Le CSS est né en 1996, à retenir. Le HTML en 1991. Donc, avant, au début de l'internet, on ne séparait pas le fond et la forme.

En bon français, Feuilles de style en cascade. On parle de "Feuilles de style" (pourquoi on parle de feuilles de style en informatique: c'est un héritage de l'imprimerie).

Une feuille de style (conc style sheet en anglais) est un document qui contient l'ensemble des règles de mise en forme d'une page web.

On dit en cascade, car les règles de style se suivent les unes les autres, On dit en cascade car les règles de style se suivent les unes les autres, si plusieurs règles ciblent le même élément, c'est la plus précise ou la dernière qui l'emporte

à retenir. Le Web date de 1991. ça peut tomber dans un quizz!

à bien retenir. En français, on dirait langage de marquage hypertexte. L'hypertexte, c'est quand on clique sur un mot d'une page, pour atterrir ailleurs (une autre page, un autre endroit de la page), c'est le lien entre les pages web.

On parle de balise HTML (les mots-clefs entre chevron, par exemple , ça c'est une balise ouvrante. Une balise fermante utilise une barre oblique. et entre les 2 le contenu de la balise.

Retenez bien qu'on parle de balises en HTML, mais en revanche de propriétés en CSS;

CSS et HTML sont les 2 langages utilisés pour faire des pages web, HTML en gros sert à dire quel contenu, et CSS a dire comment on veut l'afficher (rouge, gras, centré, etc).

La version qu'on utilise de CSS et le CSS3 et pour HTML le HTML5. Voilà les choses basiques à connaitre.

Une autre façon de faire un mémo, est de bien utiliser le surlignage avec Hypothesis. Vous pouvez créer un groupe privé, ça mettra de côté toutes les parties que vous soulignez pour y revenir, avec vos annotations qui servent à apprendre.

Très important de bien comprendre comment on navigue dans GitHub.

C'est incroyable comme les gens ne savent pas apprendre, ils surlignent tout, sauf ce qu'il est important de retenir. Ici, une info importante.

Vous n'êtes pas obligés d'installer Visual Studio Code. Il y a beaucoup d'autres logiciels. VSCodium est mieux, car sans les mouchards Microsoft; Voici une version sans installation (portable, à juste mettre sur une clef USB): https://portapps.io/app/vscodium-portable/, il y a aussi Notepad++; qu'on peut aussi mettre sur une clef USB,; etc...

In Macau, we have Macanese--an Asian Creole language that is a combination of Chinese, Hindi, Dutch and African.

I read Edward Franklin Frazier, a social worker in the US who had a similar racial experience and spoke French and English.

- [Amy X. Zhang - Wikum](https://homes.cs.washington.edu/~axz/wikum.html)
    - [GitHub - amyxzhang/wikum: tool for collectively summarizing large discussions](https://github.com/amyxzhang/wikum)

A description of the type of things Activate does w AI agents. Ref'd in [[Paolo’s Weblog It’s still time for free AI love]]

Description of how Activate keep their prompts, skills, databases, memory architecture under their own control and within their own environment.

Moving means wiring up another model or models, but the rest is kept as is.

[[Paolo Valdemarin p]] on avoiding lock-in in a single specific AI silo. Bc what is state of the art will shift every few months.

• Detriots auto industry was a defining pull factor for black migrants
• to get elected detriot had some serious political barriers
• By 1970 the voting age percejt was almost 50, this made blacks BOP
• Detriots municipal election was at large and nonpartisan so people were not under the banners of parties and they had to win aross the city
• Per the agrument at the begging of the book, this is going to inhibit black politicans ability to get elected as well as the voting power of the population
• Black population is stepping mainly into this compettion between ford and the labor unions on the political level
• Oldest and largest chapters of the NAACP
• As in other cities, Black churches play a major role in all spheres of life, but politival and civil rights mobilization in general
• The ford motor company has a lot of say in who gets elected (maybe will chnage as their base of employees chnages) and before the major influx of the black population they are supporting discrimatory candidates
• 1920 election starts the immunization towards civil rights (or just anti racits) policy
• All or nothing kind of politics, because the black vote is in BOP, KKK will always mobolix=ze agaisntb and other candidate will always mobolize for
• Ford complicated the balncing of politica; preference and economic wellbeing
• In all of these examples the impratnt part is that the balk vote is non-trival, something to be feared or garnered, and this si before the true boom
• Explicit racism is orertty jarring for detriot
• Race becomes a wedge issue as the population and strength of BVAP increases
• "chnage his stance on racial issies once it became clear that Blak Detroiters we important"
• 1961 is the first victory for the Black community in determining the kayor, might go on to become the status quo
• In detriot, even in a system that was set up to limit their political voice (indeirectly), they could have been the BOP in 19/22 elections, with its least influential, still 50% of the time
• Politicians became more responsive to the opinions of Black politicians as the proportio of the oting age population increased
• Detriot had serious structrual barriers for balck people holding office
• It would take black politicians some time to get going but eventually they would have some very meanigful political representation
• black politicians were primarily concerned with anti-discrimination laws (jobs and housing)
• While not limited to civil reform, racial policy was importsnt at the begginbg as a means of reprsentation
• they were human, not monolithic and cared about a lot of things
• migrant legislators were particuarly concerned with the migrant concersn (hand up) which extended to non-black migrants as well
• locally, the political system made it hard for balck officials to be elected based on the support of blak homogoneus communiiues, which I remind you were fucking required by detriot whites
• outcome of the sytem was the exlusion of the black population from municipal eledted office
• detriot lagged in national representation (congress)
• while the population grew, conservative candidates won by convicing whites to vote reacially conservative
• the system in detriot rwally lagged the potential influence until there was a mass bloc

This sentence uses vague words that do not clearly explain the main idea. Replacing general words like “people” or “life” with more specific details helps the reader better understand the topic. Being precise makes the writing clearer and stronger.

This sentence uses vague words that do not clearly explain the main idea. Replacing general words like “people” or “life” with more specific details helps the reader better understand the topic. Being precise makes the writing clearer and stronger.

I agree that a good research paper should be focused and detailed. When a topic is clear and specific, it helps the reader understand the information better. It also allows the writer to go deeper into the subject instead of just giving basic information. This makes the research paper stronger and more meaningful.

Franklin's autobiography begins by addressing his estranged son.

so it drives the way you act and think

combining power of an element

greater in number, strength, or influence

gather or collect

statistical tendency of >=2 varis to predictably change together

cause to exist, develop

this depends on culture and how individuals perceive happiness

Even though they objected this act they still ended up feeding and housing the British troops in their own homes.

The Spanish wanted the land they arrived on to be all theirs, and they wanted the Indians to act a their slaves even though they had the land first. While the British simply wanted the Indians to move elsewhere they could have their own area.

When The English settlement disappeared the Indians took over. Although the English disappeared it's possible they went to live with the Indians so they could survive.

Instead of coming up with their own principles they used German ones and came up with a new name.

Explication du résultat introduite par "probablement" : absence de risque à diffuser de fausses informations dans ce genre de contexte et motivation des participants qui ont fait l'objet d'entretiens dans lesquels on retrouve l'absence d'intérêt pour la véracité de l'information et l'envie de rire. Les participants cités ont conscience qu'il s'agit de fausses informations.

Si l'on croise cette explication avec les résultats relatifs aux fausses informations d'intérêt public diffusés auprès d'une connaissance avec qui l'on partage les mêmes idées : la première explication, l'absence de risque tient la route (on est toujours dans un espace privé) ; la seconde en revanche me pose question. L'envie de rire avec ou de provoquer quelqu'un dont on n'est pas proche est un comportement plutôt rare. Je pose l'hypothèse que ce résultat (fausse information d'intérêt public + idéologique et non affective) permet de mesurer l'adhésion à la fausse information. Et ce résultat, selon le graphique, n'est pas négligeable.

Résultats de l'expérimentation introduits par le conditionnel "il semblerait" (nous sommes dans une recherche préliminaire d'où la prudence de l'auteure dans ses conclusions): les participants n'échangent pas le même type d'information dans tous les contextes conversationnels. Dit autrement: chaque contexte conversationnel va permettre l'échange de certains types d'informations / chaque type d'information va s'échanger dans un type de contexte conversationnel particulier.

Suite de l'explication de l'expérimentation : les participants pouvent s'échanger des informations réparties dans 4 catégories différentes.

Hypothèse de l'auteure introduite par "il est possible" : certains espaces conversationnelles caractérisés par la désinhibition (l'absence de contrôle) et la familiarité (une forme d'intimité) contribuent à la propagation des fake news.

Conclusion sous forme de prédiction : arrivée des fausses informations jusque dans les médias traditionnels en quête de clics.

En 2026, cette conclusion s'est vérifiée. A une nuance près: loin d'être contraints par leur modèle économique à favoriser les informations qui font du clic faisant ainsi involontairement le jeu des producteurs de fake news, certains médias traditionnels (TV, presse écrite, radio) prônent volontairement la promotion de ces fausses informations en accord avec un agenda politique et idéologique. Ils diffusent des informations fausses auxquels ils adhèrent (et leurs lecteurs aussi ?).

Voir cette vaste enquête du journal Le Monde : https://www.lemonde.fr/les-decodeurs/article/2025/11/16/la-methode-bollore-comment-l-industriel-breton-s-est-cree-un-empire-mediatique-en-vingt-ans_6653611_4355770.html

Et le livre de Marie Bénilde : Le péril Bolloré.

Enchaînement logique qui fait le lien entre les résultats de l'étude et les RS sous forme d'un argument épistémique : les espaces auparavant privés où s'échangent des fausses informations sont, depuis l'arrivée des RS, publics et jouissent d'une forte visibilité.

Enchaînement logique sous forme d'argument épistémique qui fait le lien entre la visibilité des fausses informations sur les RS et leur propagation : exploitation de ces échanges par des acteurs qui y ont un intérêt politique et/ou financier.

Argument épistémique : RS projettent les espaces conversationnelles privés dans l'espace public et incarnent aussi des espaces publics anonymes (2 conditions expérimentales de l'étude où se partagent le plus les fausses infos sans intérêt public).

Suite de l'explication de l'expérimentation : la consigne donnée aux participants était de choisir dans quels contextes conversationnels ils souhaitaient partager ces différents types d'informations.

VI 1: les contextes conversationnels à 6 modalités.

VI 2 : les informations à 4 modalités.

VD : choix de partager une d'information dans un ou plusieurs contextes conversationnels.

Présentation de l'expérimentation : elle s'appuie sur un dispositif expérimental grâce auquel les participants peuvent s'échanger des informations dans six contextes conversationnels différents.

Hypothèse testée grâce une expérimentation à caractère exploratoire dont les résultats ont été approfondis lors de recherches doctorales (les liens sont vérifiés).

Raison 2 qui reprend l'hypothèse de départ sous la forme d'un enchaînement de questions : les personnes qui échangent des fakes news n'y adhèrent pas toutes indistinctement, elles les partagent pour d'autres raisons.

Raison 1 : le nombre de fake news partagés doit être comparé au nombre total des interactions et exemple à l'appui (les liens sont vérifiés), ce nombre est très faible.

Un chiffre global sur la proportion de fake news échangées par rapport à l'ensemble des informations échangées sur différents RS aurait été plus convaincant mais d'après mes recherches, ce chiffre est difficile à trouver.

Auteur : Manon Berriche, doctorante en sociologie au Medialab de Science Po.

Contexte : The Conversation, media en ligne qui fédère, sous la forme d'une association à but non lucratif, des établissements d'enseignement supérieur et de recherche. Des universitaire et des chercheurs en collaboration avec des journalistes proposent des articles d'analyse de l'actualité.

Thèse défendue par l'auteure dès le titre : les discussions informelles alimentent la diffusion des fake news.

L'auteure choisit de nous présenter plus précisément les résultats relatifs aux informations fausses et sans intérêt public. Elles sont partagées (graphique à l'appui) dans deux contextes spécifiques : auprès d'un ami proche affectivement et idéologiquement et dans un espace public anonyme. Notons que selon le graphique, elles finissent majoritairement dans la poubelle : elles ne sont pas échangées. Ce qui semble accréditer la thèse selon laquelle une majorité d'individus n'y adhèrent pas.

L'auteure ne nous présente pas les résultats pour les informations fausses et d'intérêt public qui diffèrent des précédents : elles sont majoritairement partagées en privé auprès d'un ami proche mais aux idées différentes et auprès d'une connaissance avec qui on partage les mêmes idées. L'intérêt d'une information fausse fait donc varier le contexte conversationnel dans lequel elle est échangée. Pourquoi ?

Argument épistémique causal: deux raisons explicitées dans la suite de l'article permettent de dire que c'est la manière dont les informations sont reçues et analysées par les individus qui importent bien davantage que le nombre de fake news partagées.

Argument épistémique causal introduit par "ainsi" : étant donné les caractéristiques de ces espaces conversationnels, la motivation des individus n'est pas de s'échanger des informations vraies mais elle est à rechercher ailleurs : faire rire, se vanter, énerver son interlocuteur etc.

Of course, people listened to the priest but did not actually apply what he said.

Franklin witnessed a man (likely a pastor or priest) quoting his Almanac while giving advice, which gave him a sense of gratification..

Franklin feels like he has gotten little recognition from other authors, despite being a renowned writer. However, he does make a decent amount of money.

On Wero, which is going live for every iDeal transaction in the Netherlands the coming months. This will def reduce my online card usage.

This is a clear statement of the difference between a normative claim (all members of class n ought to be given equal consideration) and a descriptive claim (all members of class n have the same capacities or characteristics.)

How did they indicate this?

These will be 42 myths with data as on this website, and this is now only to represent a section: https://pudding.cool/2019/10/shelters/

These will be just 10 SVG pictograms per group that fill up depending on the percentage of "believers"

• "The Great Migration Looms large in most African American family histories"
• Six and a half million people participated
• The Great Migration was unprecedented, any voluntary migration up until this point had been small and sercetive
• Black people move north beause it is the most feasible and the idea of staying in the redemption era south is bonkers
• Kansas was the first hint of the great migration
• Great migration occured in two waves, 1916 and 1940, brought on by world wars and the change in agriculture.
• 1915: the opprotunity for agency and industrial work outside of the south entices many migrants
• The great depression puts a pause or just an inhibitor on the Great Miugration before the boom in industry fol,,ing the second workd war strts it up agaisn
• Second wave is 1940s through to the 1960s (five million)
• What was the role of culture? Was there any desire to escape the south as a region more than as an economy?
• Leaving along the east coast meant you stayed along the east coast (usuallyn ending up in NYC)
• Migrants often stayed in a straight line migration because their transportation oopprions were kimited
• Great ,igration is a leaderless moverment, just individuals seeking to improve their lives
• There was almost a chain migration effect, the people in ghe noethn looking to pill others out of the economic and cultutal shitstrom of the south
• It was just a mega personal expierience, it sort of mimics how national migration to the US looks now
• Highly educated and young adults were the most likely groups to leave
• Taste of life outside of the souyth often meant a decrease in the likelgood of returning, this implies some cultural influence
• Men went first, again, mimics modern trends
• Economics first, escaping racism second
• Black people struggled to make a living as sharecroppers and then there was agricultural disaster (push)
• In general the wages and work was better in the inustrail north (pull), WWII expands these opprotunities
• "There were civic, educational, and political benefits of living outside the south"
• there were also moral push and pull factors, a sense of fairness, justice, amnd the way humans deserve to be treated
• "Black Americans wanted to fully participates in American society"
• Black migrants were non-immunized voters, they were not steeped in political beliefs or ytraditions because they had been robbed of them for so long
• The north BVAP skyrocketetd as young people move and then had kids

• "The great migration unlocked Black Americans ability yo participate as full citizens in our democracy... in some instances for the first time"
• northern politiicians interactions with black voters chmaged as the population grew and there was an increase of Black elected officials
• partys responses were positive if they had no ther choice; black population would signifigantly affect the outcome
• highlight the agency of black people in the great migration
• its been studied through almost every angle except politics
• Black voters (when an important block) could seriously chnage the policiies that fficials took up, negative if they wwanted to alienatate the vite but positive to win it
• We are looking at top down change, how the motivations of the politicians chnaged
• secular realignment, parties are constanrtly changing all the time and can arrive at a completely differnt plcae over decades -politicians were mobolizing the black vote for the first time
• black colaitions were able to chnage the policies locally befire nationally (intuitive)
• we're gonna argue that the inlfux of migrants chnaged the place more than the place chnaged the migrants

romantic relationship with the intent of marriage

• Black people needed to escape the south
• That is, black people of all backgrounds
• The book is about the way the great migration changed politics
• For black people, residency was the difference between freedom and slavery, voting and not voting
• A.) Black Americans moved out of the south and into the north in primarily rural areas. B.) The migration chnaged black citizens ability to participtae (locally and nationally) in politics because there were fewer barriers. "New Pool of eleigible voters" C.) White democrats in the north tought that a colaition of black viters would outright win them tight elections, or at least be a powerful bloc. and D.) Democrats both negativelt and positiely cganged thier campaign startegies to win or supress the balck vote they now viewed as imp[ortant.
• demographic chnaged are important to explain party position change
• How do people chnage the politics of a place?
• chapter two is important, one I should skim at least,
• place chaoters read at least the midwest and then read conclusion.

2023

Enquête sur le Milieu Périscolaire et les Établissements Privés : Failles de Sécurité et Défaillances Institutionnelles

Résumé Exécutif

Cette synthèse met en lumière une crise de confiance et de sécurité au sein du système périscolaire et des établissements scolaires en France.

L'enquête révèle que le temps périscolaire — qui peut représenter jusqu'à cinq heures par jour pour 5,5 millions d'élèves — souffre d'un manque criant de surveillance et de données officielles.

Malgré la multiplication des signalements d'agressions sexuelles et de maltraitances, les structures administratives (mairies et Éducation nationale) sont accusées d'inertie, voire d'avoir instauré une forme d'omerta pour protéger l'image des institutions.

Le recrutement précaire, l'absence de suivi statistique des violences au niveau ministériel et les retards dans les enquêtes administratives créent un environnement vulnérable pour les enfants, particulièrement en maternelle.

1. Le Secteur Périscolaire : Un Système sous Haute Tension

Le temps périscolaire concerne 90 % des enfants de maternelle et d'élémentaire.

Bien que ces activités se déroulent au sein des écoles, elles dépendent des municipalités et non de l'Éducation nationale.

