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Noting that none of the other TSG pathways were mutated in these tumors shows how little we actually can prove about PDA. This cancer can have many mutations that accelerate the disease and we aren't truly sure what mutation combinations are the cause of this cancer's aggressiveness.

This sentence highlights the main scientific problem the study is addressing. Just because mutations like KRAS and TP53 are commonly found in pancreatic cancer does not prove they are sufficient or that they must occur together to cause disease. Observing mutations in patient samples cannot determine causation. Therefore, the authors use a genetically engineered mouse model to systematically test whether combining KrasG12D and Trp53R172H is enough to drive invasive and metastatic PDA.

So document the process for updating the site in an SOP, making sure they're written in sufficient detail to be executable (by an agent—a user agent—sans LLMs), and then host the documents that detail those procedures on your site, as first-class content.

"Updating the site" then entails 1. consulting the SOP, and 2. carrying out the procedure there (either manually, or having your agent do it).

This is all achievable on a static site, provided there are Web-accessible (and, ideally, CORS-enabled) endpoints to control what content appears there (like the GitHub API, to name one example).

Requires active engagement from the reader.

Plot simple definition

This is true because if not analyzing well it leads to confusion.

This paragraph stood out to me because it shows how people can still build close relationships even when they aren’t communicating face-to-face. I think this connects to social penetration theory because relationships grow when people share more personal information over time, and that can still happen through texting or social media. Even if technology limits things like body language or tone of voice, people can still get to know each other by communicating regularly and opening up more. The part about COVID-19 makes this feel realistic because a lot of relationships had to move online, but people still stayed connected. The hyperpersonal model is also interesting because it suggests online communication can sometimes make relationships feel even closer, which might be because people feel more comfortable sharing personal things. Overall, this paragraph shows that relationships can still develop as long as people keep sharing information and communicating.

Coming soon to this special series on Myeloid Cells: Leading experts provide their perspectives and answer provocative questions surrounding myeloid cells. Stay tuned!

I found this quote quite resonant, highlighting the inherent tensions in the activity of preservation. Though, I don't know if I agree with what the author says in the following passage regarding archivists being in the business of saving souls! In my estimation, an archivist is more like a shepherd, a docent, or perhaps, to use a million dollar word, an interlocutor between life and death, between the past and present (and so too the future). The article also made me think about hospices, of course, and the philosophy of palliative care - how one passes from this life to the next, with what dignity, in what repose. Moreover, the quote draws, for me, an important analogy between material objects and the temporal body - how one is, in effect, substituted for the other, allowing this transfiguration, as the author puts it.

Le TDAH : Entre Trouble Neurodéveloppemental et Neurodivergence

Résumé Exécutif

Ce document propose une synthèse des connaissances actuelles et des débats entourant le Trouble du Déficit de l'Attention avec ou sans Hyperactivité (TDAH).

Longtemps considéré comme une pathologie exclusivement infantile, le TDAH est désormais reconnu comme un trouble persistant à l’âge adulte, touchant environ 2,5 % de cette population.

Le cœur du débat oppose une vision purement clinique, centrée sur le traitement des symptômes (inattention, agitation, impulsivité), à une approche basée sur la neurodiversité, percevant ces différences comme des atouts potentiels pour la société.

Bien que le traitement médicamenteux (méthylphénidate) reste le plus efficace pour réduire les risques de mortalité et améliorer le quotidien, l'adaptation de l'environnement social et professionnel apparaît comme un levier crucial pour l'intégration et le bien-être des personnes concernées.

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1. Définition et Nature du TDAH

Un trouble de la régulation de l'attention

Le TDAH ne se définit pas par une absence totale d'attention, mais par une difficulté à la réguler.

Il se manifeste par :

• Une distractibilité marquée : Difficulté à rester concentré sur des tâches routinières ou ennuyeuses.

• Une agitation motrice : Un besoin constant de mouvement, parfois intériorisé.

• Une impulsivité : Des réactions spontanées difficiles à cadrer.

• Une variabilité attentionnelle : L'attention est souvent détournée de son objet initial vers des stimuli environnementaux que le cerveau ne parvient pas à filtrer.

La perspective de la neurodivergence

Le concept de neurodiversité, formulé en 1998 par Judy Singer, postule qu'aucun cerveau n'est identique.

Dans ce cadre, la neurodivergence désigne un fonctionnement cérébral s'écartant de la moyenne.

Le Professeur André Zimpel suggère que le TDAH pourrait être perçu comme un "système d'alarme" pour la communauté, signalant un excès de monotonie ou de sédentarité dans notre environnement moderne.

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2. Diagnostic et Évolution Démographique

Un sous-diagnostic chez l'adulte

Bien que les cas recensés augmentent, le TDAH reste largement sous-diagnostiqué chez les adultes.

• Estimation : 2,5 % des adultes sont concernés.

• Le cas spécifique des femmes : Le diagnostic est souvent plus tardif chez les filles (comme l'illustre le parcours de Vanessa Bolk, diagnostiquée à 28 ans).

Elles présentent souvent un "TDAH caché" car elles développent de meilleures capacités d'adaptation sociale, bien que le sentiment de chaos intérieur persiste.

Historique de la perception clinique

| Année | Évolution de la conception | | --- | --- | | 1844 | Heinrich Hoffman décrit l'instabilité motrice chez l'enfant. | | 1902 | Frédéric Schtill lie les symptômes à un "dysfonctionnement cérébral minimal". | | 1980 | Le terme officiel "TDAH" s'impose. | | Actuel | Reconnaissance du trouble comme une condition permanente et non uniquement infantile. |

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3. Impacts Sociaux et Risques Sanitaires

Conséquences sur le parcours de vie

Le TDAH non pris en charge peut mener à des trajectoires de vie difficiles :

• Échecs scolaires et abandons de formations professionnelles.

• Sentiment de rejet et "blessure narcissique" (impression de ne pas être aimé sans traitement).

• Vulnérabilité accrue à la dépression, au burnout et à l'anxiété.

Santé et espérance de vie

Des données récentes indiquent une réduction de l'espérance de vie de 7 à 8 ans chez les personnes atteintes de TDAH.

Cette surmortalité s'explique par :

• Un risque accru d'accidents et de suicides.

• Des facteurs de risque comportementaux : tabagisme précoce, consommation d'alcool, troubles alimentaires menant au surpoids.

• Des maladies cardio-vasculaires liées au stress chronique de l'inadaptation.

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4. Stratégies de Traitement et de Prise en Charge

Le traitement médicamenteux

Le méthylphénidate (connu sous le nom de Ritaline) est un stimulant du système nerveux central.

Paradoxalement, il aide les personnes hyperactives à se calmer en leur permettant de mieux cadrer leur impulsivité et de lutter contre une "fatigue" liée à la monotonie.

• Efficacité : Supérieure à la psychothérapie seule pour les symptômes primaires.

• Bénéfices : Réduction documentée des accidents et des suicides (études scandinaves).

• Effets secondaires : Troubles du sommeil, de l'appétit et mains froides.

Innovations et thérapies alternatives

• Stimulation cérébrale par courant continu : Une méthode de recherche visant à modifier la communication entre les cellules nerveuses pour améliorer l'attention (séances d'environ 21 minutes).

• Psychothérapie comportementale : Utile pour gérer les conséquences psychologiques et organiser le quotidien, bien que moins efficace que les médicaments sur le déficit attentionnel pur.

• Activité physique : Recommandée comme régulateur naturel.

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5. Le TDAH comme Atout pour la Société

Malgré les difficultés, les profils TDAH possèdent des compétences inestimables dans des contextes spécifiques :

• Tolérance au risque : Dans un monde en bouleversement, leur capacité à agir sous pression et leur absence de peur face au risque sont cruciales.

• Pensée visuelle et conceptuelle : À l'ère de l'intelligence artificielle, leur aptitude à penser en images plutôt qu'en checklists est un avantage (ex: en cybersécurité).

• Créativité : Une capacité à apporter des perspectives divergentes, essentielles à l'intelligence globale d'une société.

Conclusion :

La gestion du TDAH appelle à un double mouvement.

D'une part, une prise en charge médicale rigoureuse pour ceux qui souffrent de leur fonctionnement cérébral.

D'autre part, une adaptation de l'environnement social et professionnel (flexibilité des procédures, tolérance à l'agitation) pour permettre à ces individus d'exprimer leur potentiel sans s'épuiser à vouloir rejoindre une norme rigide.

Briefing : Génétique et Réussite Scolaire

Synthèse de la problématique

Ce document synthétise l'intervention de Franck Ramus concernant l'influence des facteurs génétiques sur la réussite scolaire.

L'analyse repose sur deux postulats fondamentaux : les enfants arrivent à l'école avec des inégalités déjà constituées, et ces inégalités résultent d'une combinaison de facteurs environnementaux (sociaux, familiaux, prénataux) et génétiques.

L'objectif est de déconstruire les réticences idéologiques face à la génétique comportementale en s'appuyant sur des données probantes issues de la recherche contemporaine.

Points clés à retenir :

• Héritabilité : Environ 50 % des différences d'intelligence générale et 30 % des différences de réussite scolaire entre individus sont attribuables à des facteurs génétiques.

• Scores polygéniques : Ces nouveaux outils de mesure expliquent entre 11 % et 13 % de la variance du niveau d'études, un ordre de grandeur comparable à celui du revenu des parents ou du niveau d'éducation de la mère.

• Interaction gène-environnement : L'environnement fourni par les parents est lui-même partiellement influencé par leur propre patrimoine génétique (concept de "nurture génétique").

• Implications pédagogiques : La connaissance des bases génétiques ne justifie pas l'inaction, mais plaide pour une différenciation pédagogique accrue afin de traiter l'hétérogénéité réelle des élèves.

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I. Déconstruction des obstacles idéologiques et conceptuels

Le débat sur la génétique est souvent entravé par des peurs irrationnelles que la recherche scientifique s'efforce de lever :

1. Le Réductionnisme : Contrairement aux critiques, les biologistes n'ambitionnent pas de réduire l'humain à ses gènes.

Ils prônent une compréhension multi-niveaux (moléculaire, cellulaire, neuronal, psychologique et sociologique).

2. Le Déterminisme : Les gènes ne sont pas un destin "gravé dans le marbre".

Les influences environnementales sont tout aussi déterminantes que les influences génétiques ; la science cherche simplement à identifier les causes, quelles qu'elles soient.

3. Le Paralogisme Naturaliste : L'idée que ce qui est "naturel" (génétique) serait acceptable ou immuable est un biais de raisonnement.

La société se construit souvent en réaction à la nature pour réduire les injustices.

4. Le Paralogisme Moraliste : Nier un fait scientifique au motif que ses implications morales déplaisent revient à prendre ses désirs pour des réalités, ce qui nuit à l'élaboration de solutions efficaces.

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II. Modélisation de la réussite scolaire

La réussite scolaire est déterminée par une structure complexe de facteurs interactifs :

Facteurs de réussite

| Catégorie | Éléments clés | | --- | --- | | Facteurs Externes | Enseignement, moyens financiers, opportunités, effort personnel. | | Capacités Cognitives | Langage, mémoire de travail, attention, raisonnement abstrait. L'intelligence générale (QI) est la moyenne pondérée de ces fonctions. | | Facteurs "Non-Cognitifs" | Motivation, personnalité (conscienciosité, ouverture), dispositions à l'effort. |

Dynamique des boucles de rétroaction

• L'effort améliore les capacités cognitives (la scolarisation est le meilleur levier connu pour augmenter l'intelligence).

• La réussite renforce la motivation, créant un cercle vertueux.

• Le génome et l'environnement agissent en amont sur le développement de ces capacités et traits de personnalité.

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III. Preuves scientifiques de l'influence génétique

La science mobilise trois types de preuves convergentes pour établir le rôle de la génétique :

1. Études d'apparentés (Jumeaux et adoptions)

• Adoption : Sur le long terme, les scores de QI des enfants adoptés sont plus corrélés à ceux de leurs parents biologiques qu'à ceux de leurs parents adoptifs (corrélation tendant vers zéro avec les parents adoptifs à l'âge adulte).

• Jumeaux : Les jumeaux monozygotes (100 % de gènes communs) se ressemblent beaucoup plus que les jumeaux dizygotes (50 % de gènes communs) pour l'intelligence et la réussite scolaire.

• Conclusion : L'héritabilité de l'intelligence générale est estimée à environ 50 %.

2. Études des mutations génétiques

• Plus de 1 000 gènes ont été identifiés comme ayant un impact sur l'intelligence en cas de mutation (ex: trisomie 21, gène FoxP2 pour le langage, gènes associés à la dyslexie).

• Le continuum de sévérité : Il n'y a pas de rupture nette entre le pathologique et le normal.

Les mutations peuvent être fortes (suppression d'une protéine) ou faibles (altération de la quantité d'expression), produisant un impact graduel sur les capacités cognitives.

3. Études génomiques (GCTA et Scores Polygéniques)

• Méthode GCTA : Mesure directe de la similarité génétique sur l'ADN. Elle confirme une héritabilité de 30 à 35 % pour l'intelligence et les matières scolaires (lecture, maths, sciences).

• Scores Polygéniques (PGS) : Compilation de milliers de petites variations génétiques. Le score "EA3" explique 11 à 13 % de la variance du niveau d'études.

◦ Exemple : Un individu dans le quintile supérieur de score génétique a 50 % de chances d'obtenir un diplôme du supérieur, contre 10 % pour le quintile inférieur.

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IV. Complexité : L'interdépendance Gènes-Environnement

L'analyse démontre que gènes et environnement ne sont pas des entités isolées mais profondément imbriquées.

La confusion Gène-Environnement ("Genetic Nurture")

Les caractéristiques environnementales (nombre de livres à la maison, revenus) sont en partie héritables.

• Les gènes des parents influencent leurs propres capacités cognitives et leur statut socio-économique.

• Ce statut détermine l'environnement qu'ils créent pour l'enfant.

• Résultat : Environ 50 % de la corrélation entre le milieu social et la réussite de l'enfant passe par la transmission génétique, et non par une influence environnementale pure.

Effet additif

Les facteurs sont cumulatifs :

• Injustice maximale : Faible score génétique + milieu familial défavorisé (< 10 % de réussite).

• Privilège maximal : Fort score génétique + milieu riche (60 % de réussite).

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V. Limites et applications pratiques

Faible valeur prédictive individuelle

Malgré leur intérêt statistique en recherche, les scores polygéniques ne permettent pas de prédire le destin d'un individu spécifique avec précision.

La marge d'erreur est trop colossale pour justifier des décisions d'orientation ou de sélection (ex: sélection d'embryons).

Le niveau scolaire réel à un instant T reste un bien meilleur prédicteur que le génome.

Message aux acteurs de l'éducation

Pour les enseignants, les causes (génétiques ou sociales) importent peu dans l'action immédiate car ils n'ont aucun levier sur le passé de l'enfant.

Recommandations :

1. Cibler le présent : Intervenir directement sur les manques cognitifs observés (ex: vocabulaire), quelle qu'en soit l'origine.

2. Pratiquer la différenciation : Puisque les enfants sont inégaux, les traiter de manière égale (uniforme) accroît les inégalités.

3. Équité vs Égalité : Adopter une pédagogie inégale (aider davantage ceux qui en ont besoin) pour compenser les différences de prédispositions.

Conclusion : La connaissance génétique ne doit pas être vue comme une menace mais comme un levier pour améliorer les recherches en sciences sociales et affiner les politiques éducatives en tenant compte de la réalité biologique de l'hétérogénéité humaine.

[https://media.newyorker.com/photos/68d41dd5a787e07278d41d3f/master/w_960,c_limit/r47425.jpg

This image visually represents Berners-Lee as surrounded by browser windows, symbolizing how his invention became the foundation of the modern digital world. The web has expanded far beyond its original academic purpose and now shapes communication, commerce, and everyday life. It also suggests the overwhelming scale of the web today compared to its original vision.

Hypertext is the core concept behind the web. It allows documents to link to each other instead of existing in isolation. Vannevar Bush’s Memex concept influenced Berners-Lee’s creation of HTML. This shows that the web was built on earlier ideas about organizing knowledge in a connected and accessible way.

This shows how the web shifted from an open system to one controlled by large corporations. Originally, anyone could create a website and participate equally. Now, platforms like Google, Facebook, and Amazon control access to information and user data. This represents a major transformation from the decentralized vision Berners-Lee originally intended.

Gopher was an alternative system that organized information using hierarchical menus instead of hyperlinks. If Gopher had become dominant, the web might have looked more like a rigid file system instead of the flexible, interconnected structure we use today. HTML’s hyperlink model allowed information to be connected in a decentralized way, which made it more scalable and creative.

This is one of the most important moments in the history of computing. HTML was created so documents could be structured in a way that computers and humans could both understand. Instead of files being isolated on individual machines, HTML allowed them to be linked together into a global network. Without HTML, the web would likely have remained fragmented, similar to early systems like CompuServe or AOL. HTML made the web universal and accessible.

• description: image depicts a mass protest of british patriots waving the union jack flag
• context: viral image shared in support of far right and anti immigration groups.
• Image has been debunked as AI generated: objects in the foreground (flags, faces and limbs) bleed together.

Stephen McDermott, “Debunked: A viral image appearing to show UK 'patriots' waving British flags is AI-generated,” The Journal, September 4, 2025, https://www.thejournal.ie/uk-flags-london-patriots-ai-generated-6807401-Sep2025/

This sentence defines the central question of the study. Although pancreatic ductal adenocarcinoma has ductal morphology, it remains unclear whether precursor lesions arise from true ductal cells or from acinar cells that undergo reprogramming. The authors test whether oncogenic KRAS expands existing ductal cells or instead drives acinar cells to adopt a duct-like state through factors such as Sox9. Defining this distinction is essential for identifying the true cell of origin in PDA.

This brings to my mind the historical example of the Mechanical Turk, and the current amazon based processes of the same name. Because the internet allows a level of abstraction from the labor which its existence necessitates, there is a lot of violence wreaked on the working classes that is never seen or discussed. I wonder if there is a way of providing compensation for the violence of these images in the jobs of the moderators.

example of flat character functions

Flat characters: static to serve a purpose in story

Archetypes do not strictly apply to characters

Secondary/Minor characters don't need to meet the main character

Antagonist definition

Protagonist definition

I have never heard of the word charecterisation before and now I understand the meaning

Question 3- Blake Morgan’s article, How AI Is Changing the Role of Teachers in Education, argues that artificial intelligence is transforming teaching by automating administrative tasks and enhancing personalized learning. Morgan emphasizes that AI can free teachers from routine grading and paperwork, allowing them to focus on more meaningful interactions with students. Morgan highlights that AI enables more individualized learning experiences, as teachers can use data-driven insights to adjust lessons to each student’s needs. Morgan also points out that AI requires teachers to develop new skills, including digital literacy and the ability to guide ethical AI use in the classroom. Overall, Morgan advocates that the purpose of the article is to show how AI can empower teachers and improve student learning outcomes while acknowledging the need for careful integration.

Question 2- I liked Blake Morgan’s article better because it provides practical examples of how AI tools are directly reshaping teachers’ responsibilities in classrooms.

Question 1- Author: Blake Morgan, "How AI Is Changing the Role of Teachers in Education,"

Unfortunately, the radians column is messed up, too tiny. $$30^{\circ}\longleftrightarrow\frac{\pi}{6}$$ $$45^{\circ}\longleftrightarrow\frac{\pi}{4}$$ $$60^{\circ}\longleftrightarrow\frac{\pi}{3}$$ $$90^{\circ}\longleftrightarrow\frac{\pi}{2}$$ $$120^{\circ}\longleftrightarrow\frac{2\pi}{3}$$ $$135^{\circ}\longleftrightarrow\frac{3\pi}{4}$$

This gets at the ethical consideration of how the internet ought to be split up, and if there should be an overall governing body to the internet. There's a thread of thought in internet ethics that purports the internet as a location which allows free speech for all, but we've seen that allowing sites like 4chan and in some cases reddit has demonstrated real harm and resulted in real violence. The issue reminds me of the tolerance paradox.

Scrolling through other people's highlight reels can make your own life feel underwhelming by comparison. like everyone else is doing more, living more, looking better. That constant over-comparison can build into real anxiety and a sense that you're falling behind somehow.

Learning about things like doomscrolling, trauma dumping, Munchausen by Internet, and digital self-harm was genuinely eye-opening. These point to something deeper about how these platforms affect people psychologically in ways that aren't always obvious.

With these moderations, social media has become safer. I do not block people, but when they offend me or do something bad, I'll block them. I'm glad that nowadays we have social media moderation because it prevents people from getting their feelings hurt. When people feel safer and more comfortable, they are more likely to continue using the platform. This shows why companies are incentivized to provide moderation tools; it protects users and helps retain them.

Having a system with no moderators puts all the responsibility on the person running the site, which sounds like freedom until you realize what that actually means. You control everything, but you're also accountable for everything. Spam, illegal content, anything that ends up there is on you. That's manageable when a site is small, but as it grows and gets more attention, it becomes a real problem fast.

If the system gives validation and success, why would someone want to escape it?

Money systems and society’s rules about women work together to make women feel like they always need to improve how they look and act

Constant comparison creates anxiety because people compete with perfected photos.

Tolentino explains that fashion and advertising don’t just show beauty standards, they make people change themselves to match those standards.

Definition: a cycle where behavior keeps reinforcing itself

Tolentino shows how capitalism, feminism, and consumer culture combine to turn self improvement into a lifelong responsibility.

I'm confused on what this sentence means.

Tolentino shows optimization started as an economic idea but slowly spread into everyday life thinking.

Self improvement feels empowering but creates a lot of pressure still

She critiques a version of feminism that treats all choices as empowerment, but those choices are shaped by society pressure

Tolentino is trying to say that instead of reducing beauty pressure, society tries to include everyone inside the beauty system but the problem never fully goes away

Even movements like sever editing which is meant to fight unrealistic beauty can create new pressures which now causes people to think they must look naturally perfect all the time

Instead of blaming unrealistic standards, women blame themselves. The system shifts responsibility from society to the individual.

Tolentino is saying women may think they freely choose to live up to beauty standards , but those choices are shaped by social pressure. Even as women gain independence, beauty expectations actually increase.

Definition: believing you cannot escape a situation

Definition: the idea that clothes affect how you think and behave

Definition: different versions or variations of something

Definition: something that motivates behavior

Definition: a way of thinking or a model people follow

Question: why does society treat appearance like a measure of character?

Summary: omen already balance work and home responsibilities, but beauty expectations add more stress to the job. Maintaining appearance requires constant effort.

People are literally pay money to become better at surviving stressful lifestyles

People pay money to become better workers and be more productive

Question: Is choice real if social pressure never disappears?

Definition: the extra benefit gained from one more choice or product

Definition: something that is only temporary

Question: why is moral value connected to appearance?

Fitness culture helps people survive capitalism instead of escape it.

Summary: the author is trying to say exercise here isn’t about joy or health, it trains people to endure stressful modern life and makes you work way harder.

Definition: unstable or insecure living/working conditions

Things that used to be optional like working constantly now feels required just to survive.

Summary: Tolentino is saying modern success looks like being busy and efficient all the time. People think productivity equals happiness even though it keeps them stuck working nonstop.

Question: what parts of life are we losing when everything becomes optimized for productivity?

Question: are people improving themselves or just trying to survive unrealistic expectations?

Paraphrase: even eating is designed for efficiency so people can keep working or consuming media.

Things meant to feel fun (fitness, beauty, lifestyle trends) become pressure and work.

Definition: a fast paced system where productivity and improvement never stop

Paraphrase: Trying to perfectly perform womanhood is impossible and unfair.

Does social media make comparison worse because the images feel more real?

Even when beauty standards change, pressure on women never disappears, it just takes a new form.

Tolentino is trying to say her life looks natural, but actually requires a lot of money and effort.

Definition: very careful and detailed

Women are expected to constantly improve their appearance, lifestyle, and productivity which means they are never staying satisfied.

Is Tolentino criticizing social media for turning real people into products?

Definition: something that can make money

Tolentino is saying society keeps creating the same type of “perfect woman,” even though trends change.

There are cases where that makes sense for the government to be in control, to block illegal content, hate speech, or misinformation. But it can just as easily become a tool to silence people, suppress different points of view, and limit freedom of expression. And that's where it gets complicated.

An important thing to consider when imposing censorship upon a certain platform is the likelihood of certain groups/communities of just migrating to another platform with less censorship. Is banning these groups the most effective way to curb hate speech?

User safety is a major concern for social media platforms. When harassment, trolling, or unsafe political content spreads, users may feel uncomfortable and leave the platform. Because of this, companies have a right to moderate harmful content to maintain trust and keep users engaged.

This brings to quesiton many site's option for anonymity towards users for any purpose. We find that most times people feel more comfortable when it comes to online posting because there are no immediate repercussions to their actions. Anonymity provides these users an extra protective layer towards their hurtful actions and can provide stronger hateful media platform uses.

Oftentimes bigger companies cut corners in order to maintain their maximum output and income. With being paid less, their working conditions are extremely severe and inhumane. These "max-moderators" lose their social and moral integrity in order to produce more.

Moderation is a field that contains a lot of gray area — it is important to consider prioritizing what needs to be taken down first, and then determining what is even worth removing. Clearer legislation is the first step to making moderators’ lives easier.

I feel like this is the biggest problem that is currently happening on many social media companies, which leads to less better performance. I think companies should have their own department of moderators that are well-trained for better moderation.

So important to consider this factor

Makes sense. Regarding the methods, I think that a logitudinal study with more cohorts would be better, instead of following just one cohort.

