materials and methods (page 16). Please see also below Reviewer #1 (Recommendations for the authors) point 4a.

(b) The authors visualize a relatively small region of chromosome 1 but make conclusions regarding the entire chromosome. Additional probes on the same chromosome should be used.

Related to this point, the discussion of why the authors are unable to reproduce the prior findings of relocation of chromosomes 10, 13, and X is not satisfying. It would be worth comparing the FISH-based painting of entire chromosomes, which generated the results suggesting relocation of these chromosomes, with the point-labelling method used here.

We agree that our approach to labeling chromosome 1 is very different than the FISH-based probes utilized before. However, we also feel that we discuss this aspect, and the difference between our and previous results, which may also stem from the used cell model, in quite a detail in the first paragraph of the results (page 4). Also, we are very careful throughout the manuscript to indicate that here we study the dynamics of a specific chromosome loci, not the entire chromosome, and have further amended the text to emphasize this. In the future, it would be very interesting to study the dynamics of also other loci of chromosome 1. As indicated also below in response to reviewer 2, we have failed to identify further gRNAs that would reliably and reproducibly label further chromosome 1 loci, suggesting that we would need to change the labeling system entirely. Unfortunately, this is not in the scope of this manuscript. Please see also below Reviewer #1 (Recommendations for the authors) point 1.

(c) The study lacks controls. Since in their hands chromosomes 10, 13, and X do not change position, they should be used as a negative control in all experiments demonstrating a shift in the location of chromosome 1.

We disagree that our study lacks controls, since we use telomeres as controls throughout the manuscript. Please see also below Reviewer #1 (Recommendations for the authors) point 2,3.

(d) I did not find information about the spatial or temporal resolution of the imaging modality. This is important to assess whether the observed changes in position, relative to time, are meaningful.

To estimate the spatial resolution, we have added new data using fixed cells (Supplementary figure 1E; corresponding text in results on page 5); temporal resolution is indicated in Materials and methods (page 17). Please see also below Reviewer #1 (Recommendations for the authors) point 4d.

(e) The authors analyze surprisingly early timepoints (up to 40 minutes) of serum starvation. Would these results look different if longer serum starvation timepoints of several hours were analyzed?

We chose to analyze early time points of serum starvation based on the previous literature reporting the chromosome relocation within the first 15 minutes of starvation. Indeed, the results might look very different later during serum starvation, since we already observe differences between 0-20 min vs 20-40 min into starvation (see for example Figure 5A-D). Analyzing further time points is not in the scope of this manuscript.

(f) The authors can do a better job of explaining what the biological meaning of the various parameters (DistR, TDist, etc.) they measure is.

We have amended Table 1 to describe the measured features more clearly. Please see also below Reviewer #1 (Recommendations for the authors) point 4e.

(g) I did not understand the reasoning for the authors' conclusion of differential behavior of homologues. Please explain this better, or idealy use more direct labeling methods that identify the individual homologues.

The differential behavior of homologues is best demonstrated in Figure 6H, which shows that in serum-containing media, the peripheral homolog has equal probability of being faster or slower compared to its homolog. However, the distribution changes upon starvation, with the peripheral loci being more frequently the faster homolog. We completely agree that further studies are needed to understand this phenomenon better, but changing the labeling method is not in the scope of this manuscript.

(h) In many figures, statistical analysis of the data is missing, including, but not limited to, Figures 1B, C, G, Figures 4, 5, 6.

We have added a Supplementary table to include inferential statistics. See also below Reviewer #1 (Recommendations for the authors) point 4b.

(i) No information is provided throughout the manuscript as to how many cells were analyzed in each experiment. This should be indicated in every figure legend.

The number of analyzed loci or nucleus is indicated in every figure. See also below Reviewer #1 (Recommendations for the authors) point 4c.

Reviewer #2 (Public review):

Summary:

The study demonstrates that CRISPR-Sirius provides a powerful approach to investigating chromosome dynamics in living cells during environmental stress. By focusing on serum starvation, the authors show that this process induces global nuclear changes, including a reduction in nuclear area and increased morphological dynamism, while at the same time driving specific reorganization of chromosome 1. Chromosome 1 relocates toward the nuclear periphery and displays distinctive patterns of motion, maintaining overall motility but punctuated by occasional long-distance displacements, particularly near the nuclear envelope. Importantly, the analysis reveals that homologous copies of chromosome 1 do not behave uniformly: peripheral loci become more mobile and responsive to starvation, whereas central homologs remain comparatively stable, often associated with nucleolar subcompartments. By integrating live imaging with machine learning and explainable AI analysis, the study highlights the complexity of nuclear organization and provides valuable insights into how chromosome-specific and locus-specific responses to stress are orchestrated within the three-dimensional nuclear landscape.

Strengths:

The study uses live-cell imaging to investigate the dynamics of loci during starvation. Livecell tracking and data interpretation are carried out using machine learning and AI models, which is a major strength.

Weaknesses:

The manuscript is at times difficult to follow, partly because the methodological descriptions are highly specialized, especially for non-expert biologists. In addition, the observations are not tested for a mechanistic basis. Experiments that could provide deeper insights are missing, for example, why chromosome 1 moves, why the peripheral homologue dislocates, or why a "long jump" is observed at the periphery even though the speed of the loci does not change. It is also unclear whether a displacement of 0.5 μm is functionally meaningful.

We appreciate the comment about the readability of our manuscript, and have seriously evaluated this point. We also completely agree that it would be interesting and important to understand the mechanistic and functional basis of the observed changes in chromatin dynamics take place upon serum starvation. However, we feel that it is not in the scope of the present manuscript. See also below Reviewer #2 (Recommendations for the authors) points 3,7-11.

Recommendations for the authors:

Reviewing Editor Comments:

I would like to first offer my congratulations on a very interesting study; second, I would like to encourage you to test a few key predictions using a perturbation experiment. Two reviewers with deep expertise in this area were supportive of the work, and both noted that such an addition would greatly increase the impact and visibility of this work in the field. I welcome a revision that addresses this seminal point. Thank you for sending your work to eLife!

We thank eLife for the positive assessment. We have aimed to address all of the reviewers comments and suggestions. However, we feel that some of the suggestions are not in the scope of this particular manuscript, since they would require setting up a different chromatin labeling system.

Reviewer #1 (Recommendations for the authors):

The following experiments would strengthen the study:

(1) Please label additional regions on chromosome 1 so as not to rely on a single point to represent the behavior of the entire chromosome.

This is an excellent suggestion, but unfortunately, despite our extensive efforts, we have failed to identify further gRNAs that would reliably label chromosome loci with the CRISPR-Sirius system. Changing the labeling system is not in the scope of the presented manuscript.

(2) Please use chromosomes 10, 13, or X as a negative control since these chromosomes do not change position in the authors' hands.

(3) Please compare the behavior of the homologues to that of either random loci or control loci on 10, 13, or X to assess whether the differential behavior observed for chromosome 10 is a specific effect.

Related to points 2 and 3, we opted to use telomeres as controls in this study. Throughout the manuscript, the behavior of chromosome 1 loci is compared to telomeres, demonstrating the specific effect of serum starvation on chr 1. For example, Figure 5A and 5B show that when analyzing mean locus displacement, chr1 and telomeres show the opposite behavior.

(4) In addition:

(a) Please provide detailed information on the sequence and location of the probes used.

We have added a schematic showing the location of the probes as Supplementary Figure S1A. In addition, the sequences are indicated in Materials and methods (page 16).

(b) Please provide a statistical analysis in all graphs.

To make statistical analysis more comprehensive, we have added supplementary table 1, showing the results of inferential statistics, namely, two-sided Mann-Whitney (MW) U-test. Descriptive statistics data are shown on figures as kernel density estimation, confidence intervals and bootstrapped changes distributions. See also below Reviewer #2 (Recommendations for the authors) point 5.

(c) Please provide throughout the manuscript in each figure legend information as to how many cells were analyzed in each experiment.

The number of analyzed loci (or nucleus) is indicated in each graph.

(d) Please provide information on the spatial and temporal resolution of the imaging modality.

The imaging settings are indicated in Materials and methods, including the temporal resolution of 0.25 frames per second (page 17). To estimate spatial resolution, and especially its relationship with the observed repositioning of the chromosome loci, we performed experiments in fixed cells, using an optically identical set-up as utilized for live imaging. Unfortunately, the microscope utilized for live imaging was taken out of use by the core facility after submission of the original draft of this manuscript, but we used a microscope with essentially a similar set-up. The data from fixed cells is now presented as Supplementary figure 1E and discussed in results on page 5. This analysis indicates that the change in minimal distance to the nuclear edge, reported in our study under serum starvation in live samples (0.32 and 0.5 micron), is more than one order of magnitude above the static error.

(e) Please better explain what the various measured parameters mean in biological terms.

We have amended Table 1 to provide better explanation of the measured parameters.

(f) Please add a scale bar to Figure 6I.’

Scale bar has been added to figure 6I.

Reviewer #2 (Recommendations for the authors):

Major points:

(1) SHAP analysis identified nuclear area (MA) and its change (sA) as the most predictive features of starvation state, while motility features (MD, MaxD, TD) showed strong interactions with nuclear morphology. Discrete features, such as displacement outliers and homolog subclassification by speed/proximity, influenced classification, particularly in MLP models. Could the authors clarify why morphological and motility features act in combinatorial and context-dependent ways? A biological interpretation of this interdependence would strengthen the study.

Unfortunately, we do not have a good biological interpretation for this. The fact that some interactions are context-dependent indicates that there could be subpopulations of cells/analyzed loci. For example, we found that the predictive value of nuclear area was high in a subgroup of low motility loci (Figure 4F and Supplementary figure 4D-F). We do not believe that adding more speculation would strengthen the study.

(2) The manuscript shows that chromosome 1 moves toward the periphery within the first 20-40 minutes of serum withdrawal. However, it remains unclear whether the locus eventually "touches" the periphery and whether it subsequently stabilizes or retracts. It would be valuable to compute the time point of minimal nuclear distance and examine whether this is transient or sustained.

With the experimental set-up utilized here, we imaged the loci for only two minutes at random time point within the first 40 minutes of the starvation. Hence extracting the time point of minimal nuclear distance is not meaningful from this dataset. As we discuss in the manuscript, following the dynamics of the same locus for longer periods of this would be very interesting in the future. However, this is not in the scope of the present manuscript.

(3) The manuscript is at times difficult to follow, partly because methodological descriptions are highly detailed in the main text. Consider moving more of the methodological content into Supplementary Methods and emphasizing the main results and interpretations in the main text for clarity.

We have carefully evaluated this point. Most methodological descriptions in the manuscript relate to the machine learning models and their explanation with SHAP. As we feel that this combination is an essential part of the manuscript, and likely the aspect that can have widest impact beyond chromatin dynamics studies, we feel that the background and our reasoning related to the chosen methods are important.

(4) The distinction between the first 20 minutes and the latter 40-minute window is intriguing. Could these different time scales be paralleled with early versus delayed gene expression responses to serum starvation? A discussion of this temporal connection would add biological depth.

This is an intriguing idea, and we have added a short note on this in the discussion (page 13). However, as we do not know how the U2OS cells utilized here respond transcriptionally to serum starvation, we are hesitant to speculate too much.

(5) If the observed interpretations are robust, could this be demonstrated more explicitly through statistical principles or reproducibility tests across independent datasets?

To provide further evidence of the robustness of our findings, we have 1) added new data to estimate the spatial resolution (Supplementary figure 1E) and 2) expand the statistical analysis as supplementary table 1. Regarding the spatial resolution (see also the response to reviewer 1), our experiments on fixed cells demonstrate that the change in minimal distance to the nuclear edge, reported in our study under serum starvation in live samples (0.32 and 0.5 micron), is more than one order of magnitude above the static error. Descriptive statistics data are shown on figures as kernel density estimation, confidence intervals and bootstrapped changes distributions. To make statistical analysis more comprehensive, we added a supplementary table, showing the results of inferential statistics, namely, two-sided Mann-Whitney (MW) U-test. MW test was used as a non-parametric statistic, with null hypothesis assuming the samples are coming from the same distribution. Null hypothesis was rejected at the p-value below 0.05. In most cases (bold font in table) MW test results were in accordance with the descriptive statistics confirming the conclusions in the study. In case of exceptions (MD, TD for telomeres and TDist), the results were reported, for example, as an “appearing trend” to reflect descriptive statistics while highlighting certainty levels.

(6) Figure labeling is difficult to follow. Please include abbreviation explanations directly in the figure panels or legends for clarity.

Abbreviations have been added to figure legends. Adding them to figures themselves would have made the figures too busy.

(7) The manuscript reports higher displacement at the nuclear periphery. Can the authors explain why displacement amplitudes increase near the periphery and how this relates to nuclear architecture?

We speculate in the manuscript (results, page 11; discussion, page 14) that actually the lower displacement observed with the central locus may, at least partially, result from anchoring this locus to the nucleolus (Fig 6I). Nevertheless, alternative explanations, such as differences in transcriptional and/or chromatin states may exist (see also the response to point 11), and this is now mentioned in the discussion (page 14).

(8) How is the movement of chromosome 1 directed specifically toward the periphery, rather than being random fluctuations? This point requires clarification.

This is an important question, but unfortunately our data does not provide an answer to this, and suggesting any mechanism would be pure speculation. Nevertheless, our results agree with previous studies utilizing fixed cells that also demonstrated movement of chromosome 1 towards nuclear periphery (Mehta et al., 2010), arguing against random fluctuation.

(9) Only chromosome 1, and not the other tested chromosomes, undergoes this relocalization. Could the authors elaborate on why some chromosomes but not others display this behavior?

Previous studies (Mehta et al., 2010) utilizing chromosome paints in fixed cells actually show the relocalization of several chromosomes upon serum starvation. The fact that we observed the relocalization of only chr1 loci is likely due to the labeling method and/or the cell model utilized in this study. This is quite explicitly discussed in the first paragraph of results (page 4).

(10) The magnitude of these movements appears relatively small (0.5 micron). Can the authors discuss whether such small but reproducible displacements are likely to be biologically meaningful in terms of nuclear function or gene regulation?

At the moment, our experimental set up allows us to analyze the dynamics of only a small portion of chr1, which indeed shows an average 0.5 micron displacement towards the nuclear periphery. Based on the chromosome painting data from fixed cells, the displacement at the level of whole chromosome is significantly larger. As mentioned in the discussion (page 13), the functional implications of radial repositioning of chromosomes upon serum starvation is not known. Therefore further discussion on the relevance of the magnitude reported here would be pure speculation.

(11) Peripheral homologs of chromosome 1 became faster and more dynamic under starvation. Why might these loci be more prone to movement? Could this be linked to differences in transcriptional activity or chromatin state between central and peripheral homologs?

At the moment we favour the idea that the central homolog is constrained by its anchorage to the nucleolus (Figure 6I). However, transcriptional activity and/or chromatin state may also play a role, and this possibility is now mentioned in the discussion on page 14.

Minor points:

(1) Figure legends use inconsistent capitalization and panel labels. These should be standardized across all figures for better readability.

We apologize for these inconsistencies, and have aimed to standardize all labeling.