Données Clés sur l'Encadrement

• Volume horaire : Jusqu'à 5 heures par jour (accueil du matin, cantine, étude du soir).

• Population concernée : 5,5 millions d'élèves.

• Perception du métier : Qualifié de « sous-métier » ou de « profession poubelle » par certains acteurs, reflétant une précarité qui impacte la qualité du recrutement.

• Financement : L'État finance à 75 % les établissements privés sous contrat, mais les contrôles sur les violences éducatives ou sexuelles y sont jugés insuffisants par des lanceurs d'alerte.

Défaillances de Recrutement

L'enquête souligne des processus d'embauche parfois expéditifs.

À Rezé, un animateur condamné pour agressions sur 12 mineurs avait été recruté à 51 ans sans expérience préalable dans l'enfance, après une carrière dans la grande distribution.

L'entretien d'embauche a été décrit comme s'étant déroulé « assez rapidement ».

2. État des Lieux des Violences et de l'Invisibilité Statistique

Un constat majeur de l'enquête est l'absence totale de données centralisées sur les violences en milieu périscolaire.

• Néant Statistique : Le ministère de la Justice a confirmé ne pas enregistrer de données spécifiques sur les violences commises par des animateurs périscolaires.

• Réalité du terrain : En compilant les articles de la presse régionale sur 10 ans, l'enquête a recensé au moins une centaine d'affaires médiatisées partout en France (Marseille, Moselle, Courbevoie, Haute-Savoie, etc.).

• Typologie des faits :

◦ Agressions sexuelles et viols sur mineurs.   

◦ Maltraitances physiques (étranglements, violences à la cantine).  

◦ Tentatives de corruption de mineurs.

3. Analyse des Failles Institutionnelles : L'Omerta et la Gestion des Signalements

L'enquête pointe du doigt une gestion administrative défaillante qui privilégie souvent la protection de l'institution au détriment de la sécurité des enfants.

Dysfonctionnements Identifiés

| Type de Dysfonctionnement | Description et Conséquences | | --- | --- | | Déplacement des agents | Pratique consistant à déplacer un animateur signalé d'une école à une autre plutôt que de le sanctionner ou de l'écarter. | | Absence de suites administratives | Dans l'affaire du 15e arrondissement de Paris, deux ans après l'ouverture d'une enquête administrative, aucun débriefing n'a été fourni aux familles. | | Ignorance des alertes parentales | Des parents avaient alerté sur des comportements suspects (animateur seul avec un enfant, porte fermée) dès 2019, soit des années avant l'arrestation de l'agresseur présumé. | | Espaces à risques | Malgré un rapport de 2015 recommandant de prohiber les espaces isolés (comme les coins bibliothèque), ces lieux ont continué d'être utilisés sans surveillance adéquate. |

Citations Marquantes sur l'Institution

• « C'était toujours on protège l'institution, on règle ça entre nous mais rien ne sort. »

• « Le sanctuaire qui se brise » : expression utilisée par les parents pour décrire la perte de confiance envers l'école.

• « Vous avez l'impression que tout le monde est complice de cette omerta. »

4. Impact Psychologique et Parole de l'Enfant

Le professeur Thierry Bobet, pédopsychiatre, apporte un éclairage crucial sur la difficulté de recueillir la parole des victimes, particulièrement entre 3 et 6 ans.

Les Obstacles à la Révélation

1. Absence de représentation : Un enfant de maternelle n'a aucune notion de ce qu'est la sexualité adulte. Il utilise des termes comme « quelqu'un m'a embêté ».

2. Confusion de l'autorité : L'animateur représente une extension de l'autorité parentale, ce qui rend la dénonciation paradoxale pour l'enfant.

3. Fragilité de la mémoire : Entre 3 et 6 ans, la mémoire n'est pas mature.

Un souvenir peut être précis pendant six mois puis devenir confus, d'où l'urgence d'une prise en charge rapide.

Signaux d'Alerte Observés par les Parents

• Régressions : Retour des couches, pipi au lit, demande de biberons.

• Troubles du comportement : Crises violentes au moment de partir à l'école, terreurs nocturnes, phobie scolaire.

• Comportements sexualisés : Jeux ou mimiques inadaptés à l'âge de l'enfant (ex: postures « vulgaires » induites par l'adulte).

5. Cas d'Étude : Le Processus de Manipulation

L'enquête détaille des modes opératoires récurrents visant à isoler les enfants et à instaurer un climat de secret.

• Le secret comme outil de contrôle : « Vous ne dites rien à la maîtresse, c'est notre secret. »

• Rituels détournés : Dans une école parisienne, l'animateur utilisait des chansons et des jeux (ex: « la culotte de mon grand-père ») pour amener les enfants à se déshabiller et à subir des attouchements sous couvert d'activité ludique.

• Posture de l'agresseur : Souvent décrit initialement comme un « papi un peu ours » ou quelqu'un de très apprécié qui « adore les enfants », utilisant cette image pour manipuler l'entourage et isoler les victimes.

Conclusion

L'enquête de Cash Investigation démontre que les violences dans le milieu périscolaire ne sont pas des faits divers isolés, mais le résultat de failles structurelles :

• manque de moyens des collectivités,
• absence de contrôle rigoureux de l'État sur le financement des écoles privées et culture du secret au sein des administrations.

L'urgence est à la transparence statistique et à une réforme profonde des protocoles de signalement et d'encadrement pour protéger les publics vulnérables.

État des Lieux du Périscolaire et de l'Enseignement Privé : Enquête sur les Violences et les Défaillances Institutionnelles

Résumé Exécutif

Ce document de synthèse expose les conclusions d'une enquête approfondie sur la sécurité et l'encadrement des enfants au sein du périscolaire public et des établissements privés sous contrat en France.

Points clés identifiés :

• Insécurité structurelle du périscolaire : Le secteur souffre d'un manque de statistiques officielles sur les violences, de recrutements précaires sans vérification de compétences réelles et d'un encadrement souvent en sous-effectif.

• Culture de l'omerta dans le privé : Malgré un financement public à hauteur de 75 %, certains établissements privés privilégient la protection de leur image institutionnelle au détriment du signalement des violences sexuelles ou pédagogiques.

• Échec de la réponse judiciaire : 73 % des plaintes pour violences sexuelles sur mineurs sont classées sans suite, et les délais d'instruction (parfois plusieurs années) nuisent à la fiabilité de la parole de l'enfant.

• Pratiques de "chaises musicales" : Au lieu d'être sanctionnés, certains animateurs signalés pour comportements inappropriés sont simplement déplacés d'une école à une autre.

• Urgence d'une réforme : Les experts préconisent une professionnalisation accrue, une centralisation des signalements et l'adoption de protocoles d'audition spécialisés (type protocole "Niche").

--------------------------------------------------------------------------------

1. Le Secteur Périscolaire Public : Un Système sous Haute Tension

Le temps périscolaire concerne 5,5 millions d'élèves en France. Bien qu'il se déroule dans l'enceinte des écoles, il dépend des mairies et non de l'Éducation nationale.

1.1. Une profession dévalorisée et précaire

Le secteur est décrit par les intervenants comme une « profession poubelle » ou un « sous-métier ».

• Conditions de travail : Temps partiels imposés, plannings morcelés et salaires de misère (entre 600 et 700 € nets par mois).

• Recrutement "à la va-vite" : Pour combler les manques, les mairies embauchent des vacataires sans aucune expérience.

Une journaliste infiltrée a été recrutée en 6 jours après un entretien où seules sa disponibilité et sa « bienveillance » ont été interrogées, sans test de compétences avec les enfants.

1.2. Défaillances d'encadrement et de surveillance

• Sous-effectifs chroniques : La loi impose un animateur pour 14 enfants de moins de 6 ans, mais des taux de 1 pour 23 ou plus sont observés sur le terrain.

• Surveillance passive : L'enquête révèle des animateurs absorbés par leur téléphone portable durant les temps de cantine ou de cour de récréation, enfreignant la charte de l'animateur.

• Violences verbales et physiques : Des scènes de cris systématiques, d'humiliations et d'intimidation (« ferme ta bouche », privation de nourriture) ont été documentées.

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2. Violences Sexuelles : Des Alertes Ignorées aux Sanctions Insuffisantes

En 10 ans, rien qu'à Paris, 128 animateurs ont été suspendus pour suspicion de violences sexuelles.

2.1. Le dysfonctionnement des signalements

Plusieurs cas démontrent que les alertes des parents ne sont pas toujours transmises à la direction :

• Affaire de l'école Baudin (Paris) : Des parents avaient alerté sur des attouchements dès septembre 2024.

L'information n'a pas été remontée, et l'animateur est resté en poste jusqu'à son interpellation en avril 2025 pour agression sur cinq enfants.

• Affaire de l'école Emerio (Paris) : Un animateur de bibliothèque, en poste depuis 20 ans, a été mis en examen. Des parents avaient pourtant signalé des situations suspectes (portes fermées, enfants sur les genoux) dès 2019.

2.2. Le déplacement des agents problématiques

L'enquête confirme une pratique de « mauvaise habitude » : le déplacement d'un animateur signalé pour maltraitance vers une autre école au sein du même arrondissement, au lieu d'un licenciement ou d'une sanction disciplinaire ferme.

| Cas de figure | Mesure constatée | Impact | | --- | --- | --- | | Maltraitance physique (fessée/secouage) | Déplacement dans une autre maternelle | Risque de récidive sur un nouveau public | | Comportements inappropriés | Mutation d'une école maternelle à une école élémentaire | Absence de dossier de suivi centralisé |

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3. L'Enseignement Privé Sous Contrat : Entre Omerta et Autonomie

L'État finance l'enseignement privé à hauteur de 10,9 milliards d'euros (2024), payant l'intégralité des salaires des enseignants.

3.1. La protection de l'image institutionnelle

Dans certains établissements catholiques, comme l'institution Champagnat (Alsace), la priorité semble être de « laver le linge sale en famille ».

• Pressions sur les victimes : Des enregistrements montrent des religieux incitant des victimes d'agressions sexuelles à retirer leur plainte pour ne pas nuire à la réputation de l'école.

• Rétention d'information : Un établissement a attendu 9 mois avant de signaler au rectorat une enseignante ayant une relation sexuelle avec un mineur de 15 ans.

3.2. Le manque de contrôle étatique

Le Secrétariat Général de l'Enseignement Catholique (SGEC) a longtemps freiné l'adoption de l'application « Faits Établissement », souhaitant filtrer les signalements avant qu'ils n'atteignent le ministère.

Ce « ministère bis » limite la visibilité de l'État sur la réalité des violences dans le privé.

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4. Dérives Idéologiques et Maltraitances : Le Cas de l'Institution "L'Espérance"

Cet établissement de Vendée, sous tutelle de la Fraternité Saint-Pierre, illustre les failles extrêmes du contrôle des écoles sous contrat.

• Violences rituelles : Le directeur pratiquait un système de "pactes" où il recevait ou donnait des claques aux élèves devant toute l'école en fonction des résultats scolaires.

• Climat de haine : Des anciens élèves témoignent de propos racistes, homophobes et xénophobes omniprésents (croix gammées sur les murs, surnoms racistes comme "Bamboula" ou "Chang").

• Non-respect des programmes : Des cours d'éducation civique sont refusés car jugés "républicains", remplacés par des enseignements sur la monarchie ou la scolastique médiévale.

• Encadrement défaillant : L'absence de surveillants adultes la nuit, remplacés par des élèves de terminale (« capitaines d'internat »), a favorisé des humiliations (rituel de la mare).

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5. La Réponse de la Justice et de la Psychiatrie

5.1. Le traumatisme de l'enfant et la parole différée

Le professeur Thierry Bobet et le docteur Louis Alvarez soulignent que :

• Un enfant de maternelle n'a aucune représentation de la sexualité adulte ; il ne parlera pas d'agression mais de quelqu'un qui l'a « embêté ».

• Le secret est souvent imposé par l'agresseur par le biais de "jeux" ou de "secrets".

• La mémoire des 3-6 ans est immature : si l'audition n'est pas immédiate, les souvenirs deviennent confus, favorisant les classements sans suite.

5.2. Statistiques et Justice

• Taux de condamnation : Seules 3 % des plaintes pour viol sur mineur aboutissent à une condamnation en France.

• Le protocole "Niche" : Utilisé dans les pays nordiques (taux de poursuite de 60 %), ce protocole d'audition filmé et standardisé est encore trop peu utilisé en France (25 % des cas contre 90 % dans certains pays).

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6. Modèles Inspirants et Pistes de Solution

6.1. L'exemple de la commune de Lemont (Vosges)

La municipalité a fait le choix politique d'un « périscolaire premium » :

• Ratios d'encadrement : 1 animateur pour 10 enfants (mieux que les 1 pour 14 légaux).

• Professionnalisation : Les temps de préparation et de réunion sont rémunérés.

• Stabilité : Contrats allant jusqu'à 33 heures par semaine pour fidéliser le personnel.

6.2. Recommandations des experts

1. Centralisation : Création d'un fichier national des signalements incluant les violences physiques et psychologiques (pas seulement sexuelles).

2. Formation : Rendre obligatoire la formation sur la protection de l'enfance et la Convention internationale des droits de l'enfant pour tout personnel encadrant.

3. Transparence : Soumettre les établissements privés aux mêmes obligations de signalement immédiat (« Faits Établissement ») que le public.

4. Priorité Judiciaire : Créer un "ticket accélérateur" pour que les enquêtes impliquant des mineurs soient traitées en priorité absolue afin de préserver la fiabilité des preuves.

Note de Synthèse : La Violence à l'École et les Stratégies d'Intervention Efficaces

Résumé Exécutif

Cette note de synthèse analyse les propos de Claire Baumont, Docteure en psychopédagogie, sur la violence en milieu scolaire.

L'idée maîtresse est que la perception d'une augmentation généralisée de la violence dans les écoles n'est pas étayée par des données probantes, mais plutôt alimentée par une couverture médiatique alarmiste.

Le monitorage national québécois (2013-2019) n'a pas confirmé cette hausse et a même noté de légères améliorations.

La professeure Baumont insiste sur l'importance de « l'effet établissement » : la nécessité pour chaque école de baser ses interventions sur les faits observés localement, là où le personnel a un pouvoir d'action réel, plutôt que sur des moyennes nationales ou des récits extérieurs.

L'analyse révèle également que les formes d'agression les plus rapportées ne sont pas toujours celles attendues.

Les comportements d'humiliation et les regards méprisants de la part des adultes envers les élèves, ainsi que les agressions entre collègues, se classent parmi les plus fréquents (3e ou 4e position), bien avant la cyberintimidation.

Les stratégies d'intervention les plus efficaces ont évolué, passant d'approches punitives inefficaces à des approches systémiques axées sur le climat scolaire et, plus récemment, sur le développement des compétences socio-émotionnelles des élèves et du personnel.

La clé réside dans le renforcement des relations par des actions quotidiennes et la responsabilisation du personnel scolaire en tant que modèles.

1. L'Expertise de Claire Baumont

L'analyse est fondée sur les perspectives de Claire Baumont, une experte reconnue dans le domaine :

• Formation et expérience : Docteure en psychopédagogie, elle a été psychologue scolaire et clinicienne auprès de jeunes avec d'importants problèmes d'adaptation.

• Carrière académique : Professeure associée au Département d'études sur l'enseignement et l'apprentissage de l'Université Laval.

• Recherche de pointe : Elle a dirigé la Chaire de recherche sur le bien-être et la prévention de la violence à l'école (2012-2023) et le premier monitorage national de la violence dans les écoles québécoises (2013-2019).

• Objectif : Ses recherches visent à améliorer la qualité de vie des élèves et du personnel scolaire.

2. Mythes et Réalités : La Montée de la Violence Scolaire

Un thème central de la discussion est la remise en question de la perception d'une augmentation de la violence dans les écoles.

• Une narration médiatique persistante : La professeure Baumont souligne que les médias rapportent une "montée de la violence" depuis près de 40 ans, souvent en généralisant à partir d'événements ponctuels et en créant un climat d'insécurité.

• Absence de preuves empiriques : Le monitorage national mené entre 2013 et 2019, utilisant des outils standardisés, n'a pas réussi à prouver une augmentation de la violence.

Au contraire, il a révélé de "légères améliorations".

• Situation actuelle : Il n'existe pas de portrait national récent pour confirmer ou infirmer une hausse depuis 2019-2020.

Il est donc crucial de garder un esprit critique face aux discours ambiants.

• La volatilité des données locales : Le suivi de certaines écoles a montré que la situation peut évoluer rapidement.

Un établissement peut voir son taux de violence augmenter en quelques années, tandis qu'un autre peut s'améliorer.

Cela démontre que les moyennes nationales ne sont pas représentatives de la réalité de chaque milieu.

3. Le Concept Clé : L'Effet Établissement

Face à l'incertitude des données nationales et à l'influence des facteurs externes, la professeure Baumont met en avant le concept de « l'effet établissement » (ou « effet école »).

• Définition : Il s'agit de se concentrer sur les composantes et les interventions sur lesquelles le personnel scolaire a un pouvoir d'action direct au sein de son propre établissement.

• Principe d'action : La première étape est d'ajuster les interventions sur la base de ce qui est réellement observé dans l'école, et non sur des perceptions externes.

• Autonomisation : Cette approche permet aux intervenants de se centrer sur des solutions concrètes et de ne pas se laisser démoraliser par des facteurs hors de leur contrôle.

Elle place l'intervenant comme le "premier décideur" de ses actions avec les ressources dont il dispose.

4. Les Dimensions de la Violence Scolaire

La violence en milieu scolaire est un phénomène complexe et multifactoriel, dont les manifestations dépassent les agressions entre élèves.

4.1. Une Problématique Multifactorielle

La violence s'explique par une interaction de facteurs à plusieurs niveaux :

• Globaux : Les conflits mondiaux et les guerres (une personne sur huit sur la planète serait en situation de guerre en décembre 2024) contribuent à un sentiment d'insécurité généralisé.

• Sociétaux : Les différences culturelles et religieuses peuvent être des sources de tension.

• Communautaires : La vie dans le quartier et la situation familiale des élèves influencent leurs comportements à l'école.

• Institutionnels : La formation du personnel scolaire joue un rôle.

Malgré ces multiples facteurs, l'effet établissement demeure le levier d'action le plus pertinent pour les intervenants.

4.2. Les Comportements d'Agression : Au-delà des Élèves

L'analyse des types de violence révèle une réalité souvent sous-estimée : l'impact du comportement des adultes.