Very informative and a good way to explain what factors may hinder learning

Not a lot of time to assess and again, there are others factors that should be considered

What factors lead to this?

How is this data being used for good?

peertube keynote by Dirk Schrödter at EU Open Source Policy Summit 2026 (he's with the German Land Schleswig-Holstein

This statement highlights that who sets the rules determines "what should be restricted" and "who is more likely to be restricted." Applied to platforms, this means content moderation is not a neutral technology, but rather an extension of a "social contract": if the rule-makers primarily represent powerful groups, moderation may draw its boundaries in their own favor, making vulnerable groups more susceptible to collateral damage or silencing. Consider Rawls's "veil of ignorance": if you didn't know you would be a minority, immigrant, sexual minority, or political dissident in the future, you would be more inclined to design a more appealable, transparent, consistent, and protective moderation system for the vulnerable. Therefore, "abstract moderation" here becomes a political and justice issue: moderation is not just about controlling extreme content, but also about preventing moderation power from being used to perpetuate inequality.

The "moderation" here emphasizes maintaining a sustainable coexistence between extremes: neither allowing all expression (leading to harassment, intimidation, and the proliferation of misinformation) nor excessive suppression (suffocating public discussion and diversity). Social media "content moderation/traffic limiting/banning" essentially translates this abstract "moderation" into enforceable boundaries, aiming to maintain basic order and trust on the platform. The problem is that when platforms concretize "moderation," they often use simple rules (keywords, model confidence levels, uniform policies) to replace complex contexts, thus easily turning "balance" into "brutal division." Therefore, content moderation is related to the moderation of moral ethics: it is essentially a governance practice of the "golden middle way," only often not done delicately or fairly enough.

I think that misinformation should be moderated, harassment or bullying. I think these are big problems that might undermine the users experience, and creates safeguards for them to enjoy the social media platform as they wish. This is beneficial for all users to make rational decisions.

Yes, I have reported someone for impersonating someone I know. If you let them, people can impersonate others and do weird things with it, like scam people. I think that social media not tolerating this really curbs that kind of scamming. For hate speech, I have probably when I was younger, but nowadays I don't see it much. I think in unmoderated spaces, everyone can be heard therefore no one can be heard.

It's nuts that no mainstream browser has incorporated basic native table-editing controls by now. (They wasted no time adding JSON pretty-printers—unsurprising, really, given that their main actual concern is propping up the JS–industrial complex and the professional developer class and not real users, which they don't actually give a shit about, contra the Priority of Constituencies.)

There is and has been for a long time a huge opportunity for a "Photopea for CSV (and JSON)" to show up and take off.

see reports https://www.woodmac.com/store/industry-sector/power-and-renewables/

https://www.reddit.com/r/typewriters/comments/1rbydwu/soviet_era_typewriter/

It's important to cite sources

https://www.reddit.com/r/typewriters/comments/1rc3m66/keys_arent_making_contact_with_paper_to_strike/

A way to organize your introduction

I have no idea what is being said.

I do not understand a lot of these words but bleft does not seem like the right word.

I think its supposed to say see

Is this supposed to say difficult?

This is wrong.

Interacción ciudadana con diseño e implementación de políticas gracias a tecnologías de comunicación digitales https://www.youtube.com/watch?v=CEN4XNth61o&t=490s cooperación sin coordinación (¿crianza mutua?) https://www.youtube.com/watch?v=CEN4XNth61o&t=490s Github pero circulo de palabra https://www.youtube.com/watch?v=CEN4XNth61o&t=490s "las personas que experimentan la participación no tienes poder legislativo, y las que tienen poder legislativo no experimentan la participación https://www.youtube.com/watch?v=CEN4XNth61o&t=490s

What is the difference between this approach and a random effect?

但是社媒健康信息，所谓的lay knowledge的弊端就是，你必须需要知道分辨，上面存在很多奇葩疗法、自创疗法、错误信息等

社媒平台确实提供了一个很好的空间、环境，让患者们实现交流、学习、自我护理

大家都在使用社交媒体分享健康信息、获取健康信息，这就好像转变为一种规范性准则，排挤了其他的意识形态和行为，具体来说，就是你得意识到，还有一大批人他不上网、不用社交媒体、不在社交媒体上关注健康方面知识，然而“这种被重新划定的医学的边界”默认所有人都可以通过这种方式获得基础知识并且实现自我护理，拿着对于某些患者是负担，因为他们其实做不到

反应两件事：1.患者在社交媒体上贡献信息、分享感受，但是最终却被医疗保健行业、国家获利，甚至有营利组织也从中获利（例如诊所） 2.既然捐献个人健康信息和劳动造福了更广泛的人群，那是否意味着一种digital divide，设备不先进或者少看健康论坛、少看社交媒体的人呗排除在外

eLife Assessment

This important study investigates how structurally diverse cardenolide toxins in tropical milkweed, especially mixtures containing nitrogen- and sulfur-containing variants, influence monarch caterpillar feeding, growth, and toxin sequestration. The experiments suggest that chemical diversity within a single group of plant toxins can have combined effects on even highly specialized herbivores that differ from the effects of each toxin alone. However, as the mixture design does not fully separate true diversity effects from the influence of the N,S-cardenolides themselves and the ecological basis for the chosen natural ratios remains weakly justified. As a result, the broader conclusions remain incomplete and would require more fully justified concentration regimes, mixture treatments that exclude N,S-cardenolides, and tests on living plants and non-adapted herbivores to firmly support the proposed coevolutionary interpretation.

Reviewer #1 (Public review):

Summary:

In the ecological interactions between wild plants and specialized herbivorous insects, structural innovation-based diversification of secondary metabolites often occurs. In this study, Agrawal et al. utilized two milkweed species (Asclepias curassavica and Asclepias incarnata) and the specialist Monarch butterfly (Danaus plexippus) as a model system to investigate the effects of two N,S-cardenolides-formed through structural diversification and innovation in A. curassavica-on the growth, feeding, and chemical sequestration of D. plexippus, compared to other conventional cardenolides. Additionally, the study examined how cardenolide diversification resulting from the formation of N,S-cardenolides influences the growth and sequestration of D. plexippus. On this basis, the research elucidates the ecophysiological impact of toxin diversity in wild plants on the detoxification and transport mechanisms of highly adapted herbivores.

Strengths:

The study is characterized by the use of milkweed plants and the specialist Monarch butterfly, which represent a well-established model in chemical ecology research. On one hand, these two organisms have undergone extensive co-evolutionary interactions; on the other hand, the butterfly has developed a remarkable capacity for toxin sequestration. The authors, building upon their substantial prior research in this field and earlier observations of structural evolutionary innovation in cardenolides in A. curassavica, proposed two novel ecological hypotheses. While experimentally validating these hypotheses, they introduced the intriguing concept of a "non-additive diversity effect" of trace plant secondary metabolites when mixed-contrasting with traditional synergistic perspectives-in their impact on herbivores.

Weaknesses:

The manuscript has two main weaknesses. First, as a study reliant on the control of compound concentrations, the authors did not provide sufficient or persuasive justification for their selection of the natural proportions (and concentrations) of cardenolides. The ratios of these compounds likely vary significantly across different environmental conditions, developmental stages, pre- and post-herbivory, and different plant tissues. The ecological relevance of the "natural proportions" emphasized by the authors remains questionable. Furthermore, the same compound may even exert different effects on herbivorous insects at different concentrations. The authors should address this issue in detail within the Introduction, Methods, or Discussion sections.

Second, the study was conducted using leaf discs in an in vitro setting, which may not accurately reflect the responses of Monarch butterflies on living plants. This limitation undermines the foundation for the novel ecological theory proposed by the authors. If the observed phenomena could be validated using specifically engineered plant lines-such as those created through gene editing, knockdown, or overexpression of key enzymes involved in the synthesis of specific N,S-cardenolides-the findings would be substantially more compelling.

Reviewer #2 (Public review):

I have reviewed both the original and revised version of this manuscript and while no additional experiments were added, I find the interpretations and discussion of the limitations of the study have improved. This is appreciated.

My original concern regarding the mixture treatments largely remains. Figure 4 nicely shows that the mixtures are more potent than the average of all single compounds. However, Fig S3 shows that the effects of mixtures are not significantly different from effects of at least one, single N,S compound (voruscharin or uscharin) across all measured growth/sequestration responses. Essentially, the effects of single N,S compounds is similar to mixtures (which also contain N,S compounds).

While the current results are certainly interesting as presented, in my view the main takeaway of the manuscript would be more compelling if it could be demonstrated that it isn't simply the presence of N,S compounds in the mixtures driving the observations. For example, does a mixture of all compounds except voruscharin or uscharin still have stronger growth/sequestration effects compared to single non-N,S compounds?

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

In the ecological interactions between wild plants and specialized herbivorous insects, structural innovation-based diversification of secondary metabolites often occurs. In this study, Agrawal et al. utilized two milkweed species (Asclepias curassavica and Asclepias incarnata) and the specialist Monarch butterfly (Danaus plexippus) as a model system to investigate the effects of two N,S-cardenolides - formed through structural diversification and innovation in A. curassavica-on the growth, feeding, and chemical sequestration of D. plexippus, compared to other conventional cardenolides. Additionally, the study examined how cardenolide diversification resulting from the formation of N,S-cardenolides influences the growth and sequestration of D. plexippus. On this basis, the research elucidates the ecophysiological impact of toxin diversity in wild plants on the detoxification and transport mechanisms of highly adapted herbivores.

Strengths:

The study is characterized by the use of milkweed plants and the specialist Monarch butterfly, which represent a well-established model in chemical ecology research. On one hand, these two organisms have undergone extensive co-evolutionary interactions; on the other hand, the butterfly has developed a remarkable capacity for toxin sequestration. The authors, building upon their substantial prior research in this field and earlier observations of structural evolutionary innovation in cardenolides in A. curassavica, proposed two novel ecological hypotheses. While experimentally validating these hypotheses, they introduced the intriguing concept of a "non-additive diversity effect" of trace plant secondary metabolites when mixed, contrasting with traditional synergistic perspectives, in their impact on herbivores.

Weaknesses:

The manuscript has two main weaknesses. First, as a study reliant on the control of compound concentrations, the authors did not provide sufficient or persuasive justification for their selection of the natural proportions (and concentrations) of cardenolides. The ratios of these compounds likely vary significantly across different environmental conditions, developmental stages, pre- and post-herbivory, and different plant tissues. The ecological relevance of the "natural proportions" emphasized by the authors remains questionable. Furthermore, the same compound may even exert different effects on herbivorous insects at different concentrations. The authors should address this issue in detail within the Introduction, Methods, or Discussion sections.

Second, the study was conducted using leaf discs in an in vitro setting, which may not accurately reflect the responses of Monarch butterflies on living plants. This limitation undermines the foundation for the novel ecological theory proposed by the authors. If the observed phenomena could be validated using specifically engineered plant lines-such as those created through gene editing, knockdown, or overexpression of key enzymes involved in the synthesis of specific N,S-cardenolides - the findings would be substantially more compelling.

Reviewer #2 (Public review):

This study examined the effects of several cardenolides, including N,S-ring containing variants, on sequestration and performance metrics in monarch larvae. The authors confirm that some cardenolides, which are toxic to non-adapted herbivores, are sequestered by monarchs and enhance performance. Interestingly, N,S-ring-containing cardenolides did not have the same effects and were poorly sequestered, with minimal recovery in frass, suggesting an alternate detoxification or metabolic strategy. These N,S-containing compounds are also known to be less potent defences against non-adapted herbivores. The authors further report that mixtures of cardenolides reduce herbivore performance and sequestration compared to single compounds, highlighting the important role of phytochemical diversity in shaping plant-herbivore interactions.

Overall, this study is clearly written, well-conducted and has the potential to make a valuable contribution to the field. However, I have one major concern regarding the interpretations of the mixture results. From what I understand of the methods, all tested mixtures contain all five compounds. As such, it is not possible to determine whether reduced performance and sequestration result from the complete mixture or from the presence of a single compound, such as voruscharin for performance and uscharin for sequestration. For instance, if all compounds except voruscharin (or uscharin) were combined, would the same pattern emerge? I suspect not, since the effects of the individual N,S-containing compounds alone are generally similar to those of the full mixture (Figure S3). By taking the average of all single compounds, the individual effects of the N,S-containing ones are being inflated by the non-N,S-containing ones (in the main text, Figure 4). In the mix, of course, they are not being 'diluted', as they are always present. This interpretation is further supported by the fact that in the equimolar mix, the relative proportion of voruscharin decreases (from 50% in the 'real mix'), and the target measurements of performance and sequestration tend to increase in the equimolar mix compared to the real mix.

Despite this issue, the discussion of mixtures in the context of plant defence against both adapted and non-adapted herbivores is fascinating and convincing. The rationale that mixtures may serve as a chemical tool-kit that targets different sets of herbivores is compelling. The non-N,S cardenolides are effective against non-adapted herbivores and the N,S-containing cardenolides are effective against adapted herbivores. However, the current experiments focus exclusively on an adapted species. It would be especially interesting to test whether such mixtures reduce overall herbivory when both adapted and non-adapted species are present.

It remains possible that mixtures, even in the absence of voruscharin or uscharin, genuinely reduce sequestration or performance; however, this would need to be tested directly to address the abovementioned concern.

Thanks for these insightful reviews and your summary assessment. We certainly agree that ours was a laboratory study with a single specialized insect, and both mixtures types had all five compounds (controlling for total toxin concentration). Thus, our conclusion that combined effects of naturally occurring toxins (within the cardenolide class) have non-additive effects for the specialized sequestering monarch are constrained by our experimental conditions. In our assay we used two mixture types, equimolar and “natural” proportions. We acknowledge that the natural proportions will vary with plant age, damage history, etc. of the host plant, Asclepias curassavica. Our proportions were based on growing the plants a few different times under variable conditions. Although we did not conduct these experiments on non-adapted insects, we discuss a related experiment that was conducted with wild-type and genetically engineered Drosophila (Lopez-Goldar et al. 2024, PNAS). In sum, we appreciate the reviewers’ comments.

Recommendations for the authors:

Reviewing Editor Comments:

(i) More convincingly justify the choice and ecological relevance of the "natural" cardenolide ratios, (ii) Clarify the interpretation of mixture effects, and (iii) more explicitly discuss the limitations of leaf-disc assays and the absence of non-adapted herbivores in light of the broader coevolutionary claims.

Thank you for these suggestions. We have added several sentences of text to the Discussion section to make these points.

Reviewer #1 (Recommendations for the authors):

(1) Statistical analysis is missing from Figure 3 and Figure S3, making it difficult to assess the significance of the data.

Much of the data in Fig. 3 is meant for descriptive presentation, with the main statistical analysis (contrast between N,S and non-N,S cardenolides given in the main text of the results. We have added treatment differences between the sequestration efficiencies to the figure as well.

(2) To help readers intuitively understand how certain results (such as ECD and sequestration efficiency) were calculated, the authors can provide the equations used for these computations.

Thank you, this was given in the methods and we have added it to the Result on first mention as well.

(3) For Figure 4, we suggest presenting the results of the equal mixture treatment and the realistic mixture treatment separately, rather than averaging the results from these two types of treatments.

We understand and appreciate this comment – all of the treatment means are given in Fig. S3. For this particular figure we have opted to stick with the binary comparison (singles vs. mixed) to maximize replication for statistical tests (typically n = 25 vs. 10).

Reviewer #2 (Recommendations for the authors):

Given the interpretations and discussion generally, I feel the manuscript would benefit from either additional experiments (mixtures w/o N-S compounds), inclusion of non-adapted herbivore performance, or reframing of the explicit interpretations from your findings.

We have added some caveats to the text but not added any additional experiments.

Also, for all treatments/mixtures are concentrations above the IC50? Perhaps this could be calculated from the information presented, but it may be best to explicitly mention this.

This is an interesting question. IC50’s are estimated from in vitro assays (with the enzyme and toxins in microplate wells) and so are not translatable to foliar concentrations. As indicated in the text, we chose cardenolide levels based on foliar concentrations to match A. curassavica.

Some minor points:

(1) Although the intact N,S-ring-containing compounds are recovered in low amounts in frass (and not sequestered), is there evidence of N,S-ring components being otherwise traceable in the frass? For example, can excess S or N be detected in frass? This could provide insight into differential detoxification or reincorporation of these elements, potentially explaining variation between voruscharin and uscharin.

Great question! We have not been able to detect breakdown projects. In other experiments we have conducted mass spectrometric analysis of bodies and frass, but have not been able to find the features representing breakdown products. Nonetheless, as mentioned below, the main conversion products are evident and measurable, as in this study.

(2) As a point of curiosity, is there evidence of interconversion between such compounds? For instance, if monarchs are fed only voruscharin, can other cardenolides be detected in their tissues?

Yes, we have tried to make this more clear in the text. Both uscharin and voruscharin are converted to calotropin and calactin.

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

Learn more at Review Commons

Reply to the reviewers

1. General Statements [optional]

*We thank the reviewers for their insightful and constructive comments, which have substantially strengthened the manuscript. We have addressed all concerns and replaced the previous non-quantitative RNA-seq analysis with a new analysis that allowed for quantitative assessment. We were encouraged to find that the revised analysis not only confirmed our original observations but also reinforced and extended our conclusions. *

2. Point-by-point description of the revisions

Reviewer #1

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Significance

Comment 1: At its current stage, this work represents a robust resource for molecular parasitology research programs, paving the way for mechanistic studies on multilayered gene expression control and it would benefit from experimental evidence for some of the claims concerning the in silico regulatory networks. Terms like "regulons", "recursive feedback loop" are employed without solid confirmation or extensive literature support. In my view, the most relevant contribution of this study is centered in the direct association between proteasome-dependent degradation and Leishmania differentiation.

__Response: __We thank the reviewer to acknowledge the impact of our work as a robust resource for further mechanistic studies. We agree that the new concepts emerging from our multilayered analysis should be experimentally assessed. However, given the scope of our analysis (i.e. a complete systems-level analysis of bona fide, hamster-isolated L. donovani amastigotes and derived promastigotes) and the amount of data presented in the current manuscript, such functional genetic analysis will merit an independent, in-depth investigation. The current version has been very much toned down and modified to emphasize the impact of our work as a powerful new resource for downstream functional analyses.

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Evidence, reproducibility and clarity

Comment 1: The narrative becomes somewhat diffuse with the shift to putative multilevel regulatory networks, which would benefit from further experimental validation.

Response: We agree with the reviewer and toned down the general discussion while suggesting putative multilevel regulatory networks for follow-up, mechanistic analyses. We now emphasize those networks for which evidence in trypanosomatids and other organisms has been published. Experimental validation of some of these regulatory networks is outside the scope of our manuscript and will be pursued as part of independent investigations.

Major issues

Comment 1: Fig.1D suggests a significant portion of the SNPs are exclusive, with a frequency of zero in one of the two stages. Were only the heterozygous and minor alleles plotted in Fig.1D, since frequencies close to 1 are barely observed? Is the same true in Sup Fig. S2B? Why do chrs 4 and 33 show unusual patterns in S2B?

__Response: __We thank the reviewer for this observation. The SNPs exclusive to either one or the other stage are likely the result of the 10% cutoff we use for this kind of analysis (eliminating SNPs that lack sufficient support, i.e. less than 10 reads). Due to bottle neck events (such as in vitro culture or stage differentiation), many low frequency SNPs are either 'lost' (filtered out) or 'gained' (passing the 10% cutoff) between the ama and pro samples. All SNPs above 10% were plotted. The absence of SNPs at 100% is one of the hallmarks of the Ld1S L. donovani strain we are using. Instead, these parasites show a majority of SNPs at a frequency of around 50%, which is likely a sign of a previous hybridization event. Chr 4 and chr 33 show a very low SNP density, most likely as they went through a transient monosomy at one moment of their evolutionary history, causing loss of heterozygosity. We now explain these facts in the figure legend.

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Comment 2: Chr26 revealed a striking contrasting gene coverage between H-1 and the other two samples. While a peak is observed for H-1 in the middle of this chr, the other two show a decrease in coverage. Is there any correlation with the transcriptomic/proteomic findings?

Response: This analysis is based on normalized median read depth, taking somy variations into account. This is now more clearly specified in the figure legend. We do not see any significant expression changes that would correlate with the observed (minor) read depth changes. As indicated in the legend, we do not consider such small fluctuations (less than +/- 1,5 fold) as significant. The reversal of the signal for chr 26 sample H1 eludes us (but again, these fluctuations are minor and not observed at mRNA level).

Comment 3: The term "regulon" is used somewhat loosely in many parts of the text. Evidence of co-transcriptomic patterns alone does not necessarily demonstrate control by a common regulator (e.g., RNA-binding protein), and therefore does not fulfill the strict definition of a regulon. It should be clear whether the authors are highlighting potential multiple inferred regulons within a list of genes or not. Maybe functional/ gene module/cluster would be more appropriate terms.

Response: We thank the reviewer for this important comment. We replaced 'regulon' throughout the manuscript by 'co-regulated, functional gene clusters' (or similar).

Comment 4: It is unclear whether the findings in Fig.3E are based on previous analysis of stage-specific rRNA modifications or inferred from the pre-snoRNA transcriptomic data in the current work or something else. I struggle to find the significance of presenting this here.

__Response: __We thank the reviewer for this comment. Yes, these data show stage-specific rRNA modifications based on previous analyses that mapped stage-specific differences of pseudouridine (Y) (Rajan et al., Cell Reports 2023, DOI: 10.1016/j.celrep.2024.114203) and 2'-O-modifications (Rajan et al., Nature Com, in revision) by various RNA-seq analyses and cryoEM. This figure has been modified in the revised version to consider the identification of stage-regulated snoRNAs in our new and statistically robust RNA-seq analysis. These data are shown to further support the existence of stage-regulated ribosomes that may control mRNA translatability, as suggested by the enriched GO terms 'ribosome biogenesis', 'rRNA processing' and 'RNA methylation' shown in Figure 2. We better integrated these analyses by moving the panels from Figure 3 to Figure 2.

Comment 5: The protein turnover analysis is missing the critical confirmation of the expected lactacystin activity on the proteasome in both ama and pro. A straightforward experiment would be an anti-polyUb western blotting using a low concentration SDS-PAGE or a proteasome activity assay on total extracts.

Response: We thank the reviewer for this comment and have now included an anti-polyUb Western blot analysis (see Fig S7).

Comment 6: The viability tests upon lactacystin treatment need a positive control for the PI and the YoPro staining (i.e., permeabilized or heat-killed promastigotes).

Response: This control is now included in Fig S7 and we have added the corresponding description to the text.

Comment 7: I found that the section on regulatory networks was somewhat speculative and less focused. Several of the associated conclusions are, in some parts, overstated, such as in "uncovered a similar recursive feedback loop" (line 566) or "unprecedented insight into the regulatory landscape" (line 643). It would be important to provide some form of direct evidence supporting a functional connection between phosphorylation/ubiquitination, ribosome biogenesis/proteins and gene expression regulation.

Response: We agree with the reviewer and have considerably toned down our statements. Functional analyses to investigate and validate some of the shown network interactions are planned for the near future and will be published separately.

Minor issues

1) The ordinal transition words "First,"/"Second," are used too frequently in explanatory sections. I noted six instances. I suggest replacing or rephrasing some to improve flow.

Response: Rectified, thanks for pointing this out.

2) Ln 168: Unformatted citations were given for the Python packages used in the study.

Response: Rectified, thanks for pointing this out.

3) Fig.1D: "SNP frequency" is the preferred term in English.

Response: Corrected.

4) Fig.2A: not sure what "counts}1" mean.

__Response: __This figure has been replaced.

5) Ln 685: "Transcripts with FC 0.01 are represented by black dots" -> This sentence is inaccurate. The intended wording might be: "Transcripts with FC 0.01 are represented by black dots"

Response: We thank the reviewer and corrected accordingly.

6) Ln 698: Same as ln 685 mentioned above.

Response: We thank the reviewer and corrected accordingly.

7) Fig.2B and elsewhere: The legend key for the GO term enrichment is a bit confusing. It seems like the color scales represent the adj. p-values, but the legend keys read "Cluster efficiency" and "Enrichment score", while those values are actually represented by each bar length. Does light blue correspond to a max value of 0.05 in one scale, and dark blue to a max value of 10-7 in the other scale?

Response: This was corrected in the figure and the legends were updated accordingly.

8) Sup Figure S3A and S4A: The hierarchical clustering dendrograms are barely visible in the heatmaps.

Response: Thanks for the comment. Figure S3 was removed and replaced by a hierarchical clustering and a PCA plot.

9) S3A Legend: The following sentence sounds a bit awkward: "Rows and columns have been re-ordered thanks to a hierarchical clustering". I suggest switching "thanks to a hierarchical clustering" to "based on hierarchical clustering".

Response: This figure was removed and the legend modified.

10) Fig.5D: The font size everywhere except the legend key is too small. In addition, on the left panel, gene product names are given as a column, while on the right, the names are shown below the GeneIDs. Consistency would make it clearer.

Response: Thank you, this is now rectified. To ensue readability, we reduced the number of shown protein kinase examples.

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Reviewer #2

Evidence, reproducibility and clarity

Comment 1: In the absence of riboprofiling the authors return to the RNA-seq to assess the levels of pre-Sno RNA (the role of the could be more explicitly stated).

Response: We thank the reviewer for this comment. We moved the snoRNA analysis from Fig 3 to Fig 2 (see also the similar comment of reviewer 1), which better integrates and justifies this analysis. Based on the new and statistically robust RNA-seq analysis, the volcano plot showing differential snoRNA expression and possible ribosome modification has been adjusted (Figures 2C and D).