References

Mehta, I.S., Amira, M., Harvey, A.J., and Bridger, J.M. (2010). Rapid chromosome territory relocation by nuclear motor activity in response to serum removal in primary human fibroblasts. Genome Biol 11, R5.

eLife Assessment

This important study reports insights into how the caspase Dcp-1, best known for cell death, can also promote tissue growth in Drosophila, extending the authors' earlier work by identifying regulatory factors that shape this non-lethal activity. The compelling findings identify a physical and functional interaction between Dcp-1 and Bruce, as well as new Dcp-1-interacting proteins that function in autophagy: Sirt1, Fkbp59, Debcl, Buffy, Atg2, and Atg8a. This work helps broaden the understanding of the non-lethal roles of Dcp-1.

Reviewer #1 (Public review):

The authors clearly demonstrate that overexpressed Dcp-1, but not Drice, is activated without canonical apoptosome components.

Using TurboID-based proximity labeling they revealed distinct proximal proteomes, among which Sirtuin 1, an Atg8a deacetylase, which promotes autophagy, was specifically required for Dcp-1 activation. Additionally, the show that autophagy-related genes, including Bcl-2 family members Debcl and Buffy, are required for Dcp-1 activation. Using structure-based prediction using AlphaFold3 they identified that Bruce, an autophagy-regulated inhibitor of apoptosis, as a Dcp-1-specific regulator acting outside the apoptosome-mediated pathway. Finally, they show that Bruce suppresses wing tissue growth. These findings indicate that non-lethal Dcp-1 activity is governed by the autophagy- Bruce axis, enabling distinct non-lethal functions independent of cell death.

Comments on revised version.

No further comments.

Reviewer #2 (Public review):

Summary:

The Drosophila executioner caspase Dcp-1 has established roles in cell death, autophagy, and imaginal disc growth. This study reports previously unrecognized factors that work together with Dcp-1. Specifically, the authors performed a turboID-based proximal ligation experiment to identify factors associated Dcp-1 and Drice. Dcp-1-specific interactors were further examined for their genetic interaction. The authors report autophagy-related genes, including Debcl and Buffy, to be required for Dcp-1 activation. In addition, the authors present evidence of an interaction between Bruce and Dcp-1. Bruce expression blocks the Dcp-1 overexpression phenotype. Inhibition of effector caspases or overexpression of Bruce commonly reduced wing growth, suggesting a relationship between the two proteins.

Strengths:

The study identifies new Dcp-1-interacting proteins and provides a functional link between Dcp-1 and Sirt1, Fkbp59, Debcl, Buffy, Atg2, and Atg8a. During the revision, the authors have also added convincing new data supporting the interaction between Dcp-1 and Bruce. They further make a strong case regarding the quality of the turboID-proteomics data. Overall, this is a strong manuscript supporting an interesting discovery.

Reviewer #3 (Public review):

Summary:

The present paper by Shinoda et al. from the Miura group builds upon findings reported in an earlier study by the same team (Shinoda et al., PNAS, 2019), which identified a non-apoptotic role for the Drosophila executioner caspase Dcp-1 in promoting wing tissue growth. That earlier work attributed this function primarily to Dcp-1 and to Decay, a caspase structurally related to executioner caspases, but not to DrICE, the principal apoptotic executioner caspase. The authors further proposed that this non-apoptotic caspase activity operates independently of the initiator caspase Dronc.

In the current study, the authors both corroborate aspects of their previous findings and extend the investigation to mechanisms regulating Dcp-1 in this context. They identify roles for the giant IAP Bruce, two BCL-2 family members, and autophagy-related components in modulating non-apoptotic Dcp-1 activity. Moreover, they show that Bruce binds to a BIR-like peptide exposed upon Dcp-1 cleavage, but not to DrICE. The study further suggests that low levels of Dcp-1 activity promote wing tissue growth, whereas excessive activity induces cell death, as evidenced by impaired wing development following Dcp-1 overexpression. Overall, the manuscript provides several intriguing insights into the non-apoptotic regulation of the comparatively weak apoptotic executioner caspase Dcp-1 and complements the group's earlier work. However, several concerns remain regarding certain interpretations of the data and the experimental rigour of some of the results.

Strengths:

A major strength of the work is its systematic genetic and biochemical approaches, which combine tissue-specific manipulation with protein interaction mapping to explore how Dcp-1 is regulated. The identification of several regulatory factors, including an inhibitor of cell death protein and components linked to autophagy, provides a coherent framework for understanding how Dcp-1 activity might be tuned.

Weaknesses:

The evidence supporting some key claims remains incomplete. In particular, the type of cell death form induced when Dcp-1 is overexpressed is not clearly established, and additional tests would be needed to distinguish between the different cell death types.

Likely impact:

The study contributes to a growing body of work showing that proteins traditionally associated with cell death can have broader roles in tissue development. This conceptual advance is likely to be of interest to researchers studying growth control and tissue maintenance.

Specific points:

(1) Nature of the wing ablation phenotype<br /> A central concern is whether the wing ablation phenotype observed upon Dcp-1 overexpression truly reflects apoptotic cell death. The authors show in Fig. 1c that nuclei in cells overexpressing Dcp-1, but not DrICE, zymogens are highly condensed, which is suggestive of apoptosis. However, it is equally plausible that this phenotype reflects a form of non-apoptotic, Dcp-1-dependent cell death (e.g. autophagy-dependent cell death). This distinction could be readily addressed using TUNEL labelling and direct caspase activity assays. The latter would be particularly informative, as it remains unclear whether zymogen Dcp-1 is capable of cleaving standard effector caspase reporters in vivo. Does the anti-cleaved Dcp-1 antibody detect Dcp-1 activation following overexpression of the Dcp-1 zymogen?

(2) Role of Decay<br /> In their earlier study, the authors identified Decay as another caspase influencing wing growth, albeit more modestly than Dcp-1. It is therefore unclear why this line of investigation was not pursued further in the current work. This omission is notable, as Decay is not implicated in apoptosis and, to date, no substantial physiological function has been assigned to this caspase in any system. At minimum, this point should be discussed explicitly.

(3) Fig. 2: Proximity labelling analysis<br /> The authors use TurboID-mediated proximity labelling to reveal distinct Dcp-1- and DrICE-associated proteomes across tissues, with a particular focus on the wing disc. They further demonstrate that RNAi-mediated knockdown of the Dcp-1-associated proteins Sirt1 and Fkbp59 suppresses the wing ablation phenotype induced by Dcp-1 overexpression, suggesting that these factors are required for Dcp-1 activity. However, it should be clarified whether Bruce was identified as a Dcp-1 interactor in the proximity labelling dataset, given its proposed central regulatory role. In addition, further discussion of Fkbp59, its known functions and how it might mechanistically influence Dcp-1 activity, would be valuable.

(4) Fig. 3: Autophagy-related factors<br /> Given that Sirt1 is known to promote autophagy, the authors next examine autophagy-related proteins and identify roles for Atg2, Atg8a, Debcl, and Buffy in Dcp-1 activation. Notably, these proteins do not promote cell death in the Hid-induced canonical apoptotic pathway. However, it is important to determine whether knockdown of Debcl, Buffy, Atg2, or Atg8a alone affects wing development in the absence of Dcp-1 overexpression, to exclude the possibility that these perturbations independently impair wing formation.

(5) Evidence for canonical autophagy<br /> The involvement of autophagy would be more convincingly demonstrated by testing additional core autophagy genes, such as Atg7, Atg5, and Atg12, as well as performing a combined knockdown of Atg8a and Atg8b. Moreover, direct assessment of autophagy at the cellular level using established genetic reporters would substantially strengthen the conclusions.

(6) Figs. 4-5: Functional consequences<br /> It would be informative to determine whether Synr, Debcl, or Buffy influence wing size on their own and whether their overexpression enhances wing growth.

(7) Terminology and interpretation of cell death<br /> Taken together, the results suggest that Dcp-1 zymogen overexpression induces a form of non-apoptotic cell death, potentially autophagy-dependent or related. The reviewer does not understand the authors' insistence on referring to this process as apoptosis. The authors should be more cautious in their terminology: there is no canonical versus non-canonical apoptosis, there is simply apoptosis. Without stronger evidence, these effects should not be described as apoptotic cell death.

Comments on revised version.

In the revised manuscript, the authors addressed each of my concerns in good faith and, in my opinion, responded to them thoroughly and satisfactorily. I have no further concerns.

Author response:

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

We are grateful to all the reviewers for dedicating time to review our manuscript and for providing insightful comments and suggestions. We have revised our manuscript in line with the reviewers' feedback. The major revisions include characterization of Dcp-1 overexpression-induced cell death, demonstration of the involvement of autophagy in Dcp-1 activation, characterization of the interaction between full-length Bruce and cleaved Dcp-1. We have introduced new figures (Figure 1 – figure supplement 1, Figure 2 – figure supplement 2, Figure 3 – figure supplement 1, Figure 5 – figure supplement 1), new panels (Figures 1D, Figure 3C, Figure 4I, J) and a new table (Table S2). The previous Figure 5 – figure supplement 1 has been relocated to Figure 4 – figure supplement 2.

With all concerns and suggestions from the reviewers addressed, our conclusion—that Bruce suppresses autophagy-regulated caspase activity and wing tissue growth in Drosophila— is now more robustly supported. We are confident that our revised manuscript makes a significant contribution to the fields of cell death, autophagy, and developmental biology, as it provides a new conceptual framework for understanding non-lethal caspase regulation. We remain hopeful that the reviewers will find it suitable for publication in eLife.

Reviewer #1 (Public review):

Summary:

The authors clearly demonstrate that overexpressed Dcp-1, but not Drice, is activated without canonical apoptosome components. Using TurboID-based proximity labeling, they revealed distinct proximal proteomes, among which Sirtuin 1, an Atg8a deacetylase, which promotes autophagy, was specifically required for Dcp-1 activation. Additionally, the show that autophagy-related genes, including Bcl-2 family members Debcl and Buffy, are required for Dcp1 activation. Using structure-based prediction using AlphaFold3, they identified that Bruce, an autophagy-regulated inhibitor of apoptosis, acts as a Dcp-1-specific regulator acting outside the apoptosome-mediated pathway. Finally, they show that Bruce suppresses wing tissue growth. These findings indicate that non-lethal Dcp-1 activity is governed by the autophagy-Bruce axis, enabling distinct non-lethal functions independent of cell death.

Strengths:

This is an excellent paper with very good structure, excellent quality data and analysis.

Weaknesses:

This reviewer did not identify any weaknesses or recommendations for revision.

We sincerely thank the reviewer for their highly positive evaluation of our work. We are pleased that the reviewer found the overall structure, data quality, and analyses to be strong, and that they clearly recognized the key findings of our study. No changes to the manuscript were required in response to this review.

Reviewer #2 (Public review):

Summary:

The Drosophila executioner caspase Dcp-1 has established roles in cell death, autophagy, and imaginal disc growth. This study reports previously unrecognized factors that work together with Dcp-1. Specifically, the authors performed a turboID-based proximal ligation experiment to identify factors associated Dcp-1 and Drice. Dcp-1-specific interactors were further examined for their genetic interaction. The authors report autophagy-related genes, including Debcl and Buffy, to be required for Dcp-1 activation. In addition, the authors present evidence of an interaction between Bruce and Dcp-1. Bruce-expression blocks the Dcp-1 overexpression phenotype. Inhibition of effector caspases or overexpression of Bruce commonly reduced wing growth, suggesting a relationship between the two proteins.

Strengths:

On the positive side, the study identifies new Dcp-1-interacting proteins and provides a functional link between Dcp-1 and Sirt1, Fkbp59, Debcl, Buffy, Atg2, and Atg8a.

Weaknesses:

The data supporting the Dcp-1/Bruce interaction are not strong, even though the title of this manuscript highlights Bruce. For example, the authors' turboID data does not support Dcp1/Bruce interaction. The case for the interaction is based on a single experiment that overexpresses a truncated Bruce transgene in S2 cells.

We sincerely thank the reviewer for their constructive and detailed evaluation of our manuscript. We appreciate the positive assessment that our study identifies new Dcp-1-associated factors and provides functional links between Dcp-1 and Sirt1, Fkbp59, and multiple autophagy-related genes, including Debcl, Buffy, Atg2, and Atg8a. We also thank the reviewer for clearly pointing out concerns regarding the strength and interpretation of the evidence connecting Bruce and Dcp-1. In the revised manuscript, we have addressed these concerns in two major ways. First, we provided additional experimental evidence explaining why TurboID-mediated labeling did not identify Bruce. Specifically, we showed that the majority of TurboID-tagged Dcp-1 expressed in wing imaginal discs remains in its full-length form, which is unlikely to engage Bruce. Second, and more importantly, we now demonstrated that endogenously expressed full-length Bruce interacts with cleaved Dcp-1 in wing imaginal discs. These new data provide strong support for a physiologically relevant interaction between Bruce and cleaved Dcp-1. Detailed descriptions of these experiments and results are provided in the point-by-point responses in the “recommendations for the authors” section. Together, these newly added data substantially strengthen the evidence for the Dcp-1/Bruce interaction and support the focus of the original manuscript title.

Reviewer #2 (Recommendations for the authors):

(1) The title of the manuscript highlights Dcp-1/Bruce interaction, even though the evidence there is not strong. The evidence for Dcp-1/Sirt1 and Dcp-1/Fkbp59 is stronger. How about changing the title to highlight these other Dcp-1 interactions?

We thank the reviewer for the thoughtful suggestion. We agree that several Dcp-1-associated factors identified in our study, particularly Sirt1 and Fkbp59, are supported by functional evidence. Specifically, our data show that Sirt1 and Fkbp59 are required for Dcp-1 overexpression-mediated activation. However, Bruce differs from these factors in both the scope and the nature of its effects on Dcp-1. Bruce is not only shown to specifically suppress Dcp-1 activity, but also to suppress wing tissue growth, indicating a broader physiological role in modulating non-lethal Dcp-1 function. Importantly, we further demonstrate that Bruce can specifically physically interact with cleaved Dcp-1. In addition, in this revised manuscript, we show that using the endogenously mStayGold::V5-tag knock-in-tagged Bruce allele, cleaved Dcp-1, induced by overexpression of Dcp-1::VENUS in wing imaginal discs, can be co-immunoprecipitated with full-length Bruce (new Figure 4I, J). These results support a physical interaction between full-length Bruce and activated Dcp-1 in vivo, consistent with a direct inhibitory role. Based on these findings, we decided to retain Bruce in the manuscript title, as it is the only factor for which both physiological and functional interactions with Dcp-1 are supported by multiple independent lines of evidence.

(2) The case for Dcp-1/Bruce interaction is not strong because the Dcp-1 turboID fails to identify Bruce. In fact, the Dcp-1 turboID approach may not have been effective, as it failed to detect many established interactions, including Diap1 (Wang et al. 1999 PMID 10481910; Tenev et al., 2006 PMID 15580265). The authors may want to comment on this.