• Violence des adultes envers les élèves : Selon des données de 2024, les comportements d'humiliation et les regards méprisants de la part des adultes se classent en 3e ou 4e position des agressions les plus rapportées par les élèves, surtout au secondaire.

Ces actes incluent les cris et les punitions humiliantes.

• Violence entre adultes : Le personnel scolaire rapporte également subir des agressions de la part de collègues.

Les insultes et l'exclusion des réunions se classent aussi en 3e ou 4e position des comportements d'agression subis par les enseignants.

• Un constat surprenant : Ces formes de violence relationnelle et psychologique sont rapportées bien plus fréquemment que la cyberintimidation, qui est souvent perçue comme un problème majeur.

L'impact de ces comportements d'adultes sur le climat scolaire et la qualité de l'enseignement est considérable.

5. Stratégies d'Intervention : Évolution et Bonnes Pratiques

Les approches pour prévenir et gérer la violence ont évolué au cours des 50 dernières années.

| Étape d'Évolution | Approche Principale | Limites et Constats | | --- | --- | --- | | Approches initiales | Programmes ciblés sur les agresseurs, basés sur la punition. | Inefficaces. "On s'est rendu compte que les punitions ça la prenait pas aux enfants de bons comportements." | | Développement | Approches globales et systémiques axées sur l'amélioration du climat scolaire. | Plus efficaces, mais peuvent être complétées. | | Approches récentes | Focalisation sur le bien-être des élèves, puis sur celui des élèves ET du personnel scolaire. | Agir sur les sources du mal-être pour prévenir la violence. | | Approche actuelle | Développement des compétences socio-émotionnelles pour tous (élèves et personnel). | Apprendre l'autorégulation, l'expression des désaccords et le savoir-être. Le personnel adulte agit comme un modèle essentiel. |

Le modèle actuel met l'accent sur le rôle crucial des adultes.

La relation qu'ils établissent avec les jeunes, basée sur leurs propres compétences socio-émotionnelles, est un facteur déterminant pour un climat scolaire positif.

6. Recommandations Finales pour une Action Efficace

Pour intervenir de manière constructive, la professeure Baumont propose une série de principes directeurs :

1. Baser les interventions sur des faits observés localement : Se concentrer sur les dynamiques propres à son établissement pour un maximum d'impact (« effet établissement »).

2. Impliquer les élèves et le personnel : Faire participer l'ensemble de la communauté scolaire aux décisions favorise le sentiment d'appartenance, l'engagement, l'entraide et la collaboration.

3. Agir avec les ressources disponibles : Plutôt que d'attendre des décisions ou des ressources gouvernementales, il est essentiel d'agir proactivement avec les moyens à disposition.

"Je suis la première personne qui peut décider de ce que je fais avec ce que j'ai."

4. Privilégier la fréquence à l'intensité : Le plus important n'est pas de réaliser de grandes activités ponctuelles, mais de poser de petits gestes significatifs au quotidien.

Il faut "savoir-faire souvent" pour renforcer durablement les relations entre adultes et élèves.

یادآوری با تأخیر

یادآوری با تأخیر

یادآوری با تأخیر

امروز چه تاریخی است؟

سیالی کلامی (حرف «پ»)

آزمون تفریق‌های متوالی ۷ (Serial 7s)

(تشخیص حرف «ف»)

عقربه‌ها (Hands at 11:10)

اعداد (Numbers)

دایره ساعت (Contour)

. اجازه دهید مراجع بدون اعمال فشار زمانی، رسم را کامل کند.

به مراجع بگویید: «لطفاً این مکعب سه‌بعدی را تا حد امکان با دقت رسم کنید.»

تصویر مرجع مکعب سه‌بعدی را به مراجع نشان دهید.

یادآوری با تأخیر

ثبت و یادسپاری فوری

ثبت و یادسپاری فوری

ساخت فضایی–دیداری – ترسیم پنج‌ضلعی‌های متقاطع

مداد

ساعت (ساعت مچی)

. یادآوری با تأخیر (آزمون حافظه)

کم کردن‌های متوالی

من سه کلمه را نام می‌برم. پس از آن‌که هر سه کلمه را گفتم، می‌خواهم آن‌ها را تکرار کنید. این سه کلمه را به خاطر بسپارید، چون پس از چند دقیقه از شما خواهم خواست آن‌ها را دوباره تکرار کنید

ثبت (یادگیری) سه کلمه

1. Examiner's role (شغل آزمون‌گر)

1. Building name (نام مکان)

1. City (شهر)

1. Province (استان)

1. Country (کشور)

برای هر پاسخ ۱۰ ثانیه به مراجع فرصت دهید. به هر پاسخ صحیح ۱ نمره بدهید.

1. Day of week (روز هفته)

1. Date (تاریخ)

1. Month (ماه)

1. Season (فصل)

Year (سال)

برای هر پاسخ ۱۰ ثانیه به مراجع فرصت دهید. به هر پاسخ صحیح ۱ نمره بدهید.

آگاهی به زمان و مکان

شماره نظام / شماره مجوز

در معرض خطر

آیا موردی وجود دارد که نیازمند ارجاع به خدمات حمایتی اجتماعی / جامعه‌محور باشد؟

عدم پایبندی به درمان

اختلالات خواب

مشکلات جسمانی

در معرض خطر

تغییر نسبت به ارزیابی قبلی

آیا مورد یا نگرانی حقوقی وجود دارد؟

هرگونه مسائل یا نگرانی‌های حقوقی را ثبت نمایید.

فعالیت‌های تفریحی یا سرگرمی‌هایی را که مراجع در حال حاضر از آن‌ها لذت می‌برد و همچنین فعالیت‌هایی را که مایل است در آینده مجدداً آغاز کند یا در آن‌ها شرکت نماید، فهرست کنید. منظور از «به تعویق‌افتاده» فعالیت‌هایی است که مراجع از آن‌ها لذت می‌برد اما به دلیل مشکلات جسمی، کاهش انگیزه یا محدودیت دسترسی، آن‌ها را به تعویق انداخته یا میزان انجام آن‌ها را کاهش داده است. نمونه‌ها: خرید، سفر، پیاده‌روی، تماشای تلویزیون، گوش دادن به موسیقی، مطالعه یا شرکت در رویدادهای اجتماعی.

برنامه‌ریزی

نوع تمرین / فعالیت شناختی

تمرین‌های شناختی پیگیری تجویز شود؛ اطمینان حاصل گردد که مراقب/همراه بیمار برنامه را به‌طور کامل درک کرده است.

در صورت اندیکاسیون، آزمون MMSE / MoCA انجام شود. نتایج در بخش یادداشت‌ها ثبت گردد.

فقط در صورت صلاحدید بالینی انتخاب شود

سطح تحصیلات / سواد

بله، غربالگری زودتر انجام شود

خیر، غربالگری در این ویزیت انجام نشود

آیا مایل به انجام غربالگری شناختی در این ویزیت هستید؟

ر صورت تمایل می‌توانید غربالگری را زودتر انجام دهید یا آن را برای این ویزیت به تعویق بیندازید.

عدم استفاده از شبکه‌های اجتماعی

میزان فعالیت در شبکه‌های اجتماعی

آیا فکر می‌کنید اکثر افراد نسبت به شما وضعیت بهتری دارند؟

آیا احساس می‌کنید وضعیت زندگی شما ناامیدکننده است؟

آیا فکر می‌کنید زنده بودن در حال حاضر موضوعی ارزشمند و خوشایند است؟

آیا نگران هستید که اتفاق بدی برای شما رخ دهد؟

Oui, le lecteur partage cela. En revanche, il est beaucoup plus interrogatif quant à la place de l'architecture dans l'analyse de cette relation.

J'entends l'association mais il serait utile de la rendre encore plus perceptible et efficiente. Le glissement entre "ville" et "bâtiment" tout au fil du texte brouille la lecture.

Au regard de ce que le lecteur a pu lire jusqu'ici et au regard du titre de la contribution, il est difficile de partager ce "surgissement" comme une évidence....

Le lien entre "ville" et "architecture", entre "narration" et "architecture", se fait au détour d'un propos a sujet de la présence d'un bâtiment à photographier dans cette "expérience urbaine"... cela peut paraitre un peu léger.

N'y aurait-il pas un glissement dans l'emploi du terme architecture renvoyant à "architecturer la ville" ?

L'architecture est l'art de bâtir, principalement - pour rester prudent - un édifice...

Or, tout au long du texte il est certes question d'architecture mais sans jamais de référence à un édifice. L'espace, la narration, la ville, sont certes là et ont tous des rapports plus qu'évident à cet art de bâtir mais le système "ville-narration-architecture" ne donne pas sa pleine mesure, notamment lorsque l'architecture est citée et mobilisée...

La nuance entre " spécialiser" et "différencier" est juste et tout à fait opérante. On pourrait toutefois trouver que l'une est plutôt douce pour l'architecture (l'espace intérieur) et l'autre brutale et violente pour l'urbanisme (l'espace urbain)...

Pourquoi alors poser la première question si ce n'est pour une question de filiation disciplinaire ou de champ ?

La ville est thème principal de la réflexion. La narration, le récit, est un thème secondaire et des liens interessants et riches sont tissés entre les deux. L'architecture n'est présente que de manière très discrète et un esprit grincheux pourrait trouver sa présence au fond peu nécessaire....

It feels "fair", and it "works"... why shouldn't the people who work harder and have "the most" mechanotechnical capabilities be assigned to a job? In other words, as a friend of mine told, if we could have 3 Michelin star cooks only, why wouldn't we? It's an enticing idea, if we had these cooks with functional diversity, from different cultural backgrounds, skin tones, health, etc. it makes sense to begin with that we would assign resources to them.

But this ignores who we would be leaving. Further, we are skipping past what makes a 3-star chef, which is to say, it's NEVER a "chef", it's a WHOLE RESTAURANT. It's the location, ambience, the service, which often takes much much longer than a "typical" one, and requires many many more people (it's an spectacle in of itself, as they have minuscule dishes, and they often prepare them in front of people ONE BY ONE), plus, it essentialises consumption, as there is ONLY ONE 3-M Vegan restaurant in the world. It requires special utensils, learning, makes the process elitist and consumerist (telling you, you don't have to engage in it, leave that to experts), displacing hobbyism (the root of innovation), failure, spiral (not linear) learning processes, and many other externalities, like the type of exotic (highly limited) produce needed to make most recipes.

And that's accounting for the magical position that the process would be inclusive of everyone, and have enough chefs to feed the whole world. In what mind? Since we can't have this kind of home cook (or robot cook) for every person, we would have to rely on mass prepared dishes, probably inundating shelves with non-recyclable plastic containers to extend the food's life, these requiring a lot more carbon for transportation, and de-skilling people (less versatile, spitting at transference and imagination for other tasks, and reducing ability to make diverse stories and engage in interdisciplinary dialogue) who would pick food from a distant commodified service.

That's dark, I think. It speaks of how retribution is so engraved in our society, that we yearn for it even if false. But the dramatic ups and downs of this kind of life, as portrayed in shows like When Life gives you Tangerines, ridiculises oppression. It makes it invisible, as you don't lose a cared one in Minecraft...

COMPETITION.

Survivorship bias distilled.

And even then, would it be adequate? I don't think so most of the times.

1. Understanding the "Toxic Cocktail" (Chemical Types)

The expert emphasizes that we are exposed to a mixture of substances that act together. Key chemicals include: * Bisphenols (BPA, BPS, BPF, etc.): BPA (Bisphenol A) is a major endocrine disruptor used in hard plastics and can linings. Crucially, the expert warns against "BPA-Free" labels, noting they are often a form of Greenwashing. Manufacturers frequently replace BPA with BPS (Bisphenol S) or BPF (Bisphenol F), which are structurally similar and potentially just as harmful [00:28:38]. * Phthalates: Used to make plastics flexible (like PVC). Found in flooring, food wraps, and cosmetics, they interfere with reproductive and metabolic health [00:07:03]. * PFAS ("Forever Chemicals"): Used in non-stick pan coatings. These do not break down easily and can stay in the human body for many years [00:14:37], [00:43:13]. * Alkylphenols & Flame Retardants: Chemicals used in detergents and furniture that accumulate in household dust and disrupt thyroid function [00:08:10], [00:15:48].

2. Health Impacts: The "Grandchild Method"

• Hormonal Mimicry: These chemicals trick the body into treating them like natural hormones (mimicking estrogen). They block receptors and can "program" fat cells to store more fat, leading to obesity [00:08:43], [00:09:18].
• Diseases: Long-term exposure is linked to Type II diabetes, infertility, and hormone-dependent cancers like breast and prostate cancer.
• Inflammation: Microplastic particles act as foreign bodies, causing chronic internal inflammation—the root cause of most civilization diseases [00:02:42].

3. Fish and Food Packaging: Best vs. Worst

• The Danger of Cans: Canned fish is ranked as the worst source of bisphenols because the fat causes chemicals from the can's lining to leach into the food [00:27:00].
• Trout (Pstrąg): The healthiest choice. It lives a short life in clean, moving water, accumulating minimal toxins [00:27:50].
• Tuna & Flounder: Recommended to avoid. Tuna lives too long (accumulating chemicals), and Flounder lives at the bottom where pollutants settle [00:27:27], [00:27:33].
• Recommendation: Buy fish in glass jars or fresh rather than in metal cans [00:27:10].

4. Hidden Exposure Sources: Imports and Interior

• Asian Imports & Clothing: Products from Asian platforms often bypass EU safety standards and contain higher toxic concentrations. Synthetic clothes from Asia are heavily impregnated with chemicals to survive weeks in transport containers. The expert strongly advises washing new clothes at least twice before the first wear to reduce skin absorption of these toxins [00:17:32].
• Tea Bags: Certain bags containing plastic mesh or glue can release billions of microplastic particles into a single cup [00:00:00].
• Home Interiors: The combination of underfloor heating + vinyl or laminate panels is highly toxic; heat "bakes" chemicals into the air you breathe [00:32:08], [00:37:12].

5. Practical Detox and Prevention

• Liver Support: The liver can clear most bisphenols in a week if you stop exposure. Warning: Avoid aggressive "juice cleanses" that cause rapid weight loss, as this floods the blood with toxins previously stored in your fat tissue [00:20:26], [00:30:02].
• The "First Step" Strategy: Start by wet-dusting your home and creating a 5-minute draft (intensive ventilation) twice a day [00:48:11].
• Kitchen Changes: Switch to glass or stainless steel for storage, stop cooking rice/grains in plastic bags (cook them loose), and use cast iron or stainless steel pans instead of non-stick [00:21:22], [00:41:48], [00:43:13].

Есть клавиатура и каждая клавиша на ней может сломаться когда n раз на неё нажмут, если такое произошло ответ к этой клавиши "yes"

rampal

where is this from?

Interesting information I learned: - Venerologie Praha (Lidická 30) offers tests for more than "the standard four" STDs. - Relationship menu - RBDSMAF-Talk for conscious relating (a framework for a pre-sex discussion)

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

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Reply to the reviewers

Manuscript number: RC-2025-03280

Corresponding author(s): Stephan Gruber

1. General Statements [optional]

First, we would like to thank the editor at Review Commons for the efficient handling of our manuscript. We also apologize for our delayed response.

We are grateful to all three reviewers for their careful evaluation of our work and for their constructive feedback, which will provide a valuable basis for improving the figures and the text, as described below. We expect to be able to complete the revision following the plan described below quickly.

We note that the reviewer reports (Rev. #1 and Rev. #3) made us realize that the manuscript text was misleading on the following point. Although we used the purified ATP hydrolysis–deficient Smc protein for sybody isolation, this does not restrict the selection to a specific conformation. As described in detail in Vazquez-Nunez et al. (Figure 5), this mutant displays the ATP-engaged conformation only in a smaller fraction of complexes (~25% in the presence of ATP and DNA), consistent with prior in vivo observations reported by Diebold-Durand et al. (Figure 5). Rather than limiting the selection to a particular configuration, our aim was to reduce the prevalence of the predominant rod state in order to broaden the range of conformations represented during sybody selection. Consistent with this interpretation, only a small number of isolated sybodies show strong conformation-specific binding in the presence or absence of ATP/DNA, as observed by ELISA (now included in the manuscript). We will revise the manuscript text accordingly to clarify this point.

2. Description of the planned revisions

Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

• *

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

Gosselin et al., develop a method to target protein activity using synthetic single-domain nanobodies (sybodies). They screen a library of sybodies using ribosome/ phage display generated against bacillus Smc-ScpAB complex. Specifically, they use an ATP hydrolysis deficient mutant of SMC so as to identify sybodies that will potentially disrupt Smc-ScpAB activity. They next screen their library in vivo, using growth defects in rich media as a read-out for Smc activity perturbation. They identify 14 sybodies that mirror smc deletion phenotype including defective growth in fast-growth conditions, as well as chromosome segregation defects. The authors use a clever approach by making chimeras between bacillus and S. pnuemoniae Smc to narrow-down to specific regions within the bacillus Smc coiled-coil that are likely targets of the sybodies. Using ATPase assays, they find that the sybodies either impede DNA-stimulated ATP hydrolysis or hyperactivate ATP hydrolysis (even in the absence of DNA). The authors propose that the sybodies may likely be locking Smc-ScpAB in the "closed" or "open" state via interaction with the specific coiled-coil region on Smc. I have a few comments that the authors should consider:

Major comments: 1. Lack of direct in vitro binding measurements: The authors do not provide measurements of sybody affinities, binding/ unbinding kinetics, stoichiometries with respect to Smc-ScpAB. Additionally, do the sybodies preferentially interact with Smc in ATP/ DNA-bound state? And, do the sybodies affect the interaction of ScpAB with SMC? It is understandable that such measurements for 14 sybodies is challenging, and not essential for this study. Nonetheless, it is informative to have biochemical characterization of sybody interaction with the Smc-ScpAB complex for at least 1-2 candidate sybodies described here.

We agree with the reviewer that adding such data would be reassuring and that obtaining solid data using purified components is not easy even for a smaller selection of sybodies. We have data that show direct binding of Smc to sybodies by various methods including ELISA, pull-downs and by biophysical methods (GCI). Initially, we omitted these data from the manuscript as we are convinced that the mapping data obtained with chimeric SMC proteins is more definitive and relevant. During the revision we will incorporate the ELISA data showing direct binding and also indicating a lack of preference for a specific state of Smc.