__Comment 2: __The authors provide a clear and comprehensive description of the data at each stage of the results and this in woven together in the discussion allowing hypotheses to be formed on the potential regulatory and signalling pathways that control the differentiation of amastigotes to promastigotes. Given the amount and breadth of data presented the authors are able to present a high-level assessment of the processes that form feedback loops and/or intersectional signalling, but specific examples are not picked out for deeper validation or exploration.

__Response: __We thank the reviewer to acknowledge the amount and breadth of data presented. As indicated above (see responses to reviewer 1), mechanistic studies will be conducted in the near future to validate some of the regulatory interactions. These will be subject of separate publications. As noted above (response to reviewer 1), we toned down the general discussion, suggest follow-up mechanistic analyses and emphasize those networks for which evidence in trypanosomatids and other organisms has been published.

__ __ Major comments:

Are the claims and the conclusions supported by the data or do they require additional experiments or analyses to support them?

Comment 1: As I have understood it from the description in the text, and in Data Table 4, the RNA-seq element of the work has only been conducted using two replicates. If this is the case, it would substantially undermine the RNA-seq and the inferences drawn from it. Minimum replicates required for inferential analysis is 3 bio-replicates and potentially up to 6 or 12. It may be necessary for the authors to repeat this for the RNA-seq to carry enough weight to support their arguments. (PMID: 27022035)

Response: We agree with the reviewer and conducted a new RNA-seq analysis with 4 independent biological replicates of spleen-purified amastigotes and derived promastigotes. Given the robustness of the stage-specific transcriptome, and the legal constrains associated with the use of animals, we chose to limit the number of replicates to the necessary. We thank the reviewer for this important comment, and the new data not only confirm the previous one (providing a high level of robustness to our data) but allowed us to increase the number of identified stage-regulated snoRNAs, thus further supporting a possible role of ribosome modification in Leishmania stage development.

Comment 2: There are several examples that are given as reciprocal or recursive signalling pathways, but these are not followed up with independent, orthogonal techniques. I think the paper currently forms a great resource to pursue these interesting signalling interactions and is certainly more than just a catalogue of modifications, but to take it to the next level ideally a novel signalling interaction would be demonstrated using an orthogonal approach. Perhaps the regulation of the ribosomes could have been explored further (same teams recently published related work on this). Or perhaps more interestingly, a novel target(s) from the ubiquitinated protein kinases could have been explored further; for example making precision mutants that lack the ubiquitination or phosphorylation sites - does this abrogate differentiation?

Response: We agree with the reviewer that the paper currently forms a great resource. In-depth molecular analysis investigating key signaling pathways and regulatory interactions are outside the scope of the current multilevel systems analysis but will be pursued in independent investigations.

Comment 3: I found the use of lactacystin a bit curious as there are more potent and specific inhibitors of Leishmania proteasomes e.g. LXE-408. This could be clarified in the write-up (See below).

__Response: __We thank the reviewer for this comment. We opted for the highly specific and irreversible proteasome inhibitor lactacystin that has been previously applied to study the Leishmania proteasome (PMID: 15234661) rather than the typanosomatid-specific drug candidate LXE408 as the strong cytotoxic effect of the latter makes it difficult to distinguish between direct effects on protein turnover and secondary effects resulting from cell death, limiting its utility for dissecting proteasome function in living parasites. We have added this information in the Results section.

Comment 4: If it is the case that only 2 replicates of the RNA-Seq have been performed it really is not the accepted level of replication for the field. Most studies use a minimum of 3 bioreplicates and even a minimum of 6 is recommended by independent assessment of DESeq2.

__Response: __See response to comment 1 above.

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Comment 5: As far as I could see, the cell viability assay does not include a positive control that shows it is capable of detecting cytotoxic effects of inhibitors. Add treatment showing that it can differentiate cytostatic vs cytotoxic compound.

__Response: __This control has now been added to Fig S7.

If you have constructive further reaching suggestions that could significantly improve the study but would open new lines of investigations, please label them as "OPTIONAL". Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated time investment for substantial experiments.

Comment 6: It is realistic for the authors to validate the cell viability assay. If the RNA-seq needs to be repeated then this would be a substantial involvement.

Response: Redoing the RNA-seq analysis was entirely feasible and very much improved the robustness of our results.

Are the data and the methods presented in such a way that they can be reproduced?

Comment 7: All the methods are written to a good level of detail. The sample prep, acquisition and data analysis of the protein mass spectrometry contained a high level of detail in a supplemental section. The authors should be more explicit about the amount of replication at each stage, as in parts of the manuscript this was quite unclear.

Response: We thank the reviewer for this comment and explicitly state the number of replicates in Methods, Results and Figure legends for all analyses. The number of replicates for each analysis is further shown in the overview Figure S1.

Are the experiments adequately replicated and statistical analysis adequate?

Comment 8: Unless I have misunderstood the manuscript, I believe the RNA-seq dataset is underpowered according to the number of replicates the authors report in the text.

Response: See response to comment 1 above.

Comment 9: Looking at Figure 1 and S1 and Data Table 4 to show the sample workflow I was surprised to see that the RNA-seq only used 2 replicates. The authors do show concordance between the individual biological replicates, but I would consider that only having 2 is problematic here, especially given the importance placed on the mRNA levels and linkage in this study. This would constitute a major weakness of the study, given that it is the basis for a crucial comparison between the RNA and protein levels.

Response: We agree and have repeated the RNAseq analysis using four independent biological replicates - see response to comment 1.

Comment 10: It also wasn't clear to me how many replicates were performed at each condition for the lactacystin treatment experiment - can the authors please state this clearly in the text, it looks like 4 replicates from Figure S1 and Data Table 8.

Response: Indeed, we did 4 replicates. This is now clarified in Methods, Results and Figure legends and shown in Figure S1.

Comment 11: Four replicates are used for the phosphoproteomics data set, which is probably ok, but other researchers have used a minimum of 5 in phosphoproteomics experiments to deal with the high level of variability that can often be observed with low abundance proteins & modifications. The method for the phosphoproteomics analysis suggests that a detection of a phosphosite in 1 sample (also with a localisation probability of >0.75) was required for then using missing value imputation of other samples. This seems like a low threshold for inclusion of that phosphosite for further relative quantitative analysis. For example, Geoghegan et al (2022) (PMID: 36437406) used a much more stringent threshold of greater than or equal to 2 missing values from 5 replicates as an exclusion criteria for detected phoshopeptides. Please correct me if I misunderstood the data processing, but as it stands the imputation of so many missing values (potentially 3 of 4 per sample category) could be reducing the quality of this analysis.

Response: We thank the reviewer for this remark and for highlighting best practices in phosphoproteomics data analysis. Unlike other studies that use cultured parasites and thus have access to unlimited amounts, our study employs bona fide amastigotes isolated from infected hamster spleens. In France, the use of animals is tightly controlled and only the minimal number of animals to obtain statistically significant results is tolerated (and necessary to obtain permission to conduct animal experiments).

Regarding the number of biological replicates, we would like to emphasize that the use of four biological replicates is fully acceptable and used in quantitative proteomics and phosphoproteomics, particularly when combined with high-quality LC-MS/MS data and stringent peptide-level filtering. While some studies indeed employ five or more replicates, this is not a strict requirement, and many high-impact phosphoproteomics studies have successfully relied on four replicates when experimental quality and depth are high. In the present study, we adopted a discovery-oriented approach, aimed at detecting as many confidently identified phosphopeptides as possible. The consistency between replicates, combined with the depth of coverage and signal quality, indicates that four replicates are adequate for both the global proteome and the phosphoproteome in this context. Importantly, the quality of the MS data in this study is supported by (i) a high number of confidently identified peptides and phosphopeptides (identification FDR0.75), and (iii) reproducible quantitative profiles across replicates. Notably, most of the identified phosphopeptides are quantified in at least two replicates within a given condition (between 73.2% and 83.4% of all the identified phosphopeptides among replicates of the same condition).

Regarding missing value imputation, we appreciate that our initial description may have been unclear and we have revised the Methods to avoid misunderstanding. Phosphosites were only considered if detected with high confidence (identification FDR0.75) in at least one replicate. This criterion was chosen to retain biologically relevant, low-abundance phosphosites, which are more difficult to identify and are often stochastically sampled in phosphoproteomics datasets. For statistical analyses, missing values within a given condition were imputed with a well-established algorithm (MLE) only when at least one observed value was present in that condition. Notably, they were replaced by values in the neighborhood of the observed intensities, rather than by globally low, noise-like values.

We agree that more stringent exclusion rules, such as those used by Geoghegan et al. (2022), are appropriate in some contexts. However, there is no universally accepted standard for missingness thresholds in phosphoproteomics, and different strategies reflect trade-offs between sensitivity and stringency. In our discovery-oriented approach, we deliberately prioritized biological coverage while maintaining data quality. Our main conclusions are supported by coherent biological patterns, rather than by isolated phosphosite measurements.

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Comment 12: For the metabolomics analysis it looks like 2 amastigote samples were compared against 4 promastigote samples. Why not triplicates of each?

Response: We thank the reviewer for noticing this point. It is an error in the figure file (Sup figure S1). Four biological replicates of splenic amastigotes were prepared (H130-1, H130-2, H133-1 and H133-2). Amastigotes from 2 biological replicates (H131-1 and H131-2) were seeded for differentiation into promastigotes in 4 flasks (2 per biological replicate) that were collected at passage 2. We have updated the figure file accordingly.

Minor comments:

__ __Specific experimental issues that are easily addressable. Are prior studies referenced appropriately?

* *Comment 1: Yes

Are the text and figures clear and accurate?

* *Comment 2: The write up is clear, with the data presented coherently for each method. The analyses that link everything together are well discussed. The figures are mostly clear (see below) and are well described in the legends. There is good use of graphics to explain the experimental designs and sample names - although it is unclear if technical replicates are defined in these figures.

Response: We thank the reviewer for these positive comments. We now included the information on replicates in the overview figure (Figure S1).

Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Comment 3: As I have understood it, the authors have calculated the "phosphostoichiometry" using the ratio of change in the phosphopeptide to the ratio of the change in total protein level changes. This is detailed in the supplemental method (see below). Whilst this has normalised the data, it has not resulted in an occupancy or stoichiometry measurement, which are measured between 0-1 (0% to 100%). The normalisation has probably been sufficient and useful for this analysis, but this section needs to be re-worded to be more precise about what the authors are doing and presenting. These concepts are nicely reviewed by Muneer, Chen & Chen 2025 (PMID: 39696887) who reference seminal papers on determination of phosphopeptide occupancy - and may be a good place to start. An alternative phrase should be used to describe the ratio of ratios calculated here, not phosphostoichiometry.

Response: We thank the reviewer for this insightful comment and fully agree with the conceptual distinction raised. The reviewer is correct that the approach used in this study does not measure absolute phosphosite occupancy or stoichiometry, which would indeed require dedicated experimental strategies and would yield values bounded between 0 and 1 (0-100%). Instead, we calculated a normalized phosphorylation change, defined as the ratio of the change in phosphopeptide abundance relative to the change in the corresponding total protein abundance (a ratio-of-ratios approach - see doi :10.1007/978-1-0716-1967-4_12), and we tested whether this normalized phosphorylation change differed significantly from zero. This normalization approach is comparable to those previously published in the « Experimental Design and Statistical Analysis of the Proteome and the Phosphoproteome » section of the following paper (DOI: 10.1016/j.mcpro.2022.100428).

Our intention was to account for protein-level regulation and thereby better isolate changes in phosphorylation dynamics. While this normalization is informative and appropriate for the biological questions addressed here, we agree that the term "phosphostoichiometry" is imprecise and not correct in this context.

In response, we (i) replaced the term "phosphostoichiometry" throughout the manuscript with a more accurate description, such as "normalized phosphorylation level", or "relative phosphorylation change normalized to protein abundance", and (ii) revised the corresponding Methods and Results text to clearly state that absolute occupancy was not measured.

This rewording will improve conceptual accuracy without altering the validity or interpretation of the results.

Comment 4: From the authors methods describing the ratio comparison approach: "Another statistical test was performed in a second step: a contrasted t-test was performed to compare the variation in abundance of each modified peptide to the one of its parent unmodified protein using the limma R package {Ritchie, 2015; Smyth, 2005}. This second test allows determining whether the fold-change of a phosphorylated peptide between two conditions is significantly different from the one of its parent and unmodified protein (paragraph 3.9 in Giai Gianetto et al 2023). An adaptive Benjamini-Hochberg procedure was applied on the resulting p-values thanks to the adjust.p function of R package cp4p {Giai Gianetto, 2016} using the Pounds et al {Pounds, 2006} method to control the False Discovery Rate level."

Response: The references have been formatted.

Comment 5: Several aspects of the figures that contain STRING networks are quite useful, particularly the way colour around the circle of each node to denote different molecular functions/biological processes. However, some have descended into "hairball" plots that convey little useful information that would be equally conveyed in a table, for example. Added to this, the points on the figure are identified by gene IDs which, while clear and incontrovertible, are lacking human readability. I suggest that protein name could be included here too.

Response: We thank the reviewer for this comment but for readability we opted to keep the figure as is. We now refer to Tables 8, 9, and 12 that allow the reader to link gene IDs to protein name and annotation (if available).

Comment 6: It is also not clear what STRING data is being plotted here, what are the edges indicating - physical interactions proven in Leishmania, or inferred interactions mapped on from other organisms? Perhaps as supplemental data provide the Cytoscape network files so readers can explore the networks themselves?

Response: We thank the reviewer for this comment. While the STRING plugin in Cytoscape enables integrated network-based analyses, it represents protein-protein associations as a single edge per protein pair derived from the combined confidence score. Consequently, the specific contribution of individual evidence channels (e.g. experimental evidence, curated databases, co-expression, or text mining) cannot be disentangled within this framework. However, this representation was considered appropriate for the present study, which focused on global network topology and functional enrichment rather than on the interpretation of individual interaction types. The information on stringency has been added to the Methods section and the Figure legends (adding the information on confidence score cutoff).

We decided not to submit the Cytoscape files as they were generated with previous versions of Cytoscape and the STRING plugin. Based on the differential abundance data shown in the tables it will be very easy to recreate these networks with the new versions for any follow up study.

Comment 7: The title of columns in table S10 panel A are written in French, which will be ok for many people particularly those familiar with proteomics software outputs, but everything else is in English so perhaps those titles could be made consistent.

__Response: __We apologize and have translated the text in English.

Comment 8: I would suggest that the authors provide a table that has all the gene IDs of the Ld1S2D strain and the orthologs for at least one other species that is in TriTrypDB. This would make it easy to interrogate the data and make it a more useful resource for the community who work on different strains and species of Leishmania. Although this data is available it is a supplemental material file in a previous paper (Bussotti et al PNAS 2021) and not easy to find.

Response: We thank the reviewer for this very useful suggestion and have added this table (Table S13).

Comment 9: Figure 5b - from the legend it is not clear where the confidence values were derived in this analysis, although this is explained in the supplemental method. Perhaps the legend can be a bit clearer.

Response: We have the following statement to the legend: 'Confidence values were derived as described in Supplementary Methods'.

Comment 10: Can the authors discuss why lactacystin was used? While this is a commonly used proteasome inhibitor in mammalian cells there is concern that it can inhibit other proteases. At the concentrations (10 µM) the authors used there are off-target effects in Leishmania, certainly the inhibition of a carboxypeptidase (PMID: 35910377) and potentially cathepsins as is observed in other systems (PMID: 9175783). There is a specific inhibitor of the Leishmania proteasome LXE-408 (PMID: 32667203), which comes closer to fulfilling the SGC criteria (PMID: 26196764) for a chemical probe - why not use this. Does lactacystin inhibit a different aspect of proteasome activity compared to LXE-408?

Response: We have add the following justification to the results section (see also response above to comment 3 for reviewer 2): We chose the highly specific and irreversible proteasome inhibitor lactacystin over the typanosomatid-specific, reversible drug candidate LXE408 as the latter's potent cytotoxicity can confound direct effects on protein turnover with secondary consequences of cell death, limiting its utility for dissecting proteasome function in living parasites.

Comment 11: The application of lactacystin is changing the abundance of a multitude of proteins but no precision follow up is done to identify if those proteins are necessary and/or sufficient from driving/blocking differentiation. This could be tested using precision edited lines that are unable to be ubiquitinated? There is a lack of direct evidence that the proteins protected from degradation by lactacystin are ubiquitinated? Perhaps some of these could be tagged and IP'd then probed for ubiquitin signal. Di-Gly proteomics to reveal ubiquitinated proteins? These suggestions should be considered as OPTIONAL experiments in the relevant section above.

Response: We very much appreciate these very interesting suggestions, which we will be considered for ongoing follow-up studies.

Comment 12: In the data availability RNA-seq section the text for the GEO link is : (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc= GSE227637) but the embedded link takes me to (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE165615) which is data for another, different study. Also, the link to the GEO site for the DNA seq isn't working and manual searches with the archive number (BioProject PRJNA1231373 ) does not appear to find anything. The IDs for the mass spec data PRIDE/ProteomeXchange don't seem to bring up available datasets: PXD035697 and PXD035698

Response: The links have now been rectified and validated. For those data that are still under quarantine, here is the login information: To access the data:

DNAseq data: https://dataview.ncbi.nlm.nih.gov/object/PRJNA1231373?reviewer=6qt24dd7f475838rbqfn228d0

RNAseq data:

https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-MTAB-16528?key=65367b55-d77f-4c06-b4bd-bc10f2dc0b14

Proteomic data: http://www.ebi.ac.uk/pride

__Username: __reviewer_pxd035698@ebi.ac.uk

__Password: __gOIcRx0g

Phosphoproteomic data: http://www.ebi.ac.uk/pride

__Username: __reviewer_pxd035697@ebi.ac.uk

__Password: __7GWtBmvx

Significance Provide contextual information to readers (editors and researchers) about the novelty of the study, its value for the field and the communities that might be interested. The following aspects are important:

* General assessment: provide a summary of the strengths and limitations of the study. What are the strongest and most important aspects? What aspects of the study should be improved or could be developed?*

Strengths: Comment 1: The molecular pathways that regulate Leishmania life-stage transitions are still poorly understood, with many approaches exploring single proteins/RNAs etc in a reductionist manner. This paper takes a systems-scale approach and does a good job of integrating the disparate -omics datasets to generate hypotheses of the intersections of regulatory proteins that are associated with life-cycle progression.

Response: We thank the reviewer for this positive assessment of our work.

Comment 2: The differentiation step studied is from amastigote to promastigote. I am not aware that this has been studied before using phosphoproteomics. The use of the hamster derived amastigotes is a major strength. While a difficult/less common model, the use of hamsters permits the extraction of parasites that are host adapted and represent "normal", host-adapted Leishmania ploidy, the promastigote experiments are performed at a low passage number. This is a strength or the work as it reduces the interference of the biological plasticity of Leishmania when it is cultured outside the host.

Response: We thank the reviewer for the acknowledgment of our relevant hamster system, for which we face many challenges (financial, ethical, administrative as protocols need to be approved by the French government).

Limitations: __ __Comment 1: Potential lack of appropriate replication (see above).

Response: See response to comment 1.

Comment 2: Lack of follow up/validation of a novel signalling interaction identified from the systems-wide approach. There is a lack of assessment of whether a single signalling cascade is driving the differentiation or these are all parallel, requisite pathways. The authors state the differentiation is not driven by a single master regulator, but I am not sure there is adequate evidence to rule this in or out.

Response: See response to comment 2 above.

Advance: compare the study to the closest related results in the literature or highlight results reported for the first time to your knowledge; does the study extend the knowledge in the field and in which way? Describe the nature of the advance and the resulting insights (for example: conceptual, technical, clinical, mechanistic, functional,...).

Comment 3: The study applies well established techniques without any particular technical step-change. The application of large-scale multi-omics techniques and integrated comparisons of the different experimental workflows allow a synthesis of data that is a step forward from that existing in the previous Leishmania literature. It allows the generation of new hypotheses about specific regulatory pathways and crosstalk that potentially drive, or are at least active, during amastigote>promastigote differentiation.

Response: We thank the reviewer for these positive comments.

*Audience: describe the type of audience ("specialized", "broad", "basic research", "translational/clinical", etc...) that will be interested or influenced by this research; how will this research be used by others; will it be of interest beyond the specific field? * This manuscript will have primary interest to those researchers studying the molecular and cell biology of Leishmania and other kinetoplastid parasites. The approaches used are quite standard (so not so interesting in terms of methods development etc.) and given the specific quirks of Leishmania biology it may not be that relevant to those working more broadly in parasites from different clades/phyla, or those working on opisthokont systems- yeast, humans etc. Other Leishmania focused groups will surely cherry-pick interesting hits from this dataset to advance their studies, so this dataset will form a valuable reference point for hypothesis generation.

Response: We thank the reviewer for this assessment and agree that our data sets will be very valuable for us and other teams to generate hypotheses for follow-up studies.

Please define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

Relevant expertise: Trypanosoma & Leishmania molecular & cell biology, RNA-seq, proteomics, transcriptional/epigenetic regulation, protein kinases - some experience of UPS system.

I have not provided comment on the metabolomics as it is outside my core expertise. However, I can see it was performed at one of the leading parasitology metabolomics labs.

Response: We thank the reviewer for sharing expertise, investing time and intelligence in the assessment of our manuscript, and the highly constructive criticisms provided.

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

__Summary: __The study presents a comprehensive multi-omics investigation of Leishmania differentiation, combining genomic, transcriptomic, proteomic, phospho-proteomic and metabolomic data. The authors aim to uncover mechanisms of post-transcriptional and post-translational regulation that drive the stage-specific biology of L. donovani. The authors provide a detailed characterization of transcriptomic, proteomic, and phospho-proteomic changes between life stages, and dissect the relative contributions of mRNA abundance and protein degradation to stage-specific protein expression. Notably, the study is accompanied by comprehensive supplementary materials for each molecular layer and provides public access to both raw and processed data, enhancing transparency and reproducibility. While the data are rich and compelling, several mechanistic interpretations (e.g., "feedback loops," "recursive networks," "signaling cascades") are overstated. Similarly, the classification of gene sets as "regulons" is not adequately supported, as no common regulatory factor has been identified and only a single condition change (amastigote to promastigote) was assessed.

__Response: __We thank the reviewer for these comments and have corrected the manuscript to eliminate all unjustified mechanistic interpretations.

Major Comments:

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Comment 1:__ Across several sections (incl abstract, L559-565, L589-599, L600-L603, L610-612, L613-614, L625, L643-645, L650-652), the manuscript describes "recursive or self-controlling networks", "signaling cascades", "self-regulating", and "recursive feedback loops" - involving protein kinases, phosphatases, and translational regulators. While the data convincingly demonstrate stage-specific changes in phosphorylation and abundance changes in key molecules, the language used implies causal, direct and directional regulatory relationships that have not been experimentally validated.

Response: __We agree with the reviewer and have corrected the text, replacing all expressions that may allude to causal or directional relationships by more neutral expressions such as 'co-expression'. __

Comment 2: Co-expression and shared function alone do not define a regulon (L363, and several other places in the manuscript). A regulon also requires the gene set to be regulated by the same factor, for which there is no evidence here. Regulons can be derived from transcriptomic experiments, but then they need to show the same transcriptional behavior across many biological conditions, while here just 1 condition change is evaluated. Therefore, this analysis is conventional GO enrichment analysis and should not be overinterpreted into regulons.

__Response: __We agree with the reviewer and have replaced 'regulon' with 'co-regulated gene clusters' (or similar).

Comment 3: LFQ intensity of 0 (e.g., L389): An LFQ intensity of 0 does not necessarily indicate that a protein is absent, but rather that it was not detected. This can occur for several reasons: (1) true biological absence in one condition, (2) low abundance below the detection threshold, or (3) stochastic missingness due to random dropout in mass spectrometry. While the authors state that adjusted p-values for the 1534 proteins exclusively detected in either amastigotes or promastigotes are below 0.01, I could not find corresponding p-values for these proteins in Table 8 ('Global_Proteomic'). An appropriate statistical method designed to handle this type of missingness should be used. In this context, I also find the following statement unclear: "identified over 4000 proteins at each stage in at least 3 out of 4 biological replicates, representing 3521 differentially expressed proteins (adjusted p-value Response: We fully agree with the reviewer, an LFQ intensity of 0 may results from various reasons. We realize that our wording may have been ambiguous. For clarity, we have modified the original text to: 'Label-free quantitative proteomic analysis of 4 replicates of amastigotes and derived promastigotes identified over 4000 proteins, including 1987 differentially expressed proteins (adjusted p-value<br /> Comment 4: L412 - Figure 3B: The figure shows proteins with infinite fold changes, which result from division by zero due to LFQ intensity values of zero in one of the compared conditions. As previously noted, interpreting LFQ zero values as true absence of expression is problematic, since these zeros can arise from several technical reasons - such as proteins being just below the detection threshold or due to stochastic dropout during MS analysis. Therefore, the calculated fold changes for these proteins are likely highly overestimated. This concern is visually supported by the large gap on the y-axis (even in log scale) between these "infinite" fold changes and the rest of the data. Moreover, given Leishmania's model of constitutive gene expression, it seems biologically implausible that all these proteins would be completely absent in one stage. This issue applies not only to Figure 3B, but also to the analyses presented in Figures 4D and 4E.

Response: __We thank the reviewer for this comment. To clarify this section, we modified the text as follows: 'Only expression changes were considered that either showed statistically significant differential abundance at both RNA and protein levels (p <br /> __Minor Comments:

Methods L132: Typo: "A according" should be "according."

__Response: __The 'A' refers to RNase A. We added a comma for clarification (...RNase A, according to...)

L158: How exactly were somy levels calculated? Please specify the method used, as I could not find a clear description in the referenced manuscript.