We thank the reviewer for raising this important point. We agree that Bruce, as well as DIAP-1, was not identified in our TurboID-MS labeling dataset (Figure 2C, Table S1). Previous studies have shown that DIAP1 interacts with Dcp-1 and Drice only after exposure of the IAP-binding motif (IBM) at the neo-N-terminus of the large executioner caspase subunit following cleavage (Tenev et al., 2005). Similarly, our co-immunoprecipitation analyses show that Bruce interacts specifically with cleaved Dcp-1, but not with full-length Dcp-1. In the revised manuscript, we confirmed by western blot that the majority of endogenously expressed Dcp-1 in wing imaginal discs is present in the full-length pro-form (new Figure 2 – figure supplement 2A). Thus, the failure to identify Bruce and DIAP1 by TurboID-MS using full-length Dcp-1 as bait is expected, as this approach primarily labels interactors of the inactive, full-length form of Dcp-1. To evaluate whether our proximity labeling approach was nevertheless effective, we compared our TurboIDMS dataset with a previously published immune-affinity purification (IAP)-MS dataset generated using catalytically inactive, C-terminally V5-tagged Dcp-1 overexpressed in Drosophila 1(2)mbn cells (Choutka et al., 2017). Although the experimental conditions differ in several respects, we observed a substantial overlap between the TurboID-MS-mediated and IAP-MS-mediated interaction lists (new Figure 2 – figure supplement 2B, new Table S2). Importantly, SesB, one of the best-characterized Dcp-1 interactors located in mitochondria (DeVorkin et al., 2014), was also identified in our mass spectrometry dataset (new Figure 2 – figure supplement 2B, new Table S2). Based on these analyses, we now more explicitly describe the experimental context and limitations of the TurboID approach, clarifying that it preferentially labels interactors of full-length Dcp-1 in the revised manuscript. We also incorporate comparisons with prior studies to further support the validity of our mass spectrometry experiments in the revised manuscript

(3) The best experimental evidence for Bruce/Dcp-1 interaction can be found in Figure 4H. But here, they see a weak interaction only when a truncated Bruce construct is overexpressed in S2 cells. Whether Dcp-1 interacts with Bruce in a physiological setting remains unsupported.

We thank the reviewer for the important comment. We agree that, in the original manuscript, the biochemical evidence for the Bruce/Dcp-1 interaction relied primarily on experiments using an overexpressed truncated Bruce construct in S2 cells and therefore did not sufficiently establish whether this interaction occurs in vivo, especially in wing imaginal discs. To address this concern, we performed additional experiments to examine the Bruce/Dcp-1 interaction. In the background of the mStayGold::V5-tag knocked-in Bruce allele, we overexpressed Dcp-1::VENUS using WPGal4 driver to induce Dcp-1 activation and tested whether full-length Bruce under endogenous expression interacts with cleaved Dcp-1 in wing imaginal discs. Following immunoprecipitation with anti-V5 antibody-conjugated magnetic agarose, we found that cleaved Dcp-1 signal was enriched by co-immunoprecipitation (new Figure 4I, J). These new data demonstrate that Bruce associates with cleaved Dcp-1 in vivo and thus support the physiological relevance of the Bruce/Dcp-1 interaction. We have clarified this point in the revised manuscript and included the corresponding data.

(4) The genetic interaction between Bruce and Dcp-1 is interesting, but the interpretation becomes complicated because Bruce inhibits Reaper, and at the same time, Dcp-1 genetically interacts with Reaper, Hid, and Grim (Figures 1E, F, G). Thus, it remains unclear if the genetic interaction between Bruce/Dcp-1 is due to a direct interaction between Bruce/Dcp-1 or alternatively, because Bruce inhibits Reaper and Grim.

We thank the reviewer for the comment. The primary function of Reaper, Hid, and Grim (RHG proteins), collectively referred to as IAP antagonists, is to directly interact with inhibitor of apoptosis proteins (IAPs), most notably DIAP-1 (Kornbluth and White, 2005; Ryoo and Baehrecke, 2010), leading to the inhibition of DIAP-1 function. RHG proteins have not been shown to directly inhibit caspases. Because inhibition of RHG proteins results in the stabilization of DIAP-1, it is likely that the effects observed upon RHG gene knockdown are mediated through DIAP-1. Consistent with this idea, overexpression of DIAP-1, while less potent than Bruce, can also suppress Dcp-1 activation (Figure 5B, C). However, we also acknowledge that Bruce suppresses Reaper- and Grim-dependent, but not Hid-dependent, cell death (Vernooy et al., 2002). In addition, Bruce directly targets Reaper through non-lysine ubiquitination, promoting its degradation (Domingues and Ryoo, 2012). Thus, it is possible that Bruce overexpression suppresses Reaper and thereby strengthens DIAP-1 function, which could indirectly contribute to the inhibition of Dcp-1 activation. Nevertheless, because the effect of Bruce overexpression is stronger than that of DIAP-1 overexpression (Figure 5B, C), and together with our physical interaction data of Bruce with cleaved Dcp-1, we propose that Bruce most likely inhibits Dcp-1 directly to attenuate its activation.

(5) In general, the manuscript could benefit from highlighting the strong data on Sirt1 and Fkbp59, while clearly acknowledging the limitations of the Bruce/Dcp-1 interaction.

We thank the reviewer for the comment. As described above, in the revised manuscript we now demonstrate that endogenously expressed full-length Bruce physically interacts with cleaved Dcp-1 in wing imaginal discs (Figure 4I, J). These new data provide strong support for a physiologically relevant interaction between Bruce and cleaved Dcp-1. Based on this evidence, we decided to highlight Bruce in the manuscript, as it is the only factor for which both physiological and functional interactions with Dcp-1 are supported by multiple independent lines of evidence.

Reviewer #3 (Public review):

Summary:

The present paper by Shinoda et al. from the Miura group builds upon findings reported in an earlier study by the same team (Shinoda et al., PNAS, 2019), which identified a nonapoptotic role for the Drosophila executioner caspase Dcp-1 in promoting wing tissue growth. That earlier work attributed this function primarily to Dcp-1 and to Decay, a caspase structurally related to executioner caspases, but not to DrICE, the principal apoptotic executioner caspase. The authors further proposed that this non-apoptotic caspase activity operates independently of the initiator caspase Dronc.

In the current study, the authors both corroborate aspects of their previous findings and extend the investigation to mechanisms regulating Dcp-1 in this context. They identify roles for the giant IAP Bruce, two BCL-2 family members, and autophagy-related components in modulating nonapoptotic Dcp-1 activity. Moreover, they show that Bruce binds to a BIR-like peptide exposed upon Dcp-1 cleavage, but not to DrICE. The study further suggests that low levels of Dcp-1 activity promote wing tissue growth, whereas excessive activity induces cell death, as evidenced by impaired wing development following Dcp-1 overexpression. Overall, the manuscript provides several intriguing insights into the non-apoptotic regulation of the comparatively weak apoptotic executioner caspase Dcp-1 and complements the group's earlier work. However, several concerns remain regarding certain interpretations of the data and the experimental rigour of some of the results.

Strengths:

A major strength of the work is its systematic genetic and biochemical approaches, which combine tissue-specific manipulation with protein interaction mapping to explore how Dcp-1 is regulated. The identification of several regulatory factors, including an inhibitor of cell death protein and components linked to autophagy, provides a coherent framework for understanding how Dcp-1 activity might be tuned.

Weaknesses:

The evidence supporting some key claims remains incomplete. In particular, the type of cell death form induced when Dcp-1 is overexpressed is not clearly established, and additional tests would be needed to distinguish between the different cell death types.

Likely impact:

The study contributes to a growing body of work showing that proteins traditionally associated with cell death can have broader roles in tissue development. This conceptual advance is likely to be of interest to researchers studying growth control and tissue maintenance.

We sincerely thank the reviewer for their thoughtful and constructive evaluation of our study. In response to these concerns, we have performed additional experiments to clarify the nature of the cell death induced by Dcp-1 overexpression. Based on the detection of cleaved Dcp-1, the detection of executioner caspase activity, and TUNEL assay, we now conclude that excessive Dcp-1 expression induces typical executioner caspase activity-dependent apoptotic cell death. Detailed explanations and experimental results are provided in the point-by-point responses below. Overall, we believe that these additions strengthen the manuscript by clarifying the dual roles of Dcp-1 in promoting tissue growth at low activity levels while triggering apoptosis when excessively activated.

Specific points:

(1) Nature of the wing ablation phenotype

A central concern is whether the wing ablation phenotype observed upon Dcp-1 overexpression truly reflects apoptotic cell death. The authors show in Figure 1c that nuclei in cells overexpressing Dcp-1, but not DrICE, zymogens are highly condensed, which is suggestive of apoptosis. However, it is equally plausible that this phenotype reflects a form of non-apoptotic, Dcp-1-dependent cell death (e.g. autophagy-dependent cell death). This distinction could be readily addressed using TUNEL labelling and direct caspase activity assays. The latter would be particularly informative, as it remains unclear whether zymogen Dcp-1 is capable of cleaving standard effector caspase reporters in vivo. Does the anti-cleaved Dcp-1 antibody detect Dcp-1 activation following overexpression of the Dcp-1 zymogen?

We thank the reviewer for this important point regarding the nature of cell death. We agree that nuclear condensation alone is not sufficient to conclude apoptotic cell death, and we therefore performed additional experiments. First, we performed TUNEL staining and detected robust TUNEL-positive signals in wing imaginal discs upon Dcp-1 overexpression (new Figure 1D), supporting apoptotic DNA fragmentation. Second, to directly test whether Dcp-1 overexpression leads to executioner caspase activity in vivo, we used two independent executioner caspase activity probes, GC3Ai (Schott et al., 2017; Zhang et al., 2013) and CD8::PARP::VENUS (Williams et al., 2006). Both probes showed clear executioner caspase activity-positive signals in wing imaginal discs upon Dcp-1 overexpression (new Figure 1 – figure supplement 1C–F), demonstrating that Dcp-1 overexpression leads to executioner caspase activity capable of cleaving standard substrates in vivo. In addition, staining with an anti-cleaved Dcp-1 antibody was positive upon Dcp-1 zymogen overexpression (new Figure 1 – figure supplement 1B), indicating that the overexpressed Dcp-1 zymogen is converted into its active form. Consistent with this result, western blot analysis revealed that Dcp-1 zymogen overexpression results in the appearance of a cleaved Dcp-1 (new Figure 1 – figure supplement 1A). Importantly, consistent with our original observation that the wing ablation phenotype is suppressed by expression of the caspase inhibitor p35, we further showed that p35 overexpression completely abolished the appearance of cleaved Dcp-1 in western blot (new Figure 1 – figure supplement 1A), suggesting that Dcp-1 activation is mediated by self-cleavage. Taken together, these new results demonstrate that Dcp-1 zymogen overexpression induces typical executioner caspase activity-dependent apoptotic cell death. We have clarified this point in the revised manuscript and included the corresponding data.

(2) Role of Decay

In their earlier study, the authors identified Decay as another caspase influencing wing growth, albeit more modestly than Dcp-1. It is therefore unclear why this line of investigation was not pursued further in the current work. This omission is notable, as Decay is not implicated in apoptosis and, to date, no substantial physiological function has been assigned to this caspase in any system. At a minimum, this point should be discussed explicitly.

We thank the reviewer for the comment regarding the role of Decay. In our previous study (Shinoda et al., 2019), we demonstrated that both Dcp-1 and Decay promote wing tissue growth in a non-lethal manner. In the present study, however, we focused our analysis on Dcp-1. This decision was based on both technical and biological considerations. From a technical perspective, we had established TurboID knock-in lines and UAS overexpression lines for Dcp-1, Drice, and Dronc, whereas corresponding genetic tools are not available for Decay. From a biological standpoint, Dcp-1 exerts a stronger effect on wing growth than Decay, as shown in our previous work, and exhibits a dual functional spectrum: Dcp-1 promotes tissue growth at low activity levels, whereas excessive activation induces overt cell death. By contrast, Decay has not been implicated in cell death in wing imaginal discs (Kondo et al., 2006). Given that a central aim of the present study was to dissect how executioner caspase activity is differentially regulated to support nonlethal functions versus apoptotic cell death, we therefore focused on the two executioner caspases that are known to participate in apoptosis, Dcp-1 and Drice. We agree with the reviewer that Decay remains an intriguing caspase with largely unexplored physiological roles, and further investigation into its regulation and function will be an important direction for future studies. Importantly, Decay has been shown to mediate Hid-induced cell death in the DIAP1- and apoptosome-independent manner in differentiating photoreceptors and accessory cells of the eye (Leulier et al., 2006). In addition, although not required for cell death, Decay accounts for most of the caspase activity during metamorphic midgut programmed cell death, which is executed by autophagy (Denton et al., 2009). Thus, similar to Dcp-1, Decay might be an executioner caspase that can be regulated independently of the canonical apoptosome-mediated pathway, potentially involving autophagy-Bruce axis, and thereby contributing to the regulation of tissue growth. We have now discussed this point in the revised manuscript.

(3) Figure 2: Proximity labelling analysis

The authors use TurboID-mediated proximity labelling to reveal distinct Dcp-1- and DrICEassociated proteomes across tissues, with a particular focus on the wing disc. They further demonstrate that RNAi-mediated knockdown of the Dcp-1-associated proteins Sirt1 and Fkbp59 suppresses the wing ablation phenotype induced by Dcp-1 overexpression, suggesting that these factors are required for Dcp-1 activity. However, it should be clarified whether Bruce was identified as a Dcp-1 interactor in the proximity labelling dataset, given its proposed central regulatory role. In addition, further discussion of Fkbp59, its known functions and how it might mechanistically influence Dcp-1 activity would be valuable.

We thank the reviewer for the comment regarding the TurboID-based proximity labeling analysis and the interpretation of the identified Dcp-1-associated factors. With respect to Bruce, we clarify that Bruce was not identified as a Dcp-1 interactor in the TurboID proximity labeling dataset. Our co-immunoprecipitation analyses in S2 cells indicate that Bruce interacts specifically with cleaved Dcp-1, but not with the full-length, inactive form. In the revised manuscript, we confirmed by western blot that the majority of endogenously expressed Dcp-1 in wing imaginal discs exists in the full-length pro-form (new Figure 2 – figure supplement 2A). Therefore, the failure to detect Bruce in the TurboID experiment using full-length Dcp-1 as bait is expected, as this approach primarily labels proteins proximal to the inactive form of Dcp-1. To examine the Bruce/Dcp-1 interaction under more physiological conditions, we performed additional in vivo experiments. Using the mStayGold::V5-tag knock-in allele of Bruce, we overexpressed Dcp1::VENUS using WP-Gal4 driver to induce Dcp-1 activation and assessed whether endogenously expressed full-length Bruce associates with Dcp-1 in wing imaginal discs. Following immunoprecipitation with anti-V5 antibody-conjugated magnetic agarose, we found that cleaved Dcp-1 signal was enriched by co-immunoprecipitation (new Figure 4I, J). These new data demonstrate that Bruce associates selectively with the cleaved, active form of Dcp-1 in vivo, thereby supporting the physiological relevance of the Bruce/Dcp-1 interaction. We have clarified this point in the revised manuscript and included the corresponding data.

FK506-binding proteins (FKBPs) are a conserved group of proteins known to bind FK506, an immunosuppressive drug. FKBPs contain FK domains, which correspond to peptidyl cis-trans isomerase (PPIase) domains. Drosophila Fkbp59 is an orthologue of the mammalian FKBP4 and FKBP5, both of which possess a C-terminal tetratricopeptide repeat (TPR) domain that functions independently of the PPIase domain by mediating protein-protein interactions. The mammalian orthologues of Drosophila Fkbp59 function as Hsp90 co-chaperones (GharteyKwansah et al., 2018). Importantly, loss of Fkbp59 results in pupal lethality (Iki et al., 2020), which precludes further mechanistic analysis on Dcp-1 activation using adult wing phenotypes. To date, the involvement of Fkbp59 in caspase regulation has not been reported. Given that Fkbp59 functions as a co-chaperone, it may facilitate Dcp-1 activation by promoting proper folding, stability, or subcellular positioning of Dcp-1 or its regulatory factors. Importantly, Dcp1 proximal proteins are enriched in chaperone-related factors, including CCT2, CCT8, Droj2, CG16817, Fkbp59, Sgt1, and nudC; seven out of sixteen identified proximal proteins are chaperone-related. These observations suggest that Dcp-1 activity may be regulated by chaperone proteins or that Dcp-1 activity may be spatially restricted to regions enriched in chaperone machinery. Further analysis of the relationship between Dcp-1 activity and chaperone-related proteins will be important to elucidate the mechanisms and functions underlying non-lethal Dcp1 activation.