Many modes of sybody binding to Smc are plausible The authors provide an elaborate discussion of sybodies locking the Smc-ScpAB complex in open/ closed states. However, in the absence of structural support, the mechanistic inferences may need to be tempered. For example, is it also not possible for the sybodies to bind the inner interface of the coiled-coil, resulting in steric hinderance to coiled-coil interactions. It is also possible that sybody interaction disrupts ScpAB interaction (as data ruling this possibility out has not been provided). Thus, other potential mechanisms would be worth considering/ discussing. In this direction, did AlphaFold reveal any potential insights into putative binding locations?

We have attempted to map the binding by structure prediction, however, so far, even the latest versions of AlphaFold are not able to clearly delineate the binding interface. Indeed, many ways of binding are possible, including disruption of ScpAB interaction. However, since the main binding site is located on the SMC coiled coils, the later scenario would likely be an indirect consequence of altered coiled coil configuration, consistent with our current interpretation.

1. Sybody expression in vivo Have the authors estimated sybody expression in vivo? Are they all expressed to similar levels?

We have tagged selected sybodies with gfp and performed live cell imaging. This showed that they are all roughly equally expressed and that they localize as foci in the cell presumably by binding to Smc complexes loaded onto the chromosome at ParB/parS sites. We will include this data in the revised version of the manuscript.

1. Sybodies should phenocopy ATP hydrolysis mutant of Smc The sybodies were screened against an ATP hydrolysis deficient mutant of Smc, with the rationale that these sybodies would interfere this step of the Smc duty cycle. Does the expression of the sybodies in vivo phenocopy the ATP hydrolysis deficient mutant of Smc? Could the authors consider any phenotypic read-outs that can indicate whether the sybody action results in an smc-null effect or specifically an ATP hydrolysis deficient effect?

As eluded to above, we think that our selection gave rise to sybodies that bind various, possibly multiple Smc conformations. Consistent with this idea, the phenotypes are similar to null mutant rather than the ATP-hydrolysis defective EQ mutant, which display even more severe growth phenotypes. We will add the following notes to the text:

“These conditions favour ATP-engaged particles alongside the typically predominant ATP-disengaged rod-shaped state (add Vazquez Nunez et al., 2021).”

“ELISA data confirm that nearly all clones bind Smc-ScpAB; however, their binding shows little or no dependence on the presence of ATP or DNA.”

Minor comments: 1. It was surprising that no sybodies were found that could target both bacillus and spneu Smc. For example, sybodies targeting the head regions of Smc that might work in a more universal manner. Could the authors comment on the coverage of the sybodies across the protein structure?

It is rather common that sybodies (like antibodies and nanobodies) exhibit strong affinity differences between highly conserved proteins (> 90 % identity). The underlying reasons for such strong discrimination are i) location of less conserved residues primarily at the target protein surface and ii) the large interaction interface between sybody and target which offers multiple vulnerabilities for disturbance, in particular through bulky side chains resulting in steric clashes. Another frequently observed phenomenon is sybody binding to a dominant epitope, which also often applies to nanobodies and antibodies. A great example for this are the dominant epitopes on SARS-CoV-2 RBDs.

Growth curves (Fig. S3) show a large jump in recovery in growth under sybody induction conditions. Could the authors address this observation here and in the text?

We suppose that this recovery represents suppressor mutants and/or (more likely) improved growth in the absence of functional Smc during nutrient limitation (see Gruber et al., 2013 and Wang et al., 2013). We will add this statement to the text.

L41- Sentence correction: Loop can be removed. Ah, yes, sorry for this confusing error. Thank you. 4. L525 - bsuSmc 'E' :extra E can be removed. To do. Thank you. 5. References need to be properly formatted. To do. Thank you. 6. The authors should add in figure legend for Fig 1i) details on representation of the purple region, and explain the grey strokes for orientation of the loop. To do. 7. How many cells were analysed in the cell biological assays? Legends should include these information. To Be Included.

Reviewer #1 (Significance (Required)):

Overall, this is an impressive study that uses an elegant strategy to find inhibitors of protein activity in vivo. The manuscript is clearly written and the experiments are logical and well-designed. The findings from the study will be significant to the broad field of genome biology, synthetic biology and also SMC biology. Specifically, the coiled coil domain of SMC proteins have been proposed to be of high functional value. The authors have elegantly identified key coiled-coil regions that may be important for function, and parallelly exhibited potential of the use of synthetic sybody/designed binders for inhibition of protein activity.

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

Review: "Single Domain Antibody Inhibitors Target the Coiled Coil Arms of the Bacillus subtilis SMC complex" by Ophélie Gosselin et al, Review Commons RC-2025-03280 Structural Maintenance of Chromosome proteins (SMCs), a family of proteins found in almost all organisms, are organizers of DNA. They accomplish this by a process known as loop extrusion, wherein double-stranded DNA is actively reeled in and extruded into loops. Although SMCs are known to have several DNA binding regions, the exact mechanism by which they facilitate loop extrusion is not understood but is believed to entail large conformational changes. There are currently several models for loop extrusion, including one wherein the coiled coil (CC) arms open, but there is a lack of insightful experimentation and analysis to confirm any of these models. The work presented aims to provide much-needed new tools to investigate these questions: conformation-selective sybodies (synthetic nanobodies) that are likely to alter the CC opening and closing reactions. The authors produced, isolated, and expressed sybodies that specifically bound to Bacillus subtilis Smc-ScpAB. Using chimeric Smc constructs, where the coiled coils were partly replaced with the corresponding sequences from Streptococcus pneumoniae, the authors revealed that the isolated sybodies all targeted the same 4N CC element of the Smc arms. This region is likely disrupted by the sybodies either by stopping the arms from opening (correctly) or forcing them to stay open (enough). Disrupting these functional elements is suggested to cause the Smc-dependent chromosome organization lethal phenotype, implying that arm opening and closing is a key regulatory feature of bacterial Smc-ScpAB. In summary, the authors present a new method for trapping bacterial Smc's in certain conformations using synthetic antibodies. Using these antibodies, they have pinpointed the (previously suggested) 4N region of the coiled coils as an essential site for the opening and closing of the Smc coiled coil arms and that hindering these reactions blocks Smc-driven chromosomal organization. The work has important implications for how we might elucidate the mechanism of DNA loop extrusion by SMC complexes. Some specific comments: Line 75: "likely stabilizing otherwise rare intermediates of the conformational cycle." - sorry, why is that being concluded? Why not stabilizing longer-lived oncformations? We will clarify this statement!

Line 89: Sorry, possibly our lack of understanding: why first ribosome and then phage display?

Ribosome display offers to screen around 10^12 sybodies per selection round (technically unrestricted library size), while for phage display, the library size is restricted to around 10^9 sybodies due to the fact that production of a phage library requires transformation of the phagemid plasmid into E. coli, thereby introducing a diversity bottleneck. This is why the sybody platform starts off with ribosome display. It switches to phage display from round 2 onwards because the output of the initial round of ribosome display is around 10^6 sybodies, which can be easily transferred into the phage display format. Phage display is used to minimize selection biases. For more information, please consult the original sybody paper (PMID: 29792401).

Line 100: Why was only lethality selected? Less severe phenotypes not clear enough?

Yes, colony size is more difficult to score robustly, as the sizes of individual transformant colonies can vary quite widely. The number of isolated sybodies was at the limit of further analysis.

Line 106: Could it be tested somehow if convex and concave library sybodies fold in Bs?

We did not focus on the non-functional sybody candidates and only sybodies of the loop library turned out to cause functional consequences at the cellular level. Notably, we will include gfp-imaging showing that non-lethal sybodies are expressed to similar levels that toxic sybodies. Given the identical scaffold of concave and loop sybodies (they only differ in their CDR3 length), we expect that the concave sybodies fold in the cytoplasm of B. subtilis. For the convex sybodies exhibiting a different scaffold, this will be tested.

Line 125: Could Pxyl be repressed by glucose?

To our knowledge and experience, repression by glucose (catabolite repression) does not work well in this context in B. subtilis.

Line 131: The SMC replacement strain is a cool experiment and removes a lot of doubts!

Thank you! (we agree 😊)

Line 141: The mapping is good and looks reliable, but looks and feels like a tour de force? Of course, some cryo-EM would have been lovely (lines 228-229 understood, it has been tried!).

Yes, we have made several attempts at structural biology. Unfortunately, Smc-ScpAB is not well suited for cryo-EM in our hands and crystallography with Smc fragments and sybodies did not yield well-diffracting crystals.

Line 179: Mmmh. Do we not assume DNA binding on top of the dimerised heads to open the CC (clamp)?

We will clarify the text here.

Line 187: Having sybodies that presumably keep the CC together (closing) and some that do not allow them to come together correctly (opening) is really cool and probably important going forward.

Thank you!

Figure 1 Ai is not very colour-blind friendly.

We are sorry for this oversight. We will try to make the color scheme more inclusive. Thank you for the notification.

Optional: did the authors see any spontaneous mutations emerge that bypass the lethal phenotype of sybody expression?

No, we did not observe spontaneous mutations suppressing the phenotype, possibly due to the limited number of cell generations observed. We tried to avoid suppressors by limiting growth, but this may indeed be a good future approach for further fine map the binding sites and to obtain insights into the mechanism of inhibition.

Optional: we think it would be nice to try some biochemical experiment with BMOE/cysteine-crosslinked B. subtilis Smc in the mid-region (4N or next to it) of the Smc coiled coils to try to further strengthen the story. Some of the authors are experts in this technique and strains might already exist?

We have indeed tried to study the impact of sybody binding on Smc conformation by cysteine cross-linking. However, we were not convinced by the results and thus prefer not to draw any conclusions from them. We will add a corresponding note to the text.

Reviewer #2 (Significance (Required)):

The authors present a new method for trapping bacterial Smc's in certain conformations using synthetic antibodies. Using these antibodies, they have pinpointed the (previously suggested) 4N region of the coiled coils as an essential site for the opening and closing of the Smc coiled coil arms and that hindering these reactions blocks Smc-driven chromosomal organization. The work has important implications for how we might elucidate the mechanism of DNA loop extrusion by SMC complexes. Thank you!

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

Gosselin et al. use the sybody technology to study effects of in vivo inhibition oft he Bacillus subtilis SMC complex. Smc proteins are central DNA binding elements of several complexes that are vital for chromosome dynamics in almost all organisms. Sybodies are selected from three different libraries of the single domain antibodies, using the „transition state" mutant Smc. They identify 14 such mutant sybodies that are lethal when expressed in vivo, because they prevent proper function of Smc. The authors present evidence suggesting that all obtained sybodies bind to a coiled-coil region close to the Smc „neck", and thereby interfere with the Smc activity cycle, as evidenced by defective ATPase activity when Smc is bound to DNA. The study is well done and presented and shows that the strategy is very potent in finding a means to quickly turn off a protein's function in vivo, much quicker than depleting the protein.

The authors also draw conclusions on the molecular mode of action of the SMC complex. The provide a number of suggestive experiments, but in my view mostly indirect evidence for such mechanism.

My main criticism ist hat the authors have used a single - and catalytically trapped form of SMC. They speculate why they only obtain sybodies from one library, and then only idenfity sybodies that bind to a rather small part oft he large Smc protein. While the approach is definitely valuable, it is biassed towards sybodies that bind to Smc in a quite special way, it seems. Using wild type Smc would be interesting, to make more robust statements about the action of sybodies potantially binding to different parts of Smc.

As explained above, we are quite confident the Smc ATPase mutation did not bias the selection in an obvious way. The surprising bias towards coiled coil binding sites has likely other explanations, as they likely form a preferred epitope recognized by sybodies.

Line 105: Alternatively, the other libraries did not produce good binders or these sybodies were 106 not stably expressed in B. subtilis. This could be tested using Western blotting - I am assuming sybody antibodies are commercially avalable. However, this test is not important for the overall study, it would just clarify a minor point.

While there are antibody fragments available to augment the size of sybodies (PMID: 40108246), these recognize 3D-epitopes and are thus not suited for Western blotting. We did not follow up on the negative results much, but would like to point out again that there are several biases that likely emerge for the same reason (bias to library, bias to coiled coil binding site). If correct, then likely few other sybodies are effectively lethal in B. subtilis, with the exception of the ones isolated and characterized. We have added this notion to the manuscript. We have also tested the expression of non-lethal sybodies by gfp-tagging and imaging. These results will be included in the revision.

Fig. 2B: is is odd to count Spo0J foci per cells, as it is clear from the images that several origins must be present within the fluorescent foci. I am fine with the „counting" method, as the images show there is a clear segregation defect when sybodies are expressed, I believe the authors should state, though, that this is not a replication block, but failure to segregate origins.

We agree that this is an important point and will add a corresponding comment to the text.

Testing binding sites of sybodies tot he SMC complex is done in an indirect manner, by using chimeric Smc constructs. I am surprised why the authors have not used in vitro crosslinking: the authors can purify Smc, and mass spectrometry analyses would identify sites where sybodies are crosslinked to Smc. Again, I am fine with the indirect method, but the authors make quite concrete statements on binding based on non-inhibition of chimeric Smc; I can see alternative explanations why a chimera may not be targeted.

We have made several attempts of testing direct binding with mixed outcomes and decided to not include those results in the light of the stronger and more relevant in vivo mapping. However, we will add ELISA results and briefly discuss grating coupled interferometry (GCI) data and pull-downs.

Smc-disrupting sybodies affect the ATPase activity in one of two ways. Again, rather indirect experiments. This leads to the point Revealing Smc arm dynamics through synthetic binders in the discussion. The authors are quite careful in stating that their experiments are suggestive for a certain mode of action of Smc, which is warranted.

In line 245, they state More broadly, the study demonstrates how synthetic binders can trap, stabilize, or block transient conformations of active chromatin-associated machines, providing a powerful means to probe their mechanisms in living cells. This is off course a possible scenario for the use of sybodies, but the study does not really trap Smc in a transient conformation, at least this is not clearly shown.

We agree and will carefully rephrase this statement. Thank you.

Overall, it is an interesting study, with a well-presented novel technology, and a limited gain of knowledge on SMC proteins. We respectfully disagree with the last point, since our unique results highlight the importance of the Smc coiled coils, which are otherwise largely neglected in the SMC literature, likely (at least in part) due the mild effect of single point mutations on coiled coil dynamics.

Reviewer #3 (Significance (Required)):

The work describes the gaining and use of single-binder antibodies (sybodies) to interfere with the function of proteins in bacteria. Using this technology for the SMC complex, the authors demonstrate that they can obtain a significant of binders that target a defined region is SMC and thereby interfere with the ATPase cycle.

The study does not present a strong gain of knowledge of the mode of action of the SMC complex.

As pointed out above, we respectfully disagree with this assertion.

• *

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

Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

• *

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

Please include a point-by-point response explaining why some of the requested data or additional analyses might not be necessary or cannot be provided within the scope of a revision. This can be due to time or resource limitations or in case of disagreement about the necessity of such additional data given the scope of the study. Please leave empty if not applicable.

As pointed out above, there are a few minor points that we prefer not to experimentally address. In particular, we do not consider it as necessary to determine the expression levels of sybodies which were non-inhibitory. We also wish to note that we attempted to obtain structural additional biochemical data and to that end performed cryo-EM, crystallography and cysteine cross-linking experiments. Unfortunately, we did not obtain sybody complex structures and the cross-linking data were unfortunately not conclusive. We also wish to note that the first author has finished her PhD and left the lab, which limits our capacity to add additional experiments. However, as the reviewers also pointed out, the main conclusions are well supported by the data already.

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

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Referee #3

Evidence, reproducibility and clarity

Gosselin et al. use the sybody technology to study effects of in vivo inhibition oft he Bacillus subtilis SMC complex. Smc proteins are central DNA binding elements of several complexes that are vital for chromosome dynamics in almost all organisms. Sybodies are selected from three different libraries of the single domain antibodies, using the „transition state" mutant Smc. They identify 14 such mutant sybodies that are lethal when expressed in vivo, because they prevent proper function of Smc. The authors present evidence suggesting that all obtained sybodies bind to a coiled-coil region close to the Smc „neck", and thereby interfere with the Smc activity cycle, as evidenced by defective ATPase activity when Smc is bound to DNA. The study is well done and presented and shows that the strategy is very potent in finding a means to quickly turn off a protein's function in vivo, much quicker than depleting the protein.

The authors also draw conclusions on the molecular mode of action of the SMC complex. The provide a number of suggestive experiments, but in my view mostly indirect evidence for such mechanism.

My main criticism ist hat the authors have used a single - and catalytically trapped form of SMC. They speculate why they only obtain sybodies from one library, and then only idenfity sybodies that bind to a rather small part oft he large Smc protein. While the approach is definitely valuable, it is biassed towards sybodies that bind to Smc in a quite special way, it seems. Using wild type Smc would be interesting, to make more robust statements about the action of sybodies potantially binding to different parts of Smc.

Line 105: Alternatively, the other libraries did not produce good binders or these sybodies were 106 not stably expressed in B. subtilis. This could be tested using Western blotting - I am assuming sybody antibodies are commercially avalable. However, this test is not important for the overall study, it would just clarify a minor point.

Fig. 2B: is is odd to count Spo0J foci per cells, as it is clear from the images that several origins must be present within the fluorescent foci. I am fine with the „counting" method, as the images show there is a clear segregation defect when sybodies are expressed, I believe the authors should state, though, that this is not a replication block, but failure to segregate origins.

Testing binding sites of sybodies tot he SMC complex is done in an indirect manner, by using chimeric Smc constructs. I am surprised why the authors have not used in vitro crosslinking: the authors can purify Smc, and mass spectrometry analyses would identify sites where sybodies are crosslinked to Smc. Again, I am fine with the indirect method, but the authors make quite concrete statements on binding based on non-inhibition of chimeric Smc; I can see alternative explanations why a chimera may not be targeted.

Smc-disrupting sybodies affect the ATPase activity in one of two ways. Again, rather indirect experiments. This leads to the point Revealing Smc arm dynamics through synthetic binders in the discussion. The authors are quite careful in stating that their experiments are suggestive for a certain mode of action of Smc, which is warranted.

In line 245, they state More broadly, the study demonstrates how synthetic binders can trap, stabilize, or block transient conformations of active chromatin-associated machines, providing a powerful means to probe their mechanisms in living cells. This is off course a possible scenario for the use of sybodies, but the study does not really trap Smc in a transient conformation, at least this is not clearly shown.