__Response: __We thank the reviewer for this comment. Aside the already quite detailed description in Methods and the reference there to the paper describing the pipeline, we now added a link to the description of the karyotype module of the giptools package (https://gip.readthedocs.io/en/latest/giptools/karyotype.html). There the following explanation can be found: "The karyotype module aims at comparing the chromosome sequencing coverage distributions of multiple samples. This module is useful when trying to detect chromosome ploidy differences in different isolates. For each sample the module loads the GIP files with the bin sequencing coverage (.covPerBin.gz files) and normalizes the meancoverage values by the median coverage of all bins. The bin scores are then converted to somy scores which are then used for producing plots and statistics." The description then goes into further detail.

L158: Chromosome 36 is not consistently disomic, as stated. It has been observed in other somy states (e.g., Negreira et al. 2023, EMBO Reports, Figure 1), even if such occurrences are rare in the studied context. Normalizing by chr36 remains a reasonable choice, but it would be helpful to confirm that the majority of chromosomes appear disomic post-normalization to support the assumption that chr36 is disomic in this dataset as well.

__Response: __We thank the reviewer for this comment. Unlike the paper cited above (using long-term cultured promastigotes), our analysis uses promastigote parasites from early culture adaptation (p2) that were freshly derived from splenic amastigotes known to be disomic (and confirmed here), which represents an internal control validating our analysis.

L163: Suggestion: Cite the GIP pipeline here rather than delaying the reference until L173.

Response: corrected

L188: "Controlled" may be a miswording. Consider replacing with "confirmed" or "validated."

Response: corrected to 'validated'

L214: Please specify which statistical test was used to assess differential expression at the protein level. L227: Similarly, clarify which statistical test was applied for determining differential expression in the phospho-proteomics data.

Response: As noted in the Methods section, a limma t-test was applied to determine proteins/phosphoproteins with a significant difference in abundance while imposing a minimal fold change of 2 between the conditions to conclude that they are differentially abundant {Ritchie, 2015; Smyth, 2005}.

__Results __ L337-339: The interpretation here is too speculative. Phrases like "suggesting" and "likely" are too strong given the evidence presented. Alternative explanations, such as mosaic variation combined with early-stage selective pressure in the culture environment, should be considered.

Response: We thank the reviewers for these suggestions and have reformulated into: 'In the absence of convergent selection, it is impossible to distinguish if these gene CNVs provide some strain-specific advantage or are merely the result of random genetic drift.'

L340: The "undulating pattern" mentioned is somewhat subjective. To support this interpretation, consider adding a moving average (or similar) line to Figure 3A, which would more clearly highlight this trend across the data points.

Response: These lines have been added to Figure 1C (not 3A).

L356: It may be more accurate to say "control of individual gene expression," since Leishmania does have promoters - the key distinction is that initiation does not occur on a gene-by-gene basis.

Response: corrected

L403-405: The statement "this is because these metabolites comprise a glycosomal succinate shunt..." should be rephrased as a hypothesis rather than a definitive explanation, as this causal link has not been experimentally validated.

Response: Thank you for the comment - we followed your advice.

L407: Replace "confirming" with "matching" to avoid overstating the agreement with previous observations.

Response: corrected

L408: Replace "correlated" with "matched" for more accurate interpretation of results.

Response: corrected

L433: It is unclear how differential RNA modifications were detected. Please specify which biological material was used, the number of replicates per life stage, and how statistical evaluation of differential modifications was performed.

Response: This figure has now been updated using our statistically robust RNA-seq analysis conducted for the revision. See comments above.

L436: This conclusion appears incomplete. While the manuscript mentions transcript-regulated proteins, it should also note that other proteins showed discordant mRNA/protein patterns. A more balanced conclusion would mention both the matching and non-matching subsets.

Response: We thank the reviewer for this comment and have made the necessary adjustments to better balance this conclusion.

L441: The phrase "poor correlation" overgeneralizes and lacks nuance. Earlier sections of the manuscript describe hundreds of genes where mRNA and protein levels correlate well, suggesting that mRNA turnover plays a key regulatory role. Please rephrase this sentence to clarify that poor correlation applies only to a subset of the data.

Response: This has been corrected to 'The discrepancies we observed in a sub-set of genes between....'.

L454: The claim that "epitranscriptomic regulation and stage-adapted ribosomes are key processes" should be supported with references. If this builds on previously published work, please cite it accordingly.

Response: corrected

L457: Proteasomal degradation is a well-established mechanism in Leishmania. These findings are interesting but should be presented in the context of existing literature (e.g. Silva-Jardim et al.2014, [PMID: 15234661]) rather than as entirely novel.

Response: corrected

L459: The authors shoumd add a microscopy image of promastigotes treated with lactacystin. This would provide insight into whether treatment affects morphology, as is known in T. cruzi (see Dias et al., 2008). It would be particularly informative if Leishmania behaves differently.

Response: We added this information to Figure S7.

L472 + L481: Table 9 shows several significant GO terms not discussed in the manuscript. Please clarify how the subset presented in the text was selected.

Response: We added this information to the text ('some of the most significantly enrichment terms included ...').

L482: The argument that a single master regulator can be excluded is unclear. Could the authors please elaborate on the reasoning or data supporting this conclusion?

Response: This statement was too speculative and has been removed. Instead, we added 'Thus, Leishmania differentiation correlates with the expression of complex signaling networks that are established in a stage-specific manner'.

L494: The term "unexpected" may not be appropriate here, as protein degradation is a well-established regulatory mechanism in trypanosomatids. Consider omitting this term to better reflect the field's current understanding.

Response: We deleted the term as suggested and reformulated to '....our results confirm the important role of protein degradation....'.

L543: The term "feedback loop" should be used more cautiously. The current data are correlative, and no interventional experiments are provided to support a causal regulatory loop between proteasomal activity and protein kinases. As such, this remains a hypothesis rather than a confirmed mechanism.

Response: We fully agree and have toned down the entire manuscript, referring to feedback loops only as a hypothesis and not as a fact emerging from our datasets, which set the stage for future functional analyses.

__Discussion __ L555: As noted in L494, reconsider using the word "unexpected."

Response: removed

L589: The data do not fully support the presence of stage-specific ribosomes. Rather, they suggest differential ribosomal function through changes in abundance and regulation. Please consider rephrasing.

Response: We thank the reviewer for this comment and have follow the advice reformulating the sentence according to the suggestion.

L657-658: The discussion of post-transcriptional and post-translational regulation of gene dosage effects would benefit from citing additional literature beyond the authors' own work. E.g. the study by Cuypers et al. (PMID: 36149920) offers a relevant and comprehensive analysis covering 4 'omic layers.

Response: We apologize for this omission and now describe and cite this publication in the Results section when concluding the results shown in Figure 1.

L659-664: The reference to deep learning for biomarker discovery appears speculative and loosely connected to the current findings. As no such methods were applied in the study, and the manuscript does not clarify what types of biomarkers are intended, this statement could be seen as aspirational rather than evidence-based. Consider either omitting or elaborating with clear justification.

Response: We agree and have deleted this section.

L690 + L705 (Figure 2): The phrase "main GO terms" is vague. Please clarify the criteria for selecting the GO terms shown - were they chosen based on adjusted p-value, enrichment score, or another metric? Additionally, define "cluster efficiency," explaining how it was calculated and what it represents.

Response: Corrected to 'some of the most significantly enriched GO terms'.

Signed: Bart Cuypers, PhD

**Referee cross-commenting**

Overall, I think the other reviewers' comments are fair. They seem to align particularly on the following points:

1) Reviewers agree that this is a comprehensive body of work with original contributions to the field of Leishmania/trypanosomatid molecular biology, and that it will serve as a valuable reference for hypothesis generation.

2) Several reviewers raise concerns about overinterpretation of the data, particularly regarding regulatory networks, regulons, and master regulators. The interpretation and large parts of the discussion are considered too speculative without additional functional validation.

3) There are comments about the incorrect statistical treatment of missing values in the proteomics experiments, which affects confidence in some of the conclusions.

4) While the correlation between the two RNA-Seq replicates is high, the decision to include only two biological replicates is seen as unfortunate and not ideal for statistical robustness.

5) The use of lactacystin should be more clearly motivated, and its limitations discussed in the context of the experiments.

Even though I did not remark on the last two points (4 and 5) in my own review, I agree with them.

Response: We thank the reviewer for this cross-comparison, which served us as guide to revise our manuscript. We believe that we have responded to all these concerns.

Reviewer #3 (Significance (Required)):

---

This study provides a rich, integrative multi-omics dataset that advances our understanding of stage-specific adaptation in the transcriptionally unique parasite Leishmania. By dissecting the relative contributions of mRNA abundance and protein turnover to final protein levels across life stages, the authors offer valuable insights into post-transcriptional and post-translational regulation. The work represents a resource-driven yet conceptually informative contribution to the field, with comprehensive supplementary materials and transparent data sharing standing out as additional strengths.

However, the mechanistic insights proposed are speculative in several places and require more cautious language. The study is most impactful as a resource and descriptive atlas, initiating hypotheses for future validation. The broad scientific community working on Leishmania, trypanosomatids, and post-transcriptional regulation in eukaryotes would benefit from this work.

Response: We thank the reviewer for this positive assessment and have modified the manuscript to further emphasize its strength as an important resource to incite mechanistic follow-up studies.

Field of reviewer expertise: multi-omics integration, bioinformatics, molecular parasitology, transcriptomics, proteomics, metabolomics, Leishmania, Trypanosoma.

Reviewer #4 (Evidence, reproducibility and clarity (Required)): __ __Summary:

This study investigates the regulatory mechanisms underlying stage differentiation in Leishmania donovani, a parasitic protist. Pesher et al., aim to address the central question of how these parasites establish and maintain distinct life cycle stages in mostly the absence of transcriptional control. The authors employed a five-layered systems-level analysis comparing hamster-derived amastigotes and their in vitro-derived promastigotes. From those parasites, they performed a genomic, transcriptomic, proteomic, metabolomic and phosphoproteomic analysis to reveal the changes the parasites undertook between the two life stages.

The main conclusion stated by the authors are:

• The stage differentiation in vitro is largely independent of major changes in gene dosage or karyotype.

• RNA-seq analysis identified substantial stage-specific differences in transcript abundance, forming distinct regulons with shared functional annotations. Amastigotes showed enrichment in transcripts related to amastins and ribosome biogenesis, while promastigotes exhibited enrichment in transcripts associated with ciliary cell motility, oxidative phosphorylation, and post-transcriptional regulation itself.

• Quantitative phosphoproteome analysis revealed a significant increase in global protein phosphorylation in promastigotes. Normalizing phosphorylation changes against protein abundance identified numerous stage-specific phosphoproteins and phosphosites, indicating that differential phosphorylation also plays a crucial role in establishing stage-specific biological networks. The study identified recursive feedback loops (where components of a pathway regulate themselves) in post-transcriptional regulation, protein translation (potentially involving stage-specific ribosomes), and protein kinase activity. Reciprocal feedback loops (where components of different pathways cross-regulate each other) were observed between kinases and phosphatases, kinases and the translation machinery, and crucially, between kinases and the proteasomal system, with proteasomal inhibition disrupting promastigote differentiation.

Response: We thank the reviewer for the time and implication dedicated to our manuscript.

Comments:

Further details are organised by order of apparition in the text:

Comment 1: Material and Methods: while the authors are indicating some key parameters, providing the codes and scripts they used throughout the manuscript would improve reproducibility.

Response: We thank the reviewer for this comment and added the URL for the codes to the data availability section.

Comment 2: Why only 2 biological replicates for RNA while the others layers have 3 or 4?

__Response: __We agree with the other reviewers and have repeated this analysis to have statistically more robust results.

Comment 3: Is the slight but reproducible increase in median coverage observed for chr 1, 2, 3, 4, 6 and 20 stable on longer culture derived promastigotes and sandfly derived promastigotes ?

Response: No, as published in Barja et al Nature EcolEvol 2017 (PMID: 29109466) and Bussotti et al PNAS 2023 (PMID: 36848551), these minor fluctuations are not predicting subsequent aneuploidies in long-term culture nor in sand fly-derived promastigotes. This information has been added to the text.

Comment 4: Is this change of ploidy a culture adaptation representation rather than a life cycle event as the authors discuss later on? (This is probably an optional request that would be nice to include, if the authors have performed the sequencing of such parasites. Otherwise, it should be mentioned in the discussion).

__Response: __Yes, this is a well-known culture adaptation phenomenon, on which we have published extensively. We added this conclusion and the references to the text.

Comment 5: L333 "Likewise, stage differentiation was not associated with any major gene copy number variation (Figure 1C, Table 2)". The authors are looking here at steady differentiated stages rather than differentiation itself. "Likewise, stage differentiation was.." would be more appropriate.

__Response: __We corrected this sentence to 'Likewise, differentiation of promastigotes was not associated with any major gene copy number variation at early passage 2'.

Comment 6: L349-355: have the mRNA presenting change in abundance between stages been normalised by their relative DNA abundance ? Said otherwise, can the wave patterns observed at the genome level explain the respective mRNA level ? Can the authors plot in a similar way the enrichment scores in regards to the position on the genome and can the authors indicate if there is a positional enrichment in addition to the functional one they observe ? This may affect the conclusion in L356-358.

Response: As noted above, we did not see any significant read depth changes at DNA level when comparing amastigotes and promastigotes. Thus there is no need to normalize the RNA-seq results to DNA read depth. Furthermore, in our comparative transcriptomics analysis, we only consider 2-fold or higher changes in mRNA abundance (which is far beyond the non-significant read depth change we have observed on DNA level). Manual inspection of the enrichment scores with respect to position did not reveal any significant signal (other than revealing some over-represented tandem gene arrays where all gene copies share the same location and GO term).

Comment 8: L415 "stage-specific expression changes correlate between protein and RNA levels, suggesting that the abundance of these proteins is mainly regulated by mRNA turn-over". Overstatement. Correlation does not suggest causation. "suggesting that the abundance of these proteins could be regulated by mRNA turn-over" would be more appropriate.

Response: We thank the reviewer for this comment and have corrected the statement accordingly.

Comment 9: Figure 3B, could the authors clarify what are the "unique genes" that are on the infinite quadrants? It seems these proteins are identified in one stage and not the other. This implies that the corresponding missing values are missing non-at random (MNAR). Rather than removing those proteins containing NMAR from the differential expression analysis, the authors should probably impute those missing values. Methods of imputation of NMAR and MAR can be found in the literature. Indeed, the level of expression in one stage of those proteins is now missing, while it could strongly affect the conclusions the authors are drawing in figure 4E regarding the proteins targeted for degradation and rescued in presence of the proteasome inhibitor.

Response: We thank the reviewer for this important comment. However, we would like to clarify several key points regarding the treatment of proteins identified in only one condition.

First, the reviewer assumes that proteins identified in one stage but not the other are necessarily missing not-at-random (MNAR). However, this cannot be definitively established, as these missing values could equally be missing completely at random (MCAR). Without additional information, categorizing them specifically as MNAR may be an oversimplification. More importantly, we have concerns about the reliability of imputation methods in this specific context. Algorithms designed to impute MNAR values (such as QRILC) replace absent data using random sampling from arbitrary probability distributions, typically assuming low intensity values. However, when no intensity value has been detected or quantified for a protein in a given condition, imputing an arbitrary low value raises significant concerns about data interpretation. Such imputed values would not reflect actual measurements but rather statistical assumptions that could introduce bias into downstream analyses. For instance, imputed values could lead to the conclusion that a protein is not differentially abundant, when in reality it is detected in one condition but completely absent in the other. In our view, there are two biologically plausible scenarios: either these proteins are expressed at levels below our detection threshold, or they are genuinely absent (or present at negligible levels) in the corresponding stage. Rather than introducing potentially misleading imputed values, we chose to treat these as genuine stage-specific differences (presence/absence), which results in infinite fold-changes in Figure 3B. Critically, our approach is strongly supported by independent validation through RNA-seq data, which corroborates the differential presence/absence patterns observed at the protein level. Furthermore, our enrichment analyses reveal significant over-representation of specific biological terms among these stage-specific proteins, providing biological coherence to these findings. These converging lines of evidence (proteomics, transcriptomics, and functional enrichment) strengthen our confidence that these represent biologically meaningful differences rather than technical artifacts.Therefore, we believe our conservative approach of treating these as genuine presence/absence differences, validated by orthogonal data, is more appropriate than introducing imputed values based on arbitrary statistical assumptions.To clarify this section, we modified the text as follows: 'Only expression changes were considered that either showed statistically significant differential abundance at both RNA and protein levels (p Comment 10: L430-435 "These data fit with the GO [...] the ribosome translational activity (34)." This discussion feels out of place and context. It is too speculative and with little support by the data presented at this stage of the manuscript. It should be removed as Figure 3E or could be placed in the discussion and supplementary information.

Response: We agree with the reviewer. In response to a comment from reviewer 1, we have moved both panels to Figure 2, which much better integrates these data.

Comment 10: The authors present an elegant way to show stage specific degradation through the comparison of stage specific proteasome blockages that show rescue in ama of proteins present in pro and vice versa. L494 "reveal an unexpected but substantial" the term unexpected is inappropriate, as several studies have shown in kinetoplastids the essential role of protein turnover through degradation / autophagy during differentiation. Furthermore the conclusions may be strongly affected by the level of expression of the proteins in the infinite quadrants as we discussed above, and should be revised accordingly.

Response: We rephrased the conclusion to 'In conclusion, our results confirm the important role of protein degradation in regulating the L. donovani amastigote and promastigote proteomes and identify protein kinases as key targets of stage-specific proteasomal activities.' Please see the response to comment 9 regarding the unique proteins.

Comment 11: L518 "These data reveal a surprising level of stage-specific phosphorylation in promastigotes, which may reflect their increased biosynthetic and proliferative activities compared to amastigotes." Overstatement. Could also be due to culture adaptation - What is the overlap of stage-specific phosphorylations with previous published datasets in other species of Leishmania? Looking at such comparisons could help to decipher the role of culture adaptation response, species specificity and true differentiation conserved mechanisms.

Response: We agree with the reviewer and have toned this statement down by adding the statement '....or simply be a consequence of culture adaptation'.

Comment 12: The discussion is extremely speculative. While some speculation at this stage is acceptable, claiming direct link and feedback without further validation is probably far too stretched. For example, the changes of phosphorylation observed on particular sets of proteins, such as phosphatase and DUBs, need to be validated for their respective change of protein activity in the direction that fits the model of the authors. Those discussions should be toned down.

Response: We agree with the reviewer and have strongly toned down the entire discussion, emphasizing the hypothesis-building character of our results, which provide a novel framework for future experimental analyses.

Comment 13: A couple of typos:

• In the phosphoproteome analysis section, "...0,2 % DCA..." should be "...0.2 % DCA..." (use a decimal point).

• L225 "...peptide match was disable." should be "...peptide match was disabled."

Response: both corrected

__Reviewer #4 (Significance (Required)): __

While there is not too much novelty around the emphasis of gene expression at post-translational level in kinetoplastid organisms, the scale of the work presented here, looking at 5 layers of potential regulations, is. Therefore, this study represents a substantial amount of work and provides interesting and comprehensive datasets useful for the parasitology community.

Response: We thank the reviewer for this positive statement.

Several potential concerns regarding the biological meaning of the findings were identified. These include the limitations of in vitro systems promastigote differentiation potentially limiting the conclusions, the challenge of inferring causality from correlative "omics" data, and the complexities of functional interpretation of changes in phosphorylation and metabolite levels. The proposed feedback loops and functional roles of specific molecules would require further experimental validation to confirm their biological relevance in the natural life cycle of Leishmania, but that would probably fall out of the scope of this manuscript.

Response: We agree with the reviewer and have modified pour manuscript throughout to remove any causal relationships. Indeed, this work is setting the stage for future investigations on dissecting some of the suggested regulatory mechanisms.

Area of expertise of the reviewers: Kinetoplastid, Differentiation, Signalling, Omics

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Referee #4

Evidence, reproducibility and clarity

Summary:

This study investigates the regulatory mechanisms underlying stage differentiation in Leishmania donovani, a parasitic protist. Pesher et al., aim to address the central question of how these parasites establish and maintain distinct life cycle stages in mostly the absence of transcriptional control. The authors employed a five-layered systems-level analysis comparing hamster-derived amastigotes and their in vitro-derived promastigotes. From those parasites, they performed a genomic, transcriptomic, proteomic, metabolomic and phosphoproteomic analysis to reveal the changes the parasites undertook between the two life stages. The main conclusion stated by the authors are:

• The stage differentiation in vitro is largely independent of major changes in gene dosage or karyotype.
• RNA-seq analysis identified substantial stage-specific differences in transcript abundance, forming distinct regulons with shared functional annotations. Amastigotes showed enrichment in transcripts related to amastins and ribosome biogenesis, while promastigotes exhibited enrichment in transcripts associated with ciliary cell motility, oxidative phosphorylation, and post-transcriptional regulation itself.
• Quantitative phosphoproteome analysis revealed a significant increase in global protein phosphorylation in promastigotes. Normalizing phosphorylation changes against protein abundance identified numerous stage-specific phosphoproteins and phosphosites, indicating that differential phosphorylation also plays a crucial role in establishing stage-specific biological networks. The study identified recursive feedback loops (where components of a pathway regulate themselves) in post-transcriptional regulation, protein translation (potentially involving stage-specific ribosomes), and protein kinase activity. Reciprocal feedback loops (where components of different pathways cross-regulate each other) were observed between kinases and phosphatases, kinases and the translation machinery, and crucially, between kinases and the proteasomal system, with proteasomal inhibition disrupting promastigote differentiation.

Comments:

Further details are organised by order of apparition in the text:

• Material and Methods: while the authors are indicating some key parameters, providing the codes and scripts they used throughout the manuscript would improve reproducibility.
• Why only 2 biological replicates for RNA while the others layers have 3 or 4?
• Is the slight but reproducible increase in median coverage observed for chr 1, 2, 3, 4, 6 and 20 stable on longer culture derived promastigotes and sandfly derived promastigotes ? Is this change of ploidy a culture adaptation representation rather than a life cycle event as the authors discuss later on? (This is probably an optional request that would be nice to include, if the authors have performed the sequencing of such parasites. Otherwise, it should be mentioned in the discussion).
• L333 "Likewise, stage differentiation was not associated with any major gene copy number variation (Figure 1C, Table 2)". The authors are looking here at steady differentiated stages rather than differentiation itself. "Likewise, stage differentiation was.." would be more appropriate. L349-355: have the mRNA presenting change in abundance between stages been normalised by their relative DNA abundance ? Said otherwise, can the wave patterns observed at the genome level explain the respective mRNA level ? Can the authors plot in a similar way the enrichment scores in regards to the position on the genome and can the authors indicate if there is a positional enrichment in addition to the functional one they observe ? This may affect the conclusion in L356-358.
• L415 "stage-specific expression changes correlate between protein and RNA levels, suggesting that the abundance of these proteins is mainly regulated by mRNA turn-over". Overstatement. Correlation does not suggest causation. "suggesting that the abundance of these proteins could be regulated by mRNA turn-over" would be more appropriate.
• Figure 3B, could the authors clarify what are the "unique genes" that are on the infinite quadrants? It seems these proteins are identified in one stage and not the other. This implies that the corresponding missing values are missing non-at random (MNAR). Rather than removing those proteins containing NMAR from the differential expression analysis, the authors should probably impute those missing values. Methods of imputation of NMAR and MAR can be found in the literature. Indeed, the level of expression in one stage of those proteins is now missing, while it could strongly affect the conclusions the authors are drawing in figure 4E regarding the proteins targeted for degradation and rescued in presence of the proteasome inhibitor.
• L430-435 "These data fit with the GO [...] the ribosome translational activity (34)." This discussion feels out of place and context. It is too speculative and with little support by the data presented at this stage of the manuscript. It should be removed as Figure 3E or could be placed in the discussion and supplementary information.
• The authors present an elegant way to show stage specific degradation through the comparison of stage specific proteasome blockages that show rescue in ama of proteins present in pro and vice versa. L494 "reveal an unexpected but substantial" the term unexpected is inappropriate, as several studies have shown in kinetoplastids the essential role of protein turnover through degradation / autophagy during differentiation. Furthermore the conclusions may be strongly affected by the level of expression of the proteins in the infinite quadrants as we discussed above, and should be revised accordingly.
• L518 "These data reveal a surprising level of stage-specific phosphorylation in promastigotes, which may reflect their increased biosynthetic and proliferative activities compared to amastigotes." Overstatement. Could also be due to culture adaptation - What is the overlap of stage-specific phosphorylations with previous published datasets in other species of Leishmania ? Looking at such comparisons could help to decipher the role of culture adaptation response, species specificity and true differentiation conserved mechanisms.
• The discussion is extremely speculative. While some speculation at this stage is acceptable, claiming direct link and feedback without further validation is probably far too stretched. For example, the changes of phosphorylation observed on particular sets of proteins, such as phosphatase and DUBs, need to be validated for their respective change of protein activity in the direction that fits the model of the authors. Those discussions should be toned down.

A couple of typos:

• In the phosphoproteome analysis section, "...0,2 % DCA..." should be "...0.2 % DCA..." (use a decimal point).
• L225 "...peptide match was disable." should be "...peptide match was disabled."

Significance

While there is not too much novelty around the emphasis of gene expression at post-translational level in kinetoplastid organisms, the scale of the work presented here, looking at 5 layers of potential regulations, is. Therefore, this study represents a substantial amount of work and provides interesting and comprehensive datasets useful for the parasitology community.