(4) Figure 3: Autophagy-related factors

Given that Sirt1 is known to promote autophagy, the authors next examine autophagy-related proteins and identify roles for Atg2, Atg8a, Debcl, and Buffy in Dcp-1 activation. Notably, these proteins do not promote cell death in the Hid-induced canonical apoptotic pathway. However, it is important to determine whether knockdown of Debcl, Buffy, Atg2, or Atg8a alone affects wing development in the absence of Dcp-1 overexpression, to exclude the possibility that these perturbations independently impair wing formation.

We thank the reviewer for the comment. To address whether knockdown of Debcl, Buffy, Atg2, or Atg8a independently affects wing development, we performed RNAi-mediated knockdown of each gene using the WP-Gal4 driver in the absence of Dcp-1 overexpression. Under these conditions, knockdown of Debcl, Buffy, Atg2, or Atg8a did not cause any detectable defects in wing morphology (new Figure 3 – figure supplement 1A), indicating that these autophagy-related factors specifically function to suppress Dcp-1-mediated cell death. We have clarified this point in the revised manuscript and included the corresponding data.

(5) Evidence for canonical autophagy

The involvement of autophagy would be more convincingly demonstrated by testing additional core autophagy genes, such as Atg7, Atg5, and Atg12, as well as performing a combined knockdown of Atg8a and Atg8b. Moreover, direct assessment of autophagy at the cellular level using established genetic reporters would substantially strengthen the conclusions.

We thank the reviewer for the constructive comment regarding the involvement of canonical autophagy. To further strengthen the evidence that autophagy is required for Dcp-1 activation, we examined additional core autophagy-related genes that function at distinct steps of the autophagy process, in addition to the previously tested Atg2, which mediates autophagosomal membrane expansion, and Atg8a, a core component directly associated with autophagosomal membranes. Specifically, we performed knockdown of genes including FIP200/Atg17, which is required for the initiation of autophagosome formation; Atg9, which is required for autophagosomal membrane nucleation; Atg5, which is required for autophagosomal membrane expansion through Atg12-Atg5-Atg16 ubiquitin-like conjugation system; and Stx17, which is required for autophagosome-lysosome fusion (Umargamwala et al., 2024). Because Atg8b is known to be specifically expressed in the male germline and is dispensable for autophagy, at least in fat body cells (Jipa et al., 2021), we did not further examine Atg8b in wing imaginal discs. Using WPGal4 driver, knockdown of each of these genes significantly suppressed Dcp-1-induced wing ablation phenotype (new Figure 3 – figure supplement 1C), supporting a requirement for canonical autophagy components across multiple stages of autophagosome biogenesis in Dcp-1 activation. Importantly, knockdown of these autophagy-related genes alone did not affect wing morphology in the absence of Dcp-1 overexpression (new Figure 3 – figure supplement 1B), as observed previously for Atg2 and Atg8a, suggesting the suppressive effects are specific to Dcp-1 overexpression-dependent cell death. Together, these results indicate that inhibition of autophagy at any of several key steps can suppress Dcp-1-dependent cell death, demonstrating that intact canonical autophagy is required for Dcp-1 activation. In addition, to directly assess autophagy at the cellular level, we monitored autophagosome formation using mCherry::Atg8a reporter. Upon overexpression of Dcp-1::VENUS in the wing pouch region, we observed a clear accumulation of Atg8a-positive puncta in wing imaginal discs (new Figure 3C), demonstrating that Dcp-1 overexpression induces autophagy in vivo. Together, these results provide both genetic and cellular evidence that canonical autophagy is activated upon Dcp-1 overexpression and is required for Dcp-1-dependent cell death. We have clarified this point in the revised manuscript and included the corresponding data.

(6) Figures 4-5: Functional consequences

It would be informative to determine whether Synr, Debcl, or Buffy influence wing size on their own and whether their overexpression enhances wing growth.

We thank the reviewer for the suggestion regarding the functional consequences of Synr, Debcl, and Buffy on wing size. As requested, we knocked down Debcl or Buffy using WP-Gal4 driver and found that this led to reduced wing size (new Figure 5 – figure supplement 1A), indicating that endogenous Debcl and Buffy promote wing growth potentially through regulating endogenous Dcp-1 activity. We have included the corresponding data in the revised manuscript. Because Synr RNAi did not show any detectable effect on the Dcp-1 overexpression-induced phenotype (Figure 3A, B), we did not further examine the effect of Synr knockdown on wing development alone. Overexpression of Synr was not examined in this study. However, Synr overexpression has previously been reported to induce cell death in wing imaginal discs, resulting in malformed adult wings (Ikegawa et al., 2023), suggesting that increased Synr expression is likely to have deleterious rather than growth-promoting effects. Because Debcl and Buffy are both required for Synr-induced cell death, overexpression of Debcl or Buffy may lead to similar phenotypes. Therefore, we did not test Debcl or Buffy overexpression in the wing imaginal discs.

(7) Terminology and interpretation of cell death

Taken together, the results suggest that Dcp-1 zymogen overexpression induces a form of nonapoptotic cell death, potentially autophagy-dependent or related. The reviewer does not understand the authors' insistence on referring to this process as apoptosis. The authors should be more cautious in their terminology: there is no canonical versus non-canonical apoptosis; there is simply apoptosis. Without stronger evidence, these effects should not be described as apoptotic cell death.

We thank the reviewer for the important comment on terminology and interpretation of the cell death phenotype. As explained in our response to comment #1, we have performed additional experiments to clarify the nature of the cell death induced by Dcp-1 overexpression. Based on the detection of cleaved Dcp-1, the detection of executioner caspase activity, and TUNEL assay, we now conclude that excessive Dcp-1 expression induces typical executioner caspase activity-dependent apoptotic cell death. At the same time, as explained in our response to comment #5, we provide both genetic and cellular evidence that canonical autophagy is activated upon Dcp-1 overexpression and promotes Dcp-1 activation. We recognized that the phrase “Dcp1 activity-regulating alternative apoptosis signaling pathway” used in Figure 5L could be misleading, as it may imply the existence of an “alternative apoptosis”. To avoid this confusion, we have revised the figure legend to read “autophagy-facilitated alternative caspase activation pathway.”

Reviewer #3 (Recommendations for the authors):

Figure 1c should be annotated more clearly so that it is evident that the images shown are grouped by genotype.

We thank the reviewer for the helpful suggestion. We have added lines to Figure 1C to improve clarity by indicating that the images are grouped by genotype.

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eLife Assessment

The authors describe a new member of the KCNE auxiliary subunits of potassium channels from a lamprey. This new subunit represents an early evolutionary member which confers new properties when expressed along with KCNQ channels. In the revised version of the manuscript, the authors present convincing evidence from several experimental approaches. The contents of this manuscript are important and should be relevant to understanding both the mechanism of modulation of KCNQ channels by KCNE subunits and the evolutionary history of these subunits, which this manuscript now extends to the divergence of early vertebrates.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

In this study, the authors describe an early diverging vertebrate KCNE gene present in jawless lampreys that they denote KCNE0.

Three forms of the protein are isolated from different lampreys, which have 95% homology to each other, but only moderate homology to KCNE1-6.

Co-expression with lamprey KCNQ1 produced a non-inactivating current, whereas co-expression with mammalian KCNQ1 resulted in less modulation. Introduction of a tetra-leucine motif from KCNE4 into KCNE0 reduced current on co-expression with KCNQ1, conferring an inhibitory effect.

Strengths:

This is an interesting and uncontroversial report of a new KCNE isoform from lower vertebrates that gives insight into the evolutionary progression of the sequence and functional properties of the accessory protein.

Reviewer #2 (Public review):

Summary:

This study functionally characterizes a single KCNE-like gene, kcne0, from a jawless vertebrate. The authors conducted multiple experiments, including TEVC, VCF, RT-PCR, and RNA-seq to show that KCNQ1 and kcne0 exhibited a broadly overlapping organ distribution in lamprey species, and KCNE0 produced a constitutively active current when co-expressed with lamprey KCNQ1, similar to the effects of human KCNE3 on KCNQ1. This modulation was species-specific, as co-expression of KCNE0 with other species' KCNQ1 was less effective. Moreover, the authors found that truncating the N-terminal had a more significant reduction of the modulatory effects than truncating the C-terminal of KCNE0. Interestingly, the introduction of the tetra-leucine motif from human KCNE4 into KCNE0 conferred KCNE0 with comparable effects of human KCNE4 on KCNQ1.

Strengths:

The authors clearly introduced an early-diverging member of the KCNE family, and convincingly demonstrated the function of this gene, KCNE0. The results are supported by experiments of multiple approaches and are clearly written. The work is significant and will interest readers from the extended research area.

Weaknesses:

No major concerns were identified with the manuscript in general.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this study, the authors describe an early diverging vertebrate KCNE gene present in jawless lampreys that they denote KCNE0.

Three forms of the protein are isolated from different lampreys, which have 95% homology to each other, but only moderate homology to KCNE1-6.

Co-expression with lamprey KCNQ1 produced a non-inactivating current, whereas co-expression with mammalian KCNQ1 resulted in less modulation. Introduction of a tetra-leucine motif from KCNE4 into KCNE0 reduced current on co-expression with KCNQ1, conferring an inhibitory effect.

Strengths:

This is an interesting and uncontroversial report of a new KCNE isoform from lower vertebrates that gives insight into the evolutionary progression of the sequence and functional properties of the accessory protein.

Thank you for reviewing our manuscript and for your constructive comments. Our point-to-point responses are shown below.

Weaknesses:

(1) No error bars visible for lamprey Q1 isoforms (open symbols) in Figure 2G. No statistical comparison was provided to indicate whether lamprey Q1 isoform V1/2s are significantly different (nor in Supplementary Table 1).

(2) There is the same issue in Figures 3 and 4. No appropriate statistical comparison is made between V1/2s for different truncations of PmKCNE0 (Figure 3), or between KCNQ1 species isoforms with and without PmE0.

We thank you for these helpful comments. Based on your suggestions, we revised the presentation of error bars in Fig. 2G and in other panels showing G–V or F–V relationships (Figs. 2J, 3F, 3N, 4C, 4F, 4I, 4L, and 5E; Supplementary Fig. 5D) to make the SEM bars clearer. We also added statistical comparisons of V_1/2 values among the three lamprey KCNQ1 orthologs in Fig. 2G and among truncation-series constructs in Figs. 3F and 3N using one-way ANOVA followed by Tukey–Kramer multiple-comparison tests. For Fig. 4, we added statistical comparisons between KCNQ1 species isoforms expressed with or without PmKCNE0 (Figs. 4C, 4F, and 4I), and between PmKCNQ1 expressed alone or with human KCNE1 or KCNE3 (Fig. 4L), using unpaired two-tailed Welch’s t-tests. These statistical comparisons are included in Supplementary Table 1.

Reviewer #2 (Public review):

Summary:

This study functionally characterizes a single KCNE-like gene, kcne0, from a jawless vertebrate. The authors conducted multiple experiments, including TEVC, VCF, RT-PCR, and RNA-seq to show that KCNQ1 and kcne0 exhibited a broadly overlapping organ distribution in lamprey species, and KCNE0 produced a constitutively active current when co-expressed with lamprey KCNQ1, similar to the effects of human KCNE3 on KCNQ1. This modulation was species-specific, as co-expression of KCNE0 with other species' KCNQ1 was less effective. Moreover, the authors found that truncating the N-terminal had a more significant reduction of the modulatory effects than truncating the C-terminal of KCNE0. Interestingly, the introduction of the tetra-leucine motif from human KCNE4 into KCNE0 conferred KCNE0 with comparable effects of human KCNE4 on KCNQ1.

Strengths:

The authors clearly introduced an early-diverging member of the KCNE family, and convincingly demonstrated the function of this gene, KCNE0. The results are supported by experiments of multiple approaches and are clearly written. The work is significant and will interest readers from the extended research area.

Weaknesses:

No major concerns were identified with the manuscript in general.

We thank you for the positive assessment of our work and for the constructive suggestions. Our point-by-point responses are provided below.

Recommendations for the authors:

Reviewer #2 (Recommendations for the authors):

(1) What is the physiological role of this KCNE0 and lamprey KCNQ1 in the lamprey species? While the authors mention that the physiological roles of KCNE0 are the next focus, it is preferable to discuss some of the potential functional significance of this newly characterised KCNE.

We thank you for this helpful suggestion. We agree that discussing the potential physiological roles of KCNQ1–KCNE0 complexes in lamprey strengthens the manuscript. We have therefore expanded the Discussion to raise the possibility that, given the broad tissue distribution of kcne0 transcripts and the ability of KCNE0 to render lamprey KCNQ1 constitutively active, KCNQ1–KCNE0 complexes may contribute to general ion homeostasis, potentially analogous to the epithelial K⁺ recycling function of mammalian KCNQ1–KCNE3, rather than to the highly specialized KCNQ1–KCNE1 function in the mammalian heart and inner ear (page 14, lines 263–267).

(2) Human KCNQ1 has 676 amino acids, but LcKCNQ1 contains just 507 amino acids. The species-specific regulatory effects of KCNE0 may not only be attributed to KCNE0 itself but might also be influenced by the species of KCNQ1. Some discussion on this possibility will be helpful.

We thank you for raising this important point. We agree that the species-specific regulatory effects observed in our cross-species pairing experiments are unlikely to be determined by KCNE0 alone and may also be influenced by species-specific features of the KCNQ1 α-subunit. To address this point, we expanded the Discussion to note that the KCNQ1 proteins used in this study vary in amino-acid length, largely reflecting differences in the cytoplasmic C-terminal region, which may affect KCNQ1–KCNE compatibility and thereby influence channel gating and coupling to KCNE subunits (pages 12–13, lines 227–238). We also updated Supplementary Fig. 4 to include LrKCNQ1 and LcKCNQ1, and clarified that the LcKCNQ1 construct used in this study encodes 644 amino acids.

(3) In Supplementary Figure 3, bands corresponding to LcKCNQ1 (507 amino acids, Supplementary Figure 1) were not seen.

We thank you for pointing out this potentially confusing point. Supplementary Fig. 3 shows RT-PCR products amplified from tissue cDNA, not full-length amplification of the LcKCNQ1 ORF. As stated in the Methods section (pages 19–20, lines 374–399), the primers used for RT-PCR in Fig. 1F and Supplementary Fig. 3 were different from those used for cloning the full-length LcKCNQ1 cDNA shown in Supplementary Fig. 1. Therefore, a band corresponding to the full-length LcKCNQ1 coding sequence was not expected in Supplementary Fig. 3.

To clarify this point, we revised the figure legends and indicated the RT-PCR primer-binding sites with orange arrows in Supplementary Figs. 1 and 2.

eLife Assessment

This useful study addresses a timely question about semantic prioritisation in visual working memory, using behavioural manipulations and drift-diffusion modelling. However, the strength of evidence is incomplete for the broader claims about working-memory representations because the main interpretation relies on indirect inferences from non-decision time, which cannot uniquely identify memory access or retrieval.