Overall, it is an interesting study, with a well-presented novel technology, and a limited gain of knowledge on SMC proteins.

Significance

The work describes the gaining and use of single-binder antibodies (sybodies) to interfere with the function of proteins in bacteria. Using this technology for the SMC complex, the authors demonstrate that they can obtain a significant of binders that target a defined region is SMC and thereby interfere with the ATPase cycle.

The study does not present a strong gain of knowledge of the mode of action of the SMC complex.

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

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

Review: "Single Domain Antibody Inhibitors Target the Coiled Coil Arms of the Bacillus subtilis SMC complex" by Ophélie Gosselin et al, Review Commons RC-2025-03280

Structural Maintenance of Chromosome proteins (SMCs), a family of proteins found in almost all organisms, are organizers of DNA. They accomplish this by a process known as loop extrusion, wherein double-stranded DNA is actively reeled in and extruded into loops. Although SMCs are known to have several DNA binding regions, the exact mechanism by which they facilitate loop extrusion is not understood but is believed to entail large conformational changes. There are currently several models for loop extrusion, including one wherein the coiled coil (CC) arms open, but there is a lack of insightful experimentation and analysis to confirm any of these models. The work presented aims to provide much-needed new tools to investigate these questions: conformation-selective sybodies (synthetic nanobodies) that are likely to alter the CC opening and closing reactions.

The authors produced, isolated, and expressed sybodies that specifically bound to Bacillus subtilis Smc-ScpAB. Using chimeric Smc constructs, where the coiled coils were partly replaced with the corresponding sequences from Streptococcus pneumoniae, the authors revealed that the isolated sybodies all targeted the same 4N CC element of the Smc arms. This region is likely disrupted by the sybodies either by stopping the arms from opening (correctly) or forcing them to stay open (enough). Disrupting these functional elements is suggested to cause the Smc-dependent chromosome organization lethal phenotype, implying that arm opening and closing is a key regulatory feature of bacterial Smc-ScpAB. In summary, the authors present a new method for trapping bacterial Smc's in certain conformations using synthetic antibodies. Using these antibodies, they have pinpointed the (previously suggested) 4N region of the coiled coils as an essential site for the opening and closing of the Smc coiled coil arms and that hindering these reactions blocks Smc-driven chromosomal organization. The work has important implications for how we might elucidate the mechanism of DNA loop extrusion by SMC complexes.

Some specific comments:

Line 75: "likely stabilizing otherwise rare intermediates of the conformational cycle." - sorry, why is that being concluded? Why not stabilizing longer-lived oncformations?

Line 89: Sorry, possibly our lack of understanding: why first ribosome and then phage display?

Line 100: Why was only lethality selected? Less severe phenotypes not clear enough?

Line 106: Could it be tested somehow if convex and concave library sybodies fold in Bs?

Line 125: Could Pxyl be repressed by glucose?

Line 131: The SMC replacement strain is a cool experiment and removes a lot of doubts!

Line 141: The mapping is good and looks reliable, but looks and feels like a tour de force? Of course, some cryo-EM would have been lovely (lines 228-229 understood, it has been tried!).

Line 179: Mmmh. Do we not assume DNA binding on top of the dimerised heads to open the CC (clamp)?

Line 187: Having sybodies that presumably keep the CC together (closing) and some that do not allow them to come together correctly (opening) is really cool and probably important going forward.

Figure 1 Ai is not very colour-blind friendly. Optional: did the authors see any spontaneous mutations emerge that bypass the lethal phenotype of sybody expression?

Optional: we think it would be nice to try some biochemical experiment with BMOE/cysteine-crosslinked B. subtilis Smc in the mid-region (4N or next to it) of the Smc coiled coils to try to further strengthen the story. Some of the authors are experts in this technique and strains might already exist?

Significance

The authors present a new method for trapping bacterial Smc's in certain conformations using synthetic antibodies. Using these antibodies, they have pinpointed the (previously suggested) 4N region of the coiled coils as an essential site for the opening and closing of the Smc coiled coil arms and that hindering these reactions blocks Smc-driven chromosomal organization. The work has important implications for how we might elucidate the mechanism of DNA loop extrusion by SMC complexes.

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Referee #1

Evidence, reproducibility and clarity

Gosselin et al., develop a method to target protein activity using synthetic single-domain nanobodies (sybodies). They screen a library of sybodies using ribosome/ phage display generated against bacillus Smc-ScpAB complex. Specifically, they use an ATP hydrolysis deficient mutant of SMC so as to identify sybodies that will potentially disrupt Smc-ScpAB activity. They next screen their library in vivo, using growth defects in rich media as a read-out for Smc activity perturbation. They identify 14 sybodies that mirror smc deletion phenotype including defective growth in fast-growth conditions, as well as chromosome segregation defects. The authors use a clever approach by making chimeras between bacillus and S. pnuemoniae Smc to narrow-down to specific regions within the bacillus Smc coiled-coil that are likely targets of the sybodies. Using ATPase assays, they find that the sybodies either impede DNA-stimulated ATP hydrolysis or hyperactivate ATP hydrolysis (even in the absence of DNA). The authors propose that the sybodies may likely be locking Smc-ScpAB in the "closed" or "open" state via interaction with the specific coiled-coil region on Smc. I have a few comments that the authors should consider:

Major comments:

1. Lack of direct in vitro binding measurements: The authors do not provide measurements of sybody affinities, binding/ unbinding kinetics, stoichiometries with respect to Smc-ScpAB. Additionally, do the sybodies preferentially interact with Smc in ATP/ DNA-bound state? And, do the sybodies affect the interaction of ScpAB with SMC? It is understandable that such measurements for 14 sybodies is challenging, and not essential for this study. Nonetheless, it is informative to have biochemical characterization of sybody interaction with the Smc-ScpAB complex for at least 1-2 candidate sybodies described here.
2. Many modes of sybody binding to Smc are plausible The authors provide an elaborate discussion of sybodies locking the Smc-ScpAB complex in open/ closed states. However, in the absence of structural support, the mechanistic inferences may need to be tempered. For example, is it also not possible for the sybodies to bind the inner interface of the coiled-coil, resulting in steric hinderance to coiled-coil interactions. It is also possible that sybody interaction disrupts ScpAB interaction (as data ruling this possibility out has not been provided). Thus, other potential mechanisms would be worth considering/ discussing. In this direction, did AlphaFold reveal any potential insights into putative binding locations?
3. Sybody expression in vivo Have the authors estimated sybody expression in vivo? Are they all expressed to similar levels?
4. Sybodies should phenocopy ATP hydrolysis mutant of Smc The sybodies were screened against an ATP hydrolysis deficient mutant of Smc, with the rationale that these sybodies would interfere this step of the Smc duty cycle. Does the expression of the sybodies in vivo phenocopy the ATP hydrolysis deficient mutant of Smc? Could the authors consider any phenotypic read-outs that can indicate whether the sybody action results in an smc-null effect or specifically an ATP hydrolysis deficient effect?

Minor comments:

1. It was surprising that no sybodies were found that could target both bacillus and spneu Smc. For example, sybodies targeting the head regions of Smc that might work in a more universal manner. Could the authors comment on the coverage of the sybodies across the protein structure?
2. Growth curves (Fig. S3) show a large jump in recovery in growth under sybody induction conditions. Could the authors address this observation here and in the text?
3. L41- Sentence correction: Loop can be removed.
4. L525 - bsuSmc 'E' :extra E can be removed.
5. References need to be properly formatted.
6. The authors should add in figure legend for Fig 1i) details on representation of the purple region, and explain the grey strokes for orientation of the loop.
7. How many cells were analysed in the cell biological assays? Legends should include these information.

Significance

Overall, this is an impressive study that uses an elegant strategy to find inhibitors of protein activity in vivo. The manuscript is clearly written and the experiments are logical and well-designed. The findings from the study will be significant to the broad field of genome biology, synthetic biology and also SMC biology. Specifically, the coiled coil domain of SMC proteins have been proposed to be of high functional value. The authors have elegantly identified key coiled-coil regions that may be important for function, and parallelly exhibited potential of the use of synthetic sybody/designed binders for inhibition of protein activity.

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Reply to the reviewers

Response to Reviewers

We thank the Reviewers for their appreciative comments (Reviewer 1: “first time that a well-established existing mathematical model of signaling response extended and applied to heterogeneous ligand mixtures”)and constructive suggestions for improvement. In this extensive revision, we have not only addressed the suggestions comprehensively but also extended our analysis of signaling antagonism to all doses and at the single-cell level using novel computational workflows. This resulted in the discovery of several mechanismsof antagonism and synergy that are dose-dependent, and dependent on the cell-specific state of the signaling network, thereby manifesting in only a subset of cells.

We have addressed Reviewer comments: we have made substantial revisions to improve clarity, rigor, and biological interpretation. Below we briefly summarize the main concerns raised by Reviewers 1-3 and how we have addressed them.

• We have rewritten the Methods section to clarify our approaches. We have also added the explanation of methodology and the rationale in the main text to improve readability and comprehensiveness (Addressing Reviewer #1 comments). This includes explaining and justifying the signaling codon approaches (Reviewer 1), our core-module parameter matching methodology and discussion (Reviewer #1, point 11, Reviewer #2, point 1), and the model schematic (Reviewer #1, point 5).
• For one of our major conclusions – that macrophages may distinguish stimuli in the context of ligand mixtures – we have validated these results with experiments, which increases confidence in this conclusion (Reviewer #2, point 3, Reviewer #3, point 2).
• We have updated the model for CpG-pIC competition using Michaelis–Menten kinetics without any additional parameters, rather than introducing new free parameters. This change removes parameter freedom for fitting combinatorial conditions, leading to a more constrained and mechanistically grounded model whose predictions align better with experimental data (Updated Figures 2 and S2; Reviewer #2, point 2).
• We have addressed all other editorial and clarification-related concerns as well, as detailed in our point-by-point response below. In addition, we have extended the scope of the manuscript. We have extended our analysis of ligand combinations across a broad dose range, from non-responsive to saturated conditions. This led to several additional discoveries. For example, we show that ultrasensitive IKK activation can underlie synergistic combinations of ligands at low doses. In contrast, beyond the CpG-poly(I:C) antagonism, we identify that competition for CD14 uptake by LPS and Pam can generate antagonism between these ligands within specific dose ranges.

Importantly, such antagonism or synergy is not evident in all cells in the population. It may also not be picked up by studies of the mean behavior. With our new computational workflow that allows for single-cell resolution we identify the conditions that must be met by the signaling network state, for antagonism or synergy to take place.

Further, we examine the hypothesis that such signaling pathway interactions affect stimulus-response specificity in combinatorial stimulus conditions. By comparing models with and without this antagonism, we demonstrate that antagonistic interactions can improve stimulus-response specificity in complex ligand mixtures.

These additional analyses provide a new mechanistic understanding of cellular information processing and elucidate how synergy and antagonism can mechanistically shape signaling fidelity in response to complex ligand mixtures.

Point-by-Point Response

Reviewer #1

Evidence, reproducibility and clarity

The authors extend an existing mathematical model of NFkB signalling under stimulation of various single receptors, to model that describes responses to stimulation of multiple receptors simultaneously. They compare this model to experimental data derived from live-cell imaging of mouse macrophages, and modify the model to account for potential antagonism between TLR3 and TLR9 response due to competition for endosomal transport. Using this framework they show that, despite distinguishability decreasing with increasing numbers of heterogenous stimuli, macrophages are still able in principle to distinguish these to a statistically significant degree. I congratulate the authors on an interesting approach that extends and validates an existing mathematical model, and also provides valuable information regarding macrophage response.

Response: We thank the reviewer for this appreciative assessment and for the careful reading of our work. The constructive comments helped us substantially improve the rigor and clarity of the manuscript.

In addition to revising the text for clarity, we have extended our analysis to systematically investigate dose-response behavior for each pair of ligand combination. Using the experimentally validated model, we explored 10 ligand pairs across a range of doses from non-responsive to saturating. This allowed us to identify mechanistic regimes in which synergy and antagonism arise at the single-cell level. In particular, we found that low-dose synergy can be explained by ultrasensitive IKK activation (Figure 4 and corresponding supplementary figures), while antagonism can emerge from competition for shared components such as CD14 (Figure 5 and corresponding supplementary figures). We further show that antagonism can enhance condition distinguishability in ligand mixtures, thereby contributing to stimulus-response specificity (Figure 5 and corresponding supplementary figures).

There are no major issues affecting the scientific conclusions of the paper, however the lack of detail surrounding the mathematical model and the 'signaling codons' that are used throughout the paper make it difficult to read. This is exacerbated by the fact that I was unable to find Ref 25 which apparently describes the model, however I was able to piece together the essential components from the description in Ref 8 and the supplementary material.

Response: This comment helped us to improve the writing. We apologize that the key reference 25 was still not publicly available. It is now published in Nature Communications. In addition, we have added more details to clarify the mathematical model as well as the signaling codons, in results and in methods. Please see below for details.

Lots of the minor comments below stem from this, however there are also a few other places that could benefit from some additional clarification and explanation.

Significance: 1. '...it remains unclear complex...' -> '...it remains unclear whether complex...' Response: We have rewritten the Significance (now it is Synopsis).

Introduction: 2. 'temporal dynamics of NFkB' - it would be good to be more concrete regarding the temporal dynamics of what aspect of this (expression, binding, conformation, etc), if possible. Response: It refers to the presence of NFκB into nucleus, which represents active NFκB capable of activating gene expression. We have clarified this (Lines 59-61 in introduction paragraph 2). “Upon stimulation, NFκB translocates into the nucleus, … activating immune gene expression (10, 15–19).”

'signaling codons' - the behaviour of these is key to the entire paper, so even if they are well described in the reference, it would be good to have a short description as early as possible so that the reader can get an idea in their mind what exactly is being discussed here. Later, it would be good to have concrete description of exactly what these capture.

Response: We thank the reviewer for this comment. We have added one whole paragraph in the early introduction to describe the concept of Signaling Codons which allow quantitative characterization of NFkB stimulus-response-specific dynamics (Lines 60-67). We have also added more concrete description of Signaling Codons in the results as well as adding an illustration for the signaling codons (Lines 169-175, Figure S2B).

'This challenge...population of macrophages' - this seems a bit out of place, and is a bit of a run on sentence, so I suggest moving this to the next paragraph and working it into the first sentence there '...regulatory mechanisms, and this challenge could be addressed with a model parameterised to account for heterogeneous...Early models ...', or something similar.

Response: We thank the reviewer for this suggestion, we have revised this as suggested. This improves the logic flow (Lines 87-88).

Ref 25: I can't find a paper with this title anywhere, so if it's an accepted preprint then it would be good to have this available as well. That said, I still think it would be difficult to grasp the work done in this paper without some description of the mathematical model here, at least schematically, if not the full set of ODEs. For example, there are numerous references to how this incorporates heterogeneous responses, the 'core module', etc, and the reader has no context of these if they aren't familiar with the structure of the model. Response: We apologize that Ref 25 was not on PubMed. Now it’s published, and we have updated the corresponding information. This comment also helped us to improve the writing by adding a description of the mathematical model in the Introduction (Lines 95-105), the results (Lines 129-141), and a detailed description of the model in the Methods (Simulation of heterogenous NFκB dynamical responses.)

We have also added the schematic of the model topology in Figure S1 (adapted from previous publications Guo et al 2025, Adelaja et al 2021) to make sure the paper is self-contained.

'A key challenge which is...' -> 'A key challenge is...' Response: We have revised the Introduction and removed this sentence.

'With model simulation ...' -> a bit of a run on sentence, I suggest breaking after 'conditions'. Response: We have revised the introduction and removed this sentence.

Results:

1. This section would benefit from a more in-depth description of the model and experimental setup. In particular for the experiment, the reader never really knows what this workflow for this is, nor what the model ingests as input, and what the predictions are of. Response: This comment helped us to improve clarity by adding an in-depth description of the model and experimental setup. We have revised the Results as suggested (Lines 129-141). We also appended the corresponding revision here for reviewer reference.

“This mechanistic model was trained on single-ligand response experimental datasets, capturing the single-ligand stimulus-response specificity of the population of macrophages while accounting for cellular heterogeneity. Specifically, quantitative NFκB dynamic trajectory data from hundreds of single macrophages responding to five single ligands (TNF, pIC, Pam, CpG, LPS) at 3-5 doses was obtained from live cell imaging experiments. The mathematical model (Figure S1) consists of a 52-dimensional system of ordinary differential equations, including 52 intracellular species, 101 reactions and 133 parameters, and is divided into five receptor modules, which respond to the corresponding ligands respectively, and the IKK-NFκB core module that contains the prominent IκBα negative feedback loop. By fitting the single-cell experimental data set with a non-linear mixed effect statistical model (coupling with 52-dimensional NFκB ODE model), the parameter distributions for the single-cell population were inferred. Analyzing the resulting simulated NFκB trajectories with Information theoretic and machine learning classification analyses confirmed that the virtual cell model simulations reproduced key SRS performance characteristics of live macrophages.”

'..mechanistic model was trained...' - trained in this study, or in the previous referenced study? Response: The mechanistic model was trained in a previous study (Guo et al 2025 Nature Comm), and we have clarified this in the revision (Lines 127 - 129).

1. 'determined parameter distributions' - this is where it would be good to have more background on the model. What parameters are these, and what do they correspond to biologically? It would also be nice to see in the methods or supplementary material how this is done (maximum likelihood, etc). Response: This comment helps us to clarify the predetermined parameter distributions. We have revised the methods to include this information (Simulation of heterogenous NFκB dynamical responses, paragraph 3). We have appended the corresponding text here for reviewer’s convenience.

“The ODE model was then fitted to the population of single-cell trajectories to recapitulate the cell-to-cell heterogeneity in the experimental data (2). This is achieved by solving the non-linear mixed effects model (NLME) through stochastic approximation of expectation maximation algorithm (SAEM) (3–6). Seventeen parameters were estimated. Within the core module, the estimated parameters included the rates governing TAK1 activation (k52, k65), the time delays of IκBα transcription regulated by NFκB (k99, k101), and the total cellular NFκB abundance (tot NFκB). Within the receptor module, receptor synthesis rates (k54 for TNF, k68 for Pam, k85 for CpG, k35 for LPS, k77 for pIC), degradation rates of the receptor–ligand complexes (k56, k61, k64 for TNF; k75 for Pam; k93 for CpG; k44 for LPS; k83 for pIC), and endosomal uptake rates (k87 for CpG; k36 and k40 for LPS; k79 for pIC) were fitted. All remaining parameters were fixed at literature-suggested values (1). The single-cell parameters inferred from experimental individual‐cell trajectories then served as empirical distributions for generating the new dataset (see SupplementaryDataset2).”