Several potential concerns regarding the biological meaning of the findings were identified. These include the limitations of in vitro systems promastigote differentiation potentially limiting the conclusions, the challenge of inferring causality from correlative "omics" data, and the complexities of functional interpretation of changes in phosphorylation and metabolite levels. The proposed feedback loops and functional roles of specific molecules would require further experimental validation to confirm their biological relevance in the natural life cycle of Leishmania, but that would probably fall out of the scope of this manuscript.

Area of expertise of the reviewers: Kinetoplastid, Differentiation, Signalling, Omics

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Referee #3

Evidence, reproducibility and clarity

Summary:

The study presents a comprehensive multi-omics investigation of Leishmania differentiation, combining genomic, transcriptomic, proteomic, phospho-proteomic and metabolomic data. The authors aim to uncover mechanisms of post-transcriptional and post-translational regulation that drive the stage-specific biology of L. donovani. The authors provide a detailed characterization of transcriptomic, proteomic, and phospho-proteomic changes between life stages, and dissect the relative contributions of mRNA abundance and protein degradation to stage-specific protein expression. Notably, the study is accompanied by comprehensive supplementary materials for each molecular layer and provides public access to both raw and processed data, enhancing transparency and reproducibility. While the data are rich and compelling, several mechanistic interpretations (e.g., "feedback loops," "recursive networks," "signaling cascades") are overstated. Similarly, the classification of gene sets as "regulons" is not adequately supported, as no common regulatory factor has been identified and only a single condition change (amastigote to promastigote) was assessed.

Major Comments:

1. Across several sections (incl abstract, L559-565, L589-599, L600-L603, L610-612, L613-614, L625, L643-645, L650-652), the manuscript describes "recursive or self-controlling networks", "signaling cascades", "self-regulating", and "recursive feedback loops" - involving protein kinases, phosphatases, and translational regulators. While the data convincingly demonstrate stage-specific changes in phosphorylation and abundance changes in key molecules, the language used implies causal, direct and directional regulatory relationships that have not been experimentally validated.
2. Co-expression and shared function alone do not define a regulon (L363, and several other places in the manuscript). A regulon also requires the gene set to be regulated by the same factor, for which there is no evidence here. Regulons can be derived from transcriptomic experiments, but then they need to show the same transcriptional behavior across many biological conditions, while here just 1 condition change is evaluated. Therefore, this analysis is conventional GO enrichment analysis and should not be overinterpreted into regulons.
3. LFQ intensity of 0 (e.g., L389): An LFQ intensity of 0 does not necessarily indicate that a protein is absent, but rather that it was not detected. This can occur for several reasons: (1) true biological absence in one condition, (2) low abundance below the detection threshold, or (3) stochastic missingness due to random dropout in mass spectrometry. While the authors state that adjusted p-values for the 1534 proteins exclusively detected in either amastigotes or promastigotes are below 0.01, I could not find corresponding p-values for these proteins in Table 8 ('Global_Proteomic'). An appropriate statistical method designed to handle this type of missingness should be used. In this context, I also find the following statement unclear: "identified over 4000 proteins at each stage in at least 3 out of 4 biological replicates, representing 3521 differentially expressed proteins (adjusted p-value < 0.01), 1534 of which were exclusively detected in either ama or pro." If a protein is exclusively detected in one stage, then by definition it should not be detected in that number of replicates at both stages. This apparent contradiction should be clarified.
4. L412 - Figure 3B: The figure shows proteins with infinite fold changes, which result from division by zero due to LFQ intensity values of zero in one of the compared conditions. As previously noted, interpreting LFQ zero values as true absence of expression is problematic, since these zeros can arise from several technical reasons - such as proteins being just below the detection threshold or due to stochastic dropout during MS analysis. Therefore, the calculated fold changes for these proteins are likely highly overestimated. This concern is visually supported by the large gap on the y-axis (even in log scale) between these "infinite" fold changes and the rest of the data. Moreover, given Leishmania's model of constitutive gene expression, it seems biologically implausible that all these proteins would be completely absent in one stage. This issue applies not only to Figure 3B, but also to the analyses presented in Figures 4D and 4E.

Minor Comments:

Methods

L132: Typo: "A according" should be "according." L158: How exactly were somy levels calculated? Please specify the method used, as I could not find a clear description in the referenced manuscript. L158: Chromosome 36 is not consistently disomic, as stated. It has been observed in other somy states (e.g., Negreira et al. 2023, EMBO Reports, Figure 1), even if such occurrences are rare in the studied context. Normalizing by chr36 remains a reasonable choice, but it would be helpful to confirm that the majority of chromosomes appear disomic post-normalization to support the assumption that chr36 is disomic in this dataset as well. L163: Suggestion: Cite the GIP pipeline here rather than delaying the reference until L173. L188: "Controlled" may be a miswording. Consider replacing with "confirmed" or "validated." L214: Please specify which statistical test was used to assess differential expression at the protein level. L227: Similarly, clarify which statistical test was applied for determining differential expression in the phospho-proteomics data.

Results

L337-339: The interpretation here is too speculative. Phrases like "suggesting" and "likely" are too strong given the evidence presented. Alternative explanations, such as mosaic variation combined with early-stage selective pressure in the culture environment, should be considered. L340: The "undulating pattern" mentioned is somewhat subjective. To support this interpretation, consider adding a moving average (or similar) line to Figure 3A, which would more clearly highlight this trend across the data points. L356: It may be more accurate to say "control of individual gene expression," since Leishmania does have promoters - the key distinction is that initiation does not occur on a gene-by-gene basis. L403-405: The statement "this is because these metabolites comprise a glycosomal succinate shunt..." should be rephrased as a hypothesis rather than a definitive explanation, as this causal link has not been experimentally validated. L407: Replace "confirming" with "matching" to avoid overstating the agreement with previous observations. L408: Replace "correlated" with "matched" for more accurate interpretation of results. L433: It is unclear how differential RNA modifications were detected. Please specify which biological material was used, the number of replicates per life stage, and how statistical evaluation of differential modifications was performed. L436: This conclusion appears incomplete. While the manuscript mentions transcript-regulated proteins, it should also note that other proteins showed discordant mRNA/protein patterns. A more balanced conclusion would mention both the matching and non-matching subsets. L441: The phrase "poor correlation" overgeneralizes and lacks nuance. Earlier sections of the manuscript describe hundreds of genes where mRNA and protein levels correlate well, suggesting that mRNA turnover plays a key regulatory role. Please rephrase this sentence to clarify that poor correlation applies only to a subset of the data. L454: The claim that "epitranscriptomic regulation and stage-adapted ribosomes are key processes" should be supported with references. If this builds on previously published work, please cite it accordingly. L457: Proteasomal degradation is a well-established mechanism in Leishmania. These findings are interesting but should be presented in the context of existing literature (e.g. Silva-Jardim et al.2014, [PMID: 15234661]) rather than as entirely novel. L459: The authors shoumd add a microscopy image of promastigotes treated with lactacystin. This would provide insight into whether treatment affects morphology, as is known in T. cruzi (see Dias et al., 2008). It would be particularly informative if Leishmania behaves differently. L472 + L481: Table 9 shows several significant GO terms not discussed in the manuscript. Please clarify how the subset presented in the text was selected. L482: The argument that a single master regulator can be excluded is unclear. Could the authors please elaborate on the reasoning or data supporting this conclusion? L494: The term "unexpected" may not be appropriate here, as protein degradation is a well-established regulatory mechanism in trypanosomatids. Consider omitting this term to better reflect the field's current understanding. L543: The term "feedback loop" should be used more cautiously. The current data are correlative, and no interventional experiments are provided to support a causal regulatory loop between proteasomal activity and protein kinases. As such, this remains a hypothesis rather than a confirmed mechanism.

Discussion

L555: As noted in L494, reconsider using the word "unexpected." L589: The data do not fully support the presence of stage-specific ribosomes. Rather, they suggest differential ribosomal function through changes in abundance and regulation. Please consider rephrasing. L657-658: The discussion of post-transcriptional and post-translational regulation of gene dosage effects would benefit from citing additional literature beyond the authors' own work. E.g. the study by Cuypers et al. (PMID: 36149920) offers a relevant and comprehensive analysis covering 4 'omic layers. L659-664: The reference to deep learning for biomarker discovery appears speculative and loosely connected to the current findings. As no such methods were applied in the study, and the manuscript does not clarify what types of biomarkers are intended, this statement could be seen as aspirational rather than evidence-based. Consider either omitting or elaborating with clear justification. L690 + L705 (Figure 2): The phrase "main GO terms" is vague. Please clarify the criteria for selecting the GO terms shown - were they chosen based on adjusted p-value, enrichment score, or another metric? Additionally, define "cluster efficiency," explaining how it was calculated and what it represents.

Signed: Bart Cuypers, PhD

Referee cross-commenting

Overall, I think the other reviewers' comments are fair. They seem to align particularly on the following points:

1. Reviewers agree that this is a comprehensive body of work with original contributions to the field of Leishmania/trypanosomatid molecular biology, and that it will serve as a valuable reference for hypothesis generation.
2. Several reviewers raise concerns about overinterpretation of the data, particularly regarding regulatory networks, regulons, and master regulators. The interpretation and large parts of the discussion are considered too speculative without additional functional validation.
3. There are comments about the incorrect statistical treatment of missing values in the proteomics experiments, which affects confidence in some of the conclusions.
4. While the correlation between the two RNA-Seq replicates is high, the decision to include only two biological replicates is seen as unfortunate and not ideal for statistical robustness.
5. The use of lactacystin should be more clearly motivated, and its limitations discussed in the context of the experiments.

Even though I did not remark on the last two points (4 and 5) in my own review, I agree with them.

Significance

This study provides a rich, integrative multi-omics dataset that advances our understanding of stage-specific adaptation in the transcriptionally unique parasite Leishmania. By dissecting the relative contributions of mRNA abundance and protein turnover to final protein levels across life stages, the authors offer valuable insights into post-transcriptional and post-translational regulation. The work represents a resource-driven yet conceptually informative contribution to the field, with comprehensive supplementary materials and transparent data sharing standing out as additional strengths.

However, the mechanistic insights proposed are speculative in several places and require more cautious language. The study is most impactful as a resource and descriptive atlas, initiating hypotheses for future validation. The broad scientific community working on Leishmania, trypanosomatids, and post-transcriptional regulation in eukaryotes would benefit from this work.

Field of reviewer expertise: multi-omics integration, bioinformatics, molecular parasitology, transcriptomics, proteomics, metabolomics, Leishmania, Trypanosoma

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Referee #2

Evidence, reproducibility and clarity

Summary:

Pescher and colleagues present a manuscript detailing the multi-omic characterisation of Leishmania donovani amastigote to promastigote differentiation and integration of this data. Their aim was to reveal the cellular mechanisms and pathways by which Leishmania differentially regulate protein and mRNA levels during life-stage progression, in the absence of differential transcriptional control. Integration of RNA-seq, proteomics, metabolomics, and phosphoproteomics identify several broad regulatory processed by which the parasite differentially modulates ribosome biogenesis and function, protein abundance by proteasomal degradation, and protein kinase signalling networks. The intersection of these processes is explicitly considered in the data analysis to identify potential recursive and reciprocal signalling networks. The authors use Leishmania donovani amastigotes derived from hamster infections, and use these to initiate amastigote to promastigote differentiation time course. Initially a DNA-seq quality control is presented to rule out dramatic ploidy changes in the differentiating lines - which is known to occur in Leishmania undergoing adaptation to tissue culture. Small changes are observed but, because only 2 passages are performed, they are low and the lines remain generally diploid. There is good correlation between replicates. The implication is that neither subtle nor dramatic changes in ploidy drive life stage differentiation.

Next, mRNA-seq is presented on duplicate samples from amastigote and promastigote forms. Correlation between the two replicates is reported to be high. Differentially abundant transcripts are identified using DESeq2 and the genes in the up/down-regulated sets are analysed by GO term enrichment (and cluster efficiency). Genes are clustered by similar function and the implication is that these compromise post-transcriptionally regulated regulons, sharing common regulatory processes. Whole cell label-free, quantitative proteomics is conducted to profile the amastigote and promastigotes forms. The differentially abundant proteins are identified and again analysed by GO term - revealing a general discordance with the RNA-seq results. The implication is that there are additional layers of regulation linking protein abundance to mRNA abundance. A metabolomics analysis performed where the authors look for changes in the metabolome of the promastigotes from the amastigotes and suggest that the stages they have exhibit expected biochemical behaviour. The RNA-seq and proteomics fold change values are then correlated to identify proteins with differential abundances linked to mRNA levels, and those that deviate from this relationship. For example, proteins that increase in promastigote forms but the corresponding mRNA is decreased etc. The authors focus in on a group of ribosomal proteins less abundant than the mRNA would suggest (as ribosome biogenesis was a regulon identified as a regulon of interest). In the absence of riboprofiling the authors return to the RNA-seq to assess the levels of pre-Sno RNA (the role of the could be more explicitly stated). They relate this to a previous study also showing differential stage specific ribosome RNA pseudouridination (and differential levels of pseudouridine transferases, this study.) - which affect ribosome translational efficiency. This is their first example of a potential recursive level of regulation.

Because protein levels can also be impacted by proteolytic turnover the authors then search for proteins that are normally degraded by the ubiquitin-proteasome system in each stage and an intermediate 18 h timepoint - potentially allowing identification of amastigote degraded proteins, promastigote degrade proteins and intriguingly, constitutively degraded proteins. The authors use the proteasome inhibitor lactacystin at 10 µM as a chemical method to block proteasome activity. This treatment is implied to block differentiation by the morphology of treated cells under microscopy. The authors suggest that proteins protected from degradation act as repressors of differentiation that override any positive signal coming from signalling pathways or newly synthesised proteins. Proteins are identified as differentially stabilised, in both amastigote, promastigote forms and during differentiation. The GO analysis identifies protein kinases as significantly enriched in this context and suggests layering of regulation by the stability of signalling proteins.

In the context of this differential regulation the authors perform a round of phosphoproteomics, and use the whole-cell proteome to normalise phosphosite abundance to protein abundance in the various stages. While not at the level of site-specific occupancy this allows them to subset the phospho modifications into various categories including those that change independently of protein levels, ie. Increasing in their "stoichiometry". GO term analysis again is used and identifies ubiquitination systems and protein kinases & phosphatases as enriched, and specific examples are described. This demonstrates that there is likely recursive and reciprocal regulatory processes at interplay between these classes of proteins.

The authors provide a clear and comprehensive description of the data at each stage of the results and this in woven together in the discussion allowing hypotheses to be formed on the potential regulatory and signalling pathways that control the differentiation of amastigotes to promastigotes. Given the amount and breadth of data presented the authors are able to present a high-level assessment of the processes that form feedback loops and/or intersectional signalling, but specific examples are not picked out for deeper validation or exploration.

Major comments:

Are the claims and the conclusions supported by the data or do they require additional experiments or analyses to support them?

As I have understood it from the description in the text, and in Data Table 4, the RNA-seq element of the work has only been conducted using two replicates. If this is the case, it would substantially undermine the RNA-seq and the inferences drawn from it. Minimum replicates required for inferential analysis is 3 bio-replicates and potentially up to 6 or 12. It may be necessary for the authors to repeat this for the RNA-seq to carry enough weight to support their arguments. (PMID: 27022035 )

There are several examples that are given as reciprocal or recursive signalling pathways, but these are not followed up with independent, orthogonal techniques. I think the paper currently forms a great resource to pursue these interesting signalling interactions and is certainly more than just a catalogue of modifications, but to take it to the next level ideally a novel signalling interaction would be demonstrated using an orthogonal approach. Perhaps the regulation of the ribosomes could have been explored further (same teams recently published related work on this). Or perhaps more interestingly, a novel target(s) from the ubiquitinated protein kinases could have been explored further; for example making precision mutants that lack the ubiquitination or phosphorylation sites - does this abrogate differentiation?

I found the use of lactacystin a bit curious as there are more potent and specific inhibitors of Leishmania proteasomes e.g. LXE-408. This could be clarified in the write-up (See below).

Please request additional experiments only if they are essential for the conclusions. Alternatively, ask the authors to qualify their claims as preliminary or speculative, or to remove them altogether.

If it is the case that only 2 replicates of the RNA-Seq have been performed it really is not the accepted level of replication for the field. Most studies use a minimum of 3 bioreplicates and even a minimum of 6 is recommended by independent assessment of DESeq2.

As far as I could see, the cell viability assay does not include a positive control that shows it is capable of detecting cytotoxic effects of inhibitors. Add treatment showing that it can differentiate cytostatic vs cytotoxic compound.

If you have constructive further reaching suggestions that could significantly improve the study but would open new lines of investigations, please label them as "OPTIONAL". Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated time investment for substantial experiments.

It is realistic for the authors to validate the cell viability assay. If the RNA-seq needs to be repeated then this would be a substantial involvement.

Are the data and the methods presented in such a way that they can be reproduced?

All the methods are written to a good level of detail. The sample prep, acquisition and data analysis of the protein mass spectrometry contained a high level of detail in a supplemental section. The authors should be more explicit about the amount of replication at each stage, as in parts of the manuscript this was quite unclear.

Are the experiments adequately replicated and statistical analysis adequate?

Unless I have misunderstood the manuscript, I believe the RNA-seq dataset is underpowered according to the number of replicates the authors report in the text.

Looking at Figure 1 and S1 and Data Table 4 to show the sample workflow I was surprised to see that the RNA-seq only used 2 replicates. The authors do show concordance between the individual biological replicates, but I would consider that only having 2 is problematic here, especially given the importance placed on the mRNA levels and linkage in this study. This would constitute a major weakness of the study, given that it is the basis for a crucial comparison between the RNA and protein levels.

It also wasn't clear to me how many replicates were performed at each condition for the lactacystin treatment experiment - can the authors please state this clearly in the text, it looks like 4 replicates from Figure S1 and Data Table 8.

Four replicates are used for the phosphoproteomics data set, which is probably ok, but other researchers have used a minimum of 5 in phosphoproteomics experiments to deal with the high level of variability that can often be observed with low abundance proteins & modifications. The method for the phosphoproteomics analysis suggests that a detection of a phosphosite in 1 sample (also with a localisation probability of >0.75) was required for then using missing value imputation of other samples. This seems like a low threshold for inclusion of that phosphosite for further relative quantitative analysis. For example, Geoghegan et al (2022) (PMID: 36437406) used a much more stringent threshold of greater than or equal to 2 missing values from 5 replicates as an exclusion criteria for detected phoshopeptides. Please correct me if I misunderstood the data processing, but as it stands the imputation of so many missing values (potentially 3 of 4 per sample category) could be reducing the quality of this analysis.

For the metabolomics analysis it looks like 2 amastigote samples were compared against 4 promastigote samples. Why not triplicates of each?

Minor comments:

Specific experimental issues that are easily addressable.

Are prior studies referenced appropriately?

Yes

Are the text and figures clear and accurate?

The write up is clear, with the data presented coherently for each method. The analyses that link everything together are well discussed. The figures are mostly clear (see below) and are well described in the legends. There is good use of graphics to explain the experimental designs and sample names - although it is unclear if technical replicates are defined in these figures.

Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

As I have understood it, the authors have calculated the "phosphostoichiometry" using the ratio of change in the phosphopeptide to the ratio of the change in total protein level changes. This is detailed in the supplemental method (see below). Whilst this has normalised the data, it has not resulted in an occupancy or stoichiometry measurement, which are measured between 0-1 (0% to 100%). The normalisation has probably been sufficient and useful for this analysis, but this section needs to be re-worded to be more precise about what the authors are doing and presenting. These concepts are nicely reviewed by Muneer, Chen & Chen 2025 (PMID: 39696887) who reference seminal papers on determination of phosphopeptide occupancy - and may be a good place to start. An alternative phrase should be used to describe the ratio of ratios calculated here, not phosphostoichiometry.

From the authors methods describing the ratio comparison approach:

"Another statistical test was performed in a second step: a contrasted t-test was performed to compare the variation in abundance of each modified peptide to the one of its parent unmodified protein using the limma R package {Ritchie, 2015; Smyth, 2005}. This second test allows determining whether the fold-change of a phosphorylated peptide between two conditions is significantly different from the one of its parent and unmodified protein (paragraph 3.9 in Giai Gianetto et al 2023). An adaptive Benjamini-Hochberg procedure was applied on the resulting p-values thanks to the adjust.p function of R package cp4p {Giai Gianetto, 2016} using the Pounds et al {Pounds, 2006} method to control the False Discovery Rate level."

Several aspects of the figures that contain STRING networks are quite useful, particularly the way colour around the circle of each node to denote different molecular functions/biological processes. However, some have descended into "hairball" plots that convey little useful information that would be equally conveyed in a table, for example. Added to this, the points on the figure are identified by gene IDs which, while clear and incontrovertible, are lacking human readability. I suggest that protein name could be included here too. It is also not clear what STRING data is being plotted here, what are the edges indicating - physical interactions proven in Leishmania, or inferred interactions mapped on from other organisms? Perhaps as supplemental data provide the Cytoscape network files so readers can explore the networks themselves?

The title of columns in table S10 panel A are written in French, which will be ok for many people particularly those familiar with proteomics software outputs, but everything else is in English so perhaps those titles could be made consistent.

I would suggest that the authors provide a table that has all the gene IDs of the Ld1S2D strain and the orthologs for at least one other species that is in TriTrypDB. This would make it easy to interrogate the data and make it a more useful resource for the community who work on different strains and species of Leishmania. Although this data is available it is a supplemental material file in a previous paper (Bussotti et al PNAS 2021) and not easy to find.

Figure 5b - from the legend it is not clear where the confidence values were derived in this analysis, although this is explained in the supplemental method. Perhaps the legend can be a bit clearer.

Can the authors discuss why lactacystin was used? While this is a commonly used proteasome inhibitor in mammalian cells there is concern that it can inhibit other proteases. At the concentrations (10 µM) the authors used there are off-target effects in Leishmania, certainly the inhibition of a carboxypeptidase (PMID: 35910377) and potentially cathepsins as is observed in other systems (PMID: 9175783). There is a specific inhibitor of the Leishmania proteasome LXE-408 (PMID: 32667203), which comes closer to fulfilling the SGC criteria (PMID: 26196764) for a chemical probe - why not use this. Does lactacystin inhibit a different aspect of proteasome activity compared to LXE-408? The application of lactacystin is changing the abundance of a multitude of proteins but no precision follow up is done to identify if those proteins are necessary and/or sufficient from driving/blocking differentiation. This could be tested using precision edited lines that are unable to be ubiquitinated? There is a lack of direct evidence that the proteins protected from degradation by lactacystin are ubiquitinated? Perhaps some of these could be tagged and IP'd then probed for ubiquitin signal. Di-Gly proteomics to reveal ubiquitinated proteins? These suggestions should be considered as OPTIONAL experiments in the relevant section above.

In the data availability RNA-seq section the text for the GEO link is :

(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc= GSE227637) but the embedded link takes me to (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE165615) which is data for another, different study. Also, the link to the GEO site for the DNA seq isn't working and manual searches with the archive number (BioProject PRJNA1231373 ) does not appear to find anything. The IDs for the mass spec data PRIDE/ProteomeXchange don't seem to bring up available datasets: PXD035697 and PXD035698

Referee cross-commenting

It seems that all the reviewers' comments touch on relatively common themes - potential overinterpretation of the RNA-seq data (such as identifying/defining regulons), & statistical analysis of the proteomics/phosphoproteomics. Experimentally adding the positive control for the cell viability assay would increase robustness of that workflow, and follow up of a pathway/interaction would boost the significance of the work. All the other reviews look to be fair and well justified. I don't have anything more to add or change based on reading the other reviews.

Significance

Provide contextual information to readers (editors and researchers) about the novelty of the study, its value for the field and the communities that might be interested.

The following aspects are important:

General assessment: provide a summary of the strengths and limitations of the study. What are the strongest and most important aspects? What aspects of the study should be improved or could be developed?

Strengths:

The molecular pathways that regulate Leishmania life-stage transitions are still poorly understood, with many approaches exploring single proteins/RNAs etc in a reductionist manner. This paper takes a systems-scale approach and does a good job of integrating the disparate -omics datasets to generate hypotheses of the intersections of regulatory proteins that are associated with life-cycle progression.

The differentiation step studied is from amastigote to promastigote. I am not aware that this has been studied before using phosphoproteomics. The use of the hamster derived amastigotes is a major strength. While a difficult/less common model, the use of hamsters permits the extraction of parasites that are host adapted and represent "normal", host-adapted Leishmania ploidy, the promastigote experiments are performed at a low passage number. This is a strength or the work as it reduces the interference of the biological plasticity of Leishmania when it is cultured outside the host.

Limitations:

Potential lack of appropriate replication (see above).

Lack of follow up/validation of a novel signalling interaction identified from the systems-wide approach. There is a lack of assessment of whether a single signalling cascade is driving the differentiation or these are all parallel, requisite pathways. The authors state the differentiation is not driven by a single master regulator, but I am not sure there is adequate evidence to rule this in or out.

Advance: compare the study to the closest related results in the literature or highlight results reported for the first time to your knowledge; does the study extend the knowledge in the field and in which way? Describe the nature of the advance and the resulting insights (for example: conceptual, technical, clinical, mechanistic, functional,...).

The study applies well established techniques without any particular technical step-change. The application of large-scale multi-omics techniques and integrated comparisons of the different experimental workflows allow a synthesis of data that is a step forward from that existing in the previous Leishmania literature. It allows the generation of new hypotheses about specific regulatory pathways and crosstalk that potentially drive, or are at least active, during amastigote>promastigote differentiation.