Reviewer #1 (Public review):

Summary:

This paper investigates whether semantic prioritization in visual working memory reflects pre-decisional access, evidence accumulation, or both, using drift diffusion modeling across a reanalysis of prior data and two new experiments. The core finding - that semantic information receives a robust pre-decisional access advantage that is amplified by attentional disruption rather than temporal delay alone - is novel and contributes meaningfully to ongoing debates about the format and accessibility of working memory representations.

Strengths:

The experimental approach is well-motivated, and the use of drift-diffusion modeling to decompose decision components adds analytical value beyond standard RT and accuracy measures. The two new experiments are pre-registered and address important questions. The broader theoretical conclusion - that working memory limits are shaped not only by storage capacity but by which representational formats remain accessible under attentional uncertainty - is an important and timely contribution to the field.

Weaknesses:

The central interpretive claims rely heavily on differences in non-decision time, a parameter that aggregates many processes unrelated to memory retrieval, making it rather difficult to uniquely attribute the observed effects to access or retrieval mechanisms specifically. Additionally, the characterization of the two memory conditions as genuinely perceptual versus semantic warrants further justification, as both may primarily require categorical rather than format-specific knowledge.

Reviewer #2 (Public review):

This manuscript aims to characterize how semantic information is prioritized relative to perceptual details in visual working memory. The central claim is that semantic judgements benefit from faster pre‑decisional access (shorter non‑decision time), and that advantages in evidence accumulation emerge under higher cognitive demands (e.g., when items are outside the focus of attention or must be maintained under interference). Based on this, the paper argues that unattended working‑memory contents are reformatted into more abstract, long‑term‑memory‑like semantic representations that remain more readily accessible than fine‑grained perceptual features.

Strengths:

(1) The question is timely and relevant to current research about the format of visual working memory.

(2) Behaviorally, the semantic advantage is carefully documented in many conditions across datasets.

(3) The use of hierarchical drift-diffusion modelling is helpful to decompose the semantic advantage into cognitive processes such as non‑decision time and drift‑rate components.

Weaknesses:

(1) The strong claims about visual working‑memory representation and "long‑term‑memory‑like" formats rest on an indirect inference from decision‑model parameters to representational content, and this link is not convincingly established. Non‑decision time, as implemented here, bundles many things, such as probe processing, cue processing, retrieval/access, and motor preparation, so reduced non‑decision time for semantic probes could reflect easier question reading, simpler response mapping, or more efficient decision preparation rather than a genuine advantage in accessing semantic memory representations. Although the manuscript acknowledges that non‑decision time includes multiple processes, it nonetheless treats this parameter as primary evidence for a retrieval‑stage semantic advantage, which overstates what the data can uniquely support.

(2) The modelling approach is relatively constrained and does not fully address the underdetermination inherent in mapping latent drift-diffusion parameters onto specific psychological mechanisms. The preferred model that allows multiple parameters (non‑decision time, drift rate, threshold) to vary provides only modest improvements in predictive accuracy over simpler models, and several key drift‑rate effects are present only in particular load or lag conditions. As a result, the theoretical interpretation that semantic prioritization primarily reflects faster access and secondarily more efficient accumulation under high demand appears rather post hoc, and alternative accounts focused on generic task efficiency or strategy differences remain plausible.

(3) The operationalization of "semantic" is narrow and largely categorical, focusing on animacy (animal/object) and a perceptual format dimension (photo/drawing), rather than richer semantic or associative relations among items. This makes it difficult to generalize the conclusions to broader claims about semantic structure and its integration into working‑memory representations. Important recent work on how semantic and associative relationships facilitate the formation, maintenance, and retrieval of visual working memory is not adequately integrated into the theoretical framing. Consequently, the discussion tends to generalize from a specific probe structure to a broader semantic prioritization theory without engaging fully with the existing literature on semantic facilitation and neural decoding of working‑memory content.

(4) The paper contrasts its behavioral/model‑based results with prior neural decoding findings, but the comparison is not fair. Neural decoding provides complementary evidence about the content and format of working memory representations, whereas drift-diffusion parameters reflect downstream decision dynamics given a probe. Because the current work does not include any direct representational or neural measure, its conclusions about representational "reformatting" and long‑term‑memory‑like access remain speculative and, in places, feel like a stretch.

(5) Overall, while the data show a semantic advantage in decision‑stage measures and the modelling provides an informative decomposition of this advantage, the manuscript does not fully achieve its stated aim of characterizing the representational format of visual working memory or demonstrating a mechanistic shift toward long‑term‑memory‑like semantic representations. The work primarily informs decision‑process analyses of the conditions under which semantic judgements are faster and more robust, rather than the nature of visual working‑memory representations themselves.

Author response:

We thank the reviewers for their constructive and careful assessment of our manuscript. We are encouraged that both reviewers recognised the value of the empirical contribution: the semantic advantage is robust across experiments, the two new experiments are pre-registered, and the drift-diffusion modelling provides an informative decomposition of behavioural performance. At the same time, both reviewers raise an important and convergent point: the manuscript currently places too much interpretive weight on non-decision time and sometimes moves too quickly from decision-model parameters to claims about the representational format of working memory.

We agree that this aspect of the manuscript should be revised. In the next version, we will substantially soften claims about adaptive reformatting and long-term-memory-like formats. We will instead frame the central contribution more precisely: semantic-category judgements show a reliable advantage at stages preceding evidence accumulation and this advantage is modulated by attentional prioritisation and interference during the maintenance interval. Our data constrain the dynamics with which different kinds of information become available for WM-guided decisions, but they do not, on their own, provide a direct measure of representational format. This hypothesis should be tested in future experiments.

At the same time, we think the data provide stronger constraints on alternative explanations than the current manuscript makes clear. The reviewers correctly note that non-decision time is not a pure retrieval parameter, as we also note in the discussion. It can include probe encoding, response preparation, motor execution, and other processes. We will therefore avoid more explicitly equating NDT directly with retrieval latency. However, many of the alternatives raised by the reviewers, such as easier question reading or simpler response mapping for semantic probes, predict a relatively fixed semantic–perceptual offset. In our experiments, the probes and response mappings are held constant across attentional conditions, while the semantic NDT advantage changes as a function of whether the relevant item can be prioritised in advance or must be selected/reactivated at test. We will restructure the Results and Discussion to make these condition × feature interactions central to the argument.

We will also clarify the logic of Experiment 1. We agree with Reviewer 1 that a valid retro-cue likely triggers retrieval or reactivation of the cued item. Our original phrasing, which described the valid-cue condition as reducing retrieval demands, was imprecise. The critical manipulation is better described as shifting item prioritisation/retrieval earlier in the trial. Under valid cueing, the relevant item can be prioritised before the probe appears, whereas under neutral cueing, item selection and access must occur after probe onset. We will rewrite this section accordingly.

We will also clarify our operationalisation of semantic and perceptual categories. The present contrast is specifically between semantic category information (animate versus inanimate) and perceptual-format information (photograph versus drawing). We agree that the perceptual judgement is still categorical and does not measure fine-grained perceptual fidelity. We will therefore avoid broad claims about semantic structure or perceptual detail in general. However, as pointed in the manuscript, we believe the contrast remains meaningful: the two dimensions are orthogonal within the same stimuli, and previous work using the same feature space showed the opposite ordering during perception (Linde-Domingo et al., 2019), where perceptual-format information was available before semantic-category information. We will move this argument earlier in the manuscript and present it as converging evidence for dissociable access dynamics, while acknowledging that it does not by itself prove representational format.

In response to the modelling concerns, we will expand the model-validation section. Specifically, we plan to add posterior predictive checks for the reported models, report model comparisons more transparently, clarify when more complex models do or do not provide practically meaningful improvements, and include sensitivity analyses using alternative parameterisations where identifiable.

We will also make several methodological clarifications. First, because the reanalysis of Kerrén et al. (2022) forms a substantial part of the manuscript, we will add a fuller description of the original task in the main text, including how the probed item was indicated at test. Second, we will rewrite the unclear sentence describing pseudo-random stimulus selection in Experiment 1 and add a control analysis testing whether performance differs when the probed item belongs to the majority versus minority category within the trial. Third, we will clarify the stimulus repetition scheme and discuss possible long-term-memory contributions. Importantly, because semantic and perceptual probes are applied to the same items from the same trials, any repetition history or proactive-interference contribution is shared across the two probe types, although we agree that this should be discussed explicitly.

Finally, we will revise the broader theoretical framing. We will remove or substantially qualify claims linking the present data directly to episodic memory and imagery. We will also integrate the recent literature suggested by Reviewer 2 on semantic structure, associative relations, long-term-memory contributions to working memory, and boundary conditions for semantic labelling effects. This will allow us to position the study as one piece of a broader literature on how semantic information influences WM performance, rather than as direct evidence for a general representational reformatting mechanism.

In summary, the revised manuscript will make a narrower but stronger claim: semantic-category information shows a robust pre-accumulation advantage during WM-guided decisions, and this advantage is shaped by attentional prioritisation and interference during maintenance. We will present this as evidence about WM access dynamics and decision components, not as direct evidence that WM representations are transformed into long-term-memory-like formats.

eLife Assessment

The manuscript by von Velsen et al. offers valuable structural insights into the mitogen-activated protein kinase (MAPK) pathway by providing cryo-EM structures of stabilized MEK1-ERK2 kinase-substrate complexes in inactive, active, and nucleotide-free states, complemented by HDX-MS, SAXS, ITC, crystallography, and molecular dynamics. The work provides solid evidence for the overall architecture of the complex and identifies interaction sites that help explain MAPK pathway specificity. However, some mechanistic conclusions are not yet fully supported, particularly the designation of one state as an active phosphoryl-transfer configuration, the claim that substrate binding releases the MEK1 catalytic machinery, the proposed link to processive phosphorylation, and the extrapolation to disease-associated mutations.

Reviewer #1 (Public review):

Summary:

This manuscript describes three conformers derived from a complex between ERK2-T185V, a variant of MEK1-DD with the KIM sequence replaced by the KIM from the p38 activator, GRA24, ADP, and AlF4-. The goal was to try to capture the complex in its active state. The results show contacts between the kinases between their N-lobe and their C-lobes that resemble MKK6-p38 complexes previously reported by the authors. Two MEK1-ERK2 conformers (States 1,3) are deemed inactive based on the lack of access of ERK-Y187 to the MEK1 active site, and the absence of ADP bound to MEK1 in State 3, while one conformer (State 2) is deemed active, but not fully active due to disorder in MEK1 activation loop (A-loop) and an essential salt bridge between strand beta3 and helix aC. HDX-MS and SAXS solution measurements and all-atom MD simulations are used to model the mutant complex and variants with WT ERK2. The study concludes that substrate recognition involves low-energy contacts with MEK, allowing substantial protein flexibility within the complex in a manner that may accommodate processive phosphorylation of ERK2.

Strengths:

The strengths of the work are that the findings provide important structural insights for MEK-ERK signaling and protein phosphorylation in general. These are valuable given that atomic resolution structures of kinase-substrate complexes are still limited in number. The authors succeeded in showing key contacts between subunits and conformational variations within the complex.

Weaknesses:

Weaknesses were that some of the conclusions about activity state, dynamics, and effects of ligand binding were less convincing. For example, that State 2 truly represents an active configuration seemed ambiguous, given the absence of Mg2+ and AlF4- in the cryoEM structure and disorder in the activation loop and the K97-E114 salt bridge. Conclusions by SAXS that ADP-AlF4 binding increases active site compaction while increasing local flexibility were not rigorously supported by HDX data, given that the latter were performed without ligand. Sections of the narrative and figures throughout were often confusing, and many assertions were made without clear explanation. Data shown in the supplementary materials were not always described in the Results, even those important for the conclusions. Figure legends and text lacked clear descriptions of specific complexes analyzed. Substantial changes are recommended to improve the readability and clarity of the work.

Reviewer #2 (Public review):

Summary:

The authors used Cryo-EM to obtain a complex between MEK1 and ERK2. They used the same method as previously used by the same authors to form a stable complex between MKK6 and p38, an extra-strong KIM replacing the wild-type KIM in MEK1. Three conformers were resolved, with the highest resolution of 3.0 Å. The multiple conformers indicate more flexibility in MEK2 than in ERK2. These data suggest that nucleotide exchange is possible while maintaining MEK1-ERK2 interactions. SAXS and HDX data reinforce the idea of flexibility. They point to interactions between the two N-terminal domains between histidines at the N-terminus of helix C and between the G helices that are maintained in each of the 3 conformers, and sequence and structure suggest these histidines may be a source of specificity in MEK1-ERK2 versus MKK6-p38 interactions. A 2.2 Å structure of a complex between ERK1 (88% identical to ERK2) and the docking peptide used was also presented. Molecular dynamics simulations suggest that the MEK1-ERK2 complex can assume a fully active configuration of MEK1.

Strengths:

This is the first structure of a MEK1-ERK2 complex. The structural data are valuable additions to our understanding of MAP2K-MAPK interactions. The discussion points offered in the results section are palatable. These include the origins of specificity and the idea of flexibility in the MAP2K in support of a processive mechanism for the dual phosphorylation activity of MAP2Ks.

Weaknesses:

(1) This reviewer considers that the abstract is overstated. Specifically, this paper does not reveal the molecular details of phosphoryl transfer, nor does it demonstrate that substrate binding releases the catalytic machinery.

(2) The discussion is in some places not supported by evidence and in others has superfluous text. Examples follow:

- "Once the αG-helix is docked, and the C-lobe histidine triad is in place, the N-lobe interactions must then be fulfilled." The data in this paper does not suggest an order of events.<br /> - "If the substrate MAPK is incorrect, the N-lobe interaction will not be stabilised, preventing alignment of the MAPK A-loop with the MAP2K active site." This statement could be described as obvious.

(3) Much of the discussion is embedded in the results, such that it is difficult to separate new facts offered by the paper from speculation.

Author response:

eLife Assessment

The manuscript by von Velsen et al. offers valuable structural insights into the mitogen-activated protein kinase (MAPK) pathway by providing cryo-EM structures of stabilized MEK1-ERK2 kinase-substrate complexes in inactive, active, and nucleotide-free states, complemented by HDX-MS, SAXS, ITC, crystallography, and molecular dynamics. The work provides solid evidence for the overall architecture of the complex and identifies interaction sites that help explain MAPK pathway specificity. However, some mechanistic conclusions are not yet fully supported, particularly the designation of one state as an active phosphoryl-transfer configuration, the claim that substrate binding releases the MEK1 catalytic machinery, the proposed link to processive phosphorylation, and the extrapolation to disease-associated mutations.

We would like to counter the final statement. We were very careful in our description of state 2, while we describe it as ‘active’ we clearly explain that the resolution of the reconstruction is not sufficient to define all the classical indicators of a kinase active state; however, the map is consistent with the active conformation, the complex is active in vitro, and the MEK1 variant used is the well known DD mutant that is constitutively active. While the A-loop is not observed, this is in agreement with many crystal structures of other DD mutants. We therefore decided to define this state as ‘active’ as the A-loop of ERK2 approaches the active site, the alpha-C helix has moved in and the A-loop of MEK1 no longer occludes the active site - to clarify the state we refer to the classically active confirmation as ‘fully active’. Our supporting data also show that the complex is highly dynamic during turnover, meaning we have captured MEK1 in a number of conformations on the landscape of an active state – we feel that rather than a limitation, this is an important observation in MAP2K studies. Finally, the determination of an 80 kDa complex by cryoEM to resolutions well below 4 Å is a huge technical achievement allowing the first snapshots of the MEK1-ERK2 complex to be visualised.