'matching cells with similar core model...' - it's difficult to follow the logic as to why this is done, so I think this needs to be a little clearer. My guess would be that the assumption is that simulated cells with similar 'core' parameters have a similar downstream signalling response, and therefore the receptors can be 'transplanted'. So it would be nice to see exactly what these distributions are and what the effect of a bad match would be. Response: We thank the reviewer for this comment. In the revision, we have explained the rationale for matching cells with similar core module (Lines 145-152).

“Previous work determined parameter distributions for only the cognate receptor module (and the core module) that provided the best fit for the relevant single ligand experimental data (Figure 1A, Step 1), but other receptor modules’ parameter values were not determined. To simulate stimulus responses to more than two ligands, we imputed the other ligand-receptor module parameters using shared core-module parameters as common variables and employing nearest-neighbor hot-deck imputation (35). In this setup, the core module functions as an “anchor” to harmonize two or more receptor-specific parameter distributions.”

This nearest-neighbor hot-deck imputation approach (the core module matching method) was shown to outperform other approaches, including random matching and rescaled-similarity matching (Guo et al. 2025, Supplementary Figure S11). For the reviewer’s convenience, we have also appended the corresponding figure below.

Figure S11 from (Guo et al., 2025). Assessment of matching techniques for predicting single-cell responses to various ligand stimuli (a-d). Heatmaps illustrating the Wasserstein distance between the signaling codon distributions predicted by the model and those observed in experiments. The analysis employs four distinct matching methods to align the five ligand-receptor module parameters: (a) “Random Matching”, (b) “Similarity Matching” (the method used in our study), (c) “Rescaled-Similarity Matching”, and (d) “Sampling Approximated Distribution”. In the heatmaps, rows represent signaling codons, columns denote ligands, and the color intensity indicates the Wasserstein distance, providing a visual metric of similarity between model predictions and experimental data. e-f. Histogram of the average Wasserstein distance between the model-predicted and experimentally observed signaling codon distributions, summarized across signaling codons (e) and ligands (f).

Some explanation of how this relates to the experimental data the parameters are fit on would also be useful. (a) Is there a correspondence between individual simulated cells and the experimental data for the single ligand stimulation, and then the smallest set of these is taken? Is there also a matching from the simulated multi-receptor modules and the multi-receptor data, and if so, is this done in the same way? Response: This comment to help us clarify the correspondence relationship between model simulations and experimental data.

Yes—there is a correspondence between individual simulated cells and the previously published experimental data (Guo et al., 2025b) for single-ligand stimulation. We have revised the first paragraph of the Results (Lines 136–148) and the Methods (Lines 544-557) to clarify how the model simulations were fit to the previous experimental dataset. See Reviewer 1, Comments 10 for the updates in Methods. We have pasted in the revised Results section below for the reviewer’s reference.

“By fitting the single-cell experimental data set with a non-linear mixed effect statistical model (coupling with 52-dimensional NFκB ODE model), the parameter distributions for the single cell population were inferred.”

'six signaling codons' - here it would be good to recapitulate what these represent, but also what the 'strength' and 'activity' correspond to (total integrated value, maximum value, etc) Response: We thank the reviewer for the suggestion and have clarified this point (Lines 169-175, Figure S2B).

'pre-defined thresholds' - no need to state these numerically in the text (although giving some sense of how/why these were chosen would give some context), but I couldn't find the values of these, nor values corresponding to the signaling codons. Response: We appreciate the reviewer’s comment. We have added this information in the figure legend (Figure 1B-C) and Method -- “Responder fraction” (Lines 666-672). Specifically, for the model simulation data, the integral thresholds are 0.4 (µM·h), 0.5 (µM·h), and 0.6 (µM·h). The peak thresholds are 0.12 (µM), 0.14 (µM), and 0.16 (µM). For the experimental data, the integral thresholds are 0.2 (A.U.·h), 0.3 (A.U.·h), and 0.4 (A.U.·h). The peak thresholds are 0.14 (A.U.), 0.18 (A.U.), and 0.22 (A.U.). Thresholds were selected so that the medium threshold yields 50% responder cells under single-ligand conditions, while the responder ratio remains unsaturated under three-ligand stimulation.

'non-responder cells are likely a result of cellular heterogeneity in receptor modules rather than the core module' - is this the 'ill health' referenced earlier? If so make this clear. Response: Yes, this is the ‘ill health’ referenced earlier, and we have clarified this (Lines 198-199).

It's also very difficult to follow this chain of logic, given that the reader at this point doesn't have any knowledge of what the 'core' module is, nor the significance of the thresholds on the signaling codons. I would suggest making this much clearer, with reference to each of these. Response: We apologize for the poor explanation. We have now explained in the Introduction (Lines 95-106) and the results (Lines 129-141) how the model is structured into receptor-proximal modules that converge on the common core module. We have also added a schematic for clarity (Figure S1). For further clarification of the math models, we have significantly revised the Methods (Simulation of heterogenous NFκB dynamical responses). The defined thresholds are clarified in the Methods -- “Responder fraction”.

'...but the model represented these as independent mass action reactions' - the significance of this may not be clear to someone not familiar with biophysical models, so probably better to make it explicit. Response: We thank the reviewer for this reminder, and we have added a description of the significance of this point (Lines 225-227).

'...we trained a random forest classifier...' - is this trained on the 'raw' experimental time series data, or on the signaling codons? Response: It is trained on the signaling codons calculated from model simulations of NFκB trajectories. We have clarified this (Lines 260-261).

'We also applied a Long Short-Term Memory (LSTM) machine learning model...' - it might be good to reference these three approaches at the beginning of this section, otherwise they seem to come out of the blue a little. Response: We have added the references of these three approaches in the beginning of this section (Lines 242-246).

'We then used machine learning classifiers...' - random forests, LSTMs, or a different model? Response: We have clarified that this as random forest classifier (Line 276).

Discussion:

1. '...over statistical models...' - suggest maybe 'purely statistical models' Response: We thank the reviewer for this suggestion. We have rewritten the whole Discussion to include the new insights of antagonism and synergy and their roles in maintaining unexpectedly high SRS performance. Thus, this sentence was removed.

'We found that endosomal transport...' - A paper by Huang, et. al. (https://www.jneurosci.org/content/40/33/6428) observed a synergistic phagocytic response between CpC and pIC stimulation in microglia. This is still consistent with a saturation effect dependent on dose, but may be worth a mention. Response: We thank the reviewer for referring this interesting paper to us, and this comment helps us to improve the Discussion of inflammatory signaling pathways besides NFκB. This paper demonstratessynergistic effects between CpG and pIC in inhibiting tumor growth and promoting cytokine production(Huang et al., 2020), such as IFN-β and TNF-α, whose expression is also regulated by the IRF and MAPK signaling pathways (Luecke et al., 2021; Sheu et al., 2023). This finding does not contradict our findings that CpG and pIC act antagonistically in the NFκB signaling pathway because of the combinatorial pathways that act on gene expression: CpG can activate the MAPK signaling pathway (Luecke et al., 2024) but not the IRF signaling pathway, whereas pIC activates the IRF signaling pathway (Akira and Takeda, 2004) but only weakly the MAPK pathway. Therefore, their combination can synergistically regulate inflammatory responses. We have added this to the discussion (Lines 515-522).

'...features termed...' -> 'features, termed' Response: We thank the reviewer for their carefully reading, and we have rewritten the Discussion.

'...we applied a Long Short-Term Memory (LSTM) machine learning model..' - maybe make clear that this is on the time-series data (also LSTM has already been defined). Response: We thank the reviewer for their carefully reading, and we have rewritten the Discussion.

Materials and methods:

1. The descriptions in this section are quite vague, so I would suggest expanding this with more detail from the supplementary material, where things are quite well explained. Response: We thank the reviewer for this suggestion, and we have rewritten the whole Methods as suggested.

'sampling distribution' - not clear what this refers to in this context Response: We have clarified this in the revision (Methods -- Simulation of heterogenous NFκB dynamical responses, paragraph 3). “The single-cell signaling-pathway parameter values used for bootstrapping sampling to generate model simulations are given in Supplementary dataset 2.”

'RelA-mVenus mouse strain' - it would be good to mention the relevance of the reporter for NFkB signaling Response: We have added the relevance of the reporter for NFkB signaling (Methods, Lines 624-626).

'...A random forest classifier...' -> a random forest classifier

Response: We have rewritten the methods.

Significance

This study provides mechanistically interpretable insight on the important question of how immune cells perform target recognition in realistic scenarios, and also provides validation of existing mathematical models by extending these beyond their original domain. The paper uses 'signaling codons' as a proxy for information processing, however in this instance it is cross-validated with an LSTM model that is applied directly to the time series data. Nevertheless, the scope of the paper is such that it does not deal with the question of how these signals are transmitted or used in a downstream immune response. To my knowledge, this is the first time that a well established existing mathematical model of signalling response has been extended and applied to heterogeneous ligand mixtures. These results will be of interest to those studying immune cell responses, and to those interested in basic research on mathematical models of signaling and cellular information processing more generally.

My background is in biophysical models, machine learning, and signaling in cancer. I have a basic understanding of immunology, but no experience in experimental cell biology.

Response: We thank the reviewer for highlighting the novelty of our study. We appreciate the reviewer’s recognition that our work advances the understanding of cellular information processing in the context of ligand mixtures, particularly as the first to extend computational models to investigate signaling fidelity under mixed-ligand conditions.

We agree that this work will interest computational biologists focused on signaling network modeling and information processing. In addition, we believe it will also be valuable for all signaling biologists, as we provide fundamental insights. For experimental biologists in particular, our model provides an efficient, quantitative framework for exploring and generating testable hypotheses.

We would also like to gently emphasize that evaluating specificity within signaling pathways is as essential as studying downstream functional responses. While immune function outcomes are certainly important, they rely on the upstream signaling pathways that first respond to environmental cues. Understanding how these signaling pathways achieve specificity and discriminability is therefore crucial. For example, this is particularly relevant for drug development targeting pathways such as NFκB, where assessing the direct signaling output—NFκB activation dynamics—can provide valuable insight into the effects of pharmacological interventions.

Reviewer #2

Evidence, reproducibility and clarity

Guo et al. developed a heterogeneous, single-cell ODE model of NFκB signaling parameterized on five individual ligands (TNF, Pam, LPS, CpG, pIC) and extended it, via core-module parameter matching, to predict responses to all 31 combinations of up to five ligands. They found that simulated responder fractions and signaling codon features generally agreed with live-cell imaging data. A notable discrepancy emerged for the CpG (TLR9) + pIC (TLR3) pair: experiments exhibited non-integrative antagonism unpredicted by the original model. This issue was resolved by incorporating a Hill-type term for competitive, limited endosomal trafficking of these ligands. Finally, by decomposing NFκB trajectories into six "signaling codons" and applying Wasserstein distances plus random-forest and LSTM classifiers, the authors showed that stimulus-response specificity (SRS) declines with ligand complexity but remains statistically significant even for quintuple mixtures. This is a well written and scientifically sound manuscript about complexities of cellular signaling, especially considering the limitations of in vitro experiments in recapitulating in vivo dynamics.

Response: We thank the reviewer for carefully reading the manuscript and for this endorsement. We have significantly improved the manuscript thanks to the reviewer’s insightful comments (see below for point-to-point responses).

Besides addressing the reviewer’s questions, we have further extended our work to investigate how ligand pairs interact across all doses and how those interactions affect stimulus-response specificity. As the reviewer pointed out, experimental studies are limited in recapitulating the multitude of complex physiological contexts. The model is helpful to explore more complex scenarios beyond the feasibility of in-vitro experimental setups. Using computational simulations, we have further explored 360 conditions generated from 10 ligand pairs, each evaluated at 6 doses spanning non-responsive to saturating levels, and with each condition considered 1000 cells to capture the heterogeneity of the population.

From this extended analysis, we identified the mechanistic bases for observations of both synergy and antagonism. Synergy for certain low-dose ligand combinations can be explained by ultrasensitive IKK activation (Figure 4), while antagonism between LPS and Pam arises from competition for the cofactor CD14 (Figure 5). We show that these phenomena are dependent on the signaling network state and therefore are not observed in all cells of the population. We define the network conditions that must be met for antagonism and synergy to occur. Importantly, we then show that antagonism can contribute to stimulus-response specificity in ligand mixtures (Figure 5).

Here are a few comments and recommendations:

1. The modeling approach used in this manuscript, while interesting, might need further validation. Inferring multi-ligand receptor parameters by matching single-ligand cells on core-module similarity may not capture true co-variation in receptor expression or adaptor availability. Single cell measurements of receptor expressions could be done (e.g. via flow cytometry) to ground this assumption in real data. If the authors think this is out of scope for this manuscript, they could fit core-matched single cell models with two receptor modules from scratch to the two-ligand experimental data. Would this fitted model produce similar receptor parameters compared to the presented approach? At least the authors should add a bit more explanation for why their modeling approach is better (or valid) than fitting the models with 2/3/4/5 receptor modules from scratch to the experimental data.

Response: We thank the reviewer for this comment, this helped us improve the explanation of the methodology, the rationale, and the validation. The methodology is based on the well-established statistical method of nearest-neighbor hot-deck imputation (Andridge and Little, 2010). In this implementation, the core module functions as a stabilizing “anchor” (common variables) to harmonize various receptor-specific parameter distributions. Similar methodologies have been successfully applied to correct batch effects or integrate single-cell RNAseq datasets using anchor cell types (Stuart et al., 2019). Our workflow has been validated on single-ligand stimuli conditions in a previous study (Guo et al., 2025) (See below 3rdparagraph). Here, we used this method to generate predictions for ligand mixtures and have validated them with experimental studies of the dual-ligand stimuli, and we found that our predictions align well with the experimental data. As the reviewer suggested in point 3, in the revision, we also added experimental validation on the binary classifiers of macrophage determines whether specific stimuli are presented in the ligand mixture. The question we are interested in in this work is how macrophage process ligand-specific information in the context of ligand mixtures. For this question, the experimental results align with the model predictions, reaching consistent conclusions.

In the revision, we have explained the rationale for using the nearest-neighbor hot-deck imputation by matching cells with similar core module (Lines 143-150).

“Previous work determined parameter distributions for only the cognate receptor module (and the core module) that provided the best fit for the single ligand experimental data (Figure 1A, Step 1), and other receptor modules parameter information is missing. To simulate stimulus responses to more than two ligands, we imputed the other ligand–receptor module parameters using shared core-module parameters as common variables and employing nearest-neighbor hot-deck imputation (35). In this setup, the core module functions as an “anchor” to harmonize two or more receptor-specific parameter distributions. This was achieved by by minimizing Euclidean distance between the core module parameters associated with the independently parameterized single-ligand models (Figure 1A, Step 2). ”

In Guo et al. (2025) (see Supplementary Figure S11), the nearest-neighbor hot-deck imputation approach (core module similarity matching method) was compared with other approaches, including random matching and rescaled-similarity matching. The results show that, after matching, the core module method best preserves the single-ligand stimulus signaling codon distributions. For the reviewer’s convenience, we have also appended the figure in the response to Reviewer 1, Comment 11.

The advantage of our workflow is that it does not need to be fit to new experimental data and still gives reliable predictions on signaling dynamics. For the reviewer’s interest, we have tried to fit core-matched single cell models with two receptor modules. As fitting parameters require sufficiently large and high-quality datasets, single-ligand stimulation data with more than 1,000 cells can be adequate to estimate 6~7 parameters (Guo et al., 2025) (approx. 1400 cells to 2000 cells per ligand). However, our current experimental dataset for combinatorial-ligand conditions contains only 500~1,000 cells, and we have tested these datasets but results show a poor fit of heterogeneous signaling dynamics. This is due to an insufficient number of cells for estimating 8~10 parameters. We estimate that at least ~1,500 cells would be needed for reliable parameter estimation under dual-ligand stimulation (and more cells may be needed for combinatorial ligand stimuli involving more ligands). This is currently not feasible to obtain for mixed ligands given the large number of combinatorial conditions.

Overall, in this paper, the nearest-neighbor hot-deck imputation approach is presented as a feasible and acceptable approach that best reflects our current understanding of the signaling network. Importantly, it helps identify potential gaps by highlighting discrepancies between model predictions and experimental observations.

(a) The refined model posits competitive, saturable endosomal transport for CpG and pIC, but no direct measurements of endosomal uptake rates or compartmental saturation thresholds are provided, leaving the Hill parameters under-constrained. The authors could produce dose-response curves for CpG and pIC individually and in combination across a range of concentrations to fit the Hill parameters for competitive uptake. (b) If this is out of scope for this paper, the authors should at least comment on why the endosome hypothesis is better than others e.g. crosstalks and other parallel pathway activations. Especially given that even the refined model simulations with Hill equations for CpG and pIC do not quite match with the experimental data (Fig 2 B,E).

Response: (a) The reviewer’s comments helped us to improve our work by employing the Michaelis-Menten Kinetics for substrate competition reactions, which increases the mathematic rigor of the CpG-pIC competition model. In this updated model, there is no free parameters to tune, as all the Vmax, Kd, should be consistent with the single-ligand scenario. And the Hill is same as single-ligand case, equal to 1.

The comments on examining dose-response curves for CpG and pIC inspired us to extend the dose-response curves for all ligand pair combination, allowing us to identify the synergy in low-dose ligand pairs and antagonism for high-dose LPS-Pam, besides CpG-pIC (new Figure 4 & 5).

(b) Regarding alternative hypotheses for antagonism—such as crosstalk or parallel-pathway activation: any antagonistic effect would have to arise from negative regulation acting within the first 30 min. However, IκBα-mediated feedback only becomes appreciable after ~30 min (Hoffmann et al., 2002), and A20-dependent attenuation requires ≥2 h (Werner et al., 2005). Beyond these delayed feedback, NFκB activation depends primarily on phosphorylation and K63-linked ubiquitination, for which no mechanism produces true antagonism; at most, combinatorial inputs saturate the response to the level of the strongest single ligand. We have added this rationale to the Discussion to explain why we favor the endosome saturation hypothesis over other mechanisms (Lines 459-465). While this may not capture every nuance, it represents the simplest model extension capable of reproducing the observed antagonism.