Audience: describe the type of audience ("specialized", "broad", "basic research", "translational/clinical", etc...) that will be interested or influenced by this research; how will this research be used by others; will it be of interest beyond the specific field?

This manuscript will have primary interest to those researchers studying the molecular and cell biology of Leishmania and other kinetoplastid parasites. The approaches used are quite standard (so not so interesting in terms of methods development etc.) and given the specific quirks of Leishmania biology it may not be that relevant to those working more broadly in parasites from different clades/phyla, or those working on opisthokont systems- yeast, humans etc. Other Leishmania focused groups will surely cherry-pick interesting hits from this dataset to advance their studies, so this dataset will form a valuable reference point for hypothesis generation.

Please define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

Relevant expertise: Trypanosoma & Leishmania molecular & cell biology, RNA-seq, proteomics, transcriptional/epigenetic regulation, protein kinases - some experience of UPS system.

I have not provided comment on the metabolomics as it is outside my core expertise. However, I can see it was performed at one of the leading parasitology metabolomics labs.

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Referee #1

Evidence, reproducibility and clarity

This study confirms and extends previous observations of discordance between RNA and protein abundances, characterized by major counter-correlations, during amastigote-to-promastigote differentiation in Leishmania parasites in culture, using a systems-level approach. The authors leverage robust omics techniques and sophisticated computational analyses to explore potential post-transcriptional and -translational control interplay in Leishmania. However, the narrative becomes somewhat diffuse with the shift to putative multilevel regulatory networks, which would benefit from further experimental validation.

Major issues

1. Fig.1D suggests a significant portion of the SNPs are exclusive, with a frequency of zero in one of the two stages. Were only the heterozygous and minor alleles plotted in Fig.1D, since frequencies close to 1 are barely observed? Is the same true in Sup Fig. S2B? Why do chrs 4 and 33 show unusual patterns in S2B?
2. Chr26 revealed a striking contrasting gene coverage between H-1 and the other two samples. While a peak is observed for H-1 in the middle of this chr, the other two show a decrease in coverage. Is there any correlation with the transcriptomic/proteomic findings?
3. The term "regulon" is used somewhat loosely in many parts of the text. Evidence of co-transcriptomic patterns alone does not necessarily demonstrate control by a common regulator (e.g., RNA-binding protein), and therefore does not fulfill the strict definition of a regulon. It should be clear whether the authors are highlighting potential multiple inferred regulons within a list of genes or not. Maybe functional/ gene module/cluster would be more appropriate terms.
4. It is unclear whether the findings in Fig.3E are based on previous analysis of stage-specific rRNA modifications or inferred from the pre-snoRNA transcriptomic data in the current work or something else. I struggle to find the significance of presenting this here.
5. The protein turnover analysis is missing the critical confirmation of the expected lactacystin activity on the proteasome in both ama and pro. A straightforward experiment would be an anti-polyUb western blotting using a low concentration SDS-PAGE or a proteasome activity assay on total extracts.
6. The viability tests upon lactacystin treatment need a positive control for the PI and the YoPro staining (i.e., permeabilized or heat-killed promastigotes).
7. I found that the section on regulatory networks was somewhat speculative and less focused. Several of the associated conclusions are, in some parts, overstated, such as in "uncovered a similar recursive feedback loop" (line 566) or "unprecedented insight into the regulatory landscape" (line 643). It would be important to provide some form of direct evidence supporting a functional connection between phosphorylation/ubiquitination, ribosome biogenesis/proteins and gene expression regulation.

Minor issues

1. The ordinal transition words "First,"/"Second," are used too frequently in explanatory sections. I noted six instances. I suggest replacing or rephrasing some to improve flow.
2. Ln 168: Unformatted citations were given for the Python packages used in the study.
3. Fig.1D: "SNP frequency" is the preferred term in English.
4. Fig.2A: not sure what "counts}1" mean.
5. Ln 685: "Transcripts with FC < 2 and adjusted p-value > 0.01 are represented by black dots" -> This sentence is inaccurate. The intended wording might be: "Transcripts with FC < 2 OR adjusted p-value > 0.01 are represented by black dots"
6. Ln 698: Same as ln 685 mentioned above.
7. Fig.2B and elsewhere: The legend key for the GO term enrichment is a bit confusing. It seems like the color scales represent the adj. p-values, but the legend keys read "Cluster efficiency" and "Enrichment score", while those values are actually represented by each bar length. Does light blue correspond to a max value of 0.05 in one scale, and dark blue to a max value of 10-7 in the other scale?
8. Sup Figure S3A and S4A: The hierarchical clustering dendrograms are barely visible in the heatmaps.
9. S3A Legend: The following sentence sounds a bit awkward: "Rows and columns have been re-ordered thanks to a hierarchical clustering". I suggest switching "thanks to a hierarchical clustering" to "based on hierarchical clustering".
10. Fig.5D: The font size everywhere except the legend key is too small. In addition, on the left panel, gene product names are given as a column, while on the right, the names are shown below the GeneIDs. Consistency would make it clearer.

Significance

At its current stage, this work represents a robust resource for molecular parasitology research programs, paving the way for mechanistic studies on multilayered gene expression control and it would benefit from experimental evidence for some of the claims concerning the in silico regulatory networks. Terms like "regulons", "recursive feedback loop" are employed without solid confirmation or extensive literature support. In my view, the most relevant contribution of this study is centered in the direct association between proteasome-dependent degradation and Leishmania differentiation.

eLife Assessment

In this valuable study, the authors present traces of bone modification on ~1.8 million-year-old proboscidean remains from Tanzania, which they infer to be the earliest evidence for stone-tool-assisted megafaunal consumption by hominins. Challenging published claims, the authors argue that persistent megafaunal exploitation roughly coincided with the earliest Acheulean tools. Notwithstanding the rich descriptive and spatial data, the behavioral inferences about hominin agency rely on traces (such as bone fracture patterns and spatial overlap) that are not unequivocal; the evidence presented to support the inferences thus remains incomplete. Given the implications of the timing and extent of hominin consumption of nutritious and energy-dense food resources, as well as of bone toolmaking, the findings of this study will be of interest to paleoanthropologists and other evolutionary biologists.

Reviewer #1 (Public review):

Domínguez-Rodrigo and colleagues make a moderately convincing case for habitual elephant butchery by Early Pleistocene hominins at Olduvai Gorge (Tanzania), ca. 1.8-1.7 million years ago. They present this at the site scale (the EAK locality, which they excavated), as well as across the penecontemporaneous landscape, analyzing a series of findspots that contain stone tools and large-mammal bones. The latter are primarily elephants, but giraffids and bovids were also butchered in a few localities. The authors claim that this is the earliest well-documented evidence for elephant butchery; doing so requires debunking other purported cases of elephant butchery in the literature, or in one case, reinterpreting elephant bone manipulation as being nutritional (fracturing to obtain marrow) rather than technological (to make bone tools). The authors' critical discussion of these cases may not be consensual, but it surely advances the scientific discourse. The authors conclude by suggesting that an evolutionary threshold was achieved at ca. 1.8 ma, whereby regular elephant consumption rich in fats and perhaps food surplus, more advanced extractive technology (the Acheulian toolkit), and larger human group size had coincided.

The fieldwork and spatial statistics methods are presented in detail and are solid and helpful, especially the excellent description (all too rare in zooarchaeology papers) of bone conservation and preservation procedures. However, the methods of the zooarchaeological and taphonomic analysis - the core of the study - are peculiarly missing. Some of these are explained along the manuscript, but not in a standard Methods paragraph with suitable references and an explicit account of how the authors recorded bone-surface modifications and the mode of bone fragmentation. This seems more of a technical omission that can be easily fixed than a true shortcoming of the study. The results are detailed and clearly presented.

By and large, the authors achieved their aims, showcasing recurring elephant butchery in 1.8-1.7 million-year-old archaeological contexts. Nevertheless, some ambiguity surrounds the evolutionary significance part. The authors emphasize the temporal and spatial correlation of (1) elephant butchery, (2) Acheulian toolkits, and (3) larger sites, but do not actually discuss how these elements may be causally related. Is it not possible that larger group size or the adoption of Acheulian technology have nothing to do with megafaunal exploitation? Alternative hypotheses exist, and at least, the authors should try to defend the causation, not just put forward the correlation. The only exception is briefly mentioning food surplus as a "significant advantage", but how exactly, in the absence of food-preservation technologies? Moreover, in a landscape full of aggressive scavengers, such excess carcass parts may become a death trap for hominins, not an advantage. I do think that demonstrating habitual butchery bears very significant implications for human evolution, but more effort should be invested in explaining how this might have worked.

Overall, this is an interesting manuscript of broad interest that presents original data and interpretations from the Early Pleistocene archaeology of Olduvai Gorge. These observations and the authors' critical review of previously published evidence are an important contribution that will form the basis for building models of Early Pleistocene hominin adaptation.

Reviewer #2 (Public review):

The authors argue that the Emiliano Aguirre Korongo (EAK) assemblage from the base of Bed II at Olduvai Gorge shows systematic exploitation of elephants by hominins about 1.78 million years ago. They describe it as the earliest clear case of proboscidean butchery at Olduvai and link it to a larger behavioral shift from the Oldowan to the Acheulean.

The manuscript makes a valuable contribution to the Olduvai Gorge record, offering a detailed description of the EAK faunal assemblage. In particular, the paper provides a high-resolution record of a juvenile Elephas recki carcass, associated lithic artifacts, and several green-broken bone specimens. These data are inherently valuable and will be of significant interest to researchers studying Early Pleistocene taphonomy.

Comments on previous round of revisions:

The revised manuscript does a good job of using less definitive language, particularly by adding "possible" qualifiers to several interpretations. This addresses the concern about overstatement.

The main issue raised in the original review, however, remains unresolved. Only two elephant bone specimens at EAK show green-bone breakage interpreted as anthropogenic, and the diagnostic basis for that interpretation is not demonstrated clearly on the EAK material itself. The manuscript discusses a suite of fracture attributes described as diagnostic of dynamic percussive breakage, but these attributes are not explicitly documented on the EAK specimens. Instead, the diagnostic traits are illustrated using material from other Olduvai contexts, and that behavior is then extrapolated to make similar claims at EAK. For a paper making a potentially important behavioral argument, the key diagnostic evidence is not clearly demonstrated at the focal assemblage.

This problem is evident in the presentation of the EAK specimens. In their response, the authors state that one EAK specimen shows "overlapping scars" and constitutes a "long bone flake"; however, these features are not clearly identifiable in the figures or captions as currently presented. The authors state that Figures S21-S23 clearly indicate human agency, including a long bone flake with overlapping scars and a view of the medullary surface, but it is unclear which specimens or surfaces these descriptions refer to. Figure S21 does appear to show green fracture and is described only as an "elephant-sized flat bone fragment with green-bone curvilinear break." Figure S22 shows the same bone and cortical surface in a different orientation, providing no additional information. In Figure S23, I cannot clearly identify a medullary surface or evidence of green-bone fracture from this image. None of these images clearly demonstrates overlapping scars, and the figures would be substantially improved by explicitly identifying the features described in the text. Even if both EAK specimens are accepted as green-broken, they do not demonstrate the co-occurrence of multiple diagnostic fracture traits such as multiple green breaks, large step fractures, hackle marks, and overlapping scars that the authors state is required to attribute dynamic percussive activity to hominins and address equifinality.

I appreciate that the authors are careful to state that spatial association between stone tools and fossils alone does not demonstrate hominin behavior, and that they treat the spatial analyses as supportive rather than decisive. While the association is intriguing, the problem is downstream: spatial association is used to strengthen an interpretation of butchery at EAK that still depends on fracture evidence that is not clearly documented at the assemblage level.

The critique concerning Nyayanga is not addressed in the revision. The manuscript proposes alternative explanations for the Nyayanga material but does not demonstrate why these are more plausible than the interpretation advanced by Plummer et al. (2023). I am not arguing that the Nyayanga material should be accepted as butchery; rather, showing that trampling is possible does not establish it as more probable than cut marks. In contrast, the EAK material is treated as evidence of butchery on the basis of evidence that, in my opinion, is more limited and less clearly demonstrated. Even if this is not the authors' intention, the uneven treatment removes an earlier megafaunal case from the comparison and strengthens the case for interpreting EAK as marking a behavioral shift toward megafaunal butchery by excluding other early cases.

While I remain concerned about how the EAK evidence is documented and interpreted, I think the manuscript is appropriate for publication and will generate useful discussion. Readers can then assess for themselves whether the available evidence supports the strength of the behavioral claims.

[Editors' note: the authors are encouraged to make this version the Version of Record.]

Author response:

The following is the authors’ response to the previous reviews

Reviewer #2 (Public review):

This problem is evident in the presentation of the EAK specimens. In their response, the authors state that one EAK specimen shows "overlapping scars" and constitutes a "long bone flake"; however, these features are not clearly identifiable in the figures or captions as currently presented. The authors state that Figures S21-S23 clearly indicate human agency, including a long bone flake with overlapping scars and a view of the medullary surface, but it is unclear which specimens or surfaces these descriptions refer to. Figure S21 does appear to show green fracture and is described only as an "elephant-sized flat bone fragment with green-bone curvilinear break." Figure S22 shows the same bone and cortical surface in a different orientation, providing no additional information. In Figure S23, I cannot clearly identify a medullary surface or evidence of green-bone fracture from this image. None of these images clearly demonstrates overlapping scars, and the figures would be substantially improved by explicitly identifying the features described in the text. Even if both EAK specimens are accepted as green-broken, they do not demonstrate the co-occurrence of multiple diagnostic fracture traits such as multiple green breaks, large step fractures, hackle marks, and overlapping scars that the authors state is required to attribute dynamic percussive activity to hominins and address equifinality.

We appreciate the reviewer’s careful evaluation of the EAK specimens. We acknowledge that the overlapping scars and medullary surface of the specimen originally shown in Figure S23 were not sufficiently clear. To address this, we have extensively revised Figure S23. In the updated Supplementary File, we have provided new annotations and line drawings that explicitly trace the outlines of the overlapping scars and clearly shows the green-bone fracture features. These enhancements ensure that the diagnostic traits discussed in the text are now directly identifiable in the visual record. This demonstrates the co-occurrence of traits: green-broken outlines and overlapping scars, which meet the criteria for identifying dynamic percussive activity. This is so following Reviewer´s 2 partial handling of our arguments; since we argued in our previous response that clear simple green-broken elephant long limb bones were an anthropogenic signature per se, given that currently no durophagous predator/scavenger (including spotted hyenas) are able to produce them. Additional secondary features like hackle marks are supportive but not necessary to attribute human agency.

I appreciate that the authors are careful to state that spatial association between stone tools and fossils alone does not demonstrate hominin behavior, and that they treat the spatial analyses as supportive rather than decisive. While the association is intriguing, the problem is downstream: spatial association is used to strengthen an interpretation of butchery at EAK that still depends on fracture evidence that is not clearly documented at the assemblage level.

The association is inferred (not demonstrated) by the strong statistical spatial association between lithics and bones. Additional taphonomic evidence (like cut marks or green-broken bones) do further support the inference but they do not demonstrate it, given the highly subjective nature of cut mark identification and the plethora of alternative scenarios: one green-broken bone would not demonstrate complete elephant butchery (it could result from a marginal exploitation of just that bone); one cutmarked bone could equally reflect several alternative access types to the remains. The reviewer recognized above the presence of green-broken elements at EAK; again, this supports anthropogenic agency better than any other alternative scenario, because one of the green-broken bones is a long bone and modern hyenas are not able to produce this kind of specimens.

The critique concerning Nyayanga is not addressed in the revision. The manuscript proposes alternative explanations for the Nyayanga material but does not demonstrate why these are more plausible than the interpretation advanced by Plummer et al. (2023). I am not arguing that the Nyayanga material should be accepted as butchery; rather, showing that trampling is possible does not establish it as more probable than cut marks. In contrast, the EAK material is treated as evidence of butchery on the basis of evidence that, in my opinion, is more limited and less clearly demonstrated. Even if this is not the authors' intention, the uneven treatment removes an earlier megafaunal case from the comparison and strengthens the case for interpreting EAK as marking a behavioral shift toward megafaunal butchery by excluding other early cases.

Again, it was never our intention to “demonstrate” anything. The reviewer is misusing this term. These types of arguments are epistemologically impossible to demonstrate. One can just discuss the heuristics of alternative scenarios. The point that we tried to make was that the Nyayanga purported cut marks on megafaunal remains are (as identified and published) impossible to differentiate from natural sedimentary abrasive marks (like trampling). Therefore, they cannot be argued to represent anthropogenic butchery on a secure basis. Especially, when they do not occur in conjunction with green-broken elements of clear dynamic loading nature.

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eLife Assessment

Mitochondrial DNA (mtDNA) exhibits a degree of resistance to mutagenesis under genotoxic stress, and this study on the mitochondrial Transcription Factor A (TFAM) presents important data concerning the possible mechanisms involved. The presented data are solid, technically rigorous, and consistent with established literature findings. The experiments are well-executed, providing convincing evidence on the change of TFAM-DNA interactions following UVC irradiation.

Reviewer #1 (Public review):

Summary:

The authors investigate how UVC induced DNA damage alters the interaction between the mitochondrial transcription factor TFAM and mtDNA. Using live-cell imaging, qPCR, atomic force microscopy (AFM), fluorescence anisotropy, and high-throughput DNA-chip assays, they show that UVC irradiation reduces TFAM sequence specificity and increases mtDNA compaction without protecting mtDNA from lesion formation. From these findings the authors suggest that TFAM acts as a "sensor" of damage rather than a protective or repair-promoting factor.

Strengths:

(1) The focus on UVC damage offers a clean system to study mtDNA damage sensing independently of more commonly studied repair pathways, such as oxidative DNA damage. The impact of UVC damage is not well understood in the mitochondria and this study fills that gap in knowledge.

(2) In particular, the custom mitochondrial genome DNA chip provides high resolution mapping of TFAM binding and reveals a global loss of sequence specificity following UVC exposure.

(3) The combination of in vitro TFAM DNA biophysical approaches combined with cellular responses (gene expression, mtDNA turnover) provides a coherent multi-scale view.

(4) The authors demonstrate that TFAM induced compaction does not protect mtDNA from UVC lesions, an important contribution given assumptions about TFAM providing protection.

Weaknesses:

(1) The authors show a decrease in mtDNA levels and increased lysosomal colocalization but do not define the pathway responsible for degradation. Distinguishing between replication dilution, mitophagy, or targeted degradation would strengthen the interpretation and justifies future experiments.

(2) The manuscript briefly notes enrichment of TFAM at certain regions of the mitochondrial genome but provides little interpretation of why these regions are favored. Discussion of whether high-occupancy sites correspond to regulatory or structural elements would add valuable context.

(3) The authors provide a discrepancy between the anisotropy and binding array results. The reason for this is not clear and one wonders if an orthogonal approach for the binding experiments would elucidate this difference (minor point).

Assessment of conclusions:

The manuscript successfully meets its primary goal of testing whether TFAM protects mtDNA from UVC damage and the impact this has on the mtDNA. While their data points to an intriguing model that TFAM acts as a sensor of damaged mtDNA, the validation of this model requires further investigation to make the model more convincing. This is likely warranted for a followup study. Also the biological impact of this compaction, such as altering transcription levels is not clear in this study.

Impact and utility of the methods:

This work advances our understanding of how mitochondria manage UVC genome damage and proposes a structural mechanism for damage "sensing" independent of canonical repair. The methodology, including the custom TFAM DNA chip, will be broadly useful to the scientific community.

Context: The study supports a model in which mitochondrial genome integrity is maintained not only by repair factors, but also by selective sequestration or removal of damaged genomes. The demonstration that TFAM compaction correlates with damage rather than protection reframes an interesting role in mtDNA quality control.

Comments on revised version:

The authors addressed all concerns during the revision.

Reviewer #2 (Public review):

Summary:

King et al. present several sets of experiments aimed to address potential impact of UV irradiation on human mitochondrial DNA as well as possible role of mitochondrial TFAM protein in handling UV irradiated mitochondrial genomes. The carefully worded conclusion derived from the results of experiments performed with human HeLa cells, in vitro small plasmid DNA, with PCR-generated human mitochondrial DNA and with UV-irradiated small oligonucleotides is presented in the title of the manuscript: "UV irradiation alters TFAM binding to mitochondrial DNA". Authors also interpret results of somewhat unconnected experimental approaches to speculate that "TFAM as a potential DNA damage sensing protein in that it promotes UVC-dependent conformational changes in the [mitochondrial] nucleoids, making them more compact. They further propose that such a proposed compaction might trigger removal of UV-damaged mitochondrial genomes as well as facilitates replication of undamaged mitochondrial genomes.

Strengths:

(1) Authors presented convincing evidence that a very high dose (1500 J/m2) of UVC applied to oligonucleotides covering the entire mitochondrial DNA genome alleviates sequence specificity of TFAM binding (Figure 3). This high dose was sufficient to cause UV-lesions in a large fraction of individual oligonucleotides. The method has been developed in the lab of one of the corresponding authors (ref. 74) and is technically well refined. This result can be published as is or in combination with other data.

(2) Manuscript also presents AFM evidence (Figure 4) that TFAM, which was long known to facilitate compaction of mitochondrial genome (Alam et al., 2003; PMID 12626705 and follow up citations), causes in vitro compaction of a small pUC19 plasmid and that approximately 3 UVC lesions per plasmid molecule results in slight albeit detectable increase in TFAM compaction of the plasmid.

Both results are discussed in line of a possible extrapolation to in vivo phenomena. The revised version of the discussion includes a clear statement that no in vivo support was provided within the set of experiments presented in the manuscript.

Weaknesses:

The experiments presented on Figures 3 and 4 may support the speculation that TFAM can carry protective role of eliminating mitochondrial genomes with bulky lesions by way of excessive compaction and removal damaged genomes from the in vivo pool, however extensive additional studies that would go well beyond the experiments described in this paper are needed to fill the gap between this set of results and the proposed explanations.

Reviewer #3 (Public review):

Summary

The study is grounded in the observation that mitochondrial DNA (mtDNA) shows some resistance to mutagenesis under genotoxic stress. The manuscript focuses on the effects of UVC-induced DNA damage on TFAM-DNA binding in vitro and in cells. The authors demonstrate increased TFAM-DNA compaction following UVC irradiation in vitro, as assessed by high-throughput protein-DNA binding assays and atomic force microscopy (AFM). The authors did not observe a similar trend in fluorescence polarization assays and attributed the difference in the extent of TFAM oligomerization as a potential reason. In cells, the authors found that UVC exposure increased mRNA levels of TFAM, POLG, and POLRMT without altering mitochondrial membrane potential. Overexpressing TFAM in cells or varying TFAM concentration in reconstituted nucleoids did not alter the accumulation or disappearance of mtDNA damage. Based on their data, the authors proposed a plausible model: following UVC-induced DNA damage, TFAM facilitates nucleoid compaction, which may signal damage in the mitochondrial genome. The proposed model may inspire future follow-up studies to further study the role of TFAM in sensing UVC-induced damage.

Comments on revised version:

The authors have addressed the reviewer's concerns.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

The authors investigate how UVC-induced DNA damage alters the interaction between the mitochondrial transcription factor TFAM and mtDNA. Using live-cell imaging, qPCR, atomic force microscopy (AFM), fluorescence anisotropy, and high-throughput DNA-chip assays, they show that UVC irradiation reduces TFAM sequence specificity and increases mtDNA compaction without protecting mtDNA from lesion formation. From these findings, the authors suggest that TFAM acts as a "sensor" of damage rather than a protective or repair-promoting factor.

Strengths:

(1) The focus on UVC damage offers a clean system to study mtDNA damage sensing independently of more commonly studied repair pathways, such as oxidative DNA damage. The impact of UVC damage is not well understood in the mitochondria, and this study fills that gap in knowledge.

(2) In particular, the custom mitochondrial genome DNA chip provides high-resolution mapping of TFAM binding and reveals a global loss of sequence specificity following UVC exposure.

(3) The combination of in vitro TFAM DNA biophysical approaches, combined with cellular responses (gene expression, mtDNA turnover), provides a coherent multi-scale view.

(4) The authors demonstrate that TFAM-induced compaction does not protect mtDNA from UVC lesions, an important contribution given assumptions about TFAM providing protection.

Weaknesses:

(1) The authors show a decrease in mtDNA levels and increased lysosomal colocalization but do not define the pathway responsible for degradation. Distinguishing between replication dilution, mitophagy, or targeted degradation would strengthen the interpretation

We thank the reviewer for their careful reading of our manuscript and thoughtful suggestions. We agree that distinguishing between replication dilution, mitophagy, and/or targeted degradation would strengthen our understanding of how UV-induced DNA damage is handled in the mitochondria. Currently we are undertaking experiments to tease this apart, but consider the scope of those experiments to be beyond this manuscript and expect to publish them in a subsequent paper rather than this one. We added text explicitly stating that these possibilities are not distinguished by our results in pages 8-9 in the Discussion under the subsection ‘Mitochondria respond to UVC-induced mtDNA damage in the absence of apparent mitochondrial dysfunction’.

(2) The sudden induction of mtDNA replication genes and transcription at 24 h suggests that intermediate timepoints (e.g., 12 hours) could clarify the kinetics of the response and avoid the impression that the sampling coincidentally captured the peak.

We agree and have added additional timepoints of 12 hours and 18 hours post exposure. We have updated Figure 2 to include the new data and have added text on page 4 to include these results.

(3) The authors report no loss of mitochondrial membrane potential, but this single measure is limited. Complementary assays such as Seahorse analysis, ATP quantification, or reactive oxygen species measurement could more fully assess functional integrity.