Regarding the A-helix release – our observation is that the helix becomes less folded on binding of substrate. There are many studies, which we cite, that show that destabilising this helix leads to release of the catalytic machinery, see Mansour et al, 1996, Biochemistry, 35, 15529-15536 and Jindal et al 2017 J. Biol. Chem. 292, 18814-18820 for initial studies. Our observation shows that this is linked to substrate binding – a very relevant new insight that demonstrates the importance of this helix, in addition to many previous studies, but links unfolding to substrate recognition for the first time.

For the mechanism of processive phosphorylation – it has been well established that both processive and distributive mechanisms exist. While the way that a distributive mechanism could work is obvious (complete dissociation of the two proteins), it has not been clear how a MAP2K can remain bound to its substrate and exchange nucleotides. While caution should be employed in interpreting our state 3 structure, it clearly shows what nucleotide exchange when bound to substrate can look like and that this low nucleotide affinity state is linked to disorder in the P-loop, the A-helix and substrate binding via the KIM. We would love to perform experiments that could demonstrate this but cannot at present think of an appropriate method – the reviewers did not suggest a route either.

Finally, for the cancer-causing mutations – there are many studies demonstrating that the mutations lead to a destabilisation of the A-helix. Our study links this to substrate recognition. While this is inference, it seems justified to describe a link between substrate recognition, A-helix unfolding and disease mutations given the large body of literature describing these events.

We are currently performing a series of in-cell activity assays that should strengthen our claims regarding the A-helix and other observations in the structure - the histidine interactions in particular.

Public Reviews:

Reviewer #1 (Public review):

Summary:

This manuscript describes three conformers derived from a complex between ERK2-T185V, a variant of MEK1-DD with the KIM sequence replaced by the KIM from the p38 activator, GRA24, ADP, and AlF4-. The goal was to try to capture the complex in its active state. The results show contacts between the kinases between their N-lobe and their C-lobes that resemble MKK6-p38 complexes previously reported by the authors. Two MEK1-ERK2 conformers (States 1,3) are deemed inactive based on the lack of access of ERK-Y187 to the MEK1 active site, and the absence of ADP bound to MEK1 in State 3, while one conformer (State 2) is deemed active, but not fully active due to disorder in MEK1 activation loop (A-loop) and an essential salt bridge between strand beta3 and helix aC. HDX-MS and SAXS solution measurements and all-atom MD simulations are used to model the mutant complex and variants with WT ERK2. The study concludes that substrate recognition involves low-energy contacts with MEK, allowing substantial protein flexibility within the complex in a manner that may accommodate processive phosphorylation of ERK2.

Strengths:

The strengths of the work are that the findings provide important structural insights for MEK-ERK signaling and protein phosphorylation in general. These are valuable given that atomic resolution structures of kinase-substrate complexes are still limited in number. The authors succeeded in showing key contacts between subunits and conformational variations within the complex.

Weaknesses:

Weaknesses were that some of the conclusions about activity state, dynamics, and effects of ligand binding were less convincing. For example, that State 2 truly represents an active configuration seemed ambiguous, given the absence of Mg2+ and AlF4- in the cryoEM structure and disorder in the activation loop and the K97-E114 salt bridge. Conclusions by SAXS that ADP-AlF4 binding increases active site compaction while increasing local flexibility were not rigorously supported by HDX data, given that the latter were performed without ligand. Sections of the narrative and figures throughout were often confusing, and many assertions were made without clear explanation. Data shown in the supplementary materials were not always described in the Results, even those important for the conclusions. Figure legends and text lacked clear descriptions of specific complexes analyzed. Substantial changes are recommended to improve the readability and clarity of the work.

We thank reviewer #1 for in-depth comments and analysis of our manuscript. However, there is a misunderstanding regarding HDX-MS and SAXS data. First, the HDX-MS data were performed on the ADP.AlF₄^- inhibited complex - this was not made sufficiently clear in the text, and we will amend this. Secondly, we are not trying to support local flexibility observed in the SAXS data with the HDX data. The HDX data support the interactions observed in the cryoEM structure and demonstrate flexibility in the proline-rich loop, the ERK A-loop and unfolding of the MEK1 A-helix. The SAXS data demonstrate that when the transition state complex is formed, the complex is more compact but flexibility within the complex increases - as observed in the dimensionless Kratky plot, supporting our observations in the cryoEM maps. Therefore, the HDX data and SAXS data are separate observations. We thank reviewer #1 for all the comments and will rewrite the manuscript in order to increase clarity as suggested.

Reviewer #2 (Public review):

Summary:

The authors used Cryo-EM to obtain a complex between MEK1 and ERK2. They used the same method as previously used by the same authors to form a stable complex between MKK6 and p38, an extra-strong KIM replacing the wild-type KIM in MEK1. Three conformers were resolved, with the highest resolution of 3.0 Å. The multiple conformers indicate more flexibility in MEK2 than in ERK2. These data suggest that nucleotide exchange is possible while maintaining MEK1-ERK2 interactions. SAXS and HDX data reinforce the idea of flexibility. They point to interactions between the two N-terminal domains between histidines at the N-terminus of helix C and between the G helices that are maintained in each of the 3 conformers, and sequence and structure suggest these histidines may be a source of specificity in MEK1-ERK2 versus MKK6-p38 interactions. A 2.2 Å structure of a complex between ERK1 (88% identical to ERK2) and the docking peptide used was also presented. Molecular dynamics simulations suggest that the MEK1-ERK2 complex can assume a fully active configuration of MEK1.

Strengths:

This is the first structure of a MEK1-ERK2 complex. The structural data are valuable additions to our understanding of MAP2K-MAPK interactions. The discussion points offered in the results section are palatable. These include the origins of specificity and the idea of flexibility in the MAP2K in support of a processive mechanism for the dual phosphorylation activity of MAP2Ks.

Weaknesses:

(1) This reviewer considers that the abstract is overstated. Specifically, this paper does not reveal the molecular details of phosphoryl transfer, nor does it demonstrate that substrate binding releases the catalytic machinery.

(2) The discussion is in some places not supported by evidence and in others has superfluous text. Examples follow:

- "Once the αG-helix is docked, and the C-lobe histidine triad is in place, the N-lobe interactions must then be fulfilled." The data in this paper does not suggest an order of events.

- "If the substrate MAPK is incorrect, the N-lobe interaction will not be stabilised, preventing alignment of the MAPK A-loop with the MAP2K active site." This statement could be described as obvious.

(3) Much of the discussion is embedded in the results, such that it is difficult to separate new facts offered by the paper from speculation.

We thank reviewer #2 for comments and thorough analysis of our manuscript. We agree that perhaps the abstract should be toned down in terms of claims of an active conformation even though we feel that the combination of the first structure of the MEK1-ERK2 complex combined with MD simulation studies clearly demonstrate how phosphoryl transfer will occur. We are now also performing in-cell assays to support our theory of A-helix regulation. For point 2 we based the order of events on data from Juyoux et al 2023 Science, 381, 1217-1225, where in long-timescale MD simulations and experimentally validated adaptive Markov state model simulations the KIM interaction was the last to dissociate after the alpha-G helix interaction. In our MD simulations of the MEK1-ERK2 complex, the interactions formed by the N-lobe were weaker than those formed by the alpha-G. Indeed, dissociation of the N-lobe was observed in various independent simulations, whereas dissociation of the alpha-G was observed only once.

Assuming that, as in the MKK6-p38a complex, the association proceeds along the reverse of the dominant dissociation pathway, the simulations suggest that the KIM interaction forms first, followed by the alpha-G and finally the N-lobes. While alternative association pathways are possible, this interpretation is consistent with the MD and in line with the main association and dissociation pathway observed for the MKK6-p38a complex. This is additionally supported by the observation that there is no catalytic activity if the KIM is removed, demonstrating this as the first essential recruitment event. We will expand this section to include our arguments.

For the second example, we feel this is rather unfair. The statement that if the His-His interaction is absent, catalysis will be prevented is only obvious if one knows about the His-His interaction - this is the first structure showing pathway-specific interactions in the variable loop regions of a MAPK. If it is obvious, why has no one described these residues as important before?

We have taken on board the comments on the style of the manuscript and will make significant changes as suggested by both reviewers.

eLife Assessment

The authors use a novel patch-leaving task to reveal a reward-reset strategy when mice choose to leave a depleting resource, and find that accumulated step-like activity in the dorsomedial striatum is correlated with the timing of these decisions. These important behavioral and neural findings are supported by substantial and convincing data. Additional control analyses would strengthen the evidence that these signals are specifically related to timing and patch-leaving decisions, rather than alternative task-related processes.

Reviewer #1 (Public review):<br /> <br /> Summary:

In this study, Shuler and colleagues record neurons from the DMS in mice performing a patch foraging task. In this task, mice had the choice between harvesting rewards from 2 ports - one the time-investment port where the rate of reward declined over time and the other a context port where the rate of reward was either high or low. Mice performed the task appropriately, switching between ports as the rate of reward declined in the time-investment port and switching more rapidly when the context port delivered high versus low rewards. The behavior of the mice was also strongly driven by time since the most recent reward receipt, in conflict with normative accounts of patch foraging. Individual DMS neurons showed bistable firing patterns, transitioning to high rates of activity at various times from reward. Overall, the population tiled the temporal space, and the accumulation of the number of neurons in the high firing state was predictive of patch exit. The rate of accumulation varied with things that also affected behavior.

Strengths:

Overall, the aims of the study were clear and important, the experiment directly addresses them, and the results are clear and provide compelling support for the authors' conclusions.

Weaknesses:

I have only a few comments and questions to consider, none of which are criticisms of what was done, really.

(1) Probably my chief question, alluded to in the discussion, is what the evidence is that DMS plays a causal role in generating these correlates and the resulting behavior, in light of the lack of causal evidence here. What are other options? Could such information depend on upstream areas such as OFC or mPFC, with DMS just a pass-through? And while I would not ask for causal data, is there a specific prediction? That is, if the area were inactivated, would mice stay longer or shorter? Not do the task? If I wanted to do a causal test of the authors' idea regarding the contribution of DMS to this behavior, what would be predicted, and what result would invalidate the hypothesis? Speculating on this a bit, beyond just saying DMS is involved, would be useful.

(2) Not much is said about the suboptimal strategy. Would DMS continue to play the same role if the mice showed no effect of recent reward and instead performed appropriately? Or is some other area doing that job? Or is this not important? I thought it was interesting that the mice basically did not treat the game quite like they were supposed to. Is it important to go back and look at what is happening in DMS under normative conditions to really know how this area contributes to proper foraging?

(3) Do these neurons also track time in the context port? Or do they only exhibit this behavior in the port where rewards are depleting? This seems like an interesting question. Do they show the same profile in different ports, if so?

Reviewer #2 (Public review):

Summary:

Here, Sutlief et al. use a novel patch-foraging task to investigate the role of dorsomedial striatal (DMS) neurons in determining when animals disengage from a resource. They show that mice, contrary to canonical optimal-foraging predictions, adopt a strategy in which reward receipt resets timing behavior, with decisions further shaped by both cumulative time spent in a patch and the overall quality of the environment. The authors further demonstrate that a subset of DMS neurons exhibits step-like activity patterns during task performance. Importantly, the accumulation of these state transitions across the neuronal population predicts the timing of patch-leaving decisions on a trial-by-trial basis, providing a potential neural mechanism underlying decisions about when to abandon a currently exploited resource.

Strengths:

This study addresses an important question using a well-designed, interesting behavioral task. The finding that mice employ a reward-triggered exit-timing policy is particularly interesting, as it is pertinent to the many patch foraging-style tasks that have been developed for use in mice, where rewards are delivered as discrete events. The identification of step-like activity in DMS neurons is mostly compelling, and the authors' trial-by-trial analysis linking this activity to behavior provides some support for its relevance to patch-leaving decisions.

Weaknesses:

A key interpretational issue is whether the DMS signal reflects timing specifically, rather than movement initiation or other task-related factors. The authors argue that once a sufficient number of neurons transition, the animal exits the time-investment port. However, it remains unclear whether this population threshold reflects a timing computation that determines when to leave in the more abstract sense, or a signal more directly related to movement onset (that may also be initiated after some proportion of the population has changed its activity). An important control would be to examine neural activity while animals are engaged at the context port. In this epoch, animals presumably do not need to time their departure in the same way, but they still eventually initiate movement. If the DMS signal reflects timing rather than movement, one would not expect the same accumulation-to-threshold pattern of step-like transitions at the context port.

It would also be helpful for the authors to clarify the behavioral definition of the leaving decision. Can mice return to the time-investment port after exiting it if they do not subsequently enter the context port? How exactly is "exit" defined: as withdrawal from the time-investment port, entry into the context port, or some other behavioral event? Is there variability in the latency between time-investment port exit and context-port entry, and if so, is this latency related to DMS step-like activity? These details are important for interpreting whether the neural activity is aligned with a timing decision, movement initiation, or the execution of a transition between task states.

The classification approach for identifying step-like activity seems generally reasonable, and the low false-positive rate against homogeneous Poisson controls is reassuring. However, one potential issue is that the identification of trial-by-trial state transitions is not independent of the session-level characterization of each neuron. The algorithm first fits a sigmoid to the pooled session data and then uses the resulting high- and low-firing-rate states to constrain interval-level fits. This may bias the analysis toward finding step-like transitions in neurons whose activity is only approximately step-like at the session level, effectively reducing the space of alternative solutions available to the interval-level fits. As implemented, the approach therefore functions more as a detector of consistency with a session-defined step model than as an unbiased test of whether individual intervals are better described by discrete state transitions versus alternative dynamics such as ramps or gradual drifts. This concern could be addressed by comparing the constrained sigmoid model against alternatives, such as constant-rate or ramping models, on held-out intervals, or by deriving state parameters from an independent subset of trials and testing classification on the remaining trials.

The inclusion threshold for the accumulation analysis is difficult to evaluate. Sessions were included if they contained at least seven simultaneously recorded step-like units, but this number is hard to interpret without knowing the total number of recorded units per session and the fraction classified as step-like. Seven units may be sufficient for fitting a population accumulation trajectory, but because the cutoff is based on an absolute number rather than a proportion of the recorded population, it is unclear whether included sessions reflect robust population-level step-like dynamics or a relatively small selected subset of DMS activity. Reporting the number and fraction of step-like units per session, as well as the sensitivity of the accumulation results across different inclusion thresholds, would help clarify this point.

Reviewer #3 (Public review):

Sutlief and colleagues report behavioral and neural results from mice performing a patch foraging task. Behaviorally, they argue that time since last reward is a major determinant of when mice decide to leave a patch. In the brain, they find neurons in the dorsomedial striatum that show step-like changes in their firing rate at a range of times following reward. Population analyses show that the cumulative fraction of neurons that have undergone such a step-like change in firing rate can be used to predict patch-leaving times with impressive accuracy.

Overall, this is an interesting set of results that has been analyzed in a principled way. The manuscript is well written, the results are explained clearly, and the evidence supporting the authors' conclusions is strong. The manuscript is therefore a potentially valuable contribution to the growing literature assessing how the brain solves stopping problems like the patch foraging scenario. I have suggestions for the authors to consider that might further increase the rigor of their results, and a few suggestions for improving the clarity of the work for readers.