Authors asses the distinguishability of single-ligand stimuli and combinatorial ligands stimuli using the simulations from the refined model. While this is informative, the simulated data could propagate deviations from the experimental data to the classifiers. How would the classifiers fare when the experimental data is used to assess the single-stimulus distinguishability? The authors could use the experimental data they already have and confirm their main claim of the paper, that cells retain stimulus-response specificity even with multiple ligand exposure. In short, how would Fig 3E look when trained/validated on available experimental data?

Response: We thank the reviewer’s valuable comments, and they helped us strengthen the rigor of our analysis by incorporating cross-model testing. Specifically, we refined our analysis of ligand presence/absence classification by including ROC AUC and balanced accuracy metrics. This adjustment accounts for the fact that the experimental data did not cover all combinatorial conditions, thereby mitigating potential biases from data imbalance and threshold choice. The experimental results are qualitatively consistent with the simulations, though—as expected—they show somewhat lower ligand distinguishability compared to the noise-free simulated dataset. We have updated Figures 3E–F (previously Figure 3E), added Figure S8, and revised the manuscript accordingly (Lines 292–301). For the reviewer’s convenience, we have also pasted in the revised manuscript text below.

“Classifiers trained to distinguish TNF-present from TNF-absent conditions achieved a Receiver Operating Characteristic-Area Under the Curve (ROC AUC) of 0.96, significantly above the 0.5 baseline (Figure 3D, Figure S8A). Extending this analysis to other ligands, cells detected LPS (0.85), Pam (0.84), pIC (0.73), and CpG (0.63) in mixtures (Figure 3D, S8A). Using experimental data from double- and triple-ligand stimuli (Figure 1D), ROC AUC values were TNF 0.74, LPS 0.74, Pam 0.66, pIC 0.75, and CpG 0.66 (Figure 3E, S8B). Classifier accuracies yielded consistent results (Figure S8C-D). These results indicated a remarkable capability of preserving ligand-specific dynamic features within complex NFκB signal trajectories that enable nuclear detection of extracellular ligands even in complex stimulus mixtures.”

While the approach of presented here with multiple simultaneous ligand exposures is a major step towards the in vivo-like conditions, the temporal aspect is still missing. That is, temporal phasing i.e. sequential exposure to multiple ligands as one would expect in vivo rather than all at once. This is probably out of scope for this paper but the authors could comment how how their work could be taken forward in such direction and would the SRS be better or worse in such conditions. Response: We thank the reviewer for this insightful comment. We have added “the temporal aspect of multiple ligand exposures” to the discussion (Lines 503-510), and we pasted the corresponding paragraph here for reviewer’s references (black fonts are previous version, and blue fonts is the revised new texts):

“Cells may be expected to interpret not only the combination of signals but also their timing and duration to mount appropriate transcriptional responses (58, 59). For example, acute inflammation integrates pathogen-derived cues with pro- and anti-inflammatory signals over a timeframe of hours to days (58), to coordinate the pathogen removal and tissue repairing process. Investigating sequential stimulus combinations in our model is therefore crucial for understanding how cells process complex physiological inputs. Simulations that account for longer timescales may require additional feedback mechanisms, as described in some of our previous studies for NFκB (15, 60). ** ”

There is no caption for Figure 3F in the figure legend nor a reference in the main text.

Response: In the revised manuscript we actually removed Figure 3F.

Significance

General assessment: This is a good manuscript in it's present form which could get better with revision. There needs more supporting data and validation to back the main claim presented in the manuscript.

Significance/impact/readership: When revised this manuscript could be of interest to a broad community involving single cells biology, cell and immune signaling, and mathematical modeling. Especially the models presented here could be used a starting point to more complex and detailed modeling approaches.

Response: We thank the reviewer for this endorsement. The reviewer’s constructive suggestion helped us significantly improve the clarity and rigor of our main conclusion.

In summary, we have strengthened the computational framework in several ways. We improved the model’s fit to experimental single-ligand training data and reformulated the antagonistic CpG-pIC model using Michaelis–Menten kinetics, thereby reducing parameter arbitrariness and increasing mechanistic interpretability. These changes led to better agreement between model predictions and experimental observations for combinatorial ligand responses (Updated Figure 2 and Figure S2), which we hope will further increase experimentalists’ confidence in the modeling results. We have also validated one key conclusion (“cells retain stimulus-response specificity even with multiple ligand exposure”) using the experimental dataset, and it aligns with the model predictions.

In addition, we have further extended our analysis and the scope. Inspired by the reviewer’s advice (and Reviewer 3’s comment 1b) on dose-combination study for CpG-pIC pair, we expanded our research to dose-response relationships for all dual-ligand combinations (Lines 302-406, Figure 4-5). This additional comprehensive analysis allowed us to identify the mechanism of synergistic and antagonistic effects in single-cell responses and to pinpoint the corresponding dose ranges among different ligand pairs.

Interestingly, we found that IKK ultrasensitive activation may lead to low-dose ligand combinations synergistic response for single cells. We also found that CD14 uptake competition between LPS and Pam may lead to antagonistic/non-integrative combination. Our simulation-based finding of non-integrative combination of LPS-Pam stimuli aligns with previous independent experimental finding of non-integrative response for LPS and Pam combination (Kellogg et al., 2017), and this independent experimental study validated our model prediction.

We further analyzed stimulus-response specificity under conditions predicted to exhibit synergy or antagonism. Our results indicate that antagonistic combinations of ligands can increase stimulus-response specificity in the context of ligand mixtures.

Reviewer #3

Evidence, reproducibility and clarity

The authors investigate experimentally single macrophages' NF-kB responses to five ligands, separately and to 3 pairs of ligands. Using the single ligand stimulations, they train an existing mathematical model to replicate single-cell NF-kB nuclear trajectories. From what I understand, for each single cell trajectory in response to a given ligand, the best fit parameters of the core module and the receptor module (specific for the given ligand) are found.

Then (again, from what I understand), single ligand models are used to generate responses to combinations of ligands. The parametrizations of single ligand models (to be combined) are chosen to have the most similar core modules. It is not described how the responses to more than one ligand are calculated - I expect that respective receptor modules work in parallel, providing signals to the core module. After observing that the response to CpG+pIC is lower (in terms of duration and total) than for CpG alone, the model is modified to account for competition for endosomal transport required by both ligands.

Having the trained model, simulations of responses to all 31 combinations of ligands are performed, and each NF-κB trajectory is described by six signaling codons-Speed, Peak, Duration, Total, Early vs. Late, and Oscillations. Next, these codons are used to reconstruct (using a random forest model) the stimuli (which may be the combination of ligands). The single and even the two ligand stimuli are relatively well recognized, which is interpreted as the ability of macrophages to distinguish ligands even if present in combination.

We thank the reviewer for careful reading of the manuscript.

Major comments

1) The demonstrated ability to recognize stimuli is based on several key assumptions that can hardly be met in reality.

Response: We thank the reviewer for this comment, which prompted us to carefully reflect on the rigor of our work, inspired us to extend our analysis to a broad range of ligand-dose combinations, and helped us improve clarifying the limitations of our approach. Please see our detailed responses below.

a) The cell knows the stimulation time, and then it can use speed as a codon. Look on fig. S4A: The trajectories in response to plC are similar to those in response to TNF, but just delayed. Response: We thank the reviewer for this comment. We updated the model parameterization to better fit to the single-ligand pIC condition (Lines 557-559). In the updated model, the simulated responses to TNF and pIC are quite different (Fig. S2A-B, Fig. S5A-B). Specifically, the Peak, Duration, EarlyVsLate, and Total signaling codons have different values. In addition, the literature suggests that timing difference of NFκB activation are sufficient to elicit differences in downstream gene expression responses, especially for the early response genes (ERG) and intermediate response genes (ING) (Figure 1 in Ando, et al, 2021). For reviewer’s convenience, we have also appended the figures. Specifically, within the first 60 minutes, ctrl exhibit higher Speed of NFκB activation, and the NFκB regulated ERG and ING show differences in the first 60 minutes (Below Fig 1a,b). Ando et al then identified the gene regulatory mechanism that is able to distinguish between differences in the Speed codon. Importantly, this mechanism does not require knowledge of t=0, i.e. when the timer was started.

The signaling codon Speed, which is based on derivatives, is one way to quantify such timing differences in activation. It was selected from a library of more than 900 different dynamic features using an information maximizing algorithm (Adelaja et al., 2021). It is possible that other ways of measuring time, e.g. time to half-max, might not be distinguished that well by these regulatory mechanisms.

b) The increase of stimulus concentration typically increases Peak, Duration, and Total, so a similar effect can be achieved by changing the ligand or concentration. Response: This (“the increase of stimulus concentration typically increases Peak, Duration, and Total”) is not an assumption. What the reviewer described (“a similar effect can be achieved by changing the ligand or concentration”) may occur or may not. The six informative signaling codons can vary under different ligands or doses. For example, with increasing doses of Pam, the NFκB response shows a higher peak, potentially making it appear more like LPS stimulation. However, as the Pam dose increases, the response duration decreases, which distinguishes it from LPS stimulation (See experimental data shown in Figure 4A, second row, and Figure 3A, second row in Luecke et al., (2024), we also pasted the corresponding figure below for reviewer’s convenience).

Figure 4A and Figure 3A from Luecke et al., (2024). Figure 4A: NFκB activity dynamics in the single cells in response to 0, 0.01, 0.1, 1, 10, and 100 ng/ml P3C4 stimulation. Eight hours were measured by fluorescence microscopy of reporter hMPDMs. Each row of the heatmap represents the p38 or NFκB signaling trajectory of one cell. Trajectories are sorted by the maximum amplitude of p38 activity. Data from two pooled biological replicates are depicted. Total # of cells: 898, 834, 827, 787, 778, and 923. Figure 3A: NFκB activity dynamics in the single cells in response to 100 ng/ml LPS stimulation. Eight hours were measured by fluorescence microscopy of reporter hMPDMs. Each row of the heatmap represents the NFκB signaling trajectory of one cell (with p38 measured shown in the original paper). Trajectories are sorted by the maximum amplitude of p38 activity. Data from two pooled biological replicates are depicted.

Inspired by the reviewer’s comment (and also Reviewer 2’s comments), in the revision, we expanded our research to dose-response relationships for all dual-ligand combinations (Lines 302-406, Figure 4-5). This additional comprehensive analysis allowed us to identify the mechanism of synergistic and antagonistic effects in single-cell responses and to pinpoint the corresponding dose ranges among different ligand pairs.

Interestingly, we found that IKK ultrasensitive activation may lead to synergistic responses to low-dose ligand combinations but only in a subset of single cells. We also found that CD14 uptake competition between LPS and Pam may lead to antagonistic/non-integrative combination. Our simulation-based finding of non-integrative combination of LPS-Pam stimuli aligns with previous independent experimental findings of non-integrative response for LPS and Pam combination (Kellogg et al., 2017).

c) Distinguishing a given ligand in the presence of some others, even stronger bases, on the assumption that these ligands were given at the same time, which is hardly justified. Response: We agree with the reviewer that ligands could be given at different times. Considering time delays between ligands (the inset and also removal) dramatically adds to the combinatorial complexity. Some initial studies by the Tay lab are beginning to explore some scenarios of time-shifted ligand pairs (Wang et al 2025). Here we focus on a systematic exploration of all ligand combinations at 6 different doses. The fact that we do not consider time delays is not an assumption but admittedly a limitation that may well be addressed in future studies. We have included a brief discussion of this issue in the discussion (Lines 503-514). We’ve appended here for reviewer’s convenience.

“Cells may be expected to interpret not only the combination of signals but also their timing and duration to mount appropriate transcriptional responses (Kumar et al., 2004; Son et al., 2023). For example, acute inflammation integrates pathogen-derived cues with pro- and anti-inflammatory signals over a timeframe of hours to days (Kumar et al., 2004), to coordinate the pathogen removal and tissue repairing process. Investigating sequential stimulus combinations in our model is therefore crucial for understanding how cells process complex physiological inputs. Simulations that account for longer timescales may require additional feedback mechanisms, as described in some of our previous studies for NFκB (Werner et al., 2008, 2005). ”

We would like to suggest that despite (or maybe because) limiting our study to coincident stimuli, we made some noteworthy discoveries.

2) For single ligands, it would be nice to see how the random forest classifier works on experimental data, not only on in silico data (even if generated by a fitted model).

Response: This comment and Reviewer 2 comment 3 have helped us strengthen the rigor of our analysis by incorporating cross-model testing. We pasted the response below.

Specifically, we refined our analysis of ligand presence/absence classification by including ROC AUC and balanced accuracy metrics. This adjustment accounts for the fact that the experimental data did not cover all combinatorial conditions, thereby mitigating potential biases from data imbalance and threshold choice. The experimental results are qualitatively consistent with the simulations, though—as expected—they show somewhat lower ligand distinguishability compared to the noise-free simulated dataset. We have updated Figures 3E–F (previously Figure 3E), added Figure S8, and revised the manuscript accordingly (Lines 292–301). For the reviewer’s convenience, we have also included the revised manuscript text below.

“Classifiers trained to distinguish TNF-present from TNF-absent conditions achieved a Receiver Operating Characteristic-Area Under the Curve (ROC AUC) of 0.96, significantly above the 0.5 baseline (Figure 3D, Figure S8A). Extending this analysis to other ligands, cells detected LPS (0.85), Pam (0.84), pIC (0.73), and CpG (0.63) in mixtures (Figure 3D, S8A). Using experimental data from double- and triple-ligand stimuli (Figure 1D), ROC AUC values were TNF 0.74, LPS 0.74, Pam 0.66, pIC 0.75, and CpG 0.66 (Figure 3E, S8B). Classifier accuracies yielded consistent results (Figure S8C-D). These results indicated a remarkable capability of preserving ligand-specific dynamic features within complex NFκB signal trajectories that enable nuclear detection of extracelular ligands even in complex stimulus mixtures.”

3) My understanding of ligand discrimination is such that it is rather based on a combination of pathways triggered than solely on a single transcription factor response trajectory, which varies with ligand concentration and ligand concentration time profile (no reason to assume it is OFF-ON-OFF). For example, some of the considered ligands (plC and CpG) activate IRF3/IRF7 in addition to NF-kB, which leads to IFN production and activation of STATs. This should at least be discussed.

Response: We thank the reviewer for this comment and fully agree. In the previous version, we discussed different signaling pathways combinatorically distinguishing stimulus. In the revision, we have extended this discussion to include the example of pIC and CpG activation, as suggested (Lines 515-522). We pasted the corresponding text below.

“Furthermore, innate immune responses do not solely rely on NFκB but also involve the critical functions of AP1, p38, and the IRF3-ISGF3 axis. The additional pathways are likely activated in a coordinated manner and provide additional information (Luecke et al., 2021). This is exemplified by the studies demonstrating synergistic effects between CpG and pIC in inhibiting tumor growth and promoting cytokine production (Huang et al., 2020), such as IFNβ and TNFα, whose expression is also regulated by the IRF and MAPK signaling pathways (Luecke et al., 2021; Sheu et al., 2023). Therefore the inclusion of parallel pathways of AP1 and MAPK, as well as the type I interferon network (Cheng et al., 2015; Davies et al., 2020; Hanson and Batchelor, 2022; Luecke et al., 2024; Paek et al., 2016; Peterson et al., 2022) are next steps for expanding the mathematical models presented here.”

Technical comments

1) Reference 25: X. Guo, A. Adelaja, A. Singh, W. Roy, A. Hoffmann, Modeling single-cell heterogeneity in signaling dynamics of macrophages reveals principles of information transmission. Nature Communications (2025) does not lead to any paper with the same or a similar title and author list. This Ref is given as a reference to the model. Fortunately, Ref 8 is helpful. Nevertheless, authors should include a schematic of the model.

Response: We apologize for the paper not being accessible on time. It is now. We have also added a schematic of the model as suggested (Figure S1) and have added detailed description of the model and simulations in introduction (Lines 95-106), results (Lines 129-141), and methods (Simulation of heterogenous NFκB dynamical responses).

2) Also Mendeley Data DOI:10.17632/bv957x6frk.1 and GitHub https://github.com/Xiaolu-Guo/Combinatorial_ligand_NFkB lead to nowhere.

Response: We thank the reviewer for this comment, and we have made the GitHub codes public. Mendeley Data DOI:10.17632/bv957x6frk.1 can be accessed via the shared link: https://data.mendeley.com/preview/bv957x6frk?a=6d56e079-d7b0-482e-951f-8a8e06ee8797

and will be public once the paper accepted.

3) Dataset 1 is not described. Possibly it contains sets of parameters of receptor modules (different numbers of sets for each module, why?), but the names of parameters never appear in the text, which makes it impossible to reproduce the data.

Response: We thank the reviewer for this comment, and we have added the description of the dataset (S3 SupplementaryDataset2_NFkB_network_single_cell_parameter_distribution.xlsx) and added the parameter names in the methods (Simulation of heterogenous NFκB dynamical responses).

4) It is difficult to understand how the simulations in response to more than one ligand are performed.

Response: We thank the reviewer for this comment, and we have improved the explanation of the methods (Results, Lines 145-152) and included a detailed description of the model and simulations for combinatorial ligands (Methods, Predicting heterogeneous single-cell responses to combinatorial-ligand stimulation).

Significance

A lot of work has been done, the methodology is interesting, but the biological conclusions are overstated.

Response: We thank the reviewer for their interest in the methodology. We have revised the title, the abstract, and added the discussion about our finding to more accurately document what we have found. In the revision, we have increased the clarity and rigor of the work. For the key conclusion that macrophages maintain some level of NFκB signaling fidelity in response to ligand mixtures, we have validated the binary classifier results on experimental data as reviewer suggested.

In the revision, we have also extended our methodology to explore further, the dose-response curves for different dosage combination for ligand pairs. This further work allowing us identified the synergistic and antagonistic regimes. By comparing the stimulus response specificity for antagonistic model vs the non-antagonistic model, we demonstrated that signaling antagonism may increase the distinguishability of presence or absence of specific ligands within complex ligand mixtures. This provides a mechanism of how signaling fidelity is maintained to the surprising degree we reported.