We focused on membrane potential because loss of membrane potential is such a well-understood of mechanism for triggering mitophagy, but agree that these additional measurements are useful. We have added experiments to assess ATP levels, but did not see changes; we have added this data to Figure 2. We have also added text highlighting that we previously assessed mtROS following the same levels of UV exposure and observed no changes (in the results section on page 5 and in the discussion section on page 9). Given that we observe no changes in membrane potential or ATP, we have opted to not move forward with Seahorse analysis for the purposes of this paper.

(4) The manuscript briefly notes enrichment of TFAM at certain regions of the mitochondrial genome but provides little interpretation of why these regions are favored. Discussion of whether high-occupancy sites correspond to regulatory or structural elements would add valuable context.

We agree a discussion of these findings provides context and insight into where the field is currently in understanding TFAM sequence specificity. We have updated text in the discussion (pages 9-10) to include our thoughts on the drivers of TFAM sequence specificity with regard to the discrepancy with the anisotropy data and the lack of overlap with regulatory/structural elements.

(5) It remains unclear whether the altered DNA topology promotes TFAM compaction or vice versa. Addressing this directionality, perhaps by including UVC-only controls for plasmid conformation, would help disentangle these effects if UVC is causing compaction alone.

We have added an additional control making this comparison and updated the text on page 7 in the results section. UVC by itself (without TFAM being present) does not alter the plasmid compaction; see new supplemental Figure S16.

(6) The authors provide a discrepancy between the anisotropy and binding array results. The reason for this is not clear, and one wonders if an orthogonal approach for the binding experiments would elucidate this difference (minor point).

The discrepancy between anisotropy and the binding array results is certainly unusual and contrary to previous studies that have used these arrays. In addition to the anisotropy experiments, we selected a ‘high occupancy’ and ‘low occupancy’ sequence from the binding array and performed oligomerization experiments using atomic force microscopy, which allowed us to detect small changes in cooperativity (see supplemental Figure S15). We previously only discussed this briefly in the results section on page 6, but we have now updated the discussion section (pages 9-10) to highlight this finding and put forth ideas for the field as to why we think this might be the case. While we do see that the binding array data aligns with oligomerization and cooperativity of TFAM, we still do not know what it is about these sequences that would drive such differences in TFAM binding, but we speculate that it could have something to do with flexibility of the DNA sequences.

Assessment of conclusions:

The manuscript successfully meets its primary goal of testing whether TFAM protects mtDNA from UVC damage and the impact this has on the mtDNA. While their data points to an intriguing model that TFAM acts as a sensor of damaged mtDNA, the validation of this model requires further investigation to make the model more convincing. This is likely warranted for a follow-up study. Also, the biological impact of this compaction, such as altering transcription levels, is not clear in this study.

We have updated wording in the Abstract, Introduction, and elsewhere in the text (as detailed in other portions of our response) to make as explicit and clear as possible which results are supported by the in vitro versus in vivo data, and which parts are conclusions supported by the data versus hypothesized models to be tested in future work.

Impact and utility of the methods:

This work advances our understanding of how mitochondria manage UVC genome damage and proposes a structural mechanism for damage "sensing" independent of canonical repair. The methodology, including the custom TFAM DNA chip, will be broadly useful to the scientific community.

Context:

The study supports a model in which mitochondrial genome integrity is maintained not only by repair factors, but also by selective sequestration or removal of damaged genomes. The demonstration that TFAM compaction correlates with damage rather than protection reframes an interesting role in mtDNA quality control.

Reviewer #2 (Public review):

Summary:

King et al. present several sets of experiments aimed to address the potential impact of UV irradiation on human mitochondrial DNA as well as the possible role of mitochondrial TFAM protein in handling UV-irradiated mitochondrial genomes. The carefully worded conclusion derived from the results of experiments performed with human HeLa cells, in vitro small plasmid DNA, with PCR-generated human mitochondrial DNA, and with UV-irradiated small oligonucleotides is presented in the title of the manuscript: "UV irradiation alters TFAM binding to mitochondrial DNA". The authors also interpret results of somewhat unconnected experimental approaches to speculate that "TFAM is a potential DNA damage sensing protein in that it promotes UVC-dependent conformational changes in the [mitochondrial] nucleoids, making them more compact." They further propose that such a proposed compaction triggers the removal of UV-damaged mitochondrial genomes as well as facilitates replication of undamaged mitochondrial genomes.

Strengths:

(1) The authors presented convincing evidence that a very high dose (1500 J/m2) of UVC applied to oligonucleotides covering the entire mitochondrial DNA genome alleviates sequence specificity of TFAM binding (Figure 3). This high dose was sufficient to cause UV lesions in a large fraction of individual oligonucleotides. The method was developed in the lab of one of the corresponding authors (reference 74) and is technically well-refined. This result can be published as is or in combination with other data.

(2) The manuscript also presents AFM evidence (Figure 4) that TFAM, which was long known to facilitate compaction of the mitochondrial genome (Alam et al., 2003; PMID 12626705 and follow-up citations), causes in vitro compaction of a small pUC19 plasmid and that approximately 3 UVC lesions per plasmid molecule result in a slight, albeit detectable, increase in TFAM compaction of the plasmid. Both results can be discussed in line with a possible extrapolation to in vivo phenomena, but such a discussion should include a clear statement that no in vivo support was provided within the set of experiments presented in the manuscript.

We thank this reviewer for their careful reading and interpretation of the manuscript. We agree that discussion of in vivo implications and extrapolations need clear statements indicating where there is not currently in vivo support. We have updated the text throughout the paper to include this.

Weaknesses:

Besides the experiments presented in Figures 3 and 4, other results do not either support or contradict the speculation that TFAM can play a protective role, eliminating mitochondrial genomes with bulky lesions by way of excessive compaction and removing damaged genomes from the in vivo pool.

To specify these weaknesses:

(1) Figure 1 - presents evidence that UVC causes a reduction in the number of mitochondrial spots in cells. The role of TFAM is not assessed.

We are working to understand the role of TFAM in vivo following UV irradiation, but believe that work should be included in follow up studies rather than this publication.

(2) Figure 2 - presents evidence that UVC causes lesions in mitochondrial genomes in vivo, detectable by qPCR. No direct assessment of TFAM roles in damage repair or mitochondrial DNA turnover is assessed despite the statements in the title of Figure 2 or in associated text. Approximately 2-fold change in gene expression of TFAM and of the three other genes does not provide any reasonable support to suggestion about increased mitochondrial DNA turnover over multiple explanations on related to mitochondrial DNA maintenance.

We agree and have updated the title of Figure 2 to better reflect the findings outlined in the figure as well as the text.

The new title is, “UVC causes mtDNA damage that decreases over time and is associated with upregulation of mtDNA replication genes, in the absence of apparent mitochondrial dysfunction.”

We agree that there are numerous mechanistic hypotheses that could explain the decrease in mtDNA damage over time. In Figure 1, we show that there is an overall decrease in mtDNA spots, and an increase in mtDNA-lysosome colocalization, suggestive of mtDNA degradation, which could serve to remove damaged genomes. One possibility is that TFAM is playing a role in the damage removal (but not repair per cell as these lesions are not repaired). Another is changes in mtDNA turnover via increasing the replication machinery in order the synthesize non-damaged mtDNA molecules to dilute out damage. These and other possibilities are not mutually exclusive. We have added text (pages 8-9) to make explicit that additional work will be required to distinguish these possibilities. We note that we have also added an additional experiment showing that TFAM knockdown affects mtDNA damage at baseline, as well as after UVC exposure (Figure 5J).

(3) Figure 5. Shows that TFAM does not protect either mitochondrial nucleoids formed in vitro or mitochondrial DNA in vivo from UVC lesions as well as has no effect on in vivo repair of UV lesions.

We agree that Figure 5 shows that TFAM does not protect DNA from UVC-induced lesions, and that a roughly 2-fold increase in TFAM protein does not alter damage reduction over time. We have added new data showing that in vivo, knockdown of TFAM results in an increase in baseline (control conditions) mtDNA damage, and also alters the rate of decrease of mtDNA damage over time after UVC (Figure 5J).

(4) Figure 6: Based on the above analysis, the model of the role of TFAM in sensing mtDNA damage and elimination of damaged genomes in vivo appears unsupported.

We have updated the legend for Figure 6 in which we outline our hypothesized role of TFAM in sensing mtDNA damage to ensure that readers know this has yet to be fully tested in vivo. We have also updated the Figure legend title from “proposed model” to “hypothesized model,” and changed the wording in the conclusion section (page 11) to highlight more clearly that this is a working model.

(5) Additional concern about Figure 3 and relevant discussion: It is not clear if more uniform TFAM binding to UV irradiated oligonucleotides with varying sequence as compared to non-irradiated oligonucleotides can be explained by just overall reduced binding eliminating sequence specific peaks.

We do not believe this is the case given the similar K_D values for the sequences tested. In our hands and in other publications (reviewed in PMID: 34440420), it has been well established that TFAM binds damaged DNA very well—essentially just as well as nondamaged DNA or better.

Additionally, a reduction in overall binding on these DNA arrays tends to make sequence specific peaks more apparent. We ran our experiments at both 30 nM and 300 nM TFAM specifically to be able to assess this question. The 300 nM data can be found in supplemental Figure S7. In this figure, we notice that the peaks appear more uniform at the high concentration (comparing Figure 3A to Figure S7A). That is presumably because there is so much more binding happening across the array that the peaks associated with the strongest binders become less pronounced. For the sake of brevity, we have not added this reasoning to the text, but are willing to do so if the Reviewers and Editor feel that it is important to include.

Reviewer #3 (Public review):

Summary:

The study is grounded in the observations that mitochondrial DNA (mtDNA) exhibits a degree of resistance to mutagenesis under genotoxic stress. The manuscript focuses on the effects of UVC-induced DNA damage on TFAM-DNA binding in vitro and in cells. The authors demonstrate increased TFAM-DNA compaction following UVC irradiation in vitro based on high-throughput protein-DNA binding and atomic force microscopy (AFM) experiments. They did not observe a similar trend in fluorescence polarization assays. In cells, the authors found that UVC exposure upregulated TFAM, POLG, and POLRMT mRNA levels without affecting the mitochondrial membrane potential. Overexpressing TFAM in cells or varying TFAM concentration in reconstituted nucleoids did not alter the accumulation or disappearance of mtDNA damage. Based on their data, the authors proposed a plausible model that, following UVC-induced DNA damage, TFAM facilitates nucleoid compaction, which may serve to signal damage in the mitochondrial genome.

Strengths:

The presented data are solid, technically rigorous, and consistent with established literature findings. The experiments are well-executed, providing reliable evidence on the change of TFAM-DNA interactions following UVC irradiation. The proposed model may inspire future follow-up studies to further study the role of TFAM in sensing UVC-induced damage.

Weaknesses:

The manuscript could be further improved by refining specific interpretations and ensuring terminology aligns precisely with the data presented.

(1) In line 322, the claim of increased "nucleoid compaction" in cells should be removed, as there is a lack of direct cellular evidence. Given that non-DNA-bound TFAM is subject to protease digestion, it is uncertain to what extent the overexpressed TFAM actually integrates into and compacts mitochondrial nucleoids in the absence of supporting immunofluorescence data.

We would like to thank this reviewer for their comments and suggestions. We feel these specific language changes have strengthened the interpretability of the text. The TFAM overexpression cells used in this experiment were given to us by Isaac et al., who demonstrated that when TFAM was overexpressed in this specific cell line, the nucleoids were indeed more compact, measured by Fiber-seq (Isaac et al., 2024; PMID: 38347148). We have removed the claim “increased compaction” from the section title, Figure 5 legend title, and from line 322 (now on page 8), and have also added an additional sentence to ensure the reader knows these cells have been shown to have presumed increased compaction by other groups.

(2) In lines 405 and 406, the authors should avoid equating TFAM overexpression with compaction in the cellular context unless the compaction is directly visualized or measured.

We have updated the text to ensure that it is clear that this was tested by other groups. We also changed the wording to “inaccessible (presumably compacted) nucleoids.” While we did not demonstrate altered compaction in our study, we think that based on the results from Isaac et al., it is likely that there was increased compaction. In addition, some readers might not have the context to make the connection between compaction and accessibility, so eliminating all reference to compaction could obscure the point.

(3) In lines 304 and 305 (and several other places throughout the manuscript), the authors use the term "removal rates". A "removal rate" requires a direct comparison of accumulated lesion levels over a time course under different conditions. Given the complexity of UV-induced DNA damage-which involves both damage formation and potential removal via multiple pathways-a more accurate term that reflects the net result of these opposing processes is "accumulated DNA damage levels." This terminology better reflects the final state measured and avoids implying a single, active 'removal' pathway without sufficient kinetic data.

We agree and have updated the language throughout the text as well as the results heading for this section.

(4) In line 357, the authors refer to the decrease in the total DNA damage level as "The removal of damaged mtDNA". The decrease may be simply due to the turnover and resynthesis of non-damaged mtDNA molecules. The term "removal" may mislead the casual reader into interpreting the effect as an active repair/removal process.

We agree and have restructured this sentence for clarity. We do believe there is some removal happening, given the increase in mtDNA colocalization in lysosomes alongside decrease of mtDNA spots in our live cell imaging. We have written it to reflect the inclusion of removal and resynthesis of nondamaged mtDNA molecules (see pages 8-9).

Recommendations for the authors:

Reviewing Editor Comments:

The reviewers appreciate the quality of the presented data but concur that they do not support the primary claims in the title and abstract. The reviewers also realize that in vivo evidence for the model would require extensive new experimentation that goes beyond a reasonable revision. The recommendation is to change the title and significantly revise text, figure titles and legends for transparency, and conclusions within results and discussion sections.

We thank the editor and all the reviewers for their feedback. We have added additional experiments, updated text throughout the entire paper to ensure our claims are supported, and revised our title. We feel that the changes we have made have indeed made the paper stronger, more transparent, and that the evidence put forth in this paper provides support for all claims made.

Reviewer #1 (Recommendations for the authors):

(1) Clarify mitochondrial response kinetics by adding an intermediate (e.g., 12 hrs) recovery timepoint for transcriptional analysis to resolve when TFAM and replication genes are induced.

We have added additional timepoints of 12 and 18 hours following exposure in Figure 2. These results strengthen our finding that the nuclear transcriptional program supporting mtDNA replication appears to be activated prior to the nuclear transcriptional program supporting mitochondrial transcription, in that POLG and TFAM come up before POLRMT and ND1.

(2) Strengthen functional readouts by assessing additional parameters of mitochondrial function to substantiate the claim that UVC does not impair mitochondrial performance.

We have referenced our previously-published data on mtROS and added a measurement of ATP following UVC exposure in Figure 2.

(3) Consider exploring whether mtDNA degradation occurs via mitophagy, nucleoid-phagy, or another pathway-potentially by using inhibitors or markers of these processes.

While we agree that this is an important follow up question and are currently working on experiments to address this, those experiments are outside the scope of this manuscript.

(4) Provide additional details for the high occupancy TFAM sites. Provide brief annotation or discussion of genomic regions showing strong TFAM binding under non-irradiated conditions that are lost during UVC treatment. This would be helpful to the field as a whole.

We have updated our discussion section to include this.

(5) Include or discuss a control using UVC irradiated pUC19 without TFAM to confirm that observed compaction categories are TFAM dependent rather than an UVC induced DNA distortion.

We have added in a supplemental figure (Figure S16) containing comparison of area analysis of control pUC19 and UV-irradiated pUC19 and we have added associated text in the results section of the paper.

(6) It would be interesting to explore the link between compaction to transcriptional output. In the TFAM overexpression model, the authors could measure expression of mtDNA encoded transcripts (e.g., ND1, COX1) to connect increased compaction with altered mitochondrial transcription.

While we agree that understanding how the compactional status alters mitochondrial transcription is worthwhile, we believe this is beyond the scope of this paper. Furthermore, this connection has previously been shown by Bruser et al., 2021 (PMID: 34818548) who showed that more compact nucleoids are not undergoing active transcription. It will be interesting to see in future work if mtDNA damage drives changes in both compaction as well as transcriptional activity.

(7) Clarify quantitative presentation in figure 2F to explicitly note whether the observed increase in fluorescence intensity was statistically insignificant and confirm that the assay sensitivity is sufficient to detect small potential changes. As presented it is not clear if there is a change.

We have changed the presentation of Figure 2F. There is a slight increase in membrane potential at the 24-hour time point and we have made that clear in the text as well. We included FCCP as a (standard) positive control, for which we can detect the associated decrease in membrane potential for. While it is always possible that a very small decrease occurred that we were unable to detect, we note that none of the six UVC-exposed groups that we tested even trended towards a decrease in MMP, making it less likely that there was an effect that we simply lacked the power or sensitivity to detect.

(8) It would be interesting if the authors can comment on whether TFAM induced compaction after UVC might shield mtDNA from other, repairable lesions (e.g., oxidative or alkylation damage), offering a broader context for this mechanism beyond just UVC.

In theory, we believe this is possible. It will also be interesting to see if the increased compaction following UVC also protects or shields the mtDNA from other enzymatic processes, such as repair proteins that may be searching for repairable lesions such as oxidative or alkylation damage. In this case, it seems as though the increased compaction would prevent the repair from happening at genomes harboring damage.

In this study we show with our in vitro nucleoids that the increased compaction does not protect against UVC, but this is likely because UVC does not need physical access to the DNA in order to damage it, as the wavelengths of UVC (centered in this case at 254nm) are readily absorbed by proteins and thus can go right through the proteins. Currently, we know that increased compaction by TFAM makes the DNA inaccessible to the enzymes required to methylate DNA used in Fiber-seq (PMID: 38347148), but we do not know if the compaction is tight enough to prevent ROS or alkylating agents from damaging the DNA. We have updated text in the discussion on page 10 to highlight some of these ideas.

Reviewer #2 (Recommendations for the authors):

Please, go over all display items and text and clarify details that can help readers to understand important specifics of the experiments. Examples are provided below:

(1) Abstract and Introduction - indicate species and cell line

We have updated the text to include this information.

(2) Table 1 "TFAM KD measurements"- title and footnotes are entirely cryptic. Please, clarify the experimental design, question(s) addressed and conclusions drawn from data.

We have updated the title of Table 1 to "Binding of TFAM to array sequences, measured using fluorescence anisotropy,” and clarified the footnotes to make sure it is clear which sequences were selected for AFM oligomerization experiments.

(3) Figure 3 and Material and Methods - specify UVC dose.

We have added this information to both the figure legend and the methods section.

(4) Figure 4 - specify UVC dose.

We have added this information to the figure legend.

(5) Figure 5. Panel B indicate which band is TFAM and which is HA-tag; Indicate clearly which panel is showing in vivo or in vitro results.

We have updated the figure to label the untagged TFAM and HA-tagged TFAM and changed the panel titles to specify if they are in vivo results.

eLife Assessment

This valuable study provides convincing evidence that MgdE, a conserved mycobacterial nucleomodulin, downregulates inflammatory gene transcription by interacting with the histone methyltransferase COMPASS complex and altering histone H3 lysine methylation. This work will interest microbiologists as well as cell and cancer biologists.

Reviewer #1 (Public review):

Summary:

This fundamental study identifies a new mechanism that involves a mycobacterial nucleomodulin manipulation of the host histone methyltransferase COMPASS complex to promote infection. Although other intracellular pathogens are known to manipulate histone methylation, this is the first report demonstrating specific targeting the COMPASS complex by a pathogen. The rigorous experimental design using of state-of-the art bioinformatic analysis, protein modeling, molecular and cellular interaction and functional approaches, culminating with in vivo infection modeling provide convincing, unequivocal evidence that supports the authors claims. This work will be of particular interest to cellular microbiologist working on microbial virulence mechanisms and effectors, specifically nucleomodulins, and cell/cancer biologists that examine COMPASS dysfunction in cancer biology.

Strengths:

(1) The strengths of this study include the rigorous and comprehensive experimental design that involved numerous state-of-the-art approaches to identify potential nucleomodulins, define molecular nucleomodulin-host interactions, cellular nucleomodulin localization, intracellular survival, and inflammatory gene transcriptional responses, and confirmation of the inflammatory and infection phenotype in a small animal model.

(2) The use of bioinformatic, cellular and in vivo modeling that are consistent and support the overall conclusions is a strengthen of the study. In addition, the rigorous experimental design and data analysis including the supplemental data provided, further strengthens the evidence supporting the conclusions.

Comments on revisions:

The authors have previously addressed the weaknesses that were identified by this reviewer by providing rational explanation and specific references that support the findings and conclusions.

Reviewer #2 (Public review):

Summary:

The manuscript by Chen et al addresses an important aspect of pathogenesis for mycobacterial pathogens, seeking to understand how bacterial effector proteins disrupt the host immune response. To address this question the authors sought to identify bacterial effectors from M. tuberculosis (Mtb) that localize to the host nucleus and disrupt host gene expression as a means of impairing host immune function. Their revised manuscript has strengthened their observations by performing additional experiments with BCG strains expressing tagged MgdE.

Strengths:

The researchers conducted a rigorous bioinformatic analysis to identify secreted effectors containing mammalian nuclear localization signal (NLS) sequences, which formed the basis of quantitative microscopy analysis to identify bacterial proteins that had nuclear targeting within human cells. The study used two complementary methods to detect protein-protein interaction: yeast two-hybrid assays and reciprocal immunoprecipitation (IP). The combined use of these techniques provides strong evidence of interactions between MgdE and SET1 components and suggests the interactions are in fact direct. The authors also carried out rigorous analysis of changes in gene expression in macrophages infected with MgdE mutant BCG. They found strong and consistent effects on key cytokines such as IL6 and CSF1/2, suggesting that nuclear-localized MgdE does in fact alter gene expression during infection of macrophages. The revised manuscript contains additional biochemical analyses of BCG strains expressing tagged MgdE that further supports their microscopy findings.

Reviewer #3 (Public review):

In this study, Chen L et al. systematically analyzed the mycobacterial nucleomodulins and identified MgdE as a key nucleomodulin in pathogenesis. They found that MgdE enters into host cell nucleus through two nuclear localization signals, KRIR108-111 and RLRRPR300-305, and then interacts with COMPASS complex subunits ASH2L and WDR5 to suppress H3K4 methylation-mediated transcription of pro-inflammatory cytokines, thereby promoting mycobacterial survival.

Comments on revisions:

The authors have previously adequately addressed previous concerns through additional experimentation. The revised data robustly support the main conclusions, demonstrating that MgdE engages the host COMPASS complex to suppress H3K4 methylation, thereby repressing pro-inflammatory gene expression and promoting mycobacterial survival. This work represents a significant conceptual advance.

Author response:

The following is the authors’ response to the previous reviews

Reviewer #2 (Recommendations for the authors):

Major:

Over-interpretation of data. There are a few instances of this:

The authors claim "Our work shows that MgdE interacts with both WDR5 and ASH2L and inhibits the methyltransferase activity of the COMPASS complex" (Line 318). However, they provide no biochemical analysis of methyltransferase activity to support this claim. While they cite Figure 4A-C and Figure 5, these data simply show (slightly) decreased cellular levels of H3K4Me. There are multiple ways H3K4Me could decrease including blocking recruitment of COMPASS to promoters or the enzymatic activity of MgdE itself.

The data itself related to H3K4Me changes (Figure 5D) is difficult to interpret in light of the controls they now provide. Examining the blot itself there seems to be a massive increase in H3K4Me in control cells expressing GFP that is not reflected in the quantification that shows only a ~2x increase in GFP-expressing cells. In addition， there is very little decrease in H3K4Me in the MgdE-expressing cells relative to controls or site-mutant (no change apparent visually and ~10% change per their quantification). However, the authors interpret this as," revealed that cells expressing WT MgdE exhibited lower levels of H3K4me3". In both these cases I would recommend the authors consider modifying their interpretation of the data.

We thank the reviewer for the comment.

(1) We have now revised this interpretation in the manuscript as follows:

Lines 311-312: “Our work shows that MgdE interacts with both WDR5 and ASH2L, leading to a decrease in H3K4me3 levels.”

(2) Figure 5D presents the results of three independent biological replicates. The bar graph shows the average signal intensity of H3K4me3 normalized to the corresponding loading controls. Accordingly, we have revised the analysis and description of the experimental results.

Lines 214-217: “Immunoblot analysis of nuclear extracts showed that cells expressing WT MgdE had ~25% lower H3K4me3 levels than EGFP-expressing cells and ~40% lower levels than those expressing the D244A/H47A mutant (Figure 5D).”

Minor

What is "CK"? Please clarify (Figure 2F).

We thank the reviewer for the comment. In this context, "CK" refers to the uninfected control group, which serves as the negative control in the experiment. We have revised the label in Figure 2F.

How many times was the BCG mouse experiment performed? This should be indicated in the figure legend? (Figure 7A).

We thank the reviewer for the comment. The BCG mouse experiment was performed once, and we have added this information to the figure legend of Figure 7A.

It is unclear why the secreted protein (after signal peptide removal) migrates at the same size as the full-length protein (Figure S2).

We thank the reviewer for the comment. The precursors of secreted proteins after translation in the cytoplasm will be translated into the periplasm immediately. Therefore, MgdE or Ag85B obtained from the whole-cell lysate (Figure S2A) mostly have had the signal peptides removed. This is also validated in the case of Rv0455c secretion by Mtb (Zhang et al., Nature Communications, 2022). This explains why MgdE (or Ag85B) proteins from whole-cell lysates or from supernatants show same size in SDS-PAGE gels.

It is still unclear why the transcripts with very little fold-change in expression (in grey) have the most significant p-values for being different (Figure 6).