(1) I don't quite understand how the behavioral task works. Are mice rewarded for making discrete nose poke responses in the investment and context ports? Or are they required to nose poke and hold? Is reward given with some probability per response (which decreases with time in the patch), or is the reward probability a function of elapsed time in the patch, time since last response, or dwell time in the port? Also, exactly what equation defines how reward probability changes over time for the high- and low-value contexts? I couldn't find these details anywhere in the manuscript, and they would be helpful for better understanding the behavior and the later neural results.

(2) How was the optimal strategy determined? Several features of the author's task violate the assumption of the marginal value theorem, so computing the optimal residence time is not a straightforward application of the classic model. There's a diagram in Figure 1h that depicts an MVT-like graphical solution, but the conventions of the plot are not familiar to me, and there's no description of how it works in the results or methods. More detail here would be much appreciated. In a similar vein, the authors report that mice generally exceeded optimal residence times in patches, but no statistical comparison is provided to back up that statement. There should be some formal test of this if it is to be included in the results.

(3) The authors argue that time since last reward is the predominant determinant of patch leaving time. However, as the authors note, time since last reward is correlated with other task variables (patch reward rate, time in patch, etc.). I don't trust that SVM coefficients can be interpreted as straightforward measures of a variable's importance for classification performance in the case of correlated predictors. A better approach would be to assess how well the model performs as subsets of variables are added or removed from the model.

(4) For the SVM analysis, I'm not quite understanding how or why the authors are using 5 s after mice left the patch as additional "Leave" examples. For instance, is time since entry computed for the investment patch, or the context patch that mice enter after they leave the investment patch? Similarly, is the time since the last reward relative to the investment patch, or the reward the mouse is likely to receive at the context patch? Moreover, I'm not sure it's safe to assume that because the mouse left at time t, time t+1 necessarily reflects conditions on which the mouse would definitely leave again. If we're thinking about the stay/leave decision as something that is being repeated sequentially on a fast time scale to determine how long mice stay in the patch, it doesn't follow that observing a mouse leave means that any patch conditions after that would necessarily result in the same decision. If that were the case, it would mean that seeing a mouse leave a patch after 2 s would preclude ever observing a residence time longer than 2 s, which is clearly not compatible with the authors' data. Ultimately, it's only possible to observe one decision to leave per trial; including data points beyond that as additional leave examples seems overly speculative to me.

(5) The authors validate their approach for quantifying step-like changes in firing rate using simulations of constant-rate Poisson spiking and observe a low false positive rate. This is encouraging, but it doesn't seem like the only way in which their method could go awry, or even the most concerning way. I would be much more interested in seeing the false positive rate for continuous, ramp-like changes in firing rate, which would be much more likely to trip up the authors' approach and are also the major relevant alternative hypothesis to step-like changes in firing rate. Random walks in firing rate might also be worth testing.

(6) The finding that cumulative "transitioned" neurons is predictive of patch leaving is interesting. However, I can't help but wonder how truly informative this variable is for predicting patch leaving. It seems as though neurons can only transition firing rates one time. That means that as time in the patch increases, the fraction of transitioned neurons naturally increases. Similarly, all visits must eventually end with the mouse leaving the patch, so the hazard rate of leaving increases with time in the patch. Given that, can the authors be certain that the cumulative transitioned neurons are really what's predicting patch leaving time, or would any generically increasing function perform roughly the same? An interesting test would be to mismatch the neural predictor and behavior at the level of trials. If this mechanism is really specific, rather than something that captures the general structure of an increasing hazard rate of leaving, then prediction of leaving time should work substantially better when the neural predictor is correctly matched to behavior on the trial for which it was recorded.

Author response:

Reviewer #1

(1) Causality and the role of DMS; a specific, falsifiable prediction. We agree that the paper should not leave the causal question implicit, and we will expand the Discussion to state a concrete prediction rather than a general claim of involvement. Briefly, if the accumulation signal we describe carries the animal's intended departure time, then suppressing DMS during patch occupancy should not simply shift exit times in one direction but should degrade their structure: exit-time variability should increase, and exit timing should lose its systematic dependence on reward-rate context and on the time of the most recent reward. A plausible alternative outcome is disengagement from the task altogether, which would be uninformative and would need to be controlled for. The result that would falsify our hypothesis is the one we will state explicitly: exit timing that remains as predictable, and as sensitive to context and reward history, under DMS suppression, as without it. We will also discuss the alternative the reviewer raises, that these signals are inherited from cortical inputs such as OFC or mPFC with DMS acting as a relay, and note that our data cannot presently distinguish this from a locally generated signal.

(2) Behavior under a normative strategy. This is an interesting question and we will address it in the Discussion. Our expectation, which we will frame as a prediction rather than a result, is that an animal timing from patch entry rather than resetting at each reward would show accumulation that begins at entry and proceeds to a context-dependent threshold at the reward-rate-optimal time, rather than the reward-triggered resets we observe. In this view, the reset structure of the neural signal is a reflection of the behavioral policy rather than a property of the region. We will make clear that this is a testable prediction that our current dataset does not address.

(3) Do these neurons also track time at the context port? We intend to answer with new analysis, and it converges with Reviewer #2's suggested analysis (below), so we treat the two together there.

Reviewer #2

(a) Timing versus movement initiation: activity at the context port. We take this to be a central interpretational concern. We will examine whether the step-like DMS activity extends to the context port, testing the interval between the final context-port reward and departure for the same step-like transitions and accumulation we observe in the time-investment port. We will apply the same comparison to the context-port inter-reward intervals, which addresses Reviewer #1's third point about whether these neurons also track time at the context port.

We want to flag one feature of the task that bears on how the outcome should be read. The context port is not a timing-free epoch. Its four rewards are delivered at predictable, regularly spaced intervals, and the interval between the final reward and the animal's departure is self-timed. Departure from the context port is therefore also a self-timed action, and observing accumulation there would not by itself indicate that the signal reflects movement initiation rather than timing. What the comparison can inform is whether the accumulation is specific to a decision about when to disengage from a depleting resource, or is a more general feature of self-timed departures. This is a meaningful distinction either way, and one we will report and interpret whichever direction the result falls.

(b) Operational definition of leaving; the exit-to-entry latency. We agree these details are necessary for interpretation and their absence is our omission. Exit is the final withdrawal from the time-investment port preceding the next context-port visit, and we will make that clear in the revised methods. Mice can and occasionally do re-enter the time-investment port without an intervening context-port visit (especially early in training). Such re-entries are not counted as exits. We will also examine whether the latency between time-investment-port exit and context-port entry relates to the accumulation slope on the corresponding interval, to test whether the neural signal relates to the decision or to the execution of the transition.

(c) Independence of interval-level fits from the session-level model. This is a fair characterization of the procedure, and we accept the distinction the reviewer draws between a detector of consistency with a session-defined step model and an unbiased test of discrete versus continuous dynamics. We will address it with a held-out validation: estimating each unit's state parameters and transition time from one half of its intervals and testing whether the transition times recovered from the withheld half agree. The discrete-versus-continuous comparison is addressed directly by the ramp simulations under Reviewer #3's point (5) below.

(d) The inclusion threshold for the accumulation analysis. We will add a supplementary figure reporting the total number of recorded units per session and the fraction classified as step-like, so that the seven-unit criterion can be evaluated against the recorded population rather than in the abstract. Yield varied substantially across sessions, from a handful of units to roughly one hundred, and we will show this distribution directly. We will also report the accumulation results across a range of inclusion thresholds spanning approximately five to eight simultaneously recorded step-like units, so that readers can assess sensitivity to the choice.

Reviewer #3

(1) Specification of the task. We agree the task description was insufficient, and we will correct this at the front of the Results and in the Methods. The time-investment port operates on a poke-and-hold basis: the mouse maintains its head in the port and rewards are delivered stochastically over time for as long as it remains, with no requirement to withdraw and re-poke. Reward delivery follows an exponentially decaying rate in time since port entry, with a time constant of eight seconds, integrating to an expected eight rewards of one microliter each (8 µL total) for indefinite occupancy; we will give the explicit function. The reward probability function in the time-investment port is identical across blocks. The high- and low-reward-rate contexts are properties of the context port alone (four rewards over five seconds versus four rewards over ten seconds), and we will make this contrast unambiguous, since it is the manipulation on which the design rests.

(2) Derivation of the optimum, Figure 1h, and a formal test of overstaying. We appreciate this comment. The optimal residence time in our task is not obtained by the classical Charnov tangent construction. It is computed by explicit maximization of the overall reward rate over the full cycle, following the framework in Sutlief et al. (2025) and shown graphically in Figure 1h. We will expand the legend of Figure 1h so its conventions are stated explicitly, give the reward-rate-maximizing derivation as an explicit equation in the Methods, and reframe the surrounding text around reward-rate maximization as the normative principle, with MVT identified as the special case it is. We will also add the formal statistical comparison of observed residence times against the computed optimum, which the reviewer correctly notes was asserted rather than tested.

(3) Interpretation of SVM coefficients with correlated predictors. We accept this criticism. We will not rest the ordering of predictors on coefficient magnitudes alone. We will add a variable inclusion-and-ablation analysis, reporting cross-validated classification performance as each predictor is added to and removed from the model, so that the contribution of time since last reward is assessed by its effect on performance rather than by its normalized weight. We will additionally add a complementary analysis of the leave hazard that estimates the contribution of each variable without requiring the classification framework.

(4) The five-second post-exit window. The reviewer is right that we did not explain this choice, and right that it rests on an assumption. Our reasoning was that a single exit moment per trial leaves the decision boundary badly under-constrained, and that treating the moments immediately following an exit as conditions under which the animal would also have left is licensed by the fact that within-patch reward rate declines monotonically with time, so conditions in the counterfactual continued visit would have been strictly less favorable than those already rejected. We accept that this is an assumption rather than an observation and will state it as such. We will also report the analysis across a range of window durations so that the independence of the result on this choice is visible. To the reviewer's specific questions: both time since entry and time since last reward are computed with respect to the time-investment port throughout, and we will state this explicitly.

(5) False positive rate against ramps and random walks. We agree this is the more informative validation, and that continuous ramping is the most relevant alternative to ours. We will generate simulated units with continuous ramp-like rate changes, matched to the firing rates and interval structure of our recorded units, and pass them through the identical classification pipeline to obtain false positive rates comparable to the Poisson analysis already reported. We will retain the flat-rate Poisson simulation and present the ramp results as additional panels of the same supplement. We will also explore random-walk dynamics. Together with the held-out validation of transition times described under Reviewer #2(c), this converts the step characterization from a single-null validation into a comparison against the relevant continuous alternatives.

(6) Specificity of the accumulation signal versus a generic increasing function. This is a valuable challenge and we will address it directly. We will implement the trial-mismatch control the reviewer proposes, randomly reassigning accumulation trajectories to reward-to-exit intervals within session and showing the extent to which predictive performance degrades relative to the correctly matched case.

We would also note two features of the existing results that speak to this concern, and which we will bring forward in the revision because we did not make them salient enough. First, a signal that merely tracked elapsed time would be expected to shift its starting level as well as its rate across trials with different exit times; instead, the accumulation slope is strongly related to exit time (mean r = -0.551) while the intercept is not (mean r = 0.013), indicating a variable rate from a stable origin. Second, and more to the point, the accumulation arrives at a common level at the moment of exit whether the animal leaves early or late. The rate of accumulation shifts with the animal’s policy on that trial such that the threshold is met at the intended time. 

What makes this predictor non-trivial is its trial-by-trial correspondence to behavior, not simply that it increases over time. We will make this argument explicitly alongside the shuffle control.

Summary

To summarize the planned additions: (i) analysis of step-like activity and its accumulation at the context port, with the interpretive caveat noted above; (ii) validation of step detection against ramping alternatives, together with held-out estimation of transition times; (iii) a trial-mismatch control for the specificity of the accumulation predictor; (iv) an inclusion-and-ablation analysis of the behavioral predictors and a complementary hazard model of the leave decision; (v) reporting of unit yield, step-like fraction, and sensitivity of the accumulation results to the inclusion threshold; (vi) analysis of the exit-to-context-entry latency in relation to the neural signal; (vii) a formal statistical test of overstaying relative to the computed optimum; and (viii) substantial clarification of the task specification, the operational definition of exit, and the derivation of the optimal residence time, including an expanded Figure 1h legend.

Our aim in the revision is to meet the specificity concern raised in the assessment as directly as the existing data allow, and we hope the revised manuscript will warrant reconsideration of the strength-of-evidence characterization.

We are grateful to the reviewers for the care evident in their reports, and to you both for handling the manuscript.

References

Charnov, E. L. (1976). Optimal foraging, the marginal value theorem. Theoretical Population Biology, 9(2), 129–136.

Sutlief, E., Walters, C., Marton, T., & Hussain Shuler, M. G. (2025). The value of initiating a pursuit in temporal decision-making. eLife. https://doi.org/10.7554/eLife.99957.2.

Signed review contributed through PaperStack

This review was contributed through PaperStack and is reproduced with the reviewer’s permission.

1. Benchmarking methodology and expert consensus

The benchmarking methodology would benefit from additional detail. It is unclear how many experts contributed to the “human expert consensus” used in the curation-agreement benchmarks (Fig. 4b and Tables 1–2). The number of reviewers is specified only for the separate time-efficiency experiment (Fig. 5d–e), and it is not clear whether the same reviewers generated the consensus labels.

The manuscript also does not explain how disagreements were resolved—for example, by majority vote—or whether the few-shot examples provided to the VLM came from recordings independent of the test data, which is important for excluding information leakage.

Because inter-expert agreement is itself only 77.8–83.3% (Fig. 5e), the expert consensus should be treated as an uncertain reference standard rather than biological ground truth. The evaluation would be strengthened by reporting the number of experts labeling each unit, the consensus procedure, individual expert–model agreement, and the sensitivity of performance to the choice of expert reference.

Reporting precision, recall, sensitivity, specificity, and confusion matrices in addition to overall percentage agreement would also clarify performance, particularly given the apparent Good/Noise class imbalance.

2. Breadth of validation

Validation is currently limited to two short recordings from two animals: a one-minute Neuropixels segment and a two-minute flexible-probe segment, each obtained from a single mouse.

Testing on held-out recordings from additional animals, laboratories, brain regions, recording durations, and signal-quality conditions would better establish whether the VLM’s curation criteria generalize beyond the recordings used to construct its prompts and few-shot examples.

Validation against experimentally derived ground truth, where available, or comparison with established automated quality-control tools would also help distinguish agreement with human judgment from unit-classification accuracy. This distinction is important because the model and human reviewers could share the same systematic biases.

3. Scope of the “fully autonomous end-to-end” framing

The “fully autonomous end-to-end” framing may require qualification. For the LLM-backend benchmark in Fig. 3, the Methods state that SpikeInterface operations such as spike sorting and waveform extraction were replaced by loading presaved results and waveforms.

This is a reasonable design for isolating the models’ code-generation and tool-chaining reliability, but the resulting completion-rate and token-usage measurements do not evaluate a complete raw-data-to-curated-output execution.

The manuscript would be clearer if it explicitly described Fig. 3 as a workflow-orchestration benchmark rather than a full end-to-end benchmark. Alternatively, a separate evaluation could run the complete pipeline on raw data and assess both successful execution and the validity of the resulting sorted and curated units.

Clarifying this distinction would help readers calibrate expectations about what “autonomous” performance has actually been demonstrated versus what remains to be tested.