REFERENCES

Adelaja, A., Taylor, B., Sheu, K.M., Liu, Y., Luecke, S., Hoffmann, A., 2021. Six distinct NFκB signaling codons convey discrete information to distinguish stimuli and enable appropriate macrophage responses. Immunity 54, 916-930.e7. https://doi.org/10.1016/j.immuni.2021.04.011

Akira, S., Takeda, K., 2004. Toll-like receptor signalling. Nat Rev Immunol 4, 499–511. https://doi.org/10.1038/nri1391

Andridge, R.R., Little, R.J.A., 2010. A Review of Hot Deck Imputation for Survey Non-response. Int Stat Rev 78, 40–64. https://doi.org/10.1111/j.1751-5823.2010.00103.x

Cheng, Z., Taylor, B., Ourthiague, D.R., Hoffmann, A., 2015. Distinct single-cell signaling characteristics are conferred by the MyD88 and TRIF pathways during TLR4 activation. Sci Signal 8, ra69. https://doi.org/10.1126/scisignal.aaa5208

Davies, A.E., Pargett, M., Siebert, S., Gillies, T.E., Choi, Y., Tobin, S.J., Ram, A.R., Murthy, V., Juliano, C., Quon, G., Bissell, M.J., Albeck, J.G., 2020. Systems-Level Properties of EGFR-RAS-ERK Signaling Amplify Local Signals to Generate Dynamic Gene Expression Heterogeneity. Cell Systems 11, 161-175.e5. https://doi.org/10.1016/j.cels.2020.07.004

Guo, X., Adelaja, A., Singh, A., Roy, W., Hoffmann, A., 2025a. Modeling single-cell heterogeneity in signaling dynamics of macrophages reveals principles of information transmission. Nature Communications.

Guo, X., Adelaja, A., Singh, A., Wollman, R., Hoffmann, A., 2025b. Modeling heterogeneous signaling dynamics of macrophages reveals principles of information transmission in stimulus responses. Nat Commun 16, 5986. https://doi.org/10.1038/s41467-025-60901-3

Hanson, R.L., Batchelor, E., 2022. Coordination of MAPK and p53 dynamics in the cellular responses to DNA damage and oxidative stress. Molecular Systems Biology 18, e11401. https://doi.org/10.15252/msb.202211401

Huang, Y., Zhang, Q., Lubas, M., Yuan, Y., Yalcin, F., Efe, I.E., Xia, P., Motta, E., Buonfiglioli, A., Lehnardt, S., Dzaye, O., Flueh, C., Synowitz, M., Hu, F., Kettenmann, H., 2020. Synergistic Toll-like Receptor 3/9 Signaling Affects Properties and Impairs Glioma-Promoting Activity of Microglia. J. Neurosci. 40, 6428–6443. https://doi.org/10.1523/JNEUROSCI.0666-20.2020

Kellogg, R.A., Tian, C., Etzrodt, M., Tay, S., 2017. Cellular Decision Making by Non-Integrative Processing of TLR Inputs. Cell Rep 19, 125–135. https://doi.org/10.1016/j.celrep.2017.03.027

Kumar, R., Clermont, G., Vodovotz, Y., Chow, C.C., 2004. The dynamics of acute inflammation. Journal of Theoretical Biology 230, 145–155. https://doi.org/10.1016/j.jtbi.2004.04.044

Luecke, S., Guo, X., Sheu, K.M., Singh, A., Lowe, S.C., Han, M., Diaz, J., Lopes, F., Wollman, R., Hoffmann, A., 2024. Dynamical and combinatorial coding by MAPK p38 and NFκB in the inflammatory response of macrophages. Molecular Systems Biology 20, 898–932. https://doi.org/10.1038/s44320-024-00047-4

Luecke, S., Sheu, K.M., Hoffmann, A., 2021. Stimulus-specific responses in innate immunity: Multilayered regulatory circuits. Immunity 54, 1915–1932. https://doi.org/10.1016/j.immuni.2021.08.018

Paek, A.L., Liu, J.C., Loewer, A., Forrester, W.C., Lahav, G., 2016. Cell-to-Cell Variation in p53 Dynamics Leads to Fractional Killing. Cell 165, 631–642. https://doi.org/10.1016/j.cell.2016.03.025

Peterson, A.F., Ingram, K., Huang, E.J., Parksong, J., McKenney, C., Bever, G.S., Regot, S., 2022. Systematic analysis of the MAPK signaling network reveals MAP3K-driven control of cell fate. Cell Systems 13, 885-894.e4. https://doi.org/10.1016/j.cels.2022.10.003

Sheu, K.M., Guru, A.A., Hoffmann, A., 2023. Quantifying stimulus-response specificity to probe the functional state of macrophages. Cell Systems 14, 180-195.e5. https://doi.org/10.1016/j.cels.2022.12.012

Son, M., Wang, A.G., Keisham, B., Tay, S., 2023. Processing stimulus dynamics by the NF-κB network in single cells. Exp Mol Med 55, 2531–2540. https://doi.org/10.1038/s12276-023-01133-7

Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W.M., Hao, Y., Stoeckius, M., Smibert, P., Satija, R., 2019. Comprehensive Integration of Single-Cell Data. Cell 177, 1888-1902.e21. https://doi.org/10.1016/j.cell.2019.05.031

Werner, S.L., Barken, D., Hoffmann, A., 2005. Stimulus Specificity of Gene Expression Programs Determined by Temporal Control of IKK Activity. Science 309, 1857–1861. https://doi.org/10.1126/science.1113319

Werner, S.L., Kearns, J.D., Zadorozhnaya, V., Lynch, C., O’Dea, E., Boldin, M.P., Ma, A., Baltimore, D., Hoffmann, A., 2008. Encoding NF-kappaB temporal control in response to TNF: distinct roles for the negative regulators IkappaBalpha and A20. Genes Dev 22, 2093–2101. https://doi.org/10.1101/gad.1680708

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Referee #3

Evidence, reproducibility and clarity

The authors investigate experimentally single macrophages' NF-kB responses to five ligands, separately and to 3 pairs of ligands. Using the single ligand stimulations, they train an existing mathematical model to replicate single-cell NF-kB nuclear trajectories. From what I understand, for each single cell trajectory in response to a given ligand, the best fit parameters of the core module and the receptor module (specific for the given ligand) are found. Then (again, from what I understand), single ligand models are used to generate responses to combinations of ligands. The parametrizations of single ligand models (to be combined) are chosen to have the most similar core modules. It is not described how the responses to more than one ligand are calculated - I expect that respective receptor modules work in parallel, providing signals to the core module. After observing that the response to CpG+pIC is lower (in terms of duration and total) than for CpG alone, the model is modified to account for competition for endosomal transport required by both ligands.

Having the trained model, simulations of responses to all 31 combinations of ligands are performed, and each NF-κB trajectory is described by six signaling codons-Speed, Peak, Duration, Total, Early vs. Late, and Oscillations. Next, these codons are used to reconstruct (using a random forest model) the stimuli (which may be the combination of ligands). The single and even the two ligand stimuli are relatively well recognized, which is interpreted as the ability of macrophages to distinguish ligands even if present in combination.

Major comments

1. The demonstrated ability to recognize stimuli is based on several key assumptions that can hardly be met in reality.

a) The cell knows the stimulation time, and then it can use speed as a codon. Look on fig. S4A: The trajectories in response to plC are similar to those in response to TNF, but just delayed.

b) The increase of stimulus concentration typically increases Peak, Duration, and Total, so a similar effect can be achieved by changing the ligand or concentration.

c) Distinguishing a given ligand in the presence of some others, even stronger bases, on the assumption that these ligands were given at the same time, which is hardly justified. 2. For single ligands, it would be nice to see how the random forest classifier works on experimental data, not only on in silico data (even if generated by a fitted model). 3. My understanding of ligand discrimination is such that it is rather based on a combination of pathways triggered than solely on a single transcription factor response trajectory, which varies with ligand concentration and ligand concentration time profile (no reason to assume it is OFF-ON-OFF). For example, some of the considered ligands (plC and CpG) activate IRF3/IRF7 in addition to NF-kB, which leads to IFN production and activation of STATs. This should at least be discussed.

Technical comments

1. Reference 25: X. Guo, A. Adelaja, A. Singh, W. Roy, A. Hoffmann, Modeling single-cell heterogeneity in signaling dynamics of macrophages reveals principles of information transmission. Nature Communications (2025) does not lead to any paper with the same or a similar title and author list. This Ref is given as a reference to the model. Fortunately, Ref 8 is helpful. Nevertheless, authors should include a schematic of the model.
2. Also Mendeley Data DOI:10.17632/bv957x6frk.1 and GitHub https://github.com/Xiaolu-Guo/Combinatorial_ligand_NFkB lead to nowhere.
3. Dataset 1 is not described. Possibly it contains sets of parameters of receptor modules (different numbers of sets for each module, why?), but the names of parameters never appear in the text, which makes it impossible to reproduce the data.
4. It is difficult to understand how the simulations in response to more than one ligand are performed.

Significance

A lot of work has been done, the methodology is interesting, but the biological conclusions are overstated.

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Referee #2

Evidence, reproducibility and clarity

Guo et al. developed a heterogeneous, single-cell ODE model of NFκB signaling parameterized on five individual ligands (TNF, Pam, LPS, CpG, pIC) and extended it, via core-module parameter matching, to predict responses to all 31 combinations of up to five ligands. They found that simulated responder fractions and signaling codon features generally agreed with live-cell imaging data . A notable discrepancy emerged for the CpG (TLR9) + pIC (TLR3) pair: experiments exhibited non-integrative antagonism unpredicted by the original model. This issue was resolved by incorporating a Hill-type term for competitive, limited endosomal trafficking of these ligands. Finally, by decomposing NFκB trajectories into six "signaling codons" and applying Wasserstein distances plus random-forest and LSTM classifiers, the authors showed that stimulus-response specificity (SRS) declines with ligand complexity but remains statistically significant even for quintuple mixtures. This is a well written and scientifically sound manuscript about complexities of cellular signaling, especially considering the limitations of in vitro experiments in recapitulating in vivo dynamics. Here are a few comments and recommendations:

1. The modeling approach used in this manuscript, while interesting, might need further validation. Inferring multi-ligand receptor parameters by matching single-ligand cells on core-module similarity may not capture true co-variation in receptor expression or adaptor availability. Single cell measurements of receptor expressions could be done (e.g. via flow cytometry) to ground this assumption in real data. If the authors think this is out of scope for this manuscript, they could fit core-matched single cell models with two receptor modules from scratch to the two-ligand experimental data. Would this fitted model produce similar receptor parameters compared to the presented approach? At least the authors should add a bit more explanation for why their modeling approach is better (or valid) than fitting the models with 2/3/4/5 receptor modules from scratch to the experimental data.
2. The refined model posits competitive, saturable endosomal transport for CpG and pIC, but no direct measurements of endosomal uptake rates or compartmental saturation thresholds are provided, leaving the Hill parameters under-constrained. The authors could produce dose-response curves for CpG and pIC individually and in combination across a range of concentrations to fit the Hill parameters for competitive uptake. If this is out of scope for this paper, the authors should at least comment on why the endosome hypothesis is better than others e.g. crosstalks and other parallel pathway activations. Especially given that even the refined model simulations with Hill equations for CpG and pIC do not quite match with the experimental data (Fig 2 B,E).
3. Authors asses the distinguishability of single-ligand stimuli and combinatorial ligands stimuli using the simulations from the refined model. While this is informative, the simulated data could propagate deviations from the experimental data to the classifiers. How would the classifiers fare when the experimental data is used to assess the single-stimulus distinguishability? The authors could use the experimental data they already have and confirm their main claim of the paper, that cells retain stimulus-response specificity even with multiple ligand exposure. In short, how would Fig 3E look when trained/validated on available experimental data?
4. While the approach of presented here with multiple simultaneous ligand exposures is a major step towards the in vivo-like conditions, the temporal aspect is still missing. That is, temporal phasing i.e. sequential exposure to multiple ligands as one would expect in vivo rather than all at once. This is probably out of scope for this paper but the authors could comment how how their work could be taken forward in such direction and would the SRS be better or worse in such conditions.
5. There is no caption for Figure 3F in the figure legend nor a reference in the main text.

Significance

General assessment: This is a good manuscript in it's present form which could get better with revision. There needs more supporting data and validation to back the main claim presented in the manuscript.

Significance/impact/readership: When revised this manuscript could be of interest to a broad community involving single cells biology, cell and immune signaling, and mathematical modeling. Especially the models presented here could be used a starting point to more complex and detailed modeling approaches.

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

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Referee #1

Evidence, reproducibility and clarity

The authors extend an existing mathematical model of NFkB signalling under stimulation of various single receptors, to model that describes responses to stimulation of multiple receptors simultaneously. They compare this model to experimental data derived from live-cell imaging of mouse macrophages, and modify the model to account for potential antagonism between TLR3 and TLR9 response due to competition for endosomal transport. Using this framework they show that, despite distinguishability decreasing with increasing numbers of heterogenous stimuli, macrophages are still able in principle to distinguish these to a statistically significant degree. I congratulate the authors on an interesting approach that extends and validates an existing mathematical model, and also provides valuable information regarding macrophage response.

There are no major issues affecting the scientific conclusions of the paper, however the lack of detail surrounding the mathematical model and the 'signaling codons' that are used throughout the paper make it difficult to read. This is exacerbated by the fact that I was unable to find Ref 25 which apparently describes the model, however I was able to piece together the essential components from the description in Ref 8 and the supplementary material.

Lots of the minor comments below stem from this, however there are also a few other places that could benefit from some additional clarification and explanation.

Significance:

'...it remains unclear complex...' -> '...it remains unclear whether complex...'

Introduction: 'temporal dynamics of NFkB' - it would be good to be more concrete regarding the temporal dynamics of what aspect of this (expression, binding, conformation, etc), if possible.

'signaling codons' - the behaviour of these is key to the entire paper, so even if they are well described in the reference, it would be good to have a short description as early as possible so that the reader can get an idea in their mind what exactly is being discussed here. Later, it would be good to have concrete description of exactly what these capture.

'This challenge...population of macrophages' - this seems a bit out of place, and is a bit of a run on sentence, so I suggest moving this to the next paragraph and working it into the first sentence there '...regulatory mechanisms, and this challenge could be addressed with a model parameterised to account for heterogeneous...Early models ...', or something similar.

Ref 25: I can't find a paper with this title anywhere, so if it's an accepted preprint then it would be good to have this available as well. That said, I still think it would be difficult to grasp the work done in this paper without some description of the mathematical model here, at least schematically, if not the full set of ODEs. For example, there are numerous references to how this incorporates heterogeneous responses, the 'core module', etc, and the reader has no context of these if they aren't familiar with the structure of the model.

'A key challenge which is...' -> 'A key challenge is...'

'With model simulation ...' -> a bit of a run on sentence, I suggest breaking after 'conditions'.

Results:

This section would benefit from a more in-depth description of the model and experimental setup. In particular for the experiment, the reader never really knows what this workflow for this is, nor what the model ingests as input, and what the predictions are of.

'..mechanistic model was trained...' - trained in this study, or in the previous referenced study?

'determined parameter distributions' - this is where it would be good to have more background on the model. What parameters are these, and what do they correspond to biologically? It would also be nice to see in the methods or supplementary material how this is done (maximum likelihood, etc).

'matching cells with similar core model...' - it's difficult to follow the logic as to why this is done, so I think this needs to be a little clearer. My guess would be that the assumption is that simulated cells with similar 'core' parameters have a similar downstream signalling response, and therefore the receptors can be 'transplanted'. So it would be nice to see exactly what these distributions are and what the effect of a bad match would be.

Some explanation of how this relates to the experimental data the parameters are fit on would also be useful. Is there a correspondence between individual simulated cells and the experimental data for the single ligand stimulation, and then the smallest set of these is taken? Is there also a matching from the simulated multi-receptor modules and the multi-receptor data, and if so, is this done in the same way?

'six signaling codons' - here it would be good to recapitulate what these represent, but also what the 'strength' and 'activity' correspond to (total integrated value, maximum value, etc)

'pre-defined thresholds' - no need to state these numerically in the text (although giving some sense of how/why these were chosen would give some context), but I couldn't find the values of these, nor values corresponding to the signaling codons.

'non-responder cells are likely a result of cellular heterogeneity in receptor modules rather than the core module' - is this the 'ill health' referenced earlier? If so make this clear.

It's also very difficult to follow this chain of logic, given that the reader at this point doesn't have any knowledge of what the 'core' module is, nor the significance of the thresholds on the signaling codons. I would suggest making this much clearer, with reference to each of these.

'...but the model represented these as independent mass action reactions' - the significance of this may not be clear to someone not familiar with biophysical models, so probably better to make it explicit.

'...we trained a random forest classifier...' - is this trained on the 'raw' experimental time series data, or on the signaling codons?

'We also applied a Long Short-Term Memory (LSTM) machine learning model...' - it might be good to reference these three approaches at the beginning of this section, otherwise they seem to come out of the blue a little.

'We then used machine learning classifiers...' - random forests, LSTMs, or a different model?

Discussion:

'...over statistical models...' - suggest maybe 'purely statistical models'

'We found that endosomal transport...' - A paper by Huang, et. al. (https://www.jneurosci.org/content/40/33/6428) observed a synergistic phagocytic response between CpC and pIC stimulation in microglia. This is still consistent with a saturation effect dependent on dose, but may be worth a mention.

'...features termed...' -> 'features, termed'

'...we applied a Long Short-Term Memory (LSTM) machine learning model..' - maybe make clear that this is on the time-series data (also LSTM has already been defined).

Materials and methods:

The descriptions in this section are quite vague, so I would suggest expanding this with more detail from the supplementary material, where things are quite well explained.

'sampling distribution' - not clear what this refers to in this context

'RelA-mVenus mouse strain' - it would be good to mention the relevance of the reporter for NFkB signaling

'...A random forest classifier...' -> a random forest classifier

Significance

This study provides mechanistically interpretable insight on the important question of how immune cells perform target recognition in realistic scenarios, and also provides validation of existing mathematical models by extending these beyond their original domain. The paper uses 'signaling codons' as a proxy for information processing, however in this instance it is cross-validated with an LSTM model that is applied directly to the time series data. Nevertheless, the scope of the paper is such that it does not deal with the question of how these signals are transmitted or used in a downstream immune response. To my knowledge, this is the first time that a well established existing mathematical model of signalling response has been extended and applied to heterogeneous ligand mixtures. These results will be of interest to those studying immune cell responses, and to those interested in basic research on mathematical models of signaling and cellular information processing more generally.

My background is in biophysical models, machine learning, and signaling in cancer. I have a basic understanding of immunology, but no experience in experimental cell biology.

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