We thank the reviewer for the comment. The p-value calculation takes into account not only the magnitude of expression change but also the consistency of expression levels within each group and the number of biological replicates. When the variation among replicates is minimal, even a small difference in group means can result in a statistically significant p-value. In our RNA-seq analysis, we used DESeq2 with three biological replicates per group. DESeq2 employs a model based on the negative binomial distribution and accounts for multiple factors, including the mean expression level, within-group variance (dispersion), sample size, and normalization accuracy. As a result, it is common to observe that genes with small variability and strong consistency between replicates may show significant p-values even with modest fold changes. Conversely, genes with larger fold changes but greater variability might not reach statistical significance.

Reference

Zhang L, Kent JE, Whitaker M, Young DC, Herrmann D, Aleshin AE, Ko YH, Cingolani G, Saad JS, Moody DB, Marassi FM, Ehrt S, Niederweis M (2022) A periplasmic cinched protein is required for siderophore secretion and virulence of Mycobacterium tuberculosis Nat Commun 13(1):2255.

This paragraph serves as the "Kairos" of the essay—addressing why this ad matters right now. Holmes uses the broader cultural anxiety surrounding AI as evidence to explain why the public reaction was so visceral. She connects the physical "crushing" in the video to the metaphorical "assault" on creative labor. By weaving in this context, she elevates the essay from a simple review of a commercial to a timely commentary on the "exploitation of labor" and the "devaluation of the individual."

Holmes performs a brilliant rhetorical pivot here by redefining the "value" of the objects. Apple’s ad views a piano as a "tool" that can be digitized and compressed. Holmes argues that a piano is an "experience" and a "memory." By shifting the definition from utility to humanity, she exposes the "folly" of Apple's logic. This serves as the emotional anchor for her entire piece, moving the argument from a tech critique to a philosophical one about what art actually is.

Holmes uses a "pro-con" or "concession-refutation" structure here. By stating what the ad is "meant to communicate", portability, efficiency, creativity in one device, she demonstrates an objective understanding of Apple’s marketing goals. This makes her subsequent "But..." in the next paragraph it is much more powerful. She isn't just complaining; she is arguing that Apple’s rhetorical intent failed because it ignored the cultural resonance of the objects being destroyed.

eLife Assessment

In their valuable study, Beaudet, Berger and Hendricks provide a mechanistic link between disease-associated tau hyperphosphorylation, loss of cooperative tau envelope formation on microtubules, and dysregulation of axonal transport prior to aggregation. Using complementary in vitro reconstitution and human iPSC-derived neuronal assays with phosphodeficient and phosphomimetic tau constructs targeting 14 disease-relevant sites, the authors convincingly show that phosphorylation state alters tau organization on microtubules and differentially impacts kinesin- and lysosome-based transport. The evidence is solid and well aligned with the conclusions, yet the work could be further strengthened by incorporating additional controls and motor-specific assays to refine the mechanistic depth.

Reviewer #1 (Public review):

Summary:

This work by Beaudet and colleagues aims at exploring the effect of phosphorylation on the formation of tau envelopes and consequently on axonal transport, both in vitro on reconstituted microtubules and in human excitatory neurons derived from IPSCs.

The authors found that a relatively widely used construct in which 14 serine or threonine residues, often hyperphosphorylated in Alzheimer's disease, are mutated to alanines (phosphodeficient), increases the density of tau envelopes compared to wildtype tau, whereas a phosphomimetic (same residues mutated to glutamic acid) reduces envelope density both in vitro and in human excitatory neurons derived from IPSCs.

By analysing the trafficking of different kinesins (KIF1a and KIF5C), they observed different effects of tau phosphorylation status on the movement of these two motors.

They then analyse transport of lysosomes by employing live imaging of lysotracker in human excitatory neurons derived from IPSCs transfected with wildtype, phosphodeficient or phosphomimetic tau, observing that phosphodeficient tau seems to reduce transport of lysosomes while phosphomimetic increases transport compared to wildtype tau.

Strengths:

(1) The work aims to study a novel and underexplored topic in the tau field, tau envelopes, and investigate their relevance to Alzheimer's disease pathology.

(2) Experiments are well conducted and of high quality.

Weaknesses:

Relying only on in vitro reconstituted microtubules and human neurons derived from IPSCs leaves some doubts about the relevance of these results for Alzheimer's disease, considering the embryonic state of IPSCs-derived neurons.

Reviewer #2 (Public review):

This manuscript examines how disease-associated hyperphosphorylation disrupts tau's role as a cooperative microtubule-binding regulator of intracellular transport. Using in vitro reconstitution assays and live-cell imaging in iPSC-derived neurons, the authors employ phosphomutant tau constructs (E14 to mimic hyperphosphorylation, AP to prevent phosphorylation) at 14 disease-associated residues to isolate phosphorylation effects independent of expression system-dependent PTM heterogeneity. The results show that hyperphosphorylated tau fails to form cooperative envelope-like structures on microtubules, instead binding diffusely and dissociating rapidly. In contrast, wild-type and phospho-resistant tau form cohesive envelopes that regulate motor protein access. At the single-molecule level, hyperphosphorylation reduces KIF5C inhibition while maintaining or enhancing KIF1A inhibition through altered processivity and detachment rates. In live neurons, hyperphosphorylated tau phenocopies tau knockout conditions, weakening tau-mediated inhibition of lysosome transport and increasing processive motility. The authors quantify tau binding using Gaussian mixture model-based image analysis and measure tau kinetics via FRAP, demonstrating that hyperphosphorylation-induced loss of cooperative binding correlates with dysregulated organelle transport. These findings establish a mechanism by which phosphorylation-driven disruption of tau's gatekeeper function on microtubules compromises axonal transport prior to aggregation in tauopathies. The paper provides interesting new knowledge for the field, but there are outstanding concerns that could be further addressed by the authors to strengthen and clarify the current manuscript:

(1) Lack of Phosphatase-Treated Control and Explicit WT Phosphorylation Quantification

Wild-type tau expressed in insect and mammalian cells is known to be phosphorylated by endogenous kinases (eg, GSK3, CDK5, MARK). The manuscript acknowledges this in the Discussion but provides no phosphatase-treated lysate control or quantification of endogenous phosphorylation on WT tau via phospho-specific Western blots. This leaves ambiguity about whether observed differences between WT and E14 reflect purely the introduced mutations or confounding baseline differences in phosphostate content.

(2) Limited Normalization of Motor Effects to Measured Tau Lattice Occupancy

Although kinesin trajectories are classified inside vs. outside tau envelopes (inherently normalizing to local tau density), motor parameters are not systematically reported as functions of tau fluorescence intensity across all constructs. Co-purifying MAPs or microtubule-modifying enzymes in cell lysates is not quantified or excluded, leaving residual uncertainty about tau-specificity of observed motor inhibition. This should be at least acknowledged in the results section.

(3) Insufficient Citation of Prior Neuronal Tau Envelope Evidence

In the Introduction, the authors state, "it was an open question if tau forms envelopes in neurons," but this understates existing evidence. Tan et al. (2019) report tau neuronal staining consistent with envelope formation, while Siahaan et al. (2021) provide more direct evidence in non-neuronal cells. The framing should acknowledge and integrate these prior findings.

(4) Unclear Wording on Expression System-Dependent Phosphorylation

The sentence "The phosphostate of tau is strongly dependent on the expression system" requires rewording. It is ambiguous whether this refers to the final phosphostate achieved after expression or the inherent phosphorylating capacity of each system. Clearer language would strengthen the methodological justification.

(5) Insufficient Quantification of Motor and Lysosome Transport Effect Magnitudes in Results Section

The data on molecular motor motility and lysosome transport are densely described. The magnitude of effects (fold-changes, percentage differences) should be explicitly stated in the Results section when first presenting findings to orient readers to biological significance. For example, effect magnitudes for lysosome run lengths, velocities, and directional bias should be quantified in text, not left to figure inspection.

(6) Incomplete Discussion of Projection Domain Necessity for Envelope Formation

The Discussion states the projection domain is "a critical regulator of both tau-tau and tau-microtubule interactions," but does not engage with prior domain dissection work. Tan et al. (2019) found that the entire projection domain is not necessary for envelope formation in vitro. The authors should discuss which projection domain regions are specifically regulated by phosphorylation vs. required for cooperativity, providing a more nuanced interpretation than implied by their current framing.

Author response:

We thank the reviewers for their thoughtful and constructive feedback. Addressing these points will strengthen the manuscript and improve its clarity.

A primary concern involved the justification for using COS7 cell lysates in reconstitution approaches and iPSC-derived neuronal model systems as models for AD. We will clarify the language throughout the manuscript to more explicitly state the study’s goals, emphasize that these systems were selected as robust, well-controlled platforms to test the mechanisms through which tau hyperphosphorylation affects microtubule interactions and tau’s role in regulating intracellular transport, and the limitations of in vitro and iPSC models.

Reviewers also raised the possibility that background phosphorylation could contribute to the effects observed in the pseudo-phosphorylation model. We cite two recent preprints that provide insight into this question through quantitatively assessing tau phosphorylation across expression systems. In the revised manuscript, we will elaborate on how their assessment of tau phosphorylation fits within the scope of our approach and clarify how our experimental controls effectively minimize uncertainty related to background phosphorylation.

Another point concerned the potential influence of other microtubule-associated proteins in lysates and the impact of tau lattice occupancy on motility outcomes. To further strengthen this aspect, we will include additional analyses correlating tau intensity along microtubules with kinesin intensity and motility behavior, and we will more clearly explain how the AP and WT controls provide confidence in the robustness of the system.

Detailed responses to each reviewer comment are provided below point by point. The planned revisions, which include clearer language, stronger justification of the experimental approaches, and additional supporting analyses, will substantially improve the clarity, rationale, and overall impact of the study.

Public Reviews:

Reviewer #1 (Public review):

Summary:

This work by Beaudet and colleagues aims at exploring the effect of phosphorylation on the formation of tau envelopes and consequently on axonal transport, both in vitro on reconstituted microtubules and in human excitatory neurons derived from IPSCs.

The authors found that a relatively widely used construct in which 14 serine or threonine residues, often hyperphosphorylated in Alzheimer's disease, are mutated to alanines (phosphodeficient), increases the density of tau envelopes compared to wildtype tau, whereas a phosphomimetic (same residues mutated to glutamic acid) reduces envelope density both in vitro and in human excitatory neurons derived from IPSCs.

By analysing the trafficking of different kinesins (KIF1a and KIF5C), they observed different effects of tau phosphorylation status on the movement of these two motors.

They then analyse transport of lysosomes by employing live imaging of lysotracker in human excitatory neurons derived from IPSCs transfected with wildtype, phosphodeficient or phosphomimetic tau, observing that phosphodeficient tau seems to reduce transport of lysosomes while phosphomimetic increases transport compared to wildtype tau.

Strengths:

(1) The work aims to study a novel and underexplored topic in the tau field, tau envelopes, and investigate their relevance to Alzheimer's disease pathology.

(2) Experiments are well conducted and of high quality.

Weaknesses:

Relying only on in vitro reconstituted microtubules and human neurons derived from IPSCs leaves some doubts about the relevance of these results for Alzheimer's disease, considering the embryonic state of IPSCs-derived neurons.

We agree with the reviewer that iPSC-derived neurons represent an immature state compared with the neurons affected in Alzheimer’s disease. However, iPSC-derived neurons, together with in vitro reconstitution, provide insight into (1) whether tau hyperphosphorylation influences its association with microtubules and its ability to form envelope-like structures thought to regulate transport, (2) how tau hyperphosphorylation affects the motility of kinesin motors that are strongly inhibited by tau, and (3) how transport of endogenous degradative organelles such as lysosomes are impacted by tau hyperphosphorylation. We hope that our studies will help to inform future studies examining how tau-related dysfunction evolves in more mature neurons and contributes to the more severe pathological effects observed at later disease stages.

We will include a paragraph in the Discussion section addressing the limitations of this study to better contextualize our findings within the broader effort to understand tauopathies and Alzheimer’s disease.

Reviewer #2 (Public review):

This manuscript examines how disease-associated hyperphosphorylation disrupts tau's role as a cooperative microtubule-binding regulator of intracellular transport. Using in vitro reconstitution assays and live-cell imaging in iPSC-derived neurons, the authors employ phosphomutant tau constructs (E14 to mimic hyperphosphorylation, AP to prevent phosphorylation) at 14 disease-associated residues to isolate phosphorylation effects independent of expression system-dependent PTM heterogeneity. The results show that hyperphosphorylated tau fails to form cooperative envelope-like structures on microtubules, instead binding diffusely and dissociating rapidly. In contrast, wild-type and phospho-resistant tau form cohesive envelopes that regulate motor protein access. At the single-molecule level, hyperphosphorylation reduces KIF5C inhibition while maintaining or enhancing KIF1A inhibition through altered processivity and detachment rates. In live neurons, hyperphosphorylated tau phenocopies tau knockout conditions, weakening tau-mediated inhibition of lysosome transport and increasing processive motility. The authors quantify tau binding using Gaussian mixture model-based image analysis and measure tau kinetics via FRAP, demonstrating that hyperphosphorylation-induced loss of cooperative binding correlates with dysregulated organelle transport. These findings establish a mechanism by which phosphorylation-driven disruption of tau's gatekeeper function on microtubules compromises axonal transport prior to aggregation in tauopathies. The paper provides interesting new knowledge for the field, but there are outstanding concerns that could be further addressed by the authors to strengthen and clarify the current manuscript:

(1) Lack of Phosphatase-Treated Control and Explicit WT Phosphorylation Quantification

Wild-type tau expressed in insect and mammalian cells is known to be phosphorylated by endogenous kinases (eg, GSK3, CDK5, MARK). The manuscript acknowledges this in the Discussion but provides no phosphatase-treated lysate control or quantification of endogenous phosphorylation on WT tau via phospho-specific Western blots. This leaves ambiguity about whether observed differences between WT and E14 reflect purely the introduced mutations or confounding baseline differences in phosphostate content.

Tau contains ~85 putative phosphorylation sites and is modified by several kinases in cells. Studies by Siahaan et al. (2024) and Fan et al. (2025) provide detailed insight into tau phosphorylation, its role in protecting the microtubule lattice from severing enzymes, and the implications of phosphorylation patterns for aggregate formation. Specifically, Fan et al. (2025) show that HEK-expressed tau is phosphorylated by endogenous kinases at 58 residues, with most phospho-occupancy levels below 15%, indicating substantial heterogeneity among individual tau molecules. In the revised manuscript, we will (1) provide justification for the use of the pseudo-phosphorylation model system as an approach to limit heterogeneity among tau molecules, (2) clarify the importance of the WT and AP controls, (3) discuss that E14, WT, and AP tau likely exhibit similar degrees of background phospho-heterogeneity, with WT tau likely exhibiting some overlap between background phosphorylation and the 14 AD-associated sites examined, and (4) expand the discussion to emphasize that although background phosphorylation is present, our results do not suggest that it contributes significantly to the observations reported in this study.

(2) Limited Normalization of Motor Effects to Measured Tau Lattice Occupancy

Although kinesin trajectories are classified inside vs. outside tau envelopes (inherently normalizing to local tau density), motor parameters are not systematically reported as functions of tau fluorescence intensity across all constructs. Co-purifying MAPs or microtubule-modifying enzymes in cell lysates is not quantified or excluded, leaving residual uncertainty about tau-specificity of observed motor inhibition. This should be at least acknowledged in the results section.

The reviewer raises a valid point. It is challenging to compare conditions where the occupancy of tau on microtubules is similar across conditions, as phosphorylation strongly effects the interaction between tau and microtubules. We will quantify and report tau intensity in single-molecule motility assays. On the second point, while effects from other MAPs or motor proteins could potentially affect kinesin motility, we would expect that these effects would be similar for all tau phosphomutant constructs, such that the effect of tau phospho-states on kinesin motility can be assessed.

(3) Insufficient Citation of Prior Neuronal Tau Envelope Evidence

In the Introduction, the authors state, "it was an open question if tau forms envelopes in neurons," but this understates existing evidence. Tan et al. (2019) report tau neuronal staining consistent with envelope formation, while Siahaan et al. (2021) provide more direct evidence in non-neuronal cells. The framing should acknowledge and integrate these prior findings.

We agree with the reviewer that evidence from several studies using reconstitution systems, fixed neurons, and live cultured cells provides evidence of tau envelope formation in neurons. Specifically, tau envelopes have been observed along taxol-stabilized or GMPCPP-capped GDP microtubules in vitro (e.g., Dixit et al., 2008; Monroy et al., 2018; Tan et al., 2019; Siahaan et al., 2019), in 4% PFA-fixed and Triton X-100–extracted DIV7 mouse hippocampal neurons (Tan et al., 2019), and in live, non-neuronal U-2 OS cells following taxol treatment (Siahaan et al., 2022) or elevated pH (Siahaan et al., 2024). However, to our knowledge, our study is the first to demonstrate tau envelope formation in live neuronal cells under normal cell culture conditions. We will revise this sentence in the manuscript to more precisely position our findings within the context of prior studies.

(4) Unclear Wording on Expression System-Dependent Phosphorylation

The sentence "The phosphostate of tau is strongly dependent on the expression system" requires rewording. It is ambiguous whether this refers to the final phosphostate achieved after expression or the inherent phosphorylating capacity of each system. Clearer language would strengthen the methodological justification.

We agree that the wording here is ambiguous and requires clarification. In the revised manuscript, we will clarify that tau phosphorylation depends on the expression system used; bacterial systems lack the capacity for many post-translational modifications compared with insect and mammalian systems. We will also emphasize that in insect and mammalian expression systems, tau phosphorylation occurs heterogeneously, as demonstrated in previous studies by Siahaan et al. (2024) and Fan et al. (2025).

(5) Insufficient Quantification of Motor and Lysosome Transport Effect Magnitudes in Results Section

The data on molecular motor motility and lysosome transport are densely described. The magnitude of effects (fold-changes, percentage differences) should be explicitly stated in the Results section when first presenting findings to orient readers to biological significance. For example, effect magnitudes for lysosome run lengths, velocities, and directional bias should be quantified in text, not left to figure inspection.

Our initial justification for omitting quantitative data from the results text was to improve readability; however, in doing so, we may have reduced the accessibility and clarity regarding the significance of the findings. In the revised manuscript, we will incorporate the relevant quantifications and statistical significance for the motility data in the text.

(6) Incomplete Discussion of Projection Domain Necessity for Envelope Formation

The Discussion states the projection domain is "a critical regulator of both tau-tau and tau-microtubule interactions," but does not engage with prior domain dissection work. Tan et al. (2019) found that the entire projection domain is not necessary for envelope formation in vitro. The authors should discuss which projection domain regions are specifically regulated by phosphorylation vs. required for cooperativity, providing a more nuanced interpretation than implied by their current framing.

We agree with the reviewer. Tan et al. (2019) demonstrated that the proline-rich region (residues 198–244) within the projection domain of full-length 2N4R tau is the minimal region required to maintain tau’s ability to form envelopes along microtubules. We will incorporate this work on the dissection of the projection domain and discuss how the phosphorylation sites examined in our study are primarily located within this region. Together, these data highlight the proline-rich region as a potential major regulator of tau–tau cooperativity.

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Switching from Church Community Builder to ChMeetings is straightforward. ChMeetings handles data migration at no cost for churches on any paid plan.

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Yes

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ChMeetings is designed to scale with churches of all sizes, including large congregations and multi-campus organizations.

Is ChMeetings a good fit for large churches switching from CCB?

Cancellation Terms

ChMeetings can be cancelled at any time with no notice period and no cancellation fees. The process requires just a few steps within the platform settings.

Church Community Builder requires a 90-day cancellation notice. Churches considering CCB should factor this term into their evaluation, particularly if they anticipate needing flexibility in the future.

ChMeetings provides free data migration for all churches moving to any paid plan. The ChMeetings team handles the transfer of member records, giving history, groups, and attendance data, accounting data, and most churches report being fully operational within a few days of starting the migration process.

Church Community Builder's migration process typically involves a structured onboarding engagement. For churches moving away from CCB, ChMeetings' team has experience handling data exports from CCB specifically, which simplifies the transition.

Data Migration

ChMeetings offers a 30-day free trial that can be activated instantly without a credit card. The trial includes access to demo data, so administrators can explore the platform with realistic content rather than starting from a blank system. Video overviews are available for major features within the trial environment.

Church Community Builder requires prospective customers to contact their team before accessing a trial. CCB offers a guided product tour, which provides a structured overview of the platform but does not allow independent, hands-on exploration of the system.

Both approaches have merit, a guided tour ensures administrators see the most relevant features for their church size, while a self-serve trial allows teams to evaluate the platform on their own schedule and terms.

ChMeetings publishes all its pricing publicly, including per-member plan costs, add-on fees, and payment processing rates. Churches can review the full cost structure independently before making any contact with the ChMeetings team.

Church Community Builder does not publish its pricing. Churches interested in CCB need to contact their sales team to receive a custom quote. This makes side-by-side cost comparison more time-consuming for administrators evaluating multiple platforms simultaneously.

Beyond features and pricing, there are several practical factors that church administrators commonly raise when evaluating church management software, particularly around how easy it is to get started, what switching looks like, and what level of commitment is required before and after signing up. Below are four areas where ChMeetings and Church Community Builder differ in ways that may be relevant to your decision.

CCB does not publish its pricing publicly, churches need to contact the sales team for a custom quote. Third-party sources report starting costs between $145 and $179 per month, scaling with congregation size. Additionally, CCB requires a 90-day cancellation notice, and PushPay's giving platform carries its own separate fee structure. Churches evaluating CCB should request a full cost breakdown, including giving fees and implementation costs before making a commitment.

• Enterprise feature depth: CCB provides advanced tools for facility management, sacrament tracking, process automation, and group management that are particularly valuable for large, complex church organizations
• PushPay integration: For churches already using PushPay for giving, CCB's native integration eliminates the need for separate systems and provides consolidated reporting across giving and administration
• Scalability: CCB is designed to handle the operational complexity of large and multi-campus churches, with tools that grow with organizational needs

One consideration worth noting: ChMeetings' pricing is based on the number of active people stored in the system, which means costs will increase as your congregation grows. Churches should review the pricing tiers carefully to anticipate future costs as they scale.

• Transparent pricing: All plans and costs are publicly listed on the ChMeetings pricing page — no sales calls required to understand what you will pay
• No giving fees: ChMeetings does not charge any fees on donations collected through the platform. Churches pay only the standard rates charged by their chosen payment processor — Stripe or PayPal
• No long-term contracts: Churches can cancel anytime without notice periods or penalties
• Free data migration: Churches moving to any paid ChMeetings plan receive free data migration assistance from the ChMeetings team
• Unlimited users and admins: ChMeetings does not limit the number of staff or volunteers who can access the platform — any active person in the system can be made a user or admin at no extra cost

ChMeetings is built around transparent, publicly available pricing that scales with congregation size. Paid plans start at $12 per month for very small churches, and the platform offers a free plan for congregations managing up to 50 people.

Value for Money: ChMeetings vs Church Community Builder

Evaluating value for money in church management software goes beyond the monthly subscription cost — it includes giving fees, implementation costs, contract flexibility, and what features are included at each price tier. ChMeetings and Church Community Builder take fundamentally different approaches to pricing, and understanding those differences will help you assess the true cost of each platform for your specific church size and needs.

Church Community Builder offers a broad and mature feature set that has proven valuable to many mid-to-large churches over the years. However, its pricing structure and contract terms introduce financial considerations that church administrators should evaluate carefully.

Churches with dedicated administrative staff and structured onboarding processes tend to get the most out of Church Community Builder's feature depth. The platform's capabilities are best utilized when there is sufficient internal capacity to configure, maintain, and train users on an ongoing basis.

• Church administrators have access to powerful tools for managing calendars, forms, process queues, and member data — though these require meaningful setup time and ongoing management
• Pastoral and ministry leaders can manage groups, follow-ups, and engagement effectively once the system is configured
• Volunteers and event planners may require guidance from administrators to navigate more complex features like check-in setup and scheduling
• Church members can access self-service features through the mobile app, though member adoption varies across congregations

Church Community Builder is a comprehensive platform with a wide feature set that gives administrators significant control over workflows, processes, and data management. This depth is genuinely valuable for large churches with dedicated administrative staff who can invest time in configuration and training.

Churches that need deep customization or highly complex workflow automation may find ChMeetings' streamlined approach somewhat limiting compared to more feature-heavy platforms. However, for most churches, its balance of functionality and simplicity represents a significant advantage.

• Church administrators can manage members, events, giving, and communication from a unified dashboard that requires minimal configuration to get started
• Pastoral and ministry leaders can access reports, track attendance, and communicate with groups without relying on technical staff
• Volunteers and event organizers can navigate scheduling and event management independently
• Church members can register for events, give online, submit forms, and update their profiles from any device

ChMeetings prioritizes simplicity and accessibility across all user roles. Its interface is designed to minimize the need for training, making it particularly well suited for churches where administrative capacity is limited or where volunteers and members need to self-serve independently.

Title: Ease of Use: ChMeetings vs Church Community Builder

Description: Ease of use means different things depending on who in your church is using the software. For churches with dedicated IT staff and complex administrative needs, a powerful but complex system may be acceptable. For churches where staff, volunteers, and members have varying technical comfort levels, simplicity becomes a priority. On Capterra, ChMeetings holds a 4.9/5 overall rating , with ease of use frequently cited as a strength. Church Community Builder holds a 3.9/5 ease of use rating on the same platform, below the 4.5 category average for church management software.

Tuta useful overview of age verification efforts globally.

67