This review is signed, but the reviewer’s name is omitted because bioRxiv’s community guidelines do not permit reviewer names in comments. To contact the reviewer, email support@paperstack.pub; PaperStack will forward the request.

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This variant is mentioned in the supplemental table, S1 CAP. No additional details provided

This variant is reported in Table S6, but only location, predictions, frequencies, etc are reported for it, not cases.

Case#: Case 6, Sex:Female, Age:34

DiseaseAssertion: STGD

FamilyInfo: n/a

CasePresentingHPOs: n/a

CaseHPOFreeText: Clinical Notes: Classic Stargardt. General notes: participant had classic features of STGD and field ERG showed abnormal cone responses with preserved rod function.

CaseNotHPOs:n/a

CaseNotHPOFreeText: n/a

Genotyping Method: Exome sequencing data generation. Additional sequencing targeted amplification fo PRPH2 and ELOVL4 using PCR.

PreviouslyPublished: n/a

Variant: ABCA4, NM_000350.3(ABCA4):c.2966T>C (p.Val989Ala)

ClinVar: Variation ID: 99180

SupplementalData: Proband variant information given in Table 1.

PMID: 28726568

Gene: ABCA4

HGNC ID: 34

Case#: Hwang Case 4, male, 52yo at report, 45yo at onset

DiseaseAssertion: Stargardt

FamilyInfo: Family history was not significant for ocular disease.

CasePresentingHPOs: HP:0000545

CaseHPOFreeText: declining vision OS, BCVA was 20/100 OD and 20/70 OS. Spherical refractive error measured −3.00 OD and −3.25 OS. Posterior segment examination was significant for central atrophy and classic peripheral pisciform flecks sparing the peripapillary regions OU (Figure 4, A and B). Autofluorescence imaging demonstrated inner atrophic flecks and outer hyperautofluorescent flecks. Moderate peripapillary hypoautofluorescence, but not atrophy, was present (Figure 4, C and D).

CaseNotHPOs: HP:0500087

CaseNotHPOFreeText:

GenotypingMethod: Genotyping was performed by the ABCR400 microarray followed by direct sequencing to confirm identified variants.

PreviouslyPublished: n/a

Variant: P1380L and S1696N

ClinVar: 7904

CAID: CA129033

SupplementalData: n/a

PMID: 10874631

Gene: ABCA4

HGNC ID: 34

Case#: patient 34, female

DiseaseAssertion: STGD

FamilyInfo: paternal first cousin with RP19, healthy father heterozygous for 1938-1 G>A splice mutation

CasePresentingHPOs: HP:0007663, HP:0000608, HP:0000603,

CaseHPOFreeText: yellowish flecks

Genotyping Method: PRISMTM Ready Reaction Sequencing Kit on an automatic fluorometric DNA sequencer

PreviouslyPublished: N/A

Variant: NM_000350.3(ABCA4):c.1938-1G>A

ClinVar: 99106 https://www.ncbi.nlm.nih.gov/clinvar/variation/99106/?term=%22ABCA4%22%5BGENE%5D+AND+%22(c.1938-1G%3EA)%22%5BVARNAME%5D

gnomAD: 0.000002488 https://gnomad.broadinstitute.org/variant/1-94060760-C-T?dataset=gnomad_r4

This variant is found on pg 11 in proband 18034. Compound heterozygous for c.2588G>C p.Gly863Ala. Said to have Stargardt based on the following criteria: "(1) patients (at least 6 years old) with at least two ABCA4 variants or one ABCA4 variant associated with a typical STGD1 phenotype and (2) presence of a well-defined atrophic lesion with/without flecks at the most recent visit of at least 300 µm in diameter (the total area of all lesions <12 mm2)." No additional details provided

Case#: Female, age 44 years old

DiseaseAssertion: Discordant STGD phenotype

FamilyInfo: Information revolving the sister of this patient is given as well as they both have a discordant STGD phenotype. Additionally, it mentions that the parents each harboured a mutation but were asymptomatic/had normal examination results.

CasePresentingHPOs: HP:0001141, HP:0007401, HP:0030602

CaseHPOFreeText: At 23 central vision was deteriorating and patient had a VA of 6/36 in the right eye and 6/60 in the left. Through fundus photography, bilateral yellow/white flecks were found at the posterior pole. 12 years later, her VA was retested and it was 6/60 in both eyes. After autofluorescnece (AF) imaging was done, there was localized low signal at the macula found with abnromal foci. In 2008 her macular atrophy had enlarged and the flecks were less apparent.

CaseNotHPOs: N/a

CaseNotHPOFreeText: In this article there was not a phenotype presented that was normal.

CasePreviousTesting: It mentioned that there were two previously reported variants on the same allele detected in the siblings and one unique novel variant on the second allele for this patient. However, the testing they used was not listed, it just stated that the variants were found through sequencing. For this patient the variants were p.L541P/p.A1038V and p.R881C.

GenotypingMethod: Just mentioned sequencing and ABCA4 screening to look for two variants p.L541V and p.A1038V and a third novel variant p.R881C.

PreviouslyPublished: N/a

Variant: 1) NM_000350.3(ABCA4):c.1622T>C (p.Leu541Pro) 2) NM_000350.3(ABCA4):c.3113C>T (p.Ala1038Val) 3) N/a

ClinVar ID: 1) 99067 2) 7894 3) N/a

**CAID: ** 3) Because there was not a reference or alternate allele provided in this article I was unable to find a CAID for p.R881C.

gnomAD: 1) Highest minor allele frequency was 0.00017 (https://www.ncbi.nlm.nih.gov/clinvar/variation/99067/) 2) Highest minor allele frequency was 0.00188 (https://www.ncbi.nlm.nih.gov/clinvar/variation/7894/) 3) N/a

SupplementalData: Figure 1 had information regarding imaging and other testing done on the patient that is vital for phenotypic characterization. Also, it mentions a variant known as p.R881C, but was unable to find anything on ClinVar or gnomAD.

This variant is found in compound heterozygosity with c.3386G>T p.(Arg1129Leu) in family MD-0247 in a previous publication (PMID: 23755871)

Case#: 11 year old female

DiseaseAssertion: Stargardt’s Disease

ParentalTesting: She was the product of an uncomplicated pregnancy born to a healthy Filipino mother and Italian/Irish father with no known family history of ocular disease. The mother and father were asymptomatic but not examined. Segregation analyses showed that both parents are asymptomatic carriers.

CasePresentingHPOs: HP:0007754, HP:0011462, HP:0008035

CasePhenotypeFreeText: The ABCA4 gene, when mutated, results in a spectrum of retinal degeneration, including Stargardt macular dystrophy, fundus flavimaculatus, autosomal recessive retinitis pigmentosa, and cone-rod dystrophy (1). Over 800 disease-associated ABCA4 gene mutations have been reported.

CaseNotHPOs: N/A

CaseNotPhenotypeFreeText: N/A

CasePreviousTesting: The proband underwent a full consultative ophthalmic examination at the Ocular Genetics Clinic at Wills Eye Hospital, including visual acuity, slit-lamp, and dilated fundus examination. Fundus autofluorescence and spectral-domain optical coherence tomography (Spectralis; Heidelberg Engineering), Goldmann visual field (Octopus 900 perimeter; Haag-Streit International), and intravenous fluorescein angiography were obtained. Full-field electroretinogram (Espion; Diagnosys LLC) and multifocal electroretinogram (Veris V.6.4.3; EDI Inc.) were performed in accordance with the International Society of Clinical Electrophysiology and Vision standards. Best-corrected visual acuity was 20/125 in the right eye and 20/200 in the left eye. The patient demonstrated eccentric fixation. Pupillary responses were normal. Slit-lamp examination was normal. Fundus examination revealed healthy optic nerves and retinal blood vessels, bilateral macular geographic pigmentary stippling with subretinal flecks in and around this area, and a blunted internal limiting membrane reflex (Fig. 1). Peripheral retina was normal.

GenotypingMethod: Genotyping microarray chips for ABCA4 can identify >98% of the most common mutations. In this report, we describe 2 novel ABCA4 variants in a patient with Stargardt disease. Bioinformatic and in silico analysis of the functional consequences of these variants provided compelling evidence for pathogenicity.

Variant: c.850_857delATTCAAGA and c.6184_6187delGTCT

CAID: CA10604079 and CA10604078

MultipleGeneVariants: N/A

PreviouslyPublished: N/A

AdditionalInfo: Bioinformatic assessment of the c.850_857delATTCAAGA mutation showed that it resulted in a truncated 317 amino acid polypeptide, devoid of several essential domains of the ABCA4 transporter. The c.6184_6187delGTCT mutation led to a premature stop codon at the C-terminal end of the protein, resulting in a loss of a total of 161 amino acid residues. Although less than 7% of the protein was absent, the important VFVNFA motif, present within the last 30 amino acids of the NBD2 domain, was deleted (Fig. 2). This motif is known to be critical to ABCA4 protein function, is highly conserved among members of the ABCA transporter subfamily, and has also been linked to Tangier disease in the ABCA1 protein (9). Removal of this motif in ABCA4 leads to a loss of retinal stimulated ATPase in vitro and energy transduction of the transporter (9, 10). Protein modeling predicted a loss of an essential β-sheet, which significantly altered its structure. The NBD domains are sites of ATP hydrolysis that provide energy for transport of R-PE through rod outer segment membranes. Enzymatic studies suggest that the NBD2 domain in particular provides energy necessary for translocation of retinal derivatives generated in the visual cycle. The structural changes in NBD2 would affect ABCA4 transporter’s ability to transport retinoids, leading to accumulation of cytotoxic lipofuscin in RPE cells and ultimately photoreceptor cell death.

Unable to annotate on PDF, so annotating here.

Case#: Proband #4, male, Chinese, onset at 12yo

DiseaseAssertion: stargardt

FamilyInfo: parents are deceased, so phase is unknown. daughter is an unaffected carrier of this variant

CasePresentingHPOs: HP:0025147, HP:0011507, HP:0000608

CaseHPOFreeText: BCVA=0.3/CF, mean retinal nerve fiber layer(µm)=167/154, Visual field(mean deviation)= 7.52/NA, fundus fluorescein angiography=type C (a pattern of speckled hypofluorescence and hyperfluorescence without central hypofluorescence)

CaseNotHPOs:

CaseNotHPOFreeText:

PreviouslyPublished: n/a

Variant: c.6289C > T p.(Pro2097Ser); c.4720G > T p.(Glu1574*) on targeted exome sequencing or WES

ClinVar: 2202780; 1460063

CAID: CA341277622; CA341283936

SupplementalData: n/a

This variant was not evaluated.

This variant is found in Supplemental Table S3, but this table lists frequencies and does not give case information

This variant is found in Supplemental Table S3, but this table lists frequencies and does not give case information

Case#: two affected sisters

DiseaseAssertion: Stargardt Disease

FamilyInfo: compound heterozygotes for the mutations. Unaffected family members did not carry either or had one of the two mutations.

CasePresentingHPOs: NR

CaseHPOFreeText: NR

CaseNotHPOs: NR

CaseNotHPOFreeText: NR

Genotyping Method: ABCA4 408 microsatellite

PreviouslyPublished: NR

Variant: NM_000350.3(ABCA4):c.5018+2T>C , NM_000350.3(ABCA4):c.655A>T

ClinVar: 265008, 632118

CAID: CA10588304, CA645372240

SupplementalData: NR

Case#: Patient#010455, Chinese, male, 18yo at onset

DiseaseAssertion: stargardt

FamilyInfo: n/a

CasePresentingHPOs: STGD1 diagnosis based on the following criteria: "a bilateral central vision defect; fundus displaying a beaten-bronze appearance and/or orange-yellow flecks in the retina from the macula to the midperiphery; fluorescein angiography presenting with a typical dark choroid; and normal to subnormal ERG results." BCVA=0.01/ 0.01

CaseHPOFreeText:

CaseNotHPOs:

CaseNotHPOFreeText:

PreviouslyPublished: n/a

Variant: p.P2097S; c.4906_4908del p.(Asn1636del) phase unknown

ClinVar: 2202780;

CAID: CA341277622;

SupplementalData: supplementary table S4 has phenotype information

PMID: 29162642

Gene: ABCA4

Disease: Stargardt disease

PMID: 24020726

Gene: ABCA4

HGNC ID: 34

Case#: a 45-year-old man from Sardinia, Italy

DiseaseAssertion: Cone rod dystrophy

FamilyInfo: Five members, this patient is the only one affected by CRD

CasePresentingHPOs: HP:0000505, HP:0007663, HP:0000603, HP:0001123, HP:0000608, HP:0007401, HP:0011504, HP:0000548, HP:0030329, HP:0000543

CaseHPOFreeText: 1998: Subacute central vision loss in both eyes, choroidal and RPE atrophy surrounding left fovea and small white patches of atrophy around right fovea. Pale appearance of optic disc in both eyes. Punctate retinal pigment epitheliopathy observed bilaterally in midperipheral retina, hyperfluorescent macular regions suggesting bull's eye maculopathy. Paracentral ring scotoma, surrounded by a relative annular scotoma, early and predominant involvement of photopic over scotopic responses; 2018: BCVA was bilateral light perception with visual field extinction. FAF showed a central round area of decreased autofluorescence corresponding to area of macular atrophy, surrounded by an area of relatively increased autofluorescence. Several roundish areas of reduced autofluorescence in midperipheral retina. Severe macular atrophy surrounded by a ring of preserved RPE in both eyes. Sparse pigmentary deposits in midperipheral retina of both eyes. Severe bilateral retinal thinning with disappearance of external retinal layers. Outer retina tubulations

CaseNotHPOs: HP:0025148

CaseNotHPOFreeText: No pigment deposits on optic disc, no dark choroid

Genotyping Method: Candidate gene approach on ABCA4 followed by whole exome sequencing

PreviouslyPublished: NR

Variant: NM_000350, c.4535C>G, p.P1512R

ClinVar: 99291

CAID: CA227203

SupplementalData: Patient's healthy brother showed the same molecular condition for ABCA4. Patient also has 2 novel frameshift mutations in C2orf71.

Case#: An 8-year old Hispanic female

DiseaseAssertion: Whole exome sequencing identified a homozygous ABCA4 missense variant (p.Arg602Trp) that has been identified as a Stargardt Disease mutation

FamilyInfo: consanguinity, her parents being first cousins, no family history of blindness. Familial cosegregation analysis was used, with both parents being heterozygous carriers.

CasePresentingHPOs: HP:0000529, HP:0000662, HP:0000556, HP:0002017,HP:0008046, HP:0031528, HP:0003678

CaseHPOFreeText: rapidly progressive vision loss, nyctalopia and retinal dystrophy, bilateral decreased vision following a febrile gastrointestinal illness with nausea and vomiting, Initial visual acuity was 20/60 at distance and 20/30 at near in both eyes, after 2 years visual acuities of 20/200 at distance in both eyes, attenuated vessels and multiple subretinal blister-like elevations, Cycloplegic retinoscopy detected very mild hyperopia and astigmatism in both eyes (OD: + 1.00 sphere + 1.00 cylinder axis 110 degrees; OS: + 0.75 sphere + 0.50 cylinder axis 60 degrees)

CaseNotHPOs: NR

CaseNotHPOFreeText: no evidence of a diffuse post-infectious/inflammatory process

Genotyping Method: DNA analysis by whole exomic sequencing

PreviouslyPublished: No

Variant: NM_000350.3:c.1804C>T

ClinVar:99084

CAID:CA